Unconditional and conditional QTL mapping for the developmental behavior of tiller number in rice (Oryza sativa L.)
Unconditional and conditional QTL mapping for the developmental behavior of tiller number in rice (Oryza sativa L.)
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水稻分蘖数发育行为的无条件和条件QTL定位（Oryza sativa L.）
DOI：
10.1007/s10709-010-9471-y
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发表时间：
2010-08-01
期刊：
影响因子：
1.5
通讯作者：
Zhang, Guiquan
中科院分区：
文献类型：
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作者：
Liu, Guifu;Zhu, Haitao;Zhang, Guiquan
以26个水稻单段代换群体及其受体亲本华粳粳74 （HJX74）为试验材料，分析了水稻分蘖数的发育行为。利用数量性状位点无条件定位法，共检测到14个控制分蘖数的QTL。影响分蘖数的qtl数量及其效应值在不同测量阶段存在差异。基于不同阶段的时间依赖性测量，可以检测到更多的qtl。通过条件QTL定位方法，可以在一定的时间间隔内揭示基因的净表达。14个分蘖数qtl表达了其在整个个体发育过程中对自身动态模式的影响。移栽后7 d内主要表现为负作用。在7 ~ 21 d， qtl处于活跃状态，表达出较大的正向效应。在21 ~ 35 d中期，它们对萎蔫分蘖具有相反的遗传效应。从那时起，这些qtl再次表达积极效应，导致无效分蘖的出现。QTL效应的动态变化与分蘖的实际变化基本一致。将无条件分析与条件分析相结合进行QTL定位，有助于全面了解数量性状发育的遗传基础。
A single segment substitution population of 26 lines and their recipient parent Hua-jing-xian 74 (HJX74) were selected as experimental materials for analyzing the developmental behavior of tiller number in rice. By the unconditional QTL (quantitative trait locus) mapping method, a total number of 14 SSSLs were detected with QTLs controlling rice tiller number. The number of QTLs significantly affecting tiller number and their effect values estimated differed across measuring stages. More QTLs could be detected based on time-dependent measures of different stages. By the conditional QTL mapping method, it is possible to reveal net expression of gene in a time interval. 14 QTLs on tiller number expressed their effects in dynamic patterns of themselves during whole ontogeny. They exhibited mainly negative effects within 7 days after transplanting. During 7-21 days, QTLs were in active status and expressed larger positive effects. In the mid-period of 21-35 days, they had opposite genetic effects to wither tillers. Since then these QTLs expressed positive effects again to cause the appearance of noneffective tillers. The dynamics of QTL effects was in agreement with the actual change of tillers. Mapping QTL combining unconditional with conditional analysis for time-dependent measures is helpful to understand roundly the genetic bases for the development of quantitative traits.