QTL identification of yield-related traits and their association with flowering and maturity in soybean

Two soybean recombinant inbred line populations, Jinpumkong 2 × SS2-2 (J × S) and Iksannamulkong × SS2-2 (I x S) showed population-specific quantitative trait loci (QTLs) for days to flowering (DF) and days to maturity (DM) and these were closely correlated within population. In the present study, we identified QTLs for six yield-related traits with simple sequence repeat markers, and biological correlations between flowering traits and yield-related traits. The yield-related traits included plant height (PH), node numbers of main stem (NNMS), pod numbers per plant (PNPP), seed numbers per pod (SNPP), 100-seed weight (SW), and seed yield per plant (SYPP). Eighteen QTLs for six yield-related traits were detected on nine chromosomes (Chrs), containing four QTLs for PH, two for NNMS, two for PNPP, three for SNPP, five for SW, and two for SYPP. Two highly significant QTLs for PH and NNMS were identified on Chr 6 (LG C2) in both populations where the major flowering gene, E1, and two DF and DM QTLs were located. One other PNPP QTL was also located on this region, explaining 12.9% of phenotypic variation. Other QTLs for yield-related traits showed population-specificity. Two significant SYPP QTLs potentially related with QTLs for SNPP and PNPP were found on the same loci of Chrs 8 (Satt390) and 10 (Sat_108). Also, highly significant positive phenotypic correlations (P < 0.01) were found between DF with PH, NNMS, PNPP, and SYPP in both populations, while flowering was negatively correlated with SNPP and SW in the J × S (P < 0.05) and I × S (P < 0.01) populations. Similar results were also shown between DM and yield-related traits, except for one SW. These QTLs identified may be useful for marker-assisted selection by soybean breeders.     

Quantitative trait loci for stomatal density and size in lowland rice

Genotypic variation in stomatal density and size has been reported but little is known of the genetic mechanisms behind these leaf traits. Using 101 recombinant inbred lines derived from a cross between a tropical japonica, IR69093-41-3-2-2 and an indica variety, IR72, we conducted a field study to determine stomatal density and size and identify quantitative trait loci (QTL) controlling these traits under lowland conditions. Ten QTLs for stomatal density and four QTLs for size were identified across growth stages and leaf surfaces (adaxial and abaxial). The contribution of each QTL to total phenotypic variation ranged from 9.3 to 15.2% for stomatal density and 9.7 to 14.3% for size. The allele from IR72 increased stomatal density and that from IR69093-41-3-2-2 increased size. The expression of the QTLs for stomatal density and size differed by growth stage indicating that these traits might be genetically controlled depending on growth stage or that each QTL had a different function by growth stage. Significant negative genetic correlations between stomatal density and size at both vegetative (r = −0.308**) and heading (r = −0.484**) stages were observed but no common QTL for these traits was detected across growth stages and leaf surfaces. These results indicate that the QTLs for density and size may neither be genetically linked nor pleiotropically controlled and findings can be used as basis for selection at the leaf level on the balance of carbon and water uptake. Further study is needed to fully understand the mechanism underlying the observed genetic association and to elucidate the function of the QTLs involved.     

Novel quantitative trait loci for yield and yield related traits identified in Basmati rice (Oryza sativa)

Increasing crop productivity is one of the prime goals of crop breeding research. Rice grain yield is a complex quantitative trait governed by polygenes. Although several QTLs governing grain yield traits have been reported and limited attempts have been made to map QTLs for grain yield parameters in Basmati rice. A population from the cross Sonasal and Pusa Basmati 1121 comprising 352 RILs was generated through the single seed descent method. A total of 12 QTLs governing yield and yield-related traits were mapped on six chromosomes, namely, 1, 2, 3, 7, 8 and 9, of which five QTLs were novel. We identified a novel and robust epistatic QTL (qPH1.1 and qPL1.1) governing plant height and panicle length, flanked by the markers RM5336-RM1 on chromosome 1. The gene encoding brassinosteroid insensitive 1-associated receptor kinase 1 precursor is the putative candidate gene underlying this epistatic QTL. Another novel QTL, qNT3.1, governing tiller number was bracketed to a region of .77 Mb between the markers RM15247 and RM15281 on chromosome 3. Of the 57 annotated gene models, Os03g0437600 encoding alpha/beta-fold hydrolase, a homologous to AtKai2 is a putative candidate gene underlying the novel QTL qNT3.1. The other QTLs such as qDFF1.1 governing days to 50% flowering co-localizes with the gene Ghd7, QTL for plant height qPH1.2 co-localizes with the gene sd1, the QTLs for panicle length co-localizes with FUWA and DEP2, the QTL for tiller number co-localizes with OsRLCK57 and QTLs for thousand-grain weight co-localize with the major gene GS3. The QTLs identified in the current study can be effectively used in marker-assisted selection for developing Basmati rice varieties with a higher yield.     

