Quantitative trait loci associated with drought tolerance at reproductive stage in rice
Quantitative trait loci associated with drought tolerance at reproductive stage in rice
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DOI：
10.1104/pp.103.035527
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发表时间：
2004-05-01
期刊：
影响因子：
7.4
通讯作者：
Toojinda, T
中科院分区：
文献类型：
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作者：
Lanceras, JC;Pantuwan, G;Toojinda, T
干旱是影响水稻产量及其稳定性的主要因素。确定影响产量及其组分对水分亏缺反应的基因组区域将有助于我们理解耐旱性的遗传学和开发更耐旱的品种。利用CT 9993 -510与1-M和IR 62266 -42与6-2杂交获得的154个双单倍体系的子集，对水稻产量及其构成因子和其他农艺性状的数量性状位点（QTL）进行了鉴定。干旱胁迫处理管理使用线源喷灌系统，它提供了一个线性下降的灌溉水平与敏感的生殖生长阶段相一致。这项研究在泰国乌汶的乌汶水稻研究中心进行。在不同水分胁迫水平下，共检测到77个影响水稻产量及其构成因素的QTL。在77个QTL中，每个性状的QTL数目为：7-籽粒产量（戈伊）、8-生物产量（BY）、6-收获指数（HI）、5-开始灌溉梯度后开花天数（DFAIG）、10-总小穗数（TSN）、7-小穗不育度（PSS）、23-穗数（PN）和11-株高（PH）。单个QTL解释的表型变异在7.5%~ 55.7%之间。在良好的浇水条件下，我们观察到高的遗传关联BY，HI，DFAIG，PSS，TSN，PH，和戈伊。干旱处理下，只有BY和HI与戈伊能力显著相关。位于第3、4和8染色体上的标记RG 104-RM 231、EMP2_2-RM 127和G2132-RZ 598与干旱处理下的戈伊、HI、DFAIG、BY、PSS和PN相关。第3、4和8染色体上的QTL的聚集效应导致了较高的籽粒产量。这些QTL将有助于水稻品种的改良，也有助于我们理解戈伊在敏感生殖期干旱条件下的遗传控制。紧密连锁或基因多效性可能是导致本试验中检测到的QTL重合的原因。在灌溉条件下，戈伊、BY、HT和PSS的QTL主效应间存在双基因互作。大多数（但不是所有）DH系在水分亏缺强度增加时对生产力的反应相同，但没有检测到灌溉处理互作的QTL。鉴定干旱胁迫下与戈伊及其组分相关的基因组区域将有助于基于分子标记的方法来提高戈伊及其稳定性，以帮助农民在干旱环境中种植水稻。
Drought is a major constraint to rice (Oryza sativa) yield and its stability in rainfed and poorly irrigated environments. Identifying genomic regions influencing the response of yield and its components to water deficits will aid in our understanding of the genetics of drought tolerance and development of more drought tolerant cultivars. Quantitative trait loci (QTL) for grain yield and its components and other agronomic traits were identified using a subset of 154 doubled haploid lines derived from a cross between two rice cultivars, CT9993-510 to 1-M and IR62266-42 to 6-2. Drought stress treatments were managed by use of a line source sprinkler irrigation system, which provided a linearly decreasing level of irrigation coinciding with the sensitive reproductive growth stages. The research was conducted at the Ubon Rice Research Center, Ubon, Thailand. A total of 77 QTL were identified for grain yield and its components under varying levels of water stress. Out of the total of 77 QTL, the number of QTL per trait were: 7-grain yield (GY); 8-biological yield (BY); 6-harvest index (HI); 5-d to flowering after initiation of irrigation gradient (DFAIG); 10-total spikelet number (TSN); 7-percent spikelet sterility (PSS); 23-panicle number (PN); and 11-plant height (PH). The phenotypic variation explained by individual QTL ranged from 7.5% to 55.7%. Under well-watered conditions, we observed a high genetic association for BY, HI, DFAIG, PSS, TSN, PH, and GY. However, only BY and HI were found to be significantly associated with GY under drought treatments. QTL flanked by markers RG104 to RM231, EMP2_2 to RM127, and G2132 to RZ598 on chromosomes 3, 4, and 8 were associated with GY, HI, DFAIG, BY, PSS, and PN under drought treatments. The aggregate effects of these QTL on chromosomes 3, 4, and 8 resulted in higher grain yield. These QTL will be useful for rainfed rice improvement, and will also contribute to our understanding of the genetic control of GY under drought conditions at the sensitive reproductive stage. Close linkage or pleiotropy may be responsible for the coincidence of QTL detected in this experiment. Digenic interactions between QTL main effects for GY, BY, HT, and PSS were observed under irrigation treatments. Most (but not all) DH lines have the same response in measure of productivity when the intensity of water deficit was increased, but no QTL by irrigation treatment interaction was detected. The identification of genomic regions associated with GY and its components under drought stress will be useful for marker-based approaches to improve GY and its stability for farmers in drought-prone rice environments.