【作者】 姜振峰；

【导师】 李玉花； 李文滨； 陈庆山；

【作者基本信息】 东北林业大学 ， 发育生物学， 2010， 博士

【摘要】 大豆起源于中国,是世界范围内重要的经济作物,也是重要的植物油和蛋白来源,在国民生产生活中具有重要作用。目前我国生产上高油和高蛋白大豆品种还不能满足生产生活需要,迫切需要利用现代分子育种技术改良现有大豆品种的油分和蛋白质含量。探讨大豆油分和蛋白含量遗传、QTL(数量性状座位)定位、GE互作(基因型和环境互作)及上位性效应对于开展大豆优质育种、改善大豆油分和蛋白品质具有重要的理论及实践意义。不同研究机构对于大豆油分和蛋白含量的遗传及QTL定位进行了广泛而深入的研究,但是结果一致性较低,原因是大豆油分和蛋白含量性状受环境条件影响明显,以前的研究虽然分析了不同遗传背景对大豆油分和蛋白含量QTL定位的影响,进行了1年或2年多点实验,但是受统计方法和分析软件限制忽略了GE互作和上位性效应。研究表明GE互作和上位性效应对于植物表型变异影响显著,因此,有必要分析GE互作和上位性效应对大豆油分和蛋白含量的影响,研究作用机制,为大豆油分和蛋白优质育种及分子生物学研究提供必要的理论依据。而且大豆油分和蛋白含量性状都属于多基因控制的数量性状,对其数量性状位点进行分析和定位,在分子辅助育种上具有重要指导意义;大豆油分和蛋白含量在不同环境条件下动态稳定能够保证优质增收,但是还没有见到关于大豆油分和蛋白含量稳定性的相关研究,为分析大豆油分和蛋白含量稳定性的遗传、QTL主效应、GE互作及上位性特性,本文利用QTL Maper 1.6版本分析了大豆油分和蛋白含量的shukla方差,明确了大豆油分和蛋白稳定性的遗传及分子机制。本研究利用源自美国大豆Charleston和中国品种东农594杂交获得的147个株系组成的重组自交系群体,在2007、2008年和2009年3个不同的地点对大豆的油分和蛋白质含量进行了遗传分析；定位了控制大豆油分和蛋白质含量的QTL；分析了大豆油分和蛋白含量的GE互作、上位性效应和大豆油分和蛋白含量稳定性QTL的主效应、上位性效应和GE互作效应。利用P1(亲本1)、P2(亲本2)和RIL(重组自交系)群体世代联合分析方法,分别对三点三年的不同环境中组合的油分和蛋白含量进行主基因+多基因混和遗传模型分析,结果表明,大豆油分含量遗传在2007年地点1(红兴隆农场)、2(佳木斯),2008年地点1和2009年地点2均为多基因遗传模型;在2007年地点及2008年地点2、地点3(哈尔滨)均为3对主基因+多基因遗传模型,2009年地点1和3均为2对主基因+多基因遗传模型。蛋白的各个年份地点的最适模型在2007年地点1和3为多基因遗传模型,其它各年各点均为2对主基因+多基因遗传模型。利用符合区间作图法(CIM)和混合区间作图法(MIM)联合对大豆油分和蛋白含量进行QTL定位,互相验证和补充。在三点三年共检测到39个控制油分QTL,位于16个连锁群,平均每个连锁群分布2.44个QTL,其中3个连锁群聚集了15个QTL,位于B1、C2和G连锁群上的特定区域内,但是解释的表型变异都很小,不能被重复检测到；利用CIM和MIM方法共检测到23个控制大豆蛋白含量的QTL,分布在14个不同的连锁群A1、B1、C1、C2、D1a、D1b、E、F、G、I、J、K、L和O,平均每个连锁群分布1.64个QTL,控制大豆蛋白QTL在连锁群C2和Dla被集中检测到,共12个,在这2个连锁群上可能存在较多的控制大豆蛋白含量基因。大豆油分和蛋白QTL存在明显的环境效应。qOIL12-1在7-3和9-1利用CIM和MIM方法聚能检测到,在9-3利用MIM方法能够被检测到;qOIL3-1在7-2、9-2和9-3利用CIM和MIM方法能够被检测到,说明控制大豆油分含量的基因能够在同一地点不同年份间稳定表达；而qOIL2-1在2009年三个地点利用CIM和MIM方法也能够被检测到,说明控制大豆油分含量的基因能够在同一年份不同地点稳定表达。说明油分含量有明显的环境效应,但是在特定条件下能够检测到在各个环境中稳定表达的QTL。说明蛋白含量具有明显环境互作效应；控制蛋白含量的QTL在2007年和2008年各点没有重复出现,说明蛋白含量受环境影响较大,但是在特定条件下能够检测到在各个环境中稳定表达的QTL。利用方差分析联合累加分布方法分析表明,大豆油分和蛋白含量上位性互作普遍存在,而且存在环境互作效应。综合分析一点三年、一年三点和三点三年的主效、上位性效应和环境互作效应分析可知,主效QTL在各点各年稳定存在,但是一致性较差,说明受环境条件影响较大。主效QTL解释的总表型变异值均高于上位性QTL解释的表型变异值,远大于上位性效应和环境互作效应解释的表型变异值,说明,主效QTL是最主要的,QTL上位性效应和上位性环境互作效应均存在,但是上位性效应解释的表型变异远大于上位性环境互作影响的表型变异,因此,在重视主效QTL同时,也要考虑QTL的上位性效应,以研究基因互作的具体机制,为分子辅助选择提供重要的理论依据。利用三点三年数据估算的Shukla稳定性方差对大豆油分和蛋白含量进行了遗传和QTL分析。遗传分析表明大豆油分含量稳定性的最优遗传模型为E-1-1,即加性上位性遗传模型,大豆蛋白含量稳定性最优遗传模型为E-1-0。利用复合区间作图法(CIM)检测大豆油分稳定性QTL得到4个QTL,为qOIL7-9、qOIL8-3、qOIL15-2和qOIL12-2位于染色体D1a、D1b、J和O,贡献率分别为5.33%、14.61%、5.83%和5.37%,共解释31.14%表型变异。阈值最高的QTL(3.52)解释的表型变异也最大(14.61%),具有潜在的应用价值;检测大豆蛋白含量稳定性QTL得到2个QTL,为qPRO1-6和qPRO17-2,位于染色体A1和L,贡献率分别为4.70%和5.73%,共解释10.43%表型变异。大豆油分和蛋白含量稳定性QTL都表现出明显的上位性效应和GE互作效应。本研究鉴定到的控制大豆油分和蛋白含量稳定性的QTL和公共图谱上相应的QTL有非常好的一致性,而且是控制大豆油分、蛋白、产量性状及其它性状的基因集中分布连锁群区段,调控代谢能力较高,具有较强的适应环境条件变化的能力,能够保持油分和蛋白等性状相对于环境变化的稳定性,是非常重要的连锁群区段。本研究对大豆油分和蛋白含量进行的遗传和QTL定位分析为主效QTL精细定位和分子辅助育种提供了理论依据,大豆油分和蛋白的稳定性遗传及QTL定位、GE互作和上位性互作分析为大豆的稳产优质育种提供了一条新的途径好方法,所定位的QTL将对大豆稳产、优质新品种的选育具有重要的理论指导意义。更多还原

