Trait identification and QTL validation for reproductive stage drought resistance in rice using selective genotyping of near flowering RILs

Drought resistance is becoming an indispensable character for rice improvement due to the dwindling global water resources. Genetic improvement for drought resistance is achieved through physiological dissection and genetic analysis of independent component traits associated with crop productivity under stress. A subset mapping population of 93 near flowering recombinant inbred lines with uniform phenology was constituted for genetic analysis of reproductive stage drought resistance. The population was phenotyped for 22 physio-morphological traits under two contrasting water regimes imposed at reproductive stage. Broad sense heritabilities of morphological traits were lower under stress than irrigated. Predominant association of plant height, panicle exsertion and harvest index with grain yield were observed under stress. The sustenance of panicle exsertion through maintaining growth during moisture stress was found as a significant trait associated with the grain yield through minimizing spikelet sterility. Selective genotyping was carried out with 23 polymorphic microsatellite markers of the established target genomic regions for drought resistance. The study validated the association of a QTL region on the long arm of chromosome 1 with plant height, panicle length, panicle exsertion, biological yield and stomatal conductance under stress. This region, flanked by markers RM246 and RM315, was known to possess the semi-dwarf gene, sd-1. Role of another major interval lying between RM256 and RM149 on chromosome 8 in defining the drought resistance could be established through identification of QTLs associated with leaf rolling, panicle exsertion, plant height, panicle length, senescence and biological yield under moisture stress condition. Few other QTLs were also identified.     

水稻株型相关性状的QTL分析

以南方籼型杂交稻恢复系泸恢99和北方粳型超级稻沈农265杂交衍生的重组自交系群体(recombinant inbred lines, RILs)为试验材料, 对株型性状(株高、穗长、分蘖和叶片性状)进行不同环境下的数量性状基因位点(quantitative trait locus, QTL)分析。共检测到39个相关QTL, 分布在水稻第1、第2、第3、第6、第7、第8和第9染色体上, LOD值介于2.50~16.90之间, 有11个QTL能在两年中被检测到。株型相关的QTL在染色体上成簇分布, 主要分布于第1、第6和第9染色体上, 这可能与株型性状间显著或极显著相关有关。其中, 在第9染色体上RM3700B–RM7424区间存在1个QTL簇, 含4个QTL, 即qPH9、qPL9、qFLL9和qSLL9, 这4个QTL在两年中均被检测到。此外, 进一步鉴定出5个能稳定表达的QTL, 其中, qPH8、qFLW6和qSLW6效应较大。这些信息综合反映了株型相关性状遗传的复杂性, 有助于我们更全面地了解和掌握株型性状的遗传基础。     

Identification of QTLs controlling quantitative characters in rice using RFLP markers

Summary Segregation of plant height (PH), tiller number (TN), panicle number (PN), average panicle length per plant (PL), average primary branch number per panicle per plant (PBN) and 1000 grain weight (1000G) were specific in an F₂ population derived from a cross of Palawan, a tall Javanica variety, and IR42, an Indica semidwarf variety. One hundred and four informative RFLP markers covering all 12 chromosomes were used for detecting putative QTLs controlling the traits. Orthogonal contrasts and interval mapping analysis were used for the analysis. QTL detected for PH on the region of chromosome 1, where semidwarfing gene sd-1 locus is located, seems to be a multiple allelic locus. An additional QTL for PH was identified on chromosome 2. Two QTLs for TN were detected on chromosomes 4 and 12. The QTL on chromosome 4 seemed also to govern the variation in PN. Four QTLs were found for the other traits, two of them for PL were located on chromosomes 6 and 2, one for PBN on chromosome 6 and the other for 1000G on chromosome 1. Additive gene actions were found to be predominant, except one QTL for PH and one QTL for PL, but partial or incomplete dominance also existed for the QTLs detected.     

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.     

