QTL‐seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations

The majority of agronomically important crop traits are quantitative, meaning that they are controlled by multiple genes each with a small effect (quantitative trait loci, QTLs). Mapping and isolation of QTLs is important for efficient crop breeding by marker‐assisted selection (MAS) and for a better understanding of the molecular mechanisms underlying the traits. However, since it requires the development and selection of DNA markers for linkage analysis, QTL analysis has been time‐consuming and labor‐intensive. Here we report the rapid identification of plant QTLs by whole‐genome resequencing of DNAs from two populations each composed of 20–50 individuals showing extreme opposite trait values for a given phenotype in a segregating progeny. We propose to name this approach QTL‐seq as applied to plant species. We applied QTL‐seq to rice recombinant inbred lines and F₂ populations and successfully identified QTLs for important agronomic traits, such as partial resistance to the fungal rice blast disease and seedling vigor. Simulation study showed that QTL‐seq is able to detect QTLs over wide ranges of experimental variables, and the method can be generally applied in population genomics studies to rapidly identify genomic regions that underwent artificial or natural selective sweeps.     

QTL detection with bidirectional and unidirectional selective genotyping: marker-based and trait-based analyses

Selective genotyping of one or both phenotypic extremes of a population can be used to detect linkage between markers and quantitative trait loci (QTL) in situations in which full-population genotyping is too costly or not feasible, or where the objective is to rapidly screen large numbers of potential donors for useful alleles with large effects. Data may be subjected to 'trait-based' analysis, in which marker allele frequencies are compared between classes of progeny defined based on trait values, or to 'marker-based' analysis, in which trait means are compared between progeny classes defined based on marker genotypes. Here, bidirectional and unidirectional selective genotyping were simulated, using population sizes and selection intensities relevant to cereal breeding. Control of Type I error was usually adequate with marker-based analysis of variance or trait-based testing using the normal approximation of the binomial distribution. Bidirectional selective genotyping was more powerful than unidirectional. Trait-based analysis and marker-based analysis of variance were about equally powerful. With genotyping of the best 30 out of 500 lines (6%), a QTL explaining 15% of the phenotypic variance could be detected with a power of 0.8 when tests were conducted at a marker 10 cM from the QTL. With bidirectional selective genotyping, QTL with smaller effects and (or) QTL farther from the nearest marker could be detected. Similar QTL detection approaches were applied to data from a population of 436 recombinant inbred rice lines segregating for a large-effect QTL affecting grain yield under drought stress. That QTL was reliably detected by genotyping as few as 20 selected lines (4.5%). In experimental populations, selective genotyping can reduce costs of QTL detection, allowing larger numbers of potential donors to be screened for useful alleles with effects across different backgrounds. In plant breeding programs, selective genotyping can make it possible to detect QTL using even a limited number of progeny that have been retained after selection.     

Yield-related QTLs and Their Applications in Rice Genetic Improvement

Grain yield is one of the most important indexes in rice breeding,which is governed by quantitative trait loci (QTLs).Different map-ping populations have been used to explore the QTLs controlling yield related traits.Primary populations such as F 2 and recombi-nant inbred line populations have been widely used to discover QTLs in rice genome-wide,with hundreds of yield-related QTLs detected.Advanced populations such as near isogenic lines (NILs) are efficient to further fine-map and clone target QTLs.NILs for primarily identified QTLs have been proposed and confirmed to be the ideal population for map-based cloning.To date,20 QTLs directly affecting rice grain yield and its components have been cloned with NIL-F 2 populations,and 14 new grain yield QTLs have been validated in the NILs.The molecular mechanisms of a continuously increasing number of genes are being unveiled,which aids in the understanding of the formation of grain yield.Favorable alleles for rice breeding have been ’mined’ from natural cultivars and wild rice by association analysis of known functional genes with target trait performance.Reasonable combination of favorable alleles has the potential to increase grain yield via use of functional marker assisted selection.     

