Genetic diversity and parentage assignment in Dojo loach, Misgurnus anguillicaudatus based on microsatellite markers

Biochemical Systematics and Ecology 61 (2015) 12e18

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Genetic diversity and parentage assignment in Dojo loach, Misgurnus anguillicaudatus based on microsatellite markers Xiaohui Bai a, b, Songqian Huang a, Xianchang Tian a, Xiaojuan Cao a, Gangming Chen a, Weimin Wang a, * a

College of Fisheries, Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, Hubei 430070, China b Tianjin Fisheries Research Institute, Tianjin 300221, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 13 January 2015 Accepted 2 May 2015 Available online

In this study, genetic diversity and structure of three Misgurnus anguillicaudatus populations from three different geographical locations in China (Hunan, Hubei and Henan province) were investigated using microsatellite markers. High level of genetic diversity of all three populations was revealed by expected heterozygosity (He), observed heterozygosity (Ho) and allele number. Significant genetic differentiations were found between all pairs of populations. The efficiency of eight microsatellite markers in parentage assignment of 540 progeny from twenty full-sib families was evaluated. Simulation based on allele frequency data demonstrated that probabilities of exclusion per locus range from 0.313 to 0.825 when no parent information is available and 0.504 to 0.904 when one parent is known. The assignment success rate based on the real data using eight markers was 96.85%. This study indicates that these M. anguillicaudatus resources are valuable genetic and breeding material for aquaculture and the microsatellite markers will be useful for investigation of genetic background and molecular marker-assisted selective breeding in this species. © 2015 Elsevier Ltd. All rights reserved.

Keywords: Genetic diversity Microsatellite markers Parentage assignment Misgurnus anguillicaudatus

1. Introduction The Dojo loach, Misgurnus anguillicaudatus (Cypriniformes: Cobitidae), is a widespread freshwater fish with native range in Japan, Korea, Taiwan and eastern coasts of the Asian continent (Saitoh, 1989). It inhabits rivers, lakes, ponds, swamps and rice fields, and can be found throughout China except for Tibetan plateau. Meanwhile, the coexistence of diploid and polyploid (3ne6n) in natural populations at some locations along the Chang Jiang River system confers on this species a significant potential as a model animal not only to study the evolutionary biology of polyploid fish, but also to be used as valuable genetic and breeding material for aquaculture (Li et al., 2008; Wang et al., 2008). At present, the loach for human consumption is mostly obtained through exploitation of wild populations. In recent years, environmental degradation and over-fishing have led to rapid decline in natural loach populations. In order to meet the expanded and consistent requirement of loach production, it is necessary to develop aquaculture techniques, such as pond culture, cage culture, rice-fish farming and flowing water fish farming (Wang et al., 2008). Therefore, the

* Corresponding author. Tel./fax: þ86 027 8728 2114. E-mail address: [email protected] (W. Wang). http://dx.doi.org/10.1016/j.bse.2015.05.005 0305-1978/© 2015 Elsevier Ltd. All rights reserved.

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development of artificial breeding techniques, that produce sufficient numbers of high-quality loach fry is urgently required to support the aquaculture of loach. The population genetic analysis of species in nature is of primary importance in developing an optimal strategy for aquaculture when genetic improvement through selective breeding is anticipated. The difficulty in managing a selective breeding program is loss of genetic variability and increases in inbreeding as a result of the inadvertent mating of related individuals (Lind et al., 2012). Microsatellite markers were regarded as an invaluable tool in the investigation of genetic diversity and pedigree tracing of hatchery populations (Haffray et al., 2012; Ma et al., 2013; Yang et al., 2014). The use of microsatellite markers for identifying parentage allows progeny from different families to be communally stocked together without requirement to mark or segregate the progeny before stocking into the ponds, providing parental genotypes are known (Jerry et al., 2004). Also estimates of relatedness based on DNA genotyping offer breeding managers of aquacultural stocks a method of avoiding inbreeding and maintaining genetic variation in the absence of pedigree information. A lot of microsatellite markers have been developed for M. anguillicaudatus in recent years, which are valuable for studies of local adaptation, population structure, genome mapping, parentage and selective breeding programs (Arias-Rodriguez et al., 2007; Chen et al., 2010; Morishima et al., 2008). The objectives of this study were to obtain information about genetic variations and population differentiation in three wild M. anguillicaudatus populations in China, and to evaluate the efficiency of microsatellite markers in parentage assignment in separate loach families. 2. Materials and methods 2.1. Sample collection The three wild populations of M. anguillicaudatus were collected from Liuyang in Hunan province, Wuhan in Hubei province and Xinxiang in Henan province (Fig. 1). Ploidy levels were determined by a flow cytometer (Cell Lab Quanta™ SC, Beckman Coulter, USA) as described by Zhu et al. (2012). A total of 120 diploid loach (Hunan, 40; Hubei, 40; Henan 40) were used for genetic diversity analysis.

