Genetic analysis and major QTL detection for maize kernel size and weight in multi-environments
Genetic analysis and major QTL detection for maize kernel size and weight in multi-environments
复制标题
多环境下玉米籽粒大小和重量的遗传分析及主要QTL检测
DOI：
10.1007/s00122-014-2276-0
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发表时间：
2014-05-01
影响因子：
5.4
通讯作者：
Qiu, Fazhan
中科院分区：
文献类型：
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作者：
Liu, Ying;Wang, Liwei;Qiu, Fazhan
本研究共鉴定出5个最优聚类中的12个主效QTL和几个上位性QTL，其中一些QTL具有多效性，将为玉米籽粒大小和粒重的精细定位和产量改良提供重要的理论依据。育种计划在这里，我们报告了一组数量性状基因座（QTL）分散在基因组中，并显着控制四个籽粒性状，包括长度，宽度，厚度和重量的表现。以V671（大粒）× Mc（小粒）杂交后代F2：3共270个家系为材料，采用复合区间作图法（CIM）进行单环境分析，沿着采用混合线性模型（CIM）进行联合分析，在5个环境下对玉米籽粒大小和粒重性状进行QTL定位。这两种定位策略分别鉴定出55个和28个QTL。在23个符合条件的菌株中，有6个菌株与环境相互作用。单环境分析表明，第1、2、4、5和9染色体上的8个遗传区域聚集了60%以上的QTL。在1.02-1.03、1.04-1.06、2.05-2.07、4.07-4.08和9.03-9.04箱的遗传区间上，有12个稳定的主效QTL被聚为5个最优聚类，其中12个主效QTL的加性效应和部分显性效应对玉米籽粒发育起着重要的控制作用。这些QTL为进一步利用更多的标记进行精细定位，以及通过分子标记辅助育种对玉米粒重和粒重进行遗传改良提供了重要的理论依据。
Key MessageTwelve major QTL in five optimal clusters and several epistatic QTL are identified for maize kernel size and weight, some with pleiotropic will be promising for fine-mapping and yield improvement.AbstractKernel size and weight are important target traits in maize (Zea maysL.) breeding programs. Here, we report a set of quantitative trait loci (QTL) scattered through the genome and significantly controlled the performance of four kernel traits including length, width, thickness and weight. From the cross V671 (large kernel) × Mc (small kernel), 270 derived F2:3families were used to identify QTL of maize kernel-size traits and kernel weight in five environments, using composite interval mapping (CIM) for single-environment analysis along with mixed linear model-based CIM for joint analysis. These two mapping strategies identified 55 and 28 QTL, respectively. Among them, 6 of 23 coincident were detected as interacting with environment. Single-environment analysis showed that 8 genetic regions on chromosomes 1, 2, 4, 5 and 9 clustered more than 60 % of the identified QTL. Twelve stable major QTLs accounting for over 10 % of phenotypic variation were included in five optimal clusters on the genetic region of bins 1.02–1.03, 1.04–1.06, 2.05–2.07, 4.07–4.08 and 9.03–9.04; the addition and partial dominance effects of significant QTL play an important role in controlling the development of maize kernel. These putative QTL may have great promising for further fine-mapping with more markers, and genetic improvement of maize kernel size and weight through marker-assisted breeding.