Bayesian QTL analyses using pedigreed families of an outcrossing species,with application to fruit firmness in apple

Key message

Proof of concept of Bayesian integrated QTL analyses across pedigree-related families from breeding programs of an outbreeding species. Results include QTL confidence intervals, individuals’ genotype probabilities and genomic breeding values.

Abstract

Bayesian QTL linkage mapping approaches offer the flexibility to study multiple full sib families with known pedigrees simultaneously. Such a joint analysis increases the probability of detecting these quantitative trait loci (QTL) and provide insight of the magnitude of QTL across different genetic backgrounds. Here, we present an improved Bayesian multi-QTL pedigree-based approach on an outcrossing species using progenies with different (complex) genetic relationships. Different modeling assumptions were studied in the QTL analyses, i.e., the a priori expected number of QTL varied and polygenic effects were considered. The inferences include number of QTL, additive QTL effect sizes and supporting credible intervals, posterior probabilities of QTL genotypes for all individuals in the dataset, and QTL-based as well as genome-wide breeding values. All these features have been implemented in the FlexQTL^? software. We analyzed fruit firmness in a large apple dataset that comprised 1,347 individuals forming 27 full sib families and their known ancestral pedigrees, with genotypes for 87 SSR markers on 17 chromosomes. We report strong or positive evidence for 14 QTL for fruit firmness on eight chromosomes, validating our approach as several of these QTL were reported previously, though dispersed over a series of studies based on single mapping populations. Interpretation of linked QTL was possible via individuals’ QTL genotypes. The correlation between the genomic breeding values and phenotypes was on average 90 %, but varied with the number of detected QTL in a family. The detailed posterior knowledge on QTL of potential parents is critical for the efficiency of marker-assisted breeding.     

Constructing a dense genetic linkage map and mapping QTL for the traits of flower development in Brassica carinata

Key message

An integrated dense genetic linkage map was constructed in a B. carinata population and used for comparative genome analysis and QTL identification for flowering time.

Abstract

An integrated dense linkage map of Brassica carinata (BBCC) was constructed in a doubled haploid population based on DArT-Seq^TM markers. A total of 4,031 markers corresponding to 1,366 unique loci were mapped including 639 bins, covering a genetic distance of 2,048 cM. We identified 136 blocks and islands conserved in Brassicaceae, which showed a feature of hexaploidisation representing the suggested ancestral crucifer karyotype. The B and C genome of B. carinata shared 85 % of commonly conserved blocks with the B genome of B. nigra/B. juncea and 80 % of commonly conserved blocks with the C genome of B. napus, and shown frequent structural rearrangements such as insertions and inversions. Up to 24 quantitative trait loci (QTL) for flowering and budding time were identified in the DH population. Of these QTL, one consistent QTL (qFT.B4-2) for flowering time was identified in all of the environments in the J block of the B4 linkage group, where a group of genes for flowering time were aligned in A. thaliana. Another major QTL for flowering time under a winter-cropped environment was detected in the E block of C6, where the BnFT-C6 gene was previously localised in B. napus. This high-density map would be useful not only to reveal the genetic variation in the species with QTL analysis and genome sequencing, but also for other applications such as marker-assisted selection and genomic selection, for the African mustard improvement.     

Highly efficient genotyping of rice biparental populations by GoldenGate assays based on parental resequencing

Key message

A new time- and cost-effective strategy was developed for medium-density SNP genotyping of rice biparental populations, using GoldenGate assays based on parental resequencing.

