Asian-Australasian Journal of Animal Sciences

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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Identification of copy number variations using high density whole-genome single nucleotide polymorphism markers in Chinese Dongxiang spotted pigs

  • Wang, Chengbin (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Chen, Hao (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Wang, Xiaopeng (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Wu, Zhongping (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Liu, Weiwei (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Guo, Yuanmei (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Ren, Jun (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Ding, Nengshui (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University)
  • Received : 2018.09.12
  • Accepted : 2019.01.08
  • Published : 2019.12.01
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Abstract

Objective: Copy number variations (CNVs) are a major source of genetic diversity complementary to single nucleotide polymorphism (SNP) in animals. The aim of the study was to perform a comprehensive genomic analysis of CNVs based on high density whole-genome SNP markers in Chinese Dongxiang spotted pigs. Methods: We used customized Affymetrix Axiom Pig1.4M array plates containing 1.4 million SNPs and the PennCNV algorithm to identify porcine CNVs on autosomes in Chinese Dongxiang spotted pigs. Then, the next generation sequence data was used to confirm the detected CNVs. Next, functional analysis was performed for gene contents in copy number variation regions (CNVRs). In addition, we compared the identified CNVRs with those reported ones and quantitative trait loci (QTL) in the pig QTL database. Results: We identified 871 putative CNVs belonging to 2,221 CNVRs on 17 autosomes. We further discarded CNVRs that were detected only in one individual, leaving us 166 CNVRs in total. The 166 CNVRs ranged from 2.89 kb to 617.53 kb with a mean value of 93.65 kb and a genome coverage of 15.55 Mb, corresponding to 0.58% of the pig genome. A total of 119 (71.69%) of the identified CNVRs were confirmed by next generation sequence data. Moreover, functional annotation showed that these CNVRs are involved in a variety of molecular functions. More than half (56.63%) of the CNVRs (n = 94) have been reported in previous studies, while 72 CNVRs are reported for the first time. In addition, 162 (97.59%) CNVRs were found to overlap with 2,765 previously reported QTLs affecting 378 phenotypic traits. Conclusion: The findings improve the catalog of pig CNVs and provide insights and novel molecular markers for further genetic analyses of Chinese indigenous pigs.

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