Characterization and precise mapping of a QTL increasing spike number with pleiotropic effects in wheat

Tiller number (TN) and spike number per plant (SN) are key components of grain yield and/or biomass in wheat. In this study, an introgression line 05210, developed by introgression of chromosomal segments from a synthetic exotic wheat Am3 into an elite cultivar Laizhou953, showed a significantly increased TN and SN, but shorter spike length (SL) and fewer grain number per spike (GNS) than Laizhou953. To investigate the quantitative trait locus (QTL) responsible for these variations, the introgressed segments in 05210 were screened by SSR markers and one follow-up segregation population was developed from the cross 05210/Laizhou953. The population showed 3:1 segregation ratios for SN, SL and GNS, indicating that QTLs for these traits have been dissected into single Mendelian factors. Bulked segregation analysis showed that the markers located on the 4B introgressed segment were polymorphic between the two bulks. Therefore, they were further analyzed in the F₂ population to construct a linkage map. Three new QTLs, QSn.sdau-4B, QSl.sdau-4B and QGns.sdau-4B, were detected for SN, SL and GNS, respectively, which explained a large portion of the phenotypic variation (30.1–67.6%) for these traits with overlapping peaks. Correlation analysis and multiple-trait, multiple-interval mapping (MMIM) suggested pleiotropic effects of the QTL on SN, SL and GNS. Therefore, the QTL was designated as QSn.sdau-4B. By a progeny test based on F₃ families using SN, the QTL was mapped as a Mendelian factor to the proximal region of 4BL. It is a key QTL responsible for variation in spike number and size, which had not been reported previously. Thus, it is an important QTL for wheat to achieve high and stable biomass and grain yield. Dissection and mapping of this QTL as a Mendelian factor laid a solid foundation for map-based cloning of grain yield-related QTLs in wheat.     

Conditional QTL mapping of protein content in wheat with respect to grain yield and its components

Grain protein content in wheat (Triticum aestivum L.) is generally considered a highly heritable character that is negatively correlated with grain yield and yield-related traits. Quantitative trait loci (QTL) for protein content was mapped using data on protein content and protein content conditioned on the putatively interrelated traits to evaluate possible genetic interrelationships between protein content and yield, as well as yield-related traits. Phenotypic data were evaluated in a recombinant inbred line population with 302 lines derived from a cross between the Chinese cultivar Weimai 8 and Luohan 2. Inclusive composite interval mapping using IciMapping 3.0 was employed for mapping unconditional and conditional QTL with additives. A strong genetic relationship was found between protein content and grain yield, and yield-related traits. Unconditional QTL mapping analysis detected seven additive QTL for protein content, with additive effects ranging in absolute size from 0.1898% to 0.3407% protein content, jointly accounting for 43.45% of the trait variance. Conditional QTL mapping analysis indicated two QTL independent from yield, which can be used in marker-assisted selection for increasing yield without affecting grain protein content. Three additional QTL with minor effects were identified in the conditional mapping. Of the three QTLs, two were identified when protein content was conditioned on yield, which had pleiotropic effects on those two traits. Conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the individual QTL level for closely correlated traits. Further, conditional QTL mapping can reveal additional QTL with minor effects that are undetectable in unconditional mapping.     

Multi-environment QTL analyses for drought-related traits in a recombinant inbred population of chickpea (Cicer arientinum L.)

A recombinant inbred line (RIL) population, comprising 181 lines derived from ILC588 × ILC3279, was evaluated in 10 environments across three locations with different moisture gradients. A drought resistance score (DRS) and three phenology traits—plant height (PLHT), days to flowering (DFLR), and days to maturity (MAT)—were recorded along with seven yield-related traits—grain yield (GY), biological yield (BY), harvest index (HI), the number of pods/3 plants (Pod), percentage of empty pods (%Epod), 100 seed weight (100 sw), and seed number/3 plants (SN). Two RILs (152, 162) showed the best GYs and DRSs under stressed and non-stressed environments. The quantitative trait loci (QTLs) analyses detected 93 significant QTLs (LOD ≥ 2.0) across the genome × environment interactions. The highest phenotypic variation (>24 %) was explained by the QTL_DFLR in Terbol-11. Four common possible pleiotropic QTLs on LG3 and LG4 were identified as associated with DFLR, DRS, GY, MAT, HI, SN, and Pod. No significant epistatic interactions were found between these QTLs and the other markers. However, the QTL for DRS was detected as a conserved QTL in three late planting environments. The markers H6C-07 (on LG3) and H5G01 (on LG4) were associated with QTLs for many traits in all environments studied except two. The allele ‘A’ of marker H6C07 (from the tolerant parent ILC588) explained 80 % of the yield increase under late planting and 29.8 % of that under dry environments. Concentrating on LG3 and LG4 in molecular breeding programs for drought could speed up improvement for these traits.     

