Literature DB >> 19123966

Impact of epistasis and QTL x environment interaction on the accumulation of seed mass of soybean (Glycine max L. Merr.).

Yingpeng Han1, Weili Teng, Desheng Sun, Yuping Du, Lijuan Qiu, Xiangling Xu, Wenbin Li.   

Abstract

The accumulation of seed mass in soybean is affected by both genotype and environment. The aim of the present study was to measure additive, epistatic and quantitative trait locus (QTL) x environment (QE) interaction effects of QTLs on the development of 100-seed weight in a population of 143 F5 derived recombinant inbred lines (RILs) developed from the cross between the soybean cultivars 'Charleston' and 'Dong Nong 594'. Broad-sense heritability of 100-seed weight from 30 days (30D) to 80D stages was 0.58, 0.52, 0.62, 0.60, 0.66 and 0.57, respectively. A total of 17 QTLs with conditional additive (a) effect and/or conditional additive x environment interaction (ae) effect at specific stages were identified in ten linkage groups by conditional mapping. Of them, only 4 QTLs had significant a effect or ae effect at different stages of seed development. Among QTLs with significant a effect, five acted positively and six acted negatively on seed development. A total of 35 epistatic pairwise QTLs of 100-seed weight were identified by conditional mapping at different developmental stages. Five pairs of QTL showed the additive x additive epistatic (aa) effect and 16 QTLs showed the aa x environment interaction (aae) effect at the different developmental stages. QTLs with aa effect as well with their environmental interaction effect appeared to vary at different developmental stages. Overall, the results indicated that 100-seed weight in soybean is under developmental, genetic and environmental control.

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Year:  2008        PMID: 19123966     DOI: 10.1017/S0016672308009865

Source DB:  PubMed          Journal:  Genet Res (Camb)        ISSN: 0016-6723            Impact factor:   1.588


  4 in total

1.  Identification of QTLs for seed and pod traits in soybean and analysis for additive effects and epistatic effects of QTLs among multiple environments.

Authors:  Zhe Yang; Dawei Xin; Chunyan Liu; Hongwei Jiang; Xue Han; Yanan Sun; Zhaoming Qi; Guohua Hu; Qingshan Chen
Journal:  Mol Genet Genomics       Date:  2013-12       Impact factor: 3.291

2.  Mapping developmental QTL for plant height in soybean [Glycine max (L.) Merr.] using a four-way recombinant inbred line population.

Authors:  Hong Xue; Xiaocui Tian; Kaixin Zhang; Wenbin Li; Zhongying Qi; Yanlong Fang; Xiyu Li; Yue Wang; Jie Song; Wen-Xia Li; Hailong Ning
Journal:  PLoS One       Date:  2019-11-20       Impact factor: 3.240

3.  Statistical method for mapping QTLs for complex traits based on two backcross populations.

Authors:  Zhu Zhihong; Hayart Yousaf; Yang Jian; Cao Liyong; Lou Xiangyang; Xu Haiming
Journal:  Chin Sci Bull       Date:  2012-07

4.  SNP-SNP Interaction Analysis on Soybean Oil Content under Multi-Environments.

Authors:  Qingshan Chen; Xinrui Mao; Zhanguo Zhang; Rongsheng Zhu; Zhengong Yin; Yue Leng; Hongxiao Yu; Huiying Jia; Shanshan Jiang; Zhongqiu Ni; Hongwei Jiang; Xue Han; Chunyan Liu; Zhenbang Hu; Xiaoxia Wu; Guohua Hu; Dawei Xin; Zhaoming Qi
Journal:  PLoS One       Date:  2016-09-26       Impact factor: 3.240

  4 in total

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