Molecular Marker–Assisted Selective Breeding of Largemouth Bass

CHAPTER 5

Molecular Marker
Assisted Selective Breeding of Largemouth Bass Contents 5.1 Microsatellite Markers Associated With Growth Traits of Largemouth Bass 5.1.1 Materials and Methods 5.1.2 Results and Analysis 5.2 Correlation Analysis of SNPs Screened in the Largemouth Bass Transcriptome Associated With Growth Traits 5.2.1 Materials and Methods 5.2.2 Results and Analysis 5.3 A 66-bp Deletion in Growth Hormone Releasing Hormone Gene 50 -Flanking Region With Largemouth Bass Recessive Embryonic Lethal 5.3.1 Materials and Methods 5.3.2 Results and Analysis 5.4 Effects of SNPs in the POU1F1 Promoter Region on Growth of Largemouth Bass 5.4.1 Materials and Methods 5.4.2 Results and Analysis 5.5 SNP Screening of the Myostatin Gene in Largemouth Bass and Analysis of Its Correlation With Growth Traits 5.5.1 Materials and Methods 5.5.2 Results and Analysis 5.6 Effect of SNPs in the Promoter Region of the PSSIII Gene on Growth of Largemouth Bass 5.6.1 Materials and Methods 5.6.2 Results and Analysis 5.7 Correlation of Promoter Polymorphism of the IGF-I Gene in Largemouth Bass With Growth Traits 5.7.1 Materials and Methods 5.7.2 Results and Analysis 5.8 Correlation of IGF-II Gene Polymorphism With Growth Traits of Largemouth Bass 5.8.1 Materials and Methods 5.8.2 Results and Analysis

Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass DOI: https://doi.org/10.1016/B978-0-12-816473-0.00005-0 Copyright © 2019 China Science Publishing & Media Ltd. Published by Elsevier Inc.

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5.9 SNPs in the Ghrelin Gene and Associations With Growth Traits in Largemouth Bass 5.9.1 Materials and Methods 5.9.2 Results and Analysis 5.10 SNP Detection of High-Density Lipoprotein Binding Protein Gene and Its Correlations With Growth Traits in Largemouth Bass 5.10.1 Materials and Methods 5.10.2 Results and Analysis 5.11 SNP Detection in PACAP and the Association With Growth Traits in Largemouth Bass 5.11.1 Materials and Methods 5.11.2 Results and Analysis 5.12 Polymorphism of Apolipoprotein Genes and Its Correlation With Growth Traits in Largemouth Bass 5.12.1 Materials and Methods 5.12.2 Results and Analysis 5.13 Pyramiding Analysis of Dominant Genotypes in Different Generation of Youlu No.1 Largemouth Bass 5.13.1 Materials and Methods 5.13.2 Results and Analysis 5.14 Pyramiding With Growth Trait Related-Markers in Largemouth Bass 5.14.1 Materials and Methods 5.14.2 Results and Analysis 5.15 Looking Forward to Molecular-Assisted Selective Breeding of Largemouth Bass References

246 246 248 253 253 255 260 261 263 267 267 268 271 272 273 276 277 280 283 287

5.1 MICROSATELLITE MARKERS ASSOCIATED WITH GROWTH TRAITS OF LARGEMOUTH BASS Two methods can be used to perform correlation analysis on target traits of aquatic animals using molecular markers. One is bulked segregant marker correlation analysis and the other is random selection marker correlation analysis, and both methods have applications in aquatic animal research. Gross and Nilsson (1999) and Kang et al. (2002) studied the relationship between growth hormone (GH) polymorphisms and weight in Atlantic salmon and brown flounder using bulked segregant marker correlation analysis. The experimental group was divided into three groups based on weight, i.e., grouped into small, medium, and largesized individuals, and the question of whether polymorphisms at the GH site affects weight was judged by determining the distributional

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differences in allele and genotype frequency among the three groups. Zhang et al. (2006b) also used this method to screen microsatellite markers related to weight. Through bulked segregant marker correlation analysis researchers can quickly identify molecular markers linked to the target characteristic, but the disadvantage is its low sensitivity and accuracy (Tang, 2003). However, the application of random selection marker correlation analysis is relatively extensive, such as screening markers of cold-resistance and weight in tilapia (Cnaani et al., 2003), identifying markers related to feed conversion rate and enteric septicemia resistance in channel catfish (He et al., 2005), as well as identifying markers associated with lymphocystivirus resistance in the flounder (Fuji et al., 2005). Random selection marker correlation analysis is a method of measuring the screened marker in the selected group and finding markers associated with target traits through analysis of variance. The advantage of this method is that the selected markers can be comprehensively studied with greater accuracy and precision; however, the disadvantages of this method are that a larger amount of DNA is required to perform the analysis and the cost of analysis is higher (Tang, 2003). In this section we screened polymorphic markers with significant distributional differences in the extremely large and extremely small groups using the obtained microsatellite markers, and analyzed the correlation between the markers and the three traits of largemouth bass, i.e., weight, body length, and body height in the random group. We also validated the effectiveness of screened markers in the extreme groups, in order to develop molecular markers associated with growth traits of largemouth bass and lay the foundation for molecular marker
assisted selective breeding of largemouth bass in the next step.

5.1.1 Materials and Methods 5.1.1.1 Experimental Fish Three hundred pairs of parental fish were selected from Jinhui farm in Jiujiang town, Foshan city in Guangdong Province. The following spring, all the selected parental fish were used for artificial breeding and their offspring were cultured in the same breeding pond. At the end of the year, 160 adult largemouth bass in the breeding pond were selected to establish a normal distribution graph for weight (Fig. 5.1). To set up the distribution, 15% of high value individuals, namely those weighing above 750 g, were taken to represent the “extremely large” group; 15% of low value individuals, weighing less than 315 g were taken to represent the

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Figure 5.1 Normal distribution graph for weight.

“extremely small” group, and 12 fish from each of the two groups were used for preliminary screening of growth-related microsatellite markers. In addition, 121 individuals of largemouth bass were randomly selected in the same breeding pond for correlation analysis of growth traits, and these 121 fish were referred to as the “random” group. Growth data of weight, body length, and body height were measured, while blood was obtained in vivo from the caudal vein, acid citrate dextrose (ACD) was added as an anticoagulant and samples were stored at 220˚C for later use. 5.1.1.2 Microsatellite Primers For this experiment, 40 microsatellite loci of largemouth bass were selected (primer information listed in Table 5.1), of which 22 were obtained from microsatellite sequences through the magnetic bead enrichment method by our laboratory (Liang et al., 2008), and the other 18 from microsatellite markers reported in the literature (Lutz-Carrillo et al., 2006). After identification, all the loci in this experimental group were found to have polymorphisms and a good genotyping effect. Primers were synthesized by Sangon Biotech Co. Ltd. (Shanghai, China). 5.1.1.3 Extraction of Genomic DNA Genomic DNA was extracted using a genomic DNA extraction kit (spin column) from TianGen Biotech Co. Ltd. (Beijing, China) according to the manufacturer’s instructions. DNA quality and concentration were detected using 0.8% agarose gel electrophoresis and spectrophotometry. DNA was stored at 220˚C until use.

Table 5.1 Repeated sequence, primer sequence, allele, and annealing temperature of microsatellite Locus

Repeated sequence

JZL31 JZL37 JZL43 JZL48 JZL60 JZL67 JZL68 JZL71 JZL72 JZL83 JZL84 JZL85 JZL105 JZL106 JZL108 JZL111 JZL114 JZL124 JZL126 JZL127 JZL131 JZL132 Lma10 Lma120

(CA)25 (CA)24 (CA)21 (GT)13 (CA)21 (CA)16 (CA)20 (GT)21 (CA)21 (CA)23 (CA)20 (CA)17 (GT)13 (GT)35 (CA)17 (GT)27 (GA)11(GT)17 (CA)28(CT)25 (AC)24 (CA)15 (CA)8 (GT)11 (TG)10(TATGTG) (GT)28

Primer sequence (50
30 )

F:TGGACTGAGGCTACAGCAGA F:TCCAGCCTTCTTGATTCCTC F:GCTGCGAGTGCGTGTAACTA F:TCGACGATCAATGGACTGAA F:AGTTAACCCGCTTTGTGCTG F:CCGCTAATGAGAGGGAGACA F:AGGCACCGTCTTCTCTTCA F:GCAGCTTCAGGTGTGTGTT F:AGGGTTCATGTTCATGGTAG F:TGTGGCAAAGACTGAGTGGA F:GAAAACAGCCTCGGGTGTAA F:GGGGCTCACTCACTGTGTTT F:GTGTCCCTGACTGTATGGC F:GCAGGCAGTGAACCCAGATT F:GTGACAGATGAGCGGAGAA F:TGTCTCAACTCCACCTACG F:CTACAGGTTAGGGAGTTACACG F:GCATTCATACACCATCATTG F:CAGGTAGCAGCGGTTAGGATG F:CAGAGAGATAGTGTCAACCA F:CAAATGCCCGGTCCACAATAAC F:CAAATGCCCGGTCCACAATAAC F:GTCTGTAAGTGTGTTTGCTG F:TGTCCACCCAAACTTAAGCC

R:CCAAGAGAGTCCCAAATGGA R:CCCGTTTAGCCAGAGAAGTG R:GGGAAGCGAGAGTCAGAGTG R:TCTGGACAACACAGGTGAGG R:GAAGGCGAAGAAGGGAGAGT R:ACAGACTAGCGTCAGCAGCA R:CATTGTGGGTGCATTCTCC R:TCGGTGAACTCCTGTCAGG R:ACACAGTGGCAAATGGAGGT R:ATTTCTCAACGTGCCAGGTC R:CACTTGTTGCTGCGTCTGTT R:GTGCGCAGACAGCTAGACAG R:TCTGATGAGGCTGTGAAAT R:TATGTATTGACGAGCGAGCAG R:GATGCTTGAGATACGACTA R:CACCCTGGCTTCATCTGC R:TGCTGAGGACACAACGAGGT R:AGCATTTTGTCAGACCACC R:TCTGAAACACGGACTCACGAC R:ACCACGGAGAAAGCCATT R:GTATTTGAGCCGGATGATAAGTG R:GTATTTGAGCCGGATGATAAGTG R:GAAACCCGAAACTTGTCTAG R:TAAGCCCATTCCCAATTCTCC

Allele

Annealing temperature (°C)

3 2 2 2 3 4 3 2 3 3 3 3 2 3 2 3 2 3 2 3 2 3 3 2

60 56 58 55 60 60 58 60 58 55 55 56 58 54 55 52 55 50 55 52 55 55 55 54 (Continued)

Table 5.1 (Continued) Locus

Repeated sequence

MiSaTPW01 MiSaTPW11 MiSaTPW12 MiSaTPW25 MiSaTPW51 MiSaTPW70 MiSaTPW76 MiSaTPW90 MiSaTPW96 MiSaTPW117 MiSaTPW123 MiSaTPW157 MiSaTPW165 MiSaTPW173 MiSaTPW184 Mdo6

(AC)16 (AGAT)13 (AGAT)21 (AGAT)11 (AGAT)31 (AGAT)43 (AGAT)22(AGAC)10 (ACAT)6 (AGAT)15(AGAC)6 (AC)24 (AC)22 (AC)21 (AC)16 (AC)15 (AC)14(CT)10 (CA)7(TA)4

Primer sequence (50
30 )

F: AGTAAAGGACCACCCTTGTCCA F: CAACATGGACGCTACTAT F: CGGTTGCAAATTAGTCATGGCT F: CCAAGGTCAGGTTTAAC F:CACAGAGACATTGCAGCTGACCCT F: ACTTCGCAAAGGTATAAC F:ACACAGTGTCAGTTCTGCA F:TGCCAGAGATCCTGAGCTAC F:CTTCTAAATGTGTGTAGGGTTGC F:TGTGAAAGGCACAACACAGCCTGC F:GCTAACTTAATCTGCTGGATGGTG F:GACCTCAATGCGGATACTGTGACC F:GTTCGCATCTGAATGCATGTGGTG F:CCACACAGTGACACAAACTGTGC F:TTGTATACCAAGTGACCTGTGG F:TGAAATGTACGCCAGAGCAG

R:GCCTGGTCATTAGGTTTCGGAG R:CAACCATCACATGCTTCT R:CAGGGTGCTCGCTGTCT R:ACCTTTGTGCTGTTCTGTC R:TGACGTATAGTACCAGCTGTGGTT R:CCTCATGCAGAAGATGTAA R: GTGAATACCTCAGCAAGCAT R:CACTTACCTGAATAACCAGAGACA R:AGCTTAGCATAAAGACTGGGAAC R:ATCGACCTGCAGACCAGCAACACT R:TGAACCTTCATAGGACAGCC R:AGGCACTCATCTGAATTGTCCATGT R:TGAAGGTATTAGCCTCAGCCTACA R:GCCATTGTGCTGCTGCAGAG R:GGGAGTGCATCTTTCTGAAGTGCC R:TGTGTGGGTGTTTATGTGGG

Allele

Annealing temperature (°C)

3 2 2 2 2 2 2 2 2 3 2 5 3 4 3 2

56 55 48 55 55 55 48 48 55 55 55 55 55 55 55 55

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5.1.1.4 PCR Reaction Procedure Each polymerase chain reaction (PCR) reaction consisted of 2.0 μL 103 buffer, 0.8 μL MgCL2 (25 mmol/L), 0.3 μL dNTP (10 μmol/L), 0.5 μL each upstream/downstream primer (20 μmol/L), 40 ng genomic DNA, and 1 U Taq enzyme (Shanghai Shenneng Bocai Biotechnology Co., Ltd. Shanghai, China), made up to a total volume of 20 μL with water. PCR procedure consisted of pre-denaturation at 94˚C for 4 min, followed by 25 cycles of denaturation at 94˚C for 30 s, annealing at 48
60˚C for 30 s, and extension at 72˚C for 30 s, then ended with extension at 72˚C for 7 min. The PCR product was separated and detected on an 8% nondenaturing polyacrylamide gel, and stained with silver nitrate. The electrophoretogram was then scanned and recorded. 5.1.1.5 Analysis of Genetic Diversity Band sizes of microsatellites were analyzed by AlphaEase FC (Stand Alone) software. Individual genotype was judged based on the DNA migration distance in the electrophoretogram. Allele number was counted at each microsatellite locus and data were processed using Popgene Version 3.2, and the following parameters were Pn calculated: Number of effective alleles (Ne): E 5 1= i51 Pi2 Average observed heterozygosity (H0): H0 5 number of heterozygotes observed/total number of individuals observed P Average expected heterozygosity (He): He 5 1 2 Pi2 PIC 5 1 2

n X i51

Pi2 2

n21 X n X  2 2 Pi Pj i51 j5i11

Polymorphism information content (PIC) where Pi and Pj in the formula indicate the frequency of alleles i and j in the population, respectively, and n is the allele number. 5.1.1.6 Chi-Square Test and Correlation Analysis of Marker-Traits Statistical analysis of the experimental data was carried out using SPSS version 15.0 software (IBM Corp. Armonk, NY, USA). Preliminary screening of the distribution of 40 microsatellite loci was conducted in the largemouth bass “extremely large” and “extremely small” groups. Least-squares analysis was carried out on the correlation between growth traits and microsatellite loci using general linear models (GLMs), and

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multiple comparisons were conducted for each genotype of the same marker. Least-squares analysis was conducted using the linear model formula, i.e., yij 5 μ 1 ai 1 eij. In this formula yij indicates the observed value of marker i; j indicates some traits of the individual; μ indicates the average of all the observed individuals in the experiment (namely total average); ai is the effective value of marker i; and eij is random error. The occurrence frequency of some genotypes was too low without analysis of statistical significance, therefore in the practical statistical analysis, each genotype could be taken into consideration only if the observed value of the samples was greater than 4.

5.1.2 Results and Analysis 5.1.2.1 Preliminary Screening of Microsatellite Loci Associated With Body Weight, Body Length, and Body Height of Largemouth Bass The result of the chi-square test showed that among all 40 selected microsatellite loci, differences in genotype distribution of 16 microsatellite loci (primers underlined) between the “extremely large” group and the “extremely small” group approached significance (P , 0.1). According to these results, the difference between JZL60, MiSaTPW76, and MiSaTPW117 was highly significant (P , 0.01), the difference between JZL67, JZL72, JZL106, JZL108, JZL124, JZL127, and MiSaTPW173 was significant (P , 0.05), and the difference between JZL37, JZL85, JZL126, JZL131, MiSaTPW70, and MiSaTPW96 approached significance (0.05 , P , 0.1). These 16 microsatellite loci were used for validation analysis of the random group in the next step (Table 5.2). 5.1.2.2 Validation of Microsatellite Loci Associated With Body Weight, Body Length, and Body Height of Largemouth Bass Correlation analysis of microsatellite loci and body weight, length, and height of largemouth bass was conducted using the least-squares method (Table 5.3). Among the 16 microsatellite loci, JZL60, JZL67, JZL72, MiSaTPW76, MiSaTPW117, and MiSaTPW173 had a significant or highly significant (P , 0.05 or P , 0.01) relationship with the above three traits, but JZL124 only had a significant relationship with body length (P , 0.05). Multiple comparisons of loci with significant differences among different genotypes and growth traits (shown in Table 5.4) showed that for marker JZL60, the average of each of the three traits of individuals with genotype AA was significantly or highly significantly

Table 5.2 Chi-square test of microsatellite loci genotype distribution in the “extremely large” and “extremely small” groups Locus

Chi-square value

Pvalue

Locus

Chi-square value

Pvalue

JZL31 JZL37 JZL43 JZL48 JZL60 JZL67 JZL68 JZL71 JZL72 JZL83 JZL84 JZL85 JZL105 JZL106 JZL108 JZL111 JZL114 JZL124 JZL126 JZL127

5.371 5.790 1.955 0.670 14.37 8.578 0.715 1.200 13.13 1.530 2.311 9.262 2.053 8.985 5.042 1.733 6.479 2.129 5.137 9.803

0.121 0.055 0.376 0.413 0.006 0.047 0.699 0.273 0.022 0.675 0.379 0.055 0.289 0.011 0.020 0.545 0.831 0.039 0.055 0.044

JZL131 JZL132 Lma10 Lma120 MiSaTPW01 MiSaTPW11 MiSaTPW12 MiSaTPW25 MiSaTPW51 MiSaTPW70 MiSaTPW76 MiSaTPW90 MiSaTPW96 MiSaTPW117 MiSaTPW123 MiSaTPW157 MiSaTPW165 MiSaTPW173 MiSaTPW184 Mdo6

8.961 1.667 9.133 1.424 0.000 1.067 2.911 0.000 0.689 13.13 18.87 0.345 4.534 13.73 2.441 8.939 5.471 15.08 3.041 3.452

0.089 0.422 0.104 0.404 1.000 0.484 0.233 1.000 0.406 0.069 0.001 0.842 0.100 0.008 0.295 0.347 0.242 0.035 0.219 0.178

Note: Locus underlined indicates P , 0.1.

Table 5.3 Correlation analysis of microsatellite markers and growth traits of largemouth bass Locus

Body weight (g)

Body length (cm)

Body height (cm)

JZL37 JZL60 JZL67 JZL72 JZL85 JZL106 JZL108 JZL126 JZL124 JZL127 MiSaTPW70 MiSaTPW76 MiSaTPW96 MiSaTPW117 MiSaTPW173 Mdo6

0.497 0.048 0.011 0.001 0.540 0.113 0.923 0.780 0.059 0.573 0.161 0.000 0.835 0.086 0.050 0.650

0.450 0.059 0.002 0.012 0.272 0.093 0.726 0.858 0.049 0.448 0.503 0.000 0.631 0.097 0.022 0.254

0.478 0.045 0.002 0.001 0.546 0.081 0.762 0.635 0.089 0.547 0.385 0.000 0.846 0.089 0.032 0.435

Note: Values in the table are the probability values from the correlation analysis of traits (weight, body length, and body height) and microsatellite loci. Superscripts  and  respectively indicate a significant relationship (P , 0.05) and a highly significant relationship (P , 0.01) between trait and marker, and values without a superscript indicate there was no significant relationship between trait and marker (P . 0.05).

Table 5.4 Multiple comparisons of different genotypes of microsatellite loci with weight, body length, and body height Locus Genotype Individual number Body weight (g) Body length (cm)

JZL60

JZL67

JZL72

JZL124

MiSaTPW76

AA AB BB BC AC BB BC AB AC AA AC AA AB BB BC AB AA CC BC BB AC BB CC BC AA AC

9 41 20 30 18 7 9 46 22 34 4 5 41 58 10 27 26 6 32 10 20 10 39 42 10 20

547.9 6 63.49 493.4 6 29.74ab 476.2 6 42.59abd 464.4 6 34.77bcd 361.4 6 44.89c 648.6 6 69.82Aa 532.4 6 61.57ABab 489.3 6 27.23ABb 437.1 6 39.38Bb 422.0 6 31.68Bb 802.5 6 90.03A 482.8 6 80.53B 461.1 6 28.12B 439.6 6 23.64B 428.0 6 56.94B 495.4 6 37.31a 493.0 6 38.02a 475.0 6 79.14a 472.8 6 34.27a 432.5 6 61.30a 401.0 6 43.35a 658.9 6 55.93A 489.5 6 28.32B 485.8 6 27.29BD 366.5 6 55.93BCD 338.6 6 39.54C a

27.80 6 1.03 25.75 6 0.48abd 25.88 6 0.69ab 25.36 6 0.56bcd 23.83 6 0.73c 28.60 6 1.13Aa 26.51 6 0.99ABab 26.02 6 0.44ABb 24.99 6 0.63Bb 24.70 6 0.51Bb 29.73 6 1.51Aa 25.42 6 1.35ABb 25.71 6 0.47ABb 25.06 6 0.39Bb 24.58 6 0.96Bb 26.12 6 0.61a 26.10 6 0.61ac 25.00 6 1.28abc 25.66 6 0.55abc 24.85 6 0.99abc 24.22 6 0.71b 28.64 6 0.91A 25.97 6 0.46B 25.87 6 0.44BD 24.20 6 0.91BCD 23.01 6 0.64C a

Body height (cm)

9.14 6 0.47Aa 8.48 6 0.22ABac 8.37 6 0.31ABabc 8.38 6 0.26ABabc 7.57 6 0.33Bb 9.82 6 0.51Aa 8.77 6 0.44ABab 8.57 6 0.19ABb 8.09 6 0.28Bb 7.98 6 0.23Bb 10.66 6 0.66A 8.23 6 0.59B 8.42 6 0.21B 8.13 6 0.18B 7.86 6 0.42B 8.64 6 0.27a 8.55 6 0.28a 8.24 6 0.58a 8.35 6 0.25a 8.09 6 0.45a 7.85 6 0.32a 9.74 6 0.41Aa 8.54 6 0.21ABb 8.52 6 0.20BDbd 7.70 6 0.41BCDbcd 7.24 6 0.29Cc

MiSaTPW117

MiSaTPW173

BC AB CC BB AC AB CD CC BD DD AC AD BB BC

47 13 23 23 13 6 20 5 25 7 7 6 11 26

521.9 6 27.57Aa 467.5 6 52.42ABab 466.7 6 39.41ABab 425.6 6 39.41ABb 359.9 6 52.42Bb 572.0 6 76.78A 515.2 6 42.06A 510.7 6 84.11A 494.5 6 37.62AC 488.2 6 71.09ABC 439.6 6 71.09ABC 533.8 6 76.78A 451.0 6 56.71ABC 348.7 6 36.88B

26.47 6 0.45a 25.23 6 0.86ab 25.47 6 0.65ab 24.67 6 0.65b 24.32 6 0.86b 27.30 6 1.24Aa 26.41 6 0.68Aa 25.70 6 1.36ABCabc 26.28 6 0.61ACa 26.05 6 1.15ABCa 24.06 6 1.15ABCabc 25.82 6 1.24ABCabc 25.88 6 0.92ABCac 23.41 6 0.59Bb

8.79 6 0.20a 8.26 6 0.39ab 8.25 6 0.29ab 8.04 6 0.29b 7.73 6 0.39b 9.30 6 0.56Aa 8.70 6 0.31Aa 8.52 6 0.62ABCa 8.66 6 0.28ACa 8.44 6 0.52ABCabc 7.81 6 0.52ABCabc 8.62 6 0.56ABCa 8.48 6 0.42ABCac 7.44 6 0.27Bb

Note: For values in the same column, superscripts with the same letter indicate there was no significant difference between two genotypes (P . 0.05), different lower case letters indicate that the difference was significant (P , 0.05), and different upper case letters indicate that the difference was highly significant (P , 0.01).

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higher than that of individuals with genotype BC or AC (P , 0.05 and P , 0.01, respectively); in addition, the average of each trait in individuals possessing allele A was higher than that in individuals possessing allele C; we therefore speculated that allele A had a positive impact on all three growth traits. For marker JZL67, the average of each of the three traits of individuals with genotype BB was significantly or highly significantly higher than that in individuals with genotype AC or AA (P , 0.01); in addition, it could be concluded that allele B had a positive impact on all three traits while allele C had a negative impact. For marker JZL72, the average of each of the three traits of individuals with genotype AC was higher or highly significantly higher than those with other genotypes (P , 0.05, P , 0.01), and we therefore speculated that genotype AC is the dominant genotype. For marker MiSaTPW76, the average of each of the three traits of genotype BB was obviously higher than that of genotype CC, BC, AA, or AC (P , 0.01); we therefore speculated that allele B had a positive effect on all three traits. For marker MiSaTPW117, the average of each trait of individuals with genotype BC was significantly higher than those with genotype BB or AC (P , 0.05), and there was no significant difference among the other genotypes, so we speculated that genotype BC was the dominant genotype. For marker MiSaTPW173, the average of each trait of individuals with genotype BC was highly significantly or significantly lower than in individuals with other genotypes (P , 0.01, P , 0.05), so we speculated that BC was a negative-effect genotype. Linkage analysis of the relationship between markers and traits involves carrying out significance tests on individuals according to their genotypes of marker loci and phenotypes of quantitative traits, where a significant difference indicates a correlation between marker and quantitative trait (Wang and Wu, 2006). The results in this study showed that there were significant correlations between each of JZL60, JZL67, JZL72, MiSaTPW76, MiSaTPW117, and MiSaTPW173 and the three traits of largemouth bass analyzed, i.e., weight, body length, and body height, but that JZL124 only correlated significantly with body length. According to these results, growth traits of individuals with certain genotypes, i.e., AA genotype of microsatellite JZL60, BB genotype of microsatellite JZL67, AC genotype of microsatellite JZL72, BB genotype of microsatellite MiSaTPW76, and BC genotype of microsatellite MiSaTPW117, were highly significantly better than those of individuals with the other genotypes of the same marker, and growth traits could thus be indirectly

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selected through these genotypes. This experiment is the first to identify microsatellite markers associated with growth traits of largemouth bass; work in the next step will involve further analysis of the microsatellite marker results obtained and exploration of whether they could be used as effective molecular markers for marker-assisted selective breeding of largemouth bass. 5.1.2.3 Analysis of Genetic Diversity Within Groups To analyze genetic diversity, 16 microsatellite loci showing significant differences in genotype distribution between the “extremely large” group and the “extremely small” group were used for amplification in random groups (Table 5.5), and 47 alleles were identified. The average allele number was 2.938, the allele number detected at each locus was 2
5, the effective allele number was 1.456
3.535 with an average of 2.142; observed heterozygosity was 0.250
0.783 with an average of 0.515; expected heterozygosity was 0.254
0.720 with an average of 0.500, and polymorphic information was 0.218
0.685 with an average of 0.445. The average allele number (Ne), heterozygosity (Ho, He), and polymorphism information are all good indicators reflecting population diversity, where a greater value indicates a higher population diversity. Table 5.5 Genetic diversity analysis of largemouth bass microsatellite loci Locus

Allele number

Effective allele

Observed heterozygosity

Expected heterozygosity

Polymorphic information

JZL37 JZL60 JZL67 JZL72 JZL85 JZL106 JZL108 JZL124 JZL126 JZL127 JZL131 MiSaTPW70 MiSaTPW76 MiSaTPW96 MiSaTPW117 MiSaTPW173 Mean SD

2 3 3 3 3 3 2 3 2 3 3 5 3 2 3 4 2.938 0.772

1.456 2.767 2.378 1.870 1.816 1.496 1.332 2.908 1.385 2.165 1.986 2.575 2.338 1.753 2.506 3.535 2.142 0.622

0.339 0.736 0.636 0.455 0.430 0.364 0.292 0.653 0.250 0.542 0.583 0.603 0.512 0.458 0.603 0.783 0.515 0.155

0.314 0.641 0.582 0.467 0.451 0.333 0.254 0.659 0.284 0.550 0.507 0.614 0.575 0.439 0.603 0.720 0.500 0.144

0.264 0.575 0.524 0.410 0.442 0.306 0.218 0.606 0.239 0.502 0.373 0.599 0.525 0.337 0.521 0.685 0.445 0.144

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The results of the cultured groups in this experiment were Ne 5 2.938, Ho 5 0.515, He 5 0.5, and PIC 5 0.445 showing a moderate level of genetic diversity, which was higher than the genetic diversity level of the groups of largemouth bass cultured in Guangdong (Liang et al., 2008; Bai et al., 2008). However the microsatellite markers used to test for genetic diversity in this experiment were different from the markers used in the studies by Liang et al. (2008) and Bai et al. (2008). We therefore speculated that the main reason for the difference is that markers we used exhibited moderate or high levels of polymorphism, while the Liang et al. (2008) and Bai et al. (2008)’s studies used randomly-selected markers including microsatellites with low polymorphism.