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.     

Quantitative trait loci for rice yield-related traits using recombinant inbred lines derived from two diverse cultivars

The thousand-grain weight and spikelets per panicle directly contribute to rice yield. Heading date and plant height also greatly influence the yield. Dissection of genetic bases of yield-related traits would provide tools for yield improvement. In this study, quantitative trait loci (QTL) mapping for spikelets per panicle, thousand-grain weight, heading date and plant height was performed using recombinant inbred lines derived from a cross between two diverse cultivars, Nanyangzhan and Chuan7. In total, 20 QTLs were identified for four traits. They were located to 11 chromosomes except on chromosome 4. Seven and five QTLs were detected for thousand-grain weight and spikelets per panicle, respectively. Four QTLs were identified for both heading date and plant height. About half the QTLs were commonly detected in both years, 2006 and 2007. Six QTLs are being reported for the first time. Two QTL clusters were identified in regions flanked by RM22065 and RM5720 on chromosome 7 and by RM502 and RM264 on chromosome 8, respectively. The parent, Nanyangzhan with heavy thousand-grain weight, carried alleles with increased effects on all seven thousand-grain weight QTL, which explained why there was no transgressive segregation for thousand-grain weight in the population. In contrast, Chuan7 with more spikelets per panicle carried positive alleles at all five spikelets per panicle QTL except qspp5. Further work on distinction between pleiotropic QTL and linked QTL is needed in two yield-related QTL clusters.     

绿豆5个产量相关性状的QTL分析

利用绿豆(Vigna radiata)品种苏绿16-10和潍绿11杂交构建的F₂和F₃群体发掘调控绿豆产量相关性状的遗传位点。同时对绿豆产量相关性状进行表型鉴定和相关性分析, 并利用构建的遗传连锁图谱进行QTL定位。结果表明, 单株产量与单株荚数、单荚粒数、百粒重和分枝数均呈正相关。单株产量与单株荚数的相关性最高, 这2个性状在F₂和F₃群体中的相关系数分别为0.950和0.914。在F₂群体中, 共检测到8个与产量性状相关的QTL位点, 其中与单株荚数、单荚粒数和单株产量相关的QTL位点各1个, 分别解释11.09% (qNPP3)、17.93% (qNSP3)和14.18% (qYP3)的表型变异; 2个与分枝数相关的QTL位点qBMS3和qBMS11, 分别解释18.51%和7.06%的表型变异; 3个与百粒重相关的QTL位点qHSW3、qHSW7和qHSW10, 分别解释5.33%、46.07%和4.24%的表型变异。在F₃群体中, qNSP3和qHSW7再次被检测到, 表明这2个QTLs有较好的遗传稳定性。同时, 开发了1个与百粒重主效QTL qHSW7紧密连锁的InDel标记R7-13.4, 并利用自然群体对该分子标记辅助筛选的有效性进行了验证。研究结果可为绿豆产量相关性状基因的定位、克隆及分子标记辅助育种提供参考。     

Whole-Genome Quantitative Trait Locus Mapping Reveals Major Role of Epistasis on Yield of Rice

Although rice yield has been doubled in most parts of the world since 1960s, thanks to the advancements in breeding technologies, the biological mechanisms controlling yield are largely unknown. To understand the genetic basis of rice yield, a number of quantitative trait locus (QTL) mapping studies have been carried out, but whole-genome QTL mapping incorporating all interaction effects is still lacking. In this paper, we exploited whole-genome markers of an immortalized F₂ population derived from an elite rice hybrid to perform QTL mapping for rice yield characterized by yield per plant and three yield component traits. Our QTL model includes additive and dominance main effects of 1,619 markers and all pair-wise interactions, with a total of more than 5 million possible effects. The QTL mapping identified 54, 5, 28 and 4 significant effects involving 103, 9, 52 and 7 QTLs for the four traits, namely the number of panicles per plant, the number of grains per panicle, grain weight, and yield per plant. Most identified QTLs are involved in digenic interactions. An extensive literature survey of experimentally characterized genes related to crop yield shows that 19 of 54 effects, 4 of 5 effects, 12 of 28 effects and 2 of 4 effects for the four traits, respectively, involve at least one QTL that locates within 2 cM distance to at least one yield-related gene. This study not only reveals the major role of epistasis influencing rice yield, but also provides a set of candidate genetic loci for further experimental investigation.     