转基因抗虫棉产量相关性状QTL的分子标记及定位

 采用亚洲棉渐渗的纤维强度突出的陆地棉优质新品系0-153与陆地棉转基因抗虫新品系sGK9708为亲本,构建了F₂及F_2∶3分离群体。利用3869对SSR引物筛选亲本,得到125对多态性引物。进一步对183个F₂群体单株分析得到150个多态性标记位点,其中100个标记位点连锁,构建20个连锁群,共覆盖660 cM,占棉花总基因组的14.67%,每个连锁群平均包含5个标记位点,标记间平均相距6.6 cM,其中13个连锁群确定了对应的染色体。利用F₂和F_2:3数据,通过复合区间作图,共检测到28个产量及相关因素的QTLs。这些控制产量性状的QTLs只存在于5个连锁群上,成簇分布。与皮棉产量性状有关的2个QTLs,均与其它多个产量相关性状的QTLs在同一个连锁区段内,增效基因遗传效应方向一致,有必要研究其在标记辅助选择中的效果。本研究没有检测到在多世代表现稳定的QTL。因此,需要培育重组自交系,进一步明确产量性状有关QTL的遗传效应。     

碱胁迫下粳稻幼苗前期耐碱性的数量性状基因座检测

以粳粳交“高产106/长白9号”F_2:3代200个家系为作图群体, 在0.15% Na₂CO₃溶液的碱性胁迫下, 进行了水稻耐碱性鉴定, 并以SSR标记构建的分子连锁图谱为基础, 对水稻幼苗前期的根数、根长和苗高及其相对碱害率进行了数量性状基因座(QTLs)的检测。结果表明, 上述性状在F₃家系群中均表现为具有1~2个峰的连续分布, 认为由主效基因和微效基因共同控制的数量性状。共检测到与碱胁迫下幼苗前期根数、根长和苗高及其相对碱害率相关的QTL 26个, 分布于第1、5、6、7、8、9和11染色体上。其中, 碱胁迫下与根数相关的QTL 4个, qRN6-1和qRN11对表型变异的解释率较大, 分别为29.91%和13.42%;与根数相对碱害率相关的QTL 5个, qRRN11-2对表型变异的解释率较大, 为23.86%;与根长相关的QTL 6个, qRRL11-2对表型变异的解释率较大, 为21.06%;与根长相对碱害率相关的QTL 2个, 但对表型变异的解释率均较低;与苗高相关的QTL 5个, qSH1和qSH11-2对表型变异的解释率较大, 分别为15.81%和16.53%;与苗高相对碱害率相关的QTL 4个, qRSH5和qRSH6-2对表型变异的解释率分别为29.89%和34.63%。而这些解释率较大的QTL所处的标记区间距离, 除qRN6-1相对较小(19.0 cM)外, 其余QTL的标记区间距离均大于26.3 cM, 需作进一步的精细定位。在所检测到的QTL中, 13个QTL的增效等位基因均来自耐碱亲本长白9号, 而其余QTL的增效等位基因来自敏碱亲本高产106;基因的主要作用方式为超显性或部分显性。     

不同水分环境下玉米产量构成因子及籽粒相关性状的QTL分析

干旱胁迫对玉米产量及其相关性状有重要影响。本研究以我国玉米育种骨干亲本齐319和掖478分别和黄早四组配构建的两个F_2:3群体为材料,应用逐步联合分析的QTL定位方法,剖析新疆不同水分环境下(包含水区和旱区)玉米产量构成因子及籽粒相关性状的遗传基础。结果表明,在相同水分处理不同年份间产量构成因子和籽粒相关性状超过70%的QTL可稳定表达,旱区QTL的稳定性明显低于水区,当全部环境联合分析时,各性状QTL稳定性呈现一定程度的降低,但超过60%的QTL仍然稳定表达。两群体中共检测到11个环境钝感的主效QTL(在2个以上环境中检测到,且至少在一个环境下的贡献率大于10%),分布在bin1.10、2.00、4.09、7.02、9.02、10.04和10.07共7个基因组区段上,除bin10.04外所有环境钝感的主效QTL在全部环境下稳定表达。因此,玉米产量构成因子和籽粒相关性状的QTL在新疆相同水分处理不同年份间,甚至不同水分条件下大部分均可稳定表达,这些主效QTL位点可为抗旱分子育种和进一步精细定位提供参考。     

