Comparative Polygenic Analysis of Maximal Ethanol Accumulation Capacity and Tolerance to High Ethanol Levels of Cell Proliferation in Yeast

The yeast Saccharomyces cerevisiae is able to accumulate ≥17% ethanol (v/v) by fermentation in the absence of cell proliferation. The genetic basis of this unique capacity is unknown. Up to now, all research has focused on tolerance of yeast cell proliferation to high ethanol levels. Comparison of maximal ethanol accumulation capacity and ethanol tolerance of cell proliferation in 68 yeast strains showed a poor correlation, but higher ethanol tolerance of cell proliferation clearly increased the likelihood of superior maximal ethanol accumulation capacity. We have applied pooled-segregant whole-genome sequence analysis to identify the polygenic basis of these two complex traits using segregants from a cross of a haploid derivative of the sake strain CBS1585 and the lab strain BY. From a total of 301 segregants, 22 superior segregants accumulating ≥17% ethanol in small-scale fermentations and 32 superior segregants growing in the presence of 18% ethanol, were separately pooled and sequenced. Plotting SNP variant frequency against chromosomal position revealed eleven and eight Quantitative Trait Loci (QTLs) for the two traits, respectively, and showed that the genetic basis of the two traits is partially different. Fine-mapping and Reciprocal Hemizygosity Analysis identified ADE1, URA3, and KIN3, encoding a protein kinase involved in DNA damage repair, as specific causative genes for maximal ethanol accumulation capacity. These genes, as well as the previously identified MKT1 gene, were not linked in this genetic background to tolerance of cell proliferation to high ethanol levels. The superior KIN3 allele contained two SNPs, which are absent in all yeast strains sequenced up to now. This work provides the first insight in the genetic basis of maximal ethanol accumulation capacity in yeast and reveals for the first time the importance of DNA damage repair in yeast ethanol tolerance.     

Quantitative trait analysis of yeast biodiversity yields novel gene tools for metabolic engineering

Engineering of metabolic pathways by genetic modification has been restricted largely to enzyme-encoding structural genes. The product yield of such pathways is a quantitative genetic trait. Out of 52 Saccharomyces cerevisiae strains phenotyped in small-scale fermentations, we identified strain CBS6412 as having unusually low glycerol production and higher ethanol yield as compared to an industrial reference strain. We mapped the QTLs underlying this quantitative trait with pooled-segregant whole-genome sequencing using 20 superior segregants selected from a total of 257. Plots of SNP variant frequency against SNP chromosomal position revealed one major and one minor locus. Downscaling of the major locus and reciprocal hemizygosity analysis identified an allele of SSK1, ssk1^{E330N…K356N}, expressing a truncated and partially mistranslated protein, as causative gene. The diploid CBS6412 parent was homozygous for ssk1^{E330N…K356N}. This allele affected growth and volumetric productivity less than the gene deletion. Introduction of the ssk1^{E330N…K356N} allele in the industrial reference strain resulted in stronger reduction of the glycerol/ethanol ratio compared to SSK1 deletion and also compromised volumetric productivity and osmotolerance less. Our results show that polygenic analysis of yeast biodiversity can provide superior novel gene tools for metabolic engineering.     

QTL mapping of fire blight resistance in Malus ×robusta 5 after inoculation with different strains of Erwinia amylovora

Fire blight caused by Erwinia amylovora is one of the most disastrous diseases in apple production. Whereas most apple cultivars are susceptible to fire blight, several wild apple species accessions like Malus ×robusta 5 (Mr5) bear significant resistance. The resistance of Mr5 is mainly inherited by a major quantitative trait locus (QTL) on linkage group 3. QTL mapping was performed after inoculation of the population 04208 (Idared × Mr5) using strains differing in their virulence to Mr5. The QTL mapping approach demonstrated that the major QTL on linkage group 3 could be confirmed after inoculation with strains non-virulent to Mr5. In contrast, the major QTL disappeared after inoculation with strains virulent to Mr5. Only after inoculation with the resistance breaking strain Ea 3049 was a minor QTL with a LOD >3 found on linkage group 3. Additionally, several minor QTLs were detected on linkage groups 5, 7, 11 and 14 of Mr5 after inoculation with virulent strains able to overcome the major resistance QTL of Mr5. Their usefulness for further breeding activities will be discussed. The strain-specific results obtained in the present study provide further evidence for the existence of gene-for-gene relationships in the host–pathogen system Mr5–E. amylovora. Of the newly discovered minor QTLs, the one detected on LG7 contributes significantly to fire blight resistance in the presence of the major QTL, independently of the strain used.     