Fig. 1. Sample locations of M. anguillicaudatus.

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In order to evaluate how reliable the microsatellite loci were in assigning parentage in a commercial breeding program, twenty females and twenty males were selected from three populations mentioned above to establish 20 full-sib families, where both parental and filial information was known. Fin clips of 40 parents and 540 of their larvae were stored in absolute ethanol until DNA extraction. 2.2. DNA extraction and microsatellite analysis Total genomic DNA was extracted by a modified protocol according to Li et al. (2011). Twelve primer pairs of microsatellite loci were used for genetic diversity analysis (Morishima et al., 2008, Table 1). Eight primer pairs of microsatellite loci were selected to estimate the efficiency of parentage assignment according to their polymorphism and length of fragments, as previously described (Morishima et al., 2008; Chen et al., 2010, Table 1). Primers were synthesized by Sangon Biotech (Shanghai) Co., Ltd., and the primers used for parentage analysis were labeled with a fluorescent dye (ROX, HEX or FAM) at the 50 -end of the forward primers. Amplifications were conducted in a 15 ml reaction volume containing 11.3 mL double distilled water, 1.5 mL 10  PCR Buffer, 0.15 mL of deoxynucleotide triphosphate (dNTPs, 10 mm/L), 0.2 mL of each primer (10 mm/L), 1.5 mL of genomic DNA (100 ng/mL), and 0.15 mL 5U/mL of Taq DNA polymerase (Takara, Japan). The PCR amplification was carried out on a C1000 DNA Engine Thermal Cycler (Bio-Rad Laboratories, Inc., CA, USA) with the following protocol: 5 min at 95  C; 35 cycles of 30 s at 95  C; 45 s at annealing temperatures given in Table 1, and 1 min at 72  C; 10 min at 72  C; and held at 16  C. PCR products used for genetic diversity analysis were resolved through 8% vertical non-denaturing polyacrylamide gels electrophoresis. All individual amplification products for parentage assignment were genotyped by ABI 3730XL Genetic Analyzer and analyzed with the GS-500 LIZ size standard using GeneMapper Version 3.5 software (Applied Biosystems). 2.3. Data analysis 2.3.1. Genetic diversity In order to evaluate the genetic diversity of three M. anguillicaudatus populations, allele number (Na), effective allele number (Ne), observed heterozygosity (Ho) and expected heterozygosity (He) were estimated using PopGene version 1.32 (Yeh et al., 1999). Deviations from the HardyeWeinberg equilibrium (HWE) were analyzed using GENEPOP 4.0 (Raymond and Rousset, 1995). Corrections for multiple significance tests were performed using Fisher's method and Bonferroni correction. The number of private alleles (NP) and inbreeding coefficient (Fis) were also calculated using GENEPOP 4.0. 2.3.2. Genetic differentiation and structure The calculation of population differentiation and their genetic distance was carried out using Arlequin 3.1 (Excoffier et al., 2005). A Bayesian clustering approach, implemented in the programme Structure ver. 2.3.2 (Pritchard et al., 2000), was used

Table 1 Characteristics of the microsatellite markers used in this study. Locus

Primer sequences (50 -30 )

Repeat motif

GenBank accession no.

Ta( C)

Mac63

F: GGGTCAGAACAAACAGCACA R: ATTGGGGTTGCTGCCCTCTTC F: CACTGCAACAAGCATTGCATA R: TTTTACCCCCAAATGGATCA F: CTTTGCTCAGCCATGATCAG R: AGCGTAAGACATCAGCATTC F: TAGCCACTAGAAGATGCTGA R: ATGTTCAAACTACCAGCTGT F: CGATGCATTGAAAATGTCCT R: CTGCTCTTTTCACAGTACCT F: CTGCATGCTCTTGCATAGGA R: CATTCATATTCCACCCTCTCG F: TATGTGAGGAAGATAAGCAG R: GAATCCAGATCAAAGCAATC F: GCAAGTACATGCTCATCCTT R: CACCTGCATTCCTTACATCT F: ATTCTGAAGGTCACCGTTGT R: GCAGCCGTTAATACACTGTC F: CTGAGACTCTTTATGTCTCAC R: CTATCAAGGGAACTGAATGG F: TCTCCTCTGACACCATCAGG R: GTACGGACACGAGTCTGGAA F: CCCTCCACTTCAACCCTACA R: GACCCTGCTGTCATCTCACA F: AGATGTACTGCACTTTCTTTA R: GAATAGCCTATATGTAAATGT

