Genome-wide association study of chicken plumage pigmentation.
Poultry industry, in the process of rapid industrialization, developed commercial chicken strains from a small number of breeds. To increase the productivity of native chickens, they were bred for economic traits. Although this process resulted in higher productivity, at the same time it decreased genetic diversity (Tadano et al., 2007). In recent years, it has become increasingly important to protect national endemic genetic resources and use local breeds to create commercial strains that can adapt to the changing environment.
In Korea, the National Institute of Animal Science (NIAS) has been studying the process of indigenization of foreign breeds in to Korea and methods to restore Korean native chicken breeds. Korean native chickens (KNCs) as defined by NIAS in 2008 are chickens that have been bred true for at least seven generations. The commercial KNC called Woorimatdag (WR CC) was developed by crossing three native chicken breeds (Heo et al., 2011). Woorimatdag has contributed to the industrialization of KNCs because of its rapid growth and the texture of the meat in comparison to the native chickens (Park, 2010). However, the use KNC H strain in the paternal line to create Woorimatdag has led to the decrease in plumage uniformity. Unlike typical white broilers, KNCs usually have colored feathers and various pigmentation patterns. Plumage color is an important factor that is used by consumers to distinguish between KNC strains. Although plumage color is easily observed, the genetics behind the feather coloration is governed by both qualitative and quantitative features (Klungland and Vage, 2000). In chickens, mutations in MC1R and TYR genes have been shown to be associated with feather pigmentation (Kerje et al., 2003; Liu et al., 2010). However, there is a lack of research on the genetics of plumage coloration in Korean chicken at the genomewide scale. The purpose of this study is to characterize the genetic polymorphism underlying different plumage color using the chicken 60K SNP chip through GWAS (genomewide association study) and to increase plumage color uniformity of Woorimatdag. The results will also be used for selecting and breeding KNC H strain.
MATERIALS AND METHODS
Sample and phenotype collection, and genotyping
A total of 274 samples from four KNC strains were collected from NIAS. It comprised of 245 KNC H strains (KNCH), 9 KNC S stains (KNCS), 9 KNC R stains (KNCR), and 11 KNC L strains (KNCL). The plumage colors of these strains range from black, black with brown, brown, red-brown, and black. KNC H strain chickens can have black to black and brown plumage and the individuals were classified into seven categories according to the number of body parts it exhibited brown plumage. Plumage color was scored for six specific body parts: head, neck, breast, back, wings, and tail. If the individual only had black feather, it was given a score of zero, however, if an individual showed brown plumage, for every body part it had brown it received 1 point. This classified the individuals into seven categories, ranging from all black to brown in all scored body parts. Blood samples were collected in EDTA tubes and DNA was extracted using Wizard genomic DNA purification kit (Promega, USA) according to the manufacturer's instruction. The genomic DNA samples were genotyped using the 60K SNP Illumina iSelect chicken array (Illumina Inc., USA).
Genome-wide association test
The 60K SNP Illumina iSelect chicken array contains 57,637 SNPs that are distributed across the chicken genome. SNPs were excluded if it had a missing rate of >5%, a minor allele frequency (MAF) of <0.01, or a Hardy-Weinberg equilibrium (HWE) test p-value of <[10.sup.-6] using PLINK 1.07 (Purcell et al., 2007). After the quality control, 53,257 SNPs were retained for further analysis. GWAS analyses on plumage coloration of whole body and the body parts traits were performed using mixed model of GEMMA (v0.93) (Zhou and Stephens, 2012), which accounts for population stratification and sample structure.
y = W[alpha]+x[beta]+u+[micro],
u~MV[N.sub.n] (0,[lambda][[tau].sup.-1]K), [epsilon]~MVNn (0,[[tau].sup.-1][I.sub.n])
Where y is an n-vector of traits (plumage coloration) for n individuals; W = ([w.sub.1], [w.sub.2], ... ,[w.sub.c]) is an nxc matrix of covariates (fixed effects) including a column of 1s; [alpha] is a c-vector of the corresponding coefficients including the intercept; x is an n-vector of marker genotypes; [beta] is the effect size of the marker; u is an n-vector of random effects; [epsilon] is an n-vector of errors; [[tau].sup.-1] is the variance of the residual errors; [lambda] is the ratio between the two variance components; K is a known nxn relatedness matrix and [I.sub.n] is an nxn identity matrix. MV[N.sub.n] denotes the n-dimensional multivariate normal distribution. Relatedness matrix K was calculated as following:
K = 1/p [p.summation over (t=1)] ([x.sub.i] - [1.sub.n] [[bar.x].sub.i]) [([x.sub.i] - [1.sub.n][[bar.x].sub.i]).sup.T]
[x.sub.i] as its ith column representing genotypes of ith SNP, [[bar.x].sub.i] as the sample mean, and [1.sub.n] as a nx1 vector of 1's. GEMMA tests the alternative hypothesis [H.sub.1]:[beta][not equal to]0 against the null hypothesis [H.sub.0]:[beta] = 0 for each SNP. To correct for multiple hypothesis testing, we obtained adjusted p values by using the Benjamini and Hochberg false discovery rate procedure (Benjamini and Hochberg, 1995), adjusted p-value 0.2 significance level is used. An overview of the test results was shown as a Manhattan plot constructed by the statistical package R. Base pair position of SNP markers were given based on the chicken genome assembly build WASHUC2. Inflation factor was calculated by the R package GenABEL with "median" option (Aulchenko et al., 2007).
