Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

The genetic architecture determinants of yield traits in peanut (Arachis hypogaea L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loci, covering a total of 1557.48 cM with an average distance of 2.56 cM between adjacent markers. The present map exhibited good collinearity with the physical map of diploid species of Arachis. Ninety-two repeatable QTLs were identified for 11 traits including height of main stem, total branching number, and nine pod- and seed-related traits. Of the 92 QTLs, 15 QTLs were expressed across three environments and 65 QTLs were newly identified. Twelve QTLs for the height of main stem and the pod- and seed-related traits explaining more than 10 % of phenotypic variation showed a great potential for marker-assisted selection in improving these traits. 相似文献   

Extreme QTL mapping of germination speed in Arabidopsis thaliana

Seed germination is a key life history transition for annual plants and partly determines lifetime performance and fitness. Germination speed, the elapsed time for a nondormant seed to germinate, is a poorly understood trait important for plants’ competitiveness and fitness in fluctuating environments. Germination speed varied by 30% among 18 Arabidopsis thaliana populations measured, and exhibited weak negative correlation with flowering time and seed weight, with significant genotype effect (P < 0.005). To dissect the genetic architecture of germination speed, we developed the extreme QTL (X‐QTL) mapping method in A. thaliana. The method has been shown in yeast to increase QTL mapping power by integrating selective screening and bulk‐segregant analysis in a very large mapping population. By pooled genotyping of top 5% of rapid germinants from ~100 000 F₃ individuals, three X‐QTL regions were identified on chromosomes 1, 3 and 4. All regions were confirmed as QTL regions by sequencing 192 rapid germinants from an independent F₃ selection experiment. Positional overlaps were found between X‐QTLs and previously identified seed, life history and fitness QTLs. Our method provides a rapid mapping platform in A. thaliana with potentially greater power. One can also relate identified X‐QTLs to the A. thaliana physical map, facilitating candidate gene identification.     

Identification of QTLs Associated with Oil Content in a High-Oil Brassica napus Cultivar and Construction of a High-Density Consensus Map for QTLs Comparison in B. napus

Increasing seed oil content is one of the most important goals in breeding of rapeseed (B. napus L.). To dissect the genetic basis of oil content in B. napus, a large and new double haploid (DH) population containing 348 lines was obtained from a cross between ‘KenC-8’ and ‘N53-2’, two varieties with >10% difference in seed oil content, and this population was named the KN DH population. A genetic linkage map consisting of 403 markers was constructed, which covered a total length of 1783.9 cM with an average marker interval of 4.4 cM. The KN DH population was phenotyped in eight natural environments and subjected to quantitative trait loci (QTL) analysis for oil content. A total of 63 identified QTLs explaining 2.64–17.88% of the phenotypic variation were identified, and these QTLs were further integrated into 24 consensus QTLs located on 11 chromosomes using meta-analysis. A high-density consensus map with 1335 marker loci was constructed by combining the KN DH map with seven other published maps based on the common markers. Of the 24 consensus QTLs in the KN DH population, 14 were new QTLs including five new QTLs in A genome and nine in C genome. The analysis revealed that a larger population with significant differences in oil content gave a higher power detecting new QTLs for oil content, and the construction of the consensus map provided a new clue for comparing the QTLs detected in different populations. These findings enriched our knowledge of QTLs for oil content and should be a potential in marker-assisted breeding of B. napus.     

Quantitative trait loci affecting amylose,amylopectin and starch content in maize recombinant inbred lines

