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Population Genomic Analyses Based on 1 Million SNPs in Commercial Egg Layers

机译:基于100万个SNP的商业蛋层种群基因组分析

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摘要

Identifying signatures of selection can provide valuable insight about the genes or genomic regions that are or have been under selective pressure, which can lead to a better understanding of genotype-phenotype relationships. A common strategy for selection signature detection is to compare samples from several populations and search for genomic regions with outstanding genetic differentiation. Wright's fixation index, FST, is a useful index for evaluation of genetic differentiation between populations. The aim of this study was to detect selective signatures between different chicken groups based on SNP-wise FST calculation. A total of 96 individuals of three commercial layer breeds and 14 non-commercial fancy breeds were genotyped with three different 600K SNP-chips. After filtering a total of 1 million SNPs were available for FST calculation. Averages of FST values were calculated for overlapping windows. Comparisons of these were then conducted between commercial egg layers and non-commercial fancy breeds, as well as between white egg layers and brown egg layers. Comparing non-commercial and commercial breeds resulted in the detection of 630 selective signatures, while 656 selective signatures were detected in the comparison between the commercial egg-layer breeds. Annotation of selection signature regions revealed various genes corresponding to productions traits, for which layer breeds were selected. Among them were NCOA1, SREBF2 and RALGAPA1 associated with reproductive traits, broodiness and egg production. Furthermore, several of the detected genes were associated with growth and carcass traits, including POMC, PRKAB2, SPP1, IGF2, CAPN1, TGFb2 and IGFBP2. Our approach demonstrates that including different populations with a specific breeding history can provide a unique opportunity for a better understanding of farm animal selection.
机译:鉴定选择的特征可以提供关于处于选择压力下或已经处于选择压力下的基因或基因组区域的有价值的见解,这可以导致对基因型-表型关系的更好理解。选择特征检测的常用策略是比较多个种群的样本并搜索具有出色遗传分化的基因组区域。赖特的固定指数FST是评估人群之间遗传分化的有用指数。这项研究的目的是基于SNP方式的FST计算来检测不同鸡群之间的选择性特征。用三个不同的600K SNP芯片对三个商业层品种和14个非商业花色品种的96个人进行基因分型。过滤后,总共有100万个SNP可用于FST计算。计算重叠窗口的FST值的平均值。然后在商品蛋层和非商品花式品种之间以及白蛋层和棕蛋层之间进行比较。比较非商业品种和商业品种,可检测到630个选择性特征,而在商业蛋层品种之间的比较中,可检测到656个选择性特征。选择特征区域的注释揭示了与生产性状相对应的各种基因,为此选择了品种。其中有NCOA1,SREBF2和RALGAPA1与生殖性状,嗜好和产卵有关。此外,一些检测到的基因与生长和car体性状有关,包括POMC,PRKAB2,SPP1,IGF2,CAPN1,TGFb2和IGFBP2。我们的方法表明,包括具有特定育种历史的不同种群可以提供一个独特的机会,以更好地了解农场动物的选择。

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