論文

査読有り
2014年7月

Identification of quantitative trait loci for downy mildew resistance in cucumber (Cucumis sativus L.)

EUPHYTICA
  • Yosuke Yoshioka
  • ,
  • Yoshiteru Sakata
  • ,
  • Mitsuhiro Sugiyama
  • ,
  • Nobuko Fukino

198
2
開始ページ
265
終了ページ
276
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1007/s10681-014-1102-8
出版者・発行元
SPRINGER

Downy mildew, caused by Pseudoperonospora cubensis (Berk. & Curt.) Rostov, is one of the most economically important foliar diseases in cucumber (Cucumis sativus L.). Cucumber line CS-PMR1, derived from self-pollination of USDA Plant Introduction 197088, has a high level of resistance to downy mildew and is considered to be promising breeding material. In this study, we performed quantitative trait locus (QTL) analysis for downy mildew resistance using 111 recombinant inbred lines (RILs) derived from a cross between CS-PMR1 and the old Japanese cultivar Santou, which exhibits moderate resistance. The resistance of the RILs and their parents was evaluated by diverse methods using different plant organs (cotyledons, true leaves), stages (seedlings and adult plants), and evaluation criteria (lesion expansion and extent of sporulation). The high resistance of CS-PMR1 was associated with many QTLs with relatively small effects, whereas the moderate resistance of Santou was associated with one major QTL and possibly two others with relatively small effects. In all assays, the major QTL at which the Santou allele was associated with increased resistance had the largest effect. This QTL allele from Santou and several of the most effective QTL alleles identified in CS-PMR1 should be highest priority for selection to efficiently breed new cultivars that carry adequate levels of downy mildew resistance.

リンク情報
DOI
https://doi.org/10.1007/s10681-014-1102-8
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000337041800010&DestApp=WOS_CPL
ID情報
  • DOI : 10.1007/s10681-014-1102-8
  • ISSN : 0014-2336
  • eISSN : 1573-5060
  • Web of Science ID : WOS:000337041800010

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