...
首页> 外文期刊>Molecular Breeding >Identification of major QTLs and epistatic interactions for seed protein concentration in soybean under multiple environments based on a high-density map
【24h】

Identification of major QTLs and epistatic interactions for seed protein concentration in soybean under multiple environments based on a high-density map

机译:基于高密度图谱鉴定多种环境下大豆种子蛋白的主要QTL和上位相互作用

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

The concentration of protein in soybean is an important trait that drives successful soybean quality. A recombinant inbred line derived from a cross between the Charleston and Dongnong594 cultivars was planted in one location across 10 years and two locations across 5 years in China (20 environments in total), and the genetic effects were partitioned into additive main effects, epistatic main effects and their environmental interaction effects using composite interval mapping and inclusive composite interval mapping models based on a high-density genetic map. Ten main-effect quantitative trait loci (QTLs) were identified on chromosomes 3, 6, 7, 13, 15 and 20 and detected in more than three environments, with each of the main-effect QTLs contributing a phenotypic variation of around 10 %. Between the intervals of the main-effect QTLs, 93 candidate genes were screened for their involvement in seed protein storage and/or amino acid biosynthesis and metabolism processes based on gene ontology and annotation information. Furthermore, an analysis of epistatic interactions showed that three epistatic QTL pairs were detected, and could explain approximately 50 % of the phenotypic variation. The additive main-effect QTLs and epistatic QTL pairs contributed to high phenotypic variation under multiple environments, and the results were also validated and corroborated with previous research, indicating thatmarker-assisted selection can be used to improve soybean protein concentrations and that the candidate genes can also be used as a foundation data set for research on gene function.
机译:大豆中蛋白质的浓度是驱动大豆成功品质的重要特征。在中国(总共20个环境)中,在中国10年的一个地点和5年的2个地点(总共20个环境)中种植了一个由查尔斯顿和东农594品种的杂交衍生的重组自交系,其遗传效应被分为加性主效应,上位性主使用基于高密度遗传图谱的复合区间映射和包含性复合区间映射模型,研究了这些效应及其环境相互作用效应。在3号,6号,7号,13号,15号和20号染色体上鉴定出10个主要效应定量性状基因座(QTL),并在超过三个环境中检测到,每个主要效应QTL的表型变异约为10%。在主要效应QTL的时间间隔之间,基于基因本体论和注释信息,筛选了93个候选基因是否参与了种子蛋白存储和/或氨基酸生物合成和代谢过程。此外,对上位性相互作用的分析表明,检测到三个上位性QTL对,可以解释约50%的表型变异。加性主效应QTL和上位性QTL对在多种环境下均造成了高表型变异,并且该结果也得到了先前研究的证实和证实,表明标记辅助选择可用于改善大豆蛋白浓度,并且候选基因可以也可用作基因功能研究的基础数据集。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号