Quantitative trait loci mapping of resistance to Laodelphax striatellus (Homoptera: Delphacidae) in rice using recombinant inbred lines

Laodelphax striatellus Fallén (Homoptera: Delphacidae), is a serious pest in rice, Oryza sativa L., production. A mapping population consisting of 81 recombinant inbred lines (RILs), derived from a cross between japonica' Kinmaze' and indica' DV85' rice, was used to detect quantitative trait loci (QTLs) for the resistance to L. striatellus. Seedbox screening test (SST), antixenosis test, and antibiosis test were used to evaluate the resistance response of the two parents and 81 RILs to L. striatellus at the seedling stage, and composite interval mapping was used for QTL analysis. When the resistance was measured by SST method, two QTLs conferring resistance to L. striatellus were mapped on chromosome 11, namely, Qsbph11a and Qsbph11b, with log of odds scores 2.51 and 4.38, respectively. The two QTLs explained 16.62 and 27.78% of the phenotypic variance in this population, respectively. In total, three QTLs controlling antixenosis against L. striatellus were detected on chromosomes 3, 4, and 11, respectively, accounting for 37.5% of the total phenotypic variance. Two QTLs expressing antibiosis to L. striatellus were mapped on chromosomes 3 and 11, respectively, explaining 25.9% of the total phenotypic variance. The identified QTL located between markers XNpb202 and C1172 on chromosome 11 was detected repeatedly by three different screening methods; therefore, it may be important to confer the resistance to L. striatellus. Once confirmed in other mapping populations, these QTLs should be useful in breeding for resistance to L. striatellus by marker-assisted selection of different resistance genes in rice varieties.     

Mapping QTLs associated with drought avoidance in upland rice grown in the Philippines and West Africa

Localizing genes that contribute to drought avoidance in a quantitative way should enable the exploitation of these genes in breeding through marker-assisted selection, and may lead to the discovery of gene identity and function. Between 110 and 176 F₆ recombinant inbred lines from a mapping population derived from a cross of upland rice varieties Bala and Azucena have been evaluated for indicators of drought avoidance in sites in the Philippines and West Africa over two dry seasons. A molecular map with 102 RFLP, 34 AFLP and six microsatellite markers has been used to map (by composite interval mapping) quantitative trait loci (QTLs) for the visual scores of leaf rolling and leaf drying and leaf relative water content. QTLs were mapped for each site and across sites. A total of 17 regions were identified which contained QTLs with a LOD score greater than 3.2. For leaf rolling, Bala was the parent contributing the majority of positive alleles whilst for the other traits, Bala and Azucena contributed more evenly. Six of the 17 regions influenced more than one trait, explaining the phenotypic correlations between traits that were observed. Three QTLs appeared to be specific to the Philippines experiments. One QTL had opposing effects in the Philippines and West Africa. QTLs for relative water content were detected on chromosome 8, congruent with an osmotic adjustment QTL identified in another population. Only three of the QTLs identified here have not been reliably identified in the two other populations that have been screened for drought avoidance. By using several populations assessed for drought avoidance in different sites, the distribution and utility of QTLs for drought avoidance in rice is being elucidated.     

A Chromosome Segment Substitution Library of Weedy Rice for Genetic Dissection of Complex Agronomic and Domestication Traits

Chromosome segment substitution lines (CSSLs) are a powerful alternative for locating quantitative trait loci (QTL), analyzing gene interactions, and providing starting materials for map-based cloning projects. We report the development and characterization of a CSSL library of a U.S. weedy rice accession ‘PSRR-1’ with genome-wide coverage in an adapted rice cultivar ‘Bengal’ background. The majority of the CSSLs carried a single defined weedy rice segment with an average introgression segment of 2.8 % of the donor genome. QTL mapping results for several agronomic and domestication traits from the CSSL population were compared with those obtained from two recombinant inbred line (RIL) populations involving the same weedy rice accession. There was congruence of major effect QTLs between both types of populations, but new and additional QTLs were detected in the CSSL population. Although, three major effect QTLs for plant height were detected on chromosomes 1, 4, and 8 in the CSSL population, the latter two escaped detection in both RIL populations. Since this was observed for many traits, epistasis may play a major role for the phenotypic variation observed in weedy rice. High levels of shattering and seed dormancy in weedy rice might result from an accumulation of many small effect QTLs. Several CSSLs with desirable agronomic traits (e.g. longer panicles, longer grains, and higher seed weight) identified in this study could be useful for rice breeding. Since weedy rice is a reservoir of genes for many weedy and agronomic attributes, the CSSL library will serve as a valuable resource to discover latent genetic diversity for improving crop productivity and understanding the plant domestication process through cloning and characterization of the underlying genes.     

