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ZBTB38 gene polymorphism associated with body measurement traits in native Chinese cattle breeds
Gene 513 (2013) 272–277
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Gene journal homepage: www.elsevier.com/locate/gene
ZBTB38 gene polymorphism associated with body measurement traits in native Chinese cattle breeds Yongfeng Liu a, b, Linsen Zan b,⁎, Yaping Xin b, Wanqiang Tian b, Linqiang Li a, Hongcheng Wang b a b
College of Food Engineering and Nutritional Science, Shaanxi Normal University, 710062, Xi'an, Shaanxi, PR China College of Animal Science and Technology, Northwest A & F University, Yangling 712100, Shaanxi, PR China
a r t i c l e
i n f o
Article history: Accepted 21 October 2012 Available online 5 November 2012 Keywords: Cattle ZBTB38 gene SNP Association analysis Body measurement
a b s t r a c t Body measurement traits, influenced by genes and environmental factors, play numerous important roles in the value assessment of productivity and economy. In this study, we investigated the association between genetic polymorphisms of the zinc finger and BTB domain containing 38 gene (ZBTB38) and body measurement traits in native Chinese cattle. Using direct DNA sequencing in 423 individuals of 8 different cattle subpopulations, 9 novel polymorphisms were identified for genotyping within 647 bp region of exon 1 of ZBTB38. Linkage disequilibrium and association analysis revealed that two coding exon polymorphisms (2323 G>A and 2325 C>T polymorphisms), missense mutations valine GTC(T) to isoleucine ATC(T), were associated with body length (BL), withers height (WH) and rump length (RL). Furthermore, the analysis of 2323 G>A and 2325 C>T SNP markers shows that there are significant effects on the BL (P=0.0488), WH (P=0.0044) and RL (P=0.0314) in the total population. These results clearly suggest that the ZBTB38 gene is among the target genes for body measurement traits in bovine breeding, and provide data for establishment of an animal model using cattle to study big animal body type. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Body measurement traits have been considered important in beef production because these are major factors that affect animal growth and development, as well as production of meat (Liu et al., 2010a, 2010b). Therefore, a study of body measurement in cattle is important in the value assessment of productivity and economy. Zinc finger and BTB domain containing 38 (ZBTB38), previously identified the murine CtBP (C-terminal binding protein)-interacting BTB (broad complex/tramtrack/brica-brac) zinc finger protein (CIBZ, also named ZENON in rat and ZBTB38 in human), is a likely candidate gene for body measurement traits (Kiefer et al., 2005; Sasai et al., 2005). Sasai et al. (2005) described the cloning and characterization of ZBTB38, and found that ZBTB38 repressed transcription via two independent domains, the BTB domain and a proximal domain referred to as RD2, in histone deacetylase (HDAC)-independent and -dependent
Abbreviations: ZBTB38, zinc finger and BTB domain containing 38; CtBP, C-terminal binding protein; BTB, broad complex, tramtrack and bric-a-brac; CIBZ, murine CtBP-interacting BTB zinc finger protein; ZENON, zinc finger gene expressed in neurons; HDAC, histone deacetylase; IGF, insulin-like growth factor; BL, body length; WH, withers height; HH, hip height; RL, rump length; HW, hip width; CD, chest depth; HG, heart girth; PBW, pin bone width; bp, base pairs; MAS, marker-assisted selection; PCR, polymerase chain reaction; SNP, single nucleotide polymorphism; HWE, Hardy–Weinberg equilibriums; LD, linkage disequilibrium; RFLP, restriction fragment length polymorphism; PIC, polymorphism information content; CDS, coding sequence; nt, nucleotides; GWA, genome wide association. ⁎ Corresponding author. Tel./fax: +86 29 87091923. E-mail address: [email protected] (L. Zan). 0378-1119/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.gene.2012.10.026
manner, respectively. ZBTB38 specifically interacted with CtBPs via RD2 and relocalized CtBPs to pericentromeric foci, suggesting that ZBTB38 exerted its repression activity via recruitment of the CtBP complex (Sasai et al., 2005). The rat ZBTB38 regulated transcription (independent of methylation) of the tyrosine hydroxylase gene, the rate-limiting enzyme of catecholamine biosynthesis (Filion et al., 2006). This was the site at which epigenetic errors of imprinting result in either the Beckwith–Wiedemann syndrome of somatic overgrowth or the growth retardation syndrome of Russell–Silver (Binder et al., 2008). ZBTB38, belonged to a novel class of methylated DNAbinding proteins, could repress Gal4-driven thymidine kinase or SV40 promoters by functionally interacting with CtBP in a histone deacetylase-dependent manner, and ZBTB38 lacks a signature methyl-CpG-binding domain but can bind methylated DNA through the conserved zinc fingers (Oikawa et al., 2008). Thus, ZBTB38 affected adult stature through regulation of the production of insulin-like growth factor (IGF)-II, perhaps during in utero development when IGF-II is known to be one of the determinants of fetal growth (Gudbjartsson et al., 2008). Based on the importance of ZBTB38 in adult stature morphogenesis and growth of the skeleton from determinations in human, ZBTB38 could be an attractive candidate gene for body measurement traits in bovine. Screening of ZBTB38 was performed by direct sequencing to detect polymorphisms, and examined their genetic association with body measurement traits in Bos taurus. Here, we present the 9 novel polymorphisms identified in ZBTB38 and the results of an association study with the body measurement traits in native Chinese beef cattle breeds.
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2. Material and methods 2.1. Animals and phenotypic data For the gene variants that identified, allele frequencies were estimated on a restricted population composed of unrelated, randomly selected purebred and crossbred individuals representing 8 breeds including Qinchuan (QC, n = 47, Shaanxi province of China), Qinchuan improvement steers (QI, n = 57, Shaanxi province of China), Nanyang (NY, n = 53, Henan province of China), Jiaxian red (JR, n = 56, Henan province of China), Xia'nan (XN, n =59, Henan province of China), Luxi (LX, n = 52, Shandong province of China), Simmental and Luxi crossbred steers (SL, n = 49, Shandong province of China), and Xuelong (Angus crossed with descendant of male Japanese Black cattle and female Fuzhou cattle) (XL, n = 50, Liaoning province of China). Meanwhile, the following traits, body length (BL), withers height (WH), hip height (HH), rump length (RL), hip width (HW), chest depth (CD), heart girth (HG) and pin bone width (PBW) were measured (Gilbert et al., 1993). For each of the body measurement traits, we measured the same one trait with the same individuals to minimize error. DNA samples were extracted from leukocytes and tissue samples using standard phenol–chloroform protocol (Mullenbach et al., 1989). 