水稻低温发芽力QTL定位和遗传分析

以Kinmaze(粳稻)／DV85(籼稻)的重组自交系F10世代群体检测了影响水稻低温发芽力性状的数量性状基因座(QTL)。通过测定不同时期的低温发芽率,确定了15℃低温、第10d为检测低温发芽率的最适处理温度和时间,该条件下能够充分检测到品种的差异和分离群体的变异。通过设置对照,证明所检测的低温发芽率不受休眠及二次休眠的影响。15℃低温、第10d时,Kinmaze的发芽率达35％,DV85的发芽率只有7％,两亲本之间存在明显差异,该群体81个家系的低温发芽率变幅在0％～99％之间。QTL分析结果检测到5个与低温发芽力相关的基因座,分别位于第2、6、7、11和12染色体上。位于第2、6和11染色体上的qLTG-2、qLTG-6和qLTG-11贡献率分别为27．1％、17．1％和15．0％,对低温发芽力性状的增效基因来自DV85;位于第7、12染色体上qLTG-7和qLTG-12的贡献率分别为22．9％和8．8％,增效基因来自Kinmaze。其中,qLTG-6和qLTG-11在染色体上的位置与已报道的有关低温发芽力QTL位置相似,而qLTG-2、qLTG-7和qLTG-12为新检测的低温发芽力基因座。上位性分析结果显示,第3与第5染色体上存在影响低温发芽力的互作位点,其互作可以提高低温发芽力,而第7染色体上的两位点之间的互作降低了低温发芽力。     

水稻对叶瘟和穗瘟部分抗性的遗传分析

在一个水稻籼籼交重组自交系群体中,选用由感病株系构成的2个亚群体和2个不同的稻瘟病菌小种,进行了水稻对叶瘟部分抗性的QTL定位,还选用由感病而且抽穗期相近的株系构成的亚群体和另一个病菌小种,进行了水稻对穗瘟部分抗性的QTL定位,将病叶面积百分比(DLA)、病斑大小(LS)和病斑数(LN)作为对叶瘟部分抗性的性状,将病斑长度(LL)和孢子量(CA)作为对穗瘟部分抗性的性状。所构建的图谱包含168个标记。应用QTLMapper 1．01b,共检测到11个表现主效应的QTL和28对双因子互作,有3个表现主效应的QTL参与对同一性状的互作。QTL的主效应对单一性状的贡献率为4．7％～38．8％,而上位性效应对单一性状的贡献率为16．0％～51．7％,QTL的主效应对大多数性状的贡献率小于互作效应,表明互作效应对于部分抗性的重要作用。对穗瘟部分抗性的两个性状LL和CA,所检测到QTL总效应的贡献率分别达到70．6％和82．6％,表明由排除了主效抗病基因的感病株系组成的亚群体适合于进行部分抗性QTL定位。     

谷子SSR分子图谱的构建及主要农艺性状QTL定位

试验拟对谷子重要农艺性状进行数量性状位点QTL分析。以表型差异较大的沈3/晋谷20F2作图群体为材料,观测其株高、穗长等性状,选用SSR做分子标记,利用完备区间作图法(BASTEN C J)进行QTL分析。结果显示,表型数据在作图群体中呈现连续分布,表现为多基因控制的数量性状,被整合的54个SSR标记构建10个连锁群,LOD阈值设置为2.0,检测到与株高相关的主效QTL2个,联合贡献率45.9637%,穗长主效QTL1个,贡献率14.9647%,与穗重、粒重相关的主效QTL为同一位点,贡献率分别为11.9601%和10.1879%。有6组QTL位点之间存在基因互作效应,大小范围为-0.4986-16.6407,对性状的贡献率在2.2716％至6.7478％之间。谷子表型控制复杂,相关QTL的检测受环境影响较大,不同连锁群QTL间互作明显。     