The loci explaining the variability of quantitative traits related to starch content and composition (amylose, amylopectin and water soluble fraction) were searched for in maize kernels. Multifactorial genetic methods were used to detect and locate QTLs (quantitative trait loci) on a genetic map consisting mainly of RFLP markers for genes with known function. The genetic material was recombinant inbred lines originating from parents differing in starch structure (dent vs. flint). Kernels were harvested from field grown plants for two successive years and under two pollination systems. Main effect and epistasis QTLs were detected using two methods, composite interval mapping (MQTL) and ANOVA. Despite large year-to-year differences, physiologically meaningful co-locations were observed between trait QTLs. Moreover, the number of expressed sequences on our map allowed the search for co-locations between QTLs and genes involved in carbohydrate metabolism. The main co-location was between an amylose QTL and Shrunken 2 (SH2) locus, on chromosome 3 (SH2 encoding for the large subunit of ADPglucose pyrophosphorylase). The importance of this locus as a candidate gene for a starch QTL is in agreement with previous studies based either on QTL co-locations or on revertant analysis. Other co-locations were observed between amylose and amylopectin QTLs and the two loci of IVR1 invertase genes on chromosomes 2 and 10. Further comparison with previously detected QTLs for carbohydrate metabolism in maize leaves showed consistent co-location in map regions devoid of candidate genes, such as near chromosome 1S telomere. The possible contribution of regulatory genes in this region is discussed.     

Targeted linkage map densification to improve cell wall related QTL detection and interpretation in maize

Several QTLs for cell wall degradability and lignin content were previously detected in the F288 × F271 maize RIL progeny, including a set of major QTLs located in bin 6.06. Unexpectedly, allelic sequencing of genes located around the bin 6.06 QTL positions revealed a monomorphous region, suggesting that these QTLs were likely “ghost” QTLs. Refining the positions of all QTLs detected in this population was thus considered, based on a linkage map densification in most important QTL regions, and in several large still unmarked regions. Re-analysis of data with an improved genetic map (173 markers instead of 108) showed that ghost QTLs located in bin 6.06 were then fractionated over two QTL positions located upstream and downstream of the monomorphic region. The area located upstream of bin 6.06 position carried the major QTLs, which explained from 37 to 59 % of the phenotypic variation for per se values and extended on only 6 cM, corresponding to a physical distance of 2.2 Mbp. Among the 92 genes present in the corresponding area of the B73 maize reference genome, nine could putatively be considered as involved in the formation of the secondary cell wall [bHLH, FKBP, laccase, fasciclin, zinc finger C2H2-type and C3HC4-type (two genes), NF-YB, and WRKY]. In addition, based on the currently improved genetic map, eight QTLs were detected in bin 4.09, while only one QTL was highlighted in the initial investigation. Moreover, significant epistatic interaction effects were shown for all traits between these QTLs located in bin 4.09 and the major QTLs located in bin 6.05. Three genes related to secondary cell wall assembly (ZmMYB42, COV1-like, PAL-like) underlay QTL support intervals in this newly identified bin 4.09 region. The current investigations, even if they were based only on one RIL progeny, illustrated the interest of a targeted marker mapping on a genetic map to improve QTL position.     

Meta-analysis of Yield QTLs Derived from Inter-specific Crosses of Rice Reveals Consensus Regions and Candidate Genes

Several reports on mapping and introgression of quantitative trait loci (QTLs) for yield and related traits from wild species showed their importance in yield improvement. The aim of this study was to locate common major effect, consistent and precise yield QTLs across the wild species of rice by applying genome-wide QTL meta-analysis for their use in marker-aided selection (MAS) and candidate gene identification. Seventy-six yield QTLs reported in 11 studies involving inter-specific crosses were projected on a consensus map consisting of 699 markers. The integration of 11 maps resulted in a consensuses map of 1,676 cM. The number of markers ranged from 32 on chromosome 12 to 96 on chromosome 1. The order of markers between consensus map and original map was generally consistent. Meta-analysis of 68 yield QTLs resulted in 23 independent meta-QTLs on ten different chromosomes. Eight meta-QTLs were less than 1.3 Mb. The smallest confidence interval of a meta-QTL (MQTL) was 179.6 kb. Four MQTLs were around 500 kb and two of these correspond to a reasonably small genetic distance 4.6 and 5.2 cM, respectively, and suitable for MAS. MQTL8.2 was 326-kb long with a 35-cM interval indicating it was in a recombination hot spot and suitable for fine mapping. Our results demonstrate the narrowing down of initial yield QTLs by Meta-analysis and thus enabling short listing of QTLs worthy of MAS or fine mapping. The candidate genes shortlisted are useful in validating their function either by loss of function or over expression.     

