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

QTLs and Genes for Salt Stress Tolerance: A Journey from Seed to Seed Continued

Rice (Oryza sativa L.) is a crucial crop contributing to global food security; however, its production is susceptible to salinity, a significant abiotic stressor that negatively impacts plant germination, vigour, and yield, degrading crop production. Due to the presence of exchangeable sodium ions (Na+), the affected plants sustain two-way damage resulting in initial osmotic stress and subsequent ion toxicity in the plants, which alters the cell's ionic homeostasis and physiological status. To adapt to salt stress, plants sense and transfer osmotic and ionic signals into their respective cells, which results in alterations of their cellular properties. No specific Na+ sensor or receptor has been identified in plants for salt stress other than the SOS pathway. Increasing productivity under salt-affected soils necessitates conventional breeding supplemented with biotechnological interventions. However, knowledge of the genetic basis of salinity stress tolerance in the breeding pool is somewhat limited because of the complicated architecture of salinity stress tolerance, which needs to be expanded to create salt-tolerant variants with better adaptability. A comprehensive study that emphasizes the QTLs, genes and governing mechanisms for salt stress tolerance is discussed in the present study for future research in crop improvement.

Delineation of genes for a major QTL governing heat stress tolerance in chickpea

Chickpea (Cicer arietinum) is a cool season grain legume experiencing severe yield loss during heat stress due to the intensifying climate changes and its associated gradual increase of mean temperature. Hence, understanding the genetic architecture regulating heat stress tolerance has emerged as an important trait to be addressed for enhancing yield and productivity of chickpea under heat stress. The present study is intended to identify the major genomic region(s) governing heat stress tolerance in chickpea. For this, an integrated genomics-assisted breeding strategy involving NGS-based high-resolution QTL-seq assay, QTL region-specific association analysis and molecular haplotyping was deployed in a population of 206 mapping individuals and a diversity panel of 217 germplasm accessions of chickpea. This combinatorial strategy delineated a major 156.8 kb QTL genomic region, which was subsequently narrowed-down to a functional candidate gene CaHSFA5 and its natural alleles associated strongly with heat stress tolerance in chickpea. Superior natural alleles and haplotypes delineated from the CaHSFA5 gene have functional significance in regulating heat stress tolerance in chickpea. Histochemical staining, interaction studies along with differential expression profiling of CaHSFA5 and ROS scavenging genes suggest a cross talk between CaHSFA5 with ROS homeostasis pertaining to heat stress tolerance in chickpea. Heterologous gene expression followed by heat stress screening further validated the functional significance of CaHSFA5 for heat stress tolerance. The salient outcomes obtained here can have potential to accelerate multiple translational genomic analysis including marker-assisted breeding and gene editing in order to develop high-yielding heat stress tolerant chickpea varieties.

The chickpea WIP2 gene underlying a major QTL contributes to lateral root development

Lateral roots are a major component of root system architecture, and lateral root count (LRC) positively contributes to yield under drought in chickpea. To understand the genetic regulation of LRC, a biparental mapping population derived from two chickpea accessions having contrasting LRCs was genotyped by sequencing, and phenotyped to map four major quantitative trait loci (QTLs) contributing to 13-32% of the LRC trait variation. A single- nucleotide polymorphism tightly linked to the locus contributing to highest trait variation was located on the coding region of a gene (CaWIP2), orthologous to NO TRANSMITTING TRACT/WIP domain protein 2 (NTT/WIP2) gene of Arabidopsis thaliana. A polymorphic simple sequence repeat (SSR) in the CaWIP2 promoter showed differentiation between low versus high LRC parents and mapping individuals, suggesting its utility for marker-assisted selection. CaWIP2 promoter showed strong expression in chickpea apical root meristem and lateral root primordia. Expression of CaWIP2 under its native promoter in the Arabidopsis wip2wip4wip5 mutant rescued its rootless phenotype to produce more lateral roots than the wild-type plants, and led to formation of amyloplasts in the columella. CaWIP2 expression also induced the expression of genes that regulate lateral root emergence. Our study identified a gene-based marker for LRC which will be useful for developing drought-tolerant, high-yielding chickpea varieties.

Functional allele of a MATE gene selected during domestication modulates seed color in chickpea

Seed color is one of the key target traits of domestication and artificial selection in chickpeas due to its implications on consumer preference and market value. The complex seed color trait has been well dissected in several crop species; however, the genetic mechanism underlying seed color variation in chickpea remains poorly understood. Here, we employed an integrated genomics strategy involving QTL mapping, high-density mapping, map-based cloning, association analysis, and molecular haplotyping in an inter-specific RIL mapping population, association panel, wild accessions, and introgression lines (ILs) of Cicer gene pool. This delineated a MATE gene, CaMATE23, encoding a Transparent Testa (TT) and its natural allele (8-bp insertion) and haplotype underlying a major QTL governing seed color on chickpea chromosome 4. Signatures of selective sweep and a strong purifying selection reflected that CaMATE23, especially its 8-bp insertion natural allelic variant, underwent selection during chickpea domestication. Functional investigations revealed that the 8-bp insertion containing the third cis-regulatory RY-motif element in the CaMATE23 promoter is critical for enhanced binding of CaFUSCA3 transcription factor, a key regulator of seed development and flavonoid biosynthesis, thereby affecting CaMATE23 expression and proanthocyanidin (PA) accumulation in the seed coat to impart varied seed color in chickpea. Consequently, overexpression of CaMATE23 in Arabidopsis tt12 mutant partially restored the seed color phenotype to brown pigmentation, ascertaining its functional role in PA accumulation in the seed coat. These findings shed new light on the seed color regulation and evolutionary history, and highlight the transcriptional regulation of CaMATE23 by CaFUSCA3 in modulating seed color in chickpea. The functionally relevant InDel variation, natural allele, and haplotype from CaMATE23 are vital for translational genomic research, including marker-assisted breeding, for developing chickpea cultivars with desirable seed color that appeal to consumers and meet global market demand.

Whole-genome sequencing based discovery of candidate genes and diagnostic markers for seed weight in groundnut

Seed weight in groundnut (Arachis hypogaea L.) has direct impact on yield as well as market price because of preference for bold seeds by consumers and industry, thereby making seed-size improvement as one of the most important objectives of groundnut breeding programs globally. Marker-based early generation selection can accelerate the process of breeding for developing large-seeded varieties. In this context, we deployed the quantitative trait locus-sequencing (QTL-seq) approach on a biparental mapping population (Chico × ICGV 02251) to identify candidate genes and develop markers for seed weight in groundnut. A total of 289.4-389.4 million reads sequencing data were generated from three libraries (ICGV 02251 and two extreme bulks) achieving 93.9-95.1% genome coverage and 8.34-9.29× average read depth. The analysis of sequencing data using QTL-seq pipeline identified five genomic regions (three on chromosome B06 and one each on chromosomes B08 and B09) for seed weight. Detailed analysis of above associated genomic regions detected 182 single-nucleotide polymorphisms (SNPs) in genic and intergenic regions, and 11 of these SNPs were nonsynonymous in the genomic regions of 10 candidate genes including Ulp proteases and BIG SEED locus genes. Kompetitive allele specific polymerase chain reaction (KASP) markers for 14 SNPs were developed, and four of these markers (snpAH0031, snpAH0033, snpAH0037, and snpAH0038) were successfully validated for deployment in breeding for large-seeded groundnut varieties.