Estimating genetic variance
We estimated the genetic variance of plumage by using GCTA (Yang et al., 2011). After calculating the genetic relationship matrix (GRM) between all pairs of samples using all the autosomal SNPs, we estimated the genetic component, or heritability, for each trait by REML analysis of an Mixed Linear Model y = X[beta]+[g.sub.G]+[epsilon], where y is a vector of phenotypes, [beta] is a vector of fixed effect such as sex, age with its incidence matrix X, [g.sub.G] is a vector of aggregate SNP effects as random effect with var ([g.sub.G]) = [A.sub.G][[sigma].sup.2.sub.G], and [A.sub.G] is the GRM estimated from all autosomal SNPs. We defined heritability or the proportion of variance explained by all autosomal SNPs as [h.sup.2.sub.G] = [[sigma].sup.2.sub.G] / [[sigma].sup.2.sub.P].
RESULTS AND DISCUSSION
Plumage color of KNC H strain
Each of the 245 KNC (H strain) was investigated individually for plumage coloration (Figure 1). The predominant plumage color of KNC H strain chickens was black, but 88 out of 245 had brown feathers in addition to the black. This mixing of brown plumage causes the uniformity of Woorimatdag to decrease. Plumage color was investigated in six body-parts: head, neck, breast, back, wings and tail. One point was given for each body part that showed brown plumage (Table 1). Out of the 207 KNC H strain hens, 157 hens only had black plumage color, while 41 hens had brown plumage on the neck and 9 hens had brown plumage on both the head and neck. None of the 38 KNC H strain roosters were pure black.
Roosters and hens, respectively, have ZZ and ZW sex chromosome, which may be the cause of the differential plumage color between sexes. Sex-linked silver locus have been shown to control silver and wild type/gold color and interfere with the coloration of red (Gunnarsson et al., 2007). This result is estimated to be associated with the difference in the color of the hen and rooster. It is possible that the sex-linked plumage coloration is related to the fact that rooster with colorful plumage has an advantage when it comes to mating success (Brawner III et al., 2000).
The SNPs associated with feather pigmentation
The genome-wide association study revealed 12 significantly associated SNPs that surpassed the significance level (Figure 2, Table 2). As genomic inflation factor is 0.987, it can be concluded that the GWAS result is not inflated by considering relatedness using GEMMA (Figure 3). Among the significant SNPs, we identified 4 susceptibility SNPs: rs14339964 (Gga3:36327458, p = 4.07 x[10.sup.-9]), GGaluGA344987 (Gga3:705798, p = 1.12x[10.sup.-6]), rs14641648 (Gga8:12987908, p = 2.06x[10.sup.-6]), and GGaluGA193591 (Gga24:5696828, p = 2.38x[10.sup.-6]) in the population (Table 2). SNP rs14339964 at Gga3:36327458 is located in an intron region of AKT3 which is known to be regulators of cell signaling in response to insulin and growth factors and involved in a wide variety of biological processes. AKT3 is one of the key genes in the formation of melanoma cells (Tsao et al., 2012). Previous studies reported that through gene-environment interactions pigmentation pathways can contribute to the formation for melanoma and tumours (Gudbjartsson et al., 2008; Ibarrola-Villava et al., 2012). Thus, we indirectly infer that AKT3 mutations may be related to plumage pigmentation. Both SNPs, GGaluGA344987 at Gga3:705798 and rs14641648 at Gga8:12987908, are located in an intergenic region around KRT7 and PAP2 which are associated with pigmentation. PAP2 is another name of LPPR5 which has been found to increase pigmentation (Shan et al., 2009). KRT7 is a member of the keratin gene family and is related with melanocytic tumors (Blum et al., 2010). DDX6 encodes a member of the DEAD box protein family, which has multiple functions including translation suppression and mRNA degradation (Weston and Sommerville, 2006). DDX6 is a previously confirmed gene for vitiligo which is a disease related with pigmentation of skin (Tang et al., 2012). Interestingly, although rs15175679 (Gga20: 8397089, p = 3.91 x[10.sup.-6]) is not significant, the variant exits in gga-mir-668 which is a region that harbors a small RNA. Previous studies of chicken embryogenesis has shown that this small RNA regulates developmental signaling pathways (Shao et al., 2012). The results of GWAS of head plumage, wing plumage, breast plumage, back plumage, neck plumage and tail plumage traits, separately identified the same SNPs: rs14339964 and rs15616451 (near gene: AKT3, ENSGALG00000020136) as the result of GWAS with the whole body trait. Through the concordant result, we infer that quantitative analysis of whole body plumage is not a simple trait (Table 3).