2.2. PCR amplification, sequencing and polymorphism identification The bovine ZBTB38 gene has only one exon, and this gene also has one exon in horse, dog, human, mouse, rat, chicken and other species. In addition, the ZBTB38 gene's one coding region (exon) is scattered over about 60695 base pairs (bp) of genomic DNA (GenBank accession No. NC_007299) on chromosomal 1. The 4151 bp mRNA of ZBTB38 gene (GenBank accession No. XM_589799) is translated into the 1205-amino acid sequence. The 3615 bp coding sequences domain and the putative amino acid sequence of bovine ZBTB38 share 87% and 88% similarity to that of human. According to the sequence of bovine ZBTB38 gene, one pair of primers (5′-CTG TGA GTA ACG GCA GTG AGA AC-3′ and 5′-GTC ACT GGC ATC GTC AAA CAT C-3′) was designed to amplify a 647 bp product of the ZBTB38 exon 1. Polymerase chain reaction (PCR) was performed in 30 μl reaction mixtures containing 50 ng DNA templates, 10 pM of each primer, 0.20 mM dNTP, 2.5 mM MgCl2 and 0.5 U Taq DNA polymerase (TaKaRa, Dalian, PR China). The PCR protocol was 95 °C for 5 min followed by 30 cycles of 94 °C for 30 s, 63 °C annealing for 30 s, and 72 °C for 30 s, and a final extension at 72 °C for 10 min. The products were purified with a Wizard Prep PCR purification kit (Shanghai Bioasia Biotechnology, PR China) and sequenced (Beijing Aolaibo Biotechnology, PR China; Applied Biosystems 3730xl DNA sequencer, Foster city, CA, USA). Genetic polymorphisms in the ZBTB38 were identified by sequencing PCR products from eight breeds, and compared with each other using SeqMan (DNASTAR, Inc., Madison, WI, USA). Single nucleotide polymorphisms (SNPs), including 2145 T>C, 2286 T>C, 2323 G>A, 2325 C>T, 2409 T>C, 2457 G>C, 2583 C>T, 2643 G>A and 2676 G>A were chosen for further analysis. 2.3. Statistic analysis The following items were statistically analyzed according to the previous approaches (Nei and Li, 1979; Nei and Roychoudhury, 1974), including genotypic numbers, allelic frequencies, Hardy–Weinberg equilibriums (HWE), gene heterozygosity, effective allele numbers and polymorphism information content (PIC). The association between SNP marker genotypes of the ZBTB38 gene and records of body measurement traits (BL, WH, HH, RL, HW, CD, HG and PBW) was analyzed by the least-squares method as applied in the GLM procedure of SAS
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(SAS Institute Inc., Cary, NC, USA), and according to the following statistical linear model: Yijkl ¼ μ þ Gi þ Sj þ BFk þ Mal þ εijkl ; where Yijkl is the observed body measurement trait, μ is the overall mean for each trait, Gi is the genotype effect, Sj is the fixed effect of sex, BFk is the fixed effect of breed and farm, Mal is the regression variable for measure age, and εijkl is the random environment effect. For the haplotype analyses, the model was fit with the same covariates in a similar manner. A widely used measure of linkage disequilibrium (LD) was examined between all pairs of biallelic loci, D′ (the correlation coefficient [Dalta |D′|]) and r2, and strength of LD between pairs of SNPs was measured as D′ using Haploview (Barrett et al., 2005; Gabriel et al., 2002). Haplotypes and their frequencies were inferred using the algorithm developed by Stephens et al. (2001). Phase probabilities of each site were calculated for each individual using PHASE software (http://depts.washington.edu/ventures/UW_Technology/Express_ Licenses/PHASEv2.php) (Stephens et al., 2001). 3. Results 3.1. Polymorphism and sequencing of the ZBTB38 gene By direct DNA sequencing, 9 polymorphisms were identified in ZBTB38 gene exon 1. The 9 SNPs, namely, 2145 T>C, 2286 T>C, 2323 G>A, 2325 C>T, 2409 T>C, 2457 G>C, 2583 C>T, 2643 G>A and 2676 G>A, were in 647 bp PCR products which DNA sequencing maps are shown in Fig. 1. The 2323 G>A and 2325 C>T mutations, missense mutations valine GTC(T) to isoleucine ATC(T), were also observed at position 775 of the coded amino acids; and the other mutations were synonymous mutations (Table 1). 3.2. Genetic variation in different breeds and association analysis We further analyzed the genotype of unrelated animals from 8 different bovine breeds, including Qinchuan, Qinchuan improvement steers, Nanyang, Jiaxian red, Xia'nan, Luxi, Simmental and Luxi crossbred steers, and Xuelong. Allelic frequencies, Hardy–Weinberg equilibriums, gene heterozygosity, effective allele numbers and PIC of the SNPs in different populations were shown in Table 1. Moreover, allele frequencies of the SNP were investigated and performed by χ2 test in all the populations of bovine in our study (Table 1). The data shown here demonstrate that the ranges (from SNP 2409 T>C to 2145 T>C) of minor allele frequencies, heterozygosis, effective allele numbers and PIC of 9 SNPs were from 0.0461 to 0.2116, 0.0879 to 0.3336, 1.0964 to 1.5007, and 0.0841 to 0.2780 among all populations, respectively, and there was significant difference in the allelic frequency only in the SNP 2409 T>C among all populations (Pb 0.05). Furthermore, only SNP 2409 T>C in the total population and subpopulations was not in HWE (Pb 0.05). The possibility of this observation is the occurrence of gene random drift due to the low minor allele frequencies. There are 512(2 9) haplotypes for 9 SNPs in bovine ZBTB38 gene, theoretically, but we found 4 haplotypes (TTGCTGCGG, TTATTGCGG, CCGCTCTAA and CCGCCGCGA). Among them, three common haplotypes (freq. >0.1) were constructed and they also showed strong LDs (Fig. 2A and B). From the result of the linkage disequilibrium analysis (Fig. 2B), we found that 2145 T>C, 2286 T>C, 2457 G>C, 2583 C>T, 2643 G>A and 2676 G>A were tight LDs (r2 >0.33); 2323 G>A and 2325 C>T were tight LDs (r2 =0.96); and 2409 T>C and others were weak LDs (r2 b 0.33). We chose 2145 T>C, 2323 G>A and 2409 T>C as tag SNPs to analyze association, respectively. Meanwhile, 8 body measurement traits were analyzed by comparison of the genotypes of 423 individuals and their phenotypic data. The results of the association analysis of the gene-specific SNP marker were shown
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2145 T>C
2286 T>C
2323 G>A
2325 C>T
2409 T>C
2457 G>C
2583 C>T
2643 G>A
2676 G>A
Fig. 1. DNA sequencing maps from several DNA templates at 9 SNPs of bovine ZBTB38.
(Table 2). At the 2323 G>A tag SNP marker, there are significant effects on the BL (P=0.0488), WH (P=0.0044) and RL (P=0.0314) in the total population. Animals with the genotype AA had higher mean values for WH and RL than those with the GG and GA genotypes (P b 0.05); animals with the genotype AA had higher mean values for BL than those with the GA genotype (P b 0.05). At 2145 T>C and 2409 T>C tag SNP markers, there are no significant effects on 8 body measurement traits in the total population (P > 0.05). In the eight subpopulations, there are significant effects on some body measurement traits, but the data are not shown because the individuals are fewer.
4. Discussion Gene heterozygosity and effective allele numbers were lower for the 9 SNPs. These results clearly indicate that the heredity of these populations and the sites controlling body measurement traits were not stable. Furthermore, the SNP 2409 T>C occurrence in the total population was not in Hardy–Weinberg equilibrium due to gene random drift. This suggests that the selected animals have been endogamous, which could be a result of the intensive selection process of the progeny testing program in order to fulfill beef industry needs. Generally, PIC was classified into the following 3 types: low polymorphism (PIC value b0.25), median polymorphism (0.25 b PIC value b0.5), and high polymorphism (PIC value >0.5) (Mateescu et al., 2005). According to this classification of PIC, most populations belong to the low polymorphism level. Therefore, our data indicate that the low frequency of ZBTB38 minor alleles at bovine ZBTB38 locus was difficult to use to characterize the native Chinese cattle breeds.
