A Survey of Copy Number Variation in the Porcine Genome Detected from Whole-Genome Sequence

An important challenge to post-genomic biology is relating observed phenotypic variation to the underlying genotypic variation. Genome-wide association studies (GWAS) have made thousands of connections between single nucleotide polymorphisms (SNPs) 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 complex traits is a meaningful goal. Copy number variations (CNVs) are gains and losses of large regions of genomic sequence between individuals of a species. Although CNVs have been associated with various phenotypic traits and diseases in humans and other species, the extent to which CNVs impact phenotypic variation remains unclear. In swine, as well as many other species, relatively little is understood about the frequency of CNVs in the genome, sizes and locations, chromosomal properties, and evolutionary processes acting to shape CNV. The objectives of this study were to identify CNVs from DNA sequence of 181 members of a heavily phenotyped experimental swine herd at the U.S. Meat Animal Research Center and to explore their evolutionary and functional properties. Approximately 56 billion paired-end reads were generated by short-read sequencing on the Illumina HiSeq and NextSeq platforms and mapped to the Sscrofa11.1 genome build. Sequence reads covered each pig’s genome at a mean of 13.37 fold (x) coverage. Individual coverage per animal ranged from 1.32x to 42.76x. Using a combination of single and multiple sample read depth approaches, we identified a total of 3,204 copy number variable regions (CNVRs). The CNVRs covered 2.28% of the porcine genome and spanned 1,615 protein-coding genes and many known quantitative trait loci (QTL). We examined various evolutionary and functional aspects of these CNVs, including GO annotation of CNV-overlapped genes, selective constraint on CNV genes, and centrality of CNV genes in protein-protein interaction (PPI) networks. Gene ontology (GO) enrichment analysis using the PANTHER database showed that CNV genes were enriched for GO terms related to sensory perception, signal transduction, olfactory receptor activity, and response to stimulus (Bonferroni corrected P-value < 0.05). Analysis of selective constraint and PPI network centrality of CNV genes revealed that reduced functional constraint and mutational bias may play a prominent role in shaping this type of structural variation.

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