Guo Yuanmei, Huang Yixuan, Hou Lijuan, Ma Junwu, Chen Congying, Ai Huashui, Huang Lusheng, Ren Jun
State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Genet Sel Evol. 2017 Feb 14;49(1):21. doi: 10.1186/s12711-017-0295-4.
Genome-wide association studies (GWAS) have been extensively used to identify genomic regions associated with a variety of phenotypic traits in pigs. Until now, most GWAS have explored single-trait association models. Here, we conducted both single- and multi-trait GWAS and a meta-analysis for nine fatness and growth traits on 2004 pigs from four diverse populations, including a White Duroc × Erhualian F intercross population and Chinese Sutai, Laiwu and Erhualian populations.
We identified 44 chromosomal regions that were associated with the nine traits, including four genome-wide significant single nucleotide polymorphisms (SNPs) on SSC2 (SSC for Sus scrofa chromosome), 4, 7 and X. Compared to the single-population GWAS, the meta-analysis was less powerful for the identification of SNPs with population-specific effects but more powerful for the detection of SNPs with population-shared effects. Multiple-trait analysis reduced the power to detect trait-specific SNPs but significantly enhanced the power to identify common SNPs across traits. The SNP on SSC7 had pleiotropic effects on the nine traits in the F and Erhualian populations. Another pleiotropic SNP was observed on SSCX for these traits in the F and Sutai populations. Both population-specific and shared SNPs were identified in this study, thus reflecting the complex genetic architecture of pig growth and fatness traits.
We demonstrate that the multi-trait method and the meta-analysis on multiple populations can be used to increase the power of GWAS. The two significant SNPs on SSC7 and X had pleiotropic effects in the F, Erhualian and Sutai populations.
全基因组关联研究(GWAS)已被广泛用于识别与猪的各种表型性状相关的基因组区域。到目前为止,大多数GWAS都探索了单性状关联模型。在此,我们对来自四个不同群体的2004头猪的九个脂肪和生长性状进行了单性状和多性状GWAS以及荟萃分析,这四个群体包括一个白色杜洛克×二花脸F代杂交群体以及中国苏太、莱芜和二花脸群体。
我们鉴定出了44个与这九个性状相关的染色体区域,包括位于猪2号染色体(SSC2)、4号、7号和X染色体上的四个全基因组显著单核苷酸多态性(SNP)。与单群体GWAS相比,荟萃分析在识别具有群体特异性效应的SNP方面能力较弱,但在检测具有群体共享效应的SNP方面能力更强。多性状分析降低了检测性状特异性SNP的能力,但显著增强了识别跨性状常见SNP的能力。位于SSC7上的SNP对F代和二花脸群体的九个性状具有多效性作用。在F代和苏太群体中,在SSCX上观察到了另一个对这些性状具有多效性的SNP。本研究中鉴定出了群体特异性和共享的SNP,从而反映了猪生长和脂肪性状复杂的遗传结构。
我们证明多性状方法和对多个群体的荟萃分析可用于提高GWAS的效能。位于SSC7和X染色体上的两个显著SNP在F代、二花脸和苏太群体中具有多效性作用。