【作者】 江建华；

【导师】 洪德林；

【作者基本信息】 南京农业大学 ， 种子科学与技术， 2011， 博士

【摘要】 目前,中国水稻年种植面积3067万hm2。其中,杂交籼稻的种植面积已达1733万hm2,约占中国籼稻种植面积的80%,占中国水稻种植面积的一半以上。相对于杂交籼稻取得的巨大成就,杂交粳稻的发展却十分缓慢。粳稻年种植面积828万hm2,以常规粳稻为主,杂交粳稻所占比例不超过3%。杂交粳稻产量竞争优势不明显是阻碍其发展的重要因素。剖析粳稻产量相关性状及其杂种优势的分子遗传基础有助于利用分子标记辅助选择改良亲本,提高产量竞争优势。本研究以粳稻栽培品种秀水79和粳稻恢复系C堡及其衍生的含有254个家系的重组自交系群体(以下简称“秀堡RIL群体”)为材料,开展了以下四个层面的分析。第一,从秀堡RIL群体中选取每穗颖花数最多和最少的极端类型个体杂交,配制2个组合6个世代,对粳稻穗部5个性状进行主基因+多基因遗传分析；第二,在多个环境下种植秀堡RIL群体,调查不同生长时期的分蘖数和苗高,对这2个性状进行动态QTL分析；第三,在2个环境下对秀堡RIL群体的生育期、株高和单株有效穗数3个性状进行条件和非条件QTL定位；第四,将秀堡RIL群体中的株系与其双亲回交,构建2个回交群体,利用秀堡RIL群体本身及其2个回交群体,检测10个产量相关性状及其中亲优势的主效位点和双基因互作位点。主要研究结果如下：1.秀堡RIL群体中每穗颖花数最多的株系与每穗颖花数最少的株系杂交后3个分离世代(B1、B2和F2),每穗颖花数性状在2个组合的各分离世代均未出现超亲个体,而其它4个穗部性状均有不同程度的超亲分离。表明每穗颖花数最多的个体已聚集了双亲表现出来的全部的增效等位基因,每穗颖花数最少的个体已聚集了双亲表现出来的全部的减效等位基因。运用主基因+多基因混合遗传模型分析显示,每穗颖花数、每穗实粒数、穗长和二次枝梗数4个性状均受2对主基因+多基因控制,以主基因遗传为主。一次枝梗数性状受1对主基因+多基因控制,以多基因遗传为主。2.水稻一生中分蘖数的增加和减少是由不同位点控制的。在南京和泗洪2个环境下调查秀堡RIL群体254个家系及双亲9个生长时期的单株分蘖数,利用混合线性模型和最佳线性无偏预测法对不同时期分蘖数变异的各效应值进行估计,并利用非条件和条件QTL定位的方法对控制单株分蘖数性状的静态位点和动态位点进行检测。结果9个调查时期共检测到13个非条件QTL,不同时期检测到的同一加性位点增效等位基因来源相同。条件定位的方法9个调查时期也检测到13个QTL。其中分蘖数增加的t1-t4期检测到7个条件QTL(qTN2.1、qTN4、qTN5.1、qTN5.2、qTN7.1、qTN9.1和qTN10), qTN4和qTN7.1增效等位基因来自秀水79,其余5个位点的增效等位基因均来自C堡。分蘖数减少的t5-t9期检测到6个条件QTL (qTN2.2、qTN3、qTN8.1、qTN8.2、qTN11.1和qTN11.2),除qTN8.2增效等位基因来自于C堡外,其余均来自秀水79。反映出水稻分蘖数的增加和减少是由不同位点控制的。秀堡RIL群体中不同株系含有的有利等位变异数与该株系的单株有效穗数呈极显著正相关(r=0.347**)。表明通过不同时期的有利等位基因的聚合可以提高单株有效穗数。3.控制苗高的位点在不同生长时期其遗传效应不同。调查南京和泗洪2年3个环境下秀堡RIL群体254个株系及其亲本9个不同生长时期的苗高,利用与上述“2”相同的分析方法对苗高性状进行分析。结果9个调查时期共检测到15个非条件加性QTL。不同时期检测到的同一加性位点增效等位基因来源相同,效应随着发育进程的推进而增大。条件定位法9个调查时期检测到16个条件加性QTL和16个互作位点对。6个加性QTL在2个时间段被检测到,其余位点(位点对)均在单个时期被检测到。说明控制苗高性状的位点具有时序性表达的特点。条件加性QTL和条件上位性QTL总遗传效应和总解释表型变异率在全生育期显示多峰分布。表明控制苗高的位点在不同调查时期的遗传效应不同。t1｜t0至t8｜t7时间段加性QTL总解释表型变异率明显大于上位性QTL的总解释表型变异率,t9｜t8时间段两者基本一致。反映出从播种至移栽后98d,控制苗高的位点以加性遗传效应为主；98d至112d受加性效应和上位性效应共同控制。GE互作遗传效应在整个调查时期均很小。4.利用非条件定位和条件定位相结合的方法可以发掘目标性状适用的有利等位变异。在南京和泗洪2个环境下种植秀堡RIL群体的254个株系及其亲本,对粳稻生育期、株高和单株有效穗数进行非条件和条件QTL定位。3个性状两种方法检测到的QTL均以加性效应为主。将生育期矫正到同一水平,单株有效穗数检测到1个适用有利等位变异RM80-160bp,加性效应为0.71。将单株有效穗数矫正到同一水平,生育期性状检测到1个适用的有利等位变异RM448-240bp,加性效应为4.64。将株高矫正到同一水平,单株有效穗数性状检测到1个适用有利等位变异RM80-160bp,加性效应为0.62；生育期性状检测到1个适用有利等位变异RM448-240bp,加性效应为3.89。利用这些适用有利等位变异改良目标性状时不会对矫正性状产生影响。5.加性×非加性以及显性×显性互作效应是粳稻秀堡组合杂种优势的主要遗传基础。调查秀堡RIL群体及其2个回交(BCF1)群体中与产量相关的10个性状,利用这些性状的表型值和中亲优势值对这10个性状进行QTL定位。3个群体共检测到78个主效QTL (Main-effect QTL,简写M-QTL),单个QTL解释表型变异率在2.4-41.9%之间。79.5%(62个)的QTL表现为加性效应,11.5%(9个)的QTL表现为部分或完全显性效应,9.0%(7个)的QTL表现为超显性效应。3个群体共检测到114对显著的双基因上位性QTL(Epistatic QTL,简写E-QTL)。RIL群体中检测到58对E-QTL,单对E-QTL解释表型变异率在1.7-8.0%之间,平均3.7%。XSBCF1群体中检测到29对E-QTL,其中利用BCF1表型值检测到17对E-QTL,每对E-QTL解释表型变异率在10.9-78.5%之间,平均29.8%；利用中亲优势值检测到12对E-QTL,每对E-QTL解释表型变异率在15.0-71.8%之间,平均46.5%。CBBCF1群体中检测到27对E-QTL,其中利用BCF1表型值检测到15对E-QTL,每对E-QTL解释表型变异率在2.7-64.4%之间,平均29.7%；利用中亲优势值检测到14对E-QTL,每对E-QTL解释表型变异率在21.2-64.1%之间,平均36.2%；有2对E-QTL以BCF1表型值和中亲优势值计算都被检测到。表明粳稻杂种优势是加性×非加性以及显性×显性互作效应共同作用的结果。更多还原