Abstract

Since the advent of molecular markers, crop researchers and breeders have dedicated huge amounts of effort to detecting quantitative trait loci (QTL) in biparental populations for genetic analysis and marker-assisted selection (MAS). In this study, we developed a new time- and cost-effective strategy for genotyping a population of progeny from a rice cross using medium-density single nucleotide polymorphisms (SNPs). Using this strategy, 728,362 “high quality” SNPs were identified by resequencing Teqing and Lemont, the parents of the population. We selected 384 informative SNPs that were evenly distributed across the genome for genotyping the biparental population using the Illumina GoldenGate assay. 335 (87.2 %) validated SNPs were used for further genetic analyses. After removing segregation distortion markers, 321 SNPs were used for linkage map construction and QTL mapping. This strategy generated SNP markers distributed more evenly across the genome than previous SSR assays. Taking the GW5 gene that controls grain shape as an example, our strategy provided higher accuracy (0.8 Mb) and significance (LOD 5.5 and 10.1) in QTL mapping than SSR analysis. Our study thus provides a rapid and efficient strategy for genetic studies and QTL mapping using SNP genotyping assays.     

Genome-wide QTL and bulked transcriptomic analysis reveals new candidate genes for the control of tuber carotenoid content in potato (Solanum tuberosum L.)

Key message

Genome-wide QTL analysis of potato tuber carotenoid content was investigated in populations of Solanum tuberosum Group Phureja that segregate for flesh colour, revealing a novel major QTL on chromosome 9.

Abstract

The carotenoid content of edible plant storage organs is a key nutritional and quality trait. Although the structural genes that encode the biosynthetic enzymes are well characterised, much less is known about the factors that determine overall storage organ content. In this study, genome-wide QTL mapping, in concert with an efficient ‘genetical genomics’ analysis using bulked samples, has been employed to investigate the genetic architecture of potato tuber carotenoid content. Two diploid populations of Solanum tuberosum Group Phureja were genotyped (AFLP, SSR and DArT markers) and analysed for their tuber carotenoid content over two growing seasons. Common to both populations were QTL that explained relatively small proportions of the variation in constituent carotenoids and a major QTL on chromosome 3 explaining up to 71 % of the variation in carotenoid content. In one of the populations (01H15), a second major carotenoid QTL was identified on chromosome 9, explaining up to 20 % of the phenotypic variation. Whereas the major chromosome 3 QTL was likely to be due to an allele of a gene encoding β-carotene hydroxylase, no known carotenoid biosynthetic genes are located in the vicinity of the chromosome 9 QTL. A unique expression profiling strategy using phenotypically distinct bulks comprised individuals with similar carotenoid content provided further support for the QTL mapping to chromosome 9. This study shows the potential of using the potato genome sequence to link genetic maps to data arising from eQTL approaches to enhance the discovery of candidate genes underlying QTLs.     

Multi-trait and multi-environment QTL analyses of yield and a set of physiological traits in pepper

Key message

A mixed model framework was defined for QTL analysis of multiple traits across multiple environments for a RIL population in pepper. Detection power for QTLs increased considerably and detailed study of QTL by environment interactions and pleiotropy was facilitated.

Abstract

For many agronomic crops, yield is measured simultaneously with other traits across multiple environments. The study of yield can benefit from joint analysis with other traits and relations between yield and other traits can be exploited to develop indirect selection strategies. We compare the performance of three multi-response QTL approaches based on mixed models: a multi-trait approach (MT), a multi-environment approach (ME), and a multi-trait multi-environment approach (MTME). The data come from a multi-environment experiment in pepper, for which 15 traits were measured in four environments. The approaches were compared in terms of number of QTLs detected for each trait, the explained variance, and the accuracy of prediction for the final QTL model. For the four environments together, the superior MTME approach delivered a total of 47 regions containing putative QTLs. Many of these QTLs were pleiotropic and showed quantitative QTL by environment interaction. MTME was superior to ME and MT in the number of QTLs, the explained variance and accuracy of predictions. The large number of model parameters in the MTME approach was challenging and we propose several guidelines to help obtain a stable final QTL model. The results confirmed the feasibility and strengths of novel mixed model QTL methodology to study the architecture of complex traits.     

Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.)

Key message

This report describes an integrative analysis of seed-oil-content quantitative trait loci (QTL) in Brassica napus , using a high-density genetic map to align QTL among different populations.