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。     

Further QTL mapping for yield component traits using introgression lines in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) under drought field environments

To better understand the underlying mechanisms of agronomic traits related to drought resistance and discover candidate genes or chromosome segments for drought-tolerant rice breeding, a fundamental introgression population, BC₃, derived from the backcross of local upland rice cv. Haogelao (donor parent) and super yield lowland rice cv. Shennong265 (recurrent parent) had been constructed before 2006. Previous quantitative trait locus (QTL) mapping results using 180 and 94 BC₃F_6,7 rice introgression lines (ILs) with 187 and 130 simple sequence repeat (SSR) markers for agronomy and physiology traits under drought in the field have been reported in 2009 and 2012, respectively. In this report, we conducted further QTL mapping for grain yield component traits under water-stressed (WS) and well-watered (WW) field conditions during 3 years (2012, 2013 and 2014). We used 62 SSR markers, 41 of which were newly screened, and 492 BC₄F_2,4 core lines derived from the fourth backcross between D123, an elite drought-tolerant IL (BC₃F₇), and Shennong265. Under WS conditions, a total of 19 QTLs were detected, all of which were associated with the new SSRs. Each QTL was only identified in 1 year and one site except for qPL-12-1 and qPL-5, which additively increased panicle length under drought stress. qPL-12-1 was detected in 2013 between new marker RM1337 and old marker RM3455 (34.39 cM) and was a major QTL with high reliability and 15.36% phenotypic variance. qPL-5 was a minor QTL detected in 2013 and 2014 between new marker RM5693 and old marker RM3476. Two QTLs for plant height (qPHL-3-1 and qPHP-12) were detected under both WS and WW conditions in 1 year and one site. qPHL-3-1, a major QTL from Shennong265 for decreasing plant height of leaf located on chromosome 3 between two new markers, explained 22.57% of phenotypic variation with high reliability under WS conditions. On the contrary, qPHP-12 was a minor QTL for increasing plant height of panicle from Haogelao on chromosome 12. Except for these two QTLs, all other 17 QTLs mapped under WS conditions were not mapped under WW conditions; thus, they were all related to drought tolerance. Thirteen QTLs mapped from Haogelao under WS conditions showed improved drought tolerance. However, a major QTL for delayed heading date from Shennong265, qDHD-12, enhanced drought tolerance, was located on chromosome 12 between new marker RM1337 and old marker RM3455 (11.11 cM), explained 21.84% of phenotypic variance and showed a negative additive effect (shortening delay days under WS compared with WW). Importantly, chromosome 12 was enriched with seven QTLs, five of which, including major qDHD-12, congregated near new marker RM1337. In addition, four of the seven QTLs improved drought resistance and were located between RM1337 and RM3455, including three minor QTLs from Haogelao for thousand kernel weight, tiller number and panicle length, respectively, and the major QTL qDHD-12 from Shennong265. These results strongly suggested that the newly screened RM1337 marker may be used for marker-assisted selection (MAS) in drought-tolerant rice breeding and that there is a pleiotropic gene or cluster of genes linked to drought tolerance. Another major QTL (qTKW-1-2) for increasing thousand kernel weight from Haogelao was also identified under WW conditions. These results are helpful for MAS in rice breeding and drought-resistant gene cloning.     

利用单片段代换系研究水稻产量相关性状QTL加性及上位性效应

产量及其相关性状如单株有效穗数、千粒重、穗实粒数、穗总粒数和结实率等是水稻重要的农艺性状,了解产量及其相关性状QTL的加性及上位性效应对以分子标记聚合育种改良水稻产量具有重要意义。本文以16个单片段代换系及15个双片段代换系分析了水稻产量相关性状QTL的加性及上位性效应。共检出影响产量及其相关性状的13个QTL,包括产量性状1个、单株有效穗数1个、千粒重4个、穗实粒数4个、穗总粒数2个和结实率1个,分布于第2、第3、第4、第7和第10染色体上。此外,检出12对双基因互作。结果显示,2个正向(或负向)产量性状QTL聚合,往往会产生负向(或正向)的上位性效应,能否产生更大(或更小)的目标性状,取决于双片段遗传效应(加性效应与上位效应代数和)绝对值与单片段最大加性效应绝对值的差。本研究结果对实施高产分子标记聚合育种方法有重要参考价值。     

