摘要
本研究：(1)利用一目惚、丰锦、笹锦、日本晴、沈农265、秋田小町、辽粳263、02428和辽粳294等9个粳稻品种及河田香稻、Kasalath、Habataki、IR36、R99和IR3等6个籼稻品种为材料构建了用于水稻基因型分析的高信息量SSR框架图；(2)比较了沈农265和丽江新团黑谷的F2群体与RIL群体的遗传信息,并利用RIL群体及构建的连锁图谱对剑叶相关性状、穗相关性状、籽粒相关性状、株高及其构成因素和3个不同生育时期的叶绿素含量进行QTL分析,并分别进行深入比较；(3)对同时控制穗长、节间长和剑叶长的重要株型相关基因qPCL9进行精细定位。主要结果如下：
(1)用489对SSR引物对9份粳稻和6份籼稻材料进行SSR标记分析,每条染色体的总体多态性信息量(PIC)值分布于0.4039～0.5840之间,籼稻亚种内的PIC值分布于0.3685～0.4952之间,粳稻亚种内的PIC值分布于0.1326～0.3164之间,籼稻的多态性高于粳稻。以PIC值作为主要参考指标筛选出适于遗传多样性分析的199对SSR引物(总体PIC值>0.50),从中选择建立了包含141个SSR引物的多样性分析体系。筛选出籼粳特异性引物93对,其中包括17对核心引物、48对二级引物和28对三级引物。确定了32对适于粳稻遗传多样性分析的引物(粳稻PIC值>0.50)。这些引物能很好地反映品种间的遗传多样性。
(2)比较分析了F2群体和RIL群体的遗传信息及控制剑叶相关性状(剑叶长、剑叶宽和比叶重)的QTL：1)多数标记在染色体上的顺序相同,但标记间距不同。F2群体中30个标记显著偏离孟德尔分离比例(P<0.05),13个标记极显著偏离预期的(1：2：1)孟德尔分离比例(P<0.0),其中19个偏向SN265,11个偏向LTH。RIL群体中62个标记显著偏离预期的(1：2：1)孟德尔分离比例(P<0.05),38个标记极显著偏离预期的(1：2：1)孟德尔分离比例(P<0.01),其中43个偏向SN265,19个偏向LTH。偏分离标记共形成10个偏分离区域,其中有6个区域同时出现在在两个群体中。2)RIL群体检测QTL的能力强于F2群体,F2群体共检测到7个控制剑叶性状的QTL(2个控制剑叶长；4个控制剑叶宽；1个控制比叶重),而RIL群体共检测到17个控制剑叶性状的QTL(7个控制剑叶长；5个控制剑叶宽；5个控制比叶重),在两群体中同时检测到的QTL有4个,分别是9号染色体上控制剑叶长的qFLL9; 4号染色体上控制剑叶宽的qFLW4;12号染色体上控制剑叶宽的qFLW12.1和6号染色体上控制比叶重的qSLW6。其中控制比叶重的qSLW6(加性效应值为1.956mg/cm2),极富研究与应用价值。
(3)12个穗部性状和3个籽粒性状在RIL群体中表现为接近正态的连续分布,变异幅度大,呈现双向超亲分离。共检测到控制12个穗部性状的QTL 39个,包括控制穗长的QTL有4个；控制一次枝梗数的QTL有5个；控制二次枝梗数的QTL有3个；控制每穗颖花数的座位有2个；控制每穗实粒数的QTL有2个；控制一次枝梗颖花数的QTL有5个；控制每个一次枝梗上的颖花数的QTL有5个；控制二次枝梗颖花数的QTL有5个；控制每个二次枝梗上的颖花数的QTL有4个；控制结实率的QTL有4个；控制一次枝梗结实率的QTL有2个；控制二次枝梗结实率的QTL有3个。这些QTL分别在第2、4、7、11和12号染色体上形成QTL簇，这一现象很可能是穗部性状显著相关的遗传基础。检测到控制籽粒性状的QTL13个,其中包括控制千粒重的QTL4个；控制粒长的QTL5个；控制粒宽的QTL4个。其中第2染色体RM250-RM207区域同时控制粒长和粒宽,第3染色体中部同时控制粒长和千粒重,第9染色体RM24412-H90区域同时控制粒长、粒宽和千粒重。
(4)对水稻株高及其构成因素进行QTL定位,并与控制赤霉素和油菜素内酯合成及信号转导的相关基因进行比对分析发现。RIL群体的株高及各构成因素均呈正态分布。株高与各构成因素间呈正相关,且相关系数由上至下递减。相邻的构成因素间呈极显著的正相关,而相距较远的构成因素间的相关性减弱甚至负相关,进一步分析表明株高主要受倒1和倒4节间长度的影响。共检测到控制株高及其构成因素的QTL 21个,分布在第1、2、3、5、6、7、8、9、11和12号染色体上。其中位于第9染色体上的QPH9b即直立穗基因EP1(DEP1或qPE9-1)对于水稻的株高起着很重要的作用,其主要通过影响倒1和倒2节间的长度来影响株高,该基因的分子功能与之前发现的众多控制株高的基因均不同,可能是一个种新的调控株高的机制。通过比较21个QTL与赤霉素和油菜素内酯合成及其信号转导相关基因发现,该群体株高的遗传基础极其复杂,根据比较分析的结果提出了株高调控的可能分子机制。
(5)对水稻分蘖期、抽穗期和成熟期的叶绿素含量以及生育后期的持绿能力进行QTL定位分析。检测到5个控制分蘖期叶绿素含量的QTL、7个控制水稻抽穗期叶绿素含量的QTL和10个控制成熟期叶绿素含量的QTL,分布在除第5染色体以外的11条染色体上。比较它们与编码叶绿素合成及降解过程中的重要酶的基因发现,虽然生育前期检测到的QTL较少,但对应的叶绿素合成降解相关基因却较多。随生育期的推移,检测到的QTL数目增多,但对应的叶绿素合成降解相关基因却减少。暗示生育前期大多数叶绿素合成(降解)相关基因表达的水平差异不大,后期控制叶绿素合成降解的个别关键基因表达水平增加。并以此为基础提出了叶片生育后期持绿的两种可能生理基础。
(6)利用F2和RIL群体在第9染色体上RM566-RM160之间鉴定到一个同时控制穗长、秆长和剑叶长的重要区域,暂命名为qPCL9。为了避免其它位点的干扰,利用标记辅助选择筛选到9号染色体长臂目标区段杂合,而背景纯合的剩余杂合单株qPCL9。在该单株衍生的889个F2个体中,未检测到三个性状之间的重组现象,因此我们推测此三个性状由同一个基因控制。因为RHL-qPCL9表现为短穗、短秆(短节间)和短剑叶表型,且其后代分离为短(658)：长(231)=2.85：1.00(χ2=0.4593,P>0.05)符合3：1的分离比,判断qPCL9为隐性基因。并利用该群体将qPCL9定位在标记RM24423和RM24434之间,根据RAP数据库的注释,该区间为198-kb,包含17个预测基因。考虑基因的表达位置和功能,AK107584(similar to cytochrome P450 monooxygenase CYP92A1)、AKl 11616(similar to elicitor-inducible cytochrome P450)和J065094C22 (similar to cytochrome P450)可能是候选基因，但也不排除其它预测基因的可能。
