Single-step genome-wide association study and candidate genes networks affecting reproductive traits in Iranian Holstein cattle

The process of reproductive in domestic livestock is one of the most important challenges of animal husbandry. Fertility is an important trait that contributes to herd profitability, and it can be improved by genomic information. One of the best ways to examine the association between single nucleotide polymorphisms (SNPs) and phenotypic performance is genome-wide association study (GWAS). This study aimed to perform single-step GWAS (ssGWAS) on reproductive traits in Holstein heifers and cows (born from 1992 to 2018) which were obtained from Animal Breeding Center of Iran. Reproductive traits included: age at first service (AFS), age at first calving (AFC), interval between first and last insemination (IFL), calving interval (CI), days from calving to first service (DFS), gestation length (GL), days open (DO), pregnancy rate (PR) and number of services per conception (NS). The animals were genotyped using SNP panels of different densities (Illumina and GeenSeek Genomic companies) and imputed to a 50K SNP density. The number of genotyped animals after quality control was 1654 and the total number of animals in the pedigree file was 3452730. Gene set enrichment analysis (GSEA) as well as pathway analysis were performed to maximize ssGWAS potential. In total 32 significant SNPs (P < 0.05) were observed of which 11 and 21 SNPs were located within candidate genes of reproductive traits in heifers and cows, respectively. Novel potential candidate genes for reproductive traits included PSEN1, ENSBTAG00000050002, USH2A, DMXL1, AVEN, CCDC93, PARP16, MRPL11, PSMA5, PABPN1, CENPF, and MRPL40. Moreover, the most significant gene ontology term was proteolysis which is involved in cellular protein catabolic process (for gestation length). As a result, the SNPs and candidate genes identified in this study could be used in genomic testing to improve fertility performance of Iranian Holstein dairy cattle and provide new information about the genetic architecture of traits.