Mapping of QTLs for morpho-agronomic and seed quality traits in a RIL population of common bean (Phaseolus vulgaris L.)

The objective of this research was to determine the quantitative trait loci (QTLs) controlling phenological traits (days to flowering, days to end of flowering, days to harvest as green pod, and days to maturity), seed size traits (seed length, seed height, seed width, and seed weight), and seed quality traits (water absorption, and coat proportion), in common bean. A population of 104 F₇ recombinant inbred lines (RILs) derived from an inter-gene pool cross between Xana, and Cornell 49242, was used to develop a genetic linkage map including 175 AFLPs, 27 microsatellites, 30 SCARs, 33 ISSRs, 12 RAPDs, 13 loci codifying for seed proteins, and the four genes Fin,fin (growth habit); Asp,asp (seed coat shininess); P,p (seed color); and I,i (resistance to bean common mosaic virus). The map has a total length of 1,042 cM distributed across 11 linkage groups aligned to those of the core linkage map of bean using common molecular markers as anchor points. The QTL analyses were carried out over three environments using the mean environment data with composite interval mapping. Thirty-one QTLs for ten traits were found to be significant in at least one environment and in the mean environment data, the number of significant QTLs identified per trait ranging from two to five. Twenty-seven of these QTLs mapped forming clusters in eight different chromosomal regions. The rationale for this clustered mapping and the possible relationship between some QTLs for phenological traits and the genes Fin and I are discussed.     

Mixed linear model approach for mapping quantitative trait loci underlying crop seed traits

The crop seed is a complex organ that may be composed of the diploid embryo, the triploid endosperm and the diploid maternal tissues. According to the genetic features of seed characters, two genetic models for mapping quantitative trait loci (QTLs) of crop seed traits are proposed, with inclusion of maternal effects, embryo or endosperm effects of QTL, environmental effects and QTL-by-environment (QE) interactions. The mapping population can be generated either from double back-cross of immortalized F₂ (IF₂) to the two parents, from random-cross of IF₂ or from selfing of IF₂ population. Candidate marker intervals potentially harboring QTLs are first selected through one-dimensional scanning across the whole genome. The selected candidate marker intervals are then included in the model as cofactors to control background genetic effects on the putative QTL(s). Finally, a QTL full model is constructed and model selection is conducted to eliminate false positive QTLs. The genetic main effects of QTLs, QE interaction effects and the corresponding P-values are computed by Markov chain Monte Carlo algorithm for Gaussian mixed linear model via Gibbs sampling. Monte Carlo simulations were performed to investigate the reliability and efficiency of the proposed method. The simulation results showed that the proposed method had higher power to accurately detect simulated QTLs and properly estimated effect of these QTLs. To demonstrate the usefulness, the proposed method was used to identify the QTLs underlying fiber percentage in an upland cotton IF₂ population. A computer software, QTLNetwork-Seed, was developed for QTL analysis of seed traits.     

Genome-wide SNP identification for the construction of a high-resolution genetic map of Japanese flounder (Paralichthys olivaceus): applications to QTL mapping of Vibrio anguillarum disease resistance and comparative genomic analysis

High-resolution genetic maps are essential for fine mapping of complex traits, genome assembly, and comparative genomic analysis. Single-nucleotide polymorphisms (SNPs) are the primary molecular markers used for genetic map construction. In this study, we identified 13,362 SNPs evenly distributed across the Japanese flounder (Paralichthys olivaceus) genome. Of these SNPs, 12,712 high-confidence SNPs were subjected to high-throughput genotyping and assigned to 24 consensus linkage groups (LGs). The total length of the genetic linkage map was 3,497.29 cM with an average distance of 0.47 cM between loci, thereby representing the densest genetic map currently reported for Japanese flounder. Nine positive quantitative trait loci (QTLs) forming two main clusters for Vibrio anguillarum disease resistance were detected. All QTLs could explain 5.1–8.38% of the total phenotypic variation. Synteny analysis of the QTL regions on the genome assembly revealed 12 immune-related genes, among them 4 genes strongly associated with V. anguillarum disease resistance. In addition, 246 genome assembly scaffolds with an average size of 21.79 Mb were anchored onto the LGs; these scaffolds, comprising 522.99 Mb, represented 95.78% of assembled genomic sequences. The mapped assembly scaffolds in Japanese flounder were used for genome synteny analyses against zebrafish (Danio rerio) and medaka (Oryzias latipes). Flounder and medaka were found to possess almost one-to-one synteny, whereas flounder and zebrafish exhibited a multi-syntenic correspondence. The newly developed high-resolution genetic map, which will facilitate QTL mapping, scaffold assembly, and genome synteny analysis of Japanese flounder, marks a milestone in the ongoing genome project for this species.     