The feather pigmentation related genes including MC1R, TYR, PMEL, MLPH, ASIP, SOX10, and SLC34A2 are well known. However, the related loci of these genes were not found in this study. The chicken 60K SNP chip does not contain SNPs of the MC1R region, and so we could not identify the effects of MC1R in this study. The results of this study are nevertheless meaningful in that novel loci affecting pigmentation at genome-wide level were found. Estimated genetic heritability was 18.2%, but estimated genetic heritability of significant SNPs was 3.1%. The results support a polygenic effect in feather pigmentation. This means previously reported genes MC1R, TYR, PMEL, MLPH, ASIP, SOX10, and SLC34A2 as well as the reported loci in this study are important in plumage coloration. The results may contribute to selecting and breeding of KNC H for plumage color uniformity.
The work was supported by a grant from the AGENDA project (No. PJ907057) in the National Institute of Animal Science, Rural Development Administration (RDA), Republic of Korea.
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Mi Na Park, Jin Ae Choi, Kyung-Tai Lee, Hyun-Jeong Lee, Bong-Hwan Choi, Heebal Kim (1), Tae-Hun Kim, Seoae Cho (2), and Taeheon Lee (1) * Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Suwon, Korea
* Corresponding Author: Taeheon Lee. Tel: +82-2-880-4822, Fax: +82-2-883-8812, E-mail: firstname.lastname@example.org
(1) Department of Agricultural Biotechnology, Animal Biotechnology Major, and Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 151-742, Korea.
(2) C&K genomics, Seoul National University Research Park, Seoul 151-919, Korea.
Submitted Jul. 10, 2013; Accepted Sept. 4, 2013; Revised Oct. 10, 2013
Table 1. Plumage color pattern of KNC H strain Feather color Point Number of Head Neck Back Breast Wings Tail chickens Male 0 1 0 0 0 0 1 3 0 1 1 0 0 0 2 2 1 1 0 0 1 0 3 9 1 1 1 0 0 0 3 1 1 1 1 0 1 0 4 14 1 1 1 0 1 0 4 4 1 1 1 1 1 0 5 5 Female Shank color 0 0 0 0 0 0 0 157 0 1 0 0 0 0 0 41 1 1 0 0 0 0 0 9 Feather color: 0 = black, 1 = black+brown. Table 2. Top SNPs associated with plumage coloration Min rs CHR Position /Maj (1) Freq rs15304667 1 70248953 G/A 0.0623 rs15408789 1 125252900 G/A 0.115 GGaluGA172731 2 149522175 G/A 0.421 rs14339964 3 36327458 A/C 0.210 GGaluGA239670 3 110847381 G/A 0.206 rs15616451 4 75015502 A/G 0.053 rs16445392 4 85858579 A/C 0.025 rs15790835 6 19031740 A/C 0.132 rs14641648 8 12987908 A/G 0.115 rs15047928 19 5092926 A/G 0.329 GGaluGA193591 24 5696828 G/A 0.121 GGaluGA344987 E22C19 705798 G/A 0.287 W28 rs Beta SE p value Q value * rs15304667 1.221 0.230 2.66E-07 0.014 rs15408789 0.548 0.116 3.58E-06 0.186 GGaluGA172731 1.180 0.244 2.43E-06 0.126 rs14339964 1.186 0.194 4.70E-09 0.000 GGaluGA239670 1.366 0.241 4.50E-08 0.002 rs15616451 0.597 0.125 3.30E-06 0.171 rs16445392 0.908 0.186 1.85E-06 0.096 rs15790835 1.087 0.227 2.89E-06 0.150 rs14641648 1.165 0.239 2.06E-06 0.107 rs15047928 1.325 0.251 2.87E-07 0.015 GGaluGA193591 