Quantitative trait loci and candidate genes for yield and related traits in Madhukar x Swarna RIL population of rice

Yield of popular rice varieties such as Swarna grown in rainfed lowlands and Madhukar grown in flood prone areas needs to be continuously improved. Recombinant inbred lines (RILs) were developed from the cross between two indica cultivars Madhukar and Swarna. QTLs were mapped using 110 markers in 168 RILs. In all, 26 QTLs were mapped for yield and five related traits on chromosomes 1, 2, 3, 6, 7, 8, 10, 11, and 12. QTL for plant height and days to flowering were co-located between RM23147 — RM337 on chromosome 8. RM251, RM314, and RM1135 were significantly associated with plant height and OsYSL17 was significantly linked with grain yield. Epistatic interaction was detected for plant height and number of tillers. Several candidate genes reported for yield and related traits underlie the QTL regions.     

Genetic dissection of rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) tiller,plant height,and grain yield based on QTL mapping and metaanalysis

Tiller number per plant (TN) and plant height (PH) are important agronomic traits related to grain yield (GY) in rice (Oryza sativa L.). A total of 30 additive quantitative trait loci (A-QTL) and 9 significant additive × environment interaction QTLs (AE-QTL) were detected, while the phenotypic and QTL correlations confirmed the intrinsic relationship of the three traits. These QTLs were integrated with 986 QTLs from previous studies by metaanalysis. Consensus maps contained 7156 markers for a total map length of 1112.71 cM, onto which 863 QTLs were projected; 78 meta-QTLs (MQTLs) covering 11 of the 30 QTLs were detected from the cross between Dongnong422 and Kongyu131 in this study. A total of 705 predicted genes were distributed over the 21 MQTL intervals with physical length <0.3 Mb; 13 of the 21 MQTLs, and 34 candidate genes related to grain yield and plant development, were screened. Five major QTLs, viz. qGY6-2, qPH7-2, qPH6-3, qTN6-1, and qTN7-1, were not detected in the MQTL intervals and could be used as newly discovered QTLs. Candidate genes within these QTL intervals will play a meaningful role in molecular marker-assisted selection and map-based cloning of rice TN, PH, and GY.     

Identification and application of major quantitative trait loci for panicle length in rice (Oryza sativa) through single‐segment substitution lines

Panicle length (PL), an important yield‐related trait, strongly affects yield components, such as grain number, grain density and rice quality. More than 200 panicle length quantitative trait loci (PL QTLs) are identified, but only a small number are applied in rice breeding. In this study, we performed QTL analysis for PL using 42 single‐segment substitution lines (SSSLs) derived from nine donors in the genetic background of HJX74. Fourteen QTLs and five heterosis QTLs (HQTLs) for PL were recognised. Three QTLs and four HQTLs acted positively, and the other eleven QTLs and one HQTL acted negatively. By scanning the single heterozygous background region of the F₂ population with large‐genetic‐effect SSSLs, we mapped PL loci qPL6‐2 and qPL7‐1 to different locations on chromosomes 6 and 7, respectively, in three consecutive years of independent trials. The genetic effects of these QTLs were further assessed. qPL6‐2 demonstrated the most positive additive effect (QTL), whereas qPL7‐1 achieved the most positive dominant effect (HQTL) for PL. These results indicated that the pyramiding of PL QTLs might increase grain yield and facilitate the application of the beneficial allele in hybrid rice breeding.     

