Genetic mapping for resistance to gray leaf spot in maize

The molecular marker technology has been used on mapping of quantitative trait loci (QTLs) associated with plant resistance. The objectives of this research were to estimate genetic parameters and to map genomic regions involved in the resistance to gray leaf spot in maize. Ninety F₃ families from the BS03 (susceptible) and BS04 (resistant) cross were used. Field trials were performed using a 10 × 10 square lattice design with three replications. Data from 62 SSR markers were used for linkage analysis. The locations of the QTLs on the linkage groups were determined by composite interval mapping method and the phenotypic variance explained by each marker was determined by regression analysis. Several QTLs associated to disease resistance were identified in the population BS03 × BS04. Some QTLs showed significant effects over the different environments studied. The existence of significant QTLs in common among different environments indicates these genomic regions as possible new tools for marker-assisted selection in maize breeding programs.     

Construction of a genetic linkage map and QTL analysis of fiber-related traits in upland cotton (Gossypium hirsutum L.)

A genetic linkage map with 70 loci (55 SSR, 12 AFLP and 3 morphological loci) was constructed using 117 F₂ plants obtained from a cross between two upland cotton cultivars Yumian 1 and T586, which have relatively high levels of DNA marker polymorphism and differ remarkably in fiber-related traits. The linkage map comprised of 20 linkage groups, covering 525 cM with an average distance of 7.5 cM between two markers, or approximately 11.8% of the recombination length of the cotton genome. The present genetic linkage map was used to identify and map the quantitative trait loci (QTLs) affecting lint percentage and fiber quality traits in 117 F_2:3 family lines. Sixteen QTLs for lint percentage and fiber quality traits were identified in six linkage groups by multiple interval mapping: four QTLs for lint percentage, two QTLs for fiber 2.5% span length, three QTLs for fiber length uniformity, three QTLs for fiber strength, two QTLs for fiber elongation and two QTLs for micronaire reading. The QTL controlling fiber-related traits were mainly additive, and meanwhile including dominant and overdominant. Several QTLs affecting different fiber-related traits were detected within the same chromosome region, suggesting that genes controlling fiber traits may be linked or the result of pleiotropy.     

Molecular markers for yield components in Brassica juncea – do these assist in breeding for high seed yield?

A population of 112 F₁-derived doubled haploid lines was produced from a reciprocal cross of Brassica juncea. The parents differed for seed quality, seed color and many agronomic traits. A detailed RFLP linkage map of this population, comprising 316 loci, had been constructed, and was used to map quantitative trait loci (QTL) for seed yield and yield components, viz. siliqua length, number of seeds per siliqua, number of siliques per main raceme and 1000-seed weight. Stable and significant QTLs were identified for all these yield components except seed yield. For yield components, a selection index based on combined phenotypic and molecular data (QTL effects) could double up the efficiency of selection compared to the expected genetic advance by phenotypic selection. Selection indices for high seed yield, based on the phenotypic data of yield and yield components, could only improve the efficiency of selection by 4% of the genetic advance that can be expected from direct phenotypic selection for yield alone. Inclusion of molecular data together with the phenotypic data of yield components in the selection indices did not improve the efficiency of selection for higher seed yield. This is probably due to often negative relationships among the yield components. Most of the QTLs for yield components were compensating each other, probably due to linkage, pleiotropy or developmentally induced relationships among them. The breeding strategy for B. juncea and challenges to marker assisted selection are discussed.     

陆地棉衣分差异群体产量及产量构成因素

 以衣分差异较大的陆地棉品种为材料,构建了包含188个F₂单株的作图群体,应用6111对SSR引物对亲本进行了分子标记筛选,结果仅获得了123个多态性位点,其中88个位点构建了总长为666.7 cM、平均距离为7.57 cM的遗传图谱,覆盖棉花基因组的14.9%。通过复合区间作图法对F₂单株和F_2∶3家系进行QTL检测,共鉴定出了18个控制产量及产量构成因素变异的QTLs,包括2个衣分QTLs、4个子棉产量QTLs、4个皮棉产量QTLs、2个衣指QTLs、3个单株铃数QTLs、2个铃重QTLs和1个子指QTL。 解释的表型变异分别为\{6.9%\}～16.9%、5.6%～16.2%、4.8%～15.6%、7.7%～13.3%、8.2%～11.6%、6.1%～7%和6.6%。不同QTLs在相同染色体区段上的成簇分布表明与产量性状相关的基因可能紧密连锁或一因多效。产量及产量构成因素QTLs的遗传方式主要以显性和超显性效应为主。检测到的主效QTLs可以用于棉花产量及产量构成因素的分子标记辅助选择。     

