水稻顶部三叶与穗重的关系及其QTL分析

 摘要: 对水稻汕优63重组自交系群体顶部3张叶片的长、宽、重和单穗重等10个性状进行了相关分析和QTL定位。穗重与9个叶片性状存在极显著的正相关，其中与倒2叶重的相关系数最大，剑叶重次之。所有性状在重组自交系群体中均存在双向超亲分离，接近正态分布。共检测到44个主效QTL和43对双位点互作影响上述10个性状。主效QTL分布于水稻的除第8染色体外的其余11条染色体上，贡献率介于3.19%~26.23%；互作分布于水稻的12条染色体上，贡献率变幅为2.03%~8.93%。第2染色体的R2510-RM211标记区间同时检测到控制单穗重和倒2叶重的QTL，该QTL对超级稻株型育种具有应用价值。     

水稻种子低氧发芽力的QTL定位和上位性分析

利用35份水稻品种资源,评价了在不同水深、温度等低氧条件下的种子萌发情况,表明水温30℃、水深0.2 m下黑暗萌发5 d为最佳鉴定方法,并以此条件下水稻种子萌发的芽长为鉴定指标,评价了359份水稻品种低氧发芽力地区间、籼粳间的差异。进一步利用81个Kinmaze/DV85 重组自交系群体进行了水稻低氧发芽力数量性状位点分析, 在第1、2、5、7染色体上检测到5 个低氧发芽力QTL,其中第5染色体上存在2个QTL,各QTL的贡献率为10.5%～19.6%。同时进行上位性分析,检测到3对互作位点,分别位于第2、3、5、11染色体上,其中位于第3染色体上标记C563-X182之间的位点与第5染色体上标记R830-X208之间的位点的互作贡献率高达48.78%。     

大豆百粒重QTL的上位效应和基因型×环境互作效应

基于Charleston×东农594重组自交系群体,采用完备区间作图和混合线性模型对2006-2010年连续5年的百粒重QTL进行定位,并进行基因×环境互作及上位性分析。结果定位了16个与大豆百粒重性状相关的QTL,其中有5个QTL分别与环境发生互作,互作贡献率在0.11%～0.52%之间;定位了8对上位互作位点,贡献率在1.15%～2.59%之间。     

大豆百粒重QTL的上位效应和基因型×环境互作效应分析

本研究中基于Charleston×东农594重组自交系群体,采用完备区间作图和混合线性模型对2006-2010年连续5年的百粒重QTL进行定位,并进行基因×环境互作及上位性分析。本研究定位了16个与大豆百粒重性状相关的QTL,其中有5个QTL分别与环境发生互作,互作贡献率在0.11%~0.52%之间;定位了8对上位互作位点,贡献率在1.15%~2.59%之间。     

多环境条件下大豆蛋白质含量稳定性QTL分析

为定位大豆蛋白质含量稳定性QTL,从而为培育高蛋白大豆品种提供依据,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,利用三种生态环境下三年数据估算的Shukla稳定性方差对大豆蛋白含量进行了遗传和QTL分析。结果表明,利用复合区间作图法（CIM）检测大豆蛋白稳定性QTL得到2个QTL,分别为qPRO1-1和qPRO17-1,位于连锁群A1和L上,贡献率分别为4.70%和5.73%,共解释10.43%的表型变异。利用混合区间作图法MIM检测到2对上位性QTL,互作染色体为A1×G和A1×A2,上位效应分别为0.19**和-0.22,贡献率为12.82%和17.42%,共解释30.24%表型变异。本实验分析多个环境下的数据,考虑到了QTL 与环境的互作效应,在三种环境条件下分析QTL,检测到了在不同环境下可以稳定出现的QTL位点。控制大豆蛋白含量的QTL位点,都表现出明显的上位性效应和GE互作效应。其中稳定性较好的QTL和公共图谱上定位的调控大豆蛋白质含量的QTL prot 1-7、cq oil003、oil8-1, prot 17-5、prot 2-1、prot 12-1等在区间上一致。     