Abstract

Rapeseed (Brassica napus) is an important source of edible oil and sustainable energy. Given the challenge involved in using only a few genes to substantially increase the oil content of rapeseed without affecting the fatty acid composition, exploitation of a greater number of genetic loci that regulate the oil content variation among rapeseed germplasm is of fundamental importance. In this study, we investigated variation in the seed-oil content among two related genetic populations of Brassica napus, the TN double-haploid population and its derivative reconstructed-F₂ population. Each population was grown in multiple experiments under different environmental conditions. Mapping of quantitative trait loci (QTL) identified 41 QTL in the TN populations. Furthermore, of the 20 pairs of epistatic interaction loci detected, approximately one-third were located within the QTL intervals. The use of common markers on different genetic maps and the TN genetic map as a reference enabled us to project QTL from an additional three genetic populations onto the TN genetic map. In summary, we used the TN genetic map of the B. napus genome to identify 46 distinct QTL regions that control seed-oil content on 16 of the 19 linkage groups of B. napus. Of these, 18 were each detected in multiple populations. The present results are of value for ongoing efforts to breed rapeseed with high oil content, and alignment of the QTL makes an important contribution to the development of an integrative system for genetic studies of rapeseed.     

QTL for resistance to root lesion nematode (Pratylenchus thornei) from a synthetic hexaploid wheat source

Key message

A whole genome average interval mapping approach identified eight QTL associated with P. thornei resistance in a DH population from a cross between the synthetic-derived wheat Sokoll and cultivar Krichauff.

Abstract

Pratylenchus thornei are migratory nematodes that feed and reproduce within the wheat root cortex, causing cell death (lesions) resulting in severe yield reductions globally. Genotypic selection using molecular markers closely linked to Pratylenchus resistance genes will accelerate the development of new resistant cultivars by reducing the need for laborious and expensive resistance phenotyping. A doubled haploid wheat population (150 lines) from a cross between the synthetic-derived cultivar Sokoll (P. thornei resistant) and cultivar Krichauff (P. thornei moderately susceptible) was used to identify quantitative trait loci (QTL) associated with P. thornei resistance. The resistance identified in the glasshouse was validated in a field trial. A genetic map was constructed using Diversity Array Technology and the QTL regions identified were further targeted with simple sequence repeat (SSR) and single-nucleotide polymorphism (SNP) markers. Six significant and two suggestive P. thornei resistance QTL were detected using a whole genome average interval mapping approach. Three QTL were identified on chromosome 2B, two on chromosome 6D, and a single QTL on each of chromosomes 2A, 2D and 5D. The QTL on chromosomes 2BS and 6DS mapped to locations previously identified to be associated with Pratylenchus resistance. Together, the QTL on 2B (QRlnt.sk-2B.1–2B.3) and 6D (QRlnt.sk-6D.1 and 6D.2) explained 30 and 48 % of the genotypic variation, respectively. Flanking PCR-based markers based on SSRs and SNPs were developed for the major QTL on 2B and 6D and provide a cost-effective high-throughput tool for marker-assisted breeding of wheat with improved P. thornei resistance.     

Clusthaplo: a plug-in for MCQTL to enhance QTL detection using ancestral alleles in multi-cross design

Key message

We enhance power and accuracy of QTL mapping in multiple related families, by clustering the founders of the families on their local genomic similarity.

Abstract

MCQTL is a linkage mapping software application that allows the joint QTL mapping of multiple related families. In its current implementation, QTLs are modeled with one or two parameters for each parent that is a founder of the multi-cross design. The higher the number of parents, the higher the number of model parameters which can impact the power and the accuracy of the mapping. We propose to make use of the availability of denser and denser genotyping information on the founders to lessen the number of MCQTL parameters and thus boost the QTL discovery. We developed clusthaplo, an R package (http://cran.r-project.org/web/packages/clusthaplo/index.html), which aims to cluster haplotypes using a genomic similarity that reflects the probability of sharing the same ancestral allele. Computed in a sliding window along the genome and followed by a clustering method, the genomic similarity allows the local clustering of the parent haplotypes. Our assumption is that the haplotypes belonging to the same class transmit the same ancestral allele. So their putative QTL allelic effects can be modeled with the same parameter, leading to a parsimonious model, that is plugged in MCQTL. Intensive simulations using three maize data sets showed the significant gain in power and in accuracy of the QTL mapping with the ancestral allele model compared to the classical MCQTL model. MCQTL_LD (clusthaplo outputs plug in MCQTL) is a versatile and powerful tool for QTL mapping in multiple related families that makes use of linkage and linkage disequilibrium (web site http://carlit.toulouse.inra.fr/MCQTL/).     

