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Combining QTL and candidate gene analysis with phenotypic model to unravel the relationship between lodging and related traits in soybean

文献类型: 外文期刊

作者: Chen, Haifeng 1 ; Yang, Zhonglu 1 ; Chen, Limiao 1 ; Zhang, Chanjuan 1 ; Yuan, Songli 1 ; Zhang, Xiaojuan 1 ; Qiu, Dez 1 ;

作者机构: 1.Chinese Acad Agr Sci, Key Lab Biol & Genet Improvement Oil Crops, Minist Agr, Oil Crops Res Inst, Wuhan 430062, Peoples R China

2.Chinese Acad Agr Sci, Key Lab Biol & Genet Improvement Oil Crops, Minist Agr, Oil Crops Res Inst, Wuhan 430062, Peoples R

关键词: Soybean;Lodging;QTL;Meta-analysis;Breeding strategy

期刊名称:MOLECULAR BREEDING ( 影响因子:2.589; 五年影响因子:2.75 )

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收录情况: SCI

摘要: Lodging is one of the major influencing factors of yield and quality in soybean [Glycine max (L.) Merr.] and other crops. To dissect the genetic basis of lodging in soybean, a recombinant inbred line population consisting of 165 lines was used to evaluate lodging percentage and eight related traits (branch number, internode length, number of nodes, plant height, stem diameter, stem strength, root length, and root weight) in three environments. Regression analysis indicated that plant height and root weight, which explain more than 55% of the variation in lodging percentage, might be the key factors influencing lodging in soybean. Nine consensus quantitative trait locus (QTLs) of lodging percentage were detected in one to three environments. Of which, eight consensus QTLs were colocated with 16 consensus QTLs of lodging-related traits by meta-analysis. In addition, seven candidate genes with the biological functions of shoot branching, root development, internode elongation, and lignin biosynthesis were identified on four pleiotropic QTL regions (oq.13-1, oq.13-2, oq.19-2, and oq.19-3) for lodging percentage and related traits. These findings showed that the consensus QTLs of lodging percentage might result from the pleiotropic QTLs affecting the lodging-related traits. Soybean lodging is determined by the cumulative effect of many traits/processes of growth and development. The combination of MAS, statistical model, and phenotypic selection will provide a powerful breeding strategy for lodging resistance in soybean.

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