水稻低温发芽性QTL的分子标记定位

利用1个粳／籼交来源的重组自交系群体,采用纸卷法在15℃低温条件下进行发芽试验,在发芽培养的6～14d中每天观测统计1次发芽率(％)。结合一张含有198个DNA标记的连锁图谱,用复合区间作图法定位水稻低温发芽性QTL。共检测到7个主效应QTL,分别位于水稻1、3、5、6和8号染色体上,单个QTL对性状的贡献率为5％～16％。其中,位于3号染色体标记区间RM148-RM85的qLTG-3-2和位于8号染色体标记区间RM223-RM210的qLTG-8-1对性状的贡献率最大,分别达16％和14％。QTL qLTG-3-2在发芽培养6～10d中表达,其效应由强渐弱,对性状的贡献率由发芽培养6d时的16．4％逐渐降低为发芽11d时的5．1％;而QTL qLTG-8-1则在发芽培养9～14d中起作用,其效应值由小逐渐增大,对性状的贡献率由发芽9d时的8．6％逐渐上升为发芽13～14d的14％。尽管这2个QTL加性效应的大小在低温发芽过程中按一定趋势变化,但加性效应的方向始终是一致的。QTL qLTG-3-2的增效基因来源于亲本特青,而QTL qLTG-8-1的增效基因来自于亲本Lemont。这2个QTL的增效等位基因有望作为分子标记辅助育种的操作对象,用于水稻品种低温发芽性的遗传改良。     

利用双单倍体群体剖析水稻产量及其相关性状的遗传基础

主效QTL、上位性效应和它们与环境的互作(QE)都是数量性状的重要遗传因素。利用籼粳交珍汕97／武育粳2号F1植株上的花药进行组织培养得到的190个双单倍体群体和179个微卫星标记,通过两年两重复田间试验,采用混合线性模型方法分析了9个控制水稻产量及其相关性状的遗传效应,得到57个主效QTL,41对上位性互作,8对QTL与环境的互作和7对上位性效应与环境的互作。单个主效QTL解释这些性状1．3％～25．8％的表型方差。各性状QTL的累积表型贡献率达11．5％～66．8％。大多数性状之间具有显著的表型相关性,相关性较高的性状之间常具有较多共同或紧密连锁的QTL。结果表明,基因的多效性或紧密连锁可能是性状相关的重要遗传基础。     

水稻穗部性状的QTL与环境互作分析

分别在两年收集珍汕97／明恢63的重组自交系群体的表现数据,运用混合线性模型的QTL定位方法,联合分析穗部5个性状的QTLs7及QTL与环境互作关系。每穗颖花数、每穗实粒数、结实率、穗长和穗着密度分别检测到10、3、6、8和7个QTLs分别解释各性状变异的29．13％、19．2％、29．46％、26．39％和35．76％。对于同一性状,高值亲本和低值亲本中均存在增效和减效QTL。相关性状QTL的位置表现相同或相似,高值亲本和低值亲本中均存在增效和减效QTL。相关性状QTL的位置表现相同或相似,成族分布。1个穗长QTL,2个每穗颖花数QTL3,3个结实率QTLs表现与环境显著互作,QTL与环境互作效应的贡献率比相应的QTL贡献率略大。遗传力稍高的每穗实粒数和穗着粒密度的DQTL与环境不互作。     

不同温度条件下水稻种子活力QTL的定位分析

为了揭示基因型与环境温度之间的互作对种子活力的影响,利用1个粳籼交来源的重组自交系群体,采用纸卷法在15、20和25℃条件下进行发芽试验,考察了发芽率、芽长、根长及干重等4个种子活力相关性状。结合一张含有198个DNA标记的连锁图谱,用作图软件QTL Mapper1.0定位与种子活力相关的QTL。共检测到34个主效应QTL。这些QTL中的绝大多数(82％)成簇分布于第3、5和8号染色体的5个不同染色体区段上,分别被命名为QTL qSV-3-1、qSV-3-2、qSV-5、qSV-8-1和qSV-8-2。其中,QTL qSV-3-1、qSV-3-2和qSV-8-1对种子活力的效应大小和方向在3个温度条件下均较一致;而QTL qSV-5和qSV-8-2主要在20和25℃条件下起作用,在15℃低温条件下作用甚微或不起作用。表明种子活力QTL具有显著的基因型与环境温度之间的互作,而且这种互作具有明显的QTL特异性。芽长是唯一同时受5个与种子活力高度相关的染色体区段共同影响的指标,因此,相对而言,作为水稻种子活力的测定指标,芽长是最具有代表性的。     