If r 2 > 0.33, the linkage disequilibrium was considered strong (Ardlie et al., 2002). Thus, 9 SNPs were divided into 3 inherited units. In every unit each SNP could be as tag SNP, and among the unit every pair had SNPs strong LDs (r2 > 0.33). Therefore, 2145 T>C, 2323 G>A and 2409 T>C were chosen as tag SNPs to analyze the association. The body measurement traits are affected by many factors, such as genotype, sex, age, breed, herd, location and other random environment factors. However, we have established one new statistical model in which the three factors (breed, herd, and location) were involved and then we have employed the least-squares method in GLM procedure of SAS software to do the related analysis, and we did not find significant difference (P>0.05) (data not shown). For the 2323 G>A tag SNP marker at bovine ZBTB38 gene, there are significant effects on the BL, WH and RL in 423 individuals (Table 2). Moreover, the G>A missense mutation of valine to isoleucine, results in the change of the part of phenotypic variation, especially on the BL, WH and RL phenotypes in cattle breeds. Therefore, we assumed that the mutation for 2323 G>A could have an important influence on many minor genes, which are involved in body length, withers height and rump length in bovine. A number of studies have recently demonstrated that the functional SNPs in ZBTB38 gene have a plausible biological role in height and other stature indexes in human (Gudbjartsson et al., 2008; Lettre et al., 2008; Liu et al., 2010c; Sanna et al., 2008; Weedon et al., 2008). Gudbjartsson et al. (2008) found that the strongest association was with the A allele of rs6763931 (effect= 7.4 ±0.7, P = 1.4 × 10−27), which was the SNP in the region with the most significant correlation with the expression of ZBTB38 in blood and in adipose tissue, the same allele being positively correlated to height and expression (P= 5.2 × 10 −13 in blood and 5.6 × 10−6 in adipose tissue). Moreover, Lettre et al. (2008) identified several new loci associated with height and other statures are located, including
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Table 1 Genotypes, allele frequencies and population genetic indexes of 9 polymorphisms in Exon 1 of ZBTB38. SNP
AA change
Breeds
Genotypes (number of animals)
2145 T>C
S715S
2286 T>C
D762D
2323 G>A
V775I
2325 C>T
V775I
2409 T>C
A803A
2457 G>C
T819T
2583 C>T
L861L
2643 G>A
T881T
2676 G>A
G892G
QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC
TT(31) TT(50) TT(20) TT(32) TT(26) TT(14) TT(47) TT(49) TT(269) TT(36) TT(51) TT(22) TT(37) TT(27) TT(16) TT(47) TT(49) TT(285) GG(37) GG(45) GG(46) GG(37) GG(45) GG(46) GG(34) GG(22) GG(312) CC(37) CC(43) CC(46) CC(38) CC(45) CC(46) CC(33) CC(22) CC(310) TT(44) TT(55) TT(48) TT(50) TT(50) TT(43) TT(49) TT(50) TT(389) GG(38) GG(54) GG(28) GG(43) GG(35) GG(23) GG(48) GG(49) GG(318) CC(38) CC(53) CC(27) CC(43) CC(36) CC(23) CC(48) CC(49) CC(317) GG(38) GG(53) GG(27) GG(43) GG(35) GG(23) GG(48) GG(49) GG(316) GG(35)
TC(14) TC(7) TC(28) TC(22) TC(31) TC(24) TC(2) TC(1) TC(129) TC(10) TC(6) TC(27) TC(18) TC(30) TC(25) TC(2) TC(1) TC(119) GA(10) GA(11) GA(7) GA(19) GA(13) GA(6) GA(14) GA(25) GA(105) CT(10) CT(13) CT(7) CT(18) CT(13) CT(6) CT(15) CT(25) CT(107) TC(2) TC(2) TC(5) TC(6) TC(9) TC(5) TC(0) TC(0) TC(29) GC(8) GC(3) GC(21) GC(12) GC(23) GC(25) GC(1) GC(1) GC(94) CT(8) CT(4) CT(22) CT(11) CT(21) CT(25) CT(1) CT(1) CT(93) GA(8) GA(4) GA(22) GA(12) GA(23) GA(26) GA(1) GA(1) GA(97) GA(10)
CC(2) CC(0) CC(5) CC(2) CC(2) CC(14) CC(0) CC(0) CC(25) CC(1) CC(0) CC(4) CC(1) CC(2) CC(11) CC(0) CC(0) CC(19) AA(0) AA(1) AA(0) AA(0) AA(1) AA(0) AA(1) AA(3) AA(6) TT(0) TT(1) TT(0) TT(0) TT(1) TT(0) TT(1) TT(3) TT(6) CC(1) CC(0) CC(0) CC(0) CC(0) CC(4) CC(0) CC(0) CC(5) CC(1) CC(0) CC(4) CC(1) CC(1) CC(4) CC(0) CC(0) CC(11) TT(1) TT(0) TT(4) TT(2) TT(2) TT(4) TT(0) TT(0) TT(13) AA(1) AA(0) AA(4) AA(1) AA(1) AA(3) AA(0) AA(0) AA(10) AA(2)
Total number of animal
Minor allele frequency
Heterozygosity
P (HWE)
Effective allele numbers
PIC
47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47
0.1915 0.0614 0.3585 0.2321 0.2966 0.5000 0.0204 0.0100 0.2116 0.1277 0.0526 0.3302 0.1786 0.2881 0.4519 0.0204 0.0100 0.1856 0.1064 0.1140 0.0660 0.1696 0.1271 0.0577 0.1633 0.3100 0.1383 0.1064 0.1316 0.0660 0.1607 0.1271 0.0577 0.1735 0.3100 0.1407 0.0426 0.0175 0.0472 0.0536 0.0763 0.1250 0.0000 0.0000 0.0461 0.1064 0.0263 0.2736 0.1250 0.2119 0.3173 0.0102 0.0100 0.1371 0.1064 0.0351 0.2830 0.1339 0.2119 0.3173 0.0102 0.0100 0.1407 0.1064 0.0351 0.2830 0.1250 0.2119 0.3077 0.0102 0.0100 0.1383 0.1489
0.3096 0.1153 0.4600 0.3565 0.4173 0.5000 0.0400 0.0198 0.3336 0.2227 0.0997 0.4423 0.2934 0.4102 0.4954 0.0400 0.0198 0.3023 0.1901 0.2021 0.1234 0.2817 0.2219 0.1087 0.2732 0.4278 0.2383 0.1901 0.2285 0.1234 0.2698 0.2219 0.1087 0.2868 0.4278 0.2418 0.0815 0.0345 0.0899 0.1014 0.1409 0.2188 0.0000 0.0000 0.0879 0.1901 0.0512 0.3975 0.2188 0.3340 0.4332 0.0202 0.0198 0.2366 0.1901 0.0677 0.4058 0.2320 0.3340 0.4332 0.0202 0.0198 0.2418 0.1901 0.0677 0.4058 0.2188 0.3340 0.4260 0.0202 0.0198 0.2383 0.2535
0.9666 0.8852 0.5570 0.7474 0.1378 0.8574 0.9894 0.9975 0.2098 0.9541 0.9158 0.5434 0.7740 0.1841 0.9776 0.9894 0.9975 0.3619 0.7167 0.9441 0.8759 0.3108 0.9985 0.9071 0.9501 0.4906 0.6951 0.7167 0.9999 0.8759 0.3582 0.9985 0.9071 0.8943 0.4906 0.6350 0.0047 0.9910 0.9371 0.9142 0.8178 0.0003 – – 0.0000 0.7727 0.9794 0.9997 0.9884 0.4379 0.7314 0.9974 0.9975 0.4565 0.7727 0.9630 0.9863 0.5180 0.8801 0.7314 0.9974 0.9975 0.1765 0.7727 0.9630 0.9863 0.9884 0.4379 0.4567 0.9974 0.9975 0.7382 0.5450
1.4485 1.1303 1.8517 1.5540 1.7160 2.0000 1.0416 1.0202 1.5007 1.2865 1.1108 1.7932 1.4152 1.6956 1.9817 1.0416 1.0202 1.4332 1.2348 1.2532 1.1407 1.3922 1.2852 1.1220 1.3759 1.7476 1.3129 1.2348 1.2962 1.1407 1.3694 1.2852 1.1220 1.4020 1.7476 1.3188 1.0887 1.0357 1.0988 1.1128 1.1640 1.2800 1.0000 1.0000 1.0964 1.2348 1.0540 1.6597 1.2800 1.5014 1.7644 1.0206 1.0202 1.3100 1.2348 1.0726 1.6830 1.3021 1.5014 1.7644 1.0206 1.0202 1.3188 1.2348 1.0726 1.6830 1.2800 1.5014 1.7423 1.0206 1.0202 1.3129 1.3396
0.2617 0.1086 0.3542 0.2930 0.3302 0.3750 0.0392 0.0196 0.2780 0.1979 0.0948 0.3445 0.2503 0.3261 0.3727 0.0392 0.0196 0.2566 0.1721 0.1816 0.1157 0.2420 0.1973 0.1028 0.2359 0.3363 0.2099 0.1721 0.2024 0.1157 0.2334 0.1973 0.1028 0.2456 0.3363 0.2125 0.0782 0.0339 0.0858 0.0963 0.1310 0.1948 0.0000 0.0000 0.0841 0.1721 0.0499 0.3185 0.1948 0.2782 0.3394 0.0200 0.0196 0.2086 0.1721 0.0654 0.3235 0.2051 0.2782 0.3394 0.0200 0.0196 0.2125 0.1721 0.0654 0.3235 0.1948 0.2782 0.3353 0.0200 0.0196 0.2099 0.2214
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Table 1 (continued) SNP
AA change
Breeds
Genotypes (number of animals)
QI NY JR XN LX SL XL Total
GG(51) GG(22) GG(37) GG(27) GG(16) GG(47) GG(49) GG(284)
GA(6) GA(27) GA(18) GA(30) GA(25) GA(2) GA(1) GA(119)
AA(0) AA(4) AA(1) AA(2) AA(11) AA(0) AA(0) AA(20)
Total number of animal
Minor allele frequency
Heterozygosity
P (HWE)
Effective allele numbers
PIC
57 53 56 59 52 49 50 423
0.0526 0.3302 0.1786 0.2881 0.4519 0.0204 0.0100 0.1879
0.0997 0.4423 0.2934 0.4102 0.4954 0.0400 0.0198 0.3052
0.9158 0.5434 0.7740 0.1841 0.9776 0.9894 0.9975 0.2729
1.1108 1.7932 1.4152 1.6956 1.9817 1.0416 1.0202 1.4393
0.0948 0.3445 0.2503 0.3261 0.3727 0.0392 0.0196 0.2587
T T C C
G A G G
C T C C
T T T C
G G C G
C C T C
G G A G
2676 G>A
2643 G>A
2583 C>T
2457 G>C
2409 T>C
2325 C>T
2286 T>C T T C C
2323 G>A
Hap. Ht 1 Ht 2 Ht 3 Ht 4 others
2145 T>C
HWE, Hardy–Weinberg equilibrium.