(CA)16

AB081633

54

(GT)16

AB303455

54

(GT)21

AB303512

56

(GT)49

AB303607

60

(CA)23

AB303610

56

(GT)22

AB303444

57

(GT)22

AB303518

60

(CA)15

AB060181

60

(GT)26

AB303605

60

(CA)33

AB303575

60

(GT)38

AB303522

60

(CA)19

AB303519

60

(CT)13

BJ839497

60

Mac190 Mac404 Mac612 Mac627 Mac133

a

Mac429

a

Mac37a Mac605a Mac477

a

Mac456a Mac449a Ma112 a

a

, the primers used for parentage assignment; Ta, annealing temperature.

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to infer the population structure. The number of clusters (K) was determined using the admixture ancestry model and correlated allele frequencies, testing K ¼ 1 to 5 with 10 runs at each K for the sampled populations. The simulation was run with 10,000 burn-in periods and 10,000 Markov chain Monte Carlo (MCMC) repetitions after burn-in. The most appropriate K was decided according to DK based on rate of change in the log probability of data between the successive K values (Evanno et al., 2005). 2.3.3. Parentage assignments Cervus 3.0 software (Kalinowski et al., 2007) was used to perform parentage assignments. Two analyses included simulation of parentage analysis and actual parentage analysis (parent pair, sexes known) were conducted to evaluate the accuracy of parentage assignments. Analysis parameters for simulation run were as follows: the number of simulated offspring was 10,000, 20 couples of candidate parents, 100% of the candidate parents sampled and genotyped, 90% of loci typed. The results from the simulation run were then used in the parentage assignment module to evaluate assignment success to the correct parents when there was no a priori information on the correct parents in 20 single families. 3. Result 3.1. Genetic diversity The 12 microsatellite loci screened in the sampled populations were all polymorphic and details of these polymorphisms are summarized in Table 2. A total of 154 alleles and 42 private alleles were detected across 12 microsatellite loci in the three populations. Fourteen private alleles were found in Henan population, nine in Hunan population, and 19 in Hubei population. An average of 12 alleles and 5.147 effective alleles per locus were recorded. Values of observed and expected heterozygosity ranged from 0.283 to 1.000 and 0.358 to 0.927, with an average of 0.711 and 0.727, respectively. All populations deviated significantly from HWE at most microsatellite loci. At these loci, significant (P < 0.05) heterozygote deficiency or excess was evident from the positive and negative Fis value, respectively.

Table 2 Genetic diversity analyses for three populations of M. anguillicaudatus. Population(N)

Microsatellite locus Mac63

Henan(40) Na 6 Ne 1.231 NP 0 Ho 0.125 He 0.190 Fis 0.345 PHW ** Hunan(40) Na 5 Ne 2.066 NP 1 Ho 0.400 He 0.523 Fis 0.382 PHW * Hubei(40) Na 9 Ne 1.744 NP 3 Ho 0.325 He 0.432 Fis 0.114 PHW ns Overall mean(120) Na 11.000 Ne 1.643 Ho 0.283 He 0.393 Fis 0.280