Quantitative trait loci for root-penetration ability and root thickness in rice: comparison of genetic backgrounds.

Drought is the major abiotic stress limiting rice (Oryza sativa) production and yield stability in rainfed lowland and upland ecosystems. Root systems play an important role in drought resistance. Incorporation of root selection criteria in drought resistance improvement is difficult due to lack of reliable and efficient screening techniques. Using a wax-petrolatum layer system simulated to compacted soil layers, root traits were evaluated in a doubled haploid (DH) population derived from the cross between 'IR64' and 'Azucena'. Twelve putative QTLs (quantitative trait loci) were detected by interval mapping comprising four QTLs for root-penetration ability, four QTLs for root thickness, two QTLs for penetrated root number, and two QTLs for total root number. These QTLs individually explained 8.4% to 16.4% of the phenotypic variation. No QTL was detected for maximum penetrated root length by interval mapping. One QTL located between RG104 and RG348 was found to influence both root-penetration ability and root thickness. QTLs for root-penetration ability and root thickness were compared across two populations, 'IR64'-'Azucena' and 'CO39'-'Moroberekan', and different testing conditions. The identified consistent QTLs could be used for marker-assisted selection for deep and thick roots with high root-penetration ability in rice.     

The Statistical Power of Inclusive Composite Interval Mapping in Detecting Digenic Epistasis Showing Common F2 Segregation Ratios

Epistasis is a commonly observed genetic phenomenon and an important source of variation of complex traits,which could maintain additive variance and therefore assure the long-term genetic gain in breeding.Inclusive composite interval mapping（ICIM） is able to identify epistatic quantitative trait loci（QTLs） no matter whether the two interacting QTLs have any additive effects.In this article,we conducted a simulation study to evaluate detection power and false discovery rate（FDR） of ICIM epistatic mapping,by considering F₂ and doubled haploid（DH） populations,different F₂ segregation ratios and population sizes.Results indicated that estimations of QTL locations and effects were unbiased,and the detection power of epistatic mapping was largely affected by population size,heritability of epistasis,and the amount and distribution of genetic effects.When the same likelihood of odd（LOD） threshold was used,detection power of QTL was higher in F₂ population than power in DH population;meanwhile FDR in F₂ was also higher than that in DH.The increase of marker density from 10 cM to 5 cM led to similar detection power but higher FDR.In simulated populations,ICIM achieved better mapping results than multiple interval mapping（MIM） in estimation of QTL positions and effect.At the end,we gave epistatic mapping results of ICIM in one actual population in rice（Oryza sativa L.）.     

Effect of population size and unbalanced data sets on QTL detection using genome-wide association mapping in barley breeding germplasm

Over the past two decades many quantitative trait loci (QTL) have been detected; however, very few have been incorporated into breeding programs. The recent development of genome-wide association studies (GWAS) in plants provides the opportunity to detect QTL in germplasm collections such as unstructured populations from breeding programs. The overall goal of the barley Coordinated Agricultural Project was to conduct GWAS with the intent to couple QTL detection and breeding. The basic idea is that breeding programs generate a vast amount of phenotypic data and combined with cheap genotyping it should be possible to use GWAS to detect QTL that would be immediately accessible and used by breeding programs. There are several constraints to using breeding program-derived phenotype data for conducting GWAS namely: limited population size and unbalanced data sets. We chose the highly heritable trait heading date to study these two variables. We examined 766 spring barley breeding lines (panel #1) grown in balanced trials and a subset of 384 spring barley breeding lines (panel #2) grown in balanced and unbalanced trials. In panel #1, we detected three major QTL for heading date that have been detected in previous bi-parental mapping studies. Simulation studies showed that population sizes greater than 384 individuals are required to consistently detect QTL. We also showed that unbalanced data sets from panel #2 can be used to detect the three major QTL. However, unbalanced data sets resulted in an increase in the false-positive rate. Interestingly, one-step analysis performed better than two-step analysis in reducing the false-positive rate. The results of this work show that it is possible to use phenotypic data from breeding programs to detect QTL, but that careful consideration of population size and experimental design are required.     

Mapping segregation distortion loci and quantitative trait loci for spikelet sterility in rice ( Oryza sativa L.)

