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A genome scan for selection signatures in Taihu pig breeds using next-generation sequencing

  • Z. Wang (a1) (a2), H. Sun (a1) (a2), Q. Chen (a1) (a2), X. Zhang (a1) (a2), Q. Wang (a1) (a2) and Y. Pan (a1) (a2)...


Taihu pig breeds are the most prolific breeds of swine in the world, and they also have superior economic traits, including high resistance to disease, superior meat quality, high resistance to crude feed and a docile temperament. The formation of these phenotypic characteristics is largely a result of long-term artificial or natural selection. Therefore, exploring selection signatures in the genomes of the Taihu pigs will help us to identify porcine genes related to productivity traits, disease and behaviour. In this study, we used both intra-population (Relative Extend Haplotype Homozygosity Test (REHH)) and inter-population (the Cross-Population Extend Haplotype Homozygosity Test (XPEHH); F-STATISTICS, FST) methods to detect genomic regions that might be under selection process in Taihu pig breeds. As a result, we found 282 (REHH) and 112 (XPEHH) selection signature candidate regions corresponding to 159.78 Mb (6.15%) and 62.29 Mb (2.40%) genomic regions, respectively. Further investigations of the selection candidate regions revealed that many genes under these genomic regions were related to reproductive traits (such as the TLR9 gene), coat colour (such as the KIT gene) and fat metabolism (such as the CPT1A and MAML3 genes). Furthermore, gene enrichment analyses showed that genes under the selection candidate regions were significantly over-represented in pathways related to diseases, such as autoimmune thyroid and asthma diseases. In conclusion, several candidate genes potentially under positive selection were involved in characteristics of Taihu pig. These results will further allow us to better understand the mechanisms of selection in pig breeding.


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These two authors contributed equally to this work.



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A genome scan for selection signatures in Taihu pig breeds using next-generation sequencing

  • Z. Wang (a1) (a2), H. Sun (a1) (a2), Q. Chen (a1) (a2), X. Zhang (a1) (a2), Q. Wang (a1) (a2) and Y. Pan (a1) (a2)...


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