5.2 CORRELATION ANALYSIS OF SNPS SCREENED IN THE LARGEMOUTH BASS TRANSCRIPTOME ASSOCIATED WITH GROWTH TRAITS Single nucleotide polymorphisms (SNPs) related to feeding habits in the largemouth bass were screened based on transcriptome data obtained by RNA sequencing (RNA-Seq) in order to cultivate largemouth bass breeding varieties that can be reared easily on artificial formula feed. Correlation analysis was performed to detect SNP markers associated with growth traits in a largemouth bass population fed completely with formula feed, and then to provide useful SNP markers for genetic improvement.

5.2.1 Materials and Methods 5.2.1.1 Experimental Fish The experimental fish in the largemouth bass treatment group belonged to the “Youlu No.1” variety and were used for feeding selection. The experimental fish in the control group were nonselected largemouth bass individuals collected at an earlier stage. For each treatment group and control group, 30
50 individuals were prepared for spawning induction and artificial breeding, where offspring from the same egg-laying batch were obtained and cultured for 6 months by Liyang Aquatic Technology Co. Ltd., Yangshan county, Qingyuan city, Guangdong, China. The experimental fish in the control group were cultured using the conventional breeding method, where fresh-frozen mixed fishes purchased from the market were used for feeding throughout the whole process. The experimental fish in the treatment group were fed with artificial feed

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from the fingerling stage at a length of about 3
5 cm, where Quanxing largemouth bass formula feed (Quanxing Aquatic Feed Co. Ltd., Shunde district, Foshan, China) was used throughout the whole process. Fish were selected randomly and several growth traits were measured, i.e., body weight, total length, head length, body height, body width, and caudal peduncle length. Caudal fin samples were cut and preserved in absolute alcohol for later use. 5.2.1.2 Development of SNPs as Molecular Markers From the Transcriptome We selected 12 experimental fish from each of the treatment and control groups. Tissue samples from the liver and muscle were mixed and the total RNA was extracted. A cDNA library was established and sequencing was then performed using an Illumina HiSeq2000 (Guangzhou Gene Denovo Biotechnology Co. Ltd., China). In total, 174 M reads were obtained and 95024 reference sequences (unigene) were obtained after assembly. The reads obtained by sequencing and Unigene were aligned using BWA software (http://bio-bwa.sourceforge.net). The alignment results were further analyzed to detect SNPs and insertions-deletions (indels) using Samtools (http://samtools.sourceforge.net), where the default parameters were employed in all the processes. Low quality data were filtered out where the filtering criteria comprised: alignment quality value MQ $ 20, mutation allele depth $ 3, and the closest distance between SNPs $ 5 bp. The SNP labels and indel labels were then obtained in the largemouth bass. In order to verify the credibility of the SNP labels, 50 high quality SNPs were selected according to the filtering criteria of FDR # 0.001 and |log2 Ratio| $ 1 to design primers. Twenty individuals were selected from the control group for SNaPshot typing verification. In order to perform further correlation analysis of the markers and traits, 327 individuals were sampled randomly from the treatment group and the verified SNPs with different expression levels in the treatment and control groups were used for correlation analysis between the markers and growth traits. Candidate markers that could be used for selective breeding of largemouth bass were then explored. 5.2.1.3 Extraction of Genomic DNA Genomic DNA was extracted using a TIANamp Genomic DNA kit (Tiangen Biotech (Co. Ltd., Beijing) according to the manufacturer’s instructions. The integrity and purity of the DNA were determined by

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0.8% agarose gel electrophoresis, and the concentration was estimated by UV spectrophotometry. Then the DNA was diluted with sterile double distilled water to a concentration of 50 ng/L and preserved at 220˚C for later use. 5.2.1.4 Genetic Parameters of the Largemouth Bass Population The extracted genomic DNA was sent to Shanghai Generay Biotech Co. Ltd. for SNaPshot typing analysis and the typing results were obtained for several SNPs loci. The frequency of each genotype and gene were calculated, and several genetic diversity indexes were obtained with PopGene 32 (Version 1.31) and PIC-Calc0.6, including the Hardy
Weinberg equilibrium (HWE), population heterozygosity (H), PIC, and effective number of alleles (Ne). 5.2.1.5 Correlation Analysis Between SNPs and Traits Normal distribution tests of the growth-related data, i.e., body weight, total length, head length, body width, and caudal peduncle, in the random population were performed using SPSS to assess whether the population was normally distributed. Next, several growth traits in the population were subjected to principal component analysis, as described by Wang and He (1993). According to the principle that the characteristic value, contribution ratio, and eigenvectors should represent the growth traits of the largemouth bass with a cumulative contribution rate .85%, the principal components were extracted that basically covered all of the genetic information for the original growth traits. Multivariate analysis of variance was conducted to determine the correlations between genotypes and quantitative traits using a GLM with SPSS 19.0. The different SNP genotypes were used as fixed factors (F) and growth traits, such as the body weight, total length, body height, and body width, as the dependent variables (D) in order to determine significance differences in quantitative traits among genotypes. We also performed multiple comparisons based on the least-significant difference (LSD) test to analyze the effects of the alleles.

5.2.2 Results and Analysis 5.2.2.1 Development of SNP Molecular Markers in the Transcriptome In total, 174 M reads were obtained using the RNA-Seq technique and 95,024 unigenes were obtained after assembly. The average length of a unigene was 956 bp. We detected 12,139 SNPs and indel loci using BWA

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Unfiltered SNPs

185

Filtered SNPs

4000 3458

3500

2932

Number

3000 2500 2000 1504 1353

1500

872

1000 500

712 424

1283

839 673

428 200

146

1441

347 180

289 120

338 187

359 147

420 199

495 161

A

G C→ T G → A G → C G → T T→ A T→ C T→ G In de l

C→

C→

G

→ T A

A →

A

→ C

0

Figure 5.2 Number and type of SNPs identified from the largemouth bass. SNP, single nucleotide polymorphism.

software and Samtools software, which included 8681 SNPs. After filtering out low quality data according to the criteria of FDR # 0.001 and |log2Ratio| $ 1, we obtained 7368 SNPs and indel loci, which included 4436 SNPs. The nucleotide mutation numbers for the four base types, i.e., A, C, G, and T, ranged from 2108 to 2307, where the most common SNPs were A-G, C-T, G-A, and T-C (Fig. 5.2). 5.2.2.2 Verification of SNPs According to the verification of the credibility of the SNPs, the SNaPshot typing results for 50 loci in 20 samples showed that three loci yielded no PCR amplification products, eight loci had relatively large PCR products, and 39 loci could be typed successfully. Among the 39 loci, four loci were monomorphisms. Thus, 35 SNPs were obtained using the RNASeq technique and the success rate was 70.0%. In a previous study, the success rate for identifying SNPs by high throughput sequencing in Gadus morhua was similar at 74.6% (2291/3072) (Hubert et al., 2010), but it was only 48% in Cyprinus carpio (12/25) in another study (Xu et al., 2012), which might have been related to the quality of the sequencing data and the filtering standards for SNPs. Our statistical analysis of the largemouth bass RNA-Seq data showed that one SNP appeared per 7.48 kb. Previous studies found that one SNP appeared approximately per 6.6 kb in C. carpio (Xu et al., 2014), while one SNP appeared per 1.0 kb in humans (Frazer et al., 2007; Wang et al., 2008c; Rieder et al., 1999). The differences in

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the SNP distribution densities between different species are related to the amount of data accumulated, and the depth and accuracy of sequencing. According to the present study, it is feasible to identify a large number of SNPs markers using a database based on the largemouth bass transcriptome. 5.2.2.3 Statistical Analysis of the Growth Traits in the Random Largemouth Bass Population We randomly sampled 323 individuals from the largemouth bass population fed completely on formula feed and measured several growth traits, i.e., body weight, total length, body width, body height, head length, and caudal length (Table 5.6). The normal distributions of the parameters in the population were confirmed using SPSS software. The growth traits of 327 individuals in the largemouth bass random population were subjected to dimensionality reduction using SPSS and the results showed that the body weight, total length, and head length could explain 72.64%, 14.15%, and 10.31% of the total population variance, respectively, whereas the total variance explained by the body width, body height, and caudal peduncle length was less than 2%. Thus, the body weight, total length, and head length were treated as the principal components for the largemouth bass, where the cumulative contribution rate for the three components reached 97.10% (Table 5.7). The body weight was correlated with the total length, body width, and body height with r2 values of 0.887, 0.943, and 0.957, respectively (Table 5.8). The preference for artificial feed is determined by the appetite of largemouth bass, but it is also necessary to consider its digestion and metabolism. In this study, the evaluation standard was quantified in a simple manner where we used the growth of largemouth bass after feeding as a measurement index. After extracting principal components from several growth-related traits of largemouth bass, the results showed that the body weight was the main principal component and it explained 72.64% of the total variation. The correlation matrix for the growth traits showed that three morphological traits, i.e., total length, body height, and body width, had relatively high correlations with body weight, i.e., 0.887, 0.903, and 0.957, respectively. Principal component analysis of the morphological traits showed that the phenotypic correlations between body weight
body length and body weight
body height in largemouth bass at 6 months of age were 0.945 and 0.948, respectively (P , 0.01) (Li et al., 2011). In a previous study, the body weight
body length and body

Table 5.6 Statistics of body weight, total length, head length, body width, body height, and caudal peduncle length of the random group of largemouth bass Character Body weight Total length Head length Body width Body height Caudal peduncle length (g) (cm) (cm) (cm) (cm) (cm)

Mean

428.36 6 8.19

28.37 6 0.16

7.34 6 0.08

4.11 6 0.03

Table 5.7 Principal components analysis on growth trait of largemouth bass Component Initial value of components

Body weight Total length Head length Body width Body height Caudal peduncle length

8.62 6 0.06

8.49 6 0.07

Sum of squares of extracted components

Total

Explained variance ratio (%)

Accumulation variance ratio (%)

Total

Variance contribution ratio (%)

Accumulated variance contribution ratio (%)

4.36 0.85 0.62 0.11 0.04 0.03

72.64 14.15 10.31 1.77 0.64 0.49

72.64 86.79 97.10 98.87 99.51 100

4.36 0.85 0.62

72.64 14.15 10.31

72.64 86.79 97.1

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Table 5.8 Correlation matrix on some growth traits of largemouth bass Body Total Head Body Body Caudal weight length length width height peduncle length

Body weight Total length Head length Body width Body height Caudal peduncle length

1 0.887 0.428 0.943 0.957 0.511

1 0.45 0.835 0.908 0.759

1 0.41 0.442 0.178

1 0.912 0.481

1 0.511

1

weight
body height correlations were also extremely high for Siniperca chuatsi (r . 0.9, P , 0.01) (Yu et al., 2012), which is consistent with our results. Thus, body weight can be used as the main evaluation indicator when assessing the growth traits of largemouth bass. There are high correlations between the morphological traits and body weight, so indirect selection can be achieved for the other growth traits when selecting based on body weight during breeding. 5.2.2.4 SNP Genotyping and Correlations With Growth Traits Thirty extremely large individuals and 30 extremely small individuals were sampled from the 327 individuals to obtain a bulked segregant analysis population and to determined whether the 35 SNPs were correlated with their growth traits. We found that SNPs belonging to the C-T type at locus 297 in unigene0022436, G-C type at locus 1322, G-A type at locus 2257, and G-A type at locus 2308 in unigene0031044 were significantly correlated with growth traits. However, three SNPs in unigene0031044 were highly associated, and locus 1322 in unigene0031044 and locus 297 in unigene0022436 were selected to verify in the random population. The SNP genotype and gene frequencies are shown in Table 5.9. Chi-squared analysis showed that the genotype frequencies of two SNPs with CC, CT, and TT (or GG, GC, and CC) were consistent with the HWE (P . 0.05). The diversity of these loci was high in the largemouth bass population, where the heterozygosity was 0.4557
0.4587 and PIC ranged from 0.4900 to 0.5631.

Table 5.9 Genotype and allele frequencies of two SNPs of largemouth bass Unigene number Position Genotype frequency Gene frequency Hardy
Weinberg equilibrium

Unigene0022436

297

Unigene0031044

1332

Mean

CC：0.33 CT：0.46 TT：0.21 GG：0.45 CG：0.46 CC：0.09

PIC

Ne

H

C：0.56 T：0.44

χ 5 1.976 (P 5 0.160)

0.5631

2.7584

0.4557

G：0.68 C：0.32

χ2 5 0.674 (P 5 0.412)

0.4900

2.3880

0.4587

0.5266

2.5732

0.4572

2

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The heterogeneity reflects the degree of genetic consistency and PIC is an indicator of polymorphism. The degree of genetic consistency is lower and the genetic variation of the population is greater when the heterozygosity of the population is higher. When PIC is greater, the proportion of heterozygotes is greater at a locus and more abundant genetic information can be provided. The average population heterozygosity for the two loci was 0.4572 and the average PIC was 0.5266 with high polymorphism (PIC . 0.5) (Botstein et al., 1980). This indicated that the largemouth bass population used for breeding had a certain level of genetic heterozygosity, rich genetic diversity, and the potential for further breeding to improve the population uniformity and production performance, thereby providing the foundation for breeding largemouth bass. The number of effective alleles (Ne) can be used to measure the genetic diversity of a population. If the alleles are distributed more evenly in the population, Ne is closer to the absolute number of alleles that are actually detected. The average Ne in the two loci was 2.5732 and the number of actual genotypes was three, which suggesting that these samples could reflect the overall population traits. In general, it is very important to consider all the genetic information for a population when analyzing economic traits (Jin et al., 2012) or statistical analysis of the results might have large errors and deviations. The SNPs and genotypes with significant correlations are shown in Table 5.10. The results showed that in unigene0022436, the mean body weight, body width, and body height of the CT genotype was significantly higher than that of the TT genotype (P , 0.05). The mean values of the six growth traits were higher in the CC genotype than the TT genotype, but the difference was not significant (P . 0.05). In unigene0031044, the mean values of all the traits were significantly higher in the GG genotype than the CC genotype, i.e., body weight, total length, head length, body width, body height, and caudal peduncle length (P , 0.05). The mean values of each of the six growth traits were higher in the CG genotype than the CC genotype, but the difference was not significant (P . 0.05). Thus, the CT genotype in unigene0022436 and the GG genotype in unigene0031044 were the dominant genotypes. Body weight was one of the principal components among several growth traits in this population, where it explained 72.64% of the variance. There were significant differences between the two genotypes and the other genotypes in terms of body weight.

Table 5.10 Correlation analysis between SNPs polymorphism and growth traits Mean of Mean of Unigene number Genotype Number Mean of head total body length length weight (g) (cm) (cm)

Unigene0022436

Unigene0031044

CC CT TT GG CG CC

108 149 70 146 150 31

427.77ab 442.64a 400.08b 448.83a 417.88ab 382.66b

28.28 28.61 28.02 28.73a 28.20ab 27.47b

7.48 7.33 7.15 7.88a 7.29a 7.28b

Note: Values with different superscript letters within a column indicate significant difference at P , 0.05.

Mean of body width (cm)

Mean of body height (cm)

Mean of caudal peduncle length (cm)

4.08ab 4.17a 4.02b 4.17a 4.07ab 3.95b

8.48ab 8.62a 8.26b 8.69a 8.40b 8.02b

8.53 8.72 8.55 8.71a 8.60ab 8.29b

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5.2.2.5 Analysis of Unigene Sequence Corresponding to SNPs The cDNA sequences of unigene0022436 and unigene0031044 were analyzed by BLASTn via the NCBI website, where the results showed that the unigene0022436 sequence with a length of 981 bp shared 93% similarity with the homeobox protein zampogna-like (zax) messenger RNA (mRNA) of Larimichthys crocea (XM_010745675.1). In addition, the total length of unigene0031044 was 2601 bp, where a sequence comprising 1218 bp shared over 84% similarity with estradiol 17beta-dehydrogenase 12-B-like mRNA in a dozen species, including L. crocea, Pundamilia nyererei, and Oreochromis niloticus (XR_797202.1; XM_005749621.1; XM_003450799. 2). The zax belongs to homolog Nkx3.2 in the NK family and it is associated with the development of visceral muscle. In the fruit fly, zax is important for midgut muscle tissue formation (Rainbow et al., 2014). In Xenopus, this gene is associated with formation of the midgut muscular layer, inner cortex of the pharynx, and hypoglycemia (Craig and Paul, 1999). Mutations in this gene are closely related to human spondylo-megaepiphyseal-metaphyseal dysplasia (Simon et al., 2012). 17β-HSD is an oxidoreductase that acts on donor CH
OH groups, where NAD or NADP is the receptor, and it is involved in the processing of estrogen and estrogen metabolism (Jerzy and Franz, 2001). Fourteen different types of 17β-HSD enzymes have been found, and their substrate prosthetic groups, tissue distributions, and the directions of the enzyme reaction are different (Luu-The, 2001; Moeller and Adamski, 2009). In vivo and in vitro experiments have shown that 17β-HSD-12B is also related to the extension of essential long-chain fatty acids as well as the biosynthesis of estradiol (Rantakari et al., 2010). According to the Open Reading Frame (ORF) Finder (http://www. ncbi.nlm.nih.gov/projects/gorf/) accessed via the NCBI website, the T-C type SNP at locus 297 in unigene0022436 belonged to a synonymous mutation and it encoded arginine/R. In unigene0031044, the G-C type SNP at locus 1322 in the 50 -untranslated region did not encode a protein. The G-A type SNP at locus 2257 and the G-A type SNP at locus 2308 belonged to synonymous mutations, which encoded asparagine/N and leucine/L, respectively. Genotypic variations in the two SNPs detected in this study did not cause changes in the translation of the protein sequence. The growth traits of individuals with CT and CC genotypes for unigene0022436 marker were better than TT, and The growth traits of individuals with genotypes GG and CG for unigene0031044 marker were superior to CC, thus the CT genotype in the former and the GG

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genotype in the latter were the dominant genotypes. However, according to the functional analysis, the SNPs in the two unigenes would not change the translated amino acids. However, some studies have suggested that synonymous mutations in SNPs may affect the shearing of mRNA, thereby affecting the functioning of a protein (Li and Zhou, 2007). The zax with the highest similarity to unigene0022436 is associated with the development of muscle tissue, and the 17β-HSD-12B gene with the highest similarity to unigene0031044 is associated with the extension of essential long-chain fatty acids, where these functional genes have direct or indirect effects on feeding and growth traits. The functions of these two genes and the mechanisms that might allow them to regulate growth traits still need to be studied, but both SNPs could be used as molecular markers related to feeding and growth in largemouth bass based on the correlation analysis, and they may be employed in the molecular-assisted breeding of largemouth bass.

5.3 A 66-BP DELETION IN GROWTH HORMONE RELEASING HORMONE GENE 50 -FLANKING REGION WITH LARGEMOUTH BASS RECESSIVE EMBRYONIC LETHAL Growth hormone releasing hormone (GHRH), a member of pituitary adenylate cyclase activating polypeptide 1 (PACAP1)/glucagon superfamily, is mainly expressed and released from the neurosecretory cells in the arcuate nuclei of the hypothalamus in rat (Sherwood et al., 2000; Merchenthaler et al., 1984; Sawchenko et al., 1985). It plays an important role to stimulate the synthesis and release of GH from the anterior pituitary by acting on GHRH receptors expressed on the somatotroph cell surface (Bloch et al., 1983; Melmed and Kleinberg, 2008). The accurate regulation of GH spatiotemporal expression is necessary for the growth and development of organisms. Isolated GH deficiency (IGHD) causes dwarfism, and GH hypersecretion causes acromegaly or gigantism in human beings (Mayo et al., 2000; Baumann, 1999; Desai et al., 2005). Mutations of the GHRH itself are candidates for inherited IGHD, because the majority of children with IGHD grow when treated with GHRH therapy (Thorner et al., 1988). However, despite extensive searches, mutations in the GHRH gene related to IGHD have not been identified, and this gene has been excluded by linkage analysis and direct gene analysis (Pe´rez Jurado et al., 1994; Franc¸a et al., 2011). On the other hand, nonpituitary GHRH has a wide spectrum of activity, exemplified by its ability to

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modulate cell proliferation, especially in malignant tissues, to regulate differentiation of some cell types, and to promote healing of skin wounds (Kiaris et al., 2011). In human, single nucleotide variants in GHRH gene were associated with bone mineral content and bone mineral density at the proximal femur and lumbar spine in the Hertfordshire cohort study (Dennison et al., 2009). Despite the functional importance of GHRH in the regulation of GH, in domestic animals only two studies of relationship between GHRH polymorphism and growth traits have been published. In Landrace pigs, GHRH AluI restriction fragment length polymorphism was associated with yield traits, such as the average daily gain and expected progeny difference for fat thickness (Franco et al., 2005). A SNPs (24241A .T) in Korean cattle GHRH showed significant associations with carcass traits of meat including cold carcass weight and longissimus muscle area (Cheong et al., 2006). A 66-bp deletion (c.-923_-858del) was discovered in GHRH 50 -flanking region of largemouth bass (Micropterus salmoides). Genotype frequency of the site in the random culture largemouth bass population was analyzed, only one DD individual was detected in two populations. The effects of genotype (ID) on growth traits and GHRH mRNA expression were investigated. In addition, the relationship between genotypes and survival rates was calculated in early embryos.

5.3.1 Materials and Methods 5.3.1.1 Experimental Animals Largemouth bass (M. salmoides) were collected from the aquaculture farms in Nanhai district, Foshan city, Guangdong Province in China (Population A, n 5 170, mean body mass 348.8 g; Population B, n 5 150, mean body mass 378.5 g). After anesthesia with MS222, growth traits of each fish including body weight, length, and height were measured, and blood was collected from caudal veins for DNA extraction. A largemouth bass family was constructed with two heterozygous individuals as parents (ID 3 ID). The filial generation fish were used to detect genotype frequency and GHRH expression levels. 5.3.1.2 Full-Length cDNA Cloning of GHRH The specific primers were designed (GHRH-5RACE-R1: 50 GATGTCATCAGGATGGACGTATC-30 and GHRH-5RACE-R2: 50 CGAACCTAATGGATGGGTAGAG-30 ) for the 50 -untranslated region (UTR) of largemouth bass GHRH, according to the known ORF and

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30 -UTR sequence (Han et al., 2011). The 50 -UTR was amplified from the SMARTer cDNA library of forebrain tissue, and the cDNA library was constructed by using a SMARTer PCR cDNA Synthesis Kit (Clontech, Mountain View, CA, USA). Nested PCR was carried out for amplifying the 50 -end of GHRH cDNA. PCR products were cloned into pMD18-T (TaKaRa, Dalian, China), and sequenced and analyzed using an ABI-3730 autosequencer (Foster, California, USA). 5.3.1.3 Isolation of GHRH 50 -Flanking Sequence and Sequence Analysis Blood DNAs were extracted using the Blood and Cell Culture DNA Kit (Tiangen, Beijing, China). GHRH 50 -flanking region was isolated from genomic DNA by using of genome walking strategy with the GenomeWalker Universal Kit (Clontech, Mountain View, CA, USA). According to the manufacturer’s instructions, nested PCR was performed using two specific primers (GHRH-5GW-R1: 50 -GCTTTCTCCATCCTCACAGCTAGTCGT-30 and GHRH-5GW-R2: 50 -TGCCCTTCACTCTCATCTCTCATCCTC-30 ) and two adaptor primers (AP1 and AP2). PCR products were cloned and sequenced. Sequence assembly was performed using the Vector NTI suite 8.0 program (Invitrogen, Carlsbad, California, USA). The transcriptional elements analysis of the 50 -flanking region was conducted with the Transcription Element Search System (http://www.cbil.upenn.edu/cgibin/tess/tess) in order to predict the cis-acting elements of the promoter. 5.3.1.4 Genotyping Deletion Sites in Random Population and in the Filial Generation of ID 3 ID Family A 66-bp indel site was found in the GHRH 50 -flanking region. In order to analyze the indel site genotype frequency in the random population (n 5 170), PCR was performed with a pair of primers GHRH-SF and GHRH-SR2 (50 -AACACAAGAGCACATTGCTTCCTC-30 ). The products were assessed by electrophoresis on 1.5% agarose gel with ethidium bromide staining. It was designated that (1) represented 66-bp insertion with the longer PCR products (308 bp), and (2) represented deletion with the shorter PCR products (242 bp). A family was constructed with two heterozygous individuals (1/ 2 ) as parents. Genotype frequency was analyzed in the filial generation embryos at early neurula stage (n 5 48) and hatching stage (n 5 48). DNA was extracted from each largemouth bass embryo, using the alkaline lysis

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method. Briefly, each single embryo was lysed in 180 μL lysis buffer (50 mM NaOH) by vortexing, and incubated at 95˚C for 10 min. After mixed with 20 μL 1 M Tris
HCl (pH 8.0) and centrifuged for 10 min at 12,000 rpm, the supernatant of 1 μL embryo solution was used as template to perform PCR in 25 μL final volume. The PCR primers and PCR product analysis were described as above. 5.3.1.5 GHRH mRNA Expression Level Assay Total RNAs from the forebrain tissues of largemouth bass (n 5 20, mean body length 10 cm) in the 1 / 2 3 1 / 2 family were isolated. Realtime PCR was performed on the ABI 7300 quantitative PCR instrument with the GHRH specific primers (50 -CCGCTCTACCCATCCATTA-30 and 50 -GCTCTCACTTTCATCTCCCAG-30 ). The 18 S rRNA was used as an internal control with the primer pair (18S-F: 50 -GGACA CGGAAAGGATTGACAG-30 and 18S-R: 50 -CGGAGTCTCGTT CGTTATCGG-30 ). PCR amplification cycles were as follows: 95˚C for 2 min; 45cycles for 95˚C for 15 s, 56˚C for 30 s, 72˚C for 30 s. Finally, the dissociation curve of amplified products was detected within the range from 65 to 95˚C. Data were analyzed using the 22WWCt method (Livak and Schmittgen, 2001). 5.3.1.6 Statistical Analysis Genotype frequency and Hardy
Weinberg equilibrium were tested using PopGene 32 Version 1.32 software (Yeh et al., 2000). The genotype of the corresponding fish was detected, and the GLM in SPSS 15.0 software (SPSS Inc., Chicago, IL, USA) was used to analyze the correlation between genotypes and largemouth bass main growth traits and the correlation between genotypes and GHRH gene expression levels. Differences among means of genotypes were calculated using Duncan’s multiplerange test and P values ,0.05 were considered statistically significant.

