PDF(Pubmed)
Abstract：
BACKGROUND: The breeding of layers emphasizes the continual selection of egg-related traits, such as egg production, egg quality and eggshell, which enhance their productivity and meet the demand of market. As the breeding process continued, the genomic homozygosity of layers gradually increased, resulting in the emergence of runs of homozygosity (ROH). Therefore, ROH analysis can be used in conjunction with other methods to detect selection signatures and identify candidate genes associated with various important traits in layer breeding.
RESULTS: In this study, we generated whole-genome sequencing data from 686 hens in a Rhode Island Red population that had undergone fifteen consecutive generations of intensive artificial selection. We performed a genome-wide ROH analysis and utilized multiple methods to detect signatures of selection. A total of 141,720 ROH segments were discovered in whole population, and most of them (97.35%) were less than 3 Mb in length. Twenty-three ROH islands were identified, and they overlapped with some regions bearing selection signatures, which were detected by the De-correlated composite of multiple signals methods (DCMS). Sixty genes were discovered and functional annotation analysis revealed the possible roles of them in growth, development, immunity and signaling in layers. Additionally, two-tailed analyses including DCMS and ROH for 44 phenotypes of layers were conducted to find out the genomic differences between subgroups of top and bottom 10% phenotype of individuals. Combining the results of GWAS, we observed that regions significantly associated with traits also exhibited selection signatures between the high and low subgroups. We identified a region significantly associated with egg weight near the 25 Mb region of GGA 1, which exhibited selection signatures and has higher genomic homozygosity in the low egg weight subpopulation. This suggests that the region may be play a role in the decline in egg weight.
CONCLUSIONS: In summary, through the combined analysis of ROH, selection signatures, and GWAS, we identified several genomic regions that associated with the production traits of layers, providing reference for the study of layer genome.
RESULTS: In this study, we generated whole-genome sequencing data from 686 hens in a Rhode Island Red population that had undergone fifteen consecutive generations of intensive artificial selection. We performed a genome-wide ROH analysis and utilized multiple methods to detect signatures of selection. A total of 141,720 ROH segments were discovered in whole population, and most of them (97.35%) were less than 3 Mb in length. Twenty-three ROH islands were identified, and they overlapped with some regions bearing selection signatures, which were detected by the De-correlated composite of multiple signals methods (DCMS). Sixty genes were discovered and functional annotation analysis revealed the possible roles of them in growth, development, immunity and signaling in layers. Additionally, two-tailed analyses including DCMS and ROH for 44 phenotypes of layers were conducted to find out the genomic differences between subgroups of top and bottom 10% phenotype of individuals. Combining the results of GWAS, we observed that regions significantly associated with traits also exhibited selection signatures between the high and low subgroups. We identified a region significantly associated with egg weight near the 25 Mb region of GGA 1, which exhibited selection signatures and has higher genomic homozygosity in the low egg weight subpopulation. This suggests that the region may be play a role in the decline in egg weight.
CONCLUSIONS: In summary, through the combined analysis of ROH, selection signatures, and GWAS, we identified several genomic regions that associated with the production traits of layers, providing reference for the study of layer genome.
摘要：
背景：层的育种强调卵相关性状的持续选择，比如产蛋,鸡蛋质量和蛋壳，这提高了他们的生产力，满足了市场的需求。随着繁殖过程的继续，层的基因组纯合性逐渐增加，导致纯合性(ROH)运行的出现。因此,ROH分析可以与其他方法结合使用以检测选择特征并鉴定与层育种中的各种重要性状相关的候选基因。
结果：在这项研究中，我们从罗德岛红种群中的686只母鸡中获得了全基因组测序数据,该种群经历了连续15代的密集人工选择.我们进行了全基因组ROH分析，并利用多种方法来检测选择的特征。在整个人群中总共发现了141,720个ROH段，其中大多数(97.35%)长度小于3Mb。确定了23个ROH岛，它们与一些带有选择签名的区域重叠，通过多信号去相关复合方法(DCMS)检测。发现了60个基因，功能注释分析揭示了它们在生长中的可能作用，发展,免疫和信号层。此外,对44个层表型进行了包括DCMS和ROH的双尾分析，以找出个体的顶部和底部10％表型的亚组之间的基因组差异。结合GWAS的结果，我们观察到,与性状显著相关的区域在高低亚组之间也表现出选择特征.我们在GGA1的25Mb区域附近确定了与卵重显着相关的区域，该区域在低卵重亚群中表现出选择特征并具有较高的基因组纯合性。这表明该地区可能在鸡蛋重量的下降中起作用。
结论：总之，通过对ROH的联合分析，选择签名,和GWAS,我们确定了几个与层的生产特征相关的基因组区域，层基因组的研究提供参考。
结果：在这项研究中，我们从罗德岛红种群中的686只母鸡中获得了全基因组测序数据,该种群经历了连续15代的密集人工选择.我们进行了全基因组ROH分析，并利用多种方法来检测选择的特征。在整个人群中总共发现了141,720个ROH段，其中大多数(97.35%)长度小于3Mb。确定了23个ROH岛，它们与一些带有选择签名的区域重叠，通过多信号去相关复合方法(DCMS)检测。发现了60个基因，功能注释分析揭示了它们在生长中的可能作用，发展,免疫和信号层。此外,对44个层表型进行了包括DCMS和ROH的双尾分析，以找出个体的顶部和底部10％表型的亚组之间的基因组差异。结合GWAS的结果，我们观察到,与性状显著相关的区域在高低亚组之间也表现出选择特征.我们在GGA1的25Mb区域附近确定了与卵重显着相关的区域，该区域在低卵重亚群中表现出选择特征并具有较高的基因组纯合性。这表明该地区可能在鸡蛋重量的下降中起作用。
结论：总之，通过对ROH的联合分析，选择签名,和GWAS,我们确定了几个与层的生产特征相关的基因组区域，层基因组的研究提供参考。