Combined use of bulked segregant analysis and microarrays reveals SNP markers pinpointing a major QTL for resistance to Phytophthora capsici in pepper

Key message

Bulked segregant analysis (BSA) using Affymetrix GeneChips revealed candidate genes underlying the major QTL for Phytophthora capsici resistance in Capsicum . Using the candidate genes, reliable markers for Phytophthora resistance were developed and validated.

Abstract

Phytophthora capsici L. is one of the most destructive pathogens of pepper (Capsicum spp.). Resistance of pepper against P. capsici is controlled by quantitative trait loci (QTL), including a major QTL on chromosome 5 that is the predominant contributor to resistance. Here, to maximize the effect of this QTL and study its underlying genes, an F₂ population and recombinant inbred lines were inoculated with P. capsici strain JHAI1-7 zoospores at a low concentration (3 × 10³/mL). Resistance phenotype segregation ratios for the populations fit a 3:1 and 1:1 (resistant:susceptible) segregation model, respectively, consistent with a single dominant gene model. Bulked segregant analysis (BSA) using Affymetrix GeneChips revealed a single position polymorphism (SPP) marker mapping to the major QTL. When this SPP marker (Phyto5SAR) together with other SNP markers located on chromosome 5 was used to confirm the position of the major QTL, Phyto5SAR showed the highest LOD value at the QTL. A scaffold sequence (scaffold194) containing Phyto5SAR was identified from the C. annuum genome database. The scaffold contained two putative NBS-LRR genes and one SAR 8.2A gene as candidates for contributing to P. capsici resistance. Markers linked to these genes were developed and validated by testing 100 F₁ commercial cultivars. Among the markers, Phyto5NBS1 showed about 90 % accuracy in predicting resistance phenotypes to a low-virulence P. capsici isolate. These results suggest that Phyto5NBS1 is a reliable marker for P. capsici resistance and can be used for identification of a gene(s) underlying the major QTL on chromosome 5.     

QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

Key message

A QTL model for the genetic control of tillering in sorghum is proposed, presenting new opportunities for sorghum breeders to select germplasm with tillering characteristics appropriate for their target environments.

Abstract

Tillering in sorghum can be associated with either the carbon supply–demand (S/D) balance of the plant or an intrinsic propensity to tiller (PTT). Knowledge of the genetic control of tillering could assist breeders in selecting germplasm with tillering characteristics appropriate for their target environments. The aims of this study were to identify QTL for tillering and component traits associated with the S/D balance or PTT, to develop a framework model for the genetic control of tillering in sorghum. Four mapping populations were grown in a number of experiments in south east Queensland, Australia. The QTL analysis suggested that the contribution of traits associated with either the S/D balance or PTT to the genotypic differences in tillering differed among populations. Thirty-four tillering QTL were identified across the populations, of which 15 were novel to this study. Additionally, half of the tillering QTL co-located with QTL for component traits. A comparison of tillering QTL and candidate gene locations identified numerous coincident QTL and gene locations across populations, including the identification of common non-synonymous SNPs in the parental genotypes of two mapping populations in a sorghum homologue of MAX1, a gene involved in the control of tiller bud outgrowth through the production of strigolactones. Combined with a framework for crop physiological processes that underpin genotypic differences in tillering, the co-location of QTL for tillering and component traits and candidate genes allowed the development of a framework QTL model for the genetic control of tillering in sorghum.     

