Location: Genetics and Animal BreedingTitle: A survey of genomic variants in commercial swine germplasm identified from whole-genome sequence
Submitted to: International Society for Animal Genetics (ISAG)
Publication Type: Abstract Only
Publication Acceptance Date: 5/22/2019
Publication Date: N/A
Technical Abstract: An important challenge to post-genomic biology is relating observed phenotypic variation to the underlying genotypic variation. Genome-wide association studies have made thousands of connections between single nucleotide polymorphisms (SNP) and phenotypes, implicating regions of the genome that may play a causal role in a variety of complex traits. Despite their success in identifying associated variants, association studies account for only a small percentage of the total heritability. Hence, determining other types of DNA variation that may make a substantial contribution to variation in traits is a meaningful goal. To aid in the development of a comprehensive list of functional variants in the swine genome, SNP and copy number variations (CNV) were identified from whole-genome sequence of 240 pigs from a swine herd at the U.S. Meat Animal Research Center (USMARC). Approximately 72 billion paired-end reads were generated by short-read sequencing on the Illumina platform and mapped to the Sscrofa11.1 genome build. Sequence reads covered each pig’s genome at a mean of 13.62 fold (x) coverage, with individual coverage per animal ranging from 0.97x to 31.13x. A total of 26,850,263 high confidence SNP were identified, located in coding sequence or untranslated regions of 78% of the genes in the porcine genome. Approximately 316,000 SNP were classified as being of high to moderate impact (i.e. loss-of-function, nonsynonymous, or regulatory). Using a combination of split reads, paired-end mapping, and read depth approaches, we identified a total of 3,538 CNV, covering 0.94% of the porcine genome and overlapping 1,402 genes. Analysis of QTL previously identified in the USMARC herd showed that SNP and CNVR were most frequently overlapped with reproductive traits, such as age of puberty and ovulation rate. Future work will be focused on understanding the role that high impact SNP and CNV play in reshaping gene structure, modulating gene expression, and ultimately contributing to phenotypic variation, particularly for reproductive traits.