Deploying QTL-seq for rapid delineation of a potential candidate gene underlying major trait-associated QTL in chickpea

A rapid high-resolution genome-wide strategy for molecular mapping of major QTL(s)/gene(s) regulating important agronomic traits is vital for in-depth dissection of complex quantitative traits and genetic enhancement in chickpea. The present study for the first time employed a NGS-based whole-genome QTL-seq strategy to identify one major genomic region harbouring a robust 100-seed weight QTL using an intra-specific 221 chickpea mapping population (desi cv. ICC 7184 × desi cv. ICC 15061). The QTL-seq-derived major SW QTL (CaqSW1.1) was further validated by single-nucleotide polymorphism (SNP) and simple sequence repeat (SSR) marker-based traditional QTL mapping (47.6% R² at higher LOD >19). This reflects the reliability and efficacy of QTL-seq as a strategy for rapid genome-wide scanning and fine mapping of major trait regulatory QTLs in chickpea. The use of QTL-seq and classical QTL mapping in combination narrowed down the 1.37 Mb (comprising 177 genes) major SW QTL (CaqSW1.1) region into a 35 kb genomic interval on desi chickpea chromosome 1 containing six genes. One coding SNP (G/A)-carrying constitutive photomorphogenic9 (COP9) signalosome complex subunit 8 (CSN8) gene of these exhibited seed-specific expression, including pronounced differential up-/down-regulation in low and high seed weight mapping parents and homozygous individuals during seed development. The coding SNP mined in this potential seed weight-governing candidate CSN8 gene was found to be present exclusively in all cultivated species/genotypes, but not in any wild species/genotypes of primary, secondary and tertiary gene pools. This indicates the effect of strong artificial and/or natural selection pressure on target SW locus during chickpea domestication. The proposed QTL-seq-driven integrated genome-wide strategy has potential to delineate major candidate gene(s) harbouring a robust trait regulatory QTL rapidly with optimal use of resources. This will further assist us to extrapolate the molecular mechanism underlying complex quantitative traits at a genome-wide scale leading to fast-paced marker-assisted genetic improvement in diverse crop plants, including chickpea.     

Genetic mapping of biomass yield in three interconnected Miscanthus populations

Improving biomass yield is a major goal of Miscanthus breeding. We conducted a study on one interspecific Miscanthus sinensis × Miscanthus sacchariflorus F₁ population and two intraspecific M. sinensis F₁ populations, each of which shared a common parent. A field trial was established at Urbana, IL during spring 2011, and phenotypic data were collected in 2012 and 2013 for fourteen yield traits. Six high‐density parental genetic maps, as well as a consensus genetic map integrating M. sinensis and M. sacchariflorus, were developed via the pseudotestcross strategy for noninbred parents with ≥1214 single‐nucleotide polymorphism markers generated from restriction site‐associated DNA sequencing. We confirmed for the first time a whole‐genome duplication in M. sacchariflorus relative to Sorghum bicolor, similar to that observed previously for M. sinensis. Four quantitative trait locus (QTL) analysis methods for detecting marker‐trait associations were compared: (1) individual parental map composite interval mapping analysis, (2) individual parental map stepwise analysis, (3) consensus map single‐population stepwise analysis and (4) consensus map joint‐population stepwise analysis. These four methods detected 288, 264, 133 and 109 total QTLs, which resolved into 157, 136, 106 and 86 meta‐QTLs based on QTL congruency, respectively, including a set of 59 meta‐QTLs common to all four analysis methods. Composite interval mapping and stepwise analysis co‐identified 118 meta‐QTLs across six parental maps, suggesting high reliability of stepwise regression in QTL detection. Joint‐population stepwise analysis yielded the highest resolution of QTLs compared to the other three methods across all meta‐QTLs. Strong, frequently advantageous transgressive segregation in the three populations indicated a promising future for breeding new higher‐yielding cultivars of Miscanthus.     