Mitochondrial Inner Membrane ABC Transporter Bcmdl1 Is Involved in Conidial Germination, Virulence, and Resistance to Anilinopyrimidine Fungicides in Botrytis cinerea

Botrytis cinerea causes gray mold on thousands of plants, leading to huge losses in production. Anilinopyrimidine (AP) fungicides have been applied to control B. cinerea since the 1990s. Although resistance to AP fungicides was detected soon after their application, the mechanism of AP resistance remains to be elucidated. In this study, a sexual cross between resistant and sensitive isolates was performed, and the genomes of parental isolates and progenies were sequenced to identify resistance-related single nucleotide polymorphisms (SNPs). After screening and verification, mutation E407K in the Bcmdl1 gene was identified and confirmed to confer resistance to AP fungicides in B. cinerea. Bcmdl1 was predicted to encode a mitochondrial protein that belonged to a half-type ATP-binding cassette (ABC) transporter. Although Bcmdl1 was a transporter, it did not mediate resistance to multiple fungicides but mediated resistance specifically to AP fungicides. On the other hand, reductions in conidial germination and virulence were observed in Bcmdl1 knockout transformants compared to the parental isolate and complemented transformants, illustrating the biological functions of Bcmdl1. Subcellular localization analysis indicated that Bcmdl1 was localized in mitochondria. Interestingly, the production of ATP was reduced after cyprodinil treatment in Bcmdl1 knockout transformants, suggesting that Bcmdl1 was involved in ATP synthesis. Since Mdl1 could interact with ATP synthase in yeast, we hypothesize that Bcmdl1 forms a complex with ATP synthase, which AP fungicides might target, thereby interfering with the metabolism of energy. IMPORTANCE Gray mold, caused by B. cinerea, causes huge losses in the production of many fruits and vegetables. AP fungicides have been largely adopted to control this disease since the 1990s, and the development of resistance to AP fungicides initiates new problems for disease control. Due to the unknown mode of action, information on the mechanism of AP resistance is also limited. Recently, mutations in mitochondrial genes were reported to be related to AP resistance. However, the mitochondrial process of these genes remains to be elucidated. In this study, we identified several AP resistance-related mutations by quantitative trait locus sequencing (QTL-seq) and confirmed that mutation E407K in Bcmdl1 conferred AP resistance. We further characterized the expression patterns, biological functions, subcellular localization, and mitochondrial processes of the Bcmdl1 gene. This study deepens our understanding of the mechanism of resistance to and mode of action of AP fungicides.

Fine mapping and causal gene identification of a novel QTL for early flowering by QTL-seq, Target-seq and RNA-seq in spring oilseed rape

A novel quantitative trait locus for early flowering in spring oilseed rape, BnaC08cqDTF, was mapped to an 86-kb region on chromosome C08, and its causal gene, CRY2, was uncovered. Days to flowering is a very important agronomic and adaptive trait of Brassica napus oilseed rape (AACC, 2n = 38). We previously identified BnaC08cqDTF as a novel candidate quantitative trait locus (QTL) for early flowering in spring oilseed rape. Here, we present fine mapping of the locus and a study of its causal gene. Initial mapping was performed by QTL sequencing of DNA pools of BC₃F₂ plants with extreme flowering times derived from crosses between the spring-type cv. No. 4512 (early flowering) and cv. No. 5246 (late flowering), along with fine mapping by target sequencing of the BC₃F₂ and BC₄F₂ populations. Fine mapping narrowed down BnaC08cqDTF to an 86-kb region on chromosome C08. The region harbored fifteen genes. After comparative analyses of the DNA sequences for mutation between A and C syntenic regions and detected by RNA-seq and qRT-PCR between the two parents, we found that BnaC08G0010400ZS harbors an A/G nonsynonymous mutation in exon 3. This single nucleotide polymorphism (SNP) haplotype was also correlated with early flowering in a 256 accession panel. BnaC08G0010400ZS is a homolog of the AT1G04400 gene (CRY2) in Arabidopsis. The analyses of transgenic Arabidopsis verified that BnaC08G0010400ZS is responsible for early flowering. Our results contribute to a better understanding of the genetic control mechanism of early flowering in spring Brassica napus and will promote the breeding for early mature varieties.

Whole genome resequencing identifies candidate genes and allelic diagnostic markers for resistance to Ralstonia solanacearum infection in cultivated peanut (Arachis hypogaea L.)

Bacterial wilt disease (BWD), caused by Ralstonia solanacearum is a major challenge for peanut production in China and significantly affects global peanut field productivity. It is imperative to identify genetic loci and putative genes controlling resistance to R. solanacearum (RRS). Therefore, a sequencing-based trait mapping approach termed "QTL-seq" was applied to a recombination inbred line population of 581 individuals from the cross of Yueyou 92 (resistant) and Xinhuixiaoli (susceptible). A total of 381,642 homozygous single nucleotide polymorphisms (SNPs) and 98,918 InDels were identified through whole genome resequencing of resistant and susceptible parents for RRS. Using QTL-seq analysis, a candidate genomic region comprising of 7.2 Mb (1.8-9.0 Mb) was identified on chromosome 12 which was found to be significantly associated with RRS based on combined Euclidean Distance (ED) and SNP-index methods. This candidate genomic region had 180 nonsynonymous SNPs and 14 InDels that affected 75 and 11 putative candidate genes, respectively. Finally, eight nucleotide binding site leucine rich repeat (NBS-LRR) putative resistant genes were identified as the important candidate genes with high confidence. Two diagnostic SNP markers were validated and revealed high phenotypic variation in the different resistant and susceptible RIL lines. These findings advocate the expediency of the QTL-seq approach for precise and rapid identification of candidate genomic regions, and the development of diagnostic markers that are applicable in breeding disease-resistant peanut varieties.

Identification of Candidate Genes for Rind Color and Bloom Formation in Watermelon Fruits Based on a Quantitative Trait Locus-Seq

Watermelon fruit rind color (RC) and bloom formation (BF) affect product value and consumer preference. However, information on the candidate gene(s) for additional loci involved in dark green (DG) RC and the genetic control of BF and its major chemical components is lacking. Therefore, this study aimed to identify loci controlling RC and BF using QTL-seq of the F₂ population derived by crossing 'FD061129' with light-green rind and bloom and 'SIT55616RN' with DG rind and bloomless. Phenotypic evaluation of the F₁ and 219 F₂ plants indicated the genetic control of two complementary dominant loci, G₁ and G₂, for DG and a dominant locus, Bf, for BF. QTL-seq identified a genomic region on Chr.6 for G₁, Chr.8 for G₂, and Chr.1 for Bf. G₁ and G₂ helped determine RC with possible environmental effects. Chlorophyll a-b binding protein gene-based CAPS (RC-m5) at G₁ matched the highest with the RC phenotype. In the 1.4 cM Bf map interval, two additional gene-based CAPS markers were designed, and the CAPS for a nonsynonymous SNP in Cla97C01G020050, encoding a CSC1-like protein, cosegregated with the BF trait in 219 F₂ plants. Bloom powder showed a high Ca²⁺ concentration (16,358 mg·kg^-1), indicating that the CSC1-like protein gene is possibly responsible for BF. Our findings provide valuable information for marker-assisted selection for RC and BF and insights into the functional characterization of genes governing these watermelon-fruit-related traits.

Genome-wide analysis suggests the potential role of lncRNAs during seed development and seed size/weight determination in chickpea

The integrated transcriptome data analyses suggested the plausible roles of lncRNAs during seed development in chickpea. The candidate lncRNAs associated with QTLs and those involved in miRNA-mediated seed size/weight determination in chickpea have been identified. Long non-coding RNAs (lncRNAs) are important regulators of various biological processes. Here, we identified lncRNAs at seven successive stages of seed development in small-seeded and large-seeded chickpea cultivars. In total, 4751 lncRNAs implicated in diverse biological processes were identified. Most of lncRNAs were conserved between the two cultivars, whereas only a few of them were conserved in other plants, suggesting their species-specificity. A large number of lncRNAs differentially expressed between the two chickpea cultivars associated with seed development-related processes were identified. The lncRNAs acting as precursors of miRNAs and those mimicking target protein-coding genes of miRNAs involved in seed size/weight determination, including HAIKU1, BIG SEEDS1, and SHB1, were also revealed. Further, lncRNAs located within seed size/weight associated quantitative trait loci were also detected. Overall, we present a comprehensive resource and identified candidate lncRNAs that may play important roles during seed development and seed size/weight determination in chickpea.

Discovery of stripe rust resistance with incomplete dominance in wild emmer wheat using bulked segregant analysis sequencing

Durable crop disease resistance is an essential component of global food security. Continuous pathogen evolution leads to a breakdown of resistance and there is a pressing need to characterize new resistance genes for use in plant breeding. Here we identified an accession of wild emmer wheat (Triticum turgidum ssp. dicoccoides), PI 487260, that is highly resistant to multiple stripe rust isolates. Genetic analysis revealed resistance was conferred by a single, incompletely dominant gene designated as Yr84. Through bulked segregant analysis sequencing (BSA-Seq) we identified a 52.7 Mb resistance-associated interval on chromosome 1BS. Detected variants were used to design genetic markers for recombinant screening, further refining the interval of Yr84 to a 2.3-3.3 Mb in tetraploid wheat genomes. This interval contains 34 candidate genes encoding for protein domains involved in disease resistance responses. Furthermore, KASP markers closely-linked to Yr84 were developed to facilitate marker-assisted selection for rust resistance breeding.