5.3.2 Results and Analysis 5.3.2.1 GHRH Gene Sequence The largemouth bass GHRH cDNA was 734 bp in total length (GenBank accession, HQ640678), containing 426 bp of the ORF encoding 141 amino acids, 146 bp 50 -UTR and 162 bp 30 -UTR (Fig. 5.3). The 50 -flanking sequence (1083 bp) and the 30 -flanking (837 bp) of the GHRH gene was obtained by use of the largemouth bass GenomeWalker library. The genomic DNA sequence of the largemouth bass GHRH

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Figure 5.3 The partial 50 -flanking sequence and exon 1 sequence of largemouth bass GHRH gene (GenBank accession, HQ640680). The proposed transcriptional start site is designated as 11. The 66-bp deletion fragment in the 50 -flanking sequence is shown in the box. Predicted binding sites of HOXD8, NR3C1, SRF, and PSAP in the deletion fragment are overstriking or underlined. The TATA-box is shown with underlines. Exon 1 is indicated by capital letters, and 50 -flanking region is indicated by lower case letters. GHRH, Growth hormone releasing hormone.

gene identified in the current study contains 4167 bp and is composed of six exons and five introns (GenBank accession, HQ640680). 5.3.2.2 Deletion Site Sequence Analysis A 66-bp deletion (c.-923_-858del) site was detected in the GHRH 50 -flanking region. Sequence analysis of the 66 bp fragment showed several potential binding sites for transcriptional elements, including one site each for homeobox D8 (HOXD8), glucocorticoid receptor (NR3C1), serum response factor (SRF), and prosaposin (PSAP) (Fig. 5.3). 5.3.2.3 Genotype Frequency in the Random Culture Population The genotypes and allele frequencies of c.-923_-858del site were analyzed in two random culture populations (A: n 5 170 and B: n 5 150) (Table 5.11). It was interesting that only an alive 2/2 genotype adult individual was detected. The HWE analysis showed that the site in the random populations were in disequilibrium (P , 0.05, chi-square test). It suggested that the deletion allele was a potential recessive lethal site. 5.3.2.4 Effects of 1 / 2 Genotype on Growth Traits and GHRH mRNA Expression Table 5.12 shows the results of correlation analysis between the genotypes and the growth traits. No significant difference was detected in body

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Table 5.11 Genotype frequencies and allelic frequencies of the GHRH 50 -flanking 66bp deletion site in two largemouth bass random populations (population A: n 5 170 and population B: n 5 150) Population

A (n 5 170)

B (n 5 150)

Genotype

Genotype/ Allele frequency (%) Genotype/ Allele frequency (%)

Allelic type

1/ 1

1/ 2

2/ 2

1

2

71.2 (121/ 170)

28.8 (49/ 170)

0 (0/170)

85.6 (291/ 340)

14.4 (49/ 340)

73.3 (110/ 150)

26.0 (39/ 150)

0.7 (1/ 150)

86.3 (259/ 300)

13.7 (41/ 300)

Table 5.12 Association between genotypes and growth traits in the largemouth bass random culture population B with 170 individuals Genotype

Body weight (g)

Body length (cm)

Body depth (cm)

Head length (cm)

1/ 1 1/ 2

350.13 6 94.62 345.38 6 86.21

23.70 6 2.70 23.68 6 2.16

7.60 6 1.05 7.65 6 0.79

6.96 6 1.19 6.89 6 1.06

weight, body length, body depth, and head length between 1 / 1 and 1 / 2 individuals. The effects of the genotypes on the GHRH mRNA expression in forebrain were analyzed using the fluorescence quantitative PCR method. The difference between the two genotypes was not significant (P . 0.05). It suggested that the - allele is not reducing GHRH mRNA abundance. 5.3.2.5 Genotype Frequency in the Filial Generation From Heterozygous Parents In order to confirm the death of 2 / 2 fish in development, we crossed a 1 / 2 female with a 1 / 2 male, and progeny were genotyped at neurula stage and hatching stage. The genotype frequency analysis results indicates that only two of 48 embryos with the 2 / 2 fish surviving at the neurula stage, and the genotype ratio of 1 / 1 : 1 / 2 : 2 / 2 was 1:1.6:0.1. At the hatching stage, 2 / 2 individuals were not detected, and the genotype ratio of 1 / 1 : 1 / 2 : 2 / 2 was 1:2:0 (Table 5.13). Assuming Mendelian segregation, the results suggest that the homozygous 2 / 2 fish die during early embryonic development.

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Table 5.13 The genotype and allele frequency in filial generation individuals from a family of heterozygous parents (1/ 2 3 1 / 2 ) during earlier embryonic development Development stage

Total number

Number of 1/1 genotype individuals

Number of 1/2 genotype individuals

Number of 2/2 genotype individuals

Ratio 1/1:1/2:2/2

Early neurula stage Hatching stage

48

18

28

2

1:1.6:0.1

48

16

32

0

1:2:0

Previously, several fish GHRH-like peptide and PACAP were hypothesized to be processed from the same transcribed gene (Parker et al., 1993; Jiang, et al., 2003). But the GHRH-like peptides were not able to demonstrate robust GH-releasing activities (Montero et al., 1998; Parker et al., 1997). Recently, the GHRH genes that stimulate GH release in teleosts were reported and analyzed from goldfish (Carassius auratus), zebrafish (Danio rerio), olive flounder (Paralichthys olivaceus), medaka (Oryzias latipes), and half-smooth tongue sole (Cynoglossus semilaevis) (Nam et al., 2011; Lee et al., 2007; Suehiro et al., 2008; Ma et al., 2011). In the present study, a 734 bp largemouth bass GHRH cDNA was cloned and 4167 bp genomic DNA sequence was identified including six exons and five introns, as well as 1083 bp 50 -flanking sequence and 837 bp 30 -flanking. In the 50 -flanking region of largemouth bass GHRH gene, a 66-bp indel polymorphic site was found. Among the two random populations (n 5 170 and n 5 150), only one 2 / 2 individual was detected. This suggests the site was in part associated with the recessive lethal phenotype caused by homozygosity for deletion alleles. To analyze the cause of death, the cis-acting transcriptional elements in the 66-bp indel sequence of largemouth bass GHRH 50 -flanking region was analyzed. The Homeobox protein is known to be a critical regulatory factor for GHRH gene expression in animals. Mutation or knockout of the Gsh-1 gene, which is one member of the Homeobox family, resulted in the lack of GHRH gene expression and led to dwarfism in mice and mouse (Li et al., 1996; Valerius et al., 1995). Although there are some reports about the transcriptional elements influencing GHRH gene expression (Ghigo et al., 1997; Romero et al., 2010), there is no adequate evidence to explain that the deletion of the cis-acting transcriptional elements in largemouth bass GHRH 50 -flanking leads to fish death.

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The progeny analysis from the family with heterozygous (1/ 2 ) parents indicated that the 2 / 2 individuals died off at the early developmental stages. The phenotype of the largemouth bass is different from the one observed in the mice with targeted disruption (knockout) of the GHRH gene (GHRHKO). Heterozygeous founder (1/ 2 ) mice were mated, and the homozygous (2/ 2 ) offsprings were obtained. The expected Mendelian ratio was conserved, showing no lethality in the GHRHKO embryos (Alba and Salvatori, 2004). On the other hand, heterozygous largemouth bass (1/ 2 ) had normal growth and GHRH mRNA levels. In GHRHKO mice, the growth traits and mRNA expression levels of GHRH, GH, and insulin-like growth factor (IGF) genes of 1 / 2 individuals were not statistically significantly different from 1 / 1 individuals, but they were significantly higher than those of 2 / 2 individuals. The data suggested that the 66-bp deletion in 50 -flanking sequence has an essential role for the production of GHRH needed for normal development. Although the cause of death was not determined, it is possible that the 66-bp deletion is a recessive site causing early embryonic developmental. Besides regulating the release of GH, GHRH peptide also plays a significant role in cell proliferation and differentiation as well as pituitary formation during the embryonic period (Mayo et al., 1985; Mayo et al., 2000; Billestrup et al., 1986). GHRH and its agonists have been shown to contribute to the recovery of heart tissue after myocardial infarction and can promote the survival and proliferation of pancreatic islets after transplantation into diabetic animals (Barabutis and Schally, 2010; Kanashiro-Takeuchi et al., 2010; Ludwig et al., 2010). Disruption of endogenous GHRH action in MDA231 cells results in both decreased cellular proliferation and increased apoptosis (Zeitler and Siriwardana, 2002). In this study, it is speculated that the 66 bp deletion stops the essential function of the production of GHRH gene, and affects the normal cellular proliferation, differentiation, and apoptosis for viability in early embryos of largemouth bass. Lethal genes will tend to be deleted from the gene pool. A late-acting lethal will be more stable in the gene pool than an early-acting lethal (Dawkins, 1976). One 2 / 2 adult fish was detected in the random population (n 5 150), which suggested that there were other factors carrying compensatory function for survival, so the recessive lethal allele could be conserved in the largemouth bass natural population with relative high genotype frequency.

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5.4 EFFECTS OF SNPS IN THE POU1F1 PROMOTER REGION ON GROWTH OF LARGEMOUTH BASS Pituitary-specific transcription factor 1 (POU1F1) is a POU family member and is expressed by the prepituitary gland in mammals. POU1F1 plays a decisive role in the positive regulation of GH, prolactin (PRL) and thyroid-stimulating hormone (TSH)-β. Mutation of the POU1F1 gene can hinder the normal expression of GH, PRL, and TSH-β, and cause abnormal pituitary development and short stature (Stasio et al., 2002). To date there have been no relevant studies on the effect of this gene mutation on aquatic animals. In this section, we used the POU1F1 gene in largemouth bass as a candidate gene associated with growth, cloned the promoter sequence of the POU1F1 gene, and detected SNPs using the direct sequencing method, to explore the relationship between SNPs in the POU1F1 promoter and growth traits of largemouth bass and thus to identify candidate markers for molecular-assisted selective breeding in the next step.

5.4.1 Materials and Methods 5.4.1.1 Experimental Fish, Reagents, and Strains A population of 126 fish from the same pond culture and same batch of fry were randomly selected and collected from Jinhui farm in Jiujiang town, Foshan city in Guangdong Province. Trizol reagent was purchased from Invitrogen (Carlsbad, CA, USA); pGEM-T Easy vector was bought from Promega (Madison, WI, USA); Blood and Cell Culture DNA Kit and GenomeWalker Universal Kit were purchased from Clontech Laboratories Inc. (Mountain View, CA, USA); RNase Free DNase I was purchased from Promega; ReverTra Ace-α Kit was purchased from Toyobo (Osaka, Japan); Power SYBR Green Master Mix was purchased from Applied Biosystems (Foster City, CA, USA); restriction enzymes DraI, PvuII, SspI, EcoRV, ScaI, StuI, AluI, and BsrBI were purchased from Fermentas (Thermo Fisher Scientific, Waltham, MA, USA); marker pBR322DNA/Msp I was purchased from Tiangen and Escherichia coli DH5α cells were stored by our laboratory. 5.4.1.2 DNA Extraction and Construction of a Genomic DNA Library Body weight, body length, total length, body height, and body width of each largemouth bass individual used in the experiment were measured, while blood was drawn in vivo from the caudal vein and anticoagulant

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(ACD) was added to the blood samples at a volume ratio of 6:1. DNA was extracted from fish blood according to the instructions of the Blood and Cell Culture DNA Kit. A genomic DNA library of largemouth bass was constructed using the restriction enzymes DraI, PvuII, SspI, EcoRV, ScaI, and StuI according to the instructions provided with the Genome Walker Universal Kit. 5.4.1.3 Amplification and Sequencing of the POU1F1 Promoter Sequence Primers P1 and P2 were designed based on the known POU1F1 cDNA sequence of largemouth bass (Table 5.14). PCR amplification was carried out using primers AP1 and P1 provided in the GenomeWalker Universal Kit according to the manufacturer’s instructions. Six genomic libraries were used as templates. PCR reactions were performed in a total volume of 20 μL containing 2.0 μL 10 3 buffer, 0.8 μL MgCL2 (25 mmol/L), 0.4 μL dNTP (10 μmol/L), 0.4 μL each upstream/ downstream primer (20 μmol/L), 40 ng genomic DNA, and 1 U Taq enzyme (Shanghai Shenneng Bocai Biotechnology Co., Ltd.). The PCR procedure consisted of pre-denaturation at 94˚C for 4 min, followed by 32 cycles of denaturation at 94˚C for 30 s, annealing at 46
56˚C for 30 s and extension at 72˚C for 30 s, then ended with extension at 72˚C for 10 min. The PCR product was diluted 100-fold and then used as the template for nested-PCR amplification using AP2 and P2, following the same procedure. Specific fragments were detected in the EcoRV library. After purification, ligation, and transformation of the amplification product, positive clones were sequenced by Shanghai Invitrogen Biotechnology Co., Ltd. 5.4.1.4 Analysis of the Transcription Element in the POU1F1 Promoter Sequence Transcription Element Search System software (http://www.cbil.upenn. edu/cgi-bin/tess/tess) was used to analyze the transcription element in the 50 flanking region. All parameter settings used default values, all ratios of similarity of the core sequence matrix and similarity of sequence matrix were larger than 0.8. 5.4.1.5 Screening of Mutation Sites Ten largemouth bass individuals were randomly chosen from experimental samples, and genomic DNA was extracted. The flanking sequence of

Table 5.14 Primers and sequences Primer Primer sequence 50 -30

P1 P2 AP1 AP2

50 -ATGAGGATTGGCAAGGGTGAGTCT-30 50 -TGGGGTGAAAGAGTCGGCACTGAACG-30 50 -GTAATACGACTCACTATAGGGC-30 50 -ACTATAGGGCACGCGTGGT-30

Primer

Primer sequence 50 -30

P3 P4 P5 P6

50 -GCAGAGCCCAAGACAAACAC-30 50 -ATGAGGATTGGCAAGGGTGAGTCT-30 50 -GATAAAGTAAGACTAAACACAAGC-30 50 -CATTCTTCTCAGGCCCCGCT-30

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1473 bp in POU1F1 was amplified using primers P3 and P4. After purification, the amplification product was sequenced by Shanghai Invitrogen Biotechnology Co., Ltd. Vector NTI Suite 11.0 was used to compare and analyze the sequencing result and to find SNP sites. 5.4.1.6 Genotype Detection in Different Individuals A partial sequence of the promoter was amplified using primers P3 and P4. Then using the PCR product as the template, a fragment of 210 bp between two SNP sites was amplified using primer P5 and P6. The amplification product was digested using the restriction enzymes AluI (site 2183) and BsrBI (site 218). Individuals carrying mutations were detected by separating the products on an 8% polyacrylamide gel. 5.4.1.7 Correlation Analysis of SNP Mutation and Haplotype Growth Analysis of allele frequency was conducted using Popgene software (Version 3.2). The presence of any correlations between SNPs and growth traits of largemouth bass was analyzed based on the least-squares method using the GEM in SPSS 17.0. Statistical analysis used the equation Yij 5 u1 Bi 1 eij, wherein Yij indicates the observed value of marker i; j indicates the characteristic of an individual; u is the average of all the individuals observed in the experiment (namely the overall average); Bi is the effective value of marker i; and eij is the random error effect corresponding to the observed value.

5.4.2 Results and Analysis 5.4.2.1 Cloning of the 50 Flanking Sequence and Prediction of Transcription Factor Action Site in the POU1F1 Gene in Largemouth Bass Six genomic enzyme digestion
ligation libraries (DraI, PvuII, SspI, EcoRV, StuI, and ScaI) of largemouth bass were used as the templates (Li et al., 2008), and the genomic walking method was employed. A 50 flanking sequence of 1629 bp and a 50 -UTR of 620 bp were obtained. The predicted transcription element in the promoter region is shown in Fig. 5.4, including the basic promoter transcription elements, such as a TATA box, CCAAT box, GATA box, and four octamer transcriptional factor 1 (Oct-1) binding sites, as well as one Homeobox transcription factor binding site and two binding sites for cAMP response element binding protein (CREB). CREB binds to two CREB binding sites in the POU1F1 promoter to initiate transcription of the POU1F1 gene. There

Figure 5.4 The promoter sequence of the POU1F1 gene in largemouth bass. POU1F1, pituitary-specific transcription factor 1. Note: The TATA box, CCAAT box, GATA box, and Oct-1 binding site are all indicated using boxes; CREB, hepatocyte nuclear factor (HNF), and zinc finger protein (ZNFP) are shown underlined. Mutated bases are indicated in bold, and binding sites for the transcription factors ecotropic viral integration site-1 (EVI 1) and heat shock factor (HSF) at the mutated sites are marked using parentheses. The start codon was set as “ 1 1”.

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are two cAMP response element sequences, CGTCA, in the promoters of the human POU1F1 and GH (Cohen et al., 1999). Two CREB binding sites are also present in the promoter of the salmon POU1F1 gene and GH gene, as well as in the GH gene promoter of rainbow trout (Wong et al., 1996). 5.4.2.2 Screening Results of Mutation Sites Comparison analysis was carried out on the POU1F1 promoter sequence of 10 individuals, and two SNPs were found at the position 2183 and 218 of its promoter. The two mutations were detected in the population of 126 individuals, and the results showed that the two SNPs were extensively present in the population. In addition, only two haplotypes, i.e., A and B (C-A was A, T-G was B) were detected at the two mutation sites (Fig. 5.5). The method used to determine the haplotype was as follows: two bands of 210 and 187 bp were identified after digestion at position 2183 using the restriction enzyme Alu I, and were named as a1 and b1; two bands of 210 and 192 bp were found after digestion at site 218 using the restriction enzyme BsrB I, and named as a2 and b2; if allele a1 was detected at site 2183, allele a2 would be detected at site 218, and if allele b1 was detected at site 2183, allele b2 would be detected at site 218, and vice versa. Therefore, allele a appearing at both sites was defined as haplotype A, and allele b detected at both sites was defined as haplotype B. The allele gene frequency and genotype of the two haplotypes are shown in Table 5.15. The band at marker 217 is the fragment of 210 bp which could not be digested by restriction enzymes, and the band at marker 190 bp is the fragment which was digested by restriction enzymes.

Figure 5.5 SNP restriction digestion electrophoretogram of site 2183 in the POU1F1 promoter. SNP, single nucleotide polymorphism; POU1F1, pituitary-specific transcription factor 1.

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Table 5.15 Gene frequency distribution of SNP mutations in the POU1F1 promoter region in a random population of largemouth bass Genotype Genotype frequency (sample size)(%) Allele frequency (%)

AA

8.7 (11)

A

B

AB BB

31.7 (40) 59.5 (75)

24.6

75.4

Table 5.16 Results of multiple comparisons of growth traits among individuals with different genotypes Characteristic Genotype

Body weight (g) Body length (cm) Total length (cm) Body height (cm) Body width (cm)

AA

AB

BB

P value

561.77 6 54.98a 27.04 6 0.91a 30.64 6 0.98a 8.96 6 0.40a 4.79 6 0.21a

542.71 6 28.83a 26.91 6 0.48a 30.66 6 0.52a 9.06 6 0.21a 4.70 6 0.11a

411.82 6 21.05b 24.48 6 0.35b 27.93 6 0.38b 7.92 6 0.15b 4.16 6 0.08b

0.000 0.000 0.000 0.000 0.000

Note: The 5% significance test was used, and significant differences are indicated by superscript letters a, b.

5.4.2.3 Correlation Analysis of Different Haplotypes and Growth Traits For correlation analysis, we selected 126 individuals weighing approximately 500 g, from the same breeding batch, cultured in the same pond, and collected at the same time, therefore differences in time, environment, and artificial feeding conditions did not need to be considered when establishing the model. The results of multiple comparison of growth traits among individuals of different genotypes are shown in Table 5.16. The results of correlation analysis showed that haplotypes composed of the two SNPs had a significant effect on weight, body length, total length, body height, and body width (P , 0.05). Growth traits of individuals with genotypes AA and AB were obviously superior to those of individuals with genotype BB. Two SNP sites were screened in the promoter of the largemouth bass POU1F1 gene in this study, and were found at position 2183 and 218. The SNP at site 2183 is the binding site of EVI-1 transforming protein. The base sequence of the binding site of the EVI-1 transforming protein is AGAT, which is altered to AGAC after mutation, thus a mutation at site 2183 would cause the disappearance of the EVI-1 transforming

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protein binding site. The EVI-1 transforming protein can inhibit signal transduction of the growth factors transforming growth factor-β (TGF-β) and bone morphogenetic protein (BMP). BMP, a secretory multifunctional protein, belongs to the TGF-β superfamily and has effects on regulation of cell proliferation and differentiation as well as promoting generation of bone and cartilage (Zhu and Lin, 2008). An A/G mutation at position 218 also abolishes the binding site of HSF. HSF is the main regulator of heat shock proteins, many of which are constitutively expressed and participate in important physiological activities under normal physiological conditions, such as protein transport and folding, causing irreversible damage and even cell death (Lindquist and Craig, 1988). The disappearance of the binding sites for EVI-1 and HSF caused by mutations at site 2183 and 218 may promote the activity or transcriptional efficiency of the promoter, and we speculated that these mutations may be the main reason why the growth traits of individuals with genotypes AA and AB are superior to those of individuals with genotype BB. There are two binding sites for the POU1F1 protein in the promoter of the GH gene in humans and mice, and both are essential in the activation process of the GH gene promoter. Two domains within the POU1F1 protein sequence, i.e., the POU1F1 unique domain and the domain shared by the whole POU family, determine its ability to bind to the promoter of the GH gene (Nelson et al., 1988). In addition, one potential binding site (TGAATATGAA) has also been found in the 50 UTR of the PRL gene in the Magang goose (Liu, 2006). A comparison was conducted between the POU1F1 gene promoter sequence in largemouth bass and the cDNA sequence of the POU1F1 gene in the black porgy (EU279458), based on speculation that its transcriptional initiation site started at A and is located at 2620 bp. Two SNPs were identified in the 50 -UTR region of the POU1F1 gene in largemouth bass, located at positions 2183 and 218, indicating that both SNPs are located in the 50 -UTR of the POU1F1 gene in largemouth bass. We speculated that SNPs identified in this study probably affect the expression level of POU1F1 mRNA and cause differences in the expression of POU1F1 protein in different organisms, thereby affecting the promoter activity of the GH and PRL genes, and resulting in different expression levels and the emergence of different growth traits so that individuals with genotypes AA and AB are superior to individuals with genotype BB. The allelic loci of adjacent SNPs in the genome tend to be passed on to offspring as a package, and this group of allelic loci of linked SNPs was

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called a haplotype. The study of a single SNP is time-consuming with low statistical efficiency, and a single SNP may have no relationship with disease or with phenotypic traits, while a group of several SNPs, namely a haplotype, could show a good correlation with physical traits. The reason for this may be that a haplotype is one row of alleles at multiple SNP loci located on the same chromosome and containing linkage disequilibrium information. Besides, correlation analysis based on haplotypes is equivalent to finding and locating genes using multiple SNPs, and the correlation between each SNP site could also be taken into consideration. As the result using the haplotype is more accurate than can be obtained using a single SNP, then the test effectiveness would also increase. Studies showed that correlation analysis based on haplotype was more effective than that based on a single SNP (Schaid, 2004). In this study we carried out genotyping on two SNP loci at positions 218 and 2183 of the POU1F1 promoter sequence in largemouth bass, and detected two haplotypes of A and B. Body weight, body length, total length, body height, and body width of individuals with genotypes AA or AB were all significantly greater than in individuals with BB (P , 0.05), indicating that multiple mutations within haplotypes could interact to form a better allele which significantly affects phenotypic traits. To summarize, using the direct sequencing method, we found that two SNP sites in the POU1F1 gene promoter of largemouth bass constituted only two haplotypes of A and B, wherein haplotype A was the dominant haplotype and could be used as the candidate molecular marker in the selection of excellent parental fish.

5.5 SNP SCREENING OF THE MYOSTATIN GENE IN LARGEMOUTH BASS AND ANALYSIS OF ITS CORRELATION WITH GROWTH TRAITS Myostatin (MSTN) is a member of the TGF-β superfamily. MSTN is a secreted polypeptide that binds to a receptor dimer on the membrane. The signal generated, mediated by three Smad proteins, is transmitted into the cell nucleus where it inhibits the transcriptional activity of MyoD family members and negatively regulates growth and development of muscle (Joulia et al., 2003). To date, in studies of aquatic animals, the MSTN gene has been cloned in D. rerio (Amli et al., 2003; Biga et al., 2005), Oncorhynchus mykiss (Rescan et al., 2001), Salmo salar (Ostbye et al., 2001), Sparus aurata (Maccatrozzo et al., 2001),

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Oreochromis mossambicus (Rodgers et al., 2001), Ictalurus punctatus (Kocabas et al., 2000), Umbrina cirrosa (Maccatrozzo et al., 2002), and M. salmoides (Li et al., 2007), and some relevant studies have been conducted on the expression of MSTN in various tissues in some fish. MSTN is expressed not only in skeletal muscle, but also in many other tissues in fish, such as liver, stomach, heart, gill, muscle, eye, brain, ovary, and spermary. The candidate gene approach is one of the commonly used methods of identifying a gene with linkage to quantitative traits at the DNA level. Since Grobet et al. (1997) and Mcpherron et al. (1997) found that the phenomenon of the double-muscled phenotype is caused by natural deficiency and variation in MSTN in Belgian Blue cattle and Piedmontese cattle, respectively, many researchers have selected the MSTN gene as a candidate gene in the horse, pig, chicken, sheep, and other livestock and carried out SNP studies on it. The results showed that mutation of MSTN is related to muscle production (Li et al., 2002; Gu et al., 2002; Zhu et al., 2007; Zhang et al., 2007). In this study, we used the MSTN gene as a candidate gene of largemouth bass growth traits to find genetic polymorphic loci in the entire MSTN gene, and to lay a basis for finding molecular markers of largemouth bass growth traits, and conducting marker-assisted selective breeding work.

5.5.1 Materials and Methods 5.5.1.1 Experimental Materials All 24 largemouth bass individuals used in SNP locus screening and 127 individuals (10 months of age) used in correlation analysis of growth traits were collected from Jinhui farm in Jiujiang town, Foshan city in Guangdong Province. The Taq DNA polymerase system was purchased from Shanghai Shenneng Bocai Biotechnology Co., Ltd. (Shanghai, China); the PMD18T vector system was purchased from Takara Biotechnology Co., Ltd. (Dalian, China), the E.Z.N.A Gel Extraction Kit was purchased from Omega Bio-tek (Norcross, GA, USA); the DNA extraction kit was purchased from Beijing Tianwei Shidai Technology Company Limited (Beijing, China); acrylamide, N,N-methylene-bis-acrylamide and glycerol were purchased from Guangzhou Weijia Technology Company Limited (Guangzhou City, China). E. coli DH5α cells were stored at our laboratory.

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5.5.1.2 Primer Synthesis Ten primers were designed based on the MSTN gene sequence of largemouth bass in Genbank (Genbank accession number: EF071854) to amplify the MSTN gene and perform relevant restriction digestion. Primer sequence, product length, and primer usage are shown in Table 5.17. 5.5.1.3 Extraction of Genomic DNA From Largemouth Bass Blood was drawn in vivo from the caudal vein and ACD anticoagulant was added. Genomic DNA was extracted using a genomic DNA extraction kit (spin column) from TianGen Biotech Co., Ltd. (Beijing, China) according to the manufacturer’s instructions. After dissolving in 100 μL distilled sterilized water, DNA quality and concentration were analyzed using 0.8% agarose gel electrophoresis. After detection, 20 μL genomic DNA was kept at 4˚C for use, while the remaining genomic DNA was stored at 220˚C for later use. 5.5.1.4 SSCP Analysis An aliquot of 5 μL PCR product was mixed with 9 μL loading buffer (95% formamide, 10 mmol/L EDTA, 0.09% xylene cyanole, 0.09% bromophenol blue, pH 8.0), denatured at 100˚C for 10 min, quickly cooled on ice for 5 min, detected by 12% nondenaturing polyacrylamide gel electrophoresis at 4˚C for 16
22 h, and stained with silver. 5.5.1.5 Cloning and Sequencing After reclaiming the fragment by low melting point agarose gel electrophoresis, the target fragment was incorporated into the pMD-T vector. Positive transformants were screened for subsequent sequencing, which was conducted by Shanghai Invitrogen Biotechnology Co., Ltd. 5.5.1.6 Reaction System and Detection The search for restriction sites at the mutation site was conducted using network restriction software (http://helix.wustl.edu/dcaps/dcaps.html) based on comparison of the target sequence to be amplified in the MSTN gene of largemouth bass and the sequencing result. The restriction enzymes TaqI and AluI identified mutation sites at 21453 and 133, respectively. Digestion was performed on the PCR product of the amplified target fragment according to the digestion reaction system and the reaction conditions of TaqI and AluI. Digested products were analyzed by 10% nondenaturing polyacrylamide gel electrophoresis.

Table 5.17 Primer information of the MSTN gene in largemouth bass Primer Base composition (50
30 ) Product length (bp)

P1 P2 P3 P4 P5 P6 P7 P8 P9 P10

F: CAAAGGAATAGTCTGCCTCATATC R: TTGTCATCTCCCAGCACGTCGTA F: GCCTATCAGTGTGGGACATTAA R: GTTTCTATTGGGCTGGTGGCGG F: AGCCCAATAGAAACGGAGCAGT R: TCATCTCCCAGCACGTCGTACT F: CCTCGACCAGTACGACGTGC R: GCGTAATAACGGTCTGAGCG F: TGTACACTTCAATCGCGCATG R: TGCGTATGTGCCTGTTCCCGT F: ATACGCATCCGCTCCCTGAAG R: ACCATAAGGGTTCAGTTTAGTGTA F: TATTCACACACACTCTGTCATT R: ACTCCCCGGAGCAATAGTTG F: GCCAACTATTGCTCCGGGGA R: CCGTCCCAACTCAAGAGCATC F: TGCTCTTGAGTTGGGACGG R: CTGGAGGAAAGAAAAGTAAGAGC F: CAAAGGAATAGTCTGCCTCATATC R: GGCAGGCGAAAGAAATGAGTA

Note: F, forward primer; R, reverse primer.

