大豆耐旱性相关性状组成型和适应型QTL挖掘及其联合分析方法研究

Drought is the paramount abiotic stress and commonly reduces soybean yield by about 36%. Developing drought-tolerance cultivars is very important for stable and high production in soybean, while identification of QTL for drought stress response traits in soybean is the prerequisite for these molecular breeding programs. At present, biparents-derived experimental populations were mainly used for QTL analysis of drought tolerance in soybean, thus genetic variation was relatively narrow. Although multi-environment trials (MET) were frequently adopted for these QTL researches, the data acquired from such MET were always separately analyzed for each individual environments and QTL by environment interactions (QEI), an important component of the genetic architecture of tolerant traits, cannot be tested and estimated. In this study, genetic dissection of drought tolerance traits in soybean will be carried out by both linkage analysis, in which a RIL population (NJRIKY) with 184 families will be included, and association analysis, in which about 300 core collections of soybean germplasm will be involved. Improved joint analysis methods which directly modeling multiple QTL, epistatic QTL and QEI, will also be developed and applied to our MET data to discover constitutive and adaptive QTL for drought tolerance. The origins of elite alleles on these loci will then be solved and superior genotypes will be designed and predicted. Functional molecular markers tightly linked to those major QTL will further be exploited. These results will surely improve our understanding of genetic basis of drought tolerance and serve MAS that aimed at increasing drought tolerance in soybean; Moreover, the new joint analysis methodology will provide a novel powerful tool for genetic analysis of abiotic stress tolerance in crops.

干旱是所有非生物胁迫中最具破坏性的，可使大豆减产约36%。培育耐旱大豆品种对大豆稳产、高产很有意义，而耐旱性状QTL发掘则是耐旱大豆分子育种的基础。目前大豆耐旱性状QTL研究在试验材料上多采用双亲本衍生群体，遗传基础狭窄；在试验设计上常采用多环境试验(MET)，但均按单环境试验进行分别分析，不能对QTL与环境互作(QEI)进行检验和估计。本研究将同时利用连锁分析RIL群体(NJRIKY)和关联分析自然群体(300多份核心种质)进行多年干旱胁迫试验，发展模型中包含多QTL、上位性QTL和QEI效应的MET试验QTL联合分析新方法用于检测大豆耐旱性状组成型和适应型QTL，解析重要QTL上优异等位基因及其来源，开发功能分子标记。研究发掘的耐旱响应QTL将为理解大豆耐旱遗传机制和耐旱大豆MAS提供基础，发展的MET试验QTL联合分析方法将为作物耐非生物胁迫响应QTL研究提供新的分析工具。

干旱是大豆生产中重要的非生物胁迫因素。大豆耐旱性相关QTL的发掘是高效、精准耐旱大豆品种标记辅助选择育种的基础。项目组以江淮大豆育种种质群体200个基因型为材料，分别进行苗期和成株期水分处理试验，多年重复测定耐旱性相关性状。应用TASSEL V5.2 MLM模型分别将各性状在两种水分处理下的BLUP值和耐旱系数与63513个SNP标记进行全基因组关联分析。在苗期株高、地上部干重、主根长和根干重4个性状上共检测到11个显著的SNP标记-性状关联（干旱胁迫下5个，正常灌溉下1个，耐旱系数5个），单个SNP标记的表型变异解释率为8.31～15.22%，干旱胁迫条件下控制株高的QTL位点Gm03_40054626与Abdel-Haleem等（2011）报道的Q_root_Gm03和Carpentieri-Pipolo等（2012）报道的qSV_Gm03共定位。在成株期株高、地上部干重、主茎节数、单株粒数和百粒重5个性状上，共检测到26个显著的SNP标记-性状关联（干旱胁迫下7个，正常灌溉下10个，耐旱系数9个），单个SNP标记的表型变异解释率为8.03～12.67%。这些控制大豆耐旱性相关性状的QTL经过验证后可用于耐旱大豆分子设计育种。QTL分析方法会影响作物耐非生物逆境（干旱、盐胁迫等）响应QTL检测的统计功效、效应和位置估计的准确度和精确度。项目组以RIL群体为例，建立了基于线性混合模型的作物耐非生物逆境响应QTL联合分析方法，编写了实现该方法的计算机程序；系统的模拟试验表明新方法对非生物逆境响应主效QTL和上位性QTL的检测功效令人满意、位置与效应估计的准确度和精确度均较好。这一方法可以为包括大豆耐旱在内的作物耐非生物胁迫响应QTL分析实践提供参考。