The main contents in this study is 1) to develop a highly informative microsatellite (SSR) marker framework for rice (Oryza sativa L.) genotyping by using fifteen rice cultivars including 6 indica varieties (He-tian-xiang-dao, Kasalath, Habataki, IR36, R99, IR3) and 9 japonica varieties (Hitomebore, Toyonishiki, Sasanishiki, Nipponbare, Akitakomachi, Shen-nong265, Liaojing263, Liaojing294,02428),2) to comparative analysis of genetic information between two populations (F2 and RIL) and to detect and compare QTL for panicle related traits, grain related traits, flag leaf traits, plant height and its components and chlorophyll content at the stages of tillering, heading and maturity by employing RIL population derived from the cross between Shennong 265 and Lijiangxintuanheigu and its genetic linkage map and 3) to fine map the important plant type related quantitative trait locus qPCL9, which controlling flag leaf length, internode length and flag leaf length. The main results are as follow:
(1) Six indica varieties and nine japonica varieties were used to analyze the polymorphism information content (PIC) value of 489 SSR markers. The PIC value of each chromosome were ranged from 0.4039 (chromosome 2) to 0.5840 (chromosome 11). Between the two rice subspecies, indica (0.3685～0.4952) gave a larger PIC value than japonica (0.1326～0.3164) and displayed a higher genetic diversity. A SSR framework including 141 highly informative markers for genotyping was selected from 199 SSR markers (PIC>0.50). Ninety-three SSR markers distributed on 12 chromosomes were found to be related to indica-japonica differentiation. Of these SSR primers,17 pairs were considered to be as core primers (all the japonica varieties have the same specific alleles, while the indica varieties have another specific alleles),48 pairs as second class primers (all the japonica (or indica) varieties have the same specific alleles, while the indica (or japonica) varieties have two or more other specific alleles) and 28 pairs as third class primers (all the japonica and indica varieties have two or more alleles, but the specific alleles are difference between japonica and indica). Thirty-two SSR markers were selected to be highly informative and useful for genetic diversity analysis of japonica varieties.This work provides a lot of useful information of SSR markers for rice breeding programs, especially for genotyping, diversity analysis and genetic mapping.