Harnessing the potential of bulk segregant analysis sequencing and its related approaches in crop breeding

Most plant traits are governed by polygenes including both major and minor genes. Linkage mapping and positional cloning have contributed greatly to mapping genomic loci controlling important traits in crop species. However, they are low-throughput, time-consuming, and have low resolution due to which their efficiency in crop breeding is reduced. In this regard, the bulk segregant analysis sequencing (BSA-seq) and its related approaches, viz., quantitative trait locus (QTL)-seq, bulk segregant RNA-Seq (BSR)-seq, and MutMap, have emerged as efficient methods to identify the genomic loci/QTLs controlling specific traits at high resolution, accuracy, reduced time span, and in a high-throughput manner. These approaches combine BSA with next-generation sequencing (NGS) and enable the rapid identification of genetic loci for qualitative and quantitative assessments. Many previous studies have shown the successful identification of the genetic loci for different plant traits using BSA-seq and its related approaches, as discussed in the text with details. However, the efficiency and accuracy of the BSA-seq depend upon factors like sequencing depth and coverage, which enhance the sequencing cost. Recently, the rapid reduction in the cost of NGS together with the expected cost reduction of third-generation sequencing in the future has further increased the accuracy and commercial applicability of these approaches in crop improvement programs. This review article provides an overview of BSA-seq and its related approaches in crop breeding together with their merits and challenges in trait mapping.

Exploring Chickpea Germplasm Diversity for Broadening the Genetic Base Utilizing Genomic Resourses

Legume crops provide significant nutrition to humans as a source of protein, omega-3 fatty acids as well as specific macro and micronutrients. Additionally, legumes improve the cropping environment by replenishing the soil nitrogen content. Chickpeas are the second most significant staple legume food crop worldwide behind dry bean which contains 17%–24% protein, 41%–51% carbohydrate, and other important essential minerals, vitamins, dietary fiber, folate, β-carotene, anti-oxidants, micronutrients (phosphorus, calcium, magnesium, iron, and zinc) as well as linoleic and oleic unsaturated fatty acids. Despite these advantages, legumes are far behind cereals in terms of genetic improvement mainly due to far less effort, the bottlenecks of the narrow genetic base, and several biotic and abiotic factors in the scenario of changing climatic conditions. Measures are now called for beyond conventional breeding practices to strategically broadening of narrow genetic base utilizing chickpea wild relatives and improvement of cultivars through advanced breeding approaches with a focus on high yield productivity, biotic and abiotic stresses including climate resilience, and enhanced nutritional values. Desirable donors having such multiple traits have been identified using core and mini core collections from the cultivated gene pool and wild relatives of Chickpea. Several methods have been developed to address cross-species fertilization obstacles and to aid in inter-specific hybridization and introgression of the target gene sequences from wild Cicer species. Additionally, recent advances in “Omics” sciences along with high-throughput and precise phenotyping tools have made it easier to identify genes that regulate traits of interest. Next-generation sequencing technologies, whole-genome sequencing, transcriptomics, and differential genes expression profiling along with a plethora of novel techniques like single nucleotide polymorphism exploiting high-density genotyping by sequencing assays, simple sequence repeat markers, diversity array technology platform, and whole-genome re-sequencing technique led to the identification and development of QTLs and high-density trait mapping of the global chickpea germplasm. These altogether have helped in broadening the narrow genetic base of chickpeas.

Evaluation of nine statistics to identify QTLs in bulk segregant analysis using next generation sequencing approaches

Background

Bulk segregant analysis (BSA) combined with next generation sequencing is a powerful tool to identify quantitative trait loci (QTL). The impact of the size of the study population and the percentage of extreme genotypes analysed have already been assessed. But a good comparison of statistical approaches designed to identify QTL regions using next generation sequencing (NGS) technologies for BSA is still lacking.

Results

We developed an R code to simulate QTLs in bulks of F2 contrasted lines. We simulated a range of recombination rates based on estimations using different crop species. The simulations were used to benchmark the ability of statistical methods identify the exact location of true QTLs. A single QTL led to a shift in allele frequency across a large fraction of the chromosome for plant species with low recombination rate. The smoothed version of all statistics performed best notably the smoothed Euclidean distance-based statistics was always found to be more accurate in identifying the location of QTLs. We propose a simulation approach to build confidence interval statistics for the detection of QTLs.

Conclusion

We highlight the statistical methods best suited for BSA studies using NGS technologies in crops even when recombination rate is low. We also provide simulation codes to build confidence intervals and to assess the impact of recombination for application to other studies. This computational study will help select NGS-based BSA statistics that are useful to the broad scientific community.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08718-y.

Genetic dissection of heterotic loci associated with plant weight by Graded pool-seq in heading Chinese cabbage (Brassica rapa)

Four heterotic QTL and a heterozygous segment for plant weight were identified by Graded Pool-Seq, QTL-seq and traditional genetic linkage analysis in heading Chinese cabbage. Heading Chinese cabbage (Brassica rapa L. spp. pekinensis) is a cross-pollinated leafy vegetable with significant heterosis. The use of heterosis is important for breeding high-yield Chinese cabbage hybrids. However, the formation and mechanism of heterosis have not been studied. We dissected the molecular mechanism of heterosis of yield-related traits in Chinese cabbage. An F₁ hybrid with high-parent heterosis of yield-related traits was selected and self-pollinated to generate segregating F₂ populations. QTL-seq, Graded Pool-seq (GPS), and traditional genetic linkage analysis were used to identify four heterotic quantitative trait loci (QTL) for plant weight: qPW1.1, qPW5.1, qPW7.1, and qPW8.1. Traditional genetic linkage analysis over two years showed that qPW8.1, located in marker A08_S45 (18,172,719) and A08_S85 (18,196,752), was mapped to a 23.5 kb genomic region. QTL qPW8.1 explained 8.6% and 23.6% of the phenotypic variation in plant weight and the total numbers of head leaves, respectively, and contained a heterozygous segment that might control the heterosis of plant weight. The qPW1.1 made an 11.7% phenotypic contribution to plant weight. The qPW7.1 was sensitive to environmental influence and explained 10.7% of the phenotypic variance. QTL qPW5.1 had a significant signal and was located in a genetic region near the centromere showing high heterozygosity. The "pseudo-overdominance" and "synergistic allelic" effects from parent line "XJD4" appear to play an important role in heterosis for plant weight in Chinese cabbage. These results provide a basis for an improved understanding of the molecular mechanism of yield-related traits and their heterosis.

QTL-seq for the identification of candidate genes for days to flowering and leaf shape in pigeonpea

To identify genomic segments associated with days to flowering (DF) and leaf shape in pigeonpea, QTL-seq approach has been used in the present study. Genome-wide SNP profiling of extreme phenotypic bulks was conducted for both the traits from the segregating population (F₂) derived from the cross combination- ICP 5529 × ICP 11605. A total of 126.63 million paired-end (PE) whole-genome resequencing data were generated for five samples, including one parent ICP 5529 (obcordate leaf and late-flowering plant), early and late flowering pools (EF and LF) and obcordate and lanceolate leaf shape pools (OLF and LLS). The QTL-seq identified two significant genomic regions, one on CcLG03 (1.58 Mb region spanned from 19.22 to 20.80 Mb interval) for days to flowering (LF and EF pools) and another on CcLG08 (2.19 Mb region spanned from 6.69 to 8.88 Mb interval) for OLF and LLF pools, respectively. Analysis of genomic regions associated SNPs with days to flowering and leaf shape revealed 5 genic SNPs present in the unique regions. The identified genomic regions for days to flowering were also validated with the genotyping-by-sequencing based classical QTL mapping method. A comparative analysis of the identified seven genes associated with days to flowering on 12 Fabaceae genomes, showed synteny with 9 genomes. A total of 153 genes were identified through the synteny analysis ranging from 13 to 36. This study demonstrates the usefulness of QTL-seq approach in precise identification of candidate gene(s) for days to flowering and leaf shape which can be deployed for pigeonpea improvement.

QTL-seq approach was utilized for mapping of genomic regions/genes associated with days to flowering and leaf shape in pigeonpea. Analysis of genomic regions and associated SNPs with days to flowering and leaf shape revealed 1 and 4 non-synonymous SNPs, respectively. The study demonstrated sequencing-based trait mapping approach can accelerate trait mapping of the targeted traits.