应用候选基因定位水稻抗稻瘟病QTL

 应用经克隆了的已知功能或有潜在功能的DNA序列,即候选基因，作为分子标记，在中156/谷梅2号F8重组自交系群体中进行水稻抗稻瘟病QTL的分析。大部分候选基因在水稻染色体上成簇分布，并且位于已知抗病基因簇区域。应用复合区间法检测到1个调控病斑大小和1个调控病斑数量的QTL，前者位于第1染色体CG36a~RM212区间，贡献率为4.17%，抗性等位基因来自父本谷梅2号；后者定位于第2染色体CG18a~RM263区间，贡献率为6.25%，抗性等位基因来自母本中156。同时检测到2对控制病叶面积和1对控制病斑大小的基因互作。这些QTL和互作基因涉及抗性基因同源序列、离子通道调控子以及编码致病相关蛋白和几丁质酶的基因，表明候选基因的应用有助于揭示QTL的功能。玉米锈病抗性基因Rp1与稻瘟病抗性有关，提示了利用水稻这个模式作物来克隆较大基因组中有利基因的可能性。     

水稻苗期盐胁迫下叶绿素荧光参数的QTL分析

 应用247个株系组成的珍汕97B/密阳46重组自交系群体及其相应的含250个分子标记的高密度分子遗传图谱,通过复合区间作图法,对苗期水培和盐胁迫条件下水稻叶片叶绿素荧光参数进行了数量性状座位（QTL）分析。检测到控制水稻叶片叶绿素荧光参数（Fo、Fm和ΦPSⅡ）的7个主效应QTL,分布在水稻的第1、4、5和11染色体上,贡献率为598%～10.74%。其中,控制水培条件下Fm的QTL与控制盐胁迫下Fo的QTL均位于第5染色体的CDO82-RG413标记区间,说明此区间的QTL具有多效性,可同时影响Fm、Fo两个叶绿素荧光参数。     

水旱条件下近红外发射光谱预报水稻直链淀粉含量与粗蛋白含量的QTL分析

以水稻珍汕97B和旱稻IRAT109杂交F9代重组自交系群体为材料,分别在水旱两种处理条件下,用近红外光谱回归模型预测群体的直链淀粉含量及粗蛋白含量。分析结果表明,两种处理条件下直链淀粉含量无显著差异,水分胁迫处理条件下粗蛋白含量显著降低。利用QTLMapper共检测到22个主效QTL和66对显著互作位点与直链淀粉含量和粗蛋白含量有关。主效QTL对直链淀粉和蛋白质含量的联合贡献率在非胁迫条件下为35.34%和37.33%,在胁迫条件下分别为53.40%和58.10％;互作位点对直链淀粉和蛋白质含量的联合贡献率在正常水分条件下分别为66.74%和57.49%,在胁迫条件下分别为48.65%和36.59%。     

粳稻SSR连锁图谱的构建及恢复系卷叶性状QTL分析

  调查了粳稻品种秀水79 (P1)与粳稻恢复系C堡 (P2)及其衍生的254个重组自交系的SSR标记基因型和两个环境下主茎剑叶卷曲度,构建了该组合的SSR标记连锁图谱并分析了剑叶卷曲度QTL及其与环境的互作。在检测的818对SSR引物中,有90对引物在P1与P2之间扩增出多态性条带。单标记回归分析显示有12个标记在两个环境下均显示与剑叶卷曲度呈极显著相关。74个信息位点构成的连锁图谱全长744.6 cM,位点间平均图距10.1 cM。利用两种分析软件 WinQTLcart 2.5和QTLNetwork 2.0共同检测到3个QTL (qRL 1、qRL 7和qRL 8 1),其中qRL 8 1是新发现的,在两个环境下贡献率分别为15.5%和12.8%,加性贡献率为6.6%,且与环境不存在互作。     

控制水稻中胚轴伸长的QTL定位

水稻中胚轴能够为幼苗破土提供动力,培育长中胚轴水稻品种有助于水稻直播技术的推广,因此,研究水稻中胚轴伸长具有重要的理论和现实意义。为分析调控水稻中胚轴伸长的遗传基础,以Asominori和IR24重组自交系(RIL)群体为材料,结合其连锁图谱,对2017年杭州收获种子的中胚轴长度性状进行QTL定位。结果表明,在Asominori/IR24重组自交系群体中共检测到3个控制中胚轴伸长的QTL位点,分别位于第2、第3和第7条染色体上,LOD值在2.34～3.41之间,单个QTL对表型贡献率在7.25%～11.07%之间。同时用Asominori遗传背景的IR24染色体片段代换系进行验证,qML2对应的代换家系CSSL12的中胚轴与Asominori相比显著伸长,qML7对应的代换家系CSSL37的中胚轴与Asominori相比显著缩短,从而验证了qML2和qML7位点的存在。与先前研究比较,qML3和qML7在不同群体不同环境下稳定表达。同时利用重组自交系群体对2018年杭州大田环境株高性状进行QTL定位,共检测到2个QTL位点,均与中胚轴QTL位点不重合,说明控制中胚轴伸长与控制株高有着不同的遗传基础。     