<Emphasis Type="Italic">In silico</Emphasis>discovery of gene-coding variants in murine quantitative trait loci using strain-specific genome sequence databases

Background  

The identification of genes underlying complex traits has been aided by quantitative trait locus (QTL) mapping approaches, which in turn have benefited from advances in mammalian genome research. Most recently, whole-genome draft sequences and assemblies have been generated for mouse strains that have been used for a large fraction of QTL mapping studies. Here we show how such strain-specific mouse genome sequence databases can be used as part of a high-throughput pipeline for the in silico discovery of gene-coding variations within murine QTLs. As a test of this approach we focused on two QTLs on mouse chromosomes 1 and 13 that are involved in physical dependence on alcohol.     

Genetic dissection of acetic acid tolerance in <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis>

Dissection of the hereditary architecture underlying Saccharomyces cerevisiae tolerance to acetic acid is essential for ethanol fermentation. In this work, a genomics approach was used to dissect hereditary variations in acetic acid tolerance between two phenotypically different strains. A total of 160 segregants derived from these two strains were obtained. Phenotypic analysis indicated that the acetic acid tolerance displayed a normal distribution in these segregants, and suggested that the acetic acid tolerant traits were controlled by multiple quantitative trait loci (QTLs). Thus, 220 SSR markers covering the whole genome were used to detect QTLs of acetic acid tolerant traits. As a result, three QTLs were located on chromosomes 9, 12, and 16, respectively, which explained 38.8–65.9 % of the range of phenotypic variation. Furthermore, twelve genes of the candidates fell into the three QTL regions by integrating the QTL analysis with candidates of acetic acid tolerant genes. These results provided a novel avenue to obtain more robust strains.     

Quantitative genetic dissection of complex traits in a QTL-mapping pedigree

This paper summarizes and modifies quantitative genetic analyses on a pedigree used to map genetic factors (i.e., QTLs) underlying a complex trait. The total genetic variance can be exactly estimated based on the F₂ family derived from two homozygous parents for alternative alleles at all QTLs of interest. The parents, F₁ hybrids, and two backcrosses are combined to each parent, and the total number of QTLs and the number of dominant QTLs are estimated under the assumptions of gene association with the two parents, equal gene effect, no linkage, and no epistasis among QTLs. Further relaxation for each of the assumptions are made in detail. The biometric estimator for the QTL number and action mode averaged over the entire genome could provide some basic and complementary information to QTL mapping designed to detect the effect and location of specific genetic factors.     

Quantitative Trait Loci for Light Sensitivity,Body Weight,Body Size,and Morphological Eye Parameters in the Bumblebee,Bombus terrestris

Bumblebees such as Bombus terrestris are essential pollinators in natural and managed ecosystems. In addition, this species is intensively used in agriculture for its pollination services, for instance in tomato and pepper greenhouses. Here we performed a quantitative trait loci (QTL) analysis on B. terrestris using 136 microsatellite DNA markers to identify genes linked with 20 traits including light sensitivity, body size and mass, and eye and hind leg measures. By composite interval mapping (IM), we found 83 and 34 suggestive QTLs for 19 of the 20 traits at the linkage group wide significance levels of p = 0.05 and 0.01, respectively. Furthermore, we also found five significant QTLs at the genome wide significant level of p = 0.05. Individual QTLs accounted for 7.5-53.3% of the phenotypic variation. For 15 traits, at least one QTL was confirmed with multiple QTL model mapping. Multivariate principal components analysis confirmed 11 univariate suggestive QTLs but revealed three suggestive QTLs not identified by the individual traits. We also identified several candidate genes linked with light sensitivity, in particular the Phosrestin-1-like gene is a primary candidate for its phototransduction function. In conclusion, we believe that the suggestive and significant QTLs, and markers identified here, can be of use in marker-assisted breeding to improve selection towards light sensitive bumblebees, and thus also the pollination service of bumblebees.     

