Detection and analysis of genome‐wide copy number variation in the pig genome using an 80 K SNP Beadchip

Abstract

Copy number variation (CNV) is an important source of genetic variability in human or animal genomes and play key roles in phenotypic diversity and disease susceptibility. In the present study, we performed a genome‐wide analysis for CNV detection using SNP genotyping data of 857 Large White pigs. A total of 312 CNV regions (CNVRs) were detected with the PennCNV algorithm, which covered 57.76 Mb of the pig genome and correspond to 2.36% of the genome sequence. The length of the CNVRs on autosomes ranged from 1.77 Kb to 1.76 Mb with an average of 185.11 Kb. Of these, 220 completely or partially overlapped with 1,092 annotated genes, which enriched a wide variety of biological processes. Comparisons with previously reported pig CNVR revealed 92 (29.49%) novel CNVRs. Experimentally, 80% of CNVRs selected randomly were validated by quantitative PCR (qPCR). We also performed an association analysis between some of the CNVRs and reproductive traits, with results demonstrating the potential importance of CNVR61 and CNVR283 associated with litter sizes. Notably, the GPER1 gene located in CNVR61 plays a key role in reproduction. Our study is an important complement to the CNV map in the pig genome and provides valuable information for investigating the association between genomic variation and economic traits.

Genome-wide detection of CNV regions and their potential association with growth and fatness traits in Duroc pigs

“…In addition, to evaluate the accuracy of the PennCNV software in determining CNV, we performed qPCR validation for nine randomly selected CNVRs and successfully con rmed seven of nine CNVRs (~ 77.8%). This percentage is similar to Wang et al [54] (75%), Dong et al [55] (70%), and Wang et al [43] (80%). Meanwhile, we also observed that two CNVRs were inconsistent with our expectations.…”

“…Gene set enrichment analysis revealed that many terms might be relevant to growth and fatness traits (see Additional le 7: Table S7). In brief, the KEGG analysis uncovers that these genes mainly signi cantly participated in Rap1 signaling pathway, which was consistent with Zheng et al [17] and Wang et al [43] Furthermore, the top terms of GO analysis were primarily enriched in negative regulation of lipid biosynthetic and metabolic process. Given that, we further identi ed the functions of these genes involved in the critical pathways and biological processes from the GeneCards database and relevant literature.…”

“…We also compared our results with previous studies on CNVRs, which showed a low overlap rate [17,35,44,46,54,[57][58][59][60]. In brief, a total of 404 CNVRs entirely or partially overlapped with the previously reported CNVRs.…”

“…Due to the uncertain boundary of the identi ed CNVRs, we used Oligo 7 software [33] to design primers for the speci c region of ADGRA1, PUSL1, MAPRE2, SGMS2, PCID2, DSCAM, GATD3A, ELFN1 and LIFR genes (see Additional le 4: Table S4). We also selected the GCG gene as the reference locus since this gene was highly conserved among pigs and existed as a single copy in animals [17,34,35]. Normal samples identi ed with no copy number change in the test region were used as a reference.…”

“…Results listed in Table 2 showed varying levels of overlapping CNVRs between studies. Due to the differences in breeds, platforms, algorithms, and CNV de nitions that have a more signi cant impact on the results [43], we used a much looser de nition of overlap, where two CNVRs were considered to be overlapping as long as they shared at least one bp [44].…”