Most appropriate annealing temperature TM (°C)

Usage

1842

57.4

Initiation of amplification

220

57.0

AluI digestion

206

58.0

Screening SNPs loci

177

58.0

Screening SNPs loci

252

58.0

Screening SNPs loci

230

58.0

Screening SNPs loci

216

50.0

Screening SNPs loci

223

57.0

Screening SNPs loci

229

56.0

Screening SNPs loci

207

57.4

TaqI digestion

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213

5.5.1.7 Statistical Analysis As samples of largemouth bass were all collected from the same farm, and collection was carried out at consistent times with no differences in year and season, the herd
year
season effect was not taken into consideration when establishing models. The statistical model was: Yij 5 u 1 Bi 1 eij where Yij is the phenotypic value; u is the population average; Bi is the influence value of the genotype; and eij is the random residual effect corresponding to the observed value. The effects of each genotype on production performance were analyzed based on the fixed effect model using the GLM in SPSS 15.0 software.

5.5.2 Results and Analysis 5.5.2.1 PCR-SSCP Result PCR amplification of the MSTN gene was conducted according to the conditions of each primer, as shown in Table 5.17. The amplified fragment size was consistent with anticipated size and the amplification effect was good with no nonspecific bands. After SSCP analysis of these fragments, SNPs were found in the DNA sequence of the promoter and in exon 1, but no polymorphisms were found in exons 2 or 3. Different individuals found to have the polymorphism were selected and their PCR products were purified and incorporated into the PMD-T vector, and then positive transformants were screened for bidirectional sequencing. Homologous comparison was conducted on the sequence obtained, and the result showed the presence of a C-T mutation at site 21453 in the promoter and a T-C mutation at site 133 in exon 1, but the amino acid encoded was unchanged and was still Ser. The result is shown in Fig. 5.6. 5.5.2.2 Restriction Digestion Result Restriction digestion of the amplification product of the mutation site at 21453 in the MSTN gene of largemouth bass was carried out using the restriction enzyme TagI, and the results showed three genotypes controlled by two codominant genes, A and B, and which were named as: AA (78, 333 bp), AB (78, 333, 412 bp), and BB (412 bp). Restriction digestion of the amplification product of exon 1 at 133 in the MSTN gene of largemouth bass was carried out using the restriction enzyme AluI, and the

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Figure 5.6 Homologous comparison of MSTN gene sequences: (A) Mutation site at 21453 in the MSTN gene promoter; (B) Mutation site at 133 in exon 1. MSTN, Myostatin. Table 5.18 Genotypes at mutation sites in the MSTN gene of largemouth bass and their genetic frequency Locus Sample size Genetic frequency (number) Allele frequency

2C1453T T 1 33C

127 125

AA

AB

BB

A

B

0.24(31) 0.41(51)

0.51(64) 0.39(49)

0.25(32) 0.2(25)

0.496 0.604

0.504 0.396

results showed three genotypes controlled by two codominant genes, A and B, named as: AA (220 bp), AB (83, 137, 220 bp), and BB (83, 137 bp). 5.5.2.3 Genotypes and Their Genetic Frequency Distribution Statistical analysis of the three genotypes expressed at sites 21453 and 133 in the MSTN gene, as well as their allele frequency in largemouth bass samples are shown in Table 5.18. The genotype at site 21453 in the MSTN gene of largemouth bass was most frequently AB, while the genetic frequency of A and B was equivalent; genotypes at site 133 in exon 1 of the MSTN gene in largemouth bass were mostly AA and AB, and the genetic frequency of A was 0.604, indicating that in largemouth bass allele A was the dominant gene. 5.5.2.4 Correlation Analysis Between Polymorphisms of the MSTN Gene and Growth Traits of Largemouth Bass GLM analysis was conducted on the different genotypes screened at two SNP sites and their correlation with the five main growth traits of largemouth bass, i.e., body weight, body length, body height, body width, and interorbital distance. The results showed that the correlation of different genotypes at two SNP sites with the five traits was not significant (P . 0.05) (shown in Table 5.19). The different genotypes at two mutation sites were

Table 5.19 Correlation analysis of different genotypes of SNPs in the MSTN gene and growth traits of largemouth bass SNP locus Genotype Body weight Body length Body height Body width Interorbital distance (g) (cm) (cm) (cm) (cm)

2 C1453T T 1 33C

AA AB BB AA AB BB

497.27 6 34.90 474.91 6 24.87 441.42 6 35.46 467.65 6 27.93 483.97 6 28.22 457.29 6 40.33

SNP, single nucleotide polymorphism.

26.00 6 0.57 25.52 6 0.41 24.91 6 0.58 25.70 6 0.46 25.40 6 0.46 25.47 6 0.66

8.53 6 0.26 8.39 6 0.18 8.24 6 0.26 8.36 6 0.20 8.45 6 0.21 8.33 6 0.29

4.50 6 0.14 4.41 6 0.10 4.31 6 0.14 4.40 6 0.11 4.43 6 0.11 4.35 6 0.16

2.22 6 0.06 2.17 6 0.04 2.13 6 0.06 2.19 6 0.04 2.15 6 0.02 2.16 6 0.06

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combined into six diplotypes (combinations with a frequency of less than 3% were deleted) and correlation analysis showed that the averages of all the five traits of diplotype D2 were higher than those of the other diplotypes; the averages of all the five traits of diplotype D5 were lower than those of the other diplotypes; and there were significant differences in all the five growth traits between diplotype D2 and D5 (P , 0.05) (Table 5.20). The MSTN gene is involved in regulation of the total amount of animal skeletal muscle, and its loss of function causes hypertrophy of skeletal muscle. Mutation in this gene can cause animal skeletal muscle to be extensively distributed with excellent meat quality traits, consequently MSTN is the ideal gene to improve the quantity and quality of livestock meat production (Meng et al., 2008). Study of the regulatory elements in the MSTN gene promoter of largemouth bass revealed the presence of two TATA-boxes and nine E-boxes, of which the E6-box was the important regulatory factor controlling MSTN gene expression in the largemouth bass (Li et al., 2008). For functional studies of the coding region of the MSTN gene, Wang et al. (2005) considered that the functional region of the MSTN gene expression product was mainly composed of 109 amino acids. The nucleotides encoding this sequence of amino acids is mainly concentrated in exon 3, wherein nine cysteines play an important role in the function of the E-box containing conserved amino acids. Conventional PCR-SSCP was used in this study to screen SNPs in the MSTN gene of largemouth bass, and two SNP sites were found: 2 C1453T located in the region between the E8-box in the promoter and the Octamer (1) regulatory element, and T 1 33C in exon 1 synonymous mutation; correlation analysis of the different genotypes of SNPs and growth traits of largemouth bass showed no significant correlation (P . 0.05), indicating that the two mutation sites in the gene did not directly affect its transcription and function, which was consistent with the location and function of the mutation site. As a method of correlation analysis and linkage disequilibrium analysis, the use of the haplotype analysis method has successfully solved several problems associated with the use of single marker analysis, such as obscure locus information, low efficiency of detection and statistics (Stephens et al., 2001). As interactions exist among different SNPs, diplotypes consisting of two haplotypes can provide more accurate genotypic frequency information than single SNPs. In this study, we carried out correlation analysis between different diplotypes in the MSTN gene and growth traits of largemouth bass, and the results showed: the average of each trait of

Table 5.20 Correlation analysis of different diplotypes in the MSTN gene and growth traits of largemouth bass Diplotypes SNP locus Frequency Body weight Body length Body height (%) (g) (cm) (cm) 2 C1453T 1 T33C

D1 D2 D3 D4 D5 D6

AA AA AB AB BB BB

AA AB AA AB AB BB

24.39 3.25 16.26 31.70 4.88 19.51

482.65 6 35.43abc 716.50 6 37.21a 445.15 6 43.39abc 495.55 6 30.31ac 327.33 6 39.22b 457.29 6 39.61abc

25.73 6 0.58ab 30.12 6 1.24a 25.66 6 0.71ab 25.60 6 0.49ab 22.49 6 1.29c 25.47 6 0.65bd

8.40 6 0.26b 10.64 6 1.00a 8.30 6 0.32b 8.49 6 0.22b 7.47 6 0.58b 8.33 6 0.29b

Note: Different letters in the same column indicate a significant difference (P , 0.05). SNP, single nucleotide polymorphism.

Body width (cm)

Interorbital distance (cm)

4.43 6 0.14ab 5.50 6 0.53a 4.36 6 0.17b 4.46 6 0.12ab 3.90 6 0.31b 4.35 6 0.15b

2.21 6 0.06ac 2.40 6 0.02a 2.17 6 0.07a 2.18 6 0.05ac 1.90 6 0.13b 2.16 6 0.06a

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body weight, body length, body height, body width, and interorbital distance of diplotype D2 was greater than the other diplotypes; the average of each trait of diplotype D5 was lower than the other diplotypes; and there was a significant difference in each of the five growth trait between diplotypes D2 and D5 (P , 0.05). We speculated that diplotype D2 correlates positively with growth traits, and could be used as the first choice in molecular marker
assisted selective breeding; while diplotype D5 showed a negative correlation with all of the growth traits of largemouth bass. From the viewpoint of breeding, individuals with dominant genotypes should be chosen and those with unfavorable genotypes should be eliminated to speed up the selective breeding process. Growth traits are quantitative traits which are controlled by multiple genes. Where major genes exist, they may be isolated or integrated in different generations. Therefore, for the two diplotypes, D2 and D5, at mutation sites in MSTN associated with growth traits of largemouth bass in this study, it is necessary to prove not only their reproducibility in different populations, but also their correlation among different generations, to further ensure the accuracy and applicability of results in this study. In addition, as one of the target traits in fish selective breeding, body weight has different degrees of correlation with morphological traits. He et al. (2009) studied the effect of nine morphological traits of largemouth bass on body weight, and found that body width, body length, and interorbital distance are the main morphological traits which directly or indirectly affect the weight of largemouth bass. Therefore, in this study we chose several growth traits, i.e., weight, body width, body length, interorbital distance, and body height, as morphological traits for correlation analysis, which had good reference value and significance for largemouth bass selective breeding and evaluation of breeding parameters.

5.6 EFFECT OF SNPS IN THE PROMOTER REGION OF THE PSSIII GENE ON GROWTH OF LARGEMOUTH BASS Somatostatin (SS), also known as GH-inhibiting hormone, functions to inhibit an organism’s secretion of GH and is an important neurotransmitter. SS family members, including SS, SS-28, SS-14, and SS-13, are mainly distributed in the central and peripheral nervous system, intestine, stomach, pancreas, thyroid, and other tissues from cyclostomes to mammals (Vanetti et al., 1993). The earliest report of fish SS was the identification of SS peptide in monkfish and channel catfish, and later their

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cDNAs were cloned (Hobart et al., 1980). At present, cDNA fragments of the gene encoding the precursor of somatostatin (PSS) in many species of fish have been cloned; however, to date there are no studies concerning SS polymorphism in fish. In this study, we used the preprosomatostatin (PSSIII) gene in largemouth bass as a candidate gene relating to growth, cloned the promoter sequence of the PSSIII gene, and identified a SNP in the gene using the direct sequencing method to analyze the relationship between SNPs in the PSSIII promoter and growth trait of largemouth bass and to provide candidate markers for molecular marker
assisted selective breeding in the next step.

5.6.1 Materials and Methods 5.6.1.1 Experimental Fish, Reagents, and Strains One experimental fish used for cloning and 293 experimental fish used for growth correlation analysis were collected from the breeding farm of Jinhui farm in Jiujiang town, Foshan city in Guangdong Province. Trizol reagent was purchased from Invitrogen; pGEM-T Easy vector was bought from Promega; Blood and Cell Culture DNA Kit and GenomeWalker Universal Kit were purchased from Clontech; RNase Free DNase I was purchased from Promega; ReverTra Ace-α Kit was purchased from Toyobo; restriction enzymes DraI, PvuII, SspI, EcoRV, ScaI, StuI, AluI, and BsrBI were purchased from Fermentas company; agarose, silver nitrate, sodium hydroxide, ammonium persulfate, TEMED, acrylamide, and N,N0 -methylene-bisacrylamide were purchased from Guangzhou Weijia Biotechnology Co., Ltd.; marker pBR322DNA/MspI was purchased from Tiangen and E. coli DH5α cells were stored by our laboratory. 5.6.1.2 DNA Extraction and Construction of a Genomic DNA Library Body weight, body length, total length, body height, and body width of each largemouth bass individual used in the experiment were measured, while blood was drawn in vivo from the caudal vein and anticoagulant (ACD) was added to the blood at a volume ratio of 6:1. DNA was extracted from fish blood according to the instructions provided with the Blood and Cell Culture DNA Kit. A genomic DNA library of largemouth bass was constructed using the restriction enzymes DraI, PvuII, SspI, EcoRV, ScaI, and StuI according to the instructions for the GenomeWalker Universal Kit.

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5.6.1.3 Amplification and Sequencing of the PSSIII Promoter Sequence Primers P1 and P2 (Table 5.21) were designed based on the obtained cDNA sequence of largemouth bass PSSIII. PCR amplification was carried out using primers AP1 and P1 provided in the kit according to the instructions provided with the GenomeWalker Universal Kit. Six genomic libraries were used as templates. PCR was carried out in a reaction volume of 20 μL, consisting of 2.0 μL 10 3 buffer, 0.8 μL MgCL2 (25 mmol/L), 0.4 μL dNTP (10 μmol/L), 0.4 μL each upstream/downstream primer (20 μmol/L), 40 ng genomic DNA, and 1 U Taq enzyme (Shanghai Shenneng Bocai Biotechnology Co., Ltd.). The first PCR procedure was carried out as follows: two-step cycling method, 94˚C, 3 min, 1 cycle; 94˚C, 30 s; 72˚C, 3 min, 7 cycles; 94˚C, 30 s; 65˚C, 3 min, 27 cycles; 67˚C, 5 min. The PCR product from the first amplification was diluted 100-fold and then used as the template for the second PCR amplification. The second PCR procedure was: two-step cyclic method, 94˚C, 3 min, 1 cycle; 94˚C, 30 s; 70˚C, 3 min, 5 cycles; 94˚C, 30 s; 68˚ C, 3 min, 27 cycles; 67˚C, 5 min. The product from the second amplification was analyzed using 1% agarose gel electrophoresis and the specific fragment was detected in the PvuII library. After purification, ligation, and transformation of the amplification product, positive clones were sequenced by Shanghai Invitrogen Biotechnology Co., Ltd. The cDNA sequence of largemouth bass PSSIII obtained above was used to design primers P3 and P4 (Table 5.21). A specific fragment was obtained based on the above procedure using the GenomeWalker method in the StuI library, and was cloned and sequenced. Finally, a relatively complete promoter sequence of largemouth bass PSSIII was obtained. 5.6.1.4 Analysis of Transcription Elements in the PSSIII Promoter Sequence Analysis of transcription elements in the 50 flanking region was carried out to predict cis-acting elements in the promoter using Transcription Element Search System software (http://www.cbil.upenn.edu/cgi-bin/tess/tess). All parameter settings used default values, all ratios of similarity of core sequence matrix and similarity of sequence matrix were larger than 0.8. 5.6.1.5 Screening of Mutation Sites Ten largemouth bass individuals were randomly chosen, and genomic DNA was extracted. Primers P5 and P6 were designed in the upstream

Table 5.21 Primers and sequences Primer Primer sequence 50 -30

P1 P2 P3 P4 P5 P6

50 -CTACAGTTCATGTGGAGATGGGAGCG-30 50 -AGCGAAGGAGTACGATAAGCAGGCAGAGC-30 50 -ACCTCTTCAAGCAGGCGGGTGGAC-30 50 -GTGGACATTTTCCACATCTCATCAACTGTG-30 50 -TAGTGCTGAATGTTCCCTGC-30 50 -GCTGTTTGGATTCAACTATGC-30

Primer

Primer sequence 50 -30

P7 P8 P9 P10 AP1 AP2

50 -TGAATGTGCACTGGTAGCTAG-30 50 -CTGAACAGAAGCCCCATGAG-30 50 -GCAGCTACAGCCTATACTATACC-30 50 -AGGTGACGGACCAGAGACTAC-30 50 -GTAATACGACTCACTATAGGGC-30 50 -ACTATAGGGCACGCGTGGT-30

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and downstream regions of the obtained promoter sequence of largemouth bass PSSIII promoter, to amplify the upstream sequence of the promoter, and two pairs of upstream/downstream primers P7, P8, P9, and P10 were designed to amplify the downstream sequence of the promoter using two-step PCR (primer sequences are shown in Table 5.21). After purification, the amplification product was sequenced by Shanghai Invitrogen Biotechnology Co., Ltd. Vector NTI Suite 11.0 was used to compare and analyze the sequencing result and to identify SNP sites. 5.6.1.6 Genotype Detection Primers were designed based on the 5 SNP loci identified in the promoter region of the largemouth bass PSSIII gene. After PCR amplification, the product was digested and detected by polyacrylamide gel electrophoresis. Digested primer sequences of different loci and corresponding restriction enzymes are shown in Table 5.21. Specific procedures were designed as follows: (1) PCR amplification was conducted using upstream/downstream primer III-F1 and III-R1 with product of 471 bp. Mutations at 2870 and 2448 sites were detected using the restriction enzymes TaqI and SspI, respectively. The product was digested using SspI; if it could be digested at site 2448, this would result in fragments of 451 and 20 bp. The band that could not be digested was named as allele A at site 2448, and the band that could be digested was named allele B; (2) PCR amplification was conducted using the upstream/downstream primers III-F2 and III-R2 to generate a product of 118 bp. Mutation at position 2101 was detected using the restriction digestion enzyme PleI. The product was single-digested using PleI, if it could be digested, this would result in fragments of 84 and 34 bp. The band that could not be digested was named allele A at site 2101, and the band that could be digested was named allele B; (3) PCR amplification was conducted using the upstream/downstream primers III-F3 and III-R3 to generate a product of 122 bp. Mutations at positions 254 and 224 were detected by digestion with the restriction enzymes HaeIII and AvaII, respectively. The product was single-digested using HaeIII; if it could be digested, fragments of 103 and 19 bp would be generated. The band that could not be digested was named allele A at site 254, and the band that could be digested was named allele B; the product was single-digested using AvaII; if it could be digested, fragments of 75 and 47 bp would be generated. The band that could not be digested was named allele A at site 224, and the band that could be digested was named allele B.

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In order to prevent the problem of the corresponding detection primer with low specificity from affecting subsequent experiments, fin lysate was used as the template and two-step PCR amplifications were conducted using two pairs of upstream/downstream primers, P7, P8 and P9, P10, before PCR amplification using the detection primers listed in Table 5.22. The amplification product was used as the template in the subsequent genotype detection. The final product was restriction enzyme digested and individuals with mutations were detected by 8% polyacrylamide gel electrophoresis. 5.6.1.7 Growth Correlation Analysis of SNPs Analysis of allele frequency was conducted using Popgene (Version 3.2). Correlations between SNPs and growth traits of largemouth bass were analyzed based on the least-squares method using the GLM in SPSS 17.0. The statistical analysis model was Yij 5 u 1 Bi 1 eij, wherein Yij indicated the observed value of marker i, j represented some individual trait; u was the average of all the individuals observed in the experiment (namely overall average); Bi was the effective value of marker i; and eij was the random error effect corresponding to the observed value.

5.6.2 Results and Analysis 5.6.2.1 Cloning of the 50 Flanking Sequence and Prediction of the Transcription Factor Action Site in the PSSIII Gene of Largemouth Bass Six genomic enzyme digestion
ligation libraries (DraI, PvuII, SspI, EcoRV, StuI, and ScaI) of largemouth bass were used as the templates (Li et al., 2008), and genomic walking was employed. A 50 flanking sequence of 1751 bp of PSSIII was obtained. The predicted result of the transcription element in the promoter region is shown in Fig. 5.7, including promoter basic transcription elements, such as TATA box, CAAT box, GATA box, and five Oct-1 binding sites, as well as five homeobox transcription factor binding sites, nine binding sites for CREB, and four binding sites for Brn POU domain factors (BRNF). 5.6.2.2 Screening Results of Mutation Sites After sequencing comparison, primers P5 and P6 were used to amplify the upstream sequence of the PSSIII promoter in largemouth bass and no SNPs were found. Primers P9 and P10 were used to amplify the

Table 5.22 Detection primers of SNPs in the PSSIII promoter SNPs Primer Primer sequence (50 -30 )

Restriction enzyme (50 -30 )

SNPs detected

2870 (A/C) 2448 (C/T) 2 101 (A/G) 254 (C/T)、 224 (C/T)

III-F1 III-R1 III-F2 III-R2 III-F3 III-R3

50 -CCATCAGCTCCATTGTACATCG-30 50 -GGTTCCAACATCACTTTGTAACTAAA-30 50 -CCTTCTGGATCTCTGGCTAG-30 50 -AGGTGACGGACCAGAGACTAC-30 50 -ACACTCCTGTCTCTGTGGGC-30 50 -CTGAACAGAAGCCCCATGAG-30

Note: Mismatched bases are marked in bold. SNP, single nucleotide polymorphism.

TaqI (TCGA) Ssp I (AATATT) PleI (GAGTC) HaeIII (GGCC) AvaII (GGWCC)

Figure 5.7 The promoter sequence of PSSIII in largemouth bass. PSSIII, preprosomatostatin. Note: Homeobox, TATA box, CAAT box, HEAT, and GATA box sequences are indicated by boxes; Oct-1, PAX2, and EVI-1 are underlined; HOMF is indicated by shading; CREB and BRNF are marked in bold. Mutated bases are marked in bold, and transcriptional factor EVI-1 and HSF binding sites at the mutated sites are indicated by parentheses. The start codon was set as “ 1 1.”

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Table 5.23 Genotype frequency distribution of SNPs in the promoter region of PSSIII in a random population of largemouth bass Locus Genotype Genotype frequency Allele frequency (%) (sample size, %)

A-870C

C-448T

A-101G

C-54T

C-24T

AA AB BB AA AB BB AA AB BB AA AB BB AA AB BB

0(0) 6.5(19) 93.5(274) 85.3(250) 13.3(39) 1.4(4) 67.6(198) 27.0(79) 5.5(16) 2.7(8) 32.4(95) 64.8(190) 6.5(19) 30.4(89) 63.1(185)

A 3.2

B 96.8

A 92.0

B 8.0

A 81.1

B 18.9

A 18.9

B 81.1

A 21.7

B 78.3

downstream sequence of the PSSIII promoter in 15 largemouth bass individuals, and five SNPs were found, which were: A/C mutation at site 2870, C/T mutation at site 2448, A/G mutation at site 2101, C/T mutation at site 254, and C/T mutation at site 224. Five mutations were detected in a random population with a sample size of 293 using primers listed in Table 5.22. The results showed that five SNPs are present in that population and the genotype frequency is shown in Table 5.23. 5.6.2.3 Correlation Analysis of Different Haplotypes and Traits Correlation of five SNPs of the PSSIII gene with growth in a random population of largemouth bass was investigated, and the multiple comparison result of growth traits among individuals with different genotypes is shown in Table 5.24. No individuals with genotype AA at site 2870 were found; individuals with genotype AB made up 6.5% of the sample population and genotype AB only showed a significant correlation with head length, body height, and caudal peduncle length (P , 0.05); three genotypes at both sites 2448 and 224 showed no significant correlation with any of the seven traits (P . 0.05); the genotype at site 2101 showed a correlation with a body weight of 0.057,

Table 5.24 Multiple comparisons of growth traits among individuals with different genotypes SNP Genotype Weight (g) Total length Body length Head length locus (cm) (cm) (cm)

A-870C C-448T

A-101G

C-54T

C-24T

AB BB AA AB BB AA AB BB AA AB BB AA AB BB

575.13 6 31.11a 526.43 6 8.19a 530.39 6 8.56a 539.09 6 21.67a 386.63 6 67.65b 539.92 6 9.60a 517.27 6 15.19ab 462.47 6 30.76b 484.75 6 48.13a 527.06 6 13.97a 532.73 6 9.88a 522.79 6 31.28a 530.47 6 14.46a 529.86 6 10.03a

31.46 6 2.28a 30.89 6 2.42a 30.97 6 0.15a 30.95 6 0.39a 28.34 6 1.20b 31.21 6 0.17a 30.53 6 0.27b 29.49 6 0.59c 30.72 6 0.86a 30.78 6 0.25a 31.02 6 0.18a 30.60 6 0.56a 30.78 6 0.26a 31.04 6 0.18a

27.83 6 0.52a 27.01 6 0.14a 27.10 6 0.14a 27.15 6 0.36a 24.29 6 1.12b 27.28 6 0.16a 26.80 6 0.25a 25.71 6 0.56b 26.55 6 0.80a 27.02 6 0.23a 27.11 6 0.16a 26.63 6 0.52a 27.06 6 0.24a 27.11 6 0.17a

11.67 6 0.52a 8.24 6 0.14b 8.43 6 0.15a 8.76 6 0.39a 7.50 6 1.22a 8.46 6 0.17a 8.60 6 0.27a 7.79 6 0.61a 7.92 6 0.86a 8.54 6 0.25a 8.45 6 0.18a 8.09 6 0.56a 8.57 6 0.26a 8.45 6 0.18a

Body height (cm)

Caudal peduncle length (cm)

Caudal peduncle height (cm)

9.89 6 0.32a 8.69 6 0.08b 8.79 6 0.09a 8.74 6 0.22a 7.84 6 0.70a 8.81 6 0.10a 8.76 6 0.16a 8.25 6 0.35a 8.41 6 0.50a 8.79 6 0.14a 8.77 6 0.10a 8.75 6 0.32a 8.77 6 0.15a 8.77 6 0.10a

6.15 6 0.16a 5.75 6 0.04b 5.79 6 0.05a 5.72 6 0.11a 5.49 6 0.36a 5.83 6 0.05a 5.73 6 0.08ab 5.39 6 0.18b 5.88 6 0.25a 5.79 6 0.07a 5.77 6 0.05a 5.64 6 0.16a 5.80 6 0.08a 5.78 6 0.05a

3.28 6 0.08a 3.27 6 0.02a 3.28 6 0.02a 3.23 6 0.06ab 2.90 6 0.18b 3.31 6 0.03a 3.21 6 0.04b 3.11 6 0.09b 3.24 6 0.13a 3.29 6 0.04a 3.27 6 0.03a 3.28 6 0.08a 3.27 6 0.04a 3.27 6 0.03a

Note: Multiple comparisons among different haplotypes used the LSD significance test method, and significant differences are indicated using the subscripts a, b.

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which was close to the significance level, and this genotype showed a significant correlation with body length, total length, caudal peduncle length, and caudal peduncle height (P . 0.05); individuals with the genotype AA at site 254 only made up 2.7% of the sample population, which was not statistically significant; individuals with genotypes AB and BB showed no significant difference in any of the growth traits (P . 0.05). SS plays an important role in regulating the expression of GH, and had been confirmed in many teleost fish (Vanetti et al., 1993). Five SNP loci were screened in the promoter region of the largemouth bass PSSIII gene, located at positions 2870, 2448, 2101, 254, and 224 bp. After further prediction of potential transcription elements in the promoter sequence, we found that the A/G mutation at site 2101 bp could cause loss of the binding site of Pax2, while none of the other four SNPs caused any alternation of transcriptional elements. Growth correlation analysis showed that SNPs at positions 2870, 2448, 2101, 254, 224 bp had no significant correlation with growth traits, while the SNP at position 2101 bp showed a significant correlation with all five growth traits. The Pax gene is the gene family exerting a regulatory function on embryogenesis, and the transcriptional factors encoded by this family regulate growth and development, embryogenesis, and organ formation of various animals, and demonstrate high conservatism from fruit fly to human. As well as pairing domain-encoding traits, the Pax gene contains one homologous domain and one octapeptide (OP). The OP consists of 24 amino acid residues and mainly performs a regulatory function in controlling transcription and repression (Eberhard et al., 2000). The allele with a Pax2 binding site at position 2101 bp in the promoter was named allele A, while that without the Pax2 binding site was named allele B. As the Pax2 protein has the OP domain exerting a repressive action on transcription, which causes the transcription efficiency of the PSSIII gene of individuals with genotype AA and AB at position 2101 to be significantly lower than those with genotype BB, growth traits, including body weight and body length, of individuals with genotype AA and AB were significantly superior to individuals with genotype BB. Direct sequencing revealed five SNP loci in the PSSIII promoter of largemouth bass, and the correlation of each locus with growth traits was analyzed. The results showed that the A base in the A/G mutation at position 2101 in the PSSIII promoter of largemouth bass is the dominant genotype.