Identification of quantitative trait loci for resistance to Verticillium wilt and yield parameters in hop (Humulus lupulus L.)

Verticillium wilt (VW) can cause substantial yield loss in hop particularly with the outbreaks of the lethal strain of Verticillium albo-atrum. To elucidate genetic control of VW resistance in hop, an F₁ mapping population derived from a cross of cultivar Wye Target, with the predicted genetic basis of resistance, and susceptible male breeding line BL2/1 was developed to assess wilting symptoms and to perform QTL mapping. The genetic linkage map, constructed with 203 markers of various types using a pseudo-testcross strategy, formed ten major linkage groups (LG) of the maternal and paternal maps, covering 552.98 and 441.1 cM, respectively. A significant QTL for VW resistance was detected at LOD 7 on a single chromosomal region on LG03 of both parental maps, accounting for 24.2–26.0 % of the phenotypic variance. QTL analysis for alpha-acid content and yield parameters was also performed on this map. QTLs for these traits were also detected and confirmed our previously detected QTLs in a different pedigree and environment. The work provides the basis for exploration of QTL flanking markers for possible use in marker-assisted selection.     

Meta-analysis of quantitative trait loci for grain yield and component traits under reproductive-stage drought stress in an upland rice population

A recombinant inbred population developed from a cross between high-yielding lowland rice (Oryza sativa L.) subspecies indica cv. IR64 and upland tropical rice subspecies japonica cv. Cabacu was used to identify quantitative trait loci (QTLs) for grain yield (GY) and component traits under reproductive-stage drought stress. One hundred fifty-four lines were grown in field trials in Indonesia under aerobic conditions by giving surface irrigation to field capacity every 4 days. Water stress was imposed for a period of 15 days during pre-flowering by withholding irrigation at 65 days after seeding. Leaf rolling was scored at the end of the stress period and eight agronomic traits were evaluated after recovery. The population was also evaluated for root pulling force, and a total of 201 single nucleotide polymorphism markers were used to construct the molecular genetic linkage map and QTL mapping. A QTL for GY under drought stress was identified in a region close to the sd1 locus on chromosome 1. QTL meta-analysis across diverse populations showed that this QTL was conserved across genetic backgrounds and co-localized with QTLs for leaf rolling and osmotic adjustment (OA). A QTL for percent seed set and grains per panicle under drought stress was identified on chromosome 8 in the same region as a QTL for OA previously identified in three different populations.     

Constructing a new integrated genetic linkage map and mapping quantitative trait loci for vegetative mycelium growth rate in Lentinula edodes

The most saturated linkage map for Lentinula edodes to date was constructed based on a monokaryotic population of 146 single spore isolates (SSIs) using sequence-related amplified polymorphism (SRAP), target region amplification polymorphism (TRAP), insertion–deletion (InDel) markers, and the mating-type loci. Five hundred and twenty-four markers were located on 13 linkage groups (LGs). The map spanned a total length of 1006.1 cM, with an average marker spacing of 2.0 cM. Quantitative trait loci (QTLs) mapping was utilized to uncover the loci regulating and controlling the vegetative mycelium growth rate on various synthetic media, and complex medium for commercial cultivation of L. edodes. Two and 13 putative QTLs, identified respectively in the monokaryotic population and two testcross dikaryotic populations, were mapped on seven different LGs. Several vegetative mycelium growth rate-related QTLs uncovered here were clustered on LG4 (Qmgr1, Qdgr1, Qdgr2 and Qdgr9) and LG6 (Qdgr3, Qdgr4 and Qdgr5), implying the presence of main genomic areas responsible for growth rate regulation and control. The QTL hotspot region on LG4 was found to be in close proximity to the region containing the mating-type A (MAT-A) locus. Moreover, Qdgr2 on LG4 was detected on different media, contributing 8.07 %–23.71 % of the phenotypic variation. The present study provides essential information for QTL mapping and marker-assisted selection (MAS) in L. edodes.     

