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Acta Agron Sin ›› 2011, Vol. 37 ›› Issue (07): 1175-1185.doi: 10.3724/SP.J.1006.2011.01175

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

Analyses of QTLs for Rice Panicle and Milling Quality Traits and Their Interaction with Environment

HU Xia1,SHI Yu-Min2,**,JIA Qian1,XU Qin1,WANG Yun1,CHEN Kai1,SUN Yong1,ZHU Ling-Hua1,XU Jian-Long1,*,LI Zhi-Kang1,3   

  1. 1 Institute of Crop Sciences / National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing 100081, China; 2 Rice Institute of Guangxi Academy of Agricultural Sciences, Nanning 530007, China; 3 International Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines
  • Received:2011-01-30 Revised:2011-03-27 Online:2011-07-12 Published:2011-05-11

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Abstract: QTLs and their interactions with environments for yield-related traits—second branch number (SBN), spikelet number per panicle (SNP), filled grains number per panicle (FGN), 1000-grain weight (TGW) and panicle weight (PW); grain type traits—grain length (GL), width (GW) and thinkness (GT); and milling quality traits—brown rice percentage (BR), milled rice percentage (MR) and head rice percentage (HR) were identified and analyzed in the two environments, Nanning of Guangxi and Sanya of Hainan, using an introgression line population derived from the cross of recurrent parent Ce258 and a donor IR75862. There were significant differences in FGN, TGW, GL, GW and HR between the two parents. Significant correlations were found among the yield-related traits, and they were strikingly negatively correlated with TGW and GL. Most yield-related traits and grain type had no significant correlations with the three milling quality traits. A total of 57 QTLs were identified for yield-related traits, grain type and milling quality, including six for SBN, four for FGN, five for each of SNP, PW and TGW, nine for GL, seven for W, one for GT, four for BR, five for MR and six for HR, which distributed on all chromosomes except chromosome 11. Most QTLs affecting SBN, SNP and TGW clustered and distributed in the chromosomes independent of the QTLs for BR, MR and HR. Some important QTLs for the above traits were identified on chromosomes 2, 3, 4, 5, and 6 which had been previously detected many times in various genetic backgrounds and environments. One QTL affecting GL and GW in the region of RM152-RM310 on chromosome 8 was newly identified, which simultaneously increased GL and GW. The stable QTLs identified in this study are of importance for marker-assisted selection (MAS) in rice breeding programs. In addition, HR was largely affected by environment and the QTLs for HR had a significant interaction with environment. The interaction characteristics of QTL with environment and its application in MAS were deeply discussed in the paper.

Key words: Quantitative trait locus, QTL ×, environment interaction, introgression lines, milling quality, yield-related traits

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