G G A A
1
Freq. 0.643 0.137 0.130 0.041 0.049
2 85
3 3
4
4
5
96 3
4
0 0
2
18 18
6 0
2 66
59
0 2
1 65
58
8 96
97 0
2 2
66 59
7 95
9 66
64 65
18 3
3 93
83
A. Haplotypes in ZBTB38
B. LDs among ZBTB38 polymorphism
Fig. 2. Gene haplotype and LD coefficients in ZBTB38. (A) Haplotypes of ZBTB38. Haplotypes with frequency >0.03 are presented. Others contain rare haplotypes. (B) Linkage disequilibrium coefficient ( D′ and r2) among ZBTB38 polymorphisms. The numbers are r2 value (%), and values of colored frame are above 33%.
Table 2 Association analysis of 2323 G>A or 2325 C>T SNP genotypes with body measurement traits at bovine ZBTB38 gene. SNP
G2323A
a,b A,B
Genotypes
GG GA AA P value
Traits (cm, mean ± SE) BL
WH
HH
RL
HW
CD
HG
PBW
147.39 ± 0.67ab 145.32 ± 1.32a 154.56 ± 4.40b 0.0448
132.21 ± 0.50A 131.71 ± 1.02A 142.71 ± 3.69B 0.0044
161.59 ± 4.44 161.79 ± 0.97 163.79 ± 4.22 0.9956
44.30 ± 0.28a 43.99 ± 0.43a 49.24 ± 1.98b 0.0314
45.90 ± 0.33 46.23 ± 0.57 48.36 ± 2.33 0.4961
70.67 ± 0.38 70.41 ± 0.70 72.96 ± 2.56 0.6051
192.57 ± 1.11 191.38 ± 2.31 196.92 ± 15.73 0.5898
25.66 ± 0.28 26.08 ± 0.67 25.11 ± 1.98 0.7318
means with different superscripts were significantly different (P b 0.05). means with different superscripts were significantly different (P b 0.01).
ZBTB38. ZBTB38 locus (rs724016, P = 5.0× 10−12), which was in an intron of the methyl-DNA-binding transcriptional repressor gene, and other genes may themselves influence height, but further work would be needed to elucidate the relevant pathways and mechanisms. Meanwhile, a SNP in ZBTB38 showed suggestive association in a previous genome-wide association scan for height (Sanna et al., 2008). Following, using data from GWA studies, a SNP of human ZBTB38 gene (rs6440003, P=1.8×10−24) was also associated with adult height in their study (Weedon et al., 2008). Above all, although many studies focus on the association of ZBTB38 gene variants with body measurement traits in human, little has been reported for bovine and other livestock. Only Liu et al. (2010a, 2010b, 2010c) discovered that the 841 A>G SNP in the coding region of the bovine ZBTB38 gene was significantly associated with body measurement traits in 722 individuals. The analysis of 841 A>G SNP marker showed that there were significant effects on the BL (P = 0.0389) in 722 individuals, significant effects on the HH (P = 0.0173) and HG (P = 0.0147) in QI population, as well as significant effects on the WH (P = 0.0094) in XL population. Therefore, based on these results of the genome-wide approach in human and according to the conformity of the conservation of biological evolution in different organisms, we applied the research results from human ZBTB38 in analyzing polymorphism and genetic effect in cattle ZBTB38 gene locus. The new findings are that the 2323 G>A and 2325 C>T SNPs of bovine ZBTB38 were significantly associated with body
length, withers height and rump length (Table 2), which are consistent with the human data. In summary, we identified nine SNPs in the ZBTB38 gene and investigated its association in different bovine breed populations. Genotyping, minor allele frequencies, heterozygosis, effective allele numbers, PIC, HWE, haplotype, linkage disequilibrium and association analysis performed on the tag SNPs, demonstrated that 2323 G>A and 2325 C>T SNPs were strong linkage and significantly associated with body measurement traits in bovine. Therefore, further work will be necessary to use the SNP for marker-assisted selection (MAS) in other breeds and larger population. It is also significant to investigate whether the ZBTB38 gene plays a role on development of those traits and whether it involves in linkage disequilibrium with other causative mutations. Acknowledgements This work was supported by the Shaanxi Provincial Natural Science Foundation of China (2011JQ3006), the National Twelfth “Five Year” Science and Technology Support Project (2011BAD28B04-03), the Beef cattle and Yak Industrial Technology System Project (CARS-38), and the Changjiang Scholars and Innovative Research Team Support Plan of The Ministry of Education (IRT0940). Moreover, the bovine populations were supported by the Qinchuan beef cattle breeding center of Shaanxi province, Nanyang, Jiaxian and Xianan cattle
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breeding center of Henan province, Luxi cattle breeding center of Shandong province, and Snow dragon beef cattle breeding center of Liaoning province (PR China). References Ardlie, K.G., Kruglyak, L., Seielstad, M., 2002. Patterns of linkage disequilibrium in the human genome. Nat. Rev. Genet. 3, 299–309. Barrett, J.C., Fry, B., Maller, J., Daly, M.J., 2005. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics (Oxford, England), 21, pp. 263–265. Binder, G., et al., 2008. The endocrine phenotype in Silver-Russell syndrome is defined by the underlying epigenetic alteration. J. Clin. Endocrinol. Metab. 93, 1042–1047. Filion, G.J., Zhenilo, S., Salozhin, S., Yamada, D., Prokhortchouk, E., Defossez, P.A., 2006. A family of human zinc finger proteins that bind methylated DNA and repress transcription. Mol. Cell. Biol. 26, 169–181. Gabriel, S.B., et al., 2002. The structure of haplotype blocks in the human genome. Science 296, 2225–2229. Gilbert, R.P., Bailey, D.R.C., Shannon, N.H., 1993. Linear body measurements of cattle before and after 20 years of selection for post weaning gain when fed two different diets. J. Anim. Sci. 71, 1712–1720. Gudbjartsson, D.F., et al., 2008. Many sequence variants affecting diversity of adult human height. Nat. Genet. 40, 609–615. Kiefer, H., Hermitte, F.C., Ravassard, P., Bayard, E., Brunet, I., Mallet, J., 2005. ZENON, a novel POZ Kruppel-like DNA binding protein associated with differentiation and/ or survival of late postmitotic neurons. Mol. Cell. Biol. 25, 1713–1729. Lettre, G., et al., 2008. Identification of ten loci associated with height highlights new biological pathways in human growth. Nat. Genet. 40, 584–591.