Markers with segregation ratio distortion are commonly observed in data sets used for quantitative trait locus (QTL) mapping. In this study, a multipoint method of maximum likelihood (ML) was newly developed to estimate the positions and effects of the segregation distortion loci (SDLs) in two F2 populations of rice (Oryza sativa L.), i.e. Taichung65/Bhadua (TB; japonica-indica cross) and CPSLO17/W207-2 (CW; japonica-japonica). Of the four parents, W207-2 and Bhadua were found to be spikelet semi-sterile and stably inherited through selfing, and spikelet fertility segregated in the two populations. Therefore, recombination frequencies were recalculated after mapping the SDLs by using the multipoint method, and the molecular linkage maps of the two F2 populations were constructed to detect QTLs underlying spikelet fertility. As a result, five SDLs in the TB population were mapped on chromosomes 1, 3, 8 and 9, respectively. Two major QTLs underlying spikelet fertility, namely qSS-6a and qSS-8a, were detected on chromosomes 6 and 8, respectively. In the CW population, a total of 12 SDLs were detected on all 12 chromosomes except 1, 5, 7 and 11. Three QTLs underlying spikelet sterility, namely qSS-2, qSS-6b and qSS-8b on chromosomes 2, 6 and 8, were determined on the whole genome scale. Interestingly, both qSS-6a and qSS-6b, detected in the two F2 populations respectively, were located on a similar position as the S5 gene on chromosome 6; while qSS-8a and qSS-8b were also simultaneously detected on similar positions of the short arm of chromosome 8 in the two populations, which should be a new sterility gene showing the same type of zygotic selection.     

Genetic resolution and verification of quantitative trait loci for flowering and plant height with recombinant inbred lines of maize.

Recombinant inbred (RI) lines offer several advantages for detecting quantitative trait loci (QTLs), including increased precision of trait measurements, power for detection of additive effects, and resolution of linked QTLs. This study was conducted to detect and characterize QTLs in maize for flowering and plant height and to compare QTL detection in an early (F2:3) generation of the same population. One hundred and eighty-six RIs from a cross between inbred lines Mo17 and H99 were evaluated in a replicated field experiment and analyzed at 101 loci detected by restriction fragment length polymorphisms. QTLs were identified by single-factor analysis of variance. A total of 59 QTLs were detected for plant height, ear height, top height, anthesis, silk emergence, and anthesis to silk interval. Individual QTLs explained 2.2-15.4% of trait variation, and multiple models including all QTLs detected for a trait explained up to 52.5% of the phenotypic variation. Comparison of QTLs detected with 150 F2:3 lines from the same population indicated that 16 (70%) of the 23 F2:3 QTLs were also observed in the F6:7 generation. Parental effects were consistent across generations. At 14 of the 16 QTLs detected in both generations, genetic effects were smaller in the F6:7. Also, some QTLs detected in the F2:3 were resolved into multiple linked QTLs in the F6:7, indicating the additional power of RI populations for mapping, with important implications for marker-assisted selection as well as map-based cloning of QTLs. Key words : Zea mays, RFLP, plant breeding, genetics, recombination.     

Validation of quantitative trait loci for Fusarium head blight and kernel discoloration in barley

Validation of quantitative trait loci (QTLs) is a prerequisite to marker assisted selection (MAS), however, only a fraction of QTLs identified for important plant traits have been independently tested for validation. Resistance to the diseases kernel discoloration (KD) and Fusarium head blight (FHB) in barley is complex and technically difficult to assess, and therefore QTLs for these traits are suitable targets for MAS. We selected two lines, from a QTL mapping population created using the resistant variety Chevron, and crossed them to susceptible parents to generate two validation populations. Genetic maps of both populations were developed for five chromosomes covering 15 selected regions containing QTLs for FHB severity, KD score and concentration of deoxynivalenol (DON), a mycotoxin produced by the FHB pathogen. QTL analyses using these validation populations confirmed that five of the possible 15 QTL regions were associated with at least one of the three traits. While some QTL were detected inconsistently across environments, QTL that could be subjected to validation in both populations were confirmed in both populations in seven out of eight instances. A QTL for KD score on chromosome 6(6H) was confirmed in both validation populations in eight of nine environments and was also associated with FHB in three of six environments. A QTL for FHB on chromosome 2(2H) was confirmed and was also associated with KD and heading date. Marker assisted selection at these two QTLs should enhance disease resistance, however, the QTL on chromosome 2(2H) will also delay heading date.     