【Abstract】 Soybean (Glycine max(L) Merr.) is the most important economic crops, originating from China.Soybean provides vegetable oil and protein for people and livestock. At present, the soybean varieties with high oil or protein content can not satisfy the demand as food or diet in China, which can be alleviated the urgent need by breed more soybean varieties with high oil or protein content than before. Molecular assistant selection (MAS) can facilitate it. To date, many studies on the genetics of oil and protein content, QTL mapping, GE effect and epistatic effect between QTL loci can help improve the quality of soybean seed. However, most results about genetics of oil content and protein content of soybean was not consistent, indicating that the oil and protein content of soybean was sensitive to environmental change. Many soybean varieties were introduced to analyze the effect of genetic background and planted in different locations and different years to clarify the environment effect. However, the GE effect and epistatic effect between QTL loci were neglected as the limitation of statistic method and no help of analysis software, nevertheless, which affected the phenotypic variation with a higher proportion. So it is necessary to clarify the effect of environmental change to GE and epistatic effect that can improve the efforts of MAS. To date, no research was reported to analyze the GE effect and epistatic effect in three years and three locations simultaneously.The population of 147 recombination inbred lines (RIL) derived from the cross of America cultivar Charleston and Chinese variety Dongnong 594 was planted in Harbin, Hongxinglong and Jiamusi in the year of 2007,2008 and 2009 simultaneously to analyze the G×E effect and epistatic effect; As the yield of oil or protein changed significantly resulted in the environmental change, QTL controlled the stability of oil and protein content was mapped using transforming method of shukla ANOVO with data of oil or protein content. The software MGDH1-4 with mixed model approach was used to analyze genetic models with data from parent 1, parent 2 and RIL population. Software QTL Maper version 1.6 was used to analyze the main effect, epistatic effect and GE effect.In current study, the genetic model of oil content of different year and location was observed as follows:multiple gene model in location 1 (Hong xinglong),2 (Jia musi) in 2007, and main genes of three pairs with multiple gene model in location 2,3 (Harbin) in 2007 and 2008, and main genes of two pairs with multiple gene model in location 1 and 3 in 2009; The genetic model of protein content of different year and location was observed as follows:multiple gene model in location 1,3 in 2007, and main genes of two pairs with multiple gene model in locations and