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5.7 CORRELATION OF PROMOTER POLYMORPHISM OF THE IGF-I GENE IN LARGEMOUTH BASS WITH GROWTH TRAITS IGF-I is always an important candidate gene in studies of animal molecular marker
assisted selective breeding. A large number of studies have confirmed that several polymorphic loci in the IGF-I gene correlate with growth traits of cattle (Davis and Simmen, 2006), pigs (Estany et al., 2007), and chickens (Zhou et al., 2005). IGF has been shown to play an important role in the growth process of fish including many physiological functions, such as promotion of cell growth, differentiation and split (Pozios et al., 2001), regulation of cell metabolism, and inducing maturation of germ cells (Weber and Sullivan, 2000), in a similar way to terrestrial animals. GH regulates IGF-I expression and function in the liver to promote growth (Moriyama et al., 2000). When IGF-I recombinant protein was injected into juvenile tilapia, the results showed that compared with the control group, the growth rate of the experimental group increased by 67.3% (Zhang et al., 2006a). A study by Dyer et al. (2004) showed that IGF-I concentration in plasma was positively associated with growth rate in Australian lungfish and Atlantic salmon, and they considered that IGF-I concentration in plasma could be the basis for evaluation of growth rate. In this section we used the IGF-I gene as a candidate gene in analysis of the growth traits of largemouth bass. We studied the relationship between polymorphic loci in the promoter of the IGF-I gene and growth traits of largemouth bass, to lay a theoretical and practical basis for identifying molecular markers of largemouth bass growth traits and carrying out marker-assisted selective breeding of fish.

5.7.1 Materials and Methods 5.7.1.1 Experimental Fish The population for correlation analysis was collected from Jinhui farm in Jiujiang town, Nanhai district of Foshan city in Guangdong Province. During the entire culture process, fish were maintained under identical feeding and management conditions. When the cultured population reached 9 months of age, individuals were randomly selected from the same pond and were weighed and photographed. The average weight was 411.69 6 8.23 g. Four body measurement indices: total length, body length, body height, and body width, were measured using Winmeasure software. The sample size in this experiment was 91 and blood samples were collected from all experimental fish. Blood DNA was extracted

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using a blood genome extraction kit from Tiangen, and DNA samples were stored at 220˚C. 5.7.1.2 Extraction of Genomic DNA Blood samples from all the experimental fish were drawn from the caudal vein and anticoagulant (ACD) was added to blood at a volume ratio of 6:1. DNA was extracted from fish blood using a blood genome extraction kit from Tiangen, and DNA samples were stored at 220˚C. 5.7.1.3 Cloning of the Promoter Sequence of the Largemouth Bass IGF-I Gene Two downstream primers were designed based on exon 1 and intron 1 sequences of the IGF-I gene in largemouth bass, as follows: GSP1: 50 -CTGTGCAAATTGTGAGCAAGTGAATGTG-30 and GSP2: 0 5 -CACATAAATGCCAC TGAAAGGAAAGAGC-30 . According to the instructions supplied with the GenomeWalker Universal Kit, genomic DNA was digested using PvuII and connected with the connector in the kit to the construct library. The primer provided in the kit—AP1: 50 GTAATACGACTCACTATAGGGC-30 —and primer GSP1 designed in this study were used for PCR amplification. The procedure involved two cycles of 94˚C for 25 s and 72˚C for 3 min, followed by 32 cycles of 94˚C for 25 s and 67˚C for 3 min, then a final cycle of 67˚C for 7 min. The product was diluted 50-fold and used as the template, AP2: 50 -ACTATAGGGCACGCGTGGT-30 and GSP2 were used as the primers for the second PCR, and the procedure was the same as above. Amplification products were recovered and purified using low melting point agarose gel, incorporated into the pMD19-T vector, and transformed into competent E. coli DH5α cells. Plasmid was extracted by the alkaline lysis method and the size of the insert fragment was determined by enzyme digestion. Positive transformants were selected and sequenced by Shanghai Invitrogen Biotechnology Co., Ltd. Transcription factor binding sites in the promoter region were predicted using the TRANSFAC database (http://www.gene-regulation.com). 5.7.1.4 Amplification and Sequencing of the IGF-I Promoter Sequence A pair of primers was designed based on the sequence of the promoter and the exon amplified in the above steps: P1: 50 -CAGAATG GTTGCCAATTC-30 and P2: 50 -CATAAATGCCACTGAAAGG-30 to amplify the IGF-I promoter sequence. The PCR reaction system consisted of 2.0 μL 10 3 buffer (MgCL2 included), 0.4 μL dNTP (10 mmol/L),

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0.4 μL each upstream/downstream primer (10 mmol/L), 1 U Taq enzyme, 1.2 μL DNA template (50 ng/μL), and 14.6 μL ddH2O. The PCR procedure involved pre-denaturation at 94˚C for 3 min, followed by 30 cycles of denaturation at 94˚C for 30 s, annealing at 56˚C for 40 s and extension at 72˚C for 50 s, then ended with extension at 72˚C for 7 min, followed by thermal insulation at 12˚C. A fragment of 1782 bp (21701 to 181) was obtained using this pair of primers, including the IGF-I promoter and part of the sequence of exon 1. Forty-six individuals were selected from among 91 experimental fishes for PCR amplification and sequencing, in order to screen polymorphic sites likely to be present in the promoter sequence. Multiple sequence alignment was conducted using Vector NTI Suite 8.0 software (InforMax, Inc., Bethesda, MD, USA). 5.7.1.5 Genotyping of Polymorphic Loci in the IGF-I Gene Promoter Primers were designed based on both flanking sequences of polymorphic loci screened; the upstream primer was P1 and downstream primer was P3: 50 -CTCTATGTCACCAGTGTGC-30 . The PCR reaction system was the same as above. The PCR procedure involved pre-denaturation at 94˚C for 3 min, followed by 30 cycles of denaturation at 94˚C for 30 s, annealing at 56˚C for 30 s and extension at 72˚C for 30 s, then ended with extension at 72˚C for 7 min, followed by thermal insulation at 12˚ C. Polymorphism of PCR products was determined by 8% polyacrylamide gel (29:1) electrophoresis for 2 h, followed by silver staining. 5.7.1.6 Expression of Liver IGF-I mRNA in Individuals With Different Genotypes Expression of liver IGF-I mRNA in individuals with different genotypes was analyzed by semiquantitative RT-PCR. Twenty-two fish of the same age were randomly collected from the same pond (AA group: n 5 5; AB group: n 5 7; BB group: n 5 8) and placed in the temporary culture pool for 7 days, at the end of which a 100 mg sample of liver was taken and RNA was extracted according to the methods supplied with the RNApure total RNA isolation kit from Bioteke, and its quality and concentration was analyzed using 1% agarose gel electrophoresis. The reverse transcription process was conducted according to the instructions supplied with the ReverTra Ace Kit (Toyobo, Osaka, Japan). Primers for detection of IGF-I mRNA expression were designed based on IGFI cDNA of largemouth bass (NCBI Genbank Accession no. DQ666526): upstream primer: 50 -ATGTCTAGCGCTCTTTCCTTTC-30 ;

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downstream primer: 50 -CTTTGGAAGCAGCACTCGTC-30 . β-actin of Nile tilapia was used as the internal reference (upstream primer: 50 ATGGTGTGACCCACACAGTGCC-30 ; downstream primer: 50 TACAGGTCCTTACGGATGTCGA-30 ). After the reaction, PCR amplification was conducted using p1 and M13 primer M4: 50 GTTTTCCCAGTCACGAC-30 in the above kit. The procedure involved 1 cycle of 94˚C for 3 min, followed by 28 cycles of 94˚C for 30 s, 54˚C for 30 s, 72˚C for 1 min, and ended with 72˚C for 7 min. The PCR reaction mixture used for amplification of IGF-I and β-actin consisted of: 2 μL of synthesized cDNA, 1 3 Taq buffer (Mg21 Plus), 10 pmol each primer, 100 mM dNTP, and 1 unit Taq DNA polymerase (TaKaRa, Japan). The amplification procedure was as follows: 94˚C for 3 min, followed by 40 cycles of 94˚C for 30 s, 60˚C for 30 s, 72˚C for 30 s, and ended with 72˚C for 5 min. The amplification product was isolated by 2% agarose gel electrophoresis, and band density was scanned using a gel imaging system (BioRad). 5.7.1.7 Data Statistics SNP alleles and genotype frequency were calculated using Excel. Correlation of haplotype with growth traits of largemouth bass was analyzed by SAS 9.0 software. The analysis model was Y 5 μ 1 G or D 1 e, where Y indicates measured values of five growth traits; μ is the average of a growth characteristic; G or D is the fixed effect of each SNP or diplotype; e indicates the random effect. Intergroup differences of different genotypes and diplotypes were tested using Duncan’s multiple-range test.

5.7.2 Results and Analysis 5.7.2.1 The 50 Flanking Sequence of the IGF-I Gene in Largemouth Bass The 50 flanking sequence of approximately 1.8 kb was obtained through amplification of the IGF-I gene promoter. Transcription factor binding sites likely to be present were analyzed using the TRANSFAC database, and the results showed the presence of several potential transcription factor binding sites with higher expression in the liver (Fig. 5.8), including HNF 1 alpha (HNF-1α), HNF-3β and CCAAT/enhancer binding protein (C/EBP), which are all multicopy. In addition, no TATA, CCAAT-like, or GAGA sequences were found in the IGF-I sequence of largemouth bass, which was similar to results reported from other species.

Figure 5.8 The 50 upstream sequence of IGF-I from largemouth bass. The sequence is numbered relative to the position of the start codon (11), the exon sequence is shown using upper case letters, and the potential transcription factor binding sites HNF-1α, HNF-3β, C/EBPα, STAT5, Pit-1α, and ER are indicated with boxes. IGF-I, insulin-like growth factor-I; HNF-1α, hepatocyte nuclear factor 1 alpha; HNF-3β, hepatocyte nuclear factor 3 beta; C/EBPα, CCAAT/enhancer binding protein alpha; ER, estrogen receptor. Source: From Li, X., Bai, J., Ye, X., et al., 2009. Polymorphisms in the 50 flanking region of the insulin-like growth factor I gene are associated with growth traits in largemouth bass Micropterus salmoides. Fish. Sci. 75 (2), 351
358. r 2009 The Japanese Society of Fisheries Science.

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5.7.2.2 Polymorphism of the 50 Flanking Sequence of the IGF-I Gene in Largemouth Bass Sequencing results showed that there were two SNPs (2635 and 2636) and one insertion
deletion mutation (from 2633 to 2632) in the 50 flanking sequence of the IGF-I gene in largemouth bass. The three polymorphic loci constituted two haplotypes: one was ATTTTTGTTTTT (haplotype A); and the other was ATAATT----TT (haplotype B). The two haplotypes resulted in changes in transcription factor binding sites, from 2649 to 2640 in haplotype A, which contains a transcription factor binding site for the estrogen receptor (ER); and from 2638 to 2629, which contains a transcription factor binding site for POU1F1 (Pit-1). Changes in transcription factor binding sites may thus affect expression of the IGF-I gene (Fig. 5.8). 5.7.2.3 Genotype and Haplotype Frequency of the IGF-I Gene Promoter Polymorphism A total of three genotypes and two haplotypes were found in the largemouth bass population in this study. Product fragments of haplotype A and haplotype B were 260 and 256 bp, respectively (Fig. 5.9). The different genotypes and their haplotype frequency are shown in Table 5.25. 5.7.2.4 Correlation Analysis of IGF-I Gene Polymorphisms and Growth Traits Statistical analysis showed that polymorphisms in the promoter of the IGF-I gene had effects on body weight and body width of largemouth bass (P , 0.05). Multiple comparisons among different genotypes indicated that individuals with genotype AA had higher body weight and greater body width than genotypes BB or AB (P , 0.05). Total length, body length, and body height showed no significant correlation with genotype (Table 5.26).

Figure 5.9 Gel electrophoresis of polymorphic loci in the 50 upstream sequence of the largemouth bass IGF-I gene. IGF-I, insulin-like growth factor-I. Source: From Li, X., Bai, J., Ye, X., et al., 2009. Polymorphisms in the 50 flanking region of the insulin-like growth factor I gene are associated with growth traits in largemouth bass Micropterus salmoides. Fish. Sci. 75 (2), 351
358. r 2009 The Japanese Society of Fisheries Science.

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Table 5.25 Haplotype and genotype frequency of polymorphic loci in the 50 upstream sequence of the largemouth bass IGF-I gene Genotype frequency (%) (sample size) Allele frequency (%)

AA 11 (10)

AB 48 (44)

BB 41 (37)

A 35

B 65

Table 5.26 Correlation analysis between genotypes at polymorphic loci in the 50 upstream sequence of the largemouth bass IGF-I gene and growth traits Traits Genotypes

Weight (g) Total length (cm) Body length (cm) Body height (cm) Body width (cm)

AA

AB

BB

Pvalue

472.35 6 23.98a 29.74 6 0.62a 26.19 6 0.58a 8.60 6 0.24a 4.52 6 0.12a

412.59 6 11.43ab 28.90 6 0.28a 25.25 6 0.26a 8.03 6 0.15a 4.21 6 0.06b

394.23 6 12.47b 28.77 6 0.33a 25.32 6 0.30a 7.95 6 0.13a 4.16 6 0.06b

0.018 0.103 0.104 0.064 0.025

Note: Different subscripts in each row indicate a significant difference (P , 0.05).

5.7.2.5 Differences in Expression of IGF-I mRNA in the Liver of Different Genotypes Semiquantitative PCR showed that polymorphism of the 50 flanking sequence of IGF-I significantly affected the expression level of IGF-I mRNA in the liver (Fig. 5.10). The mRNA level of IGF-I in the liver of individuals with genotype AA was higher than in individuals with genotypes AB or BB (P 5 0.018 and P 5 0.001, respectively). In the 1770 bp upstream sequence of the IGF-I gene in largemouth bass, there was no TATA box or CAAT box, and the IGF-I gene in the human, mouse, salmon, and carp has similar traits. Both the TATA box and CAAT box are basic promoter elements and their absence in the IGF-I gene may cause nonspecificity of the transcription initiation site (Kajimoto and Rotwein, 1991). This phenomenon is closely related to the function of the IGF gene in development and organ-specific aspects. Moreover, in the promoter of the IGF gene, binding sites for C/EBP, HNF-1, HNF-3, and other transcription factors expressed more highly in the liver were also multiple copies. These promoter traits were closely related to the extensive functions of IGF-I (Nolten et al., 1995). Polymorphic loci in the promoter of the largemouth bass IGF-I gene affected weight and body width. Individuals with genotype AA had higher

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Figure 5.10 (A) Expression analysis of IGF-I mRNA in the liver of largemouth bass. The band at 279 bp was IGF-I, and that at 412 bp was the β-actin gene. (B) IGF-I mRNA expression of the three genotypes. IGF-I mRNA concentration was calibrated using β-actin as the internal standard. IGF-I, insulin-like growth factor-I. Source: From Li, X., Bai, J., Ye, X., et al., 2009. Polymorphisms in the 50 flanking region of the insulin-like growth factor I gene are associated with growth traits in largemouth bass Micropterus salmoides. Fish. Sci. 75 (2), 351
358. r 2009 The Japanese Society of Fisheries Science.

body weight than individuals with genotype AB or BB. It has also been reported that polymorphic loci in the IGF-I promoter correlate with growth in humans and livestock. In humans, one polymorphic locus in the IGF-I promoter has been shown to correlate closely with serum IGF-I level, weight at birth, and body height (Rietveld et al., 2004). One CA repeat polymorphism in the bovine IGF-I promoter showed a correlation with weight at birth, weaning weight and weight at 1 year of age (Moody et al., 1996). In order to further study the effects of polymorphic loci in the IGF-I promoter on the growth of largemouth bass, semiquantitative RT-PCR was used in this study to measure the effects of the three genotypes of IGF-I promoter polymorphism on IGF-I expression. The results showed that IGF-I promoter polymorphism affected expression of the IGF-I gene in the liver. The expression level of the liver IGF-I gene in individuals with genotype AA was higher than that in individuals with genotypes AB or BB, a finding which was consistent with the results of growth

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correlation analysis. One reason might be changes in transcription factor binding sites. The transcription factor binding site formed by haplotype A was for the ER, while that formed by haplotype B was for Pit-1α. ER is an estrogen-dependent transcription factor which regulates genetic expression (Levin, 2009). Pit-1 is mainly expressed in the pituitary gland and plays a crucial role in cell differentiation, while it also acts as a transcription factor for GH and PRL (Andersen and Rosenfeld, 1994). A large number of in vivo and in vitro experiments have demonstrated ERmediated estrogen regulation of IGF-I expression. In the HepG2 cell line which expresses exogenous ER, the response to 1026 M 17 beta-estradiol of one reporter gene plasmid containing 600 bp of the chicken IGF-I promoter could be increased 8.6-fold (Maor et al., 2006). In the mouse uterus, mediated by the ER, estrogen stimulated the generation of IGF-I (Klotz et al., 2002). In contrast, there is no evidence that Pit-1 has any relationship with IGF-I gene expression. The results of this experiment indicated that changes in transcription factor binding could regulate expression of the IGF-I gene in largemouth bass. IGF-I is the most important candidate gene in relation to largemouth bass growth traits, and polymorphic markers in the IGF-I promoter are expected to be used for marker-assisted selective breeding of largemouth bass.

5.8 CORRELATION OF IGF-II GENE POLYMORPHISM WITH GROWTH TRAITS OF LARGEMOUTH BASS IGF-II is an important candidate gene in human growth and development, as well as in regulating the growth traits of domestic animals. A large number of studies have indicated that human IGF-II not only affects birth weight, but also affects weight in adult humans (Gomes et al., 2005; Zhang et al., 2006c). In research on aquatic animals, a QTL positioning study on barramundi showed that IGF-II positioned in just the LG10 region affected body weight and body length (Wang et al., 2008a). In this section, the entire genome sequence of the IGF-II gene in largemouth bass was cloned, SNPs in IGF-II were screened, and correlation of these SNPs with growth traits of largemouth bass was analyzed.

5.8.1 Materials and Methods 5.8.1.1 Experimental Animals Experimental fish were collected from Jinhui farm in Jiujiang town, Nanhai district in Foshan city. All the fish were incubated for the same time and maintained under the same conditions of culture and

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management. At approximately 9 months of age, 127 individuals of largemouth bass were randomly selected and weighed, and four body measurement indices: total length, body length, body height, and body width, were measured. The average weight of experimental fish was 411.69 6 8.23 g. Blood samples were drawn from the caudal vein of all the experimental fishes and mixed with anticoagulant (ACD) at a blood volume ratio of 1:6. DNA was extracted from fish blood using a blood genome extraction kit from Tiangen, and all DNA samples were stored at 220˚C. 5.8.1.2 Cloning of the IGF-II Genomic Sequence Degenerate primers were designed in the homologous conservative region based on cDNA sequences of gilthead (Duguay et al., 1996), barramundi (Collet et al., 1997), tilapia (Chen et al., 1997), European seabass (Terova et al., 2007), white seabream (Ponce et al., 2008), and other fish IGF-II sequences in Genbank. The upstream IGF-II primer was F: 50 ATGGARACCCMGMAAAGAYACG 30 ; and the downstream IGF-II primer was R: 50 -TCATTTGTGRYTGACRWAGTTGTC-30 . This pair of primers was used to directly amplify the genomic sequence of the IGF-II gene. PCR reactions were carried out in a 20 μL reaction mixture consisting of 50 ng DNA template, 2.0 μL 10 3 buffer, 2.5 mM MgCL2, 0.20 mM each upstream/downstream primer, and 0.20 mM dNTP. The PCR procedure involved pre-denaturation at 94˚C for 5 min, followed by 30 cycles of denaturation at 94˚C for 45 s, annealing at 60˚C for 1 min and extension at 72˚C for 1 min, then ended with extension at 72˚C for 10 min, and finally stored at 4˚C. After purification using a genomic DNA purification kit (Promega), the PCR product was incorporated into the pMD19-T vector, and transformed into competent E. coli DH5α cells. The transformant was used to extract the plasmid through alkaline lysis, the size of the inserted fragment was determined by digestion, and positive transformants were picked and sent to Shanghai Invitrogen Biotechnology Co., Ltd. for sequencing. 5.8.1.3 Cloning of the Promoter Sequence in the IGF-II Gene Two downstream primers, GSP1: 50 -CCTTCATTCTGCTGC TCTCCGTTCTCC-30 and GSP2: 50 -AGTGAGTGGTGTCCG TATCTTTTCTGG-30 , were designed in exon 1 of the IGF-II gene. According to the instructions of GenomeWalker Universal Kit, genomic DNA was digested using PvuII and connected with the connector in the kit to a construct library. The primer provided in the kit was

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AP1:50 -GTAATACGACTCACTATA-GGGC-30 and was used together with primer GSP1 designed in this study for PCR amplification. The procedure involved two cycles of 94˚C for 25 s and 72˚C for 3 min, followed by 32 cycles of 94˚C for 25 s and 67˚C for 3 min, then a final cycle of 67˚C for 7 min. The product was then diluted 50-fold as the template, AP2: 50 -ACTATAGGGCACGCGTGGT-30 and GSP2 were used as primers for the second PCR, and the procedure used was the same as above. The methods of transformation, identification, and sequencing of amplification products were the same as above. The TRANSFAC database was used to predict the cis-acting elements in the promoter (http://www. gene-regulation.com). 5.8.1.4 Screening of SNPs in the IGF-II Gene In order to screen for polymorphisms in IGF-II, four pairs of primers (Table 5.27) were designed based on the IGF-II sequences obtained above. Twenty individuals of largemouth bass were bought in the local market and used to screen for polymorphisms. A genomic DNA extraction kit was used to extract DNA. The IGF-II gene fragment was obtained through PCR amplification, and the PCR product was purified by gel electrophoresis and then directly sequenced. 5.8.1.5 Genotyping of SNPs in the IGF-II Gene A total of four SNPs were found in the IGF-II gene of largemouth bass, and the RFLP method was used in this experiment to perform genotyping of SNPs. Specific primers were designed based on both flanking sequences of each SNP, and the amplification conditions of these primers are shown in Table 5.28. When PCR products contained SNP fragments, 2
4 units of a restriction digestion enzyme were added to each microgram DNA template for digestion. The digestion time was 3 h. The PCR product after digestion was isolated using 12% polyacrylamide gel electrophoresis and silver stained. 5.8.1.6 Statistical Analysis SNP alleles and genotype frequency were calculated using Excel. The chi-square test was used to analyze whether each SNP was in HWE. The haplotypes of the four SNPs were calculated using Arlequin software (http://lgb.unige.ch/arlequin/). For the diplotypes with a sample size greater than three, their correlation with growth traits of largemouth bass was analyzed using SAS 9.0. The analysis model was: Y 5 μ 1 G or D 1 e,

Table 5.27 Amplification primers of the IGF-II genomic sequence in largemouth bass Primer Primer sequence Locusa

IGF-II 1 IGF-II 2 IGF-II 3 IGF-II 4

a

50 GTGAGCCACCAAATGTCATC 30 50 TGTTCCCTCTGGTTACCTTC 30 50 ATGGAAACCCAGAAAAGATAC 30 50 GGTGCTATTACTTTACTGGT 30 50 CACGCACTCACACTCATACG 30 50 CACAGTGTCAGGCACATAGG 30 50 GGAAACAATGCTAATCATCG 30

2741. . . 2 722 172. . . 1 91 11. . . 1 21 11465. . . 1 1484 11253. . . 1 1272 12827. . . 1 2846 12770. . . 1 2789

50 TCATTTGTGGTTGACGAAGT 30

14373. . . 1 4392

Base position was referred to as the transcriptional start codon (11).

Annealing temperature (°C)

Product length (bp)

Amplification region

52

832

51

1484

53

1594

54

1623

Promoter and Exon 1 Exon 1, 2 and Intron 1 Intron 2 and Exon 3 Intron 3 and Exon 4

Table 5.28 Genotyping primers of SNPs in the largemouth bass IGF-II gene and amplification conditions SNP Product Primer length (bp) Locus Forward/ Position Sequence (50
30 ) Reverse

Annealing temperature (°C)

Restriction enzyme

C127T

226

56

TaqI

T1012G

196

52

HinfI

C1836T

214

54

NdeI

C1851T

214

54

MboII

F R F R F R F R

1
22 207
226 935
953 858
875 1715
1734 1909
1928 1715
1734 1909
1928

ATGGAAACCCAGAAAAGATACG GCACAAAAATGATGCGATC ATGTCTTCGTCCAGTCGTG AGCGAAACATGTACGCAGC CTTCAGTTTGTACAGTCTGC GTGGGAGCACATCTATGTTG CTTCAGTTTGTACAGTCTGC GTGGGAGCACATCTATGTTG

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where Y indicated the measured values of five growth traits; μ was the average of a growth trait; G or D was the fixed effect of each SNP or diplotype; and e indicated the random effect. Intergroup differences of different genotypes and diplotypes were tested using Duncan’s multiplerange test.

5.8.2 Results and Analysis 5.8.2.1 Sequence of the IGF-II Gene in Largemouth Bass The sequence of approximately 5.2 kb of the largemouth bass IGF-II gene was cloned (GenBank accession number: GQ328049), including a 50 upstream sequence of 764 bp. The positions of introns and exons in the largemouth bass IGF-II gene were determined based on comparison of IGF-II cDNA of barramundi (Collet et al., 1997), tilapia (Chen et al., 1997), and European seabass (Terova et al., 2007). There were four exons and three introns in the IGF-II gene. The length of each of the four exons was 75, 151, 182, and 240 bp, and the length of the introns were 852, 1481, and 1417 bp. Transcription factor binding sites in the IGF-II gene were predicted using the TRANSFAC database, including C/EBP, HNF, Sp1, and TATA box. 5.8.2.2 SNP Loci in the Largemouth Bass IGF-II Gene A total of four SNPs (C127T, T1012G, C1836T, and C1861T) were identified in the IGF-II gene. Among them, SNP T1012G was located in exon 2 and was identified as a synonymous mutation. SNP C127T was located in intron 1, while SNP C1836T and SNP C1861T were located in intron 2. 5.8.2.3 Allele and Genotype Frequency of the Four SNPs The allele and genotype frequency of the four SNPs are shown in Table 5.29. In the two alleles of SNP C82T, SNP C1836T, and SNP C1851T, C was the dominant allele. However in SNP T1012G, G was the dominant allele. The dominant allele frequency of all four SNPs was very high, exceeding 70% in all SNPs. Chi-square analysis showed that all the SNP loci were in Hardy
Weinberg equilibrium. 5.8.2.4 Analysis of Haplotypes and Diplotypes Through analysis of the three genotypes of all four SNPs, a total of seven haplotypes were obtained in the largemouth bass population, and the haplotype frequency is shown in Table 5.30. Haplotype 1 was the most

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Table 5.29 Allele frequency and genotype frequency of the four SNPs in the IGF-II gene of largemouth bass Locus

Genotype frequency (%)

SNP C82T

CC 55.12 TT 54.33 CC 58.27 CC 55.12

SNP G1012T SNP C1836T SNP C1851T

CT 40.16 GT 40.16 CT 39.37 CT 39.37

Allele frequency (%)

TT 4.72 GG 5.51 TT 2.36 TT 5.51

C 75.20 T 74.41 C 77.95 C 74.80

T 24.80 G 25.59 T 22.05 T 25.20

SNP, single nucleotide polymorphism.