Identification of Novel QTLs for Isolate-Specific Partial Resistance to Plasmodiophora brassicae in Brassica rapa

Plasmodiophora brassicae, the causal agent of clubroot disease of the Brassica crops, is widespread in the world. Quantitative trait loci (QTLs) for partial resistance to 4 different isolates of P. brassicae (Pb2, Pb4, Pb7, and Pb10) were investigated using a BC₁F₁ population from a cross between two subspecies of Brassica rapa, i.e. Chinese cabbage inbred line C59-1 as a susceptible recurrent parent and turnip inbred line ECD04 as a resistant donor parent. The BC₁F₂ families were assessed for resistance under controlled conditions. A linkage map constructed with simple sequence repeats (SSR), unigene-derived microsatellite (UGMS) markers, and specific markers linked to published clubroot resistance (CR) genes of B. rapa was used to perform QTL mapping. A total of 6 QTLs residing in 5 CR QTL regions of the B. rapa chromosomes A01, A03, and A08 were identified to account for 12.2 to 35.2% of the phenotypic variance. Two QTL regions were found to be novel except for 3 QTLs in the respective regions of previously identified Crr1, Crr2, and Crr3. QTL mapping results indicated that 1 QTL region was common for partial resistance to the 2 isolates of Pb2 and Pb7, whereas the others were specific for each isolate. Additionally, synteny analysis between B. rapa and Arabidopsis thaliana revealed that all CR QTL regions were aligned to a single conserved crucifer blocks (U, F, and R) on 3 Arabidopsis chromosomes where 2 CR QTLs were detected in A. thaliana. These results suggest that some common ancestral genomic regions were involved in the evolution of CR genes in B. rapa.     

Intersubspecific subcongenic mouse strain analysis reveals closely linked QTLs with opposite effects on body weight

A previous genome-wide QTL study revealed many QTLs affecting postnatal body weight and growth in an intersubspecific backcross mouse population between the C57BL/6J (B6) strain and wild Mus musculus castaneus mice captured in the Philippines. Subsequently, several closely linked QTLs for body composition traits were revealed in an F₂ intercross population between B6 and B6.Cg-Pbwg1, a congenic strain on the B6 genetic background carrying the growth QTL Pbwg1 on proximal chromosome 2. However, no QTL affecting body weight has been duplicated in the F₂ population, except for mapping an overdominant QTL that causes heterosis of body weight. In this study, we developed 17 intersubspecific subcongenic strains with overlapping and nonoverlapping castaneus regions from the B6.Cg-Pbwg1 congenic strain in order to search for and genetically dissect QTLs affecting body weight into distinct closely linked loci. Phenotypic comparisons of several developed subcongenic strains with the B6 strain revealed that two closely linked but distinct QTLs that regulate body weight, named Pbwg1.11 and Pbwg1.12, are located on an 8.9-Mb region between D2Mit270 and D2Mit472 and on the next 3.6-Mb region between D2Mit205 and D2Mit182, respectively. Further analyses using F₂ segregating populations obtained from intercrosses between B6 and each of the two selected subcongenic strains confirmed the presence of these two body weight QTLs. Pbwg1.11 had an additive effect on body weight at 6, 10, and 13?weeks of age, and its castaneus allele decreased it. In contrast, the castaneus allele at Pbwg1.12 acted in a dominant fashion and surprisingly increased body weight at 6, 10, and 13?weeks of age despite the body weight of wild castaneus mice being 60% of that of B6 mice. These findings illustrate the complex genetic nature of body weight regulation and support the importance of subcongenic mouse analysis to dissect closely linked loci.     

A haplotype inference algorithm for trios based on deterministic sampling

Background

The three-dimensional shape of grain, measured as grain length, width, and thickness (GL, GW, and GT), is one of the most important components of grain appearance in rice. Determining the genetic basis of variations in grain shape could facilitate efficient improvements in grain appearance. In this study, an F_7:8 recombinant inbred line population (RIL) derived from a cross between indica and japonica cultivars (Nanyangzhan and Chuan7) contrasting in grain size was used for quantitative trait locus (QTL) mapping. A genetic linkage map was constructed with 164 simple sequence repeat (SSR) markers. The major aim of this study was to detect a QTL for grain shape and to fine map a minor QTL, qGL7.

Results

Four QTLs for GL were detected on chromosomes 3 and 7, and 10 QTLs for GW and 9 QTLs for GT were identified on chromosomes 2, 3, 5, 7, 9 and 10, respectively. A total of 28 QTLs were identified, of which several are reported for the first time; four major QTLs and six minor QTLs for grain shape were also commonly detected in both years. The minor QTL, qGL7, exhibited pleiotropic effects on GL, GW, GT, 1000-grain weight (TGW), and spikelets per panicle (SPP) and was further validated in a near isogenic F₂ population (NIL-F₂). Finally, qGL7 was narrowed down to an interval between InDel marker RID711 and SSR marker RM6389, covering a 258-kb region in the Nipponbare genome, and cosegregated with InDel markers RID710 and RID76.