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Gene journal homepage: www.elsevier.com/locate/gene
ZBTB38 gene polymorphism associated with body measurement traits in native Chinese cattle breeds Yongfeng Liu a, b, Linsen Zan b,⁎, Yaping Xin b, Wanqiang Tian b, Linqiang Li a, Hongcheng Wang b a b
College of Food Engineering and Nutritional Science, Shaanxi Normal University, 710062, Xi'an, Shaanxi, PR China College of Animal Science and Technology, Northwest A & F University, Yangling 712100, Shaanxi, PR China
a r t i c l e
i n f o
Article history: Accepted 21 October 2012 Available online 5 November 2012 Keywords: Cattle ZBTB38 gene SNP Association analysis Body measurement
a b s t r a c t Body measurement traits, influenced by genes and environmental factors, play numerous important roles in the value assessment of productivity and economy. In this study, we investigated the association between genetic polymorphisms of the zinc finger and BTB domain containing 38 gene (ZBTB38) and body measurement traits in native Chinese cattle. Using direct DNA sequencing in 423 individuals of 8 different cattle subpopulations, 9 novel polymorphisms were identified for genotyping within 647 bp region of exon 1 of ZBTB38. Linkage disequilibrium and association analysis revealed that two coding exon polymorphisms (2323 G>A and 2325 C>T polymorphisms), missense mutations valine GTC(T) to isoleucine ATC(T), were associated with body length (BL), withers height (WH) and rump length (RL). Furthermore, the analysis of 2323 G>A and 2325 C>T SNP markers shows that there are significant effects on the BL (P=0.0488), WH (P=0.0044) and RL (P=0.0314) in the total population. These results clearly suggest that the ZBTB38 gene is among the target genes for body measurement traits in bovine breeding, and provide data for establishment of an animal model using cattle to study big animal body type. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Body measurement traits have been considered important in beef production because these are major factors that affect animal growth and development, as well as production of meat (Liu et al., 2010a, 2010b). Therefore, a study of body measurement in cattle is important in the value assessment of productivity and economy. Zinc finger and BTB domain containing 38 (ZBTB38), previously identified the murine CtBP (C-terminal binding protein)-interacting BTB (broad complex/tramtrack/brica-brac) zinc finger protein (CIBZ, also named ZENON in rat and ZBTB38 in human), is a likely candidate gene for body measurement traits (Kiefer et al., 2005; Sasai et al., 2005). Sasai et al. (2005) described the cloning and characterization of ZBTB38, and found that ZBTB38 repressed transcription via two independent domains, the BTB domain and a proximal domain referred to as RD2, in histone deacetylase (HDAC)-independent and -dependent
Abbreviations: ZBTB38, zinc finger and BTB domain containing 38; CtBP, C-terminal binding protein; BTB, broad complex, tramtrack and bric-a-brac; CIBZ, murine CtBP-interacting BTB zinc finger protein; ZENON, zinc finger gene expressed in neurons; HDAC, histone deacetylase; IGF, insulin-like growth factor; BL, body length; WH, withers height; HH, hip height; RL, rump length; HW, hip width; CD, chest depth; HG, heart girth; PBW, pin bone width; bp, base pairs; MAS, marker-assisted selection; PCR, polymerase chain reaction; SNP, single nucleotide polymorphism; HWE, Hardy–Weinberg equilibriums; LD, linkage disequilibrium; RFLP, restriction fragment length polymorphism; PIC, polymorphism information content; CDS, coding sequence; nt, nucleotides; GWA, genome wide association. ⁎ Corresponding author. Tel./fax: +86 29 87091923. E-mail address: [email protected] (L. Zan). 0378-1119/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.gene.2012.10.026
manner, respectively. ZBTB38 specifically interacted with CtBPs via RD2 and relocalized CtBPs to pericentromeric foci, suggesting that ZBTB38 exerted its repression activity via recruitment of the CtBP complex (Sasai et al., 2005). The rat ZBTB38 regulated transcription (independent of methylation) of the tyrosine hydroxylase gene, the rate-limiting enzyme of catecholamine biosynthesis (Filion et al., 2006). This was the site at which epigenetic errors of imprinting result in either the Beckwith–Wiedemann syndrome of somatic overgrowth or the growth retardation syndrome of Russell–Silver (Binder et al., 2008). ZBTB38, belonged to a novel class of methylated DNAbinding proteins, could repress Gal4-driven thymidine kinase or SV40 promoters by functionally interacting with CtBP in a histone deacetylase-dependent manner, and ZBTB38 lacks a signature methyl-CpG-binding domain but can bind methylated DNA through the conserved zinc fingers (Oikawa et al., 2008). Thus, ZBTB38 affected adult stature through regulation of the production of insulin-like growth factor (IGF)-II, perhaps during in utero development when IGF-II is known to be one of the determinants of fetal growth (Gudbjartsson et al., 2008). Based on the importance of ZBTB38 in adult stature morphogenesis and growth of the skeleton from determinations in human, ZBTB38 could be an attractive candidate gene for body measurement traits in bovine. Screening of ZBTB38 was performed by direct sequencing to detect polymorphisms, and examined their genetic association with body measurement traits in Bos taurus. Here, we present the 9 novel polymorphisms identified in ZBTB38 and the results of an association study with the body measurement traits in native Chinese beef cattle breeds.