Detection of QTL for six yield-related traits in oilseed rape (<Emphasis Type="Italic">Brassica napus</Emphasis>) using DH and immortalized F<Subscript>2</Subscript> populations

The inheritance of yield-related traits in rapeseed (Brassica napus) is poorly understood, and the investigations on mapping of quantitative trait loci (QTL) for such traits are only few. QTL related to six traits were mapped which include plant height (PH), height of lowest primary effective branch (HPB), length of main inflorescence (LMI), silique length (SL), number of primary branches (FB) and silique density (SD). A set of 258 doubled haploid (DH) lines derivatives of a cross between a canola variety Quantum and a resynthesized B. napus line No.2127-17, and a fixed immortalized F₂ (designated as IF₂) population generated by randomly permutated intermating of these DHs were investigated. A genetic linkage map was constructed using 208 SSR and 189 SRAP markers for the DH population. Phenotypic data were collected from three environments for the two populations. Using composite interval mapping analyses, 30 and 22 significant QTL were repeatedly detected across environments for the six traits in the DH and IF₂ populations, respectively. Twenty-nine QTL were common between the two populations. The directions of parental contribution for all common QTL were the same, showing a great potential for marker-assisted selection in improving these traits. Some chromosomal regions harbor QTL for multiple traits, which were consistent with significant phenotypic correlations observed among traits. The results provided a better understanding of the genetic factors controlling yield-related traits in rapeseed. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.)

Development of high-yielding wheat varieties with good end-use quality has always been a major concern for wheat breeders. To genetically dissect quantitative trait loci (QTLs) for yield-related traits such as grain yield, plant height, maturity, lodging, test weight and thousand-grain weight, and for quality traits such as grain and flour protein content, gluten strength as evaluated by mixograph and SDS sedimentation volume, an F₁-derived doubled haploid (DH) population of 185 individuals was developed from a cross between a Canadian wheat variety “AC Karma” and a breeding line 87E03-S2B1. A genetic map was constructed based on 167 marker loci, consisting of 160 microsatellite loci, three HMW glutenin subunit loci: Glu-A1, Glu-B1 and Glu-D1, and four STS-PCR markers. Data for investigated traits were collected from three to four environments in Manitoba, Canada. QTL analyses were performed using composite interval mapping. A total of 50 QTLs were detected, 24 for agronomic traits and 26 for quality-related traits. Many QTLs for correlated traits were mapped in the same genomic regions forming QTL clusters. The largest QTL clusters, consisting of up to nine QTLs, were found on chromosomes 1D and 4D. HMW glutenin subunits at Glu-1 loci had the largest effect on breadmaking quality; however, other genomic regions also contributed genetically to breadmaking quality. QTLs detected in the present study are compared with other QTL analyses in wheat.     

A complete genetic linkage map and QTL analyses for bast fibre quality traits, yield and yield components in jute (Corchorus olitorius L.)

We report the first complete microsatellite genetic map of jute (Corchorus olitorius L.; 2n = 2 × = 14) using an F₆ recombinant inbred population. Of the 403 microsatellite markers screened, 82 were mapped on the seven linkage groups (LGs) that covered a total genetic distance of 799.9 cM, with an average marker interval of 10.7 cM. LG5 had the longest and LG7 the shortest genetic lengths, whereas LG1 had the maximum and LG7 the minimum number of markers. Segregation distortion of microsatellite loci was high (61%), with the majority of them (76%) skewed towards the female parent. Genomewide non-parametric single-marker analysis in combination with multiple quantitative trait loci (QTL)-models (MQM) mapping detected 26 definitive QTLs for bast fibre quality, yield and yield-related traits. These were unevenly distributed on six LGs, as co-localized clusters, at genomic sectors marked by 15 microsatellite loci. LG1 was the QTL-richest map sector, with the densest co-localized clusters of QTLs governing fibre yield, yield-related traits and tensile strength. Expectedly, favorable QTLs were derived from the desirable parents, except for nearly all of those for fibre fineness, which might be due to the creation of new gene combinations. Our results will be a good starting point for further genome analyses in jute.     