【Abstract】 Rice (Oryza sativa L.) growing area in China is 30,670,000 ha each year. Among them, indica hybrid rice planting area is 17,330,000 ha and accounts for more than 80 percent of China indica rice planting area and 50 percent of China’s rice growing area. Japonica rice growing area in China is 8,280,000 ha annually. The area planted with japonica hybrid rice only occupied 3 percent of the total area of japonica rice in China. Therefore, great space exists for developing japonica hybrid rice, compared with indica hybrid rice, in which great achievement had been made. The major reason for low speed of japonica hybrid rice development is that competitive heterosis of hybrid cultivar is not conspicuous in yield, compared with conventional cultivar in japonica rice. Dissecting molecular genetic basis of yield-related traits and its heterosis is helpful to improve competitive heterosis of hybrid cultivar in yield by molecular marker-assisted selection (MAS). Four studies were carried out by using the recombinant inbred line population ("Xiubao RIL population" for short hereinbelow) contained 254 lines derived from a cross between Xiushui 79 (japonica cultivar variety) and C Bao (japonica restorer line) and their parents in this study. Firstly, genetic segregation analysis of the five panicle traits were conducted by using the mixed major gene plus polygene inheritance model for P1, P2, F1, B1, B2 and F2 generations of two crosses, which were made by using two lines having panicles with the most spikelet number and two lines having panicles with the least spikelet number selected from Xiubao RIL population. Secondly, dynamic QTL analysis of tiller number (TN) and seedling height (SH) in different investigated stages were performed by using Xiubao RIL population across environments. Thirdly, unconditional QTL mapping and conditional QTL mapping of growing duration (GD), plant height (PH) and panicle number per plant (PN) were performed by using Xiubao RIL population in two environments. Finally, QTLs of ten yield-related traits and their mid-parental heterosis were detected by using of the Xiubao RIL population and the two backcross populations. The main results are as follows:1. The transgressive segregation of the five traits except spikelet number per panicle (SNP) was observed in three segregation generations (B1、B2 and F2) in both of the two crosses. The result indicated the lines having panicles with the most spikelet number polymerized all exhibited positive alleles from two parents, whereas the lines having panicles with the least spikelet number polymerized all exhibited negative alleles from two parents. By using major gene-polygene mixed inheritance models, genetic analyses showed that SNP, filled grain number per panicle (FGP), panicle length (PL) and secondary branch number per panicle (SBN) were controlled by two major genes plus polygenes. The four traits were mainly governed by major genes. Primary branch number per panicle (PBN) was controlled by one major genes plus polygenes. The trait was mainly governed by polygenes.2. Increase and decrease of TN were controlled by different loci in rice of all development stages. Tiller numbers of 254 recombinant inbred lines and two parents, Xiushui 