优良水稻染色体片段代换系Z746的鉴定及重要农艺性状QTL定位及其验证

粒型、株高及穗部组成性状与产量形成密切相关,是水稻重要农艺性状,但遗传基础复杂。染色体片段代换系是用于复杂性状遗传研究的良好材料。本研究鉴定了一个以日本晴为受体、西恢18为供体亲本的水稻优良染色体片段代换系Z746。Z746携带来自西恢18的7个代换片段,平均代换长度为3.99 Mb,其株高、粒长和穗部性状均与受体存在显著差异。进一步通过日本晴与Z746杂交构建的次级F2群体共检测到36个相关QTL,分布于2号、3号、4号、6号和11号染色体。其中5个可能与已克隆基因等位,如qPH3-1等, 8个可被多次检出,表明这些是遗传稳定的主效QTL。Z746的粒长主要由4个QTL(qGL3、qGL4、qGL2、qGL6)控制,其中qGL3和qGL4对粒长变异的贡献率分别为60.28%和27.47%。株高由5个QTL控制,穗长由4个QTL控制,每穗粒数由2个QTL控制,千粒重由2个QTL控制。然后以MAS在F3共选出8个单片段代换系,并以此在F4进行了相关QTL验证,共有24个QTL可被8个单片段代换系(SSSL)检出,重复检出率为66.7%,表明这些QTL遗传稳定。本研究为目的 QTL的进一步...     

Validating a segment on the short arm of chromosome 6 responsible for genetic variation in the hull silicon content and yield traits of rice

Rice is a typical silicon-accumulating plant and the beneficial effect of silicon on rice has long been recognized. In a previous study using 244 recombinant inbred lines (RILs) of an indica rice cross, Zhenshan 97B/Milyang 46 grown in 2003, four QTLs were detected for hull silicon content. QTL qHUS-6 had the largest effect among these, and the same interval also had significant effects on yield traits in the same population. The primary objective of this study was to validate the QTL effect in this region on HUS and yield traits. The same RIL population and another RIL population of lower heterogeneity were grown in 2004. QTL qHUS-6 was found to have significant additive effects on hull silicon content with a consistent direction in the two populations. From a residual heterozygous line selected from RILs of the same cross, 15 F_2:3 lines that differed only in a 2.15-Mb segment extending from RM587 to RM6119 on the short arm of chromosome 6 were derived. In these lines, qHUS-6 displayed a major effect, so did QTLs for yield traits previously detected in the same region. Two more QTLs for HUS detected in 2003, qHUS-1-1 and qHUS-1-2, also had consistent effects in the Zhenshan 97B/Milyang 46 RIL population in 2004. Thus this study verified three candidate regions for fine mapping HUS QTLs and determining the genetic relationship between silicon content and yield traits in rice.     

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.     

Mapping quantitative trait loci for awnness and yield component traits in isogenic lines derived from an Oryza sativa / O. rufipogon cross

An advanced backcross line, HR9118, was produced from a single plant of BC₂F₃ families derived from a cross between Oryza rufipogon Griff. (IRGC 105491) as a donor parent and the O. sativa subsp. japonica cv. Hwaseongbyeo as a recurrent parent. Although HR9118 resembled Hwaseongbyeo, several traits were different from those of Hwasoengbyeo, including days to heading, plant height, and awn. These differences between Hwasongbyeo and HR9118 could be attributed to introgressed O. rufipogon chromosome segments into HR9118. Introgression analysis using 460 SSR markers revealed that three O. rufipogon-specific chromosome segments were detected in HR9118 genome. F_2:3 populations derived from the cross between Hwaseongbyo and HR9118, consisting of 340 F₂ plants and 137 F₃ lines, were used to map and characterize QTLs for 12 traits. QTL analysis identified a total of 17 QTLs in the F_2:3 populations. Of these, seven QTLs were shared by the F₂ and F₃ populations, whereas the other ten QTLs were identified only in the F₃ population. In seven (41.2%) QTLs identified in this study, the O. rufipogon-derived alleles contributed desirable agronomic effects despite the overall undesirable characteristics of the wild phenotype. Each of three O. rufipogon introgressed segments contained multiple QTLs, indicating linkage and/or pleotropic effects. A cluster of eight QTLs was detected on chromosome 8 including a major QTL for awn. Substitution mapping using F₂ population indicated that awn8 was located within an interval between two SSR makers RM23326 and RM23356 which are 590 kb apart. SSR markers tightly linked to QTLs for yield components detected in this study will facilitate cloning of the gene underlying this QTL as well as marker-assisted selection for variation in grain weight in an applied breeding program.     