Optimization of BSA-seq experiment for QTL mapping

Deep sequencing-based bulked segregant analysis (BSA-seq) has become a popular approach for quantitative trait loci (QTL) mapping in recent years. Effective statistical methods for BSA-seq have been developed, but how to design a suitable experiment for BSA-seq remains unclear. In this paper, we show in theory how the major experimental factors (including population size, pool proportion, pool balance, and generation) and the intrinsic factors of a QTL (including heritability and degree of dominance) affect the power of QTL detection and the precision of QTL mapping in BSA-seq. Increasing population size can improve the power and precision, depending on the QTL heritability. The best proportion of each pool in the population is around 0.25. So, 0.25 is generally applicable in BSA-seq. Small pool proportion can greatly reduce the power and precision. Imbalance of pool pair in size also causes decrease of the power and precision. Additive effect is more important than dominance effect for QTL mapping. Increasing the generation of filial population produced by selfing can significantly increase the power and precision, especially from F2 to F3. These findings enable researchers to optimize the experimental design for BSA-seq. A web-based program named BSA-seq Design Tool is available at http://124.71.74.135/BSA-seqDesignTool/ and https://github.com/huanglikun/BSA-seqDesignTool.

The genetics of vigour-related traits in chickpea (Cicer arietinum L.): insights from genomic data

QTL controlling vigour and related traits were identified in a chickpea RIL population and validated in diverse sets of germplasm. Robust KASP markers were developed for marker-assisted selection. To understand the genetic constitution of vigour in chickpea (Cicer arietinum L.), genomic data from a bi-parental population and multiple diversity panels were used to identify QTL, sequence-level haplotypes and genetic markers associated with vigour-related traits in Australian environments. Using 182 Recombinant Inbred Lines (RILs) derived from a cross between two desi varieties, Rupali and Genesis836, vigour QTL independent of flowering time were identified on chromosomes (Ca) 1, 3 and 4 with genotypic variance explained (GVE) ranging from 7.1 to 28.8%. Haplotype analysis, association analysis and graphical genotyping of whole-genome re-sequencing data of two diversity panels consisting of Australian and Indian genotypes and an ICRISAT Chickpea Reference Set revealed a deletion in the FTa1-FTa2-FTc gene cluster of Ca3 significantly associated with vigour and flowering time. Across the RIL population and diversity panels, the impact of the deletion was consistent for vigour but not flowering time. Vigour-related QTL on Ca4 co-located with a QTL for seed size in Rupali/Genesis836 (GVE = 61.3%). Using SNPs from this region, we developed and validated gene-based KASP markers across different panels. Two markers were developed for a gene on Ca1, myo -inositol monophosphatase (CaIMP), previously proposed to control seed size, seed germination and seedling growth in chickpea. While associated with vigour in the diversity panels, neither the markers nor broader haplotype linked to CaIMP was polymorphic in Rupali/Genesis836. Importantly, vigour appears to be controlled by different sets of QTL across time and with components which are independent from phenology.

Comparative QTL mapping for male sterility of cultivated strawberry (Fragaria × ananassa Duch.) using different reference genome sequences

Male sterility is one of the reproductive isolation systems in plants and quite useful for F₁ seed production. We previously identified three independent quantitative trait loci (QTLs) for male sterility of cultivated strawberry, Here, we identified the specific subgenomes in which these QTLs are located by QTL-seq approach. QTLs qMS4.1, qMS4.2, and qMS4.3 were mapped separately in subgenomes Fvb4-4, Fvb4-3, and Fvb4-1, respectively, in 'Camarosa' genome assembly v. 1.0.a1. Candidate regions of qMS4.1 and qMS4.3 were clearly detected around 12-26 Mb in Fvb4-4 and 12-14 Mb in Fvb4-1, respectively; those of qMS4.2 were fragmented in Fvb4-3, which suggests that some scaffolds were incorrectly assembled in Fvb4-3. qMS4.3 was mapped to chr4X1 of 'Reikou' genome assembly r2.3, and qMS4.1 and qMS4.2 were both mapped to chr4Av, which indicates that differentiation of the subgenomes in which both QTLs are located was insufficient in 'Reikou' r2.3. Although 'Camarosa' genome assembly v. 1.0.a1 is an unphased map, which merges homologous chromosomes into one sequence, 'Reikou' genome assembly r2.3 is a phased map, which separates homologous chromosomes. QTL mapping to different reference genomes clearly showed the specific features of each reference genome, and that using different kinds of reference map could accelerate fine mapping and map-based cloning of certain genes of cultivated strawberry.

Identification of blossom-end rot loci using joint QTL-seq and linkage-based QTL mapping in tomato

Blossom-End Rot is Quantitatively Inherited and Maps to Four Loci in Tomato. Blossom-end rot (BER) is a devastating physiological disorder that affects tomato and other vegetables, resulting in significant crop losses. To date, most studies on BER have focused on the environmental factors that affect calcium translocation to the fruit; however, the genetic basis of this disorder remains unknown. To investigate the genetic basis of BER, two F₂ and F_3:4 populations along with a BC₁ population that segregated for BER occurrence were evaluated in the greenhouse. Using the QTL-seq approach, quantitative trait loci (QTL) associated with BER Incidence were identified at the bottom of chromosome (ch) 3 and ch11. Additionally, linkage-based QTL mapping detected another QTL, BER3.1, on ch3 and BER4.1 on ch4. To fine map the QTLs identified by QTL-seq, recombinant screening was performed. BER3.2, the major BER QTL on ch3, was narrowed down from 5.68 to 1.58 Mbp with a 1.5-LOD support interval (SI) corresponding to 209 candidate genes. BER3.2 colocalizes with the fruit weight gene FW3.2/SlKLUH, an ortholog of cytochrome P450 KLUH in Arabidopsis. Further, BER11.1, the major BER QTL on ch11, was narrowed down from 3.99 to 1.13 Mbp with a 1.5-LOD SI interval comprising of 141 candidate genes. Taken together, our results identified and fine mapped the first loci for BER resistance in tomato that will facilitate marker-assistant breeding not only in tomato but also in many other vegetables suffering for BER.

Combining QTL-seq and linkage mapping to fine map a candidate gene in qCTS6 for cold tolerance at the seedling stage in rice

BACKGROUND

Cold stress caused by low temperatures is an important factor restricting rice production. Identification of cold-tolerance genes that can stably express in cold environments is crucial for molecular rice breeding.

RESULTS

In this study, we employed high-throughput quantitative trait locus sequencing (QTL-seq) analyses in a 460-individual F2:3 mapping population to identify major QTL genomic regions governing cold tolerance at the seedling stage in rice. A novel major QTL (qCTS6) controlling the survival rate (SR) under low-temperature conditions of 9°C/10 days was mapped on the 2.60-Mb interval on chromosome 6. Twenty-seven single-nucleotide polymorphism (SNP) markers were designed for the qCST6 region based on re-sequencing data, and local QTL mapping was conducted using traditional linkage analysis. Eventually, we mapped qCTS6 to a 96.6-kb region containing 13 annotated genes, of which seven predicted genes contained 13 non-synonymous SNP loci. Quantitative reverse transcription PCR analysis revealed that only Os06g0719500, an OsbZIP54 transcription factor, was strongly induced by cold stress. Haplotype analysis confirmed that +376 bp (T>A) in the OsbZIP54 coding region played a key role in regulating cold tolerance in rice.

CONCLUSION

We identified OsbZIP54 as a novel regulatory gene associated with rice cold-responsive traits, with its Dongfu-104 allele showing specific cold-induction expression serving as an important molecular variation for rice improvement. This result is expected to further exploration of the genetic mechanism of rice cold tolerance at the seedling stage and improve cold tolerance in rice varieties by marker-assisted selection.

Genome resequencing reveals DNA polymorphisms associated with seed size/weight determination in chickpea

Crop productivity in legumes is determined by number and size/weight of seeds. To understand the genetic basis of seed size/weight in chickpea, we performed genome resequencing of 13 small- and 5 large-seeded genotypes using Illumina platform. Single nucleotide polymorphisms (SNPs) and insertions/deletions (InDels) differentiating small- and large-seeded genotypes were identified. A total of 17,902 SNPs and 2594 InDels located in promoter and/or coding regions that may contribute to seed size/weight were detected. Of these, 266 SNPs showed significant association with seed size/weight trait. Twenty-three genes including those involved in cell growth/division, encoding transcription factors and located within QTLs associated with seed size/weight harbored SNPs within transcription factor binding motif(s) and/or coding region. The non-synonymous SNPs were found to affect the mutational sensitivity and stability of the encoded proteins. Overall, we provided a high-quality SNP map for large-scale genotyping applications and identified candidate genes that determine seed size/weight in chickpea.