In vitro screening and QTL analysis for drought tolerance in diploid potato

Drought stress is a major abiotic constraint limiting crop production worldwide. Screening for drought tolerance and the traits that enhance drought tolerance is not straightforward in large mapping populations. In this study, we investigated the possibility of screening a mapping population in vitro for PEG-induced water deficit stress and recovery potential. We have measured several shoot and root growth parameters or traits in the C × E diploid potato mapping population. Significant variation was observed for genotype-specific responses to water deficit and recovery potential. Genetic variation and heritability estimates were high to very high for the measured traits depending on growth conditions. In order to identify potato QTLs for drought tolerance and recovery potential an SNP marker-rich integrated linkage map was used. A total of 23 QTLs were detected under control, stress and recovery treatments explaining 10.3–22.4% of the variance for each phenotypic trait. Among these, 10 QTLs were located on chromosome 2. Three QTLs involved in the important trait root to shoot ratio were identified on linkage groups 2, 3 and 8. These loci explained together 41.1% of the variance for this trait, and may be breeding targets for stress tolerance and yield in the field as well. The SNP markers derived from EST sequences underlying these QTLs led to the identification of putative candidate genes for further study in potato. This study constitutes the first knowledge of in vitro screening of a mapping population for drought tolerance in potato.     

Genetic mapping of QTLs for horticulture traits in a F2-3 population of bitter gourd (Momordica charantia L.)

An extensive genetic linkage map was constructed for bitter gourd (Momordica charantia L.) via the study of F₂ progenies derived from two cultivated inbred lines (gynoecia Z-1-4 and 189-4-1). The map included 194 loci on 11 chromosomes consisting of 26 EST-SSR loci, 28 SSR loci, 124 AFLP loci, and 16 SRAP loci. This map covered 1005.9 cM with 12 linkage groups. A total of 43 quantitative trait loci (QTLs), with a single QTL associated with 5.1–33.1 % phenotypic variance, were identified on nine chromosomes for 13 horticulture traits by analyzing the F_2-3 families and the genetic linkage map. The 13 horticulture traits which were investigated in three environments included female flower ratios (FFR), first female flower node (FFFN), fruit length, fruit diameter, flesh thickness, fruit shape, fruit pedicel length, fruit length pedicel ratios, fruit weight (FW), fruit numbers per plant (FPP), yield per plant (YPP), stem diameter (SD), and internodes length (IL). One QTL cluster region was detected on Lg-5 which contained the most important QTLs for YPP, FPP, FFFN, FFR, and FW with high contributions to phenotypic variance (5.8–25.4 %).     

Detection of quantitative trait loci (QTLs) for seedling traits and drought tolerance in wheat using three related recombinant inbred line (RIL) populations

In order to detect quantitative trait loci (QTLs) for drought tolerance in wheat during seed germination conditional and unconditional QTL analyses of eight seedling traits were conducted under two water regimes using three related F₉ recombinant inbred line populations with a common female parent. A total of 87 QTLs for the eight seedlings traits and 34 specific QTLs related to drought tolerance were detected. Seventy-one of these QTLs were major QTLs with contributions to phenotypic variance of >10 %. Of the 34 QTLs related to drought tolerance only eight were also detected by unconditional analysis of seedling traits under osmotic stress conditions indicating that most of the QTLs related to drought tolerance could not be detected by unconditional QTL analysis. Therefore, conditional QTL analysis of stress-tolerance traits such as drought tolerance was feasible and effective. Of 11 important QTL clusters located on chromosomes 1BL, 1D, 2A, 2B, 2D, 4A, 6B, and 7B, nine were detected in multiple populations and eight were detected by both unconditional and conditional analyses.     