Conclusion

Materials with very different phenotypes were used to develop mapping populations to detect QTLs because of their complex genetic background. Progeny tests proved that the minor QTL, qGL7, could display a single mendelian characteristic. Therefore, we suggested that minor QTLs for traits with high heritability could be isolated using a map-based cloning strategy in a large NIL-F₂ population. In addition, combinations of different QTLs produced diverse grain shapes, which provide the ability to breed more varieties of rice to satisfy consumer preferences.     

Molecular mapping for fruit-related traits,and joint identification of candidate genes and selective sweeps for seed size in melon

Melon is a popular fruit vegetable crop worldwide with diverse morphological variation. We report a high-density genetic map of melon and nine major QTLs with physical region ranging from 43.47 kb to 1.89 Mb. Importantly, two seed-related trait QTLs were repeatedly detected in two environments, and the mapping region was narrowed to 522 kb according to a regional linkage analysis. A total of 40 annotated genes were screened for nonsynonymous variations, of which EVM0009818, involved in cytokinin-activated signaling, was differentially expressed in the young fruits of parents based on RNA-seq. Selective sweep analysis identified 152 sweep signals for seed size, including the two seed-related QTLs and nine homologs that have been verified to regulate seed size in Arabidopsis or rice. This work illustrates the power of a joint analysis combining resequencing-based genetic map for QTL mapping and a combination of KASP genotyping and RNA-seq analysis to facilitate QTL fine mapping.     

Mapping of Genomic Regions (Quantitative Trait Loci) Controlling Production and Quality in Industrial Cultures of the Edible Basidiomycete Pleurotus ostreatus

Industrial production of the edible basidiomycete Pleurotus ostreatus (oyster mushroom) is based on a solid fermentation process in which a limited number of selected strains are used. Optimization of industrial mushroom production depends on improving the culture process and breeding new strains with higher yields and productivities. Traditionally, fungal breeding has been carried out by an empirical trial and error process. In this study, we used a different approach by mapping quantitative trait loci (QTLs) controlling culture production and quality within the framework of the genetic linkage map of P. ostreatus. Ten production traits and four quality traits were studied and mapped. The production QTLs identified explain nearly one-half of the production variation. More interestingly, a single QTL mapping to the highly polymorphic chromosome VII appears to be involved in control of all the productivity traits studied. Quality QTLs appear to be scattered across the genome and to have less effect on the variation of the corresponding traits. Moreover, some of the new hybrid strains constructed in the course of our experiments had production or quality values higher than those of the parents or other commercial strains. This approach opens the possibility of marker-assisted selection and breeding of new industrial strains of this fungus.     

Fine mapping of a preharvest sprouting QTL interval on chromosome 2B in white wheat

Key message

Fine mapping by recombinant backcross populations revealed that a preharvest sprouting QTL on 2B contained two QTLs linked in coupling with different effects on the phenotype.

Abstract

Wheat preharvest sprouting (PHS) occurs when grain germinates on the plant before harvest, resulting in reduced grain quality. Previous mapping of quantitative trait locus (QTL) revealed a major PHS QTL, QPhs.cnl-2B.1, located on chromosome 2B significant in 16 environments that explained from 5 to 31 % of the phenotypic variation. The objective of this project was to fine map the QPhs.cnl-2B.1 interval. Fine mapping was carried out in recombinant backcross populations (BC₁F₄ and BC₁F₅) that were developed by backcrossing selected doubled haploids to a recurrent parent and self-pollinating the BC₁F₄ and BC₁F₅ generations. In each generation, three markers in the QPhs.cnl-2B.1 interval were used to screen for recombinants. Fine mapping revealed that the QPhs.cnl-2B.1 interval contained two PHS QTLs linked in coupling. The distal PHS QTL, located between Wmc453c and Barc55, contributed 8 % of the phenotypic variation and also co-located with a major seed dormancy QTL determined by germination index. The proximal PHS QTL, between Wmc474 and CNL415-rCDPK, contributed 16 % of the variation. Several candidate genes including Mg-chelatase H subunit family protein, GTP-binding protein and calmodulin/Ca²⁺-dependent protein kinase were linked to the PHS QTL. Although many recombinant lines were identified, the lack of polymorphism for markers in the QTL interval prevented the localization of the recombination breakpoints and identification of the gene underlying the phenotype.     

