Marete Andrew G, Guldbrandtsen Bernt, Lund Mogens S, Fritz Sébastien, Sahana Goutam, Boichard Didier
UMR GABI, INRA, AgroParisTech, Université Paris Saclay, 78350 Jouy en Josas, France.
Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
Front Genet. 2018 Nov 6;9:522. doi: 10.3389/fgene.2018.00522. eCollection 2018.
A within-breed genome-wide association study (GWAS) is useful when identifying the QTL that segregates in a breed. However, an across-breed meta-analysis can be used to increase the power of identification and precise localization of QTL that segregate in multiple breeds. Precise localization will allow including QTL information from other breeds in genomic prediction due to the persistence of the linkage phase between the causal variant and the marker. This study aimed to identify and confirm QTL detected in within-breed GWAS through a meta-analysis in three French dairy cattle breeds. A set of sequence variants selected based on their functional annotations were imputed into 50 k genotypes for 46,732 Holstein, 20,096 Montbeliarde, and 11,944 Normande cows to identify QTL for milk production, the success rate at insemination of cows (fertility) and stature. We conducted within-breed GWAS followed by across-breed meta-analysis using a weighted Z-scores model on the GWAS summary data (i.e., -values, effect direction, and sample size). After Bonferroni correction, the GWAS result identified 21,956 significantly associated SNP ( < 0.05), while meta-analysis result identified 9,604 significant SNP ( < 0.05) associated with the phenotypes. The meta-analysis identified 36 QTL for milk yield, 48 QTL for fat yield and percentage, 29 QTL for protein yield and percentage, 13 QTL for fertility, and 16 QTL for stature. Some of these QTL were not significant in the within-breed GWAS. Some previously identified causal variants were confirmed, e.g., BTA14:1802265 (fat percentage, = 1.5 × 10; protein percentage, = 7.61 × 10) both mapping the DGAT1-K232A mutation and BTA14:25006125 ( = 8.58 × 10) mapping gene was confirmed for stature in Montbeliarde. New QTL lead SNP shared between breeds included the intronic variant rs109205829 ( gene), and the intergenic variant rs41592357 (1.38 Mb upstream of the gene and 0.65 Mb downstream of the gene). Rs110425867 ( gene) was the top variant associated with fertility, and new QTL lead SNP included rs109483390 (0.1 Mb upstream of the gene and 0.07 Mb downstream of gene), and rs42412333 (0.45 Mb downstream of the gene). An across-breed meta-analysis had greater power to detect QTL as opposed to a within breed GWAS. The QTL detected here can be incorporated in routine genomic predictions.
当鉴定某个品种中分离的数量性状基因座(QTL)时,品种内全基因组关联研究(GWAS)很有用。然而,跨品种荟萃分析可用于提高鉴定在多个品种中分离的QTL的能力以及对其进行精确定位。由于因果变异与标记之间连锁相的持续性,精确定位将允许在基因组预测中纳入来自其他品种的QTL信息。本研究旨在通过对三个法国奶牛品种进行荟萃分析,来鉴定和确认在品种内GWAS中检测到的QTL。基于其功能注释选择的一组序列变异被推算到46,732头荷斯坦奶牛、20,096头蒙贝利亚尔奶牛和11,944头诺曼底奶牛的50k基因型中,以鉴定产奶量、奶牛授精成功率(繁殖力)和体高的QTL。我们先进行了品种内GWAS,然后使用加权Z分数模型对GWAS汇总数据(即P值、效应方向和样本量)进行跨品种荟萃分析。经过Bonferroni校正后,GWAS结果鉴定出21,956个显著相关的单核苷酸多态性(SNP,P < 0.05),而荟萃分析结果鉴定出9,604个与表型相关的显著SNP(P < 0.05)。荟萃分析鉴定出36个产奶量QTL、48个乳脂产量和百分比QTL、29个乳蛋白产量和百分比QTL、13个繁殖力QTL以及16个体高QTL。其中一些QTL在品种内GWAS中并不显著。一些先前鉴定出的因果变异得到了确认,例如,BTA14:1802265(乳脂百分比,P = 1.5×10⁻⁶;乳蛋白百分比,P = 7.61×10⁻⁵)定位到DGAT1-K232A突变,以及BTA14:25006125(P = 8.58×10⁻⁵)定位到的基因在蒙贝利亚尔奶牛的体高中得到了确认。品种间共享的新QTL领先SNP包括内含子变异rs109205829(基因),以及基因间变异rs41592357(基因上游1.38 Mb和基因下游0.65 Mb)。Rs110425867(基因)是与繁殖力相关的顶级变异,新的QTL领先SNP包括rs109483390(基因上游0.1 Mb和基因下游0.07 Mb),以及rs42412333(基因下游0.45 Mb)。与品种内GWAS相比,跨品种荟萃分析检测QTL的能力更强。这里检测到的QTL可纳入常规基因组预测中。