Mapping QTLs for aluminum tolerance in maize

Aluminum toxicity is one of the major constraints for plant development in acid soils, limiting food production in many countries. Cultivars genetically adapted to acid soils may offer an environmental compatible solution, providing a sustainable agriculture system. The aim of this work was to identify genomic regions associated with Al tolerance in maize, and to quantify the genetic effects on the phenotypic variation. A population of 168F_3:4 families derived from a cross between two contrasting maize inbred lines for Al tolerance was evaluated using the NSRL and RSRL parameters in nutrient solution containing toxic level of aluminum. Variance analyses indicated that the NSRL was the most reliable phenotypicindex to measure Al tolerance in the population, being used for further QTL mapping analysis. RFLP and SSR markers were selected for bulked segregant analysis, and additional SSR markers, flanking the polymorphisms of interest, were chosen in order to saturate the putative target regions. Seven linkage groups were constructed using 17 RFLP and 34 SSR markers. Five QTLs were mapped on chromosomes 2, 6 and 8, explaining 60% of the phenotypic variation. QTL₄ and marker umc043 were located on chromosomes 8and 5, close to genes encoding for enzymes involved in the organic acids synthesis pathways, a widely proposed mechanism for Al tolerance in plants. QTL₂ was mapped in the same region as Alm2,also associated with Al tolerance in maize. In addition, dominant and additive effects were important in the control of this trait in maize. This revised version was published online in July 2006 with corrections to the Cover Date.     

Comparison of QTLs mapped in RILs and their test-cross progenies of tropical maize for insect resistance and agronomic traits

Quantitative trait loci (QTL) affecting resistance to south-western corn borer Diatraea grandiosella (SWCB) and sugarcane borer Diatraea saccharalis (SCB) have been identified previously in F_2:3 lines and recombinant inbred lines (RILs) of tropical maize using restriction fragment length polymorphism (RFLP) analyses. Our objective was to determine whether QTLs identified in these generations are also expressed in test crosses (TC) of RILs. A population of 166 TC progenies was developed by crossing RILs from the cross CML131 (susceptible) × CML67 (resistant) with the unrelated, susceptible tester line CML216. Resistance to first-generation SWCB, measured as leaf-feeding damage (LFD) under artificial infestation, and other agronomic traits were evaluated in two environments for the TC progenies and three environments for 183 RILs. The correlation between line per se and TC performance was low for LFD and intermediate for most agronomic traits. Estimates of the genotypic variance and heritabilities were smaller in the TC progenies than in the RILs for all traits. Quantitative trait loci were identified using an RFLP linkage map with 136 loci. For LFD, four QTLs were detected in the TC progenies, of which two were in common with nine QTLs previously mapped in the RILs. Few QTLs for agronomic traits were common to the two types of progeny, because of the low consistency of QTL positions for all traits in RIL and TC progenies, the use of TC progenies should be considered in QTL mapping studies as the first step for marker-assisted selection in hybrid breeding.     

QTL mapping for six ear leaf architecture traits under water‐stressed and well‐watered conditions in maize (Zea mays L.)

Morphological traits for ear leaf are determinant traits influencing plant architecture and drought tolerance in maize. However, the genetic controls of ear leaf architecture traits remain poorly understood under drought stress. Here, we identified 100 quantitative trait loci (QTLs) for leaf angle, leaf orientation value, leaf length, leaf width, leaf size and leaf shape value of ear leaf across four populations under drought‐stressed and unstressed conditions, which explained 0.71%–20.62% of phenotypic variation in single watering condition. Forty‐five of the 100 QTLs were identified under water‐stressed conditions, and 29 stable QTLs (sQTLs) were identified under water‐stressed conditions, which could be useful for the genetic improvement of maize drought tolerance via QTL pyramiding. We further integrated 27 independent QTL studies in a meta‐analysis to identify 21 meta‐QTLs (mQTLs). Then, 24 candidate genes controlling leaf architecture traits coincided with 20 corresponding mQTLs. Thus, new/valuable information on quantitative traits has shed some light on the molecular mechanisms responsible for leaf architecture traits affected by watering conditions. Furthermore, alleles for leaf architecture traits provide useful targets for marker‐assisted selection to generate high‐yielding maize varieties.     

Mapping the QTLs underlying drought stress at developmental stage of sorghum (Sorghum bicolor (L.) Moench) by association analysis

This study was conducted to identify quantitative trait loci (QTLs) for drought tolerance in sorghum (Sorghum bicolor (L.) Moench) by association mapping using a simple sequence repeat (SSR)-marker-based diversity research set. Genotypic data for 98 SSR marker loci on ten chromosomes were used for the association analysis. The experiment was conducted under control (well-watered) and drought stress conditions, and the phenotypic values of 23 morphological traits were recorded. Drought tolerance was assessed by using a leaf drying score as a parameter of the tolerance/susceptibility: scores were assigned on a scale from 1 (most tolerant) to 9 (most susceptible). Under the control conditions, 17 QTLs associated with 12 traits were identified on chromosomes 1, 2, 4, 8, 9, and 10, with ?Log₁₀ (P) ranging from 2.5 to 7.6 and explaining 9.5–57.5 % of the total phenotypic variance for the traits. Under the drought stress conditions, nine QTLs associated with 8 traits were identified on chromosomes 1, 2, 3, and 10 that explained 9–61.2 % of the total phenotypic variance for the traits, with ?Log₁₀ (P) ranging from 2.5 to 3.5. QTLs for some traits were detected only under the drought stress condition, suggesting that these traits are important in drought tolerance. These QTLs could be used to further dissect the genetic and physiological basis of drought tolerance in sorghum.     