years except location 1,3 in 2007.QTL controlling oil content and protein content of soybean was estimated by CIM and MIM which is supplementary and verified each other. Thirty-nine QTL controlling oil content were identified, which located sixteen linkage groups across 2007.2008 and 2009 in three locations. Fifteen QTL clustered to three linkage groups, B1, C2 and G, which R2 was small and no repeat in either years or locations; Twenty-three QTL controlling protein content were identified, which located fourteen linkage groups across 2007,2008 and 2009 in three locations. Twelve QTL clustered to two linkage groups, C2 and Dla, which R2 was small and no repeat in either years or locations.G×E effect was observed both for the QTL of oil content and protein content. Such as, qOIL12-1can be identified in location 3 in 2007 and in location 1 in 2009 by CIM and MIM, and in location 3 in 2009 by MIM; qOIL2-1 can be identified by CIM and MIM across 3 location in 2009. Similar result can be observed in protein.Epistatic effect can be observed by ANOVA and cumulative distribution method both oil content and protein content and interaction between epistatic effect and environment was observed. Main effect, epistatic effect and G×E were analyzed using the software QTL Maper 1.6 for the data of one location across three years, of one year across three location and three location across three years. QTL main effect can be identified across every year or every location with low consistency, which resulted from significantly environmental change. R2 of main QTL was high than epistatic QTL and much higher than interaction QTL between epistatic effect and environment. Therefore, it is necessary to analyze main QTL and epistatic QTL simultaneously for MAS.The stability of oil content and protein content was estimated using shukla ANOVO results. E-1-1 was estimated as the optimally genetic model for stability of oil content and E-1-0 was estimated as the optimally genetic model for stability of protein content. Four QTL, qOIL7-9、qOIL8-3、qOIL15-2 and qOIL12-2 located linkage group Dla、Dlb、J and O respectively and responsible for R2,5.33%、14.61%、5.83% and 5.37% respectively, were identified for stability of oil content by CIM. QTL with the highest LOD was responsible for the highest R2 (14.61%). Two QTL, qPRO1-6 and qPRO17-2, were identified for protein content, located on linkage group Al and L respectively, and accounted for 4.70% and 5.73% of the phenotyping variation. Moreover, the chromosome region controlled the stability of oil content and protein content also possess genes controlled other traits, which region can regulate the metabolic pathway more than other regions to adapt environmental change. The current study provides theoretical evidence for fine QTL mapping and MAS.更多还原