Improving heifer conception rate using translational genomics

Elizabeth Margaret Keuter

Selection has successfully increased milk production at the expense of fertility in dairy cattle for almost 50 years. Current heifer conception rate (HCR) for Holsteins is estimated to be between 55-60%, and economic losses associated with a failed conception is estimated to range between $450-$640. If HCR rose 1% it would save the US dairy industry approximately $20 million annually. The objective of this study was to identify loci associated with HCR. Breeding and health records from 3,359 Holstein heifers were analyzed from a commercial heifer raising facility in located southern Idaho. All heifers were bred by artificial insemination (AI) after an observed estrus, and pregnancy was determined by rectal palpation on day 35 post-AI. After analyzing breeding and health records, 497 heifers were selected and classified as highly fertile (conceived on first AI service) and 388 heifers were selected and classified as subfertile (conceived after 4 or more AI attempts). Extracted DNA from each heifer was genotyped using the Illumina BovineHD Beadchip. A genome-wide association analysis (GWAA) was conducted using the efficient mixed model association eXpedited additive test with a genomic relationship matrix (EMMAX-GRM) and pseudo-heritability was estimated. Single nucleotide polymorphisms (SNPs) associated with HCR were used as gene proxies for a SNP-based gene set enrichment analysis (GSEA-SNP). Biological connections were drawn between GSEA-SNP and GWAA results using a pathway analysis. The GWAA identified 115 SNPs representing 68 quantitative trait loci associated with HCR. Pseudo-heritability was estimated at 0.61. The GSEA-SNP identified 4 gene sets associated with HCR and 40 unique leading edge genes that enriched these gene sets. Pathway analysis identified 169 canonical pathways associated with HCR using Benjamini-Hochberg corrected P values. These results indicate that there are ample opportunities to improve conception rate in Holstein heifers through genomic selection. Reducing the considerable economic losses associated with poor reproductive performance in dairy cattle requires the development of genomic tools to enable the selection of heifers with superior fertility as well as a sustained educational effort to increase the adoption of genetic management practices that improve reproductive performance, thereby increasing industry profitability.

Improving heifer conception rate using translational genomics

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