Identification of Candidate Genes Conferring Cold Tolerance to Rice (Oryza sativa L.) at the Bud-Bursting Stage Using Bulk Segregant Analysis Sequencing and Linkage Mapping

Low-temperature tolerance during the bud-bursting stage is an important characteristic of direct-seeded rice. The identification of cold-tolerance quantitative trait loci (QTL) in species that can stably tolerate cold environments is crucial for the molecular breeding of rice with such traits. In our study, high-throughput QTL-sequencing analyses were performed in a 460-individual F_{2 : 3} mapping population to identify the major QTL genomic regions governing cold tolerance at the bud-bursting (CTBB) stage in rice. A novel major QTL, qCTBB9, which controls seed survival rate (SR) under low-temperature conditions of 5°C/9 days, was mapped on the 5.40-Mb interval on chromosome 9. Twenty-six non-synonymous single-nucleotide polymorphism (nSNP) markers were designed for the qCTBB9 region based on re-sequencing data and local QTL mapping conducted using traditional linkage analysis. We mapped qCTBB9 to a 483.87-kb region containing 58 annotated genes, among which six predicted genes contained nine nSNP loci. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis revealed that only Os09g0444200 was strongly induced by cold stress. Haplotype analysis further confirmed that the SNP 1,654,225 bp in the Os09g0444200 coding region plays a key role in regulating the cold tolerance of rice. These results suggest that Os09g0444200 is a potential candidate for qCTBB9. Our results are of great significance to explore the genetic mechanism of rice CTBB and to improve the cold tolerance of rice varieties by marker-assisted selection.

Genome-wide profiling of miRNAs during seed development reveals their functional relevance in seed size/weight determination in chickpea

MicroRNAs (miRNAs) are non-coding small RNAs that regulate gene expression at transcriptional and post-transcriptional levels. The role of miRNAs in seed development and seed size/weight determination is poorly understood in legumes. In this study, we profiled miRNAs at seven successive stages of seed development in a small-seeded and a large-seeded chickpea cultivar via small RNA sequencing. In total, 113 known and 243 novel miRNAs were identified. Gene ontology analysis revealed the enrichment of seed/reproductive/post-embryonic development and signaling pathways processes among the miRNA target genes. A large fraction of the target genes exhibited antagonistic correlation with miRNA expression. The sets of co-expressed miRNAs showing differential expression between the two cultivars were recognized. Known transcription factor (TF) encoding genes involved in seed size/weight determination, including SPL, GRF, MYB, ARF, HAIKU1, SHB1, KLUH/CYP78A5, and E2Fb along with novel genes were found to be targeted by the predicted miRNAs. Differential expression analysis revealed higher transcript levels of members of SPL and REVOLUTA TF families and lower expression of their corresponding miRNAs in the large-seeded cultivar. At least 19 miRNAs known to be involved in seed development or differentially expressed between small-seeded and large-seeded cultivars at late-embryogenesis and/or mid-maturation stages were located within known quantitative trait loci (QTLs) associated with seed size/weight determination. Moreover, 41 target genes of these miRNAs were also located within these QTLs. Altogether, we revealed important roles of miRNAs in seed development and identified candidate miRNAs and their target genes that have functional relevance in determining seed size/weight in chickpea.

QTL-seq analysis of powdery mildew resistance in a Korean cucumber inbred line

QTL mapping and RT-PCR analyses identified the CsGy5G015660 as a strong powdery mildew resistance candidate gene and natural variation of CsGy5G015660 allele was observed using 115 core germplasm. Powdery mildew (PM) is among the most serious fungal diseases encountered in the cultivation of cucurbits. The development of PM-resistant inbred lines is thus of considerable significance for cucumber breeding programs. In this study, we applied bulked segregant analysis combined with QTL-seq to identify PM resistance loci using F₂ population derived from a cross between two Korean cucumber inbred lines, PM-R (resistant) and PM-S (susceptible). Genome-wide SNP profiling using bulks of the two extreme phenotypes identified two QTLs on chromosomes 5 and 6, designated pm5.2 and pm6.1, respectively. The two PM resistance loci were validated using molecular marker-based classical QTL analysis: pm5.2 (30% R² at LOD 11) and pm6.1 (11% R² at LOD 3.2). Furthermore, reverse transcriptase-PCR analyses, using genes found to be polymorphic between PM-R and PM-S, were conducted to identify the candidate gene(s) responsible for PM resistance. We found that transcripts of the gene CsGy5G015660, encoding a putative leucine-rich repeat receptor-like serine/threonine-protein kinase (RPK2), showed specific accumulation in PM-R prior to the appearance of disease symptoms, and was accordingly considered a strong candidate gene for PM resistance. In addition, cleaved amplified polymorphic sequence markers from CsGy5G015660 were developed and used to screen 35 inbred lines. Natural variation in the CsGy5G015660 allele was also observed based on analysis of a core collection of 115 cucumber accessions. Our results provide new genetic insights for gaining a better understanding of the genetic basis of PM resistance in cucumber, and pave the way for further utilization in cucumber PM resistance breeding programs.

A Robust and Rapid Candidate Gene Mapping Pipeline Based on M2 Populations

The whole-genome sequencing-based bulked segregant analysis (WGS-BSA) has facilitated the mapping candidate causal variations for cloning target plant genes. Here, we report an improved WGS-BSA method termed as M2-seq to expedite the mapping candidate mutant loci by studying just M₂ generation. It is an efficient mutant gene mapping tool, rapid, and comparable to the previously reported approaches, such as Mutmap and Mutmap+ that require studying M₃ or advanced selfed generations. In M2-seq, background variations among the M₂ populations can be removed efficiently without knowledge of the variations of the wild-type progenitor plant. Furthermore, the use of absolute delta single-nucleotide polymorphism (SNP) index values can effectively remove the background variation caused by repulsion phase linkages of adjacent mutant alleles; and thereby facilitating the identification of the causal mutation in target genes. Here, we demonstrated the application of M2-seq in successfully mapping the genomic regions harboring causal mutations for mutant phenotypes among 10 independent M₂ populations of soybean. The mapping candidate mutant genes just in M₂ generation with the aid of the M2-seq method should be particularly useful in expediting gene cloning especially among the plant species with long generation time.

QTL-seq identifies BnaFT.A02 and BnaFLC.A02 as candidates for variation in vernalization requirement and response in winter oilseed rape (Brassica napus)

Winter, spring and biennial varieties of Brassica napus that vary in vernalization requirement are grown for vegetable and oil production. Here, we show that the obligate or facultative nature of the vernalization requirement in European winter oilseed rape is determined by allelic variation at a 10 Mbp region on chromosome A02. This region includes orthologues of the key floral regulators FLOWERING LOCUS C (BnaFLC.A02) and FLOWERING LOCUS T (BnaFT.A02). Polymorphism at BnaFLC.A02 and BnaFT.A02, mostly in cis-regulatory regions, results in distinct gene expression dynamics in response to vernalization treatment. Our data suggest allelic variation at BnaFT.A02 is associated with flowering time in the absence of vernalization, while variation at BnaFLC.A02 is associated with flowering time under vernalizing conditions. We hypothesize selection for BnaFLC.A02 and BnaFT.A02 gene expression variation has facilitated the generation of European winter oilseed rape varieties that are adapted to different winter climates. This knowledge will allow for the selection of alleles of flowering time regulators that alter the vernalization requirement of oilseed rape, informing the generation of new varieties with adapted flowering times and improved yields.

Discovery of genomic regions and candidate genes for grain weight employing next generation sequencing based QTL-seq approach in rice (Oryza sativa L.)

Rice (Oryza sativa L.) yield enhancement is one of the prime objectives of plant breeders. Elucidation of the inheritance of grain weight, a key yield component trait, is of paramount importance for raising the yield thresholds in rice. In the present investigation, we employed Next-Generation Sequencing based QTL-seq approach to identify major genomic regions associated with grain weight using mapping populations derived from a cross between BPT5204 and MTU3626. QTL-seq analysis identified three grain weight quantitative trait loci (QTL) viz., qGW1 (35-40 Mb), qGW7 (10-18 Mb), and qGW8 (2-5 Mb) on chromosomes 1, 7 and 8, respectively and all are found to be novel. Further, qGW8 was confirmed through conventional QTL mapping in F₂, F₃ and BC₁F₂ populations and found to explain the phenotypic variance of 17.88%, 16.70% and 15.00%, respectively, indicating a major QTL for grain weight. Based on previous reports, two candidate genes in the qGW8 QTL were predicted i.e., LOC_Os08g01490 (Cytochrome P450), and LOC_Os08g01680 (WD domain, G-beta repeat domain containing protein) and through in silico analysis they were found to be highly expressed in reproductive organs during different stages of grain development. Here, we have demonstrated that QTL-seq is one of the rapid approaches to uncover novel QTLs controlling complex traits. The candidate genes identified in the present study undoubtedly enhance our understanding of the mechanism and inheritance of the grain weight. These candidate genes can be exploited for yield enhancement after confirmation through complementary studies.