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2. Material and methods 2.1. Animals and phenotypic data For the gene variants that identified, allele frequencies were estimated on a restricted population composed of unrelated, randomly selected purebred and crossbred individuals representing 8 breeds including Qinchuan (QC, n = 47, Shaanxi province of China), Qinchuan improvement steers (QI, n = 57, Shaanxi province of China), Nanyang (NY, n = 53, Henan province of China), Jiaxian red (JR, n = 56, Henan province of China), Xia'nan (XN, n =59, Henan province of China), Luxi (LX, n = 52, Shandong province of China), Simmental and Luxi crossbred steers (SL, n = 49, Shandong province of China), and Xuelong (Angus crossed with descendant of male Japanese Black cattle and female Fuzhou cattle) (XL, n = 50, Liaoning province of China). Meanwhile, the following traits, body length (BL), withers height (WH), hip height (HH), rump length (RL), hip width (HW), chest depth (CD), heart girth (HG) and pin bone width (PBW) were measured (Gilbert et al., 1993). For each of the body measurement traits, we measured the same one trait with the same individuals to minimize error. DNA samples were extracted from leukocytes and tissue samples using standard phenol–chloroform protocol (Mullenbach et al., 1989). 2.2. PCR amplification, sequencing and polymorphism identification The bovine ZBTB38 gene has only one exon, and this gene also has one exon in horse, dog, human, mouse, rat, chicken and other species. In addition, the ZBTB38 gene's one coding region (exon) is scattered over about 60695 base pairs (bp) of genomic DNA (GenBank accession No. NC_007299) on chromosomal 1. The 4151 bp mRNA of ZBTB38 gene (GenBank accession No. XM_589799) is translated into the 1205-amino acid sequence. The 3615 bp coding sequences domain and the putative amino acid sequence of bovine ZBTB38 share 87% and 88% similarity to that of human. According to the sequence of bovine ZBTB38 gene, one pair of primers (5′-CTG TGA GTA ACG GCA GTG AGA AC-3′ and 5′-GTC ACT GGC ATC GTC AAA CAT C-3′) was designed to amplify a 647 bp product of the ZBTB38 exon 1. Polymerase chain reaction (PCR) was performed in 30 μl reaction mixtures containing 50 ng DNA templates, 10 pM of each primer, 0.20 mM dNTP, 2.5 mM MgCl2 and 0.5 U Taq DNA polymerase (TaKaRa, Dalian, PR China). The PCR protocol was 95 °C for 5 min followed by 30 cycles of 94 °C for 30 s, 63 °C annealing for 30 s, and 72 °C for 30 s, and a final extension at 72 °C for 10 min. The products were purified with a Wizard Prep PCR purification kit (Shanghai Bioasia Biotechnology, PR China) and sequenced (Beijing Aolaibo Biotechnology, PR China; Applied Biosystems 3730xl DNA sequencer, Foster city, CA, USA). Genetic polymorphisms in the ZBTB38 were identified by sequencing PCR products from eight breeds, and compared with each other using SeqMan (DNASTAR, Inc., Madison, WI, USA). Single nucleotide polymorphisms (SNPs), including 2145 T>C, 2286 T>C, 2323 G>A, 2325 C>T, 2409 T>C, 2457 G>C, 2583 C>T, 2643 G>A and 2676 G>A were chosen for further analysis. 2.3. Statistic analysis The following items were statistically analyzed according to the previous approaches (Nei and Li, 1979; Nei and Roychoudhury, 1974), including genotypic numbers, allelic frequencies, Hardy–Weinberg equilibriums (HWE), gene heterozygosity, effective allele numbers and polymorphism information content (PIC). The association between SNP marker genotypes of the ZBTB38 gene and records of body measurement traits (BL, WH, HH, RL, HW, CD, HG and PBW) was analyzed by the least-squares method as applied in the GLM procedure of SAS
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(SAS Institute Inc., Cary, NC, USA), and according to the following statistical linear model: Yijkl ¼ μ þ Gi þ Sj þ BFk þ Mal þ εijkl ; where Yijkl is the observed body measurement trait, μ is the overall mean for each trait, Gi is the genotype effect, Sj is the fixed effect of sex, BFk is the fixed effect of breed and farm, Mal is the regression variable for measure age, and εijkl is the random environment effect. For the haplotype analyses, the model was fit with the same covariates in a similar manner. A widely used measure of linkage disequilibrium (LD) was examined between all pairs of biallelic loci, D′ (the correlation coefficient [Dalta |D′|]) and r2, and strength of LD between pairs of SNPs was measured as D′ using Haploview (Barrett et al., 2005; Gabriel et al., 2002). Haplotypes and their frequencies were inferred using the algorithm developed by Stephens et al. (2001). Phase probabilities of each site were calculated for each individual using PHASE software (http://depts.washington.edu/ventures/UW_Technology/Express_ Licenses/PHASEv2.php) (Stephens et al., 2001). 3. Results 3.1. Polymorphism and sequencing of the ZBTB38 gene By direct DNA sequencing, 9 polymorphisms were identified in ZBTB38 gene exon 1. The 9 SNPs, namely, 2145 T>C, 2286 T>C, 2323 G>A, 2325 C>T, 2409 T>C, 2457 G>C, 2583 C>T, 2643 G>A and 2676 G>A, were in 647 bp PCR products which DNA sequencing maps are shown in Fig. 1. The 2323 G>A and 2325 C>T mutations, missense mutations valine GTC(T) to isoleucine ATC(T), were also observed at position 775 of the coded amino acids; and the other mutations were synonymous mutations (Table 1). 3.2. Genetic variation in different breeds and association analysis We further analyzed the genotype of unrelated animals from 8 different bovine breeds, including Qinchuan, Qinchuan improvement steers, Nanyang, Jiaxian red, Xia'nan, Luxi, Simmental and Luxi crossbred steers, and Xuelong. Allelic frequencies, Hardy–Weinberg equilibriums, gene heterozygosity, effective allele numbers and PIC of the SNPs in different populations were shown in Table 1. Moreover, allele frequencies of the SNP were investigated and performed by χ2 test in all the populations of bovine in our study (Table 1). The data shown here demonstrate that the ranges (from SNP 2409 T>C to 2145 T>C) of minor allele frequencies, heterozygosis, effective allele numbers and PIC of 9 SNPs were from 0.0461 to 0.2116, 0.0879 to 0.3336, 1.0964 to 1.5007, and 0.0841 to 0.2780 among all populations, respectively, and there was significant difference in the allelic frequency only in the SNP 2409 T>C among all populations (Pb 0.05). Furthermore, only SNP 2409 T>C in the total population and subpopulations was not in HWE (Pb 0.05). The possibility of this observation is the occurrence of gene random drift due to the low minor allele frequencies. There are 512(2 9) haplotypes for 9 SNPs in bovine ZBTB38 gene, theoretically, but we found 4 haplotypes (TTGCTGCGG, TTATTGCGG, CCGCTCTAA and CCGCCGCGA). Among them, three common haplotypes (freq. >0.1) were constructed and they also showed strong LDs (Fig. 2A and B). From the result of the linkage disequilibrium analysis (Fig. 2B), we found that 2145 T>C, 2286 T>C, 2457 G>C, 2583 C>T, 2643 G>A and 2676 G>A were tight LDs (r2 >0.33); 2323 G>A and 2325 C>T were tight LDs (r2 =0.96); and 2409 T>C and others were weak LDs (r2 b 0.33). We chose 2145 T>C, 2323 G>A and 2409 T>C as tag SNPs to analyze association, respectively. Meanwhile, 8 body measurement traits were analyzed by comparison of the genotypes of 423 individuals and their phenotypic data. The results of the association analysis of the gene-specific SNP marker were shown
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2145 T>C
2286 T>C
2323 G>A
2325 C>T
2409 T>C
2457 G>C
2583 C>T
2643 G>A
2676 G>A
Fig. 1. DNA sequencing maps from several DNA templates at 9 SNPs of bovine ZBTB38.
(Table 2). At the 2323 G>A tag SNP marker, there are significant effects on the BL (P=0.0488), WH (P=0.0044) and RL (P=0.0314) in the total population. Animals with the genotype AA had higher mean values for WH and RL than those with the GG and GA genotypes (P b 0.05); animals with the genotype AA had higher mean values for BL than those with the GA genotype (P b 0.05). At 2145 T>C and 2409 T>C tag SNP markers, there are no significant effects on 8 body measurement traits in the total population (P > 0.05). In the eight subpopulations, there are significant effects on some body measurement traits, but the data are not shown because the individuals are fewer.
4. Discussion Gene heterozygosity and effective allele numbers were lower for the 9 SNPs. These results clearly indicate that the heredity of these populations and the sites controlling body measurement traits were not stable. Furthermore, the SNP 2409 T>C occurrence in the total population was not in Hardy–Weinberg equilibrium due to gene random drift. This suggests that the selected animals have been endogamous, which could be a result of the intensive selection process of the progeny testing program in order to fulfill beef industry needs. Generally, PIC was classified into the following 3 types: low polymorphism (PIC value b0.25), median polymorphism (0.25 b PIC value b0.5), and high polymorphism (PIC value >0.5) (Mateescu et al., 2005). According to this classification of PIC, most populations belong to the low polymorphism level. Therefore, our data indicate that the low frequency of ZBTB38 minor alleles at bovine ZBTB38 locus was difficult to use to characterize the native Chinese cattle breeds.