Genetic diversity and association mapping of seed vigor in rice (Oryza sativa L.)

Key message

Twenty-seven QTLs were identified for rice seed vigor, in which 16 were novel QTLs. Fifteen elite parental combinations were designed for improving seed vigor in rice.

Abstract

Seed vigor is closely related to direct seeding in rice (Oryza sativa L.). Previous quantitative trait locus (QTL) studies for seed vigor were mainly derived from bi-parental segregating populations and no report from natural populations. In this study, association mapping for seed vigor was performed on a selected sample of 540 rice cultivars (419 from China and 121 from Vietnam). Population structure was estimated on the basis of 262 simple sequence repeat (SSR) markers. Seed vigor was evaluated by root length (RL), shoot length (SL) and shoot dry weight in 2011 and 2012. Abundant phenotypic and genetic diversities were found in the studied population. The population was divided into seven subpopulations, and the levels of linkage disequilibrium (LD) ranged from 10 to 80 cM. We identified 27 marker–trait associations involving 18 SSR markers for three traits. According to phenotypic effects for alleles of the detected QTLs, elite alleles were mined. These elite alleles could be used to design parental combinations and the expected results would be obtained by pyramiding or substituting the elite alleles per QTL (apart from possible epistatic effects). Our results demonstrate that association mapping can complement and enhance previous QTL information for marker-assisted selection and breeding by design.     

Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.     

基于单片段代换系的水稻穗长QTL加性及其上位性效应

穗长是影响水稻（Oryza sativa）产量的重要因子之一,研究水稻穗长QTL间的上位性效应对于发掘水稻产量潜力具有重要意义。该研究以16个单片段代换系（single segment substitution lines,SSSLs）和15个双片段聚合系（double segment pyramiding lines,DSPLs）为材料研究了水稻穗长QTL的加性及上位性效应。以P〈0.01为阈值,共检测到6个穗长QTL和9对基因互作座位。其中2个（Pl-2和Pl-10）是尚未报道的穗长QTL。穗长QTL互作后,一些互作对的上位性效应与单个QTL的作用方式及效应大小各不相同,预示着基因聚合后会产生不同的互作效应。该研究结果对于通过分子聚合育种手段改良穗长具有重要意义。     

利用粳稻染色体片段置换系群体检测水稻抗亚铁毒胁迫有关性状QTL

潜育性水稻田广泛分布于中国、斯里兰卡、印度、印度尼西亚、塞拉里昂、利比亚、尼日利亚、哥伦比亚和菲律宾等国,其中我国南方稻区就有近700万公顷低产潜育性水稻田。该类水稻田还原性强,矿质营养失调,尤以Fe^2 过量积累,对水稻生长发育产生不良的逆境胁迫作用。培育抗亚铁毒的水稻品种是简便、经济有效地提高稻谷产量的重要途径之一。该文利用由粳稻品种Asominori与籼稻品种IR24杂交衍生的Asominori染色体片段置换系(Chromosome Segment Substitution Lines,CSSLs)群体为材料,检测与抗亚铁毒胁迫有关性状QTL。共检测到与抗亚铁毒胁迫有关性状QTL14个,各QTL的LOD值为2．72～6．63。其中检测到与抗亚铁毒胁迫直接有关的性状叶片棕色斑点指数QTL3个,分别位于第3、9、11染色体C515～XNpb279、R2638～C1263和G1465～C950之间,对应的贡献率分别为16．45％、11．16％和28．02％;与其他已发表的定位结果比较发现,位于第三染色体C515～XNpb279间控制叶片棕色斑点指数的QTL与水稻功能图谱上控制叶绿素含量的QTL的位置一致;表明在亚铁毒胁迫条件下,水稻在其叶片表面出现棕色斑点,叶片衰老,产生一些叶绿素降解物或衍生物,以提高叶片细胞对亚铁等重金属毒害的耐受力。另外,在第11染色体G1465～C950之间检测到了控制叶片棕色斑点指数、茎干重和根干重QTL1个,为主效QTL。在第6染色体XNpb386～XNpb342之间检测到控制茎干重、株高、根长和根干重QTL1个,是否与水稻抗亚铁毒有关需要进一步研究。本研究旨在通过定位与抗亚铁毒有关的QTL,借助与之紧密连锁的分子标记有效地聚合这些QTL,培育出抗亚铁毒性强的水稻新种质材料。     

