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ARS Home » Plains Area » Clay Center, Nebraska » U.S. Meat Animal Research Center » Livestock Bio-Systems » Research » Publications at this Location » Publication #336427

Title: A survey of single nucleotide polymorphisms identified from whole-genome sequencing and their functional effect in the porcine genome

Author
item Keel, Brittney
item Nonneman, Danny - Dan
item Rohrer, Gary

Submitted to: Animal Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/21/2017
Publication Date: 8/1/2017
Publication URL: http://handle.nal.usda.gov/10113/5700708
Citation: Keel, B.N., Nonneman, D.J., Rohrer, G.A. 2017. A survey of single nucleotide polymorphisms identified from whole-genome sequencing and their functional effect in the porcine genome. Animal Genetics. 48(4):404-411. doi:10.1111/age.12557.

Interpretive Summary: One of the key aims of livestock genetics and genomics research is to discover the genetic variants underlying economically important traits such as reproductive performance, feed efficiency, disease resistance/susceptibility, and product quality. In order to understand the basis by which variation in DNA is associated with a particular phenotype, it is necessary to know whether that variant is functional, i.e. whether it alters the function of a gene or set of genes. ARS scientists have sequenced the genome of 72 influential sires and dams of a heavily phenotyped experimental herd of swine and identified approximately 22 million variants. This extremely large number of variants makes analyzing their individual effects unfeasible. By utilizing the swine genome annotation, researchers found that only ~139,000 of these variants were expected to alter or disrupt the protein coded by a gene and or to regulate protein production. These are the variants that are likely to have a more significant effect on phenotypic variation and will be the focus of future analyses which will evaluate their effect on various performance traits. This work is the first step in identifying functional genetic markers that influence economically relevant traits in swine. Continued examination of these variants is expected to lead to the development of panels of functional genetic markers that will allow swine producers and breeders to be able to make more rapid genetic progress by including them into their selection decisions.

Technical Abstract: Genetic variants detected from sequence have been used to successfully identify causal variants and map complex traits in several organisms. High and moderate impact variants, those expected to alter or disrupt the protein coded by a gene and those that regulate protein production, likely have a more significant effect on phenotypic variation than other types of genetic variants. Hence, a comprehensive list of these functional variants would be of considerable interest in swine genomic studies, particularly those targeting fertility and production traits. Whole-genome sequence was obtained from 72 of the founders of an intensely phenotyped experimental swine herd at the U.S. Meat Animal Research Center (USMARC). These animals included all 24 of the founding boars (12 Duroc and 12 Landrace) and 48 Yorkshire-Landrace composite sows. Sequence reads were mapped to the Sscrofa 10.2 genome build, resulting in a mean of 6.1 fold (x) coverage per genome. A total of 22,342,915 high confidence SNPs were identified from the sequenced genomes. These included 21 million previously reported SNPs and 79% of the 62,163 SNPs on the PorcineSNP60 Beadchip assay. Variation was detected in the coding sequence or untranslated regions (UTRs) of 87.8% of the genes in the porcine genome: loss-of-function variants were predicted in 504 genes, 10,202 genes contained nonsynonymous variants, 10,773 had variation in UTRs, and 13,010 genes contained synonymous variants. Approximately 139,000 SNPs were classified as loss-of-function, nonsynonymous, or regulatory, which suggests that over 99% of the variation detected in our pigs could potentially be ignored, allowing us to focus on a much smaller number of functional SNPs during future analyses.