Quantitative trait loci underlying domestication- and yield-related traits in an Oryza sativa x Oryza rufipogon advanced backcross population

To understand the genetic characteristics of the traits related to differentiation between cultivated rice and its wild progenitor, genetic factors controlling domestication- and yield-related traits were identified using a BC3F2 population derived from an accession of common wild rice (donor, Oryza rufipogon Griff.) collected from Yuanjiang, Yunnan province, China, and an indica cultivar, Teqing (recipient, Oryza sativa L.). A genetic linkage map consisting of 125 simple sequence repeat (SSR) markers was constructed. Based on the phenotypes of the 383 BC3F2 families evaluated in two environments, two domestication-related morphological traits, panicle shape and growth habit, were found to be controlled by single Mendelian factors. This implies that the recessive mutations of single genes controlling some morphological traits could have been easily selected during early domestication. By single-point analysis and interval mapping, 59 putative quantitative trait loci (QTLs) that influence 11 quantitative traits were detected at two sites, and 37.5% of the QTL alleles originating from O. rufipogon had a beneficial effect for yield-related traits in the Teqing background. Regions with significant QTLs for domestication- and yield-related traits were detected on chromosomes 1, 4, 5, 7, 8, and 12. Fine mapping and cloning of these domestication-related genes and QTLs will be useful in elucidating the origin and differentiation of Asian cultivated rice in the future.     

Quantitative trait loci for seed yield and yield-related traits, and their responses to reduced phosphorus supply in Brassica napus

Background and Aims

One of the key targets of breeding programmes in rapeseed (Brassica napus) is to develop high-yield varieties. However, the lack of available phosphorus (P) in soils seriously limits rapeseed production. The aim of this study was to dissect the genetic control of seed yield and yield-related traits in B. napus grown with contrasting P supplies.

Methods

Two-year field trials were conducted at one site with normal and low P treatments using a population of 124 recombinant inbred lines derived from a cross between ‘B104-2’ and ‘Eyou Changjia’. Seed yield, seed weight, seed number, pod number, plant height, branch number and P efficiency coefficient (PEC) were investigated. Quantitative trait locus (QTL) analysis was performed by composite interval mapping.

Key Results

The phenotypic values of most of the tested traits were reduced under the low P conditions. In total, 74 putative QTLs were identified, contributing 7·3–25·4 % of the phenotypic variation. Of these QTLs, 16 (21·6 %) were detected in two seasons and in the mean value of two seasons, and eight QTLs for two traits were conserved across P levels. Low-P-specific QTLs were clustered on chromosomes A1, A6 and A8. By comparative mapping between Arabidopsis and B. napus, 161 orthologues of 146 genes involved in Arabidopsis P homeostasis and/or yield-related trait control were associated with 45 QTLs corresponding to 23 chromosomal regions. Four gene-based markers developed from genes involved in Arabidopsis P homeostasis were mapped to QTL intervals.

Conclusions

Different genetic determinants were involved in controlling seed yield and yield-related traits in B. napus under normal and low P conditions. The QTLs detected under reduced P supply may provide useful information for improving the seed yield of B. napus in soils with low P availability in marker-assisted selection.     

QTL and epistatic analyses of heterosis for seed yield and three yield component traits using molecular markers in rapeseed (Brassica napus L.)

Aiming to explore the basis of heterosis in rapeseed, QTLs for yield and three yield component traits were mapped and the digenic interactions were detected in an F₂ population derived from a cross between two elite rapeseed lines, SI-1300 and Eagle, in this study. Twenty-eight QTLs were detected for the four yield traits, with only two of them detected simultaneously in the Wuhan and Jingmen environments. Additive, partial dominance, dominance, and overdominance effects were all identified for the investigated traits. Dominance (including partial dominance) was shown by 55% of the QTLs, which suggests that dominance is a major genetic basis of heterosis in rapeseed. At the P ?? 0.01 level with 1000 random permutations, 108 and 104 significant digenic interactions were detected in Wuhan and Jingmen, respectively, for the four yield-related traits using all possible locus pairs of molecular markers. Digenic interactions, including additive by additive, additive by dominance, and dominance by dominance, were frequent and widespread in this population. In most cases (78.3%), the interactions occurred among marker loci for which significant effects were not detected by single-locus analysis. Some QTLs (57.1%) detected by single-locus analysis were involved in epistatic interactions. It was concluded that epistasis, along with dominance (including partial dominance), is responsible for the expression of heterosis in rapeseed.     