QTL analysis for thousand-grain weight under terminal drought stress in bread wheat (<Emphasis Type="Italic">Triticum</Emphasis><Emphasis Type="Italic">aestivum</Emphasis> L.)

Grain yield under post-anthesis drought stress is one of the most complex traits, which is inherited quantitatively. The present study was conducted to identify genes determining post-anthesis drought stress tolerance in bread wheat through Quantitative Trait Loci (QTLs) analysis. Two cultivated bread wheat accessions were selected as parental lines. Population phenotyping was carried out on 133 F_2:3 families. Two field experiments and two experiments in the greenhouse were conducted at IPK-Gatersleben, Germany with control and post-anthesis stress conditions in each experiment. Thousand-grain weight was recorded as the main wheat yield component, which is reduced by post-anthesis drought stress. Chemical desiccation was applied in three experiments as simulator of post-anthesis drought stress whereas water stress was applied in one greenhouse experiment. Analysis of variance showed significant differences among the F_2:3 families. The molecular genetic linkage map including 293 marker loci associated to 19 wheat chromosomes was applied for QTL analysis. The present study revealed four and six QTLs for thousand-grain weight under control and stress conditions, respectively. Only one QTL on chromosome 4BL was common for both conditions. Five QTLs on chromosomes 1AL, 4AL, 7AS, and 7DS were found to be specific to the stress condition. Both parents contributed alleles for drought tolerance. Taking the known reciprocal translocation of chromosomes 4AL/7BS into account, the importance of the short arms of homoeologous group 7 is confirmed for drought stress.     

Fine mapping of major QTLs for alkaline tolerance at the seedling stage in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.) through genetic linkage analysis combined with high-throughput DNA sequencing

Exploiting genes and quantitative trait loci (QTLs) related to maize (Zea mays L.) alkaline tolerance is helpful for improving alkaline resistance. To explore the inheritance of maize alkaline tolerance at the seedling stage, a mapping population comprising 151 F_2:3 lines derived from the maize cross between Zheng58, tolerant to alkaline, and Chang7-2, sensitive to alkaline, was used to establish a genetic linkage map with 200 SSR loci across the 10 maize linkage groups, with an average interval of 6.5 cM between adjacent markers. QTLs for alkaline resistant traits of alkaline tolerance rating (ATR), germination rate (GR), relative conductivity (RC), weight per plant (WPP) and proline content (PC) were detected. The obtained results were as follows: Five QTLs on chromosomes 2, 5 and 6 (GR and WPP: chr. 2; PC and ATR: chr. 5; and RC: chr. 6) were mapped. For precise mapping of the QTLs related to alkaline resistance, two bulked deoxyribonucleic acid (DNA) pools were constructed using individual DNAs from the most tolerant 30 F₂ individuals and the most sensitive 30 F₂ individuals according to the ATR and used to establish a high density map of SLAF markers strongly associated with the ATR by specific locus amplified fragment sequencing (SLAF-Seq) combined with super bulked segregant analysis (superBSA). One marker-intensive region involved three SLAFs at 296,000–6,203,000 bp on chromosome 5 that were closely related to the ATR. Combined with preliminary QTL mapping with superBSA, two major QTLs on chromosome 5 associated with alkaline tolerance at the maize seedling stage were mapped to marker intervals of dCap-SLAF31521 and dCap-SLAF31535 and phi024 and dCap-SLAF31521, respectively. These QTL regions involved 9 and 75 annotated genes, respectively. These results will be helpful for improving maize alkaline tolerance at the seedling stage by marker-assisted selection programs and will be useful for fine mapping QTLs for maize breeding.     