Construction of an integrative linkage map and QTL mapping of grain yield-related traits using three related wheat RIL populations

Key message

A novel high-density consensus wheat genetic map was obtained based on three related RIL populations, and the important chromosomal regions affecting yield and related traits were specified.

Abstract

A prerequisite for mapping quantitative trait locus (QTL) is to build a genetic linkage map. In this study, three recombinant inbred line populations (represented by WL, WY, and WJ) sharing one common parental line were used for map construction and subsequently for QTL detection of yield-related traits. PCR-based and diversity arrays technology markers were screened in the three populations. The integrated genetic map contains 1,127 marker loci, which span 2,976.75 cM for the whole genome, 985.93 cM for the A genome, 922.16 cM for the B genome, and 1,068.65 cM for the D genome. Phenotypic values were evaluated in four environments for populations WY and WJ, but three environments for population WL. Individual and combined phenotypic values across environments were used for QTL detection. A total of 165 putative additive QTL were identified, 22 of which showed significant additive-by-environment interaction effects. A total of 65 QTL (51.5 %) were stable across environments, and 23 of these (35.4 %) were common stable QTL that were identified in at least two populations. Notably, QTkw-5B.1, QTkw-6A.2, and QTkw-7B.1 were common major stable QTL in at least two populations, exhibiting 11.28–16.06, 5.64–18.69, and 6.76–21.16 % of the phenotypic variance, respectively. Genetic relationships between kernel dimensions and kernel weight and between yield components and yield were evaluated. Moreover, QTL or regions that commonly interact across genetic backgrounds were discussed by comparing the results of the present study with those of previous similar studies. The present study provides useful information for marker-assisted selection in breeding wheat varieties with high yield.     

Identification of agronomically important QTL in tetraploid potato cultivars using a marker–trait association analysis

Key message

Nineteen tuber quality traits in potato were phenotyped in 205 cultivars and 299 breeder clones. Association analysis using 3364 AFLP loci and 653 SSR-alleles identified QTL for these traits.

Abstract

Two association mapping panels were analysed for marker–trait associations to identify quantitative trait loci (QTL). The first panel comprised 205 historical and contemporary tetraploid potato cultivars that were phenotyped in field trials at two locations with two replicates (the academic panel). The second panel consisted of 299 potato cultivars and included recent breeds obtained from five Dutch potato breeding companies and reference cultivars (the industrial panel). Phenotypic data for the second panel were collected during subsequent clonal selection generations at the individual breeding companies. QTL were identified for 19 agro-morphological and quality traits. Two association mapping models were used: a baseline model without, and a more advanced model with correction for population structure and genetic relatedness. Correction for population structure and genetic relatedness was performed with a kinship matrix estimated from marker information. The detected QTL partly not only confirmed previous studies, e.g. for tuber shape and frying colour, but also new QTL were found like for after baking darkening and enzymatic browning. Pleiotropic effects could be discerned for several QTL.     

Multiple-line cross QTL mapping for biomass yield and plant height in triticale (× Triticosecale Wittmack)

Key message

QTL mapping in multiple families identifies trait-specific and pleiotropic QTL for biomass yield and plant height in triticale.

Abstract

Triticale shows a broad genetic variation for biomass yield which is of interest for a range of purposes, including bioenergy. Plant height is a major contributor to biomass yield and in this study, we investigated the genetic architecture underlying biomass yield and plant height by multiple-line cross QTL mapping. We employed 647 doubled haploid lines from four mapping populations that have been evaluated in four environments and genotyped with 1710 DArT markers. Twelve QTL were identified for plant height and nine for biomass yield which cross-validated explained 59.6 and 38.2 % of the genotypic variance, respectively. A major QTL for both traits was identified on chromosome 5R which likely corresponds to the dominant dwarfing gene Ddw1. In addition, we detected epistatic QTL for plant height and biomass yield which, however, contributed only little to the genetic architecture of the traits. In conclusion, our results demonstrate the potential of genomic approaches for a knowledge-based improvement of biomass yield in triticale.     

