Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, China.
PLoS One. 2018 Sep 17;13(9):e0200846. doi: 10.1371/journal.pone.0200846. eCollection 2018.
Low temperature stress is one of the major abiotic stresses limiting the productivity of Geng (japonica) rice grown the temperate regions as well as in tropical high lands worldwide. To develop rice varieties with improved cold tolerance (CT) at the reproductive stage, 84 BC2 CT introgression lines (ILs) were developed from five populations through backcross breeding. These CT ILs plus 310 random ILs from the same BC populations were used for dissecting genetic networks underlying CT in rice by detecting QTLs and functional genetic units (FGUs) contributing to CT. Seventeen major QTLs for CT were identified using five selective introgression populations and the method of segregation distortion. Of them, three QTLs were confirmed using the random populations and seven others locate in the regions with previously reported CT QTLs/genes. Using multi-locus probability tests and linkage disequilibrium (LD) analyses, 46 functional genetic units (FGUs) (37 single loci and 9 association groups or AGs) distributed in 37 bins (~20%) across the rice genome for CT were detected. Together, each of the CT loci (bins) was detected in 1.7 populations, including 18 loci detected in two or more populations. Putative genetic networks (multi-locus structures) underlying CT were constructed based on strong non-random associations between or among donor alleles at the unlinked CT loci/FGUs identified in the CT ILs, suggesting the presence of strong epistasis among the detected CT loci. Our results demonstrated the power and usefulness of using selective introgression for simultaneous improvement and genetic dissection of complex traits such as CT in rice.
低温胁迫是限制温带地区和全球热带高地粳稻生产的主要非生物胁迫之一。为了培育在生殖阶段耐冷性(CT)提高的水稻品种,通过回交育种从五个群体中开发了 84 个 BC2 CT 导入系(ILs)。这些 CT ILs 加上来自同一 BC 群体的 310 个随机 ILs,用于通过检测 QTL 和对 CT 有贡献的功能遗传单位(FGUs)来解析水稻 CT 的遗传网络。使用五个选择导入群体和分离失真方法,鉴定了 17 个 CT 的主要 QTL。其中,三个 QTL 通过随机群体得到确认,另外七个位于先前报道的 CT QTL/基因区域。使用多基因概率检验和连锁不平衡(LD)分析,在水稻基因组的 37 个 bin(~20%)中检测到 46 个用于 CT 的功能遗传单位(FGUs)(37 个单基因座和 9 个关联群或 AG)。每个 CT 基因座(bin)在 1.7 个群体中被检测到,包括在两个或更多群体中检测到的 18 个基因座。基于在 CT ILs 中鉴定的不相关 CT 基因座/FGUs 上供体等位基因之间或之间的强非随机关联,构建了 CT 的潜在遗传网络(多基因座结构),表明检测到的 CT 基因座之间存在强烈的上位性。我们的结果证明了使用选择性导入同时改良和遗传剖析水稻等复杂性状(如 CT)的有效性和有用性。