Identification of a novel QTL for the number of spikelets per panicle using a cross between indica‐ and japonica‐type high‐yielding rice cultivars in Japan

Yield is a complex trait. To improve it, the accumulation of the favourable alleles of valuable genes is required for each yield‐related trait. In this study, we used two high‐yielding rice cultivars developed in Japan, indica‐type ‘Takanari’ and japonica‐type ‘Momiroman’, for a genetic analysis of the sink capacity‐related traits. An F₂ population showed transgressive segregation for the number of spikelets per panicle. Quantitative trait locus (QTL) analysis detected four QTLs for the trait. Two of the QTLs were most likely identical to previously cloned GN1a and APO1, and their Takanari alleles had positive effects. The Momiroman alleles of the other two QTLs had positive effects, and one of these QTLs was most likely identical to SPIKE/GPS. The QTL on the long arm of chromosome 3 appeared to be novel; it clustered with QTLs for grain length and days‐to‐heading. Substitution mapping revealed that the close linkage of QTLs caused the clustering. These results suggest that the combination of the favourable alleles of detected QTLs could lead to greater sink capacity than that of the parental cultivars.     

Genetic studies of seed longevity in hexaploid wheat using segregation and association mapping approaches

Xieyou9308 is the first commercial super hybrid rice released in 1996 in China. To clarify its genetic mechanism underlying high yield potential, a recombinant inbred line (RIL) population derived from the cross between the maintainer line XieqingzaoB (XQZB) and the restorer line Zhonghui9308 (ZH9308) and two derived backcross F₁ (BCF₁) populations were developed for the identification of quantitative trait loci (QTLs) related to ten important agronomic traits (tiller number (TN), heading date (HD), and grain yield per plant (GYPP), etc.). The BCF₁ performance was closely correlated with the performance of their parental RILs according to both the analysis of broad-sense heritability (h _B ²) and phenotypic correlation coefficient (PCC) in the two BCF₁ populations, but not proved by QTL analysis. A total of 21 additive-effect main QTLs (M-QTLs), 22 dominant-effect M-QTLs, and 19 dominant-effect M-QTLs were detected with the WinQTLCart 2.50 software for the ten traits in the RIL and two BCF₁ populations, respectively. Of theses, three QTLs (qHD7a, qPPP3a, and qPL10) of 21 were detected repeatedly in the RIL and one BCF₁ populations, ten QTLs underlying four traits were only detected repeatedly in two BCF₁ populations, and nine QTLs controlling more than two traits were detected repeatedly, the additive-effect QTLs and dominant-effect QTLs play an important role in the performance of agronomic traits and no epistatic QTL of additive by additive effect and dominant by dominant-effect was detected for all traits in three populations. This research is valuable for M-QTL related to important agronomic trait in future fine mapping and positional cloning.     