Identification of Novel Strain-Specific and Environment-Dependent Minor QTLs Linked to Fire Blight Resistance in Apples

Since its first report almost 200 years ago, fire blight, caused by the gram-negative bacterium Erwinia amylovora, has threatened apple and pear production globally. Identifying novel genes and their functional alleles is a prerequisite to developing apple cultivars with enhanced fire blight resistance. Here, we report 13 strain-specific and environment-dependent minor QTLs linked to fire blight resistance from a segregating Malus sieversii × Malus × domestica mapping population. Interval mapping at 95% confidence and Kruskal–Wallis analysis at P value =?0.005 were used to identify QTLs for three strains of E. amylovora differing in virulence and pathogenicity. The QTLs identified explain a small to moderate part of resistance variability, and a majority was not common between years or E. amylovora strains. These QTLs are distributed in eight linkage groups of apples and comparison of their map position to previously identified fire blight resistance QTLs indicates that most are novel loci. Interaction between experimental conditions in the greenhouse and field, and between years, and differences in virulence levels of strains might be responsible for strain- and year-specific QTLs. The QTLs identified on LG10 for strain Ea273 in 2011 and strain LP101 in 2011, and on LG15 for strain LP101 could be the same QTLs identified previously with strain CFBP1430 in cultivar “Florina” and “Co-op16 × Co-op17” mapping population, respectively. We discuss the potential impact of newly identified minor fire blight QTLs and major gene-based resistance on the rate of mutation in pathogen populations to overcome resistance and durability of resistance.     

Further studies on using multiple-cross mapping (MCM) to map quantitative trait loci

We have completed whole-genome scans for quantitative trait loci (QTLs) associated with acute ethanol-induced activation in the six F₂ intercrosses that can be formed from the C57BL/6J (B6), DBA/2J (D2) , BALB/cJ (C), and LP/J (LP) inbred strains. The goal was to test the hypothesis that given the relatively simple structure of the laboratory mouse genome, the same QTLs will be detected in multiple crosses which in turn will provide support for the strategy of multiple-cross mapping (MCM). QTLs with LOD scores greater than 4 were detected on Chrs 1, 2, 3, 8, 9, 13, 14, and 16. Only for the QTL on distal Chr 1 was there convincing evidence that the same or at least a very similar QTL was detected in multiple crosses. We also mapped the Chr 2 QTL directly in heterogeneous stock (HS) animals derived from the four inbred strains. At G₁₉ the QTL was mapped to an approximately 3-Mbp interval and this interval was associated with a haplotype block with a largely biallelic structure: B6-L:C-D2. We conclude that mapping in HS animals not only provides significantly greater QTL resolution, at least in some cases it provides significantly more information about the QTL haplotype structure.     

Detection and verification of malting quality QTLs using wild barley introgression lines

A malting quality quantitative trait locus (QTL) study was conducted using a set of 39 wild barley introgression lines (hereafter abbreviated with S42ILs). Each S42IL harbors a single marker-defined chromosomal segment from the wild barley accession ‘ISR 42-8’ (Hordeum vulgare ssp. spontaneum) within the genetic background of the elite spring barley cultivar ‘Scarlett’ (Hordeum vulgare ssp. vulgare). The aim of the study was (1) to verify genetic effects previously identified in the advanced backcross population S42, (2) to detect new QTLs, and (3) to identify S42ILs exhibiting multiple QTL effects. For this, grain samples from field tests in three different environments were subjected to micro malting. Subsequently, a line × phenotype association study was performed with the S42ILs in order to localize putative QTL effects. A QTL was accepted if the trait value of a particular S42IL was significantly (P < 0.05) different from the recurrent parent as a control, either across all tested environments or in a particular environment. For eight malting quality traits, altogether 40 QTLs were localized, among which 35 QTLs (87.5%) were stable across all environments. Six QTLs (15.0%) revealed a trait improving wild barley effect. Out of 36 QTLs detected in a previous advanced backcross QTL study with the parent BC₂DH population S42, 18 QTLs (50.0%) could be verified with the S42IL set. For the quality parameters α-amylase activity and Hartong 45°C, all QTLs assessed in population S42 were verified by S42ILs. In addition, eight new QTL effects and 17 QTLs affecting two newly investigated traits were localized. Two QTL clusters harboring simultaneous effects on eight and six traits, respectively, were mapped to chromosomes 1H and 4H. In future, fine-mapping of these QTL regions will be conducted in order to shed further light on the genetic basis of the most interesting QTLs.     

