Identification of candidate genes associated with reproduction in dairy cattle

Date: Monday, January 12, 2015
Time: 2:10 PM
Room: Pacific Salon 2
M. Sofia Ortega , University of Florida, Gainesville, FL
Sarah D. Cochran , University of Florida, Gainesville, FL
Daniel J. Null , Animal Genomics and Improvement Laboratory, ARS-USDA, Beltsville, MD
John B. Cole , Animal Genomics and Improvement Laboratory, ARS-USDA, Beltsville, MD
Anna C. Denicol , University of Florida, Gainesville, FL
Peter J. Hansen , University of Florida, Gainesville, FL
There is a negative genetic correlation between reproduction and production in dairy cattle. One approach to improve selection for reproduction without selecting against production is to identify genes associated with fertility but not with production traits. Single nucleotide polymorphisms (SNPs) in 434 genes previously linked to reproductive processes were evaluated for association with estimated breeding values (EBV) for reproduction and production traits in a population of 550 Holstein bulls. Most SNPs were in the coding region and were selected to maximize amino acid change. There were 40 SNPs associated with daughter pregnancy rate (DPR). Of these, 25 SNPs were not associated with production traits, 14 were associated in opposite directions for DPR and at least one production trait, and one (CPSF1) was  associated in the same direction.  Effects of 39 of the 40 SNP on EBV for DPR were determined in 2337 Holstein cows. Together, the 39 SNPs explained 17% of the genetic variation for DPR, with the most explanatory SNPs for COQ9 (3.2%), HSD17B12 (1.6%), CAST (1.3%), APBB1 (1.3%), and C7H19orf60 (1.3%). Inclusion of the candidate SNPs into genomic estimates of DPR obtained by genome-wide SNP arrays increased reliability of the estimate by 0.2%. Removing SNPs in the arrays physically close to the candidate SNPs did not alter genomic estimates, indicating that genetic variation associated with candidate SNPs was independent of variation due to genome-wide SNPs. Some of the SNPs may be useful for estimating EBV for fertility. The genes are potential targets for physiological regulation to improve fertility.