Identification and multiple comparisons of QTL and epistatic interaction conferring high yield under boron and phosphorus deprivation in Brassica napus

Boron (B) and phosphorus (P) are two essential nutrients for plants. To unravel the genetic basis of B and P efficiency in Brassica napus, quantitative trait locus (QTL) and epistatic interaction analysis for yield and yield-related traits under contrast B and P conditions were performed using two mapping populations across various environments. Main effect QTLs were detected by QTLNetwork and QTL Icimapping (ICIM), and were compared with our previously reported main effect QTLs identified by QTLCartographer. Epistatic QTLs were identified by QTLNetwork, ICIM and Genotype matrix mapping (GMM), and multiple comparisons of main effect QTLs and epistatic QTLs were conducted. For the two mapping populations, 51 main effect QTLs were identified by QTLNetwork, 106 by ICIM. Among them, 35 main effect QTLs were simultaneously identified by three programs. Moreover, 578, 18 and 62 epistatic QTLs were identified by GMM, QTLNetwork and ICIM, respectively. Interestingly, a total of 235 epistatic QTLs identified by GMM were associated with 50 main effect QTLs identified by three programs. However, only nine epistatic QTLs identified by QTLNetwork and ICIM were involved in main effect QTLs. Twenty-two main effect QTLs in the BERIL population overlapped with 20 main effect QTLs for the same traits in the BQDH population, but no main effect QTLs were detected both under P and B stress environments, indicating the genetic differences in B and P homeostasis in B. napus. By in silico mapping, 29 candidate genes were located in the consensus QTL intervals. This study suggested the availability of dissecting genetic basis for complex traits under B/P deficiency by analyzing main effect QTLs and epistatic QTLs using multiple programs across different environments. The robust main effect QTLs and epistatic QTLs associated could be useful in breeding B and P efficient cultivars of B. napus.     

利用东乡普通野生稻染色体片段置换系定位产量相关性状QTL

以东乡普通野生稻和日本晴为亲本构建的染色体片段置换系为研究材料,2019年分别在北京、山东临沂和江西南昌对分蘖数、穗粒数和粒形等11个产量相关性状进行多环境鉴定,结合染色体片段置换系基因型数据定位水稻产量相关性状QTL。3个环境共检测到68个QTL,包括株高4个、穗长5个、分蘖数2个、一次枝梗数7个、一次枝梗粒数8个、二次枝梗数8个、二次枝梗粒数10个、每穗粒数6个、千粒重7个、粒长8个和粒宽3个;LOD值介于2.50~12.66之间,贡献率变幅为4.67%~27.79%,15个QTL的贡献率大于15%;24个QTL与已报道位点/基因位置重叠,44个QTL为新发现位点;6个QTL在2个环境能被检测到,1个QTL qTGW2能在3个环境检测到,且是还未报道的新位点。最后,利用BSA法验证了qPH7、qPBPP8-2和qGW10三个QTL的可靠性。本研究将为后续产量相关性状基因克隆以及进一步解析其遗传基础和分子调控机制奠定基础。     

Genetic analysis of heterotic loci detected in a cross between indica and japonica rice (Oryza sativa L.)

The study on the genetic basis of heterosis has received significant attention in recent years. In this study, using a set of introgression lines (ILs) and corresponding testcross F₁ populations, we investigated heterotic loci (HL) associated with six yield-related traits in both Oryza sativa L. subsp. indica and japonica. A total of 41 HL were detected on the basis of mid-parent heterosis values with single-point analysis. The F₁ test-cross population showed superiority in most yield-related traits and was characterized by a high frequency of overdominant HL. Thirty-eight of the 41 HL were overdominant, and in the absence of epistasis, three HL were dominant, suggesting that heterotic effects at the single-locus level mainly appeared to be overdominant in rice. Twenty-four HL had a real positive effect, suggesting that they are viable candidates for the improvement of rice yield potential. Compared with the quantitative trait loci (QTLs) detected in the ILs, only six out of the 41 (14.6%) HL were detected in QTL analysis under the same statistical threshold, indicating that heterosis and trait performance may be conditioned by different sets of loci.     