Next Generation Sequencing Based Forward Genetic Approaches for Identification and Mapping of Causal Mutations in Crop Plants: A Comprehensive Review

The recent advancements in forward genetics have expanded the applications of mutation techniques in advanced genetics and genomics, ahead of direct use in breeding programs. The advent of next-generation sequencing (NGS) has enabled easy identification and mapping of causal mutations within a short period and at relatively low cost. Identifying the genetic mutations and genes that underlie phenotypic changes is essential for understanding a wide variety of biological functions. To accelerate the mutation mapping for crop improvement, several high-throughput and novel NGS based forward genetic approaches have been developed and applied in various crops. These techniques are highly efficient in crop plants, as it is relatively easy to grow and screen thousands of individuals. These approaches have improved the resolution in quantitative trait loci (QTL) position/point mutations and assisted in determining the functional causative variations in genes. To be successful in the interpretation of NGS data, bioinformatics computational methods are critical elements in delivering accurate assembly, alignment, and variant detection. Numerous bioinformatics tools/pipelines have been developed for such analysis. This article intends to review the recent advances in NGS based forward genetic approaches to identify and map the causal mutations in the crop genomes. The article also highlights the available bioinformatics tools/pipelines for reducing the complexity of NGS data and delivering the concluding outcomes.

Prospects of next generation sequencing in lentil breeding

Lentil is an important food legume crop that has large and complex genome. During past years, considerable attention has been given on the use of next generation sequencing for enriching the genomic resources including identification of SSR and SNP markers, development of unigenes, transcripts, and identification of candidate genes for biotic and abiotic stresses, analysis of genetic diversity and identification of genes/ QTLs for agronomically important traits. However, in other crops including pulses, next generation sequencing has revolutionized the genomic research and helped in genomic assisted breeding rapidly and cost effectively. The present review discuss current status and future prospects of the use NGS based breeding in lentil.

Identification of SNPs and InDels associated with berry size in table grapes integrating genetic and transcriptomic approaches

BACKGROUND

Berry size is considered as one of the main selection criteria in table grapes breeding programs, due to the consumer preferences. However, berry size is a complex quantitive trait under polygenic control, and its genetic determination of berry weight is not yet fully understood. The aim of this work was to perform marker discovery using a transcriptomic approach, in order to identify and characterize SNP and InDel markers associated with berry size in table grapes. We used an integrative analysis based on RNA-Seq, SNP/InDel search and validation on table grape segregants and varieties with different genetic backgrounds.

RESULTS

Thirty SNPs and eight InDels were identified using a transcriptomic approach (RNA-Seq). These markers were selected from SNP/InDel found among segregants from a Ruby x Sultanina population with contrasting phenotypes for berry size. The set of 38 SNP and InDel markers was distributed in eight chromosomes. Genotype-phenotype association analyses were performed using a set of 13 RxS segregants and 41 table grapes varieties with different genetic backgrounds during three seasons. The results showed several degrees of association of these markers with berry size (10.2 to 30.7%) as other berry-related traits such as length and width. The co-localization of SNP and /or InDel markers and previously reported QTLs and candidate genes associated with berry size were analysed.

CONCLUSIONS

We identified a set of informative and transferable SNP and InDel markers associated with berry size. Our results suggest the suitability of SNPs and InDels as candidate markers for berry weight in seedless table grape breeding. The identification of genomic regions associated with berry weight in chromosomes 8, 15 and 17 was achieved with supporting evidence derived from a transcriptome experiment focused on SNP/InDel search, as well as from a QTL-linkage mapping approach. New regions possibly associated with berry weight in chromosomes 3, 6, 9 and 14 were identified.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Integrating genomics for chickpea improvement: achievements and opportunities

Integration of genomic technologies with breeding efforts have been used in recent years for chickpea improvement. Modern breeding along with low cost genotyping platforms have potential to further accelerate chickpea improvement efforts. The implementation of novel breeding technologies is expected to contribute substantial improvements in crop productivity. While conventional breeding methods have led to development of more than 200 improved chickpea varieties in the past, still there is ample scope to increase productivity. It is predicted that integration of modern genomic resources with conventional breeding efforts will help in the delivery of climate-resilient chickpea varieties in comparatively less time. Recent advances in genomics tools and technologies have facilitated the generation of large-scale sequencing and genotyping data sets in chickpea. Combined analysis of high-resolution phenotypic and genetic data is paving the way for identifying genes and biological pathways associated with breeding-related traits. Genomics technologies have been used to develop diagnostic markers for use in marker-assisted backcrossing programmes, which have yielded several molecular breeding products in chickpea. We anticipate that a sequence-based holistic breeding approach, including the integration of functional omics, parental selection, forward breeding and genome-wide selection, will bring a paradigm shift in development of superior chickpea varieties. There is a need to integrate the knowledge generated by modern genomics technologies with molecular breeding efforts to bridge the genome-to-phenome gap. Here, we review recent advances that have led to new possibilities for developing and screening breeding populations, and provide strategies for enhancing the selection efficiency and accelerating the rate of genetic gain in chickpea.

Identification of Genetic Locus Underlying Easy Dehulling in Rice-Tartary for Easy Postharvest Processing of Tartary Buckwheat

As a highly nutritious crop, Tartary buckwheat (Fagopyrum tartaricum) strongly adapts and grows in adverse environments and is widely grown in Asia. However, its flour contains a large proportion of the hull that adheres to the testa layer of the groats and is difficult to be removed in industrial processing. Fortunately, rice-Tartary, with the loose and non-adhering hull, provides potentiality of improving Tartary buckwheat that can dehull easily. Here, we performed high-throughput sequencing for two parents (Tartary buckwheat and rice-Tartary) and two pools (samples from the F2 population) and obtained 101 Gb raw sequencing data for further analysis. Sequencing reads were mapped to the reference genome of Tartary buckwheat, and a total of 633,256 unique SNPs and 270,181 unique indels were found in these four samples. Then, based on the Bulked Segregant Analysis (BSA), we identified a candidate genetic region, containing 45 impact SNPs/indels and 36 genes, that might underly non-adhering hull of rice-Tartary and should have value for breeding easy dehulling Tartary buckwheat.

Whole-genome resequencing-based QTL-seq identified candidate genes and molecular markers for fresh seed dormancy in groundnut

The subspecies fastigiata of cultivated groundnut lost fresh seed dormancy (FSD) during domestication and human-made selection. Groundnut varieties lacking FSD experience precocious seed germination during harvest imposing severe losses. Development of easy-to-use genetic markers enables early-generation selection in different molecular breeding approaches. In this context, one recombinant inbred lines (RIL) population (ICGV 00350 × ICGV 97045) segregating for FSD was used for deploying QTL-seq approach for identification of key genomic regions and candidate genes. Whole-genome sequencing (WGS) data (87.93 Gbp) were generated and analysed for the dormant parent (ICGV 97045) and two DNA pools (dormant and nondormant). After analysis of resequenced data from the pooled samples with dormant parent (reference genome), we calculated delta-SNP index and identified a total of 10,759 genomewide high-confidence SNPs. Two candidate genomic regions spanning 2.4 Mb and 0.74 Mb on the B05 and A09 pseudomolecules, respectively, were identified controlling FSD. Two candidate genes-RING-H2 finger protein and zeaxanthin epoxidase-were identified in these two regions, which significantly express during seed development and control abscisic acid (ABA) accumulation. QTL-seq study presented here laid out development of a marker, GMFSD1, which was validated on a diverse panel and could be used in molecular breeding to improve dormancy in groundnut.

QTL-seq for identification of loci associated with resistance to Phytophthora crown rot in squash

Phytophthora capsici Leonian, the causal agent of foliar blight, root rot, fruit rot and crown rot syndromes in squash (Cucurbita moschata), is a devastating pathogen worldwide. Resistance to Phytophthora crown rot in University of Florida breeding line #394-1-27-12 (C. moschata) is conferred by three independent dominant genes (R1R2R3). Availability of DNA markers linked to R1R2R3 genes would allow efficient breeding for Phytophthora crown rot resistance through marker-assisted selection (MAS). The goal of the current study was to identify quantitative trait loci (QTLs) associated with resistance to Phytophthora crown rot in an F₂ population (n = 168) derived from a cross between #394-1-27-12 (R) and Butter Bush (S) using QTL-seq bulk segregant analysis. Whole-genome resequencing of the resistant (n = 20) and susceptible (n = 20) bulk segregants revealed ~900,000 single nucleotide polymorphisms distributed across C. moschata genome. Three QTLs significantly (P < 0.05) associated with resistance to Phytophthora crown rot were detected on chromosome 4 (QtlPC-C04), 11 (QtlPC-C11) and 14 (QtlPC-C14). Several markers linked to these QTLs are potential targets for MAS against Phytophthora crown rot in C. moschata. The present study reports the first QTLs associated with Phytophthora crown rot resistance in C. moschata.