Relationship Between Coleoptile Length and Drought Resistance and Their QTL Mapping in Rice

By using a set of recombinant inbred line(RIL)population involving in 195 lines derived from a cross of Zhenshan 97B (lowland variety)and IRAT109(upland variety),the correlation analysis between coleoptile length(CL)and drought resistance index (DRI)and their QTL identification were conducted.There existed a significantly positive relationship between CL and DRI with the correlation coefficient of 0.2206**under water stress conditions.Under normal and water stress conditions,a total of eleven and four QTLs for CL and DRI,respectively,were detected on chromosomes 1,2,4,5,6,7,9,11 and 12 by using a linkage map including 213 SSR markers,which explained 4.84%to 22.65%of phenotypic variance.Chromosomes 1 and 9 possessing the QTLs for DRI harbored simultaneously QTLs for CL,and qCL9 shared the same chromosome location with qDRI9(RM160-RM215).Comparing the QTLs related to drought resistance in other studies,QTLs for CL and DRI were located in the same or adjacent marker interval as those related to root traits,such as number,dry weight,depth,and length of root.Moreover,sixteen and three pairs of epistatic loci for CL and DRI were found,which accounted for 56.17%and 11.93%of the total variation in CL and DRI,respectively.     

Mapping of QTLs for Germination Characteristics under Non-stress and Drought Stress in Rice

Identification of genetic factors controlling traits associated with seed germination under drought stress conditions, leads to identification and development of drought tolerant varieties. Present study by using a population of F2：, derived from a cross between a drought tolerant variety, Gharib （indica） and a drought sensitive variety, Sepidroud （indica）, is to identify and compare QTLs associated with germination traits under drought stress and non-stress conditions. Through QTL analysis, using composite interval mapping, regarding traits such as germination rate （GR）, germination percentage （GP）, radicle length （RL）, plumule length （PL）, coleorhiza length （COL） and coleoptile length （CL）, totally 13 QTLs were detected under pole drought stress （-8 MPa poly ethylene glycol 6000） and 9 QTLs under non-stress conditions. Of the QTLs identified under non-stress conditions, QTLs associated with COL （qCOL-5） and GR （qGR-1） explained 21.28% and 19.73% of the total phenotypic variations, respectively Under drought stress conditions, QTLs associated with COL （qCOL-3） and PL （qPL-5） explained 18.34% and 18.22% of the total phenotypic variations, respectively. A few drought-tolerance-related QTLs identified in previous studies are near the QTLs detected in this study, and several QTLs in this study are novel alleles. The major QTLs like qGR-1, qGP-4, qRL-12 and qCL-4 identified in both conditions for traits GR, GP, RL and CL, respectively, should be considered as the important and stable trait-controlling QTLs in rice seed germination. Those major or minor QTLs could be used to significantly improve drought tolerance by marker-assisted selection in rice.     

Rice Root Genetic Architecture: Meta-analysis from a Drought QTL Database

During the last 10 years, a large number of quantitative trait loci (QTLs) controlling rice root morphological parameters have been detected in several mapping populations by teams interested in improving drought resistance in rice. Compiling these data could be extremely helpful in identifying candidate genes by positioning consensus QTLs with more precision through meta-QTL analysis. We extracted information from 24 published papers on QTLs controlling 29 root parameters including root number, maximum root length, root thickness, root/shoot ratio, and root penetration index. A web-accessible database of 675 root QTLs detected in 12 populations was constructed. This database includes also all QTLs for drought resistance traits in rice published between 1995 and 2007. The physical position on the pseudo-chromosomes of the markers flanking each QTL was determined. An overview of the number of root QTLs in 5-Mb segments covering the whole genome revealed the existence of “hot spots,” The 32 trait × chromosome combinations comprising six or more QTLs were subjected to a meta-QTL analysis using the software package MetaQTL. The method enabled us both to determine the likely number of true QTLs in these areas using an Akaike information criterion and to estimate their position. The meta-QTL confidence intervals were notably reduced and, for the smallest ones, encompassed only a few genes.     