79 and C Bao, were recorded every 14 days until maturity across two environments, Nanjing and Sihong. Genetic effects for TN at different measuring stages were estimated by the mixed line model and the best linear unbiased prediction method. Static loci and dynamic loci affecting tiller numbers were detected by using unconditional and conditional QTL mapping methods. Thirteen unconditional additive QTLs were identified for TN at nine stages. For the identical locus detected at various stages, positive alleles came from the identical parent. Seven of the 13 conditional additive QTLs were detected from stage 1 to stage 4 when TN increased. Xiushui 79 carried positive alleles for qTN4 and qTN7.1, and C Bao carried positive alleles for qTN2.1, qTN5.1, qTN5.2, qTN9.1 and qTN10. The remaining 6 loci (qTN2.2, qTN3, qTN8.1, qTN8.2, qTN11.1 and qTN11.2) were detected between stage 5 and stage 9 when TN decreased. Alleles which decreased tiller mortality were except for qTN8.2, from Xiushui 79. Within the 13 conditional QTLs detected, number of elite alleles contained by the RILs extremely significantly positive correlated with productive number per plant (r=0.347**) of the lines. These results indicate that tiller morphogenesis and mortality are controlled by different loci, and it is possible to enhance productive panicles per plant by pyramiding the elite alleles at different stages.3. Genetic effects of loci affecting SH were different at different growing stages. SH of 254 recombinant inbred lines and two parents, Xiushui 79 and C Bao were measured at nine investigated stages by subjected to three different environments. Genetic analysis was conducted by using the same method as mentioned above "2". The result showes that fifteen unconditional additive QTLs were identified at nine different developmental stages. For the identical unconditional additive locus detected at various stages, alleles with positive effect came from the identical parent. And the additive effect increased with the plant growth. Sixteen conditional additive QTLs and sixteen epistatic QTL pairs involved in SH were identified at nine measurement stages. It shows that these loci of SH exhibited the temporal expression pattern. Total additive genetic effect and total expained phenotypic variability of conditional QTL shows multimodal distribution in whole development stages. The result indicated genetic effects of loci affecting SH were different at different growing stages. Total expained phenotypic variability of epistatic QTL significant less than that of additive QTL from t1|t0 to t8|t7, whereas both of them was consistent in t9|t8. It reflected that the additive effect was the major genetic effect at the period from sowing to 98d after transplanting, whereas SH was controlled by both additive effect and epistatic effect during 98d and 112d. Effect of GxE interaction was small during all developmental stages.4. Applicable elite allele of target trait can be mined by the combination of unconditional with conditional mapping. Unconditional QTL mapping