水稻籼粳杂种生殖障碍的基因定位分析

籼稻(Oryza sativa L.ssp.indica)与粳稻(O.sativa ssp.japonica)杂交优势明显但存在生殖隔离。生殖障碍主要表现为胚囊败育、花粉败育、开花时花药不开裂和雌雄异熟。应用具有137个标记位点的籼、粳杂交(“窄叶青8号”/“京系17”)F_1花药培养获得的127个双单倍体(DH)群体构建的RFLP图谱,对控制籼、粳杂种小穗败育的基因座位进行了定位研究。结果在第1、3、4、5、6、7、8、12染色体上检测到10个基因座位,其中第3、12染色体上的2个不育基因位点stj-3和stj-12与同一杂交组合F_2分离群体中发现的异常分离热点处于相同的染色体区段。Ssj-6的基因加性效应为负值,有增加籼、粳亲和性的作用;其余的不育基因座位皆有增加籼、粳杂种不育性的作用。     

Mapping QTLs associated with drought avoidance in upland rice

The identification of molecular markers linked to genes controlling drought resistance factors in rice is a necessary step to improve breeding efficiency for this complex trait. QTLs controlling drought avoidance mechanisms were analyzed in a doubled-haploid population of rice. Three trials with different drought stress intensities were carried out in two sites. Leaf rolling, leaf drying, relative water content of leaves and relative growth rate under water stress were measured on 105 doubled haploid lines in two trials and on a sub-sample of 85 lines in the third one. Using composite interval mapping with a LOD threshold of 2.5, the total number of QTLs detected in all trials combined was 11 for leaf rolling, 10 for leaf drying, 11 for relative water content and 10 for relative growth rate under stress. Some of these QTLs were common across traits. Among the eleven possible QTLs for leaf rolling, three QTLs (on chromosomes 1, 5 and 9) were common across the three trials and four additional QTLs (on chromosomes 3, 4 and 9) were common across two trials. One QTL on chromosome 4 for leaf drying and one QTL on chromosome 1 for relative water content were common across two trials while no common QTL was identified for relative growth rate under stress. Some of the QTLs detected for leaf rolling, leaf drying and relative water content mapped in the same places as QTLs controlling root morphology, which were identified in a previous study involving the same population. Some QTL identified here were also located similarly with other QTLs for leaf rolling as reported from other populations. This study may help to chose the best segments for introgression into rice varieties and improvement of their drought resistance.     

Locating QTLs controlling several adult root traits in an elite Chinese hybrid rice

This study aimed to elucidate the genetics of the adult root system in elite Chinese hybrid rice. Several adult root traits in a recombinant inbred line (RIL) population of Xieyou 9308 and two backcross F₁ (BCF₁) populations derived from the RILs were phenotyped under hydroponic culture at heading stage for quantitative trait locus (QTL) mapping and other statistical analysis. There a total of eight QTLs detected for the root traits. Among of them, a pleiotropic QTL was repeatedly flanked by RM180 and RM5436 on the short arm of chromosome 7 for multiple traits across RILs and its BCF₁ populations, accounting for 6.88% to 25.26% of the phenotypic variances. Only additive/dominant QTLs were detected for the root traits. These results can serve as a foundation for facilitating future cloning and molecular breeding.     

Mapping of QTLs governing agronomic and yield traits in chickpea

Chickpea is one of the most important leguminous cool season food crops, cultivated prevalently in South Asia and Middle East. The main objective of this study was to identify quantitative trait loci (QTLs) associated with seven agronomic and yield traits in two recombinant inbred line populations of chickpea derived from the crosses JG62 × Vijay (JV population) and Vijay × ICC4958 (VI population) from at least three environments. Single locus QTL analysis involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated traits to detect pleiotropic QTLs. Two-locus analysis was conducted to identify the main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions. Through CIM analysis, a total of 106 significant QTLs (41 in JV and 65 in VI populations) were identified for the seven traits, of which one QTL each for plant height and days to maturity was common in both the populations. Six pleiotropic QTLs that were consistent over the environments were also identified. LG2 in JV and LG1a in VI contained at least one QTL for each trait. Hence, concentrating on these LGs in molecular breeding programs is most likely to bring simultaneous improvement in these traits.