(2) Comparative analysis of genetic information and QTL controlling flag leaf related traits including flag leaf length, flag leaf width and specific leaf weight between two populations (F2 and RIL) derived from a same cross between two japonica rice cultivars, 'Shennong265'and'Lijiangxintuanheigu' were studied.1) Most markers had same sequence along chromosomes, but the genetic distance between two markers was different. Thirty and thirteen markers showed genetic distortion significantly and extremely significantly in F2 population, separately. Nineteen and eleven markers deviated toward SN265 and LTH, separately. Sixty two and thirty eight markers showed genetic distortion significantly and extremely significantly in RIL population, separately. Forty three and nineteen markers deviated toward SN265 and LTH, separately. These distortional markers formed ten segregation distortion regions (SDR). Six of them were detected in both F2 and RIL populations.2) RIL population had more powerful detective ability than F2 population. Seven QTL controlling flag leaf related traits including two controlling leaf length, four controlling leaf width and one controlling specific weight were detected in F2 population. While seventeen QTL for these traits (seven for leaf length, five for leaf width and five for specific leaf weight) were detected in RIL population. Four QTL were detected in both populations including qFLL9 controlling flag leaf length on chromosome 9, qFLW4 controlling flag leaf width on chromosome 4, qFLW12.1controlling flag leaf width on chromosome 12 and qSLW6 controlling specific leaf weight on chromosome 6. Among them, qSLW6 (Additive effect=1.956mg/cm2) for specific leaf weight has a high research and application value.
(3) 12 panicle related traits and 3 grain related traits showed a continuous normal distribution in the RIL population and transgressive segregation was also identified in all 15 traits.39 QTL were identified for panicle related traits including four for panicle length, five affecting primary branch number per panicle, three controlling secondary branch number per panicle, two affecting spikelet number per panicle, two controlling grain number per panicle, five for spikelet number of primary branch, five for spikelet number per primary branch, five controlling spikelet number of secondary branch, five affecting spikelet number per secondary branch, four controlling percent seed set, two for percent seed set of primary branch and two controlling percent seed set of secondary branch. They showed cluster forms on chromosome 2, 4,7,11 and 12. Clusters of QTL in genome would be the important genetic basis of the correlation among panicle related traits.13 QTL were detected for grain related traits (4 for 1000-grains weight,5 for grain length and 4 for grain width). The region between RM205 and RM207 on chromosome 2 controlled both phenotypes of grain length and width. The middle of chromosome 3 affected grain length and 1000-grains weight. The region between RM24412 and H90 controlled grain length, grain width and 1000-grains weight on chromosome 9.