Genetic analysis of shoot fresh weight in a cross of wild (<Emphasis Type="Italic">G. soja</Emphasis>) and cultivated (<Emphasis Type="Italic">G. max</Emphasis>) soybean

Shoot fresh weight (SFW) is one of the parameters, used to estimate the total plant biomass yield in soybean. In the present study, a total of 188 F_5:8 recombinant inbred lines (RIL) derived from an interspecific cross of PI 483463 (Glycine soja) and Hutcheson (Glycine max) were investigated for SFW variation in the field for three consecutive years. The parental lines and RILs were phenotyped in the field at the R6 stage by measuring total biomass in kg/plot to identify the QTLs for SFW. Three QTLs qSFW6_1, qSFW15_1, and qSFW19_1 influencing SFW were identified on chromosome 6, 15, and 19, respectively. The QTL qSFW19_1 flanked between the markers BARC-044913-08839 and BARC-029975-06765 was the stable QTL expressed in all the three environments. The phenotypic variation explained by the QTLs across all environments ranged from 6.56 to 21.32 %. The additive effects indicated contribution of alleles from both the parents and additive × environment interaction effects affected the expression of SFW QTL. Screening of the RIL population with additional SSRs from the qSFW19_1 region delimited the QTL between the markers SSR19-1329 and BARC-29975-06765. QTL mapping using bin map detected two QTLs, qSFW19_1A and qSFW19_1B. The QTL qSFW19_1A mapped close to the Dt1 gene locus, which affects stem termination, plant height, and floral initiation in soybean. Potential candidate genes for SFW were pinpointed, and sequence variations within their sequences were detected using high-quality whole-genome resequencing data. The findings in this study could be useful for understanding genetic basis of SFW in soybean.     

Molecular genetic analysis of grain protein content and flour whiteness degree using RILs in common wheat

Grain protein content (GPC) and flour whiteness degree (FWD) are important qualitative traits in common wheat. Quantitative trait locus (QTL) mapping for GPC and FWD was conducted using a set of 131 recombinant-inbred lines derived from the cross ‘Chuan 35050 × Shannong 483’ in six environmental conditions. A total of 22 putative QTLs (nine GPC and 13 FWD) were identified on 12 chromosomes with individual QTL explaining 4.5–34.0% phenotypic variation. Nine QTLs (40.9%) were detected in two or more environments. The colocated QTLs were on chromosomes 1B and 4B. Among the QTLs identified for GPC, QGpc.sdau-4A from the parent Shannong 483 represented some important favourable QTL alleles. QGpc.sdau-2A.1 and QFwd.sdau-2A.1 had a significant association with both GPC and FWD. The markers detected on top of QTL regions could be potential targets for marker-assisted selection.     

Genomic regions controlling components of resistance for pea rust caused by Uromyces fabae (Pers.) de-Bary

Pea rust caused by Uromyces fabae (Pers.) de-Bary is an important disease in subtropical regions of the world. The use of partial resistance or slow rusting is an important strategy for developing varieties having durable rust resistance. A mapping population of 136 F_6:7 Recombinant Inbred Lines (RILs) derived from the cross HUVP 1?×?FC 1 was evaluated for disease severity percent (DS%) and three components of slow rusting, number of aecial pustules per leaf (AP), leaf area covered by sporulating pustules (LASP) and number of aecial cups per leaf (TNAC) during crop seasons 2006–07 and 2007–08 in polyhouse and field experiments. The components were governed by four quantitative trait loci, two major (Qruf on LGVII, Qruf2 on LGI), and two minor QTLs (Qruf1 on LG VII and Qruf3 on LGVI). This confirmed the positions of one each of the major (Qruf) and minor (Qruf1) QTLs and also detected two new QTLs Qruf2 and Qruf3. The new major QTL Qruf2 (phenotypic variance 21.3 to 29.6 %) appeared to be the most important component-specific QTL and played key role in deciding disease resistance. The minor QTL Qruf3 appeared environment-specific and contributed by the susceptible parent.     

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.