QTL mapping for salt tolerance and domestication-related traits in Vigna marina subsp. oblonga,a halophytic species

Key message

QTL mapping in F ₂ population [ V. luteola × V. marina subsp. oblonga ] revealed that the salt tolerance in V. marina subsp. oblonga is controlled by a single major QTL.

Abstract

The habitats of beach cowpea (Vigna marina) are sandy beaches in tropical and subtropical regions. As a species that grows closest to the sea, it has potential to be a gene source for breeding salt-tolerant crops. We reported here for the first time, quantitative trait loci (QTLs) mapping for salt tolerance in V. marina. A genetic linkage map was constructed from an F₂ population of 120 plants derived from an interspecific cross between V. luteola and V. marina subsp. oblonga. The map comprised 150 SSR markers. The markers were clustered into 11 linkage groups spanning 777.6 cM in length with a mean distance between the adjacent markers of 5.59 cM. The F_2:3 population was evaluated for salt tolerance under hydroponic conditions at the seedling and developmental stages. Segregation analysis indicated that salt tolerance in V. marina is controlled by a few genes. Multiple interval mapping consistently identified one major QTL which can explain about 50 % of phenotypic variance. The flanking markers may facilitate transfer of the salt tolerance allele from V. marina subsp. oblonga into related Vigna crops. The QTL for domestication-related traits from V. marina are also discussed.     

MulSatDB: a first online database for mulberry microsatellites

Key message

Simple sequence repeat motifs were mined from the genome and EST sequences of Morus notabilis and archived in MulSatDB. Bioinformatics tools were integrated with the database for the analysis of genomic datasets.

Abstract

Mulberry is a crop of economic importance in sericulture, which shapes the lives of millions of rural people among different Eurasian and Latin American countries. Limited availability of genomic resources has constrained the molecular breeding efforts in mulberry, a poorly studied crop. Microsatellite or simple sequence repeat (SSR) has revolutionized the plant breeding and is used in linkage mapping, association studies, diversity, and parentage analysis, etc. Recent availability of mulberry whole genome assembly provided an opportunity for the development of mulberry-specific DNA markers. In this study, we mined a total of 217,312 microsatellites from whole genome and 961 microsatellites from EST sequences of Morus notabilis. Mono-repeats were predominant among both whole genome and EST sequences. The SSR containing EST sequences were functionally annotated, and SSRs mined from whole genome were mapped on chromosomes of the phylogenetically related genus—Fragaria vesca, to aid the selection of markers based on the function and location. All the mined markers were archived in the mulberry microsatellite database (MulSatDB), and the markers can be retrieved based on different criteria like marker location, repeat kind, motif type and size. Primer3plus and CMap tools are integrated with the database to design primers for PCR amplification and to visualize markers on F. vesca chromosomes, respectively. A blast tool is also integrated to collate new markers with the database. MulSatDB is the first and complete destination for mulberry researchers to browse SSR markers, design primers, and locate markers on strawberry chromosomes. MulSatDB is freely accessible at http://btismysore.in/mulsatdb.     

Genetic analysis and major QTL detection for maize kernel size and weight in multi-environments

Key Message

Twelve major QTL in five optimal clusters and several epistatic QTL are identified for maize kernel size and weight, some with pleiotropic will be promising for fine-mapping and yield improvement.

Abstract

Kernel size and weight are important target traits in maize (Zea mays L.) breeding programs. Here, we report a set of quantitative trait loci (QTL) scattered through the genome and significantly controlled the performance of four kernel traits including length, width, thickness and weight. From the cross V671 (large kernel) × Mc (small kernel), 270 derived F_2:3 families were used to identify QTL of maize kernel-size traits and kernel weight in five environments, using composite interval mapping (CIM) for single-environment analysis along with mixed linear model-based CIM for joint analysis. These two mapping strategies identified 55 and 28 QTL, respectively. Among them, 6 of 23 coincident were detected as interacting with environment. Single-environment analysis showed that 8 genetic regions on chromosomes 1, 2, 4, 5 and 9 clustered more than 60 % of the identified QTL. Twelve stable major QTLs accounting for over 10 % of phenotypic variation were included in five optimal clusters on the genetic region of bins 1.02–1.03, 1.04–1.06, 2.05–2.07, 4.07–4.08 and 9.03–9.04; the addition and partial dominance effects of significant QTL play an important role in controlling the development of maize kernel. These putative QTL may have great promising for further fine-mapping with more markers, and genetic improvement of maize kernel size and weight through marker-assisted breeding.     

