A global analysis of CNVs in swine using whole genome sequence data and association analysis with fatty acid composition and growth traits
Copy number variations (CNVs) are important genetic variants complementary to SNPs, and can be considered as biomarkers for some economically important traits in domestic animals. In the present study, a genomic analysis of porcine CNVs based on next-generation sequencing data was carried out to identify CNVs segregating in an Iberian x Landrace backcross population and study their association with fatty acid composition and growthrelated traits. A total of 1,279 CNVs, including duplications and deletions, were detected, ranging from 106 to 235 CNVs across samples, with an average of 183 CNVs per sample. Moreover, we detected 540 CNV regions (CNVRs) containing 245 genes. Functional annotation suggested that these genes possess a great variety of molecular functions and may play a role in production traits in commercial breeds. Some of the identified CNVRs contained relevant functional genes (e.g.;CLCA4, CYP4X1, GPAT2, MOGAT2, PLA2G2A and PRKG1, among others). The variation in copy number of four of them (CLCA4, GPAT2, MOGAT2 and PRKG1) was validated in 150 BC1-LD (25% Iberian and 75% Landrace) animals by qPCR. Additionally, their contribution regarding backfat and intramuscular fatty acid composition and growth±related traits was analyzed. Statistically significant associations were obtained for CNVR112 (GPAT2) for the C182(n-6)/C183(n-3) ratio in backfat and carcass length, among others. Notably, GPATs are enzymes that catalyze the first step in the biosynthesis of both triglycerides and glycerophospholipids, suggesting that this CNVR may contribute to genetic variation in fatty acid composition and growth traits. These findings provide useful genomic information to facilitate the further identification of trait-related CNVRs affecting economically important traits in pigs. © 2017 Revilla et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Main Authors: | , , , , , , , |
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Format: | journal article biblioteca |
Language: | eng |
Published: |
2017
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Online Access: | http://hdl.handle.net/20.500.12792/3701 |
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