Genetic dissection of yield-related traits in a recombinant inbred line population created using a key breeding parent in China’s wheat breeding

Understanding the genetics underlying yield formation of wheat is important for increasing wheat yield potential in breeding programs. Nanda2419 was a widely used cultivar for wheat production and breeding in China. In this study, we evaluated yield components and a few yield-related traits of a recombinant inbred line (RIL) population created by crossing Nanda2419 with the indigenous cultivar Wangshuibai in three to four trials at different geographical locations. Negative and positive correlations were found among some of these evaluated traits. Five traits had over 50 % trial-wide broad sense heritability. Using a framework marker map of the genome constructed with this population, quantitative trait loci (QTL) were identified for all traits, and epistatic loci were identified for seven of them. Our results confirmed some of the previously reported QTLs in wheat and identified several new ones, including QSn.nau-6D for effective tillers, QGn.nau-4B.2 for kernel number, QGw.nau-4D for kernel weight, QPh.nau-4B.2 and QPh.nau-4A for plant height, and QFlw.nau-5A.1 for flag leaf width. In the investigated population, Nanda2419 contributed all QTLs associated with higher kernel weight, higher leaf chlorophyll content, and a major QTL associated with wider flag leaf. Seven chromosome regions were related to more than one trait. Four QTL clusters contributed positively to breeding goal-based trait improvement through the Nanda2419 alleles and were detected in trials set in different ecological regions. The findings of this study are relevant to the molecular improvement of wheat yield and to the goal of screening cultivars for better breeding parents.     

Molecular mapping in tropical maize (Zea mays L.) using microsatellite markers. 2. Quantitative trait loci (QTL) for grain yield, plant height, ear height and grain moisture

A previous genetic map containing 117 microsatellite loci and 400 F(2) plants was used for quantitative trait loci (QTL) mapping in tropical maize. QTL were characterized in a population of 400 F(2:3) lines, derived from selfing the F(2) plants, and were evaluated with two replications in five environments. QTL determinations were made from the mean of these five environments. Grain yield (GY), plant height (PH), ear height (EH) and grain moisture (GM) were measured. Variance components for genotypes (G), environments (E) and GxE interaction were highly significant for all traits. Heritability was 0.69 for GY, 0.66 for PH, 0.67 for EH and 0.23 for GM. Using composite interval mapping (CIM), a total of 13 distinct QTLs were identified: four for GY, four for PH and five for EH. No QTL was detected for GM. The QTL explained 32.73 % of the phenotypic variance of GY, 24.76 % of PH and 20.91 % of EH. The 13 QTLs displayed mostly partial dominance or overdominance gene action and mapped to chromosomes 1, 2, 7, 8 and 9. Most QTL alleles conferring high values for the traits came from line L-14-4B. Mapping analysis identified genomic regions associated with two or more traits in a manner that was consistent with correlation among traits, supporting either pleiotropy or tight linkage among QTL. The low number of QTLs found, can be due to the great variation that exists among tropical environments.     

Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum

The identification of quantitative trait loci (QTLs) affecting agronomically important traits enable to understand their underlying genetic mechanisms and genetic basis of their complex interactions. The aim of the present study was to detect QTLs for 12 agronomic traits related to staygreen, plant early development, grain yield and its components, and some growth characters by analyzing replicated phenotypic datasets from three crop seasons, using the population of 168 F₇ RILs of the cross 296B × IS18551. In addition, we report mapping of a subset of genic-microsatellite markers. A linkage map was constructed with 152 marker loci comprising 149 microsatellites (100 genomic- and 49 genic-microsatellites) and three morphological markers. QTL analysis was performed by using MQM approach. Forty-nine QTLs were detected, across environments or in individual environments, with 1–9 QTLs for each trait. Individual QTL accounted for 5.2–50.4% of phenotypic variance. Several genomic regions affected multiple traits, suggesting the phenomenon of pleiotropy or tight linkage. Stable QTLs were identified for studied traits across different environments, and genetic backgrounds by comparing the QTLs in the study with previously reported QTLs in sorghum. Of the 49 mapped genic-markers, 18 were detected associating either closely or exactly as the QTL positions of agronomic traits. EST marker Dsenhsbm19, coding for a key regulator (EIL-1) of ethylene biosynthesis, was identified co-located with the QTLs for plant early development and staygreen trait, a probable candidate gene for these traits. Similarly, such exact co-locations between EST markers and QTLs were observed in four other instances. Collectively, the QTLs/markers identified in the study are likely candidates for improving the sorghum performance through MAS and map-based gene isolations.     