Table 5.30 Haplotype and diplotype frequency of the IGF-II gene in largemouth bass Haplotype

SNP C82T

SNP T1012G

SNP SNP C1836T C1851T

Frequency (%)

Diplotype

Frequency (%)

H1 H2 H3 H4 H5 H6 H7

C T C T T C T

T G G G T T T

C T C C T T T

70.4 18.5 3.1 3.9 2.0 1.5 0.4

H1H1 H1H2 H1H3 H1H5 H4H4 H2H4 H1H4 H6H6 H2H3 H2H5 H1H7 H3H3

49.61 33.86 3.15 3.15 2.36 1.57 1.57 1.57 0.79 0.79 0.79 0.79

C T C T T C C

SNP, single nucleotide polymorphism.

common haplotype and its frequency reached 70.4%. Another relatively common haplotype was haplotype 2 with a frequency of 18.5%. The two most common haplotypes were used as reference, and two haplotype branches were obtained through analysis. A mutation T-G at site 1012 of haplotype 1 used as the reference turned it into haplotype 3, and a mutation C-T at site 1836 created haplotype 6. Using haplotype 2 as the reference, a mutation T-C at site 1836 turned it into haplotype 4, and a mutation G-T at site 1012 turned it into haplotype 5. Further, a mutation T-C at site 1851 turned haplotype 5 into haplotype 7. Haplotype changes showed that SNP T1012G and SNP C1836T were the two active mutations. The seven haplotypes constituted 13 diplotypes

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(Table 5.30), and the two common diplotypes of D1 and D2 accounted for 83.47% of the overall diplotype frequency. 5.8.2.5 Correlation of SNPs With Growth Traits The correlation of four SNPs and the diplotypes they constituted with growth traits of largemouth bass was analyzed using the GLM process. No single SNP showed any significant correlation with growth traits. Correlation analysis of haplotype with growth traits (Table 5.31) showed that haplotype correlated significantly with body weight, total length, body length, body height, and body width (P , 0.05). Multiple comparisons among haplotypes showed the growth traits of the H1H3 population were the best, while those of H4H4 were the worst. The growth performance of the H1H3 population was better than the other haplotypes (H1H1, H1H2, and H4H4) (P , 0.05). Meanwhile, the body weight and body width of H1H5 were greater than those of populations H1H1, H1H2, and H4H4. The genomic sequence of largemouth bass IGF-II, approximately 5.2 kb in length, was cloned in this study. The IGF-II gene in largemouth bass consists of four exons and three introns, and its structure is similar to the IGF-II gene structure of teleosts reported in other studies (Radaelli et al., 2003; Tse et al., 2008; Palamarchuk et al., 1997; Chen et al., 1997). A TATA box was identified at a site 150 bp upstream of the IGFII gene promoter, similar to the IGF-II gene in barramundi (Radaelli et al., 2003), tilapia (Chen et al., 1998), rainbow trout (Shamblott et al., 1998), and other fish, indicating that the IGF-II gene structure of teleosts is quite similar. A total of four SNPs was found in the largemouth bass IGF-II gene. Only SNP T1012G was located in the exon, while the other three SNPs were located in the introns. Thus more SNPs were identified in the introns of the largemouth bass IGF-II gene than in the exons, a phenomenon which has also been reported in largemouth bass IGF-I and MyoD (Li et al., 2009a; Yu et al., 2009). Differences in SNP distribution between exons and introns showed that the exon regions experienced a stronger selective pressure. In previous studies, single SNP analysis was the method commonly used in correlation analysis between candidate genes and economic traits. However, studies in recent years have shown that haplotype or diplotype analysis produces better statistical results, as haplotype correlation analysis can reveal interactions among multiple SNPs in one gene

Table 5.31 Correlation of diplotypes of the IGF-II gene in largemouth bass with growth traits Diplotype Weight (g) Total length (cm) Body length (cm) Body width (cm)

H1H1 H1H2 H1H3 H1H5 H4H4

451.86 6 20.13 401.27 6 24.18A 845.88 6 79.27B 765.13 6 79.27B 281.33 6 91.53AC

28.93 6 0.39 27.94 6 0.47AC 35.15 6 1.53B 31.88 6 1.53BC 24.61 6 1.77AD

A

Data in the table are means 6 standard error.

AC

25.37 6 0.36 24.44 6 0.43AC 31.17 6 1.42B 28.19 6 1.42BC 21.71 6 1.64AD AC

8.35 6 0.16 7.87 6 0.19A 11.33 6 0.62B 9.95 6 0.62BC 6.81 6 0.72A

AC

Upper case letters in the same column indicate a significant difference (P , 0.05).

A, B

Body thickness (cm)

4.34 6 0.08A 4.12 6 0.10A 5.73 6 0.32B 5.58 6 0.32B 3.65 6 0.37AC

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(Drysdale et al., 2000). In this study, a single SNP showed no correlation with growth traits, while haplotypes and diplotypes of the four SNPs showed significant correlation with growth traits. H1H3 and H1H5 populations had much better growth performance, therefore haplotype H3 and H5 might be the haplotypes which are beneficial to growth. Growth traits of H4H4 were the worst, suggesting that haplotype H4 might have an adverse effect on growth. These results showed the interaction among the four SNPs in the IGF-II gene, and SNP markers in the IGF-II gene could thus be used in future breeding practices of largemouth bass. On the other hand, the sample size of each diplotype in this experiment was limited; therefore, a larger sample size should be investigated in future to further validate the correlation between the IGF-II gene and growth traits of largemouth bass.

5.9 SNPS IN THE GHRELIN GENE AND ASSOCIATIONS WITH GROWTH TRAITS IN LARGEMOUTH BASS Ghrelin is an endogenous ligand of the GH secretagogue receptor and many studies of the association between ghrelin gene polymorphism and growth have been conducted in recent years. A SNP locus found in the promoter region of the human ghrelin gene is significantly associated with the body mass index and waistline (P , 0.05) (Vartiainen et al., 2006). The polymorphic locus Leu72Met in the ghrelin gene has significant effects in terms of a high body mass index and low insulin secretion in obese children (Korbonits et al., 2002). A SNP found in the chicken ghrelin gene also affects several growth traits (Fang et al., 2007; He et al., 2007). In this section, the ghrelin gene was used as a candidate gene and associations were analyzed between the SNPs in this gene and growth traits of largemouth bass.

5.9.1 Materials and Methods 5.9.1.1 Materials The largemouth bass samples used for screening SNP loci in this experiment were obtained from the aquatic breeding base at the Pearl River Fisheries Research Institute. The largemouth bass individuals were bred in the same batch and fed with artificial feed after acclimation. Twelve extremely large individuals with an average body weight of 480 6 22.15 g and 12 extremely small individuals with an average body weight of 320 6 19.32 g were selected. The caudal fins were cut and preserved

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in absolute ethanol at 220˚C for subsequent DNA extraction and SNP screening. The largemouth bass samples used for association analysis were collected from the largemouth bass aquaculture base in Yangshan town, Qingyuan city, Guangdong, and their average body weight was 428 6 17.78 g. The sampled population was acclimated with artificial formula feed from a length of 2 cm and they were fed using artificial feed throughout the whole process. Growth traits including body weight, total length, body width, and body height were measured in 327 individuals, which were randomly selected from the population at 7 months of age in the association analysis. The fins were cut to extract DNA for SnaPshot typing using a DNA extraction kit purchased from Tiangen Biotech (Beijing) Co. Ltd. and 2 3 Taq PCR master mix was purchased from Takara Biotechnology (Dalian) Co. Ltd. The primers were synthesized by Guangzhou Jige Biotechnology Co. Ltd. Low melting point agarose was purchased from Sigma (USA). 5.9.1.2 Genomic DNA Extraction DNA was extracted according to the instructions provided with the kit. Fin samples weighing about 60 mg were cut into pieces and digested at 56˚C until they were transparent to obtain the lysate. The concentration was determined using an ultraviolet spectrophotometer and the extracted DNA was then stored at 220˚C. 5.9.1.3 Primer Design Primers were designed based on the largemouth bass ghrelin gene promoter sequence in GenBank (GenBank accession number FJ392504.1) using Primer Premier 5.0. The upstream primer was GH-F: 50 -ACTTCCATAA CAACTGACCTGCACT-30 , and the downstream primer was GH-R: 50 -GTAACAAATGCTTGTGCTTTCGTGT-30 . The primers were synthesized by Guangzhou Jige Biotechnology Co. Ltd. 5.9.1.4 PCR Amplification and SNP Loci Screening The PCR reaction mixtures comprised 10 μL 2 3 Taq PCR master mix, 0.5 μL upstream/downstream primers, 0.5 μL template DNA, and ddH2O was added to make the total volume up to 20 μL. The PCR reaction procedure comprised pre-denaturation at 94˚C for 2 min, followed by 35 cycles of denaturation at 94˚C for 10 s, annealing at 57˚C for 15 s, and extension at 72˚C for 30 s, with a final extension at 72˚C for 10 min. Next, 1.2% agarose gel electrophoresis was used to detect the

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amplification products. The PCR products were sequenced by Guangzhou Ige Biotechnology Co. Ltd. The sequencing results was aligned and screened for SNP loci using BioEdit software. 5.9.1.5 SnaPshot Typing Typing was performed by Shanghai Generay Biotech Co. Ltd. using the SnaPshot method. The specific method comprised multiplex PCR of DNA based on the SNP loci information obtained by sequencing. The 3-μL PCR products were purified using ExoI and FastAP, incubated at 37˚C for 1 h, inactivated with ExoI and FastAP enzyme at 75˚C for 15 min, and the purified products were used in the extension reaction with the SnaPshot kit provided by ABI company based on the kit instructions, and they were then detected using an ABI 3730XL sequencer. 5.9.1.6 Statistical Analysis of Data Genetic parameters comprising the number of effective alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), and allele frequency were calculated using Popgene 32 (version 3.2). Correlation analysis was conducted based on a GLM using SPSS 17 software. The dependent variables comprised the growth traits, i.e., body weight, total length, body width, and body height, and the independent variables were the different genotypes of the screened SNP loci. The biometric model was Yij 5 μ 1 Bi 1 eij, where Yij represents the observed value of marker i for individual j, μ represents the average value among all the individuals observed in the experiment, Bi is the effective value for marker i, and eij is the random residual effect of the corresponding individual observed value.

5.9.2 Results and Analysis 5.9.2.1 Screening for SNP Loci in the Ghrelin Gene A fragment measuring 602 bp was obtained after PCR amplification using the primers GH-F and GH-R. Two SNP loci were found after sequencing and aligning (Fig. 5.11), which were designated as S1: A-642C and S2: A-639C. The two mutant loci were located in the same Oct-1 in the largemouth bass ghrelin gene promoter. 5.9.2.2 Genetic Structure of the Ghrelin Gene SNP Loci in the Population The ghrelin gene was typed in 327 largemouth bass individuals using the SnaPshot typing technique and the typing results were processed with

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Figure 5.11 Partial sequence alignment around the mutation of the promoter of ghrelin gene (the shadings represent the mutation site). Table 5.32 The polymorphic parameters of two SNPs site of ghrelin gene Site Ne He Ho PIC Hardy
Weinberg equilibrium

S1 S2

1.9362 1.1620

0.4843 0.1396

0.6831 0.1508

0.3667 0.1289

0.1206 0.0047

Popgene32 software. Partial genetic parameters for the SNP loci are shown in Table 5.32. The statistical analysis of the genotypes, genotype frequency, and allele frequency for the SNP loci are shown in Table 5.33. Three base combinations, i.e., AA, AC, and CC, were found at the S1 locus, which we designated as the AA, AC, and CC genotypes, respectively. Only two base combinations, i.e., AA and AC, were found at the S2 locus, which we designated as the AA and AC genotypes, respectively. 5.9.2.3 Association Analysis Between Different Haplotypes and Growth Traits The association analysis was performed using a GLM and the correlation results for the S1 and S2 loci with the growth traits are shown in

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Table 5.33 Genotype and gene frequency of the SNPs site of ghrelin gene Site Sample Number/genotype frequency Gene frequency number

S1 S2

327 327

AA

AC

CC

A

C

22/0.067 278/0.850

224/0.685 49/0.150

81/0.248

0.4092 0.9246

0.5908 0.0754

Table 5.34. For locus S1, the average body weight, body width, total length, head length, body height, and caudal peduncle length were all higher in individuals with the AA genotype compared with those with the AC genotype, and there was a significant difference in head length between individuals with the AA and AC genotypes (P , 0.05). In total, five diplotypes were formed by combinations of the S1 and S2 loci: D1 (AC and AA), D2 (AA and AA), D3 (CC and AA), D4 (AC and AC), and D5 (CC and AC). The associations between different diplotypes and growth traits are shown in Table 5.35. The body weight, total length, and body height were significantly higher in fish with the D1 diplotype compared with those with the D3 diplotype (P , 0.05). The body weight, body width, and body height were significantly higher in fish with the D1 diplotype compared with those with the D4 diplotype (P , 0.05). The ghrelin gene is directly related to animal feeding and GH secretion, and it is one of the most important candidate genes considered in molecular breeding studies of animals in recent years. In this study, we detected two SNP loci, S1 and S2, in the largemouth bass ghrelin gene promoter, but only two genotypes, i.e., AA and AC, occurred at the S2 locus, and CC genotype was not found. We conducted typing for 269 largemouth bass individuals from different sources and the results showed that the CC genotype was absent (not found in this study). Thus, we suggest that CC genotype may be lethal during a specific development stage in the offspring. A previous study of the largemouth bass GHRH gene conducted in our laboratory found that all individuals with the BB genotype at the mutation locus in the promoter died during the fry stage after hatching (Ma et al., 2014). According to our previous study, the mutation site was the binding site for many transcriptional factors, and the mutation affected the transcription and expression of the gene, thereby affecting normal cellular proliferation in the organism (Valerius et al., 1995). Polymorphisms in a promoter are likely to cause changes in the binding

Table 5.34 Correlation of ghrelin genotypes with growth traits SNP Genotype Number Body weight Body width site (g) (cm)

S1

S2

AA AC CC AA AC

22 224 81 278 49

408.61 6 31.38 437.58 6 9.89 408.21 6 16.08 434.00 6 8.88 396.38 6 21.04

4.05 6 0.11 4.12 6 0.04 4.06 6 0.06 4.12 6 0.03 4.00 6 0.07

Total length (cm)

Head length (cm)

Body depth (cm)

Caudal peduncle length (cm)

27.90 6 0.60ab 28.59 6 0.19a 27.88 6 0.31b 28.45 6 0.17a 27.92 6 0.40b

7.18 6 0.35 7.35 6 0.10 7.36 6 0.17 7.41 6 0.09 6.93 6 0.13

8.29 6 0.25ab 8.59 6 0.08a 8.28 6 0.13b 8.54 6 0.07 8.24 6 0.17

8.49 6 0.22 8.67 6 0.07 8.49 6 0.12 8.61 6 0.06 8.64 6 0.15

Data in the table are X 6 SE, different superscript letters in the same column indicate significant difference at P , 0.05. SNP, single nucleotide polymorphism.

Table 5.35 Correlation of ghrelin gene diplotypes with growth traits Diplotype S1 S2 Number Body weight (g) Body width (cm)

D1 D2 D3 D4 D5

AC AA AA AA CC AA AC AC CC AC

188 22 70 36 11

447.44 6 10.80a 408.61 6 31.38ab 404.56 6 17.29b 386.07 6 24.55b 431.41 6 43.78ab

4.16 6 0.04a 4.05 6 0.11ab 4.05 6 0.06ab 3.95 6 0.09b 4.15 6 0.15ab

Total length (cm)

Head length (cm)

Body depth (cm)

Caudal peduncle length (cm)

28.75 6 0.21a 27.90 6 0.60ab 27.79 6 0.33b 27.78 6 0.46ab 28.43 6 0.83ab

7.42 6 0.11 7.18 6 0.32 7.46 6 0.18 6.99 6 0.16 6.70 6 0.28

8.67 6 0.09a 8.29 6 0.25ab 8.25 6 0.14b 8.16 6 0.19b 8.48 6 0.35ab

8.70 6 0.08 8.49 6 0.22 8.43 6 0.12 8.55 6 0.17 8.93 6 0.31

Data in the table are X 6 SE, different superscript letters in the same column indicate significant difference at P , 0.05.

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sites for transcription factors to affect gene transcription and expression, and ultimately the related traits in animals (Du et al., 2011; Aruhan, 2012; Song et al., 2011; Yang et al., 2013). The two SNPs found in this study were located in the promoter and mutations changed the binding site sequence for a transcriptional regulatory element, Oct-1. The sequence of the Oct-1 binding site was ATGCAAAT and it became CTGCAAAT, CTGAAAAT, or ATGAAAAT after mutation, which disrupted the Oct-1 binding site (Zhao et al., 2002). Thus, mutations at the S1 and S2 loci resulted in the loss of the Oct-1 binding site. A study of adenovirus replication in an in vitro experiment showed that Oct-1 can promote DNA replication because translation of the adenovirus-related protein was interrupted after Oct-1 was deleted (Rosenfeld, 1991). Mammary gland cells cannot secrete PRL normally after deletion of the Oct-1 binding site from the mouse β-casein gene or injection of antiOct-1 protein (Xu et al., 2014; Kim and Peterson, 1995). A mutation in the Oct-1 binding site also significantly reduced the transcription and expression of the mouse β-casein gene (Dong et al., 2009; Dong and Zhao, 2007; Saito and Oka, 1996), thereby indicating that the Oct-1 transcriptional factor plays an important role in cell proliferation and stimulating the expression of specific genes. We suggest that the SNPs found in this experiment cause the deletion of the Oct-1 binding site to affect the transcription and expression of the ghrelin gene, thereby affecting the growth of individuals with genotype CC and their leading to their death due to abnormal development. A haplotype comprises an allele with two or more SNPs located on the same chromosome, where it contains linked and disequilibrium information. The interaction among multiple mutant loci may be greater than the effect of a single locus, so there might be more significant effects on the related traits (Daly et al., 2001; Akey et al., 2001; Morris and Kaplan, 2002; Epstein and Satten, 2003), as shown by strong correlations between the analyzed loci and traits (Clark, 2004). We conducted correlation analysis between the two SNPs in the largemouth bass ghrelin gene and growth traits using single locus analysis and haplotype analysis. The results showed that there were significant differences in only 1
2 growth traits among the different genotypes at a single locus, but there were significant differences in four growth indexes, i.e., body weight, body width, total length, and body height, between the D1 diplotype and the D3 and D4 diplotypes. From a breeding viewpoint, the dominant D1 genotype should be selected, whereas the D3 and D4 diplotypes should be eliminated.

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5.10 SNP DETECTION OF HIGH-DENSITY LIPOPROTEIN BINDING PROTEIN GENE AND ITS CORRELATIONS WITH GROWTH TRAITS IN LARGEMOUTH BASS High-density lipoprotein (HDL) binding protein (HBP) exists widely in fibroblasts, aortic endothelial cells, and liver cells, which can bind to HDL and apolipoprotein AI (apoAI), and participate in lipid transport in cells (McKnight et al., 1992; Kumagai et al., 2007). Chen et al. (2003) reported that HBP gene can regulate the transfer of lipids and affect lipid intake efficiency of D. rerio. As an important energy source, lipid provides energy and essential fatty acids for fishes, especially for carnivorous fishes with low utilization efficiency of carbohydrates. However, too much fat in food will not only cause fatty liver disease in fishes, but also retard the growth of fishes (Liang and Qian, 2007; Tu et al., 2012). Studies have shown that high fat content in feed is not conducive to the growth of Cyprinus longipectoralis, Lates calcarifer, and Leiocassis longirostris Gunther (Tu et al., 2012; Williams et al., 2003; Pei et al., 2004). Moreover, the mutation of lipid metabolismrelated genes in fishes will affect lipid metabolism and the growth of fish (Li et al., 2012c). Considering the important role of HBP in the transfer and metabolism of lipids, the mutation of HBP gene may affect the digestion and absorption of fat by fishes, thus exerting an effect on the growth of fishes. Largemouth bass, also known as black bass, green bass, and bucketmouth, is an important economic freshwater fish species with excellent meat quality, rapid growth, and extensive thermal adaptability (Li et al., 2007). In previous studies, good results have been achieved in the breeding of high-quality largemouth bass varieties, and new varieties with high growth vigor were obtained (Fan et al., 2012). In order to further shorten the breeding cycle and enhance the selection efficiency, growth traits of largemouth bass can be improved with a molecular marker
assisted selection method. In this study, using HBP gene as a candidate gene for growth traits of largemouth bass, the SNP of HBP gene was detected by direct sequencing, and its correlations with growth traits were analyzed, aiming at obtaining SNP markers correlated with body weight, body length, and other growth traits of largemouth bass, which provided candidate markers for subsequent molecular marker
assisted selection of largemouth bass.

5.10.1 Materials and Methods 5.10.1.1 Materials Samples for screening SNP loci were collected from largemouth bass (M. salmoides) in the aquatic breeding base of Pearl River Fisheries

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Research Institute. Fins of 20 fish were collected and preserved at 220˚C in absolute ethanol. Largemouth bass samples were collected from Jinhui farm of Jiujiang town, Foshan city, Guangdong Province. In December 2011, about 500 parent fish were cultivated and bred in a 800 m2 concrete pond. On April 15, 2012, a total of one million fertilized eggs were collected and hatched in a 10 m2 concrete pond. After hatching, about 60,000 largemouth bass fries were reared in a 5336 m2 pond. In December 2012, 165 adult largemouth bass were randomly selected from the pond to measure the body weight, total length, body length, body height, caudal peduncle length and caudal peduncle height. In addition, tail fins were cut off and preserved at 220˚C in ethanol. 5.10.1.2 Screening of SNP Loci Genomic DNA was extracted using 96-well Tissue DNA Extraction Kit (Guangzhou Xinyan Biotechnology Co., Ltd.). Primers were designed according to the sequences of HBP gene (GenBank accession number: KF652241): F: 50 -CGCTGAATATAACTCTTACAAGACG-30 ; R: 50 -AGCGAGTGCTGGATGAGAGAGTGA-30 The designed primers were synthesized by Guangzhou Jige Biotechnology Co., Ltd. The total PCR reaction volume was 20 μL, containing 50 ng of template DNA, 10 μL of 2 3 Taq PCR master mix, and 0.5 μL of each of upstream and downstream primers (20 pmol/μL); ddH2O was added to a final volume of 20 μL. The PCR amplification was started with initial denaturation at 94˚C for 3 min, followed by 30 cycles of denaturation at 94˚C for 30 s, annealing at 61.3˚C for 30 s, and extension at 72˚C for 30 s; the amplification was completed by holding the reaction mixture at 72˚C for 7 min to allow complete extension of PCR products. PCR products were stored at 4˚C and detected by using electrophoresis on 1.5% agarose gel. The amplified fragment was sequenced by Shanghai Boshang Biotechnology Co., Ltd. The sequencing results were aligned using Bio Edit software to screen SNP loci. 5.10.1.3 SNP Genotyping by SnaPshot Assay The sequence information of fin DNA of 165 largemouth bass samples and three obtained SNP loci was collected for SNP genotyping with SnaPshot method by Shanghai Generay Biological Engineering Co., Ltd. According to the sequence information of three SNP loci, primers were

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designed using primer 5 software (synthesized by Shanghai Generay Biological Engineering Co., Ltd.) for multiplex PCR amplification; 3 μL of PCR products were purified by ExoI and FastAP to remove the remaining primers and dNTPs in PCR products, respectively; according to the introductions of SnaPshot Multiplex Kit (ABI Corporation), PCR products were purified for extension reaction and detected using ABI 3730XL sequencer; 1 μL of extension products were added with 8 μL of loading buffer, denatured at 95˚C for 3 min and placed into an ice-water bath immediately. 5.10.1.4 Statistical Analysis Correlation analysis was performed with multivariate analysis module of GLM using SPSS17 software, with body weight, total length, body length, body height, caudal peduncle length, and caudal peduncle height as dependent variables, with different genotypes at the screened SNP loci as independent variables. The established model was Yij 5 μ 1 Bi 1 eij, where Yij indicates the observed value of the ith marker of the trait in the jth individual; μ indicates the average of all individuals observed (overall average); Bi indicates the effect value of the ith marker; and eij indicates the random residual effect of the observed value of corresponding individual.

5.10.2 Results and Analysis 5.10.2.1 Acquisition and Analysis of SNP Loci of Partial HBP Sequence After PCR amplification, a 639 bp fragment was obtained and sequenced. The sequencing results were aligned, and three SNP loci were obtained. As shown in Fig. 5.12, three SNP loci were located in the 30 untranslated region; the first base of start codon ATG was denoted as 1, three SNP loci were named H1(G 1 2782T), H2(T 1 2817C), and H3(G 1 2857A), respectively. 5.10.2.2 Genetic Structure Analysis of SNP Loci of HBP Gene in Populations SNP loci in 165 largemouth bass individuals were genotyped by SnaPshot assay. The results of SNP genotyping were analyzed using Popgene32 software, and genetic parameters of three SNP mutation loci were obtained. As shown in Table 5.36, genetic PIC of H1, H2, and H3 was 0.3701, 0.3701, and 0.3648, respectively. PIC ranging between 0.25 and

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Figure 5.12 Sequence alignment of HBP gene in 20 individuals. Note: The shaded sequences represent different base mutations at three loci. HBP, high-density lipoprotein-binding protein.

Table 5.36 Genetic diversity at three SNP loci of HBP gene Locus

Effective

Expected

Observed

Polymorphism

Hardy
Weinberg

number

heterozygosity

heterozygosity

information

equilibrium

content

of alleles

H1 H2 H3

Ne

He

Ho

PIC

1.9619 1.9619 1.9231

0.4918 0.4918 0.4815

0.4970 0.4970 0.5333

0.3701 0.3701 0.3648

0.8917 0.8917 0.1650

PIC, polymorphism information content.

0.5 indicated moderately polymorphic; therefore, all the three polymorphic loci (H1, H2, and H3) belonged to moderately polymorphic loci and were in Hardy
Weinberg equilibrium state. Statistics of genotype and gene frequency at three SNP loci in largemouth bass were shown in Table 5.37. Base G at locus H1 and base T at locus H2 were linked, forming haplotype A; base T at locus H1 and base C at locus H2 were linked, forming haplotype B; loci H1 and H2 formed genotypes AA, AB, and BB; locus H3 consisted of base combinations AA, AG, and GG, which were named genotypes AA, AB, and BB, respectively. 5.10.2.3 Analysis of Correlations Between Loci H1, H2, and H3 of HBP Gene and Various Growth Traits Correlation analysis was performed using GLM. The correlations between loci H1, H2, and H3 of HBP gene and various growth traits

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Table 5.37 Genotype and gene frequency at three SNP loci in largemouth bass Locus Total sample N/Genotype frequency (%) Gene frequency (%) number AA AB BB A B

H1H2 H3

165 165

30/18.18 22/13.33

82/49.70 88/53.33

53/32.12 55/33.33

0.4303 0. 4000

0.5697 0. 6000

were shown in Table 5.38. To be specific, loci H1 and H2 formed three genotypes, namely AA, AB, and BB. The average phenotypic value of six growth traits (body weight, total length, body length, body height, caudal peduncle length, and caudal peduncle height) of largemouth bass individuals with BB genotype was higher than that of individuals with AB genotype and AA genotype; largemouth bass individuals with BB genotype and AB genotype varied significantly in body weight and total length (P , 0.05), while largemouth bass individuals with AA genotype exhibited no significant differences in the average phenotypic value of various growth traits compared with individuals with AB genotype and BB genotype (P . 0.05); largemouth bass individuals with different genotypes at H3 locus exhibited no significant differences in various growth traits (P . 0.05). Loci H1, H2, and H3 formed six diplotypes, including D1 (GG, TT, and GG), D2 (TT, CC, and GG), D3 (TT, CC, and AA), D4 (GT, CT, and AG), D5 (GT, CT, and GG), and D6 (TT, CC, and AG). The correlations between different diplotypes of HBP gene and various growth traits were shown in Table 5.39. Specifically, body weight and total length of largemouth bass individuals with diplotype D4 were significantly higher than that of individuals with diplotype D6 (P , 0.05); overall, body weight, total length, body length, body height, caudal peduncle length, and caudal peduncle height of largemouth bass individuals with dominant diplotype D6 were superior to other diplotypes. Haplotype analysis is a common correlation analysis and linkage disequilibrium analysis method to solve the issues of low locus detection and statistical efficiency in single marker analysis, which can truly reflect the relevance between the analyzed loci and traits (Daly et al., 2001; Zhang and Li, 2007). Four SNP loci were found in IGF-II gene of largemouth bass (M. salmoides). The results of correlation analysis between single locus and growth traits show that there are no significant differences. The results of haplotype analysis indicate that the diplotypes H1H3 and H1H5 vary significantly compared with other diplotypes (P , 0.05)

Table 5.38 Correlations between different genotypes at SNP loci of HBP gene and various growth traits SNP Genotype Sample Body weight (g) Total length Body length Body locus number (cm) (cm) height (cm)

H1H2

H3

AA(GGTT) AB(GTCT) BB(TTCC) AA AB BB

473.97 6 20.34ab 467.71 6 12.30a 513.32 6 15.30b 500.50 6 24.12 479.65 6 12.06 482.86 6 15.27

30 82 53 22 88 55

29.82 6 0.44ab 29.80 6 0.27a 30.68 6 0.33b 30.37 6 0.52 29.98 6 0.26 30.11 6 0.33

26.49 6 0.40 26.24 6 0.24 26.69 6 0.30 26.50 6 0.47 26.36 6 0.24 26.51 6 0.30

8.57 6 0.16 8.59 6 0.10 8.85 6 0.12 8.79 6 0.20 8.60 6 0.10 8.70 6 0.12

Caudal peduncle length (cm)

Caudal peduncle height (cm)

5.32 6 0.13 5.20 6 0.08 5.42 6 0.10 5.45 6 0.15 5.24 6 0.08 5.31 6 0.10

3.42 6 0.08 3.41 6 0.05 3.54 6 0.06 3.52 6 0.10 3.42 6 0.05 3.49 6 0.06

Note: Data in the table are means 6 standard error. Different letters in the same column indicate significant differences (P , 0.05). SNP, single nucleotide polymorphism.