水稻柱头外露率QTLs定位及其互作分析

以协青早B/密阳46所构建的RIL群体及其相应分子遗传图谱,设置海南和杭州两地遗传试验,应用基于混合线性模型检测QTL主效应、上位性效应和G×E互作效应的遗传分析方法,对水稻柱头外露率(%)进行QTL联合分析．结果表明,该性状明显表现出海南较高(21．83%)而杭州较低(8．35%)的趋势．试验检测到1个主效应QTL(qSE6-1),其LOD值高达28．16,对性状表型的贡献率为14．14%,增效等位基因来自于母本,加性效应为5．10%,不存在显著的GE互作．试验还检测到3对显著的加性×加性双基因互作,上位性互作性效应和贡献率相对较小,且与环境不存在显著的互作．     

水稻光合功能相关性状QTL分析

利用粳稻Kinmaze／籼稻DV85杂交后代单粒传衍生的81个F11家系所组成的重组自交系（Recombinant Inbred Lines,RILs）群体,研究水稻光合功能相关性状的数量性状基因座（QTL）。在水稻抽穗后7d测定叶片全氮含量（TLN）、叶绿素a／b比值（Chl．a：b）和叶绿素含量（Chl）。共检测到6个QTL,各QTL的LOD值为2．66～4．81,贡献率为11．2％-29．6％,其中,在第1、2和11染色体上检测到3个与全氮含量相关的QTL,相应贡献率为17．3％、15．3％、13．7％;在第3和4染色体检测到2个与叶绿素a／b比值相关的QTL,贡献率为13．8％和29．6％;在第1染色体检测到1个与叶绿素含量相关的QTL,贡献率为11．2％。4个QTL为本研究新检测的基因座。有趣的是,控制叶绿素含量的qCC-1位于第1染色体上RFLP标记C122附近,与已报道的NADH-谷氨酸合成酶基因位置一致,而叶绿素合成始于谷氨酸,暗示该基因座与水稻光合功能关系极为密切。然而,对抽穗后30d叶绿素含量进行QTL分析,结果未检测到与其相关的QTL,表明控制叶绿素含量qCC-1效应随水稻叶片的衰老而降低。     

小麦纹枯病抗性的QTL分析和抗病基因的分子标记

对RIL-8群体纹枯病抗性进行QTL检测,检测到一个加性QTL,位于1A染色体上,贡献率为21.57%;检测到4对QTL间互作位点,涉及7条染色体,互作贡献率分别为11.63%、6.54%、14.04%、20.01%,互作总贡献率为52.23%.通过对RIL-SES群体118个系检测,发现1个SSR标记Xgwm526,位于2B染色体上,与纹枯病抗病基因距离为27.9cM;一个ISSR标记IS840,与纹枯病抗病基因距离为16.9cM.     

Epistatic interaction is an important genetic basis of grain yield and its components in maize

A population of 294 recombinant inbred lines (RIL) derived from Yuyu22, an elite maize hybrid extending broadly in China, has been constructed to investigate the genetic basis of grain yield, and associated yield components in maize. The main-effect quantitative trait loci (QTL), digenic epistatic interactions, and their interactions with the environment for grain yield and its three components were identified by using the mixed linear model approach. Thirty-two main-effect QTL and forty-four pairs of digenic epistatic interactions were detected for the four measured traits in four environments. Our results suggest that both additive effects and epistasis (additive × additive) effects are important genetic bases of grain yield and its components in the RIL population. Only 30.4% of main-effect QTL for ear length were involved in epistatic interactions. This implies that many loci in epistatic interactions may not have significant effects for traits alone but may affect trait expression by epistatic interaction with the other loci.     

The main effects, epistatic effects and environmental interactions of QTLs on the cooking and eating quality of rice in a doubled-haploid line population