Genetic mapping of quantitative trait loci for fiber quality and yield trait by RIL approach in Upland cotton

The improvement of cotton fiber quality has become more important because of changes in spinning technology. Stable quantitative trait loci (QTLs) for fiber quality will enable molecular marker-assisted selection to improve fiber quality of future cotton cultivars. A simple sequence repeat (SSR) genetic linkage map consisting of 156 loci covering 1,024.4 cM was constructed using a series of recombinant inbred lines (RIL) developed from an F₂ population of an Upland cotton (Gossypium hirsutum L.) cross 7235 × TM-1. Phenotypic data were collected at Nanjing and Guanyun County in 2002 and 2003 for 5 fiber quality and 6 yield traits. We found 25 major QTLs (LOD ≥ 3.0) and 28 putative QTLs (2.0 < LOD < 3.0) for fiber quality and yield components in two or four environments independently. Among the 25 QTLs with LOD ≥ 3, we found 4 QTLs with large effects on fiber quality and 7 QTLs with large effects on yield components. The most important chromosome D8 in the present study was densely populated with markers and QTLs, in which 36 SSR loci within a chromosomal region of 72.7 cM and 9 QTLs for 8 traits were detected.     

Detection of quantitative trait locus for leaffolder (Cnaphalocrocis medinalis (Guenée)) resistance in rice on linkage group 1 based on damage score and flag leaf width

Rice leaffolder (RLF) (Cnaphalocrocis medinalis (Guenée) is a destructive and widespread insect pest throughout the rice growing regions in Asia. The genetics of resistance to RLF in rice is very complex and not thoroughly explored. The present study was conducted to detect the quantitative trait loci (QTL) associated with RLF resistance involving 176 recombinant inbred lines (RILs) of F₈ generation derived from a cross between IR36, a leaffolder susceptible variety and TNAULFR831311, a moderately resistant indica rice culture. Simple sequence repeat (SSR) markers were used to construct specific linkage groups of rice. All the RILs were screened to assess their level of resistance to RLF by measuring the leaf area damaged. Besides this, the length and width of the flag leaf of each RIL were measured since these two parameters were considered as correlated traits to the RLF resistance in rice. All the above parameters observed across the RILs showed quantitative variation. Correlation analysis revealed that damage score based on greenhouse screening was positively correlated with length and width of the flag leaf. Out of 364 SSR markers analysed, 90 were polymorphic between the parents. Multi-point analysis carried out on segregating 69 SSR marker loci linkage group wise resulted in construction of linkage map with eleven groups of 42 SSR markers. Through single marker analysis, 19 SSR markers were found to have putative association with the three phenotypic traits studied. Of these markers, RM472 was identified as a locus having major effect on RLF resistance trait based on length of the flag leaf. Interval mapping detected two QTLs on linkage group 1. Among these QTLs, the QTL flanked by RM576–RM3412 were found to be associated with width of the flag leaf and RLF resistance. The putative SSR markers associated with leaffolder resistance identified in the present study may be one of the loci contributing resistance to RLF in rice.     

不同生态环境下玉米产量性状QTL分析

以玉米（Zea mays L.）自交系黄早四和Mo17为亲本得到的191个F₂单株为作图群体,衍生的184个F_2∶3 家系作为性状评价群体,分析了单株穗数、穗行数、行粒数、百粒重和单株籽粒产量在北京和新疆2个生态环境下的表现和数量性状基因位点的定位结果。QTL检测结果表明,2个环境共检测出47个QTL,分布于除第10染色体以外的9条染色体,其中与单株穗数相关的QTL共10个,可解释的表型变异为5.3%~25.6%;与穗行数相关的QTL共13个,可解释的表型变异为4.5%~23.2%;与行粒数相关的QTL有9个,解释的表型变异为5.4%~13.7%;与百粒重相关的QTL达10个,可解释的表型变异为4.9%~13.3%;与单株籽粒产量相关的QTL有5个,可解释的表型变异为6.1%~35.8 %。大部分产量QTL只在单一环境下被检测到,说明产量相关QTL与环境之间存在明显的互作。表型相关显著的产量性状,它们的QTL容易在相同或相邻标记区间检测到。研究还发现了若干个QTL富集区域,可能是发掘通用QTL的候选位点。     

Mapping QTLs of traits contributing to yield and analysis of genetic effects in tetraploid cotton