超级稻品种中嘉早17高产相关性状的QTL定位

水稻产量事关粮食安全,对水稻高产基因的进一步挖掘意义重大。本研究采用花药培养技术,构建了包含101个株系的中嘉早17×D50的加倍单倍体群体(DH群体)。考察海南陵水、浙江杭州高产田块和杭州山区低产田块3种种植环境下DH群体各株系、亲本中嘉早17和D50的有效穗数、每穗粒数、结实率以及千粒重等产量相关性状,同时构建DH群体的遗传连锁图谱。QTL定位分析表明,3种种植环境下共检测到74个具有显著加性效应的QTL,其贡献率变幅为3.7%~43.2%,分布于水稻12条染色体。其中,qPH1-1和qFLL12在3种种植环境下均被检测到,其贡献率分别为8.9%、24.2%、43.2%和16.6%、17.9%、18.9%。此外,qPH3、qFLL10-2、qFLW11-1、qPL11、qGNP11、qSSR3以及qTGW5-17个QTL在其中2种种植环境下被同时检测到,其贡献率变幅为7.4%~42.2%。QTL×环境互作分析表明,仅qPH1-1、qFLW2、qEPP1和qTGW5-14个QTL存在显著的加性×环境互作效应。进一步对qTGW5-1定位区间所包含的GW5测序分析表明,高产株系和低产株系的GW5等位基因分别来自亲本中嘉早17和D50,这与检测到的qTGW5-1的加性效应来自亲本中嘉早17相符。本研究为今后水稻产量相关基因的进一步挖掘以及借助分子聚合育种培育超高产品种提供了理论依据和技术支撑。     

Identification of chromosome regions conferring dry matter accumulation and photosynthesis in wheat (<Emphasis Type="Italic">Triticum</Emphasis> <Emphasis Type="Italic">aestivum</Emphasis> L.)

Dry matter accumulation (DMA) and photosynthetic capacity are important traits that influence biological yield and ultimate grain yield in wheat. In this study, quantitative trait loci (QTLs) analyses for DMA of stem, leaves, total plant and photosynthesis traits (Fv/Fm) at the jointing and anthesis stages were studied, using a set of 168 doubled haploid lines (DHLs) derived from the cross Huapei 3 (HP3)/Yumai 57 (YM57). QTL analyses were performed using QTL-Network 2.0 software based on the mixed linear model approach. A total of 18 additive QTLs and 12 pairs of epistatic QTLs were distributed on 16 of the 21 chromosomes. Most of the additive QTLs associated with DMA co-located in the same or adjacent chromosome intervals with QTLs for grain yield and related traits. A major locus Qculmc.sau-5D.1 (14.2%) close to the molecular marker Xwmc215 detected at the jointing stage was shared by QTLs for heading date and vernalization sensitivity, indicating tight linkages or pleiotropisms. One pair of epistatic QTLs, Qleavesc.sau-4A and Qleavesc.sau- 6B, explained 13.11% of the phenotypic variation at anthesis. All QTL × environment interactions were detected at the jointing stage, showing the importance of the jointing stage in determining the final outcome of plant development.     

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.     

Molecular mapping of quantitative trait loci for plant growth, yield and yield related traits across three diverse locations in a doubled haploid rice population

A doubled haploid (DH) population of 125lines derived from IR64 × Azucena, an indica – japonica cross were grown in three different locations in India during the wet season of 1995. The parents of mapping population had diverse phenotypic values for the eleven traits observed. The DH lines exhibited considerable amount of variation for all the traits. Transgressive segregants were observed. Interval analysis with threshold LOD > 3.00 detected a total of thirty four quantitative trait loci (QTL) for eleven traits across three locations. The maximum number of twenty QTL were detected at Punjab location of North India. A total of seven QTL were identified for panicle length followed by six QTL for plant height. Eight QTL were identified on three chromosomes which were common across locations. A maximum of seven QTL were identified for panicle length with the peak LOD score of 6.01 and variance of 26.80%. The major QTL for plant height was located on Chromosome 1 with peak LOD score of 16.06 flanked by RZ730-RZ801 markers. Plant height had the maximum number of common QTL across environment at the same marker interval. One QTL was identified for grain yield per plant and four QTL for thousand grain weight. Clustering of QTL for different traits at the same marker intervals was observed for plant height, panicle exsertion, panicle number, panicle length and biomass production. This suggests that pleiotropism and or tight linkage of different traits could be the plausible reason for the congruence of several QTL. Common QTL identified across locations and environment provide an excellent opportunity for selecting stable chromosomal regions contributing to yield and yield components to develop QTL introgressed lines that can be deployed in rice breeding program. This revised version was published online in July 2006 with corrections to the Cover Date.