Papers

Peer-reviewed
Dec, 2016

Effect of candidate gene polymorphisms on reproductive traits in a Large White pig population

ANIMAL SCIENCE JOURNAL
  • Shuji Sato
  • ,
  • Takashi Kikuchi
  • ,
  • Yoshinobu Uemoto
  • ,
  • Satoshi Mikawa
  • ,
  • Keiichi Suzuki

Volume
87
Number
12
First page
1455
Last page
1463
Language
English
Publishing type
Research paper (scientific journal)
DOI
10.1111/asj.12580
Publisher
WILEY-BLACKWELL

The objective of this study was to test for association of candidate single nucleotide polymorphisms (SNPs) with sow prolificacy reproductive traits, such as litter size, ovulation rate and lifetime performance, in gilts of a Large White pig population. Preliminary research on 25 animals selected from the high- and low-performance groups of 347 animals with case-control studies indicated that seven genes were associated with total number of piglets born (TNB). Six of the seven genes were associated with reproductive traits, including TNB, number of piglets born alive (NBA) and average weight of piglet weaning (AWW). A MBL2 SNP was significantly associated with TNB and NBA in first parity. A CFB SNP was associated with TNB in first parity. An ACE SNP was associated with TNB in first and second parities. An EGF polymorphism was associated with TNB, NBA and AWW in second parity. A KCNC2 polymorphism was significantly associated with TNB and NBA in second parity. A SLC22A5 SNP was associated with TNB and NBA in second parity. Six candidate SNPs were associated with TNB; the only exception was a PRKAG3 polymorphism. A candidate gene approach enables some of these polymorphisms to be used in genetic improvement programs based on marker-assisted selection.

Link information
DOI
https://doi.org/10.1111/asj.12580
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/27018129
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000389323700001&DestApp=WOS_CPL
ID information
  • DOI : 10.1111/asj.12580
  • ISSN : 1344-3941
  • eISSN : 1740-0929
  • Pubmed ID : 27018129
  • Web of Science ID : WOS:000389323700001

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