Amylose content (AC), gel consistency (GC) and gelatinazation temperature (GT) are three important traits that influence the cooking and eating quality of rice. The objective of this study was to characterize the genetic components, including main-effect quantitative trait loci (QTLs), epistatic QTLs and QTL-by-environment interactions (QEs), that are involved in the control of these three traits. A population of doubled haploid (DH) lines derived from a cross between two indica varieties Zhenshan 97 and H94 was used, and data were collected from a field experiment conducted in two different environments. A genetic linkage map consisting of 218 simple sequence repeat (SSR) loci was constructed, and QTL analysis performed using qtlmapper 1.6 resolved the genetic components into main-effect QTLs, epistatic QTLs and QEs. The analysis detected a total of 12 main-effect QTLs for the three traits, with a QTL corresponding to the Wx locus showing a major effect on AC and GC, and a QTL corresponding to the Alk locus having a major effect on GT. Ten digenic interactions involving 19 loci were detected for the three traits, and six main-effect QTLs and two pairs of epistatic QTLs were involved in QEs. While the main-effect QTLs, especially the ones corresponding to known major loci, apparently played predominant roles in the genetic basis of the traits, under certain conditions epistatic effects and QEs also played important roles in controlling the traits. The implications of the findings for rice quality improvement are discussed.     

Identification of QTLs with Additive,Epistatic, and QTL × Seed Maturity Interaction Effects for Seed Vigor in Rice

Seed maturity is a critical process of seed vigor establishment. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential (GP), germination rate (GR), germination index (GI), and time for 50 % of germination (T₅₀), at 4, 5, and 6 weeks after heading in 2 years. Significant differences of seed vigor were observed among two parents and RIL population; the heritability of four traits was more than 90 % at three maturity stages. A total of 19 additive and 2 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program, respectively, in 2012, while 16 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The phenotypic variation explained by each additive, epistatic QTL, and QTL × seed maturity interaction ranged from 9.19 to 22.94 %, 7.23 to 7.75 %, and 0.05 to 0.63 %, respectively. Ten additive QTLs were stably expressed in 2 years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of ten stably expressed additive QTLs with those previously identified, they might be true QTLs for seed vigor; the regions of QTLs for seed vigor are likely to coincide with QTLs for seed dormancy, seed reserve mobilization, low-temperature germinability, and seedling growth. Using four selected RILs, three cross-combinations were predicted to improve seed vigor; 9 to 10 elite alleles could be pyramided by each combination. The selected RILs and the identified QTLs might be applicable for the improvement of seed vigor by marker-assisted selection (MAS) in rice.     

Comparison of QTL controlling seedling vigour under different temperature conditions using recombinant inbred lines in rice (Oryza sativa)

BACKGROUND AND AIMS: Seedling vigour is one of the major determinants for stable stand establishment in rice (Oryza sativa), especially in a direct seeding cropping system. The objectives of this study were to identify superior alleles with consistent effects on seedling vigour across different temperature conditions and to investigate genotype x environmental temperature interactions for seedling vigour QTL. METHODS: A set of 282 F13 recombinant inbred lines (RILs) derived from a rice cross were assessed for four seedling vigour traits at three temperatures (25 degrees C, 20 degrees C and 15 degrees C). Using a linkage map with 198 marker loci, the main-effect QTL for the traits were mapped by composite interval mapping. KEY RESULTS: A total of 34 QTL for the four seedling vigour traits were identified. Of these QTL, the majority (82%) were clustered within five genomic regions, designated as QTL qSV-3-1, qSV-3-2, qSV-5, qSV-8-1 and qSV-8-2. All of these five QTL had small individual effects on the traits, explaining 3.1-15.8 % of the phenotypic variation with a mean of 7.3 %. QTL qSV-3-1, qSV-3-2 and qSV-8-1 showed almost consistent effects on the traits across all three temperatures while qSV-5 and qSV-8-2 had effects mainly at the 'normal' temperatures of 20 degrees C and 25 degrees C. Among the five QTL identified, all and four showed additive effects on shoot length and germination rate, respectively. The contributions of these five QTL to shoot length and germination rate were also much larger than those to the other two traits. CONCLUSIONS: A few of genomic regions (or QTL) were identified as showing effects on seedling vigour. For these QTL, significant genotype x environmental temperature interactions were found and these interactions appeared to be QTL-specific. Among the four seedling vigour traits measured, shoot length and germination rate could be used as relatively good indicators to evaluate the level of seedling vigour in rice.     