Table 5.39 Correlations between different diplotypes of HBP gene and various growth traits Diplotype SNP locus Sample Body weight (g) Total length Body length number (cm) (cm) H1 H2 H3

D1 D2 D3 D4 D5 D6

GG TT TT GT CT TT

TT CC CC CT CT CC

GG GG AA AG GG AG

30 5 22 62 20 26

473.97 6 20.45ab 520.80 6 50.10ab 500.50 6 23.88ab 461.58 6 14.23a 486.70 6 25.05ab 522.73 6 21.97b

29.82 6 0.44ab 31.32 6 1.08ab 30.37 6 0.52ab 29.64 6 0.31a 30.26 6 0.54ab 30.81 6 0.47b

26.49 6 0.40 26.80 6 0.99 26.50 6 0.47 26.16 6 0.28 26.47 6 0.50 26.84 6 0.43

Body height (cm)

Caudal peduncle length (cm)

Caudal peduncle height (cm)

8.57 6 0.17 9.26 6 0.41 8.79 6 0.19 8.51 6 0.12 8.77 6 0.20 8.82 6 0.18

5.32 6 0.13 5.20 6 0.32 5.45 6 0.15 5.16 6 0.09 5.32 6 0.16 5.44 6 0.14

3.42 6 0.08 3.69 6 0.20 3.52 6 0.10 3.37 6 0.06 3.55 6 0.10 3.54 6 0.09

Note: Data in the table are means 6 standard error. Different letters in the same column indicate significant differences (P , 0.05). SNP, single nucleotide polymorphism.

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(Li et al., 2012b). MC4R gene in tilapia (O. niloticus) and MSTN gene in largemouth bass were investigated by haplotype analysis, and several markers correlated with growth traits were obtained (Liu et al., 2009; Yu et al., 2010). In this study, three SNP markers of HBP gene and their correlations with various growth traits in largemouth bass were investigated with single locus analysis and haplotype analysis methods. Different genotypes at a single locus and growth traits exhibit no significant differences; haplotype analysis results indicate that different genotypes and growth traits exhibit significant differences (P , 0.05), and the effects of candidate markers on growth traits are improved with the increase of locus number, which may be due to the interactions between different SNPs; specifically, the interactions between multiple mutation loci may be greater than that of a single locus. Three SNPs screened in the present study were located in the 30 noncoding region of HBP gene. Their correlations with various growth traits were analyzed, and the results show that these three SNPs exhibit certain effects on the growth traits. The 30 noncoding region of mRNA does not encode amino acids, but plays an important role in the regulation of gene expression. The 30 regulatory region can not only regulate the stability, degradation rate, and utilization efficiency of mRNA, but also plays a guiding role in the encoding process of specific amino acids (Wang et al., 2008b). Wang et al. (2013) found that 30 UTR of SR-BI gene significantly affects the stability of mRNA (P , 0.05), which is the key to the regulation of post-transcriptional level of SR-BI gene. Base mutations or deletions in the 30 noncoding region of functional genes can affect normal splicing, thereby leading to changes in gene expression level or even loss of function (Kambadur et al., 1997). Two SNP loci were found in the 30 noncoding region of apolipoprotein A-I-1 gene in grass carp, which formed diplotypes D3 and D6 that exhibit significant differences (P , 0.05) in body length, body height, and head length, while diplotype D3 can be used as a candidate marker for molecular marker
assisted selection of grass carp (Liu et al., 2012). Moreover, studies have shown that SNPs in the 30 regulatory region of different genes in other animals also have an impact on gene function, resulting in differences in traits (Gu et al., 2002; Jiang et al., 2001). In this study, the polymorphism of the 30 noncoding region of HBP gene leads to significantly higher body weight and total length of genotype BB formed by loci H1 and H2 than those of genotype AB (P , 0.05); diplotype D6 formed by loci H1, H2, and H3 exhibited significantly higher body weight and total length than diplotype D4 (P , 0.05).

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Studies have shown that both homozygous and heterozygous genotypes can become inferior genotypes. For instance, correlation analysis of the polymorphism of five SNP loci of GH receptor genes in C. carpio var. Jian with growth traits indicates that the polymorphism of five SNP loci is significantly correlated with weight gain (P , 0.05), and the five genotypes for rapid weight gain include one heterozygous genotype and four homozygous genotypes (Tao et al., 2011). Correlation analysis of SNP loci in the fourth intron of IGF-I gene in C. carpio var. Jian with weight gain also confirms that the inferior genotypes are heterozygous (Li et al., 2012b). In the present study, correlation analysis suggests that heterozygous genotype AB formed by loci H1 and H2 is an inferior genotype. It is speculated that two alleles exhibit mutual inhibition, thereby resulting in lower body weight and total length of heterozygous genotypes than homozygous genotypes. A large number of studies have confirmed that HBP gene plays a critical role in lipid metabolism. Katoh et al. (2001) reported that HBP specifically binding to apoAI as a ligand can regulate the process of lipid transport in eel (Anguilla japonica). Chen et al. (1997) found that HBP gene plays an important role in energy accumulation and lipid transfer in zebra fish (D. rerio). Therefore, it is inferred that HBP mutations will affect the utilization of lipids by largemouth bass, thus exerting a certain effect on the growth traits of largemouth bass.

5.11 SNP DETECTION IN PACAP AND THE ASSOCIATION WITH GROWTH TRAITS IN LARGEMOUTH BASS PACAP is a pleiotropic hormone in fish that not only stimulates and enhances the secretion of GH, gonadotropin, PRL, and somatolactin (Montero et al.,1998; Matsuda et al., 2008), but also is involved in the regulation of food intake (Nakata et al., 2004) and feeding behavior (Yue et al., 2008; Mukai et al., 2006; Piqueras et al., 2004). PACAP was first discovered in the hypothalamus of sheep (Ovis aries) (Miyata et al., 1989), and was mainly present in the central nervous system. PACAP could significantly reduce the intake of Gallus domesticus (Tachibana et al., 2003). After intracerebroventricular injection of PACAP, the food intake and activity of Mus musculus and C. auratus were significantly decreased (Money et al., 1992; Matsuda et al., 2006). It was found that in mice with PACAP deficiency, body weight in response to a high carbohydrate dietary (51%) intake was significantly affected, indicating that PACAP

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could affect carbohydrate absorption (Nakata et al., 2004) and thereby influence growth. PACAP is an effective GH releasing factor, and recombinant PACAP peptide could improve the growth rate of fish, such as carp (C. carpio) (Lugo et al., 2008) and grouper (Epinephelus coioides) (Jiang et al., 2005). PACAP plays an important role in the growth and feeding of animals. Association studies of PACAP polymorphism and growth traits were carried out to find the molecular markers related to growth. SNPs found in the introns of the PACAP gene of Qinchuan cattle (Bos taurus) were significantly associated with body length, body depth, body weight, and other growth traits (Hao et al., 2010). The mutation C1049A in PACAP gene of Huainan partridge chicken (G. domesticus) had a significant effect on the egg laying performance of the chicken, egg weight, and protein content of 30-week-old chickens, with the AA genotype significantly higher than the CC genotype (Li et al., 2015a). SNPs in the PACAP gene of tilapia (Oreochromis spp) were significantly related to fish body weight, total length, and other growth traits (Zou et al., 2015). In view of the influence of SNPs in the PACAP gene on animal growth traits, it was speculated that the gene mutation could affect the intake of the largemouth bass and influence its growth. PACAP was used as a candidate gene in this study to explore the association between its polymorphism and growth traits, in order to obtain SNP markers associated with growth traits of the largemouth bass and provide data for molecular marker
assisted breeding selection.

5.11.1 Materials and Methods 5.11.1.1 Materials In this experiment, a largemouth bass population from an 8-month artificial culture grown in the same pond was obtained from Liyang Aquatic Co. Ltd. in Yangshan county in Qingyuan city, Guangdong. In all, 327 fish were randomly selected from the population and the growth data, such as body weight, total length, body width, body depth, of each fish were measured for the correlation analysis of growth traits. DNA extracted from the fin was used for typing. Twelve extremely large individuals with an average body weight of 480 g and 12 extremely small individuals with an average body weight of 320 g were selected from the 327 fishes for SNP detection. A DNA extraction kit was purchased from TianGen Biotech Co. Ltd. (Beijing, China); 2 3 Taq PCR master mix was purchased from Takara Biotechnology Co Ltd. (Dalian, China);

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primers were synthesized by Jige Biotechnology Co. Ltd. (Guangzhou, China); DNA molecular weight standards were purchased from Whiga Biotechnology Co. Ltd. (Guangzhou, China), and low melting point agarose was purchased from Sigma-Aldrich (St. Louis, MO, USA). 5.11.1.2 Extraction of Genomic DNA The extraction of genomic DNA from the largemouth bass fin was carried out according to the DNA extraction kit instructions. DNA was finally dissolved in TE buffer solution and its purity and concentration were determined. DNA was stored at 220˚C for further experiments. 5.11.1.3 PCR Amplification of the PACAP Gene Primer designs were based on the PACAP gene sequence of largemouth bass cloned in our laboratory (GenBank accession number: HQ640681.1) using Primer Premier 5.0, five pairs of primers were designed. Primer sequences and parameters are listed in Table 5.40. The PCR reaction system for amplification included 10 μL 2 3 Taq PCR master mix, 0.5 μL (20 μmol/L) upstream/downstream primer, 20 ng template DNA, and ddH2O to a volume of 20 μL. The PCR reaction procedure was pre-denaturation at 94˚C for 10 min, followed by 35 Table 5.40 Primers used to amplify PACAP from largemouth bass Primer Sequence Amplified fragment size (bp)

PF1

50 -TCTCCCTGCTTCCCTGCCAT-30

688

PR1 PF2

50 -GCCCACATCCAAATCTTCAA-30 50 -AAGATTTGGATGTGGGCACT-30

818 726

PR2

50 -AAGGGAGAACACTCGTCACA-30

620

PF3 PR3 PF4 PR4 PF5 PR5

50 -GATGACAATTCGTGCAGGGT-30 50 -GTAGCTGTCGGTGAAGATCC-30 50 -CTCCGCTACACAAGTCCAGG-30 50 -TCTTTTGGATAAGGGCTCTG-30 50 -ATGGAGGAAGAGTCAGAGCC-30 50 -ACTAACTGTGCGGTATCAAG-30

381

Amplified region

Exon 1, 2 and intron 1, 2 Intron 2 Exon 3, 4 and intron 3, 4 Intron 4 and exon 5 30 flanking sequence

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cycles of denaturation 94˚C for 10 s and 57˚C annealing for 15 s, ending with an extension of 72˚C for 10 min. PCR product was detected in 1.2% agarose gel electrophoresis and preserved at 4˚C. Sequencing results were aligned and SNP loci were selected using BioEdit software. Gene typing for SNP loci in the PACAP gene of 327 largemouth bass individuals was carried out by Shanghai Generay Biotech Co., Ltd. using the SnaPshot method (Zhao et al., 2003). 5.11.1.4 Statistical Analysis of Data Genetic parameters, such as the number of effective alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), and allele frequency were calculated using Popgene 32 (version 3.2). Correlation analysis of typing results with the growth traits of largemouth bass was based on a GLM carried out using SPSS17 software. The dependent variables were morphological characters such as total length, body width, body depth, and body weight, and the independent variables were the different genotypes of two selected SNP loci. The biometric model was Yij 5 μ 1 Bi 1 eij, where Yij represents the observed value of marker i, individual j; and μ represents the average value of all the observed individuals in the experiment; Bi is the effective value of the i marker; and eij is the random residual effect of the corresponding individual observed value.

5.11.2 Results and Analysis 5.11.2.1 Screening for the PACAP Gene Mutation Loci The amplified fragments with lengths of 688, 820, 725, 620, and 381 bp were obtained by PCR using five pairs of primers. After sequencing and alignment, one SNP locus A-2282C located in intron 4 of PACAP was detected in the fragment amplified using primer PF3 and PR3. Among the 24 samples, there were 14 mutation loci with base C and 10 mutation loci with base A. The mutation loci and the adjacent sequences are shown in Fig. 5.13. The largemouth bass PACAP gene with a length of 3232 bp was analyzed for SNPs in this study. However, only a single SNP locus was found in intron 4, which was equivalent to 0.31 SNPs per thousand bases. This density was much less than that screened in the HBP gene, IGF-I gene, and MyoD gene (Li et al., 2009b; Yu et al., 2009). The SNP density in these genes was 4.69/1000, 1.76/1000, and 4.48/1000 bp, respectively. It was found that the mutation rate of PACAP was also low with only one or two SNP mutation loci when analyzing polymorphisms in tilapia, Huainan partridge chicken, Qingyuan partridge chicken, and Qinchuan

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Figure 5.13 Partial sequence alignment around the mutation in PACAP (the shaded bases represent the mutation site). PACAP, pituitary adenylate cyclase-activating polypeptide.

cattle. It was suggested that PACAP was relatively conserved in evolution and mutations and might have a greater effect on function. 5.11.2.2 Genetic Structure Analysis of SNP Loci Mutations in PACAP Typing of SNP loci in PACAP of 327 largemouth bass individuals was carried out using SnaPshot technology. The results were analyzed by Popgene 32 software and some genetic parameters of SNP loci mutations were obtained. The experimental population was in HWE equilibrium at that mutation loci. Effective alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), and polymorphic information content were 1.8465, 0.5409, 0.6442, and 0.3533, respectively. Three genotypes, AA, AC, and CC, were found at locus A-2282 with a frequency of 0.034 (11/ 327), 0.645(211/327), and 0.321(105/327), respectively. The gene frequency of allele A was 0.3558 and that of allele C was 0.6442. 5.11.2.3 Correlation Analysis of the A2282 Locus and Growth Traits The correlations between different genotypes of PACAP A-2282C and morphological characters, i.e., body weight, body width, total length, head length, body depth, and caudal peduncle length, were analyzed using GLM and the results are shown in Table 5.41. The average body

Table 5.41 Genotype of the SNP and its correlation of PACAP genotypes with growth traits SNP site Genotype Number Body weight (g) Body width Total length (cm) (cm)

A-2282C

AA AC CC

11 211 105

341.18 6 29.76a 445.50 6 10.19b 403.03 6 14.44a

3.79 6 0.16a 4.16 6 0.04b 4.04 6 0.05

26.48 6 0.86a 28.69 6 0.20b 27.92 6 0.28a

Head length (cm)

Body depth (cm)

Caudal peduncle length (cm)

6.63 6 0.29 7.42 6 0.10 7.26 6 0.14

7.81 6 0.36a 8.65 6 0.08b 8.26 6 0.12a

8.02 6 0.31a 8.71 6 0.07b 8.49 6 0.10

The data are X 6 SE, superscripts within the same column indicate significant differences, P , 0.05. SNP, single nucleotide polymorphism.

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weight, body depth, and total length of the population with an AC genotype were increased by 30.6%, 10.7%, and 8.3%, respectively, compared with those of the population with an AA genotype, and were increased by 10.5%, 4.7%, and 2.7%, respectively, compared with those of the population with a CC genotype. The body weight, body depth, and total length of the population with an AC genotype were significantly higher than those of populations with AA and CC genotypes (P , 0.05). The body width and caudal peduncle of populations with the AC genotype were significantly higher than those of the AA genotype (P , 0.05). In addition, the average body weight, body depth, and total length of populations with the AA genotype were increased by 18.1%, 5.8%, and 5.4%, respectively, compared with the CC genotype population, but there was no significant difference in all the growth traits between populations with AA and CC genotype (P , 0.05). PACAP could be involved in the regulation of vertebrate growth and food intake, studies have shown that SNP in PACAP was significantly associated with growth traits of animals (Hao et al., 2010; Tao and Boulding, 2003; Zou et al., 2015). Although in this study the SNP locus was found in an intron of the largemouth bass PACAP gene, that mutation was significantly associated with growth traits. Introns do not encode amino acids, but they play an important role in the regulation of gene expression. Studies of mammals have found that introns that are downstream of termination codons could cause the termination codons under immature status to be recognized, and thereby mediate mRNA degradation to influence gene expression (Maquat, 2004). Introns not only have positive regulating abilities to enhance gene expression, regulate variable shear, improve transcription and translation efficiency, and regulate the initiation of transcription (Lu and Cullen, 2003; Xie and Wu, 2001; Chang, 2000; Wang et al., 2004), but also have negative regulating effects that hinder gene transcription (Ding et al., 2006). The results of Klett and Bonner (1999) indicated that partial mutation in introns might change the expression activity of genes and thereby affect their biological functions. The SNPs associated with growth traits found in PACAP of B. taurus, Salvelinus leucomaenis, and G. domesticus were also located in intron regions (Hao et al., 2010; Tao and Boulding, 2003; Li et al., 2015a). It is proposed that mutations in the PACAP intron of largemouth bass change the translation efficiency or expression of the gene, and thereby affect growth traits.

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5.12 POLYMORPHISM OF APOLIPOPROTEIN GENES AND ITS CORRELATION WITH GROWTH TRAITS IN LARGEMOUTH BASS Apo is an important component of plasma lipoproteins and has the function of promoting lipid transport, regulating enzyme activity, and guiding the binding of plasma lipoproteins to the receptor. The Apo gene cluster is a region which has been studied relatively well and found to be closely related to lipoprotein metabolism (Swaney et al., 1974; Steinmetz and Utermann, 1985; Trang et al., 2016). The largemouth bass is a carnivorous fish that mainly uses protein and fat as a source of energy, its ability to use carbohydrates is low (Bai and Li, 2013). Fat is a very important source of energy in the development of largemouth bass artificial formula feed. In view of the role of Apo in regulating the fat absorption process, mutations in the Apo gene may affect the lipid absorption of largemouth bass and its growth and metabolism. In this section, the Apo gene cluster was used as a candidate gene, SNPs were screened and correlation analysis of growth traits was carried out in order to obtain SNPs related to lipid metabolism of largemouth bass.

5.12.1 Materials and Methods 5.12.1.1 Sample Source Twenty adult largemouth bass were obtained from the productive base of Pearl River Fisheries Research Institute for SNP screening. 159 individuals of largemouth bass with average weight of about 500 g that were bred in the same batch and same pond in the Nanhai district of Foshan city, Guangzhou were selected and used for correlation analysis, and the fins of fish were cut and preserved in absolute alcohol. 5.12.1.2 Primer Design According to functional annotation of the EST sequence with putative SNPs in the cDNA library of sequenced largemouth bass transcriptom (Jing et al., 2012), the primers were designed using Primer Premier 5.0 for PCR amplification of Apo genes (Table 5.42). 5.12.1.3 Screening and Typing of SNP Loci Genomic DNA of 20 largemouth bass individuals was used for PCR amplification. PCR products were detected by 1.2% agarose gel electrophoresis, and sent to Shanghai Invitrogen Biotechnique Co. Ltd. for

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Table 5.42 Primers used for amplicfication of Apo gene in largemouth bass Annealing Object Primer Nucleotide constitutes Length temperature gene of products

P1 P2 P3

AATCAAGACCACCCTAACTG TTAGACAGAGGTTCAGGCAC TGAGGTGGAGGTTGGCTTAT GCCCAGCAGGTGAAAGAA AAAACAGAGTCACAGCCAAGA GTGATGGTGGTGGTAGGC

903

55

ApoA1

239

55

ApoA4

452

55

ApoC1

sequencing. The sequences obtained were aligned and analyzed using Vector NTI Suite 8.0. DNA was extracted from fins of 159 largemouth bass individuals and used for SNP typing by Shanghai Generay Biotech Co. Ltd. with the SnaPshot method. 5.12.1.4 Statistical Analysis Allele frequency was calculated using Popgene (version 3.2) software, and the least squares analysis was performed on the correlation between genotypes at different SNPs loci and major growth traits of largemouth bass. The biometric model was Yij 5 μ 1 Bi 1 eij, where Yij represents the observed value of marker i of individual j; μ represents the average value of all the observed individuals in the experiment; Bi was the effective value of the i marker; and eij was the random residual effect of the observed value.

5.12.2 Results and Analysis 5.12.2.1 SNPs Loci in Apo Gene Three pairs of primers (P1, P2, and P3) were used for amplifying ApoA1, ApoA4, and ApoC1. Three fragments of the expected size were obtained with the length of 903, 239, and 452 bp, respectively. Four SNP loci were detected by sequence alignment. One SNP locus A 1 489C was obtained in ApoA1, which was located at 490 bp from the start codon ATG in coding sequence (CDS) region. The codon was changed from CCA to CCC and both codons encoded proline (P), therefore it was a synonymous mutation. One SNP locus A 1 633T was obtained in ApoA4, which was located at 634 bp from the start codon. The codon was changed from TCA to ACA and therefore encode serine (S) and threonine (T), respectively, which is a missense mutation. Two SNP loci

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A 1 24G and A 1 75C detected in ApoC1 were located at 24 and 75 bp in the CDS, respectively. The mutation types were GCA to GCG and ATA to ATC, and these codons encoded alanine (A) and isoleucine (I), consequently, both mutations were synonymous. 5.12.2.2 Genetic Diversity Analysis of Four SNP Loci The same genotype and allele frequency were found in the mutation sites of three loci (Table 5.43), A 1 633T, A 1 24G, and A 1 75C through SNP typing of 159 largemouth bass individuals. These results suggested that the three SNPs were complete linked and ApoC1 and ApoA4 might be on the same chromosome and were adjacent to each other. Genetic diversity analysis was carried out on four SNP loci of 159 largemouth bass individuals. The genetic parameters obtained by SnaPshot typing and the Popgene process are shown in Table 5.44. A locus is highly polymorphic when PIC .0.5, has moderate polymorphism when PIC , 0.5, and has low polymorphism when PIC ,0.25. Based on the rule described above, all four loci were moderately polymorphic and in a state of HWE (P . 0.05). Table 5.43 Genotype and allele frequency of four SNP sites in largemouth bass population Locus Genotype frequency (%) Allele frequency (%)

A 1 489C A 1 633T A 1 24G A 1 75C

AA 32.08 AA 34.59 GG 34.59 AA 34.59

AC 54.09 AT 52.20 AG 52.20 AC 52.20

CC 13.84 TT 13.21 AA 13.21 CC 13.21

A 0.59 A 0.61 G 0.61 A 0.61

C 0.41 T 0.39 A 0.39 C 0.39

Table 5.44 Polymorphic parameters for four SNPs sites in different apolipoprotein genes SNP locus Ne He Ho PIC HWE (P-value)

A 1 489C A 1 633T A 1 24G A 1 75C Average

1.873 1.941 1.941 1.941 1.924

0.471 0.490 0.490 0.490 0.485

0.478 0.522 0.522 0.522 0.511

0.357 0.367 0.367 0.367 0.365

0.917 0.658 0.658 0.658

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5.12.2.3 Growth Correlation Analysis of Four SNP Loci in Apo The results of correlation analysis (Table 5.45) showed that a significant difference in body weight and body height existed in individuals with type AC and CC at locus A 1 489 (P , 0.05). The total length of all individuals with type AC was longer than individuals with type AA and CC, but the difference was not significant (P . 0.05). The individuals with different genotypes had significant differences for body weight and body high for A 1 489C site in ApoA1 (P , 0.05). The individuals with genotypes AC had a larger value than the individuals with the genotype AA and CC in body height and caudal peduncle length. For site of A 1 633T in ApoA4, the individuals with genotypes AT had a larger value than the individuals with the genotype AA and TT in body height and caudal peduncle length. For sites of A 1 24G and A 1 75C in ApoC1 genes, individuals with different genotypes had significant differences for body weight, body height, or total length (P , 0.05) and the individuals with genotypes AG or AC had major effects on largemouth bass growth traits. Apo plays an important role in lipid metabolism and is involved in the process of synthesis, transport, and metabolism of lipids and cholesterol. Mutations in the Apo gene can possibly influence its function, and polymorphisms in the Apo gene are known to affect the human blood lipid level (Di et al., 2015). Apo gene polymorphism of grass carp also has association with growth traits (Liu et al., 2012). Four SNP loci in the Table 5.45 The correlation analysis between each SNP and growth traits Locus Genotype Body weight Total length Body height

A 1 489C A 1 633T A 1 24G A 1 75C

AA AC CC AA AT TT GG AG AA AA AC CC

478.28 6 17.53ab 502.17 6 13.51a 436.50 6 26.70b 429.57 6 27.13a 507.85 6 13.65b 472.89 6 16.76ab 472.89 6 16.76ab 507.85 6 13.65a 429.57 6 27.13b 429.57 6 27.13a 507.85 6 13.65b 472.89 6 16.76ab

30.16 6 0.36 30.49 6 0.27 29.55 6 0.54 29.24 6 0.55a 30.76 6 0.27b 29.88 6 0.37ab 29.88 6 0.37ab 30.76 6 0.27b 29.24 6 0.55a 29.24 6 0.55a 30.76 6 0.27b 29.88 6 0.37ab

8.68 6 0.13ab 8.86 6 0.10a 8.36 6 0.19b 8.34 6 0.20a 8.89 6 0.10b 8.64 6 0.12ab 8.64 6 0.12ab 8.89 6 0.10b 8.34 6 0.20a 8.34 6 0.20ab 8.89 6 0.10b 8.64 6 0.12ab

Notes: Values with different superscript letters within a column indicates significant difference at P , 0.05.

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largemouth bass Apo gene were all correlated with growth traits, indicating that Apo plays an important role in fish growth and metabolism. The four SNP loci detected were all located on exons, which would have a greater impact on the encoded Apo. Especially as the mutation at locus A 1 633T in ApoA4 was a missense mutation that changed the encoded amino acids from serine into threonine. Although both serine and threonine are uncharged polar hydroxyl amino acids, the amino acid changes could lead to a change of protein structure and function and certainly affect the function of ApoA4. Even though the mutations of three other SNPs in this study (A 1 489C, A 1 24G, and A 1 75C) were synonymous, a large number of studies have shown that synonymous mutations do not cause changes in amino acids encoded by genes but may still affect the synthesis, maturation, transport, and translation of mRNA and ultimately lead to functional changes (Shen et al., 1999). A 1 633 locus in ApoA4 had the same genotype frequency with A 1 24G and A 1 75C loci in ApoC1, suggesting that these SNPs were completely linked and ApoA4 and ApoC1 were located at a close distance on the same chromosome. The results from correlation analysis of growth traits showed that individuals with three heterozygous loci had the best growth traits, and the body weight of individuals with a heterozygous genotype was higher than individuals with a homozygous genotype by 7.39%
18.2%, which might be caused by superdominancy. This phenomenon that the phenotype or physiological function of one allele pair in a heterozygous genotype is superior to that in a homozygous genotype has been observed in livestock species and other fish (Jin et al., 2010; Tao et al., 2011; Li et al., 2012d).

5.13 PYRAMIDING ANALYSIS OF DOMINANT GENOTYPES IN DIFFERENT GENERATION OF YOULU NO.1 LARGEMOUTH BASS The idea of gene pyramiding was first proposed by Yadav et al. (1990) when studying improved disease resistance and stress resistance traits in mustard. More and more researchers began to focus on gene pyramiding studies of quantitative traits with the expectation of accelerated breeding through gene pyramiding selective breeding techniques. Eight growthassociated molecular markers already identified in our laboratory had significant or extremely significant relationships with growth traits. Among those, four loci of SNPs were located in the 50 flanking region of the

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IGF-I gene (Li et al., 2009a), the promoter of the POU1F1 gene (Du et al., 2011), the PSSIII promoter, and the MSTN gene (Yu et al., 2010); meanwhile four microsatellite DNA loci were JZL60, JZL67, MisaTpw76, and MisaTpw117 (Fan et al., 2009). In order to better utilize these markers, it is necessary to explore their pyramiding effect. These eight molecular markers associated with growth traits of largemouth bass were used in this study to analyze the changes of dominant genotypes within selective breeding generations of largemouth bass, with the result potentially providing a theoretical basis for pyramiding selective breeding of markers associated with growth traits.

