Genome-wide detection of selective signatures in Simmental cattle
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  • 作者:Huizhong Fan (1)
    Yang Wu (1)
    Xin Qi (1)
    Jingjing Zhang (1) (2)
    Juan Li (1)
    Xue Gao (1)
    Lupei Zhang (1)
    Junya Li (1)
    HuiJiang Gao (1)
  • 关键词:Bovine genome ; EHH test ; Gene annotation ; Selection signature
  • 刊名:Journal of Applied Genetics
  • 出版年:2014
  • 出版时间:August 2014
  • 年:2014
  • 卷:55
  • 期:3
  • 页码:343-351
  • 全文大小:960 KB
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  • 作者单位:Huizhong Fan (1)
    Yang Wu (1)
    Xin Qi (1)
    Jingjing Zhang (1) (2)
    Juan Li (1)
    Xue Gao (1)
    Lupei Zhang (1)
    Junya Li (1)
    HuiJiang Gao (1)

    1. Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, People’s Republic of China
    2. College of Animal Science and Technology, Agricultural University of Jilin, Changchun, 130118, China
  • ISSN:2190-3883
文摘
Artificial selection has greatly improved the beef production performance and changed its genetic basis. High-density SNP markers provide a way to track these changes and use selective signatures to search for the genes associated with artificial selection. In this study, we performed extended haplotype homozygosity (EHH) tests based on Illumina BovineSNP50 (54?K) Chip data from 942 Simmental cattle to identify significant core regions containing selective signatures, then verified the biological significance of these identified regions based on some commonly used bioinformatics analyses. A total of 224 regions over the whole genome in Simmental cattle showing the highest significance and containing some important functional genes, such as GHSR, TG and CANCNA2D1 were chosen. We also observed some significant terms in the enrichment analyses of second GO terms and KEGG pathways, indicating that these genes are associated with economically relevant cattle traits. This is the first detection of selection signature in Simmental cattle. Our findings significantly expand the selection signature map of the cattle genome, and identify functional candidate genes under positive selection for future genetic research.

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