The genetic basis of stay-green in rice analyzed in a population of doubled haploid lines derived from an<Emphasis Type="Italic"> indica</Emphasis> by<Emphasis Type="Italic"> japonica</Emphasis> cross

Delayed leaf-senescence, or stay-green, has been regarded as a desired characteristic for the production of a number of crops including rice. In this study, we analyzed the genetic basis of stay-green using a population of 190 doubled haploid lines from the cross between an indica parent Zhenshan 97 and a stay-green japonica parent Wuyujing 2. The population was tested in replicated field trials in 2 consecutive years, and six traits were defined to evaluate the stay-green characteristics. A genetic linkage map with 179 SSR (simple sequence repeat) marker loci was constructed. The software QTLMapper, based on a mixed linear model approach, was applied to detect QTLs, epistatic effects and their environmental interactions for these traits. A total of 46 main-effect QTLs was detected for the six traits that can be localized to 25 chromosomal regions. The individual effects of all the QTLs were small. Fifty digenic interactions were resolved that involved 66 loci distributed on all 12 chromosomes. Environmental interactions were detected for 18 of the main-effect QTLs and 14 of the epistatic interactions. Collectively, the epistatic effects and QTL by year interactions accounted for large proportions of the phenotypic variations. The results also showed that most of the stay-green traits were negatively correlated with yield and its component traits. The implications of the results in crop improvement were discussed.Communicated by C. Möllers     

Dynamic Quantitative Trait Locus Analysis of Seed Vigor at Three Maturity Stages in Rice

Seed vigor is an important characteristic of seed quality. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential, germination rate, germination index and time for 50% of germination, at 4 (early), 5 (middle) and 6 weeks (late) after heading in two years. A total of 24 additive and 9 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program respectively in 2012; while 32 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The additive, epistatic and QTL × development interaction effects regulated the dry maturity developmental process to improve seed vigor in rice. The phenotypic variation explained by each additive, epistatic QTL and QTL × development interaction ranged from 5.86 to 40.67%, 4.64 to 11.28% and 0.01 to 1.17%, respectively. The QTLs were rarely co-localized among the different maturity stages; more QTLs were expressed at the early maturity stage followed by the late and middle stages. Twenty additive QTLs were stably expressed in two years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of these stably expressed additive QTLs with those previously identified, the regions of QTL for seed vigor are likely to coincide with QTL for grain size, low temperature germinability and seed dormancy; while 5 additive QTL might represent novel genes. Using four selected RILs, three cross combinations of seed vigor for the development of RIL populations were predicted; 19 elite alleles could be pyramided by each combination.     

水稻种子萌发和苗期ABA敏感性的QTL定位分析

植物激素ABA参与不同的生理过程,尤其是在种子发育和非生物逆境的适应都需要ABA的调控.以水稻珍汕97和旱稻IRAT109为亲本的重组自交系群体为材料,分别调查种子发芽和苗期对ABA的敏感程度.种子发芽阶段以ABA处理下的相对发芽势（Relative germination vigor,RGV）和相对发芽率（Relative germination rate,RGR）为指标,苗期以ABA喷施处理下的卷叶程度（Leaf rolling scores by ABA spaying,LRS）和含ABA水培条件下的卷叶程度（Leaf rolling scores by ABA culturing,LRC）为指标.性状相关分析表明发芽阶段的相对发芽势与苗期卷叶程度呈显著正相关.用复合区间作图法和混合线性模型对ABA敏感性QTL定位和上位性效应分析.两种软件检测到的主效QTL位点大致相同.共检测到5个单位点QTL和6对上位性QTL与发芽阶段的ABA敏感性有关;8个单位点QTL和5对上位性QTL与水稻苗期对ABA的敏感性有关;在苗期,两种ABA处理条件下共检测到两个共同的QTL;仅一个共同的QTL同时控制发芽阶段和苗期对ABA的敏感性.这些研究结果说明,水稻对ABA的敏感性同时受单位点的多基因和上位性基因控制;而且控制种子萌发阶段发芽势和苗期对ABA敏感性的遗传基础有很大的不同.     