Upland rice grown in soil-filled chambers and exposed to contrasting water-deficit regimes: II. Mapping quantitative trait loci for root morphology and distribution

Root morphological characteristics are known to be important in the drought resistance of some rice (Oryza sativa L.) varieties. The identification of quantitative trait loci (QTLs) associated with root morphology and other drought resistance-related traits should help breeders produce more drought resistant varieties. Stability in the expression of root growth QTL across rooting environments is critical for their use in breeding programs. A greenhouse experiment in which a mapping population of 140 recombinant inbred lines and the parental varieties Bala and Azucena were grown in glass-sided soil chambers and evaluated for root growth and water uptake was conducted. In each of 2 years, two treatments were used; an early water-deficit (WD0) in which seeds were sown into wet soil but received no more water, and a late water-deficit (WD49) in which the plants were watered for 49 days and then received no water for a week. The major differences between treatments and years in dry matter partitioning and root growth traits are reported elsewhere. Here, the identification of QTLs for root growth traits by composite interval mapping is described. At LOD>3.2, there were six QTLs for the weight of roots below 90 cm and maximum root length, 11 for root to shoot ratio, 12 for the number of roots past 100 cm, and 14 for root thickness. A total of 24 regions were identified as containing QTLs (these regions often contained several QTLs identified for different root traits). Some were revealed only in individual experiments and/or for individual traits, while others were common to different traits or experiments. Seven QTLs, on chromosomes 1, 2, 4, 7, 9 (two QTLs) and 11, where considered particularly noteworthy. The complex results are discussed in the context of previously reported QTLs for root growth in other populations, the interaction between QTL with the environment and the value of QTLs for breeding.     

Root plasticity under fluctuating soil moisture stress exhibited by backcross inbred line of a rice variety,Nipponbare carrying introgressed segments from KDML105 and detection of the associated QTLs

In rainfed lowland rice ecosystem, rice plants are often exposed to alternating recurrences of waterlogging and drought due to erratic rainfall. Such soil moisture fluctuation (SMF) which is completely different from simple or progressive drought could be stressful for plant growth, thereby causing reduction in yield. Root plasticity is one of the key traits that play important roles for plant adaptation under such conditions. This study aimed to evaluate root plasticity expression and its functional roles in dry matter production and yield under SMF using Nipponbare, KDML 105 and three backcross inbred lines (BILs) and to identify QTL(s) associated with root traits in response to SMF at two growth stages using Nipponbare/KDML105 F₂ plants. A BIL, G3-3 showed higher shoot dry matter production and yield than Nipponbare due to its greater ability to maintain stomatal conductance concomitant with greater root system development caused by promoted production of nodal and lateral roots under SMF. QTLs were identified for total nodal root length, total lateral root length, total root length, number of nodal roots, and branching index under SMF at vegetative and reproductive stages. The QTLs detected at vegetative and reproductive stages were different. We discuss here that relationship between root system of G3-3 and the detected QTLs. Therefore, G3-3 and the identified QTLs could be useful genetic materials in breeding program for improving the adaptation of rice plants in target rainfed lowland areas.     

水稻耐热性的QTL定位及耐热性与光合速率的相关性

应用典型的籼粳交组合IR64×Azucena花药培养的DH群体及其已构建的分子连锁图谱,在田间及温室高温条件下对该DH群体的结实性状进行考查,采用QTLmapper 1.0软件检测控制结实率的加性和上位性效应的QTL。在第1、3、4、8和11等5条染色体上,共检测到6个具有加性效应的QTL,其中位于第1、3染色体的2个加性效应QTL来自父本Azucena的等位基因,它们是耐热的QTL,能分别提高结实率9.50和6.46个百分点,其贡献率分别为19.15%和2.86%;位于其余3条染色体的4个加性效应的QTL来自母本IR64的等位基因,它能提高结实率4.33~10.37个百分点,在第1、2、3、4、5、7、8、11等8条染色体之间还检测到8对加性×加性上位性效应,其贡献率为2.27%~8.13%。同时还对水稻分蘖盛期和抽穗期进行了光合速率的测定,发现抽穗期剑叶光合速率与耐热性呈显著的正相关。     

Mapping quantitative trait loci associated with root growth in upland rice (Oryza sativa L.) exposed to soil water-deficit in fields with contrasting soil properties

A mapping population of 114 lines from Bala × Azucena was grown under drought stress at two field sites with contrasting soil physical properties. Drought was imposed between 35 and 65 days after sowing (DAS) and root density at 35 cm depth was measured 70 DAS. Leaf rolling, leaf drying and relative water content were recorded as indicators of drought avoidance. Root density correlated with indicators of drought avoidance. Two significant and two putative quantitative trait loci (QTLs) for root density and 28 QTLs for drought avoidance were identified. Most QTLs did not agree between sites. There was also reasonable agreement between leaf-drying QTLs and previously reported root-growth QTLs detected under controlled conditions (in contrast to a previous screen on soil with a higher penetration resistance). These data also reveal QTL × environment interaction, which will need to be understood more clearly if progress towards breeding for drought resistance via alterations of root morphology is to be achieved.     

