論文

査読有り
2013年12月

QTL Map Meets Population Genomics: An Application to Rice

PLOS ONE
  • Jeffrey A. Fawcett
  • Tomoyuki Kado
  • Eriko Sasaki
  • Shohei Takuno
  • Kentaro Yoshida
  • Ryuichi P. Sugino
  • Shunichi Kosugi
  • Satoshi Natsume
  • Chikako Mitsuoka
  • Aiko Uemura
  • Hiroki Takagi
  • Akira Abe
  • Takashige Ishii
  • Ryohei Terauchi
  • Hideki Innan
  • 全て表示

8
12
開始ページ
e83720
終了ページ
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1371/journal.pone.0083720
出版者・発行元
PUBLIC LIBRARY SCIENCE

Genes involved in the transition from wild to cultivated crop species should be of great agronomic importance. Population genomic approaches utilizing genome resequencing data have been recently applied for this purpose, although it only reports a large list of candidate genes with no biological information. Here, by resequencing more than 30 genomes altogether of wild rice Oryza rufipogon and cultivated rice O. sativa, we identified a number of regions with clear footprints of selection during the domestication process. We then focused on identifying candidate domestication genes in these regions by utilizing the wealth of QTL information in rice. We were able to identify a number of interesting candidates such as transcription factors that should control key domestication traits such as shattering, awn length, and seed dormancy. Other candidates include those that might have been related to the improvement of grain quality and those that might have been involved in the local adaptation to dry conditions and colder environments. Our study shows that population genomic approaches and QTL mapping information can be used together to identify genes that might be of agronomic importance.

リンク情報
DOI
https://doi.org/10.1371/journal.pone.0083720
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/24376738
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000328882000110&DestApp=WOS_CPL
ID情報
  • DOI : 10.1371/journal.pone.0083720
  • ISSN : 1932-6203
  • PubMed ID : 24376738
  • Web of Science ID : WOS:000328882000110

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