Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (Arachis hypogaea L.).
Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (Arachis hypogaea L.).
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DOI：
10.1007/s11032-016-0587-3
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Jiang H
中科院分区：
文献类型：
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作者：
Chen Y;Ren X;Zheng Y;Zhou X;Huang L;Yan L;Jiao Y;Chen W;Huang S;Wan L;Lei Y;Liao B;Huai D;Wei W;Jiang H
花生产量性状的遗传结构决定因素我们对此知之甚少。本研究利用重组自交系（RIL）定位了产量性状的数量性状基因座（QTL）。构建了一张包含609个位点的遗传连锁图谱，总覆盖长度为1557.48cM，相邻标记间的平均距离为2.56cM。该图谱与花生属二倍体种的物理图谱具有良好的共线性。共检测到主茎高、总分枝数等11个性状和9个荚粒性状的92个可重复QTL。在92个QTL中，有15个QTL在3种环境中均有表达，65个QTL是新发现的。主茎高、角果和籽粒相关性状的12个QTLs对表型变异的解释率均在10%以上，显示了标记辅助选择在这些性状改良中的巨大潜力。性状间Meta分析共发现33个共有QTL。共有QTL和其他QTL进一步整合为29个多效的唯一QTL，平均可信区间为1.86cM。QTL的显著共定位与这些性状间的显著表型相关一致。产量性状遗传结构的复杂性得到了证实。目前发现的与荚果和种子相关性状的QTL可能是影响花生产量性状的最基本的遗传因素。该结果为花生有利基因的精细定位、克隆和分子育种设计提供了良好的基础。本文的在线版本（doi：10.1007/s11032-016-0587-3）包含补充材料，可供授权用户使用。
The genetic architecture determinants of yield traits in peanut (Arachis hypogaea L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loci, covering a total of 1557.48 cM with an average distance of 2.56 cM between adjacent markers. The present map exhibited good collinearity with the physical map of diploid species of Arachis. Ninety-two repeatable QTLs were identified for 11 traits including height of main stem, total branching number, and nine pod- and seed-related traits. Of the 92 QTLs, 15 QTLs were expressed across three environments and 65 QTLs were newly identified. Twelve QTLs for the height of main stem and the pod- and seed-related traits explaining more than 10 % of phenotypic variation showed a great potential for marker-assisted selection in improving these traits. The trait-by-trait meta-analysis revealed 33 consensus QTLs. The consensus QTLs and other QTLs were further integrated into 29 pleiotropic unique QTLs with the confidence interval of 1.86 cM on average. The significant co-localization of QTLs was consistent with the significant phenotypic correlations among these traits. The complexity of the genetic architecture of yield traits was demonstrated. The present QTLs for pod- and seed-related traits could be the most fundamental genetic factors contributing to the yield traits in peanut. The results provide a good foundation for fine mapping, cloning and designing molecular breeding of favorable genes in peanut. The online version of this article (doi:10.1007/s11032-016-0587-3) contains supplementary material, which is available to authorized users.