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Acta Agron Sin ›› 2010, Vol. 36 ›› Issue (10): 1674-1682.doi: 10.3724/SP.J.1006.2010.01674

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Mapping Quantitative Trait Loci for 100-Seed Weight in Soybean (Glycine max L. Merr.)

WANG Xia,XU Yu,LI Guang-Jun,LI He-Nan,GEN Wen-Quan,ZHANG Yuan-Ming*   

  1. National Key Laboratory of Crop Genetics and Germplasm enhancement/National Center for Soybean Improvement,Nanjing Agricultural University,Nanjing 210095,China
  • Received:2010-03-25 Revised:2010-07-05 Online:2010-10-12 Published:2010-08-04
  • Contact: ZHANG Yuan-ming，E-mail: soyzhang@njau.edu.cn E-mail:wangxiahappie@gmail.com

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Abstract: 100-seed weight is an important yield component of soybean and has been positively correlated with seed yield. A genetic linkage map using 504 F2 plants from direct and reciprocal crosses between Lishuizhongzihuang and Nannong 493-1 was constructed. 100-seed weight for these F2:4 families were measured at Jiangpu experimental station of Nanjing Agricultural University and Linyi experimental station in 2008, respectively. The above information was used to detect quantitative trait locus (QTL) for 100-seed weight using composite interval mapping (CIM) in Win QTL Cartographer V. 2.5 and joint analysis under the framework of penalized maximum likelihood. The results showed that sixteen QTLs were identified by the CIM while thirty-nine QTLs, including twenty-four main-effect QTLs, one environmental effect, one cytoplasmic effect, one environmental interaction and twelve cytoplasmic interactions, were detected by joint analysis. Ten common main-effect QTLs detected by the above two methods, three common QTLs between direct and reciprocal crosses at the two environments, and four consensus QTLs from Meta analysis showed the stability of the results. These results provide a theoretical basis for genetic analysis of soybean yield and marker-assisted breeding.

Key words: Soybean, 100-seed weight, Quantitative trait loci, Multi-marker joint analysis, Cytoplasmic interaction, Meta analysis

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