1.162 0.240 2.38E-06 0.123 GGaluGA344987 1.110 0.222 1.12E-06 0.058 rs gG SNP **0 Gene Location rs15304667 0.143 STK38L Intron rs15408789 0.112 AP1S2 Intergenic GGaluGA172731 0.575 ENSGALG000 Intergenic 18081 rs14339964 0.394 AKT3 Intron GGaluGA239670 0.447 TFAP2B Intergenic rs15616451 0.060 ENSGALG000 Intergenic 20136 rs16445392 0.044 MXD4 Intron rs15790835 0.249 ENSGALG000 Intergenic 5969 rs14641648 0.237 PAP2 Intron rs15047928 0.585 FAM211A Intron GGaluGA193591 0.247 DDX6 Intron GGaluGA344987 0.454 KRT7 Intergenic (1) Minor allele/Major allele. * Adjusted p value. ** Estimated variance. Table 3. Top SNPs associated with plumage coloration by each part Plumage Min part rs ID CHR Position /Maj (1) Freq Head rs14398623 3 97933258 A/G 0.115 rs318020030 7 19055437 A/G 0.350 rs16669242 9 14516013 A/C 0.296 GGaluGA105119 14 14228307 G/A 0.321 rs14112979 18 7210201 G/A 0.341 Wing rs13982792 1 1.83E+08 A/G 0.463 rs14131527 2 4895894 A/G 0.346 rs14188826 2 59639362 A/G 0.058 rs14339964 3 36327458 A/C 0.210 rs14404313 3 103537929 C/A 0.146 GGaluGA110134 15 9605683 G/A 0.333 rs15027075 17 10503821 A/G 0.357 Breast rs14316836 3 7925459 G/A 0.293 Back rs14401050 3 100155987 A/G 0.204 rs15616451 4 75015502 A/G 0.053 GGaluGA287070 5 49185847 G/A 0.393 GGaluGA095084 13 11601056 G/A 0.082 rs15022353 15 7826821 A/G 0.216 Plumage part rs ID Beta SE p value Q value * Head rs14398623 -0.149 0.030 1.56E-06 0.081 rs318020030 0.220 0.045 1.79E-06 0.093 rs16669242 0.235 0.041 2.74E-08 0.001 GGaluGA105119 0.154 0.032 2.76E-06 0.144 rs14112979 0.219 0.042 3.26E-07 0.017 Wing rs13982792 0.153 0.033 3.48E-06 0.181 rs14131527 0.114 0.022 4.14E-07 0.022 rs14188826 0.163 0.034 2.70E-06 0.140 rs14339964 0.146 0.029 1.19E-06 0.062 rs14404313 0.203 0.036 3.75E-08 0.002 GGaluGA110134 0.175 0.037 3.52E-06 0.184 rs15027075 0.111 0.023 2.70E-06 0.141 Breast rs14316836 0.062 0.013 2.49E-06 0.129 Back rs14401050 0.174 0.036 2.23E-06 0.116 rs15616451 0.118 0.024 1.71E-06 0.089 GGaluGA287070 0.198 0.038 4.53E-07 0.024 GGaluGA095084 0.175 0.033 1.81E-07 0.009 rs15022353 0.178 0.029 1.84E-09 9.56E-05 Plumage part rs ID Gene Location Head rs14398623 RNF144A Intron rs318020030 PPP1R9B Intron rs16669242 FGF12 Intergenic GGaluGA105119 ENSGALG000 Intergenic 00023628 rs14112979 HELZ Intron Wing rs13982792 XPO4 Intron rs14131527 XIRP1 Intron rs14188826 PRL Intergenic rs14339964 AKT3 Intron rs14404313 NT5C1B Intergenic GGaluGA110134 MSI1 Intron rs15027075 PBX3 Intron Breast rs14316836 LCLAT1 Intron Back rs14401050 E2F6 Intergenic rs15616451 ENSGALG000 Intergenic 00020136 GGaluGA287070 VRK1 Intergenic GGaluGA095084 SGCD Intron rs15022353 TTC28 Intron (1) Minor allele/Major allele. * Adjusted p value.
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|Author:||Park, Mi Na; Choi, Jin Ae; Lee, Kyung-Tai; Lee, Hyun-Jeong; Choi, Bong-Hwan; Kim, Heebal; Kim, Tae-H|
|Publication:||Asian - Australasian Journal of Animal Sciences|
|Date:||Nov 1, 2013|
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