Abstract
Copy number variations (CNVs) are important structural variations that can cause significant phenotypic diversity. Reliable CNVs mapping can be achieved by identification of CNVs from different genetic backgrounds. Investigations on the characteristics of overlapping between CNV regions (CNVRs) and protein-coding genes (CNV genes) or miRNAs (CNV-miRNAs) can reveal the potential mechanisms of their regulation. In this study, we used 50 K SNP arrays to detect CNVs in Duroc purebred pig. A total number of 211 CNVRs were detected with a total length of 118.48 Mb, accounting for 5.23% of the autosomal genome sequence. Of these CNVRs, 32 were gains, 175 losses, and four contained both types (loss and gain within the same region). The CNVRs we detected were non-randomly distributed in the swine genome and were significantly enriched in the segmental duplication and gene density region. Additionally, these CNVRs were overlapping with 1,096 protein-coding genes (CNV-genes), and 39 miRNAs (CNV-miRNAs), respectively. The CNV-genes were enriched in terms of dosage-sensitive gene list. The expression of the CNV genes was significantly higher than that of the non-CNV genes in the adult Duroc prostate. Of all detected CNV genes, 22.99% genes were tissue-specific (TSI > 0.9). Strong negative selection had been underway in the CNV-genes as the ones that were located entirely within the loss CNVRs appeared to be evolving rapidly as determined by the median dN plus dS values. Non-CNV genes tended to be miRNA target than CNV-genes. Furthermore, CNV-miRNAs tended to target more genes compared to non-CNV-miRNAs, and a combination of two CNV-miRNAs preferentially synergistically regulated the same target genes. We also focused our efforts on examining CNV genes and CNV-miRNAs functions, which were also involved in the lipid metabolism, including DGAT1, DGAT2, MOGAT2, miR143, miR335, and miRLET7. Further molecular experiments and independent large studies are needed to confirm our findings.
Highlights
Recent findings have shown that structural DNA variations are widespread in animal genomes, such as those of rodents (Graubert et al, 2007) and primates (Freeman et al, 2006)
Identifying Copy number variations (CNVs) from different genetic backgrounds can validate the data on CNV regions discovered in various investigations and achieve reliable CNVs mapping that describes the genome-wide characteristics of various populations
We identified a total number of 1,371 CNVs within the autosome genome of Duroc populations (Table 1), whose sizes ranged from 8.37 to 2,838.50 kb
Summary
Recent findings have shown that structural DNA variations are widespread in animal genomes, such as those of rodents (Graubert et al, 2007) and primates (Freeman et al, 2006). With recent advances in high-throughput sequencing technologies, various approaches can be applied to perform genome-wide CNV mapping, including DNA hybridization in BAC/PAC/oligonucleotide arrays, SNP chips, and next-generation sequencing. Using genome-wide technologies of higher resolution, tremendous quantities of CNVs have been identified in many farm animal species, such as cattle (Liu et al, 2010; Mei et al, 2020), pig (Ramayo-Caldas et al, 2010; Jiang et al, 2014; Wang et al, 2015a), sheep (Liu et al, 2013; Zhu et al, 2016; Di Gerlando et al, 2019), and chicken (Griffin et al, 2008; Seol et al, 2019). Identifying CNVs from different genetic backgrounds can validate the data on CNV regions discovered in various investigations and achieve reliable CNVs mapping that describes the genome-wide characteristics of various populations
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