(4) QTL affecting plant height and its component factors were analyzed by employing 126 recombinant inbred lines (RIL) derived from a cross between two japonica rice cultivars, Shennong265 and Lijiangxintuanheigu. And then compared them with the genes involved in gibberellins and brassinosteroid biosynthesis and transduction. Plant height and its component factors showed a continuous normal distribution in the RIL population. The plant height showed a high positive correlation with its component factors, respectively. The correlation between plant height and its component factors descended from upper to lower. The correlation between adjacent plant height components was positively significant while the significance of the correlation between non-adjacent plant height components was less even negative. Further result indicated that the plant height is mainly affected by the length ofⅠinternode andⅣinternode.A total of 21 QTL controlling plant height and its components were identified on chromosomes 1,2,3,5,6,7,8,9,11 and 12, respectively. QPH9b (EP1, DEP1 or qPE9-1) on chromosome 9 plays a very important role in affecting plant height through controlling theⅠinternode andⅡinternode length from top. Its molecular function was different from the other genes controlling plant height be identified previously. So, it would be provided a novel mechanism for plant height. Comparison between 21 QTL and genes controlling gibberellins and brassinosteroid biosynthesis and transduction indicated that the genetic basis of plant height is extremely complex in this RIL population. And possible molecular mechanism for plant height was proposed by result of the comparison.
(5) We analyzed the QTL controlling chlorophyll content at the stages of tillering, heading and maturity. Five, seven and ten QTL controlling chlorophyll contents at tillering stage, heading stage and maturity stage were detected, respectively. They were distributed on all rice chromosomes except chromosome 5.Comparison of the QTL and the genes underlying the key enzymes of chlorophyll biosynthesis and degradation revealed that relatively more QTL detected at earlier stage co-located with the genes related to chlorophyll biosynthesis and degradation. With the growth stage going on, more QTL were detected but only a few of them involved in chlorophyll biosynthesis and degradation. The results suggested that the expression level of most genes related to chlorophyll biosynthesis (degradation) had no difference at earlier stage but specific key genes increased at later stage. And two possible genetic bases for stay-green were proposed.
(6)qPCL9, which controlling panicle length, culm length and flag leaf length, was identified on chromosome 9 in both F2 and RIL populations. In order to eliminate the influence of other loci, one single residual heterozygous plant for qPCL9 region, RHL-qPCL9 was selected based on MAS. We did not obtain any recombination among these three traits.This result revealed that these three traits were controlled by a same gene. We found that the heterozygous RHL-qPCL9 plant had short panicle, cuhn and flag leaf, and the segregation ratio between short plants and long plants in the segregating population was 658:231=2.85:1.00, fitting well to the 3:1 ratio (χ2=0.4593,P>0.05). These results revealed that the length of panicle, culm and flag leaf was controlled by a single gene,and it is a recessive trait in this population. Using this segregating population, this region was narrowed down to an interval between RM24423 and RM24434. According to the rice annotation project database, there are seventeen predicted genes in the 198-kb target region. Considering the organ specificity in gene expression and the molecular function information from a protein knowledgebase,AK107584 (similar to cytochrome P450 monooxygenase CYP92A1),AK111616 (similar to elicitor-inducible cytochrome P450) and J065094C22 (similar to cytochrome P450) might be the most likely candidate genes for qPCL9, but does not rule out the possible of the ten other candidate genes.
引文
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