Translational Genomics For Improving Sow Fertility

Sow fertility traits, such as litter size and number of lifetime parities produced (reproductive longevity), are economically important. Selection for these traits is difficult because they are lowly heritable, polygenic, sex-limited, and express late in life. Age at puberty is an early indicator of reproductive longevity. Gilts that achieve puberty at an early age have a greater probability to produce more parities over their lifetime. However, measuring age at puberty is time consuming and tedious. Identifying pleiotropic polymorphisms that affect age at puberty and other fertility traits, including reproductive longevity, could help to improve the accuracy of genomic prediction for sow fertility traits. We developed a custom Affymetrix SNP array (SowPro90) including SNPs located in major QTL regions for age at puberty, other fertility and disease related traits, and potential loss of function SNPs. Genetic variants were identified using deep transcriptomic and genomic sequencing, gene network analysis, and genome-wide association (GWAS) carried out at University of Nebraska-Lincoln (UNL) and US Meat Animal Research Center (USMARC). This novel SNP array was used to fine map the genetic sources associated with fertility traits. Using a Bayesian haplotype approach (BayesIM), SowPro90 haplotypes were inferred and assigned to the entire UNL population and were used in an association analysis for age at puberty and other fertility traits. Five major QTL regions located on four chromosomes (SSC2, SSC7, SSC14, SSC18) were discovered for age at puberty. As expected, a negative correlation (r = −0.96 to −0.10; PP2RX3, OAS1, NR2F2, PTPN11). These SNPs showed significant or suggestive effects on age at puberty, reproductive longevity, and litter size traits in the UNL population and litter size traits in the commercial sows. It will be beneficial to further characterize these SNPs and candidate genes to understand their impact on protein sequence and function, gene expression, splicing process, and how these changes affect phenotypic variation of fertility traits. Advisor: Daniel Cioban