QTL-Seq and Sequence Assembly Rapidly Mapped the Gene BrMYBL2.1 for the Purple Trait in Brassica rapa

Anthocyanins have strong antioxidant activity and are believed to be healthy for human beings. The Brassica rapa L. ssp. chinensis var. purpurea “Zicaitai” is rich in anthocyanins. We constructed an F₂ population of Zicaitai and “Caixin” (Brassica rapa ssp. parachinensis) and it shows clear segregation of the purple phenotype (i.e., variation in anthocyanin enrichment). Here, quantitative trait locus (QTL)-Seq was performed with two sample groups from the F₂ population: one exhibiting an intense purple phenotype and the other showed a completely green phenotype. The results showed that the QTL-Seq and linkage analysis located different major loci. This indicates that there are two major genetic factors that plays different roles in regulating anthocyanin enrichment in Zicaitai. This was further supported by the data simulation of an in silico F₂ population that QTL-Seq and linkage analysis can locate different major loci. Furthermore, the draft genomes of the two parents (Zicaitai and Caixin) were assembled and utilized to search for mutations in candidate genes. A ~100-bp insertion was found in the third exon of gene BrMYBL2.1 in Zicaitai. BrMYBL2.1 is a negative regulator of anthocyanin biosynthesis, while BrEGL3.2—previously located by linkage mapping—is a positive regulator. For these populations with multiple genes contributing large effects to a trait, a strategy of low depth re-sequencing of F₂ individuals followed by QTL-Seq analysis with the free combination of sample groups is proposed. Furthermore, draft-sequence assembly of parental genomes together with QTL mapping is suggested as an efficient means for fine-mapping genes rapidly in segregating populations.

Fine Mapping of the High-pH Tolerance and Growth Trait-Related Quantitative Trait Loci (QTLs) and Identification of the Candidate Genes in Pacific White Shrimp (Litopenaeus vannamei)

High-pH tolerance and growth are important traits for the shrimp culture industry in areas with saline-alkali water. In the present study, an F1 full-sib family of Pacific white shrimp (Litopenaeus vannamei) was generated with a new "semidirectional cross" method, and double-digest restriction site-associated DNA sequencing (ddRAD-Seq) technology was applied to genotype the 2 parents and 148 progenies. A total of 3567 high-quality markers were constructed for the genetic linkage map, and the total map length was 4161.555 centimorgans (cM), showing 48 linkage groups (LGs) with an average interlocus length of 1.167 cM. With a constrained logarithm of odds (LOD) score ≥ 2.50, 12 high-pH tolerance and 2 growth (body weight) QTLs were located. L. vannamei genomic scaffolds were used to assist with the detection of 21 stress- and 5 growth-related scaffold genes. According to the high-pH transcriptome data of our previous study, 6 candidate high-pH response genes were discovered, and 5 of these 6 genes were consistently expressed with the high-pH transcriptome data, validating the locations of the high-pH tolerance trait-related QTLs in this study. This paper is the first report of fine-mapping high-pH tolerance and growth (body weight) trait QTLs in one L. vannamei genetic map. Our results will further benefit marker-assisted selection work and might be useful for promoting genomic research on the shrimp L. vannamei.

Genetic mapping of green curd gene Gr in cauliflower

Gr5.1 is the major locus for cauliflower green curd color and mapped to an interval of 236 Kbp with four most likely candidate genes. Cauliflower with colored curd enhances not only the visual appeal but also the nutritional value of the crop. Green cauliflower results from ectopic development of chloroplasts in the normal white curd. However, the underlying genetic basis is unknown. In this study, we employed QTL-seq analysis to identify the loci that were associated with green curd phenotype in cauliflower. A F2 population was generated following a cross between a white curd (Stovepipe) and a green curd (ACX800) cauliflower plants. By whole-genome resequencing and SNP analysis of green and white F2 bulks, two QTLs were detected on chromosomes 5 (Gr5.1) and 7 (Gr7.1). Validation by traditional genetic mapping with CAPS markers suggested that Gr5.1 represented a major QTL, whereas Gr7.1 had a minor effect. Subsequent high-resolution mapping of Gr5.1 in the second large F2 population with additional CAPS markers narrowed down the target region to a genetic and physical distance of 0.3 cM and 236 Kbp, respectively. This region contained 35 genes with four of them representing the best candidates for the green curd phenotype in cauliflower. They are LOC106295953, LOC106343833, LOC106345143, and LOC106295954, which encode UMP kinase, DEAD-box RNA helicase 51-like, glutathione S-transferase T3-like, and protein MKS1, respectively. These findings lay a solid foundation for the isolation of the Gr gene and provide a potential for marker-assisted selection of the green curd trait in cauliflower breeding. The eventual isolation of Gr will also facilitate better understanding of chloroplast biogenesis and development in plants.

Molecular Mapping and Candidate Gene Analysis for GA3 Responsive Short Internode in Watermelon (Citrullus lanatus)

Plants with shorter internodes are suitable for high-density planting, lodging resistance and the preservation of land resources by improving yield per unit area. In this study, we identified a locus controlling the short internode trait in watermelon using Zhengzhouzigua (long internode) and Duan125 (short internode) as mapping parents. Genetic analysis indicated that F1 plants were consistent with long internode plants, which indicates that the long internode was dominant over the short internode. The observed F2 and BC1 individuals fitted the expected phenotypic segregation ratios of 3:1 and 1:1, respectively. The locus was mapped on chromosome 9 using a bulked segregant analysis approach. The region was narrowed down to 8.525 kb having only one putative gene, Cla015407, flanking by CAPS90 and CAPS91 markers, which encodes gibberellin 3β-hydroxylase (GA 3β-hydroxylase). The sequence alignment of the candidate gene between both parents revealed a 13 bp deletion in the short internode parent, which resulted in a truncated protein. Before GA3 application, significantly lower GA3 content and shorter cell length were obtained in the short internode plants. However, the highest GA3 content and significant increase in cell length were observed in the short internode plants after exogenous GA3 application. In the short internode plants, the expression level of the Cla015407 was threefold lower than the long internode plants in the stem tissue. In general, our results suggested that Cla015407 might be the candidate gene responsible for the short internode phenotype in watermelon and the phenotype is responsive to exogenous GA3 application.

BRM: a statistical method for QTL mapping based on bulked segregant analysis by deep sequencing

Motivation

Bulked segregant analysis by deep sequencing (BSA-seq) has been widely used for quantitative trait locus (QTL) mapping in recent years. A number of different statistical methods for BSA-seq have been proposed. However, determination of significance threshold, the key point for QTL identification, remains to be a problem that has not been well solved due to the difficulty of multiple testing correction. In addition, estimation of the confidence interval is also a problem to be solved.

Results

In this paper, we propose a new statistical method for BSA-seq, named Block Regression Mapping (BRM). BRM is robust to sequencing noise and is applicable to the case of low sequencing depth. Significance threshold can be reasonably determined by taking multiple testing correction into account. Meanwhile, the confidence interval of QTL position can also be estimated.

Availability and implementation

The R scripts of our method are open source under GPLv3 license at https://github.com/huanglikun/BRM.

Supplementary information

Supplementary data are available at Bioinformatics online.

Identification of heat-tolerance QTLs and high-temperature stress-responsive genes through conventional QTL mapping, QTL-seq and RNA-seq in tomato

BACKGROUND

High temperature is one of the major abiotic stresses in tomato and greatly reduces fruit yield and quality. Identifying high-temperature stress-responsive (HSR) genes and breeding heat-tolerant varieties is an effective way to address this issue. However, there are few reports on the fine mapping of heat-tolerance quantitative trait locus (QTL) and the identification of HSR genes in tomato. Here, we applied three heat tolerance-related physiological indexes, namely, relative electrical conductivity (REC), chlorophyll content (CC) and maximum photochemical quantum efficiency (F_v/F_m) of PSII (photosystem II), as well as the phenotypic index, the heat injury index (HII), and conventional QTL analysis combined with QTL-seq technology to comprehensively detect heat-tolerance QTLs in tomato seedlings. In addition, we integrated the QTL mapping results with RNA-seq to identify key HSR genes within the major QTLs.