High-Density Genetic Linkage Map Construction and QTL Mapping of Grain Shape and Size in the Wheat Population Yanda1817 × Beinong6

High-density genetic linkage maps are necessary for precisely mapping quantitative trait loci (QTLs) controlling grain shape and size in wheat. By applying the Infinium iSelect 9K SNP assay, we have constructed a high-density genetic linkage map with 269 F ₈ recombinant inbred lines (RILs) developed between a Chinese cornerstone wheat breeding parental line Yanda1817 and a high-yielding line Beinong6. The map contains 2431 SNPs and 128 SSR & EST-SSR markers in a total coverage of 3213.2 cM with an average interval of 1.26 cM per marker. Eighty-eight QTLs for thousand-grain weight (TGW), grain length (GL), grain width (GW) and grain thickness (GT) were detected in nine ecological environments (Beijing, Shijiazhuang and Kaifeng) during five years between 2010–2014 by inclusive composite interval mapping (ICIM) (LOD≥2.5). Among which, 17 QTLs for TGW were mapped on chromosomes 1A, 1B, 2A, 2B, 3A, 3B, 3D, 4A, 4D, 5A, 5B and 6B with phenotypic variations ranging from 2.62% to 12.08%. Four stable QTLs for TGW could be detected in five and seven environments, respectively. Thirty-two QTLs for GL were mapped on chromosomes 1B, 1D, 2A, 2B, 2D, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6B, 7A and 7B, with phenotypic variations ranging from 2.62% to 44.39%. QGl.cau-2A.2 can be detected in all the environments with the largest phenotypic variations, indicating that it is a major and stable QTL. For GW, 12 QTLs were identified with phenotypic variations range from 3.69% to 12.30%. We found 27 QTLs for GT with phenotypic variations ranged from 2.55% to 36.42%. In particular, QTL QGt.cau-5A.1 with phenotypic variations of 6.82–23.59% was detected in all the nine environments. Moreover, pleiotropic effects were detected for several QTL loci responsible for grain shape and size that could serve as target regions for fine mapping and marker assisted selection in wheat breeding programs.     

Editor's choice: High-Resolution Linkage and Quantitative Trait Locus Mapping Aided by Genome Survey Sequencing: Building Up An Integrative Genomic Framework for a Bivalve Mollusc

Genetic linkage maps are indispensable tools in genetic and genomic studies. Recent development of genotyping-by-sequencing (GBS) methods holds great promise for constructing high-resolution linkage maps in organisms lacking extensive genomic resources. In the present study, linkage mapping was conducted for a bivalve mollusc (Chlamys farreri) using a newly developed GBS method—2b-restriction site-associated DNA (2b-RAD). Genome survey sequencing was performed to generate a preliminary reference genome that was utilized to facilitate linkage and quantitative trait locus (QTL) mapping in C. farreri. A high-resolution linkage map was constructed with a marker density (3806) that has, to our knowledge, never been achieved in any other molluscs. The linkage map covered nearly the whole genome (99.5%) with a resolution of 0.41 cM. QTL mapping and association analysis congruously revealed two growth-related QTLs and one potential sex-determination region. An important candidate QTL gene named PROP1, which functions in the regulation of growth hormone production in vertebrates, was identified from the growth-related QTL region detected on the linkage group LG3. We demonstrate that this linkage map can serve as an important platform for improving genome assembly and unifying multiple genomic resources. Our study, therefore, exemplifies how to build up an integrative genomic framework in a non-model organism.     

Analysis of an intraspecific RIL population uncovers genomic segments harbouring multiple QTL for seed relevant traits in lentil (<Emphasis Type="Italic">Lens culinaris</Emphasis> L.)