and conditional QTL mapping were conducted for GD, PH and PN using Xiubao RIL population. The RIL population consisted of 254 lines and two parents were planted in two environments, Nanjing and Sihong. Result showed that additive effects were major in all of QTLs for GD, PH and PN detected by the two methods. After GD was adjusted to an identical level, RM80-160bp was detected as an applicable elite allele for PN, with additive effect 0.71. After PN was adjusted to an identical level, RM448-240bp was detected as an applicable elite allele for GD, with additive effect 4.64. After PH was adjusted to an identical level, RM80-160bp was detected as an applicable elite allele for PN, with additive effect 0.62, and RM448-240bp was detected as an applicable elite allele for GD, with additive effect 3.89. These applicable elite alleles could be used to improve target traits without influencing the adjusted trait.5. The heterosis in japonica rice is attributable to the orchestrated outcome of additive by non-additive and dominant by dominant interactions. QTLs of GD, PH, PN, PL, SNP, spikelet ferlitity (SF), spikelet density (SD), PBN, SBN and secondary branch distribution density (SPD) were detected by using phenotypic value in Xiubao RIL population, and BCF1 phenotypic value and mid-parental heterosis value in the two backcross populations, XSBCF1 and CBBCF1.78 M-QTLs (Main-effect QTLs) were identified in the 3 population. The percentage of phenotypic variance explained by each QTL ranged from 2.4%to 41.9%. 79.5%(62) of the QTLs detected showed an additive effect,11.5%(9) a partial-to-complete dominant effect, and 9.0%(7) an overdominant effect.114 pairs of QTL were detected in the 3 populations showing digenic interactions. Among them,58 pairs of E-QTL were detected in RIL population, and the percentage of phenotypic variance explained by each pair of QTL ranged from 1.7% to 8.0%, with an average 3.7%. In XSBCF1 population,29 pairs of E-QTL were detected.17 pairs of E-QTL were detected by using XSBCF1 phenotypic value, and the percentage of phenotypic variance explained by each E-QTL ranged from 10.9% to 78.5%, with an average 29.8%.12 pairs of E-QTL were detected by using mid-parental heterosis value (HMP), and the percentage of phenotypic variance explained by each E-QTL ranged from 15.0% to 71.8%, with an average 46.5%. In CBBCF1 population,27 pairs of E-QTL were detected.15 pairs of E-QTL were detected by using BCF1 phenotypic value, and the percentage of phenotypic variance explained by each pair of E-QTL ranged from 2.7% to 64.4%, with an average 29.7%.14 pairs of E-QTL were detected by using the mid-parental heterosis value (HMP), and the percentage of phenotypic variance explained by each pair of E-QTL ranged from 21.2% to 64.1%, with an average 36.2%.2 pairs of E-QTL were detected by using both BCF1 phenotypic value and HMP value in CBBCF1 population. These results showed that additive×non-additive and dominant×dominant interactions effect were the primary genetic basis of heterosis in Xiubao crosses in japonica rice.更多还原