The effect of semi-dwarf genes on root system size in field-grown barley

Root system size (RSS) was measured in 12 diverse barley genotypes and 157 double-haploid lines (DHs), using electric capacitance. The parents of the DHs, Derkado and B83-12/21/5, carry different semi-dwarfing genes, sdw1 and ari-e.GP, respectively. Estimates of RSS were taken in the field thrice during plant development: stem elongation (RSS1), heading (RSS2) and grain filling (RSS3). The 12 barley genotypes were assessed over 3 years and at two or three locations each year; the DH mapping population was assessed at two locations in 2002. Among the 12 barley genotypes, those with the semi-dwarf genes had greater RSS values in all 3 years (28.9, 24.6 and 15.0% in years 1, 2 and 3, respectively) compared to non-semi-dwarf controls. The DH population showed transgressive segregation on both sides of the parent means, indicating polygenic control of RSS. Quantitative trait loci (QTLs) for RSS were found on five of the seven chromosomes: 1H, 3H, 4H, 5H and 7H and these were compared with previously mapped agronomic traits. The TotalRSS QTL on 3H was associated with sdw1 and QTLs for height, plant yield and plant weight. The RSS3 QTL on 5H was associated with ari-e.GP and QTLs for height, plant yield, plant weight, harvest index and tiller number. The RSS3 QTL on 7H was also associated with a TotalRSS QTL and QTLs for plant weight and harvest index. Other RSS QTLs were not associated with any other trait studied. RSS is considered to be a polygenic trait linked to important traits, in particular to yield. The study highlights the effects of semi-dwarfing genes and discusses the potential for breeding for root traits.     

A genetic analysis of seed and berry weight in grapevine.

Fruit size and seedlessness are highly relevant traits in many fruit crop species, and both are primary targets of breeding programs for table grapes. In this work we performed a quantitative genetic analysis of size and seedlessness in an F1 segregating population derived from the cross between a classical seeded (Vitis vinifera L. 'Dominga') and a newly bred seedless ('Autumn Seedless') cultivar. Fruit size was scored as berry weight (BW), and for seedlessness we considered both seed fresh weight (SFW) and the number of seeds and seed traces (SN) per berry. Quantitative trait loci (QTL) analysis of BW detected 3 QTLs affecting this trait and accounting for up to 67% of the total phenotypic variance. QTL analysis for seedlessness detected 3 QTLs affecting SN (explaining up to 35% of total variance) and 6 affecting SFW (explaining up to 90% of total variance). Among them, a major effect QTL explained almost half of the phenotypic variation for SFW. Comparative analysis of QTLs for these traits reduced the number of grapevine genomic regions involved, one of them being a major effect QTL for seedlessness. Association analyses showed that microsatellite locus VMC7F2, closely linked to this QTL, is a useful marker for selection of seedlessnes.     

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.     

Identification of main effect and epistatic quantitative trait loci for morphological and yield-related traits in peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

An effort was made in the present study to identify the main effect and epistatic quantitative trait locus (QTL) for the morphological and yield-related traits in peanut. A recombinant inbred line (RIL) population derived from TAG 24 × GPBD 4 was phenotyped in seven environments at two locations. QTL analysis with available genetic map identified 62 main-effect QTLs (M-QTLs) for ten morphological and yield-related traits with the phenotypic variance explained (PVE) of 3.84–15.06%. Six major QTLs (PVE >?10%) were detected for PLHT, PPP, YPP, and SLNG. Stable M-QTLs appearing in at least two environments were detected for PLHT, LLN, YPP, YKGH, and HSW. Five M-QTLs governed two traits each, and 16 genomic regions showed co-localization of two to four M-QTLs. Intriguingly, a major QTL reported to be linked to rust resistance showed pleiotropic effect for yield-attributing traits like YPP (15.06%, PVE) and SLNG (13.40%, PVE). Of the 24 epistatic interactions identified across the traits, five interactions involved six M-QTLs. Three interactions were additive × additive and remaining two involved QTL × environment (QE) interactions. Only one major M-QTL governing PLHT showed epistatic interaction. Overall, this study identified the major M-QTLs for the important productivity traits and also described the lack of epistatic interactions for majority of them so that they can be conveniently employed in peanut breeding.