5.13.1 Materials and Methods 5.13.1.1 Experimental Materials Youlu No.1 largemouth bass were collected from the breeding base of Pearl River Fisheries Research Institute and Jinhui farm in Jiujiang town, Foshan city. Thirty caudal fin tissue samples were randomly selected from each of Youlu No.1 F2, F3, F5, and F6 and preserved, and genomic DNA was extracted. Primers used in PCR reaction of each locus were purchased from Sangon Biotech Co., Ltd. (Shanghai, China). The TIANamp Genomic DNA Kit was purchased from TianGen Biotech Co., Ltd. (Beijing, China). Taq DNA polymerase, buffer, and dNTP were purchased from HuaMei Bioengineering Company. The restriction enzymes TaqI, BsrBI, and AluI were purchased from Fermentas. 5.13.1.2 Extraction of Genomic DNA Total DNA of largemouth bass fin tissue was extracted according to instructions provided with the kit purchased from Tiangen Biotech Co., Ltd. DNA quality and concentration were analyzed by spectrophotometry following 0.8% agarose gel electrophoresis. DNA was stored at 220˚C until use. 5.13.1.3 PCR Amplification Before PCR amplification, primers were labeled using FAM, ROX, or HEX fluorescence. The PCR reaction mixture of 20 μL consisted of 2.0 μL 10 3 buffer, 0.8 μL MgCL2 (25 mmol/L), 0.4 μL dNTP (10 μmol/L), 0.4 μL each upstream/downstream primer (20 μmol/L), 40 ng genomic DNA, and 1 U Taq enzyme (Shanghai Shenneng Bocai Biotechnology Co., Ltd.). The PCR procedure involved pre-denaturation at 94˚C for 4 min, followed by 32 cycles of denaturation at 94˚C for 30 s,

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annealing at 48
63˚C for 30 s and extension at 72˚C for 30 s, then ended with extension at 72˚C for 10 min. 5.13.1.4 Detection of Amplification Product Genotyping of short tandem repeats (STR) was performed by Sangon Biotech Co., Ltd. STR sequence analysis was carried out using DYY-8 type steady flow electrophoresis (Shanghai Qite Analytical Instruments Ltd.), a gel imaging system (Gene Genius Company) and 3730XL sequencer (ABI, Applied Biosystems). The genotype of each locus in each individual fish was determined based on the molecular weight of each amplification band. The genotypes of deleted mutation loci in four microsatellite loci and the IGF-I gene were directly analyzed using STR genotyping techniques; three SNP loci located in POU1F1, PSSIII, and MSTN genes were digested using the restriction enzymes TaqI, BsrBI, and AluI, respectively, before STR genotyping. 5.13.1.5 Statistical Indicators The frequency (p) of the dominant genotype at each locus among each generation of the selective breeding population, as well as the average number and distribution of the dominant genotype in each breeding generation were calculated. The formula used to calculate the dominant genotype number in each generation is shown below: P xi fi P5 P fi where P is the average number of eight dominant genotypes; xi is the frequency of the dominant genotype i; fi is the detection number of largemouth bass corresponding to the dominant genotype i.

5.13.2 Results and Analysis 5.13.2.1 Detection of Molecular Markers of the Dominant Genotype With the progression of selective breeding, among F2, F3, F5, and F6, the number of individuals with two dominant genotypes gradually decreased, while individuals with four dominant genotypes gradually increased (Table 5.46). These results of each dominant genotype frequency showed that, with the exception of the frequency of dominant genotypes in PSSIII and POU1F1, which showed some fluctuation, the frequency of other dominant genotypes gradually increased (Table 5.47).

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Table 5.46 Number of dominant genotypes contained in different individuals in selected breeding generations Generation

F2 F3 F5 F6

Dominant genotype number 0

1

2

3

4

5

6

0 1 0 0

3 4 4 1

20 14 10 9

6 9 9 12

1 2 7 5

0 0 0 2

0 0 0 1

Table 5.47 Frequency of dominant genotypes in each generation of Youlu No.1 largemouth bass F2 F3 F5 F6

MisaTpw76

MisaTpw117

IGF-I

PSSIII

POU1F1

JZL67

MSTN

JZL60

Total

0 0.069 0.120 0.200

0.043 0.321 0.353 0.300

0 0.067 0.133 0.067

1.000 0.897 0.862 1.000

0.900 1.000 0.833 0.777

0.033 0.133 0.185 0.133

0.038 0.071 0.267 0.333

0.143 0.143 0.143 0.267

2.157 2.701 2.896 3.077

IGF-I, insulin-like growth factor-I; PSSIII, preprosomatostatin; POU1F1, pituitary-specific transcription factor 1; MSTN, myostatin.

5.13.2.2 Number and Distribution of Dominant Genotypes in Each Generation An average of eight dominant genotypes in each generation was obtained based on quantity statistical analysis of each dominant genotype among F2, F3, F5, and F6 of Youlu No.1 largemouth bass. The results showed that dominant genotype number gradually increased from F2 to F5, indicating that traditional selective breeding caused pyramiding of dominant genotypes, but the pyramiding rate of dominant genotypes gradually decreased (Table 5.48). In other words, with the increase in the growth rate of F2, F3, F5, and F6, the average number of dominant genotypes was also simultaneously increased. To date there have been few reports on the differences in contribution rate of different genes in gene pyramiding. This study found growthassociated dominant genotypes with relatively large contributions to growth in gene pyramiding of largemouth bass. The result of eight growth-associated dominant genotypes showed that the occurrence frequency of dominant genotypes at the SNP locus and the MisaTpw76 locus in the MSTN gene increased with the acceleration of Youlu No.1 largemouth bass from generation to generation; while the frequency of the other six dominant genotypes sometimes increased, but sometimes

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Table 5.48 Average number of dominant genotypes in each generation of Youlu No.1 largemouth bass Generation F2 F3 F5 F6

Number of dominant genotypes

2.12

2.70

2.90

3.08

reduced or remained unchanged in the selective breeding process. From F2 to F3, the dominant genotype frequency of the SNP locus and the JZL60 locus in the PSSIII gene did not increase, while that of all the other loci increased to some extent. From F3 to F5, dominant genotype frequency of all other loci increased except for that of the SNP locus and JZL60 locus in the PSSIII gene and the POUIFI gene; from F5 to F6, the dominant genotype frequency of all the SNP, MisaTpw117 and JZL67 loci in the IGF-I gene. and the POUIFI gene decreased, while that of all the other loci increased. From F2 to F6, among the eight markers, only the dominant genotype frequency of the MisaTpw76 and SNP loci located in the MSTN gene gradually increased, indicating that the effect of the two markers on growth traits was obvious. The result of the previous studies in our laboratory showed that: the average weight of individuals with dominant genotypes at the MisaTpw76 locus and located in the MSTN gene was higher than that of individuals with other genotypes by 46.18% (Fan et al., 2009) and 53.24% (Yu et al., 2010), respectively; the average body weight of individuals with dominant genotypes in each of other six markers was 16.86%
35.84% higher than that of individuals with other genotypes (Li et al., 2009a; Yu et al., 2010; Du et al., 2011); the result obtained in this study was similar to previous studies. When eight growth markers were used to assist with selection of parent fish, dominant genotypes at the SNP located in the MSTN gene and MisaTpw76 loci had a better selection effect than those of the other six molecular markers and should be used as the primary markers for parent fish screening in the future, in order to improve the growth traits of largemouth bass. At present, the study of growth traits and growth-associated gene pyramiding mostly use two or three loci. This study explored the relationship between growth traits and multiple growth-associated dominant genotypes, which has rarely been studied in aquatic animals. The result showed that with progress in the breeding generation of Youlu No.1 largemouth bass, the average number of dominant genotypes increased from generation to generation, which was consistent with the phenomenon of

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the growth rate increasing with the generations, indicating that traditional selective breeding using morphology and weight as indicators also resulted in pyramiding of dominant genotypes. This study found that the number of dominant genotypes increased from F2 to F3, from F3 to F5, and from F5 to F6 by 0.58, 0.2, and 0.18, respectively. The increasing amplitude gradually decreased, which was consistent with the observation that target traits of a breeding population gradually tend to stabilize. Theoretically, artificial selective breeding aims to gradually select and retain some traits, which causes trait-related genotype frequency to increase. With the increase of breeding generations, the homozygote rate of the gene would rise and selection effectiveness would decrease, changing the amplitude of the phenotype and possibly causing the genotype frequency to decrease to some extent (Yang, 2006), and consequently decrease the amplitude of the dominant genotype number. Li et al. (2012a) carried out a study on three growth-associated loci in the ANGPTL6 gene of Luxi cattle, and found that the increase in the dominant genotype number was synchronized with improvement in the growth traits which could be applied to the molecular breeding practice of Luxi cattle. Zhao et al. (2010) found, in a study of selective breeding generation of large yellow croaker, that the gene frequency of two loci increased regularly with the development of breeding generations, and they speculated that the two loci might show correlations with selected breeding traits. We also found in this study that with the progress of selected breeding generations of Youlu No.1 largemouth bass, the average number of dominant genotypes gradually increased, reflecting the fact that the number of the eight dominant genotype markers chosen in this study in largemouth bass individuals showed a correlation with the growth rate.

5.14 PYRAMIDING WITH GROWTH TRAIT RELATED-MARKERS IN LARGEMOUTH BASS Gene pyramiding is a breeding method to obtain good varieties through carrying out hybridization between different genotypes and pyramiding beneficial genotypes into the same genome (Bertrand et al., 2004). Gene pyramiding has been reported successfully in crops and livestock. For instance, in rice plants the yield was increased by 23% by pyramiding three dominant genotypes of genetic loci associated with a trait for rice spikelet number (Zhang et al., 2004; Motoyuki and Matsuoka, 2006); the body weight of Huai pigs was significantly increased after pyramiding

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three growth-related dominant genotypes compared with other combinations of the genotypes (Tao, 2011); and significantly increased egg laying was obtained in white-ear chickens after pyramiding genotypes related to laying eggs (Li et al., 2010). Studies on Chinese Merino sheep (Zeng et al., 2011) and Sujiang pig (Wang et al., 2007) also showed that the higher the degree of pyramiding dominant genotypes associated with growth traits, the better were the traits. There have been rare studies on gene pyramiding in aquatic animals. The number of growth-related dominant markers in German mirror carp (C. carpio) individuals with extremely large body mass and extremely small body mass was analyzed in Sun et al. (2009), and the results showed that the number of mean dominant genotypes in extremely large individuals and extremely small individuals were 1.7 and 0.7, respectively, indicating that the pyramiding of dominant genotypes was associated with growth traits. Previously, genetic improvement and molecular genetic studies of largemouth bass were carried out, and a number of growth-related molecular markers were screened, such as SNP loci in POU1F1, PSSIII (Du et al., 2011), IGF-I (Li et al., 2009a), and the MSTN (Yu et al., 2010) genes, and microsatellite loci JZL60, JZL67, MisaTpw76, and MisaTpw117 (Fan et al., 2009). On the basis of the previous studies, individuals with a more dominant genotype were screened for population breeding in this study, and the correlation between the pyramiding number of growth-related dominant genotypes in the offspring and growth traits was analyzed. The results could provide basic information and the practical basis for the molecular marker
assisted breeding of largemouth bass.

5.14.1 Materials and Methods 5.14.1.1 Experimental Fish Largemouth bass with the average body mass of about 0.6 kg were obtained from the Tropical and Subtropical Fish Genetics and Breeding Center in the Pearl River Fisheries Research Institute and 196 individuals were selected for parent fish by detecting genotypes of molecular markers. Twenty largemouth bass individuals with more than four dominant genotypes were selected (9 female fish and 11 male fish) and were put into a cement pool with an area of 10 m2 and the height of 0.5 m for population breeding. An artificial oxytocin injection was used to promote synchronous spawning, fertilized eggs were collected within 5 days and the hatched fry were put into the cement pool for culture. After the fry were raised for 2 months, 5000 individuals were randomly selected and put

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into a pond of 114 m2 for raising. Water fleas, water earthworms, and fish cream were used for feeding in the cement pool, while fresh iced fish were used for feeding in the pond. At the age of 9 months, 288 experimental fish were randomly collected from the cultural pond, and fins were cut down and preserved in alcohol at 220˚C for later use. 5.14.1.2 Molecular Markers Related to Growth Traits The selected markers were four SNP loci located in the POU1F1, PSSIII, IGF-I, and MSTN genes and four microsatellite loci JZL60, JZL67, MisaTpw76, and MisaTpw117, which were all obtained by screening in our laboratory, and correlation analysis confirmed that they were significantly or extremely significantly correlated with growth traits. Primer sequence, annealing temperature, and length of the amplified product of primers used in the PCR reaction for each marker are listed in Table 5.49. All the primers were synthesized by Sangon Biotech (Shanghai) Co. Ltd., and labeled with fluorescence (Table 5.49). 5.14.1.3 Extraction of Genomic DNA and PCR Amplification Tissue DNA was extracted from the fin according to the instruction of a TIANamp Genomic DNA Kit purchased from Tiangen Biotech Co. Ltd. (Beijing, China). DNA concentration was determined using ultraviolet spectrophotometry and DNA was preserved at 220˚C for later use. Fluorescence FAM, HEX, and ROX were used to label primers before PCR amplification (Table 5.49). The PCR reaction mixture (20 μL) for DNA amplification included 10 3 buffer 2.0 μL, MgCl2 (25 mmol/L) 0.8 μL, dNTP (10 μmol/L) 0.4 μL, upstream/downstream primers 0.4 μL (20 μmol/L), template DNA 40 ng, and Taq polymerase 1 U. The PCR reaction procedure was pre-denaturation at 94˚C for 4 min, followed by 32 cycles of denaturation 94˚C for 30 s, 48
60˚C annealing for 30 s, 72˚C extension for 30 s, then ended with an extension at 72˚C for 10 min. 5.14.1.4 Detection of Amplification Products The PCR products were detected by capillary electrophoresis, and the labeled genotypes were distinguished according to the differences in fragment size. Genetic typing was commissioned to Sangon Biotech Co. Ltd. (Shanghai, China). Electrophoresis was carried out using DYY-8 SteadyState Steady-Flow Electrophoresis (Shanghai Qite Analytical Instruments Co., Ltd.), and typing was carried out using gel imaging system (Gene Genius) and 3730XL sequence analyzer (US ABI). Three SNP loci

Table 5.49 PCR primer information of molecular markers related to largemouth bass growth Primer Nucleotide constitutes Size (bp)

MSTN C 2 1453 MSTN C 2 1454 MSTN T 1 33 C MSTN T 1 34 C IGF-I 2 632 F IGF-I 2 632 R PSSIII 2 101 F PSSIII 2 101 R POU1F1 2 18 F POU1F1 2 18 R JZL60 F JZL60 R JZL67 F JZL67 R MisaTpw76 F MisaTpw76 R MisaTpw117 F MisaTpw117 R

TF TR F R

CAAAGGAATAGTCTGCCTCATATC GGCAGGCGAAAGAAATGAGTA GCCTATCAGTGTGGGACATTAA GTTTCTATTGGGCTGGTGGCGG ATCTGAAATAGGCTACGTC CTCTATGTCACCAGTGTGC CCTTCTGGATCTCTGGCTAG AGGTGACGGACCAGAGACTAC GATAAAGTAAGACTAAACACAAGC CATTCTTCTCAGGCCCCGCT AGTTAACCCGCTTTGTGCTG GAAGGCGAAGAAGGGAGAGT CCGCTAATGAGAGGGAGACA ACAGACTAGCGTCAGCAGCA ACACAGTGTCAGTTCTGCA GTGAATACCTCAGCAAGCAT TGTGAAAGGCACAACACAGCCTGC ATCGACCTGCAGACCAGCAACACT

Annealing temperature (°C)

Fluorescence

220

57

FAM

412

57.4

FAM

260

55.5

HEX

118

53

HEX

210

52

ROX

227

60

FAM

266

60

HEX

268

48

FAM

220

55

HEX

MSTN, myostatin; IGF-I, insulin-like growth factor-I; PSSIII, preprosomatostatin; POU1F1, pituitary-specific transcription factor 1.

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located respectively in POU1F1, PSSIII, and MSTN were genotyped after digestion by restriction endonucleases TaqI, BsrBI, and AluI. The genotype of deletion mutation sites and four microsatellite loci in the IGF-I gene were analyzed using STR genotyping technology directly. 5.14.1.5 Statistical Analysis of Data The number of dominant genotypes in each largemouth bass individual were counted, and these largemouth bass individuals were grouped according to the number of dominant genotypes. Least squares analysis was performed on the correlation between dominant genotypes and major growth traits of largemouth bass based on a GLM by SPSS 15.0. The biometric model was Yij 5 u 1 Bi 1 eij, where Yij represents the observed value of marker i, individual j; u represents the average value of all the observed individuals in the experiment (overall average); Bi is the effective value of the i marker; and eij is the random residual effect of the observed value.

5.14.2 Results and Analysis 5.14.2.1 Number of Dominant Genotypes in Parent and Offspring Fish Through the detection of dominant genotypes of 196 breeding parent individuals of largemouth bass, the number of individuals containing four and five dominant genotypes were 17 and 3, respectively, accounting for 8.67% and 1.53%; the number of individuals with two and three dominant genotypes were 81 and 59, respectively, accounting for 41.33% and 30.10%; and the number of individuals containing only one dominant genotype was 40 which accounted for 20.41%. The number of average dominant genotypes in this population was 2.36. In order to pyramid the dominant genotypes, individuals with a dominant genotype number of four and five were used as parent fish for breeding. The results show that the average number of dominant genotypes in the offspring was 2.99, which was significantly higher than the parent population. These suggest that an effective way to pyramid dominant genotypes is to select parent largemouth bass with more dominant genotypes for population breeding. 5.14.2.2 Correlation of Dominant Genotype Number in Offspring With Growth Eight growth-related molecular markers were detected using STR genotyping in 288 largemouth bass offspring. The distribution frequency of dominant genotypes of SNP loci in IGF-I, POU1F1, PSSIII, and MSTN

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gene and microsatellite loci JZL60, JZL67, MisaTpw76, and MisaTpw117 are shown in Table 5.50. The results show that the distribution frequency of the dominant genotype POU1F1 was highest in the offspring population, which reached 89.93%, while the distribution frequency of the dominant MisaTpw76 genotype was the lowest, at only 12.85%. The result of correlation analysis between dominant genotype number contained in largemouth bass and the average body mass are shown in Table 5.51. It can be seen that the dominant genotype number in largemouth bass was between one and six, the number of average dominant genotypes was 2.99 per individual, and the number of individuals containing two or three dominant genotypes accounted for 34.72% and 38.19%, respectively. The number of dominant genotypes in largemouth bass was positively related to body mass. There was an extremely significant difference in the body mass between individuals containing five or six dominant genotypes compared with the other individuals (P # 0.05). Most growth traits of aquatic animals, such as body mass and body length, are quantitative traits controlled by multiple minor genes, their genetic basis is complex and it is difficult to improve the target traits rapidly and accurately by traditional breeding methods. Studies have shown that molecular marker
assisted selection is an important technique to Table 5.50 Frequency of dominant genotype in largemouth bass Locus M76 M117 IGF-I PSSIII POU1F1 J67

Frequency (%)

12.85

14.58

13.19

25.00

89.93

26.04

MSTN

J60

17.01

25.00

IGF-I, insulin-like growth factor-I; PSSIII, preprosomatostatin; POU1F1, pituitary-specific transcription factor 1; MSTN, myostatin.

Table 5.51 Correlation analysis of dominant genotype number with growth traits Number of dominant Frequency of fishes Body weight (g) genotypes (number)

6 5 4 3 2 1

2.78(8) 6.94(20) 15.28(44) 38.19(110) 34.72(100) 2.08(6)

305.60 6 33.29a 302.50 6 52.69a 273.02 6 47.10ab 258.81 6 55.69bc 239.56 6 50.71bc 227.83 6 50.49c

Notes: Values with different superscript letters within a column indicates significant difference at P , 0.05.

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achieve the rapid improvement of quantitative traits and it has become a focus in aquatic genetics and breeding research (Sacco et al., 2013; Yue, 2013). A number of growth-related molecular markers of largemouth bass have been found in previous studies, from which eight growth-related molecular were used in this study. Individuals containing markers with more than four dominant genotypes were screened for population breeding, and the pyramiding effect of dominant genotypes in offspring was analyzed. The results show that the average number of dominant genotypes in offspring was 2.99 which was higher than the average number in the parent population of 2.36. This suggests that carrying out population breeding by selecting parent fish with more dominant genotype number could effectively improve the number of dominant genotypes contained in largemouth bass individuals. The result of correlation analysis showed that the dominant genotype number in offspring individuals was significantly correlated with growth traits, which was consistent with the pyramiding effect of dominant genotype in the litter size of pig (Chen and Li, 2000), the growth of Luxi cattle (Li et al., 2012a), and milk production of Chinese Holstein cattle. Using the multiple gene pyramiding method could effectively improve the corresponding traits, and a better selected breeding effect would be reached by directly selecting the largemouth bass individuals with a greater number of dominant genotypes related to growth in future breeding practice. In the process of favorable genotype pyramiding, generally, more than half of the materials would be eliminated by increasing each gene for screening, as a result the probability of targeting an individual for selection would be greatly reduced. This phenomenon was also observed in this study, the distribution of the dominant genotype in the offspring was not uniform and the number of individuals containing two or three dominant genotypes was relatively high, accounting for 34.72% and 38.19%, respectively. There were also individuals with 4
6 dominant genotypes but the number was relatively low, suggesting that the selection of parents in future breeding processes should be more targeted, such as focusing on the selection of homozygote parents of dominant genotypes, so as to improve gene pyramiding efficiency. The average body mass of largemouth bass group with dominant genotype was higher than one with other genotype for each growthrelated marker. Largemouth bass with the dominant genotype in the MSTN gene had a significantly higher growth rate than the others. Moreover, the average body mass of individuals with a MSTN dominant

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genotype (288.63 g) was higher than that of the other individuals (251.86 g) (P , 0.01). However, there was no significant difference in growth rate between populations with the dominant genotype of SNP loci in the IGF-I, PSSIII, and POU1F1 genes and microsatellite loci JZL60, JZL67, MisaTpw76, and MisaTpw117 and other populations, which was consistent with the previous research results found in our laboratory. The previous study showed that the average body mass of individuals containing dominant genotype in the MSTN gene was higher than that of individuals with other genotypes by 53.24% (Yu et al., 2010). However, the body mass of individuals containing dominant genotypes in the other seven markers was higher than that of individuals with other genotypes on the same locus by 16.86%
46.18% (Du et al., 2011; Li et al., 2009a; Fan et al., 2009). The MSTN gene could be used as a major selection marker when using dominant genotype markers to assist parent selection.

5.15 LOOKING FORWARD TO MOLECULAR-ASSISTED SELECTIVE BREEDING OF LARGEMOUTH BASS The molecular marker
assisted selective breeding technique is a modern breeding technique which indirectly selects target traits using molecular markers related to target traits, namely by detecting differences in DNA sequences of individual animals with different phenotypes in the same environment through modern molecular biological techniques, to identify a beneficial gene (or genotype), and then conducting selection through analysis of the genome in reserved individuals (Sun, 2010). The molecular marker
assisted selective breeding technique could compensate for the inadequacy of traditional breeding, not only by enabling accurate and stable selection in the early period of breeding, but also by solving the problem of difficult identification when reusing a recessive gene. It was predicted that molecular marker
assisted selective breeding could improve breeding efficiency by 2
3 times compared with traditional breeding techniques (Gomez-Raya and Klemetsdal, 1999). At present domestic and international studies on molecular marker
assisted selective breeding of aquatic animals have mainly focused on basic connections of molecular marker positioning and identification, and there have been few reports on the application of molecular markers in breeding research, especially regarding studies carried out for growth traits and other quantitative traits. In the process of largemouth bass breeding research, we

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combined the existing development achievements of growth-associated molecular markers to explore the application of molecular marker
assisted selective breeding of largemouth bass. Multigene pyramiding breeding is one of the primary technology strategies with greater application in molecular marker
assisted selective breeding at present (Fan and Deng, 2008). This technique pyramids dominant genotypes into the same genome using hybridization (hybridization between different genotypes) in genetics or breeding, as well as backcross techniques. Namely, it constitutes a breeding method to conduct hybridization between individuals with different genotypes, and then selects homozygous individuals with dominant genes in all target loci through molecular markers in the segregative generation, thus selecting individuals with favorable performance traits to achieve pyramiding of dominant genotypes (Qin et al., 2006). Most growth traits in aquatic animals such as weight and body length are quantitative traits controlled by multiple genes with a complex genetic basis. A single gene has limited effect on a trait, thus it is necessary to develop linked markers with multiple genes impacting economic traits, and then pyramid multiple growth markers with beneficial genotypes and apply them to breeding, thus improving the breeding effect more effectively. Recently, more than 13 growth traitassociated molecular markers of largemouth bass were identified by using correlation analysis. They included microsatellite molecular markers identified dominant genotypes associated with weight, body length, and body height as AA at locus JZL60, BB at locus JZL67, AC at locus JZL72, BB at locus MiSaTPW76, and BC at locus MiSaTPWll7. Meanwhile, the study of SNPs and haplotypes, forming diplotype molecular markers, revealed that two haplotypes were composed of one GTTT deficiency and two SNPs in the IGF-I gene: ATTTTTGTTTTT (haplotype A) and ATAATTTT (haplotype B). The weight and body width of individuals with genotype AA were significantly higher than those of individuals with genotype AB or BB; while two diplotype markers associated with growth traits were found in the MSTN gene. Two diplotype markers associated with growth traits composed of four SNP loci were found in the IGF-II gene; one haplotype marker associated with growth trait was found in the POU1F1 gene, and its correlation with growth was further verified in full-sib families; one SNP locus in the largemouth bass PSSIII gene was significantly correlated with body weight, body length, total length, caudal peduncle length, and caudal peduncle height; one lethal deletion mutation locus was found in the promoter region of the GHRH

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gene, and the average weight of individuals with dominant genotypes of a growth-associated marker was higher than that of individuals with other genotypes by 16.86%
53.24%. After identifying the above markers that had effects on growth traits of largemouth bass, eight fast-growth markers were used to analyze the pyramiding of dominant genotypes in Youlu No.1 largemouth bass populations of different breeding generations. The results showed that the average number of molecular markers of dominant genotypes in F2, F3, F5, and F6 breeding populations were 2.12, 2.70, 2.90, and 3.08, respectively, and showed an increasing tendency with increasing generations; artificial breeding could pyramid dominant genes to some extent, and with the progress of breeding generations, the molecular marker number of dominant genotypes had a synchronous increasing tendency with growth rate of largemouth bass. In addition, the number of fast-growth markers contained in the Youlu No.1 largemouth bass breeding population was obviously larger than in the nonbreeding population. On the basis of the above combined research, we aimed to use growth trait-associated dominant genotypes as fast-growth markers to assist in selection of largemouth bass parents, establish a breeding population enriched with dominant genotypes, evaluate the effect of molecular marker
assisted selective breeding compared with traditional breeding methods on the basis of phenotypic selection, and explore the practical application of molecular marker
assisted selective breeding of largemouth bass. First, we selectively pyramided well-grown individuals with beneficial genotypes of over four markers to form the breeding population from which to breed offspring, and to evaluate the effect of molecular marker
assisted selective breeding compared with traditional breeding of offspring using phenotypes as the parent selection basis in the same year. Next, we used selective pyramiding of well-growth individuals with dominant genotypes of over six markers in the first filial generation of molecular marker
assisted selective breeding, bred offspring, and further evaluated and validated the effect of molecular marker
assisted selective breeding compared with traditional breeding on the offspring using phenotypes as the basis of parent selection in the same year. The detailed technical route is shown in Fig. 5.14. Another ongoing molecular marker
assisted selective breeding project is to guide high-hatching parental selection using molecular markers. Fry hatching rate is an important factor directly affecting fry production in the hatchery. Improving the fry hatching rate could reduce hatching production costs to some extent and increase the economic efficiency of

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The breeding population of Youlu No.1 largemouth bass

Markers associated with growth traits

Analyze difference for dominant genotypes between Youlu No.1 largemouth bass and control population

Markers associated with growth traits

Select parents with different genotypes to hybridize and establish family and analyze dominant genotypes pyramiding in offspring using

Analyze pyramiding of dominant genotypes in different breeding generations of Youlu No.1 largemouth basss

Analysis of pyramiding effect of growth-associated markers

Select 80 largemouth bass individuals pyramided with over four genotypes beneficial to growth as parents to breed offspring after mass mating

Select same number of extremely large individuals and extremely small individuals based on weight as the index, and analyze differences in molecular marker enrichment

Select individuals of largemouth bass as the control population on the basis of phenotype value, and breed offspring after mass mating

Select parental individuals with pyramiding of over six dominant genotypes in the first filial generation, and breed offspring freely

Select individuals of largemouth bass as the control population on the basis of phenotype value, and breed offspring after mass mating

Conduct a growth comparison experiment under the same cultural conditions, to evaluate the effect of molecular marker-assisted selective breeding

Initially establish molecular marker-assisted selective breeding technique of growth traits in largemouth bass

Conduct growth comparison experiment under the same cultural condition, to evaluate effect of molecular marker assisted selection breeding

Figure 5.14 Technical route of molecular marker
assisted selective breeding of largemouth bass.

the culture. One lethal deletion mutation locus was found in the promoter region of the GHRH gene, and an AB 3 AB family was established for that locus. Genotype frequency analysis of the offspring showed that individuals with genotype BB died before hatching, therefore that molecular marker was used to guide selection of largemouth bass parents with a high hatching rate. In large-scale breeding production, individuals homozygous for the AA gene should be selected as parents for breeding, thus the generation of individuals with genotype BB could be controlled and the fry hatching rate of largemouth bass could be improved.

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