鉴定与低分化品种之间表型分化有关的基因组区域的联合方法:在撒丁岛绵羊种群中的应用。

Salvatore Mastrangelo, Slim Ben Jemaa, Gianluca Sottile, Sara Casu, Baldassare Portolano, Elena Ciani, Fabio Pilla
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引用次数: 10

摘要

选择性育种已经导致许多牲畜品种的基因组发生改变。在这项研究中,我们确定了可能解释撒丁岛两个近亲品种之间一些表型差异的基因组区域。利用Illumina Ovine 50K基因阵列对44只动物进行基因分型,其中撒丁岛祖先黑(SAB) 20只,撒丁岛白(SW) 24只。采用病例对照全基因组关联研究(GWAS)、贝叶斯群体分化分析(FST)和Rsb指标分别鉴定出68、38和15个显著标记。两种方法之间的比较发现,GWAS和FST之间共有22个重叠标记,GWAS和Rsb之间共有1个重叠标记。Rsb检测到的三个标记也位于ST分析附近。此外,GWAS和FST方法鉴定的一个候选标记位于两个品种共享的纯合岛序列中。我们确定了几个基因涉及许多表型差异(如身材和生长,繁殖,耳朵大小,毛色,行为)在两个分析品种之间。该研究表明,结合几种全基因组方法可以改善发现涉及育种性状变异性和负责表型多样性的区域,甚至在密切相关的品种之间。总的来说,这种全基因组方法的结合可以扩展到具有相似遗传背景的其他牲畜品种,以了解密切相关种群之间遗传变异模式的形成过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combined approaches to identify genomic regions involved in phenotypic differentiation between low divergent breeds: Application in Sardinian sheep populations.

Selective breeding has led to modifications in the genome of many livestock breeds. In this study, we identified the genomic regions that may explain some of the phenotypic differences between two closely related breeds from Sardinia. A total of 44 animals, 20 Sardinian Ancestral Black (SAB) and 24 Sardinian White (SW), were genotyped using the Illumina Ovine 50K array. A total of 68, 38 and 15 significant markers were identified using the case-control genome-wide association study (GWAS), the Bayesian population differentiation analysis (FST ) and the Rsb metric, respectively. Comparisons among the approaches revealed a total of 22 overlapping markers between GWAS and FST and one marker between GWAS and Rsb. Three markers detected by Rsb were also located near (<2 Mb) to highly significant regions identified by GWAS and FST analyses. Moreover, one candidate marker identified by GWAS and FST approaches was located in a run of homozygosity island that was shared by both breeds. We identified several genes involved in many phenotypic differences (such as stature and growth, reproduction, ear size, coat colour, behaviour) between the two analysed breeds. This study shows that combining several genome-wide approaches could improve discovery of regions involved in the variability of breeding traits and responsible for the phenotypic diversity even between closely related breeds. Overall, the combination of such genome-wide methods can be extended to other livestock breeds that share between them a similar genetic background, to understand the process that shapes the patterns of genetic variability between closely related populations.

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