Improving seed related traits remains key objective in lentil breeding. In recent years, genomic resources have shown great promise to accelerate crop improvement. However, limited genomic resources in lentil greatly restrict the use of genomics assisted breeding. The present investigation aims to build an intraspecific genetic linkage map and identify the QTL associated with important seed relevant traits using 94 recombinant inbreds (WA 8649090 × Precoz). A total of 288 polymorphic DNA markers including simple sequence repeat (SSR), inter simple sequence repeat (ISSR) and random amplified polymorphic DNA (RAPD) were assayed on mapping population. The resultant genetic linkage map comprised 220 loci spanning 604.2 cM of the lentil genome, with average inter-marker distance of 2.74 cM. QTL mapping in this RIL population uncovered a total of 18 QTL encompassing nine major and nine minor QTL. All major QTL were detected for seed related traits viz., seed diameter (SD), seed thickness (ST), seed weight (SW) and seed plumpness (SP) across two locations. A considerable proportion of the phenotypic variation (PV) was accounted to these QTL. For instance, one major QTL on LG5 controlling SW (QTL 15) explained 50% PV in one location, while the same QTL accounted for 34.18% PV in other location. Importantly, the genomic region containing multiple QTL for different seed traits was mapped to a 17-cM region on LG5. The genomic region harbouring QTL for multiple traits opens up exciting opportunities for genomics assisted improvement of lentil.     

Influence of dent corn genetic backgrounds on QTL detection for plant-height traits and their relationships in high-oil maize

QTL mapping for plant-height traits has not been hitherto reported in high-oil maize. A high-oil maize inbred ‘GY220’ was crossed with two dent maize inbreds (‘8984’ and ‘8622’) to generate two connected F_2:3 populations. Four plant-height traits were evaluated in 284 and 265 F_2:3 families. Single-trait QTL mapping and multiple-trait joint QTL mapping was used to detect QTLs for the traits and the genetic relationship between plant height (PH) and two other plant-height traits. A total of 28 QTLs and 12 pairs of digenic interactions among detected QTLs for four traits were detected in the two F_2:3 families. Only one marker was shared between the two populations. Joint analysis of PH with ear height (EH) and PH with top height (TH) detected 32 additional QTLs. Our results showed that QTL detection for PH was dependent on the genetic background of dent corn inbreds. Multiple-trait joint QTL analysis could increase the number of detected QTLs.     

Dissecting Quantitative Trait Loci for Boron Efficiency across Multiple Environments in Brassica napus

High yield is the most important goal in crop breeding, and boron (B) is an essential micronutrient for plants. However, B deficiency, leading to yield decreases, is an agricultural problem worldwide. Brassica napus is one of the most sensitive crops to B deficiency, and considerable genotypic variation exists among different cultivars in response to B deficiency. To dissect the genetic basis of tolerance to B deficiency in B. napus, we carried out QTL analysis for seed yield and yield-related traits under low and normal B conditions using the double haploid population (TNDH) by two-year and the BQDH population by three-year field trials. In total, 80 putative QTLs and 42 epistatic interactions for seed yield, plant height, branch number, pod number, seed number, seed weight and B efficiency coefficient (BEC) were identified under low and normal B conditions, singly explaining 4.15–23.16% and 0.53–14.38% of the phenotypic variation. An additive effect of putative QTLs was a more important controlling factor than the additive-additive effect of epistatic interactions. Four QTL-by-environment interactions and 7 interactions between epistatic interactions and the environment contributed to 1.27–4.95% and 1.17–3.68% of the phenotypic variation, respectively. The chromosome region on A2 of SYLB-A2 for seed yield under low B condition and BEC-A2 for BEC in the two populations was equivalent to the region of a reported major QTL, BE1. The B. napus homologous genes of Bra020592 and Bra020595 mapped to the A2 region and were speculated to be candidate genes for B efficiency. These findings reveal the complex genetic basis of B efficiency in B. napus. They provide a basis for the fine mapping and cloning of the B efficiency genes and for breeding B-efficient cultivars by marker-assisted selection (MAS).