Average over loci

Mac190

Mac404

Mac612

Mac627

Mac133

Mac429

Mac37

Mac605

Mac477

Mac456

Mac449

8 3.805 0 0.950 0.746 0.277 ***

11 9.425 1 0.972 0.907 0.070 ns

3 1.481 0 0.400 0.329 0.220 ns

7 1.551 4 0.385 0.360 0.070 ns

12 3.805 5 0.475 0.747 0.367 **

6 1.804 1 0.475 0.451 0.053 ns

2 1.025 0 0.025 0.025 0.013 e

5 4.285 0 1.000 0.777 0.293 ***

9 5.153 1 1.000 0.816 0.229 ***

14 9.139 0 1.000 0.898 0.110 *

10 3.787 2 0.625 0.745 0.163 ***

7.583 3.841 1.177 0.619 0.582 0.038

8 4.611 1 1.000 0.789 0.265 ***

12 7.330 1 1.000 0.875 0.145 **

5 1.847 1 0.513 0.465 0.106 ns

3 1.995 0 0.800 0.505 0.596 ***

4 3.292 0 0.750 0.705 0.065 ns

4 2.348 0 0.975 0.581 0.698 ***

8 3.548 0 1.000 0.727 0.393 ***

4 2.089 0 0.886 0.529 0.699 ***

6 3.292 0 1.000 0.705 0.436 ***

16 12.835 1 1.000 0.934 0.085 ns

11 2.097 4 0.333 0.530 0.363 ***

7.167 3.908 0.750 0.805 0.655 0.229

10 5.300 0 1.000 0.822 0.220 ***

11 7.360 2 1.000 0.889 0.126 *

5 1.363 1 0.275 0.270 0.019 ns

10 3.819 5 0.400 0.748 0.469 ***

8 4.746 0 0.564 0.804 0.301 *

7 2.736 0 0.795 0.643 0.241 ***

10 5.170 1 0.725 0.817 0.114 *

11 6.275 4 0.800 0.851 0.061 ns

8 4.901 0 1.000 0.806 0.244 ns

17 11.393 2 1.000 0.926 0.081 *

11 7.143 1 0.600 0.871 0.314 ***

9.750 5.162 1.583 0.707 0.740 0.037

11.000 5.074 0.983 0.806 0.254

15.000 8.989 0.991 0.893 0.114

6.000 1.555 0.395 0.358 0.115

14.000 2.535 0.529 0.608 0.066

13.000 5.207 0.597 0.814 0.201

8.000 3.472 0.748 0.715 0.331

10.000 4.183 0.583 0.764 0.097

11.000 4.340 0.895 0.773 0.310

9.000 5.988 1.000 0.837 0.303

19.000 12.396 1.000 0.923 0.092

17.000 6.383 0.521 0.847 0.280

12.000 5.147 0.711 0.727 0.077

Na, number of alleles per loci; Ne, effective number of alleles; NP, private alleles; Ho, observed heterozygosity; He, expected heterozygosity; Fis, inbreeding coefficient; PHW, HardyeWeinberg probability test; ns means not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001 after Bonferroni correction.

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X. Bai et al. / Biochemical Systematics and Ecology 61 (2015) 12e18 Table 3 Pairwise genetic differentiation (FST) (below diagonal) and Nei's genetic distance (above diagonal) in three populations of M. anguillicaudatus. Population

Henan

Henan Hunan Hubei a

0.217a 0.102a

Hunan

Hubei

0.518

0.268 0.304

0.120

a

All pairwise FST is statistically significant (P < 0.001) after Bonferroni correction.

Fig. 2. Genetic structure of three M. anguillicaudatus populations based on the microsatellite genotype.

3.2. Population differentiation and structure Pairwise FST values were significant (P < 0.001) between pairs of the three populations, with the largest of 0.217 (between Henan and Hunan) and the smallest of 0.102 (between Henan and Hubei), which is consistent with the Nei's genetic distance between them (Table 3). Calculation of DK based on the output of the Bayesian clustering in STRUCTURE indicated the most likely K ¼ 3. The three populations could be divided into three genetic clusters and each population has their own population structure (Fig. 2). This result was consistent with the geographical distribution of the three populations.

3.3. Parentage assignments 3.3.1. Computed simulation based on microsatellite loci Summary statistics for the eight markers used in the simulations of the hypothetical loach breeding population are given in Table 4. Probabilities of exclusion per locus ranged from 0.313 to 0.825 when no parent information was available (Excl 1) and from 0.504 to 0.904 when one parent was known (Excl 2). The result of simulations indicate that the accuracy of parentage assignment increases with the number of markers used. The combined exclusion power for the 8 microsatellite loci for Excl 1 and Excl 2 was 0.9985 and 0.9999, respectively.

Table 4 Summary statistics of eight microsatellite loci used in simulation study of M. anguillicaudatus. Locus

Na

Ho

He

PIC

Excl 1

Excl 2

Fn

Mac37 Mac133 Mac429 Mac477 Mac605 Mac456 Ma112 Mac449 Average CEP

13 17 11 12 14 26 23 22 17

0.681 0.761 0.707 0.766 0.762 0.713 0.726 0.661 0.722

0.690 0.870 0.770 0.852 0.858 0.954 0.805 0.818 0.827

0.669 0.858 0.747 0.835 0.843 0.951 0.783 0.808 0.811

0.313 0.597 0.406 0.546 0.565 0.825 0.468 0.514 0.529 0.9985

0.504 0.748 0.589 0.709 0.724 0.904 0.640 0.684 0.688 0.9999

0.0115 þ0.0685 þ0.0499 þ0.0540 þ0.0616 þ0.1443 þ0.0536 þ0.1158 e

Na, Ho, He as described in Table 1; PIC, polymorphism information content; Excl 1, exclusion probability without known parents; Excl 2, exclusion probability with genotype of one parent known; Fn, Frequency of null allele; CEP, combined exclusion probability.

