QTL consistency and meta-analysis for grain yield components in three generations in maize
QTL consistency and meta-analysis for grain yield components in three generations in maize
复制标题
DOI：
10.1007/s00122-010-1485-4
复制
发表时间：
2011-03-01
影响因子：
5.4
通讯作者：
Zhou, Y. G.
中科院分区：
文献类型：
--
作者：
Li, J. Z.;Zhang, Z. W.;Zhou, Y. G.
籽粒产量是玉米最重要和最复杂的性状。在本研究中，对源自马齿玉米自交系 Dan232 和爆米花自交系 N04 杂交的总共 258 个 F-9 重组自交系 (RIL) 在四种环境下的八个谷物产量组成部分进行了评估。在每种环境下并在组合分析中检测到所有性状的数量性状基因座（QTL）及其上位相互作用。 Meta 分析用于整合遗传图谱并检测源自同一杂交的三个世代（RIL、F-2:3 和 BC2F2）的 QTL。总共检测到 103 个 QTL、42 对上位相互作用和 16 个元 QTL (mQTL)。 13 个 QTL 中，有 12 个贡献率 (R (2)) 超过 15%，在 3-4 个环境（或组合分析）中一致检测到，并整合到 mQTL 中。在所有四种环境和组合分析中仅检测到 q100GW-7-1。在三种环境和组合分析中，100qGW-1-1 具有最大的 R (2) (19.3-24.6%)。相比之下，BC2F2和F-2:3代中检测到了6个籽粒产量成分的35个QTL，三代之间没有共同的QTL位于相同的标记区间。 5 号染色体上只有 100 个粒重 (100GW) QTL 位于相邻的标记区间。在 RIL 和 F-2:3 代中检测到了 4 个常见 QTL，在 RIL 和 BC2F2 代之间检测到了 2 个。五个重要的 mQTL（mQTL7-1、mQTL10-2、mQTL4-1、mQTL5-1 和 mQTL1-3）中的每一个均包含与 2-6 个性状相关的 7-12 个 QTL。总之，我们发现遗传结构和环境对 QTL 检测有强烈影响的证据，主要 QTL 跨环境和世代的高度一致性，以及谷物产量组成部分显着的 QTL 共定位。 5个主要QTL（q100GW-1-1、q100GW-7-1、qGWP-4-1、qERN-4-1和qKR-4-1）的精细定位和5个mQTL遗传区域单染色体片段系的构建值得进一步研究，可用于标记辅助育种。
Grain yield is the most important and complex trait in maize. In this study, a total of 258 F-9 recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F-2:3 and BC2F2) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R (2)) over 15% were consistently detected in 3-4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R (2) (19.3-24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC2F2 and F-2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F-2:3 generations, and two between the RIL and BC2F2 generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7-12 QTL associated with 2-6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.