Identification of quantitative trait loci across interspecific F2, F2:3 and testcross populations for agronomic and fiber traits in tetraploid cotton

The most widely grown tetraploid Gossypium hirsutum and G. barbadense differ greatly in yield potential and fiber quality and numerous quantitative trait loci (QTLs) have been reported. However, correspondence of QTLs between experiments and populations is poor due to limited number of markers, small population size and inaccurate phenotyping. The purpose of the present study was to map QTLs for yield, yield components and fiber quality traits using testcross progenies between a large interspecific F₂ population and a commercial cotton cultivar as the tester. The results were compared to these from its F₂ and F_2:3 progenies. Of the 177 QTLs identified from the three populations, 65 fiber QTLs and 51 yield QTLs were unique with an average of 8–12 QTLs per traits. All the 26 chromosomes carried QTLs, but differed in the number of QTLs and the number of QTLs between fiber and yield QTLs. The congruence of QTLs identified across populations was higher (20–60 %) for traits with higher heritabilities including fiber quality, seed index and lint percentage, but lower (10–25 %) for lower heritability traits-seedcotton and lint yields. Major QTLs, QTL clusters for the same traits and QTL ‘hotspots’ for different traits were also identified. This research represents the first report using a testcross population in QTL mapping in interspecific cotton crosses and provides useful information for further comparative analysis and marker-assisted selection.     

Identification and validation of a yield-enhancing QTL cluster in rice (Oryza sativa L.)

Improvement of rice grain yield (YD) is an important goal in rice breeding. YD is determined by its related traits such as spikelet fertility (SF), 1,000-grain weight (TGW), and the number of spikelets per panicle (SPP). We previously mapped quantitative trait loci (QTLs) for SPP and TGW using the recombinant inbred lines (RILs) derived from the crosses between Minghui 63 and Teqing. In this study, four QTLs for SF and four QTLs for YD were detected in the RILs. Comparison of the locations of QTLs for these three yield-related traits identified one QTL cluster in the interval between RM3400 and RM3646 on chromosome 3. The QTL cluster contained three QTLs, SPP3a, SF3 and TGW3a, but no YD QTL was located there. To validate the QTL cluster, a BC₄F₂ population was obtained, in which SPP3a, SF3 and TGW3a were simultaneously mapped to the same region. SPP3a, SF3 and TGW3a explained 36.3, 29.5 and 59.0 % of phenotype variance with additive effect of 16.4 spikelets, 6 % SF and 1.8 g grain weight, respectively. In the BC₄F₂ population, though the region has opposite effects on TGW and SPP/SF, a YD QTL YD3 identified in this cluster region can increase 4.6 g grains per plant, which suggests this QTL cluster is a yield-enhancing QTL cluster and can be targeted to improve rice yield by marker aided selection.     

Identification of genetic factors affecting plant density response through QTL mapping of yield component traits in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

It is generally believed that grain yield per unit area of modern maize hybrids is related to their adaptability to high plant population density. In this study, the effects of two different plant densities (52,500 and 90,000 plants/hm²) on 12 traits associated with yield were evaluated using a set of 231 F_2:3 families derived from two elite inbred lines, Zheng58 and Chang7-2. Evaluation of the phenotypes expressed under the two plant density conditions showed that high plant density condition could decrease the value of 10 measured yield component traits, while the final grain yield per hectare and the rate of kernel production were increased. Twenty-seven quantitative trait loci (QTLs) for 10 traits were detected in both high and low plant density conditions; among them, some QTLs were shown to locate in five clusters. Thirty QTLs were only detected under high plant density. These results suggest that some of the yield component traits perhaps were controlled by a common set of genes, and that kernel number per row, ear length, row number per ear, cob diameter, cob weight, and ear diameter may be influenced by additional genetic mechanisms when grown under high plant density. The QTLs identified in this study provide useful information for marker-assisted selection of varieties targeting increased plant density.     

Genome-wide association study of differences in 14 agronomic traits under low- and high-density planting models based on the 660k SNP array for common wheat

One hundred and ninety-seven wheat accessions from Yellow and Huai Winter Wheat Region (YHW) were evaluated for differences of 14 agronomic traits under low- and high-density plantings. Compared with the high-density plantings, plant height, neck length, uppermost internode length, flag leaf angle and number of sterile spikelets under the low-density plantings reduced, while heading date, flowering date, flag leaf length and width, spike length, number of fertile spikelets, grain number per spike, thousand-kernel weight and grain weight per spike increased. A total of 1,118 markers were detected based on GWAS, and seven QTLs were confirmed. One QTL on chromosomes 5BL and two other QTLs on 5Dl were all tightly associated with flowering date difference. Bioinformatics analysis revealed that two haploblocks in 5Dl were involved, and the Vrn-D1 locus was located in this interval. A region on chromosome 5B at around 531.5 Mb was significantly associated with plant height difference. Two QTLs including AX-94840438 (7BL) and AX-94563647 (7DS) were responsible for neck length or uppermost internode length difference.     

