Mapping QTLs of root morphological traits at different growth stages in rice
Mapping QTLs of root morphological traits at different growth stages in rice
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水稻不同生育阶段根系形态性状QTL定位
DOI：
10.1007/s10709-007-9199-5
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发表时间：
2008-06-01
期刊：
影响因子：
1.5
通讯作者：
Li, Zichao
中科院分区：
文献类型：
--
作者：
Qu, Yanying;Mu, Ping;Li, Zichao
根系是吸收土壤水分和养分的重要器官，影响着植物的抗旱性。利用分子标记进行数量性状基因座(QTL)的定位，可以通过分子标记辅助选择(MAS)来估计遗传结构参数和改良根部性状。利用水稻‘IRAT109’与水稻‘乐府’杂交的120个重组自交系(RIL)作图群体，对水稻根系发育性状进行QTL定位。所有的植物材料都生长在聚氯乙烯管中。分别在苗期(I)、分蘖期(II)、抽穗期(III)、灌浆期(IV)和成熟期(V)进行了根基厚度(BRT)、根数(RN)、最大根长(MRL)、根鲜重(RFW)、根干重(RDW)和根体积(RV)的表型分析。表型相关分析表明，BRT与MRL在大多数分期中呈正相关，而与RN不相关。除苗期外，MRL与RN均不相关。各生长阶段的BRT、MRL、RN与RFW、RDW、RV呈正相关。利用QTLMapper 1.6软件进行QTL分析，将遗传成分划分为加性效应QTL、上位性QTL和QTL逐年互作(Q×E)效应。结果表明，BRT、RN和MRL以加性效应为主，RFW、RDW和RV以上位性效应为主，Q×E效应对控制根系性状也有重要作用。在5个时期共检测到84个加性效应QTL和86对上位性QTL。只有12个加性QTL在至少两个阶段表达。这表明大多数QTL是发育阶段特异的。在抽穗期检测到2个主效QTL brt9a和brt9b，在不受环境影响的情况下分别解释了BRT表型变异的19%和10%。这些QTL可用于改良根部性状的育种工作。
Roots are a vital organ for absorbing soil moisture and nutrients and influence drought resistance. The identification of quantitative trait loci (QTLs) with molecular markers may allow the estimation of parameters of genetic architecture and improve root traits by molecular marker-assisted selection (MAS). A mapping population of 120 recombinant inbred lines (RILs) derived from a cross betweenjaponicaupland rice ‘IRAT109’ and paddy rice ‘Yuefu’ was used for mapping QTLs of developmental root traits. All plant material was grown in PVC-pipe. Basal root thickness (BRT), root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW) and root volume (RV) were phenotyped at the seedling (I), tillering (II), heading (III), grain filling (IV) and mature (V) stages, respectively. Phenotypic correlations showed that BRT was positively correlated to MRL at the majority of stages, but not correlated with RN. MRL was not correlated to RN except at the seedling stage. BRT, MRL and RN were positively correlated to RFW, RDW and RV at all growth stages. QTL analysis was performed using QTLMapper 1.6 to partition the genetic components into additive-effect QTLs, epistatic QTLs and QTL-by-year interactions (Q × E) effect. The results indicated that the additive effects played a major role for BRT, RN and MRL, while for RFW, RDW and RV the epistatic effects showed an important action and Q × E effect also played important roles in controlling root traits. A total of 84 additive-effect QTLs and 86 pairs of epistatic QTLs were detected for the six root traits at five stages. Only 12 additive QTLs were expressed in at least two stages. This indicated that the majority of QTLs were developmental stage specific. Two main effect QTLs, brt9a and brt9b, were detected at the heading stage and explained 19% and 10% of the total phenotypic variation in BRT without any influence from the environment. These QTLs can be used in breeding programs for improving root traits.