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3.3.2. Pedigree analysis in 20 full-sib families By comparing the assigned results with the individual identifications, 92.41% of the offspring were assigned to their real parents using six microsatellite loci. The correct matching rate was up to 96.85% when eight microsatellite loci were used, which was lower than those predicted by the simulations. 4. Discussion Polymorphic molecular markers can be a useful tool for monitoring the genetic diversity and ascertaining parentage in fish populations (Lind et al., 2012). The number of alleles and heterozygosity are important indices for assessing population variation at the genetic level (Leberg, 2002). In the present study, the average number of alleles, Ho and He observed at the population level were relatively high compared to the average value from other M. anguillicaudatus populations (Shan et al., 2009) and other freshwater species (DeWoody and Avise, 2000), suggesting that all three populations could have good potential for genetic breeding. More than half of the 12 microsatellite loci exhibited significant deviations from the HWE in all three populations, which was mostly caused by heterozygote excess. The three populations did not experience a recent bottleneck (Bai, 2014), a probable explanation for heterozygote excess could be a rather limited sample size, causing the allele frequencies in female and male populations to differ (Balloux, 2004). Therefore, a larger sample size would be needed to calculate the HardyeWeinberg expectations in the populations with high allelic and gene diversity, as argued by Yue et al. (2013). Genetic divergence estimated by pairwise FST values (0.102e0.217) showed moderate and significant genetic differentiation among the three M. anguillicaudatus populations. Similar results were reported in other M. anguillicaudatus populations (Abbas, 2009; Khan et al., 2005). Geographical distance with physical and environmental barriers in between, may keep these populations reproductively isolated from each other. Moreover, reproductive habits of the loach, nonmigratory behavior and eggs that stick to local substrate limit the gene flow between nearby populations (Breder and Rosen, 1966). This was also supported by the separate gene pools and private alleles in the three populations in this study. These genetically differentiated populations may show variation in economically important traits and produce hybrid vigour in genetic breeding programs (Kumagai et al., 2004). Simulations in many previous studies suggested a high potential of microsatellite markers for application in parentage assignment (Jerry et al., 2004; Luo et al., 2014). The performance of microsatellites in assignment of offspring to their parents is affected by the allelic diversity of markers and/or genotype variations of parents (Bernatchez and Duchesne, 2000; Sekino et al., 2003). The assignment success rate was 94.3% in Salmo salar using only four most informative loci (Norris et al., 2000). However, in Penaeus japonicus, when six microsatellite markers were used, only 47% of the progeny was successfully assigned to their true parents (Jerry et al., 2004). In the present study, the efficiency of assignment using eight markers was 96.85%, which was higher than the results reported for Japanese flounder (Paralichthys olivaceus) (Sekino et al., 2003), mud crab (Scylla paramamosain) (Ma et al., 2013) and mandarin fish (Siniperca chuatsi) (Yang et al., 2014). Discrepancies between the simulations and real data sets were also observed, as reported in other parentage assignment studies. Null alleles are the dominant source affecting the accuracy of parentage determination with microsatellite markers (Pemberton et al., 1995). Mutation is another effective factor, but with lower possibility. Furthermore, scoring error due to allele-stuttering is an inevitable cause for mismatches (O'Reilly et al., 1998). In the present study, different frequency of null allele was detected at eight microsatellite loci in offspring, which might be the main factor affecting the accuracy of parentage determination. However, the null allele frequencies in this study were below the upper limit value for parentage assignment analysis (Dakin and Avise, 2004), suggesting that it is feasible to identify parentage relationships in M. anguillicaudatus using eight microsatellite markers. As it is expected that inbreeding will increase and genetic variability decrease during the course of a breeding program (Sherman et al., 2004), the assignment power is expected to decrease over time. Thus, additional highly polymorphic microsatellite markers with low null allele frequency may be required for breeding programs. In general, the three populations included in this study had relatively high genetic variation and significant genetic differentiation among populations, which could be a good basis for the future breeding programs. Our analyses have shown that a high level of parentage assignment success can be achieved with eight microsatellite loci, which means that these genetic markers are an easily available and powerful tool for practical selective breeding in M. anguillicaudatus. Acknowledgments This work was financially supported by the National Natural Science Foundation of China (31372180) and the Tianjin science and technology plan projects (12ZCZDNC01100). 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