Fiber yield and yield components – including lint index (LI), seed index (SI), lint yield (LY), seed cotton yield (SCY) and number of seeds per boll (NSPB) – were investigated on the farm of Huazhong Agricultural University in a population of 69 F₂ individuals and corresponding F_2:3 families derived from a cross between high-fiber-yield Gossypium hirsutum CV Handan 208 and a low-fiber-yield Gossypium barbadense CV Pima 90. On the basis of the genetic map constructed previously from the same population by Lin et al. (Plant Breed., 2005), quantitative trait locus (QTL) analysis was performed with the software QTL Cartographer V2.0 using composite interval mapping method (LOD ≥ 3.0). A total of 21 QTLs were identified, which were located in 15 linkage groups. The number of QTLs per trait ranged from one to seven. Of these QTLs detected, one affecting LI explained 24.3% of phenotypic variation (PV), five influencing SI explained 16.15–39.21% of PV, seven controlling LY explained 13.01–28.35% of PV, and two controlling SCY explained 22.76 and 39.97% of PV, respectively. Simultaneously, the detected six QTLs for NSPB were located on five linkage groups, which individually explained 28.01–38.32% of the total phenotypic variation. The results would give breeders further insight into the genetic basis of fiber yield.     

向日葵高密度遗传连锁图谱构建及两种水分条件下芽期性状的QTL分析

干旱胁迫对向日葵发芽出苗有重要影响。以K55×K58组合衍生的187个F6重组自交系为材料,利用SSR、SRAP、AFLP标记构建向日葵高密度遗传连锁图谱,设置正常水分(CK)和模拟干旱(18%聚乙二醇PEG-6000)两种水分条件,调查9个芽期数量性状,PCR扩增株系,构建一张包含17个连锁群、1105个标记(368个SSR、368个SRAP和369个AFLP)的高密度遗传连锁图谱。该图谱覆盖基因组长度3846.0 c M,平均图距3.48 c M,连锁群长度147.6~295.5 c M,每个连锁群标记数10~165个。两种条件下检测到33个QTL,其中干旱条件下检测到发芽指数、发芽率、胚芽长、胚根长、胚芽鲜重和胚根鲜重6个性状的14个QTL,可解释6.1%~14.0%的表型变异;正常水分(CK)条件下检测到发芽势、胚根长、胚芽鲜重、胚根鲜重、胚根干重和胚芽干重6个性状的19个QTL,可解释6.1%~25.8%的表型变异。两种水分条件下检测到Qefw5-1、Qefw5-2、Qefw5-4、Qrfw5、Qrfw10和Qrl9共6个QTL的遗传贡献率超过10%,此外,还检测到9个影响干旱胁迫与正常水分条件下性状差值的QTL,可能对抗旱性有直接贡献。这些QTL可为向日葵芽期抗旱分子设计育种研究提供重要参考。     

QTL analysis of yield-related traits in sunflower under different water treatments

A set of sunflower recombinant inbred lines (RILs) was used to study agronomical traits under greenhouse and field conditions each with two water treatments and three replications. The difference among RILs was significant for all the traits studied in all conditions; and water treatment × RILs interaction was also observed for most of the traits in both field and greenhouse conditions. Because of the low rate of drought stress, this part of field data are not informative. Several quantitative trait loci (QTLs) were identified for yield-related traits with the percentage of phenotypic variance explained by QTLs ( R ²) ranging from 4% to 40%. Several QTLs for grain yield per plant (GYP) under four water treatments were identified on different linkage groups, among which two were specific to a single treatment ( GYPN.4.1 , GYPI.7.1 ). Three QTLs for GYP were overlapped with several QTLs for drought-adaptative traits detected in our previous study ( Poormohammad Kiani et al. 2007b ). The whole results do highlight interesting genomic regions for marker-based breeding programmes for drought tolerance in sunflower.     

QTL analysis of seed dormancy in rice (Oryza sativa L.)

Effective cumulative temperature (ECT) after heading would be a more reasonable parameter for seed sampling of pre-harvest sprouting/seed dormancy (SD) tests in segregating populations than the days after flowering. SD is an important agronomic trait associated with grain yielding, eating quality and seed quality. To identify genomic regions affecting SD at different grain-filling temperatures, and to further examine the association between SD and ECT during grain-filling, 127 double haploid (DH) lines derived from a cross between ZYQ8 (indica)/JX17 (japonica) by anther culture were analyzed. The quantitative trait loci (QTLs) and their digenic epistasis for SD were identified using a molecular linkage map of this population. A total of four putative QTLs for SD (qSD-3, qSD-5, 6 and 11) were detected on chromosomes 3, 5, 6 and 11, together explaining 41.4% of the phenotypic variation. Nine pairs of digenic epistatic loci were associated with SD on all but chromosome 9, and their contributions to phenotypic variation varied from 2.87%–8.73%. The SD QTL on chromosome 3 was identical to the QTLs found in other mapping populations with different genetic backgrounds, which could be a desirable candidate for gene cloning and marker-assisted selection in rice breeding.