QTL mapping of grain quality traits in rice

Grain quality improvement is one of the most important goals in a rice breeding program. An indica variety with small grain size was crossed to a japonica variety with large grain size to construct a set of recombinant inbred lines (RILs) which was used to identify quantitative trait loci (QTLs) controlling eight grain quality traits. Based on a linkage map of 185 SSR markers, a total of 16 QTLs were mapped on six chromosomes. A pleiotropic main effect QTL (M-QTL) flanked by RM3204 and RM16 on chromosome 3 influences the grain length (GL), length width ratio (LWR) and head rice ratio (HRR), explaining the phenotypic variation of 46.0, 36.1 and 29.7%, respectively. A total of 18 epistatic QTLs were identified for all the traits except MRR, distributed on all the chromosomes except chromosome 10. Two M-QTLs for GL and one M-QTL for GW were involved in epistatic QTL. No significant interaction between M-QTL or epistatic QTL and environment was detected except AC having significant M-QTL by environment interaction with minor effect. GL and LWR have a significant negative relation with HRR which might make it difficult to develop long grain with higher HRR in the rice breeding practice.     

QTL mapping rolling,stomatal conductance and dimension traits of excised leaves in the Bala × Azucena recombinant inbred population of rice

The identification of markers linked to genes contributing to drought resistance promises opportunities to breed high yielding rice varieties for drought prone areas. Several studies using different mapping populations have previously identified quantitative trait loci (QTLs) for traits theoretically related to drought resistance. A mapping population of 176 F₆ recombinant inbred lines (RILs) derived from two upland rice varieties with contrasting aboveground drought avoidance traits (Bala and Azucena) with a linkage map of 157 markers was used to map QTLs for aboveground leaf morphological and physiological traits related to drought avoidance. Plants were grown for 6 weeks under controlled environmental conditions with three replications. Leaves were excised and placed on a balance. The rate of leaf rolling and water loss was recorded, after which leaf area, dry weight and specific leaf area were characterized. A simple method of estimating time to stomatal closure was employed. A total of 13 QTLs were detected for leaf morphological traits, three for initial transpiration and four for the proportion of water loss required to reach a specific advanced state of leaf rolling. No QTLs were detected for time of stomatal closure or speed of leaf rolling, nor for either water loss or transpiration at stomatal closure despite clear parental differences and moderate heritabilities in most of these traits. The co-location of QTLs for traits measured here and for drought avoidance previously reported from field experiments on chromosome 1, 3 and 5 link the genetics of drought resistance to leaf dimensions and physiology. However, a physiological explanation for a QTL for drought avoidance on chromosome 7 remains elusive.     

籼稻C84和粳稻春江16B重组自交系遗传图谱构建及籽粒性状QTL定位与验证

【目的】本研究旨在挖掘水稻粒型新基因、探索其分子机理,解析籽粒发育调控遗传网络奠定基础,并为通过分子标记聚合有利基因开展超级稻分子设计育种提供理论依据。【方法】以植株和籽粒形态差异较大的晚粳稻品种春江16B(CJ16B）和广亲和中籼稻背景恢复系C84为亲本构建含有188个家系的重组自交系为作图群体,利用158对在双亲中存在多态性差异的分子标记,构建了遗传连锁图谱,总遗传距离为1428.40cM,平均标记间距为9.04cM。在构建遗传图谱的基础上,完成RIL188个株系籽粒的粒长、粒宽、粒厚、长宽比和千粒重等5个性状考查并进行QTL定位。【结果】在海南陵水和浙江杭州两地共检测到籽粒相关主效QTL30个,包括籽粒QTL新座位18个,解释遗传变异3.51%~17.25%。其中粒长、粒宽、粒厚和长宽比QTL位点分别为9个、5个、5个和6个,千粒重QTL位点5个。经基因座位比对,发现有5个QTL区间与已克隆的调控籽粒形态相关基因座位相近,我们通过对双亲目标基因的测序并根据差异位点设计dCAPs分子标记进行验证。【结论】该RIL群体及其遗传图谱可用于水稻重要农艺性状主效QTL基因的定位和克隆,新定位的18个粒型QTL可以为水稻籽粒发育调控网络提供补充和资料积累。