源于陕A群、陕B群玉米自交系在不同密度条件下配合力分析

采用NC-II遗传设计,以郑58、昌7-2为测验种,与17份高密度条件下筛选的玉米自交系组配成34份杂交组合,2014—2015年分别于陕西杨凌、长武、榆林进行3种密度(45 000、67 500和90 000株hm–2)配合力分析试验。采用PROC VARCOMP分析不同密度条件下产量及耐密性相关性状的遗传效应,采用频率直方分布图研究不同密度条件下产量及耐密性相关性状一般配合力(GCA)平均数的变化规律,利用AMMI评价玉米自交系与杂交组合的稳定性。结果表明,产量、倒伏率、茎秆强度主要受加性遗传效应控制,空秆率主要受非加性遗传效应控制。加性遗传效应对产量及耐密性相关性状的贡献率随种植密度的增加呈上升趋势。玉米自交系产量、空秆率、倒伏率、茎秆强度的一般配合力频率均属于正态分布,随着种植密度的增加,产量GCA的平均值提高了0.28,空秆率GCA平均值降低了0.21,倒伏率GCA平均值降低了0.03,茎秆强度GCA平均值增加了0.02。玉米杂交组合产量与玉米自交系产量GCA密切相关(r=0.877**,r=0.811**,r=0.672**)。随着种植密度的增加,表现稳定的玉米自交系及杂交组合的数量呈上升趋势。因此,强化逆境选择压力,实施高密度选择策略,是增强玉米自交系耐密性和抗倒性,提升一般配合力,实现产量增益的有效措施。     

Genetic dissection of intersubgenomic heterosis in Brassica napus carrying genomic components of B. rapa

Although strong intersubgenomic heterosis for seed production has been observed between “natural” domesticated Brassica napus (rapeseed, AACC) and a new type of rapeseed into which subgenomic components of Brassica rapa (AA) have been introgressed, the molecular genetic mechanism of this intersubgenomic heterosis is not understood. In this study, a recombinant inbred line population of new type rapeseed derived from a cross between B. napus and B. rapa, together with a population from a backcross with the parental line of B. napus, was used to identify single-locus quantitative trait locus (QTL) and interacting QTL pairs for yield and nine yield-related traits. More than half of single-locus QTLs and interacting QTL pairs detected were involved with the novel alleles induced by the introgression of B. rapa. The alleles directly from B. rapa A genome played a secondary role in contributing to intersubgenomic heterosis. Allelic and nonallelic interactions of both novel alleles generated by B. rapa introgression and the alleles directly from B. rapa A genome contributed to the intersubgenomic heterosis between “natural” domesticated rapeseed and new type rapeseed into which B. rapa had been introgressed. Six loci for fixed heterosis were identified and their possible applications are also discussed.     

Mapping quantitative trait loci for yield-related traits in soybean (Glycine max L.)

Development of soybean cultivars with high seed yield is a major focus in soybean breeding programs. This study was conducted to identify genetic loci associated with seed yield-related traits in soybean and also to clarify consistency of the detected QTLs with QTLs found by previous researchers. A population of 135 F_2:3 lines was developed from a cross between a vegetable soybean line (MJ0004-6) and a landrace cultivar from Myanmar ({"type":"entrez-nucleotide","attrs":{"text":"R18500","term_id":"772110","term_text":"R18500"}}R18500). They were evaluated in the experimental field of Kasetsart University, Kamphaeng Saen, Nakhon Pathom, Thailand in a randomized complete block design with two replications each in 2011 and 2012 growing seasons. The two parents exhibited contrasting characteristics for most of the traits that were mapped. Analysis of variance showed that the main effects of genotype and environment (year) were significant for all studied traits. Genotype by environment interaction was also highly significant for all the traits. The population was genotyped by 149 polymorphic SSR markers and the genetic map consisted of 129 SSR loci which converged into 38 linkage groups covering 1156 cM of soybean genome. There were 10 QTLs significantly associated with seed yield-related traits across two seasons with single QTLs explaining between 5.0% to 21.9% of the phenotypic variation. Three of these QTLs were detected in both years for days to flowering, days to maturity and 100 seed weight. Most of the detected QTLs in our research were consistent with earlier QTLs reported by previous researchers. However, four novel QTLs including SF1, SF2 and SF3 on linkage groups L and N for seed filling period and PN1 on linkage group D1b for pod number were identified in the present study.     