If r 2 > 0.33, the linkage disequilibrium was considered strong (Ardlie et al., 2002). Thus, 9 SNPs were divided into 3 inherited units. In every unit each SNP could be as tag SNP, and among the unit every pair had SNPs strong LDs (r2 > 0.33). Therefore, 2145 T>C, 2323 G>A and 2409 T>C were chosen as tag SNPs to analyze the association. The body measurement traits are affected by many factors, such as genotype, sex, age, breed, herd, location and other random environment factors. However, we have established one new statistical model in which the three factors (breed, herd, and location) were involved and then we have employed the least-squares method in GLM procedure of SAS software to do the related analysis, and we did not find significant difference (P>0.05) (data not shown). For the 2323 G>A tag SNP marker at bovine ZBTB38 gene, there are significant effects on the BL, WH and RL in 423 individuals (Table 2). Moreover, the G>A missense mutation of valine to isoleucine, results in the change of the part of phenotypic variation, especially on the BL, WH and RL phenotypes in cattle breeds. Therefore, we assumed that the mutation for 2323 G>A could have an important influence on many minor genes, which are involved in body length, withers height and rump length in bovine. A number of studies have recently demonstrated that the functional SNPs in ZBTB38 gene have a plausible biological role in height and other stature indexes in human (Gudbjartsson et al., 2008; Lettre et al., 2008; Liu et al., 2010c; Sanna et al., 2008; Weedon et al., 2008). Gudbjartsson et al. (2008) found that the strongest association was with the A allele of rs6763931 (effect= 7.4 ±0.7, P = 1.4 × 10−27), which was the SNP in the region with the most significant correlation with the expression of ZBTB38 in blood and in adipose tissue, the same allele being positively correlated to height and expression (P= 5.2 × 10 −13 in blood and 5.6 × 10−6 in adipose tissue). Moreover, Lettre et al. (2008) identified several new loci associated with height and other statures are located, including
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Table 1 Genotypes, allele frequencies and population genetic indexes of 9 polymorphisms in Exon 1 of ZBTB38. SNP
AA change
Breeds
Genotypes (number of animals)
2145 T>C
S715S
2286 T>C
D762D
2323 G>A
V775I
2325 C>T
V775I
2409 T>C
A803A
2457 G>C
T819T
2583 C>T
L861L
2643 G>A
T881T
2676 G>A
G892G
QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC QI NY JR XN LX SL XL Total QC
TT(31) TT(50) TT(20) TT(32) TT(26) TT(14) TT(47) TT(49) TT(269) TT(36) TT(51) TT(22) TT(37) TT(27) TT(16) TT(47) TT(49) TT(285) GG(37) GG(45) GG(46) GG(37) GG(45) GG(46) GG(34) GG(22) GG(312) CC(37) CC(43) CC(46) CC(38) CC(45) CC(46) CC(33) CC(22) CC(310) TT(44) TT(55) TT(48) TT(50) TT(50) TT(43) TT(49) TT(50) TT(389) GG(38) GG(54) GG(28) GG(43) GG(35) GG(23) GG(48) GG(49) GG(318) CC(38) CC(53) CC(27) CC(43) CC(36) CC(23) CC(48) CC(49) CC(317) GG(38) GG(53) GG(27) GG(43) GG(35) GG(23) GG(48) GG(49) GG(316) GG(35)
TC(14) TC(7) TC(28) TC(22) TC(31) TC(24) TC(2) TC(1) TC(129) TC(10) TC(6) TC(27) TC(18) TC(30) TC(25) TC(2) TC(1) TC(119) GA(10) GA(11) GA(7) GA(19) GA(13) GA(6) GA(14) GA(25) GA(105) CT(10) CT(13) CT(7) CT(18) CT(13) CT(6) CT(15) CT(25) CT(107) TC(2) TC(2) TC(5) TC(6) TC(9) TC(5) TC(0) TC(0) TC(29) GC(8) GC(3) GC(21) GC(12) GC(23) GC(25) GC(1) GC(1) GC(94) CT(8) CT(4) CT(22) CT(11) CT(21) CT(25) CT(1) CT(1) CT(93) GA(8) GA(4) GA(22) GA(12) GA(23) GA(26) GA(1) GA(1) GA(97) GA(10)
CC(2) CC(0) CC(5) CC(2) CC(2) CC(14) CC(0) CC(0) CC(25) CC(1) CC(0) CC(4) CC(1) CC(2) CC(11) CC(0) CC(0) CC(19) AA(0) AA(1) AA(0) AA(0) AA(1) AA(0) AA(1) AA(3) AA(6) TT(0) TT(1) TT(0) TT(0) TT(1) TT(0) TT(1) TT(3) TT(6) CC(1) CC(0) CC(0) CC(0) CC(0) CC(4) CC(0) CC(0) CC(5) CC(1) CC(0) CC(4) CC(1) CC(1) CC(4) CC(0) CC(0) CC(11) TT(1) TT(0) TT(4) TT(2) TT(2) TT(4) TT(0) TT(0) TT(13) AA(1) AA(0) AA(4) AA(1) AA(1) AA(3) AA(0) AA(0) AA(10) AA(2)
Total number of animal
Minor allele frequency
Heterozygosity
P (HWE)
Effective allele numbers
PIC
47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47 57 53 56 59 52 49 50 423 47
0.1915 0.0614 0.3585 0.2321 0.2966 0.5000 0.0204 0.0100 0.2116 0.1277 0.0526 0.3302 0.1786 0.2881 0.4519 0.0204 0.0100 0.1856 0.1064 0.1140 0.0660 0.1696 0.1271 0.0577 0.1633 0.3100 0.1383 0.1064 0.1316 0.0660 0.1607 0.1271 0.0577 0.1735 0.3100 0.1407 0.0426 0.0175 0.0472 0.0536 0.0763 0.1250 0.0000 0.0000 0.0461 0.1064 0.0263 0.2736 0.1250 0.2119 0.3173 0.0102 0.0100 0.1371 0.1064 0.0351 0.2830 0.1339 0.2119 0.3173 0.0102 0.0100 0.1407 0.1064 0.0351 0.2830 0.1250 0.2119 0.3077 0.0102 0.0100 0.1383 0.1489
0.3096 0.1153 0.4600 0.3565 0.4173 0.5000 0.0400 0.0198 0.3336 0.2227 0.0997 0.4423 0.2934 0.4102 0.4954 0.0400 0.0198 0.3023 0.1901 0.2021 0.1234 0.2817 0.2219 0.1087 0.2732 0.4278 0.2383 0.1901 0.2285 0.1234 0.2698 0.2219 0.1087 0.2868 0.4278 0.2418 0.0815 0.0345 0.0899 0.1014 0.1409 0.2188 0.0000 0.0000 0.0879 0.1901 0.0512 0.3975 0.2188 0.3340 0.4332 0.0202 0.0198 0.2366 0.1901 0.0677 0.4058 0.2320 0.3340 0.4332 0.0202 0.0198 0.2418 0.1901 0.0677 0.4058 0.2188 0.3340 0.4260 0.0202 0.0198 0.2383 0.2535
0.9666 0.8852 0.5570 0.7474 0.1378 0.8574 0.9894 0.9975 0.2098 0.9541 0.9158 0.5434 0.7740 0.1841 0.9776 0.9894 0.9975 0.3619 0.7167 0.9441 0.8759 0.3108 0.9985 0.9071 0.9501 0.4906 0.6951 0.7167 0.9999 0.8759 0.3582 0.9985 0.9071 0.8943 0.4906 0.6350 0.0047 0.9910 0.9371 0.9142 0.8178 0.0003 – – 0.0000 0.7727 0.9794 0.9997 0.9884 0.4379 0.7314 0.9974 0.9975 0.4565 0.7727 0.9630 0.9863 0.5180 0.8801 0.7314 0.9974 0.9975 0.1765 0.7727 0.9630 0.9863 0.9884 0.4379 0.4567 0.9974 0.9975 0.7382 0.5450
1.4485 1.1303 1.8517 1.5540 1.7160 2.0000 1.0416 1.0202 1.5007 1.2865 1.1108 1.7932 1.4152 1.6956 1.9817 1.0416 1.0202 1.4332 1.2348 1.2532 1.1407 1.3922 1.2852 1.1220 1.3759 1.7476 1.3129 1.2348 1.2962 1.1407 1.3694 1.2852 1.1220 1.4020 1.7476 1.3188 1.0887 1.0357 1.0988 1.1128 1.1640 1.2800 1.0000 1.0000 1.0964 1.2348 1.0540 1.6597 1.2800 1.5014 1.7644 1.0206 1.0202 1.3100 1.2348 1.0726 1.6830 1.3021 1.5014 1.7644 1.0206 1.0202 1.3188 1.2348 1.0726 1.6830 1.2800 1.5014 1.7423 1.0206 1.0202 1.3129 1.3396
