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Theoretical and Applied Genetics

, Volume 119, Issue 4, pp 605–612 | Cite as

Using three overlapped RILs to dissect genetically clustered QTL for fiber strength on Chro.D8 in Upland cotton

  • Hong Chen
  • Neng Qian
  • Wangzhen Guo
  • Qingping Song
  • Baocheng Li
  • Fujun Deng
  • Cunguang Dong
  • Tianzhen ZhangEmail author
Original Paper

Abstract

Fiber strength is an important trait among cotton fiber qualities due to ongoing changes in spinning technology. Major quantitative trait loci (QTL) for fiber quality enable molecular marker-assisted selection (MAS) to effectively improve fiber quality of cotton cultivars. We previously identified a major QTL for fiber strength derived from 7235 in Upland cotton. In the present study, in order to fine-map fiber strength QTL, we chose three recombinant inbred lines (RIL), 7TR-133, 7TR-132, and 7TR-214, developed from a cross between 7235 and TM-1 for backcrossing to TM-1 to develop three large mapping populations. Phenotypic data for fiber strength traits were collected in Nanjing (JES/NAU) and Xinjiang (BES/XJ) in 2006 and 2007. Three simple sequence repeat (SSR) genetic linkage maps on Chro.24(D8) were constructed using these three backcrossed populations. The SSR genetic maps were constructed using 907 individuals in (7TR-133 × TM-1)F2 (Pop A), 670 in (7TR-132 × TM-1)F2 (Pop B), and 940 in (7TR-214 × TM-1)F2 (Pop C). The average distance between SSR loci was 0.62, 1.7, and 0.56 cM for the three maps. MapQTL 5 software detected five-clustered QTL (2.5 < LOD < 29.8) on Chro.D8 for fiber strength following analysis of three RIL backcrossed F2/F2:3 progenies at JES/NAU and BES/XJ over 2 years. Five QTL for fiber strength exhibited a total phenotypic variance (PV) of 28.8–59.6%.

Keywords

Quantitative Trait Locus Simple Sequence Repeat Marker Recombinant Inbred Line Major Quantitative Trait Locus Simple Sequence Repeat Locus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was financially supported in part by grants from the High-tech program 863 (2006AA100105), Jiangsu province key project (BE2008310), and the 111 Project (B08025).

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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Hong Chen
    • 1
  • Neng Qian
    • 1
  • Wangzhen Guo
    • 1
  • Qingping Song
    • 2
  • Baocheng Li
    • 2
  • Fujun Deng
    • 2
  • Cunguang Dong
    • 2
  • Tianzhen Zhang
    • 1
    Email author
  1. 1.National Key Laboratory of Crop Genetics and Germplasm EnhancementNanjing Agricultural UniversityNanjingChina
  2. 2.Cotton Research InstituteXinjiang Academy of Agriculture and Reclamation SciencesXinjiangChina

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