Identification of Quantitative Trait Loci for ABA Sensitivity at Seed Germination and Seedling Stages in Rice

Abscisic acid (ABA) is one of the important plant hormones, which plays a critical role in seed development and adaptation to abiotic stresses. The sensitivity of rice (Oryza sativa L.) to exogenous ABA at seed germination and seedling stages was investigated in the recombinant inbred line (RIL) population derived from a cross between irrigated rice Zhenshan 97 and upland rice IRAT109, using relative germination vigor (RGV), relative germination rate (RGR) and leaf rolling scores of spraying (LRS) or culturing (LRC) with ABA as sensitivity indexes. The phenotypic correlation analysis revealed that only RGV at germination stage was positively correlated to ABA sensitivity at seedling stage. QTL detection using composite interval mapping (CIM) and mixed linear model was conducted to dissect the genetic basis of ABA sensitivity, and the single-locus QTLS detected by both methods are in good agreement with each other. Five single QTLs and six pairs of epistatic QTLs were detected for ABA sensitivity at germination stage. Eight single QTLs and five pairs of epistatic QTLs were detected for ABA sensitivity at seedling stage. Two QTLs were common between LRS and LRC; and one common QTL was detected for RGV, LRS and LRC simultaneously. These results indicated that both single and epistatic loci were involved in the ABA sensitivity in rice, and the genetic basis of ABA sensitivity at seed germination and seedling stage was largely different.     

Detection of quantitative trait loci for seminal root traits in maize (Zea mays L.) seedlings grown under differential phosphorus levels

Suboptimal phosphorus availability is a primary constraint for terrestrial plant growth. Seminal roots play an important role in acquisition of nutrients by plant seedlings. The length and number of seminal roots may be particularly important in acquisition of immobile nutrients such as phosphorus by increasing soil exploration. The objective of this study was to identify quantitative trait loci (QTL) controlling seminal root growth in response to phosphorus stress in maize, and to characterize epistatic interactions among QTL. Seminal root length and number were evaluated in 162 recombinant inbred lines derived from a cross between B73 and Mo17 in seedlings grown in a controlled environment. B73 and Mo17 significantly differed for seminal root length under low phosphorus, but not under adequate phosphorus conditions. Seminal root length of the population grown under low phosphorus ranged from 0 to 79.2 cm with a mean of 32.3 cm; while seminal root length of plants grown under high phosphorus ranged from 0.67 to 59.0 cm with a mean of 23.4 cm. Under low phosphorus, one main-effect QTL was associated with seminal root length and three QTL with seminal root number; under high phosphorus, two QTL with seminal root length and three QTL for seminal root number. These accounted for 11, 25.4, 22.8, and 24.1% of the phenotypic variations for seminal root length and number at low phosphorus, and seminal root length and number at high phosphorus, respectively. Di-genic epistatic loci were detected for seminal root length at low phosphorus (two pairs) seminal root number at low phosphorus (eight pairs), seminal root length at high phosphorus (four pairs), and seminal root number at high phosphorus (two pairs), which accounted for 23.2, 50.6, 32.2, and 20.3% of the total variations, respectively. Seminal root traits observed here were positively yet weakly correlated with shoot biomass in the field under low phosphorus, although no coincident QTL were detected. These results suggest that epistatic interactions are important in controlling genotypic variation associated with seedling seminal root traits.     

Identification of quantitative trait loci across recombinant inbred lines and testcross populations for traits of agronomic importance in rice

This study was conducted to determine whether quantitative trait loci (QTL) controlling traits of agronomic importance detected in recombinant inbred lines (RILs) are also expressed in testcross (TC) hybrids of rice. A genetic map was constructed using an RIL population derived from a cross between B5 and Minghui 63, a parent of the most widely grown hybrid rice cultivar in China. Four TC hybrid populations were produced by crossing the RILs with three maintaining lines for the widely used cytoplasmic male-sterile (CMS) lines and the genic male-sterile line Peiai64s. The mean values of the RILs for the seven traits investigated were significantly correlated to those of the F1 hybrids in the four TC populations. Twenty-seven main-effect QTL were identified in the RILs. Of these, the QTL that had the strongest effect on each of the seven traits in the RILs was detected in two or more of the TC populations, and six other QTL were detected in one TC population. Epistatic analysis revealed that the effect of epistatic QTL was relatively weak and cross combination specific. Searching publicly available QTL data in rice revealed the positional convergence of the QTL with the strongest effect in a wide range of populations and under different environments. Since the main-effect QTL is expressed across different testers, and in different genetic backgrounds and environments, it is a valuable target for gene manipulation and for further application in rice breeding. When a restorer line that expresses main-effect QTL is bred, it could be used in a number of cross combinations.