Genome-wide association for milk production traits and somatic cell score in different lactation stages of Ayrshire, Holstein, and Jersey dairy cattle

摘要

We performed genome-wide association analyses formilk, fat, and protein yields and somatic cell score basedon lactation stages in the first 3 parities of CanadianAyrshire, Holstein, and Jersey cattle. The genome-wideassociation analyses were performed considering 3 differentlactation stages for each trait and parity: from 5to 95, from 96 to 215, and from 216 to 305 d in milk. Effectsof single nucleotide polymorphisms (SNP) for eachlactation stage, trait, parity, and breed were estimatedby back-solving the direct breeding values estimatedusing the genomic best linear unbiased predictor andsingle-trait random regression test-day models containingonly the fixed population average curve and therandom genomic curves. To identify important genomicregions related to the analyzed lactation stages, traits,parities and breeds, moving windows (SNP-by-SNP) of20 adjacent SNP explaining more than 0.30% of totalgenetic variance were selected for further analyses ofcandidate genes. A lower number of genomic windowswith a relatively higher proportion of the explainedgenetic variance was found in the Holstein breed comparedwith the Ayrshire and Jersey breeds. Genomicregions associated with the analyzed traits were locatedon 12, 8, and 15 chromosomes for the Ayrshire, Holstein,and Jersey breeds, respectively. Especially forthe Holstein breed, many of the identified candidategenes supported previous reports in the literature.However, well-known genes with major effects on milkproduction traits (e.g., diacylglycerol O-acyltransferase1) showed contrasting results among lactation stages,traits, and parities of different breeds. Therefore, ourresults suggest evidence of differential sets of candidategenes underlying the phenotypic expression of the analyzedtraits across breeds, parities, and lactation stages.Further functional studies are needed to validate ourfindings in independent populations.