不同环境条件下水稻结实率的QTL定位分析

摘要：为了揭示水稻结实率的遗传机理并为优良基因的利用以及分子标记辅助选择提供理论依据，本研究以环境敏感的籼稻品种T219和不敏感的籼稻品种T226为亲本构建的202个株系的重组自交系(RILs)为作图群体，利用8种不同环境条件的试验结果，对RIL的结实率进行了基因型与环境互作分析和QTL的定位分析。结果表明：水稻结实率受环境的影响很大，存在着显著的基因型与环境互作效应；同时，8种环境共检测到分布在9条染色体上的17个QTL，贡献率变幅为4.6~35.7%。其中大部分QTL均只在一个或两个特定的环境中发现，表现为QTL与环境的互作、贡献率较小，且它们的增效等位基因大都来自T226。而位于第3染色体MRG5959-MRG2180区间的qSS3-1，共在6个环境中一致检测到，贡献率分别在各环境中均为最大（15.6~35.7%）、其增效的等位基因来源于亲本T226。另外位于第5染色体上的RM592-RM169区间的qSS5-3，也在同一年份的5个不同的试验条件下同时发现，贡献率为6.9~17.9%，其增效的等位基因来源于亲本T219。

Identification of QTLs for Seed Setting Rate of Rice in Eight Various Environments

Abstract: To understand the genetic basis of seed setting (SS) in rice, genotype by environment (G×E) interaction and QTLs for SS were analyzed using a population with 202 recombinant inbred lines (RIL) derived from a cross between 2 indica varieties, T226 and T219, under eight different environments. Significant G×E interaction for SS in rice was detected using AMMI statistical model, and the IPCA1 and IPCA2 of G×E interaction explained a total of 57.6% of the variation. QTLs controlling the SS were detected by interval analysis, and a total of 17 QTLs on 9 chromosomes were identified across eight environments, explained the phenotypic variances from 4.6% to 35.7%, respectively. Most of the QTLs were detected in one or two environment, explained small part of phenotypic variances. While a QTL（qSS3-1） on chromosome 3 detected across six environments, explained maximum phenotypic variances in each detected environment and its allele for increasing the SS was derived from T226. The QTL (qSS5-3) on chromosome 5 was detected in 5 environments, however Its allele from T219 increasing the SS .