Abstract #200

# 200
Genetic dissection of bull fertility in dairy cattle.
Yi Han1, Paula Nicolini1,2, Francisco Peñagaricano*1, 1University of Florida, Gainesville, FL, 2Universidad de la República, Tacuarembó, Uruguay.

Improving reproductive performance of dairy cattle has become one of the major challenges of the dairy industry worldwide. Most studies have investigated cow fertility while bull fertility has received much less attention. However, there is growing evidence that the service sire represents an important source of variation for conception rate in dairy cattle. As such, the main objective of this study was to perform a comprehensive analysis to reveal the genomic architecture underlying male fertility in dairy cattle. Sire Conception Rate was used as a measure of bull fertility including records in both Holstein and Jersey bulls. The analysis included the application of alternative genome-wide association mapping approaches and the subsequent use of gene set enrichment tools. The association analyses identified several genomic regions strongly associated with bull fertility. Most of these regions harbor genes, such as CCT6A, CKB, IGF1R, KAT8 and TDRD9 with functions related to sperm biology, including sperm development, motility and sperm-egg interaction. Some regions showed marked dominance effects, which provide more evidence for the importance of non-additive effects in fitness traits such as male fertility. Moreover, gene set analyses revealed many significant Gene Ontology and Medical Subject Headings terms, including fertilization, sperm motility, calcium channel regulation, and SNARE proteins. Most of these terms are directly implicated in sperm physiology and male fertility. Our study contributes to the identification of genetic variants and biological pathways responsible for the genetic variation in bull fertility in Holstein and Jersey breeds. Additionally, our findings may provide opportunities for improving dairy bull fertility via marker-assisted selection.

Key Words: sire conception rate, association analysis, gene set enrichment