Genetic dissection of seed weight by QTL analysis and detection of allelic variation in Indian and east European gene pool lines of <Emphasis Type="Italic">Brassica juncea</Emphasis>

Key message

Seed weight QTL identified in different populations were synthesized into consensus QTL which were shown to harbor candidate genes by in silico mapping. Allelic variation inferred would be useful in breeding B. juncea lines with high seed weight.

Abstract

Seed weight is an important yield influencing trait in oilseed Brassicas and is a multigenic trait. Among the oilseed Brassicas, Brassica juncea harbors the maximum phenotypic variation wherein thousand seed weight varies from around 2.0 g to more than 7.0 g. In this study, we have undertaken quantitative trait locus/quantitative trait loci (QTL) analysis of seed weight in B. juncea using four bi-parental doubled-haploid populations. These four populations were derived from six lines (three Indian and three east European lines) with parental phenotypic values for thousand seed weight ranging from 2.0 to 7.6 g in different environments. Multi-environment QTL analysis of the four populations identified a total of 65 QTL ranging from 10 to 25 in each population. Meta-analysis of these component QTL of the four populations identified six ‘consensus’ QTL (C-QTL) in A3, A7, A10 and B3 by merging 33 of the 65 component Tsw QTL from different bi-parental populations. Allelic diversity analysis of these six C-QTL showed that Indian lines, Pusajaikisan and Varuna, hold the most positive allele in all the six C-QTL. In silico mapping of candidate genes with the consensus QTL localized 11 genes known to influence seed weight in Arabidopsis thaliana and also showed conserved crucifer blocks harboring seed weight QTL between the A subgenomes of B. juncea and B. rapa. These findings pave the way for a better understanding of the genetics of seed weight in the oilseed crop B. juncea and reveal the scope available for improvement of seed weight through marker-assisted breeding.

     

QTL-seq identifies an early flowering QTL located near Flowering Locus T in cucumber

Key message

Next-generation sequencing enabled a fast discovery of a major QTL controlling early flowering in cucumber, corresponding to the FT gene conditioning flowering time in Arabidopsis.

Abstract

Next-generation sequencing technologies are making it faster and more efficient to establish the association of agronomic traits with molecular markers or candidate genes, which is the requirement for marker-assisted selection in molecular breeding. Early flowering is an important agronomic trait in cucumber (Cucumis sativus L.), but the underlying genetic mechanism is unknown. In this study, we identified a candidate gene for early flowering QTL, Ef1.1 through QTL-seq. Segregation analysis in F₂ and BC₁ populations derived from a cross between two inbred lines “Muromskij” (early flowering) and “9930” (late flowering) suggested quantitative nature of flowering time in cucumber. Genome-wide comparison of SNP profiles between the early and late-flowering bulks constructed from F₂ plants identified a major QTL, designated Ef1.1 on cucumber chromosome 1 for early flowering in Muromskij, which was confirmed by microsatellite marker-based classical QTL mapping in the F₂ population. Joint QTL-seq and traditional QTL analysis delimited Ef1.1 to an 890 kb genomic region. A cucumber gene, Csa1G651710, was identified in this region, which is a homolog of the FLOWERING LOCUS T (FT), the main flowering switch gene in Arabidopsis. Quantitative RT-PCR study of the expression level of Csa1G651710 revealed significantly higher expression in early flowering genotypes. Data presented here provide support for Csa1G651710 as a possible candidate gene for early flowering in the cucumber line Muromskij.