Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle

BMC Genomics

Research Article

Lesley-Ann Raven¹  Benjamin G Cocks¹  Ben J Hayes¹ 

[1] Biosciences Research Division, Department of Primary Industries Victoria, 5 Ring Road, 3086, Bundoora, Australia;La Trobe University, 3086, Bundoora, Victoria, Australia;Dairy Futures Co-operative Research Centre, 3086, Bundoora, Victoria, Australia;

关键词: Multibreed analysis;    Genomic selection;    Dairy cattle;    Single nucleotide polymorphism;   

DOI  :  10.1186/1471-2164-15-62

 received in 2013-05-17, accepted in 2014-01-18,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundGenome wide association studies (GWAS) in most cattle breeds result in large genomic intervals of significant associations making it difficult to identify causal mutations. This is due to the extensive, low-level linkage disequilibrium within a cattle breed. As there is less linkage disequilibrium across breeds, multibreed GWAS may improve precision of causal variant mapping. Here we test this hypothesis in a Holstein and Jersey cattle data set with 17,925 individuals with records for production and functional traits and 632,003 SNP markers.ResultsBy using a cross validation strategy within the Holstein and Jersey data sets, we were able to identify and confirm a large number of QTL. As expected, the precision of mapping these QTL within the breeds was limited. In the multibreed analysis, we found that many loci were not segregating in both breeds. This was partly an artefact of power of the experiments, with the number of QTL shared between the breeds generally increasing with trait heritability. False discovery rates suggest that the multibreed analysis was less powerful than between breed analyses, in terms of how much genetic variance was explained by the detected QTL. However, the multibreed analysis could more accurately pinpoint the location of the well-described mutations affecting milk production such as DGAT1. Further, the significant SNP in the multibreed analysis were significantly enriched in genes regions, to a considerably greater extent than was observed in the single breed analyses. In addition, we have refined QTL on BTA5 and BTA19 to very small intervals and identified a small number of potential candidate genes in these, as well as in a number of other regions.ConclusionWhere QTL are segregating across breed, multibreed GWAS can refine these to reasonably small genomic intervals. However, such QTL appear to represent only a fraction of the genetic variation. Our results suggest a significant proportion of QTL affecting milk production segregate within rather than across breeds, at least for Holstein and Jersey cattle.

【 授权许可】

CC BY   
© Raven et al.; licensee BioMed Central Ltd. 2014