Genome-wide association study and gene network analysis of fertility, retained placenta, and metritis in US Holstein cattle J.B. Cole1, K.L. Parker Gaddis2, D.J. Null1, C. Maltecca3, and J.S. Clay4 1 Animal Genomics and Improvement Laboratory, ARS, USDA, Bldg 005, BARC-West, 10300 Baltimore Avenue, Beltsville, MD 20705 2 Council on Dairy Cattle Breeding, 4201 Northview Drive, Bowie, MD 20716, USA 3 Department of Animal Science, College of Agriculture and Life Sciences, North Carolina State University, Campus Box 7621, Raleigh, NC 27695 4 Dairy Records Management Systems, 313 Chapanoke Road, Suite 100, Raleigh, NC 27603 The objectives of this research were to identify genes, genomic regions, and gene networks associated with three measures of fertility (daughter pregnancy rate, DPR; heifer conception rate, HCR; and cow conception rate, CCR) and two measures of reproductive health (metritis, METR; and retained placenta, RETP) in US Holstein cows using producer-reported data. A five-trait mixed model analysis was used to perform a genome-wide association study (GWAS) to identify significant SNP located within 25 kbp of genes in bull and cow predictor populations. Gene ontology (GO) and medical subject heading (MeSH) analyses were used to identify pathways and processes over-represented compared to a background set of all annotated Bos taurus genes. An adaptive weight matrix was used to identify significant associations among genes. GWAS results identified different sets of SNP in the two predictor populations, with the SNP of largest effect affecting protein processing, cell-cell signaling, sex differentiation, and embryonic development. Significant GO and MeSH terms also differed between predictor populations, but terms associated with reproductive processes were identified in both cases. The degree of nodes in the network analysis did not deviate from expectations, but fertility-related terms also were identified, and several of the most-connected genes were associated with male or female fertility and embryo size and morphology in mice or humans, most notably ITPR1, SETB1, LMNB1, NEO1, and DGKA. None of the 100 SNP explaining the most variance in the GWAS were among the most connected genes in the networks. While this study identified genes and interactions among them clearly related to fertility, no obvious associations with peripartum reproductive health were found. A more powerful experimental design, such as a case-control study, may be needed to identify relationships among fertility and reproductive tract health. Keywords: dairy cattle, fertility, health, reproduction
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Biology - Disease Resistance 1, , 610, 2018
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