QTL epistatic analysis for yield components with single‐segment substitution lines in rice

Epistasis is an important genetic component in determining the phenotype of complex quantitative trait. In this article, 12 single‐locus heterozygotes and 66 double‐locus heterozygotes were developed and then were applied to assay QTL epistasis for four yield‐associated traits under two planting densities. Of 264 (66 × 4) tested interactions, 130 (49.2%) were significant at the p < .05 level. QTL with the same effect directions had higher probabilities of interactions. The negative epistasis at least included one positive effect QTL but the positive epistasis one negative QTL. The detected epistasis was sensitive to planting density. Epistasis also exhibited pleiotropic effects.     

基于多个相关群体的玉米雄穗相关性状QTL分析

雄穗相关性状对玉米生产至关重要。为了解析玉米雄穗相关性状的遗传机制,利用以黄早四为共同亲本组配的11个重组自交系群体,对玉米雄穗一级分枝数、雄穗主轴长和雄穗干重3个性状进行QTL分析。经过对11个群体及亲本两年三点的田间鉴定,单环境和联合环境下的玉米雄穗相关性状QTL定位,及基因型与环境互作和上位性互作分析,检测到15个在多环境下稳定表达(5个环境以上)的“环境钝感”主效QTL,其中,在染色体bin3.04区域,齐319群体和旅28群体中都定位到1个主效雄穗一级分枝数相关QTL,其平均贡献率分别为17.4%和14.4%,并且2个群体的QTL标记区间高度重叠,在IBM2008 Neighbors图谱上的重叠区间为226.0~230.1。对比不同群体结果发现,在2个群体以上都能检测到的一致性区间21个,其中在第2、第3、第6、第8染色体上的5个一致性区间在3个群体中可稳定表达。这些多环境和多个遗传背景下稳定表达的位点可作为玉米雄穗性状分子标记辅助选择、精细定位及基因克隆的候选位点。     

A QTL atlas for grain yield and its component traits in maize (Zea mays)

Grain yield and its component traits are essential targets in maize breeding. These traits are genetically complex and controlled by a large number of quantitative trait loci (QTL). The aim of this study was to compile reported QTL and major genes for grain yield and its component traits in a QTL atlas, as a valuable resource for the maize community. To this end, 1,177 QTL related to maize yield were collected from 56 studies published between 1992 and 2018. These QTL were projected to genetic map “IBM2 2008 Neighbors”, which led to the identification of 135 meta-QTL. Some genomic regions appear to be hotspots for yield-related meta-QTL, often affecting more than one of the investigated traits. Moreover, we catalogued 20 major maize loci associated with yield and identified 65 maize homologs of 21 rice yield-related genes. Interestingly, we found that a significant proportion of them are located in meta-QTL regions. Collectively, this study provides a reference for QTL fine-mapping and gene cloning, as well as for molecular marker-assisted breeding of yield-related traits in maize.     

Impact of seasonal changes on spikelets per panicle,panicle length and plant height in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Temperature and photoperiod fluctuate rapidly in different seasons of the year, and analyzing their effects on rice yield components is crucial for adaptation of rice under various climatic conditions. To study the effects of seasonal changes on yield components, 168 recombinant inbred lines derived from a cross between two Oryza sativa L. indica varieties, Zhenshan 97 and Zhongzao 18 were grown for phenotype collection, in three different seasons, within a year. The results implied that temperatures across the three seasons played a crucial role in determining the trait effects. Spikelets per panicle (SPP), panicle length (PL) and plant height (PH) traits increased with high temperatures in middle season. Genetic analysis detected major quantitative trait loci (QTLs) qSPP10, qPL10 and qPH10 for SPP, PL and PH in the interval between markers RM1375 and RM3229 on chromosome 10, in all the three seasons. Two-way ANOVA showed that genotype by environment and QTL by environment interactions for these traits were highly significant (P < 0.0001). The region with a cluster of QTLs detected in all three seasons could be the preferred target to breeders in developing rice varieties that can be accustomed to different seasonal changes.