0.2617 0.1086 0.3542 0.2930 0.3302 0.3750 0.0392 0.0196 0.2780 0.1979 0.0948 0.3445 0.2503 0.3261 0.3727 0.0392 0.0196 0.2566 0.1721 0.1816 0.1157 0.2420 0.1973 0.1028 0.2359 0.3363 0.2099 0.1721 0.2024 0.1157 0.2334 0.1973 0.1028 0.2456 0.3363 0.2125 0.0782 0.0339 0.0858 0.0963 0.1310 0.1948 0.0000 0.0000 0.0841 0.1721 0.0499 0.3185 0.1948 0.2782 0.3394 0.0200 0.0196 0.2086 0.1721 0.0654 0.3235 0.2051 0.2782 0.3394 0.0200 0.0196 0.2125 0.1721 0.0654 0.3235 0.1948 0.2782 0.3353 0.0200 0.0196 0.2099 0.2214
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Table 1 (continued) SNP
AA change
Breeds
Genotypes (number of animals)
QI NY JR XN LX SL XL Total
GG(51) GG(22) GG(37) GG(27) GG(16) GG(47) GG(49) GG(284)
GA(6) GA(27) GA(18) GA(30) GA(25) GA(2) GA(1) GA(119)
AA(0) AA(4) AA(1) AA(2) AA(11) AA(0) AA(0) AA(20)
Total number of animal
Minor allele frequency
Heterozygosity
P (HWE)
Effective allele numbers
PIC
57 53 56 59 52 49 50 423
0.0526 0.3302 0.1786 0.2881 0.4519 0.0204 0.0100 0.1879
0.0997 0.4423 0.2934 0.4102 0.4954 0.0400 0.0198 0.3052
0.9158 0.5434 0.7740 0.1841 0.9776 0.9894 0.9975 0.2729
1.1108 1.7932 1.4152 1.6956 1.9817 1.0416 1.0202 1.4393
0.0948 0.3445 0.2503 0.3261 0.3727 0.0392 0.0196 0.2587
T T C C
G A G G
C T C C
T T T C
G G C G
C C T C
G G A G
2676 G>A
2643 G>A
2583 C>T
2457 G>C
2409 T>C
2325 C>T
2286 T>C T T C C
2323 G>A
Hap. Ht 1 Ht 2 Ht 3 Ht 4 others
2145 T>C
HWE, Hardy–Weinberg equilibrium.
G G A A
1
Freq. 0.643 0.137 0.130 0.041 0.049
2 85
3 3
4
4
5
96 3
4
0 0
2
18 18
6 0
2 66
59
0 2
1 65
58
8 96
97 0
2 2
66 59
7 95
9 66
64 65
18 3
3 93
83
A. Haplotypes in ZBTB38
B. LDs among ZBTB38 polymorphism
Fig. 2. Gene haplotype and LD coefficients in ZBTB38. (A) Haplotypes of ZBTB38. Haplotypes with frequency >0.03 are presented. Others contain rare haplotypes. (B) Linkage disequilibrium coefficient ( D′ and r2) among ZBTB38 polymorphisms. The numbers are r2 value (%), and values of colored frame are above 33%.
Table 2 Association analysis of 2323 G>A or 2325 C>T SNP genotypes with body measurement traits at bovine ZBTB38 gene. SNP
G2323A
a,b A,B
Genotypes
GG GA AA P value
Traits (cm, mean ± SE) BL
WH
HH
RL
HW
CD
HG
PBW
147.39 ± 0.67ab 145.32 ± 1.32a 154.56 ± 4.40b 0.0448
132.21 ± 0.50A 131.71 ± 1.02A 142.71 ± 3.69B 0.0044
161.59 ± 4.44 161.79 ± 0.97 163.79 ± 4.22 0.9956
44.30 ± 0.28a 43.99 ± 0.43a 49.24 ± 1.98b 0.0314
45.90 ± 0.33 46.23 ± 0.57 48.36 ± 2.33 0.4961
70.67 ± 0.38 70.41 ± 0.70 72.96 ± 2.56 0.6051
192.57 ± 1.11 191.38 ± 2.31 196.92 ± 15.73 0.5898
25.66 ± 0.28 26.08 ± 0.67 25.11 ± 1.98 0.7318
means with different superscripts were significantly different (P b 0.05). means with different superscripts were significantly different (P b 0.01).
ZBTB38. ZBTB38 locus (rs724016, P = 5.0× 10−12), which was in an intron of the methyl-DNA-binding transcriptional repressor gene, and other genes may themselves influence height, but further work would be needed to elucidate the relevant pathways and mechanisms. Meanwhile, a SNP in ZBTB38 showed suggestive association in a previous genome-wide association scan for height (Sanna et al., 2008). Following, using data from GWA studies, a SNP of human ZBTB38 gene (rs6440003, P=1.8×10−24) was also associated with adult height in their study (Weedon et al., 2008). Above all, although many studies focus on the association of ZBTB38 gene variants with body measurement traits in human, little has been reported for bovine and other livestock. Only Liu et al. (2010a, 2010b, 2010c) discovered that the 841 A>G SNP in the coding region of the bovine ZBTB38 gene was significantly associated with body measurement traits in 722 individuals. The analysis of 841 A>G SNP marker showed that there were significant effects on the BL (P = 0.0389) in 722 individuals, significant effects on the HH (P = 0.0173) and HG (P = 0.0147) in QI population, as well as significant effects on the WH (P = 0.0094) in XL population. Therefore, based on these results of the genome-wide approach in human and according to the conformity of the conservation of biological evolution in different organisms, we applied the research results from human ZBTB38 in analyzing polymorphism and genetic effect in cattle ZBTB38 gene locus. The new findings are that the 2323 G>A and 2325 C>T SNPs of bovine ZBTB38 were significantly associated with body
length, withers height and rump length (Table 2), which are consistent with the human data. In summary, we identified nine SNPs in the ZBTB38 gene and investigated its association in different bovine breed populations. Genotyping, minor allele frequencies, heterozygosis, effective allele numbers, PIC, HWE, haplotype, linkage disequilibrium and association analysis performed on the tag SNPs, demonstrated that 2323 G>A and 2325 C>T SNPs were strong linkage and significantly associated with body measurement traits in bovine. Therefore, further work will be necessary to use the SNP for marker-assisted selection (MAS) in other breeds and larger population. It is also significant to investigate whether the ZBTB38 gene plays a role on development of those traits and whether it involves in linkage disequilibrium with other causative mutations. Acknowledgements This work was supported by the Shaanxi Provincial Natural Science Foundation of China (2011JQ3006), the National Twelfth “Five Year” Science and Technology Support Project (2011BAD28B04-03), the Beef cattle and Yak Industrial Technology System Project (CARS-38), and the Changjiang Scholars and Innovative Research Team Support Plan of The Ministry of Education (IRT0940). Moreover, the bovine populations were supported by the Qinchuan beef cattle breeding center of Shaanxi province, Nanyang, Jiaxian and Xianan cattle
Y. Liu et al. / Gene 513 (2013) 272–277
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