RESULTS

A total of five major QTLs were detected: qHII-1-1, qHII-1-2, qHII-1-3, qHII-2-1 and qCC-1-5 (qREC-1-3). qHII-1-1, qHII-1-2 and qHII-1-3 were located, respectively, in the intervals of 1.43, 1.17 and 1.19 Mb on chromosome 1, while the interval of qHII-2-1 was located in the intervals of 1.87 Mb on chromosome 2. The locations observed with conventional QTL mapping and QTL-seq were consistent. qCC-1-5 and qREC-1-3 for CC and REC, respectively, were located at the same position by conventional QTL mapping. Although qCC-1-5 was not detected in QTL-seq analysis, its phenotypic variation (16.48%) and positive additive effect (0.22) were the highest among all heat tolerance QTLs. To investigate the genes involved in heat tolerance within the major QTLs in tomato, RNA-seq analysis was performed, and four candidate genes (SlCathB2, SlGST, SlUBC5, and SlARG1) associated with heat tolerance were finally detected within the major QTLs by DEG analysis, qRT-PCR screening and biological function analysis.

CONCLUSIONS

In conclusion, this study demonstrated that the combination of conventional QTL mapping, QTL-seq analysis and RNA-seq can rapidly identify candidate genes within major QTLs for a complex trait of interest to replace the fine-mapping process, thus greatly shortening the breeding process and improving breeding efficiency. The results have important applications for the fine mapping and identification of HSR genes and breeding for improved thermotolerance.

QTL-BSA: A Bulked Segregant Analysis and Visualization Pipeline for QTL-seq

In recent years, the application of Whole Genome Sequencing (WGS) on plants has generated sufficient data for the identification of trait-associated genomic loci or genes. A high-throughput genome-assisted QTL-seq strategy, combined with bulked-segregant analysis and WGS of two bulked populations from a segregating progeny with opposite phenotypic trait values, has gained increasing popularities in research community. However, there is no publicly available user friendly software for the identification and visualization. Hence, we developed a tool named QTL-BSA (QTL-bulked segregant analysis and visualization pipeline), which could facilitate the rapid identification and visualization of candidate QTLs from QTL-seq. As a proof-of-concept study, we have applied the tool for the rapid discovery and the identification of genes related with the partial blast resistance in rice. Genomic region of the major QTL identified on chromosome 6, is located between 1.52 and 4.32 Mb, which is consistent with previous studies (2.39-4.39 Mb). We also derived the gene and QTLs functional annotation of this region. QTL-BSA offers a comprehensive solution to facilitate a wide range of programming and visualization tasks in QTL-seq analysis, is expected to be used widely by the research community.

Towards Exploitation of Adaptive Traits for Climate-Resilient Smart Pulses

Pulses are the main source of protein and minerals in the vegetarian diet. These are primarily cultivated on marginal lands with few inputs in several resource-poor countries of the world, including several in South Asia. Their cultivation in resource-scarce conditions exposes them to various abiotic and biotic stresses, leading to significant yield losses. Furthermore, climate change due to global warming has increased their vulnerability to emerging new insect pests and abiotic stresses that can become even more serious in the coming years. The changing climate scenario has made it more challenging to breed and develop climate-resilient smart pulses. Although pulses are climate smart, as they simultaneously adapt to and mitigate the effects of climate change, their narrow genetic diversity has always been a major constraint to their improvement for adaptability. However, existing genetic diversity still provides opportunities to exploit novel attributes for developing climate-resilient cultivars. The mining and exploitation of adaptive traits imparting tolerance/resistance to climate-smart pulses can be accelerated further by using cutting-edge approaches of biotechnology such as transgenics, genome editing, and epigenetics. This review discusses various classical and molecular approaches and strategies to exploit adaptive traits for breeding climate-smart pulses.

Role of genomics in promoting the utilization of plant genetic resources in genebanks

Global efforts have seen the world's plant genetic resources (PGRs) conserved in about 1625 germ plasm repositories. Utility of these resources is important in increasing the resilience and productivity of agricultural production systems. However, despite their importance, utility of these resources has been poor. This article reviews the real and potential application of the current advances in genomic technologies in improving the utilization of these resources. The actual and potential application of these genomic approaches in plant identification, phylogenetic analysis, analysing the genetic value of germ plasm, facilitating germ plasm selection in genebanks as well as instilling confidence in international germ plasm exchange system is discussed. We note that if genebanks are to benefit from this genomic revolution, there is need for fundamental changes in the way genebanks are managed, perceived, organized and funded. Increased collaboration between genebank managers and the user community is also recommended.

Is Chickpea a Potential Substitute for Soybean? Phenolic Bioactives and Potential Health Benefits

Legume seeds are rich sources of protein, fiber, and minerals. In addition, their phenolic compounds as secondary metabolites render health benefits beyond basic nutrition. Lowering apolipoprotein B secretion from HepG2 cells and decreasing the level of low-density lipoprotein (LDL)-cholesterol oxidation are mechanisms related to the prevention of cardiovascular diseases (CVD). Likewise, low-level chronic inflammation and related disorders of the immune system are clinical predictors of cardiovascular pathology. Furthermore, DNA-damage signaling and repair are crucial pathways to the etiology of human cancers. Along CVD and cancer, the prevalence of obesity and diabetes is constantly increasing. Screening the ability of polyphenols in inactivating digestive enzymes is a good option in pre-clinical studies. In addition, in vivo studies support the role of polyphenols in the prevention and/or management of diabetes and obesity. Soybean, a well-recognized source of phenolic isoflavones, exerts health benefits by decreasing oxidative stress and inflammation related to the above-mentioned chronic ailments. Similar to soybeans, chickpeas are good sources of nutrients and phenolic compounds, especially isoflavones. This review summarizes the potential of chickpea as a substitute for soybean in terms of health beneficial outcomes. Therefore, this contribution may guide the industry in manufacturing functional foods and/or ingredients by using an undervalued feedstock.

Characterization and Rapid Gene-Mapping of Leaf Lesion Mimic Phenotype of spl-1 Mutant in Soybean (Glycine max (L.) Merr.)

In plants, lesion mimic mutants (LMMs) reveal spontaneous disease-like lesions in the absence of pathogen that constitutes powerful genetic material to unravel genes underlying programmed cell death (PCD), particularly the hypersensitive response (HR). However, only a few LMMs are reported in soybean, and no related gene has been cloned until now. In the present study, we isolated a new LMM named spotted leaf-1 (spl-1) from NN1138-2 cultivar through ethyl methanesulfonate (EMS) treatment. The present study revealed that lesion formation might result from PCD and excessive reactive oxygen species (ROS) accumulation. The chlorophyll content was significantly reduced but antioxidant activities, viz., superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT), as well as the malondialdehyde (MDA) contents, were detected higher in spl-1 than in the wild-type. According to segregation analysis of mutant phenotype in two genetic populations, viz., W82×spl-1 and PI378692×spl-1, the spotted leaf phenotype of spl-1 is controlled by a single recessive gene named lm1. The lm1 locus governing mutant phenotype of spl-1 was first identified in 3.15 Mb genomic region on chromosome 04 through MutMap analysis, which was further verified and fine mapped by simple sequence repeat (SSR) marker-based genetic mapping. Genetic linkage analysis narrowed the genomic region (lm1 locus) for mutant phenotype to a physical distance of ~76.23 kb. By searching against the Phytozome database, eight annotated candidate genes were found within the lm1 region. qRT-PCR expression analysis revealed that, among these eight genes, only Glyma.04g242300 showed highly significant expression levels in wild-type relative to the spl-1 mutant. However, sequencing data of the CDS region showed no nucleotide difference between spl-1 and its wild type within the coding regions of these genes but might be in the non-coding regions such as 5' or 3' UTR. Hence, the data of the present study are in favor of Glyma.04g242300 being the possible candidate genes regulating the mutant phenotype of spl-1. However, further validation is needed to prove this function of the gene as well as its role in PCD, which in turn would be helpful to understand the mechanism and pathways involved in HR disease resistance of soybean.

Identification of quantitative trait loci governing subgynoecy in cucumber

QTL-seq analysis identified three major QTLs conferring subgynoecy in cucumbers. Furthermore, sequence and expression analyses predicted candidate genes controlling subgynoecy. The cucumber (Cucumis sativus L.) is a typical monoecious having individual male and female flowers, and sex differentiation is an important developmental process that directly affects its fruit yield. Subgynoecy represents a sex form with a high degree of femaleness and would have alternative use as gynoecy under limited resource conditions. Recently, many studies have been reported that QTL-seq, which integrates the advantages of bulked segregant analysis and high-throughput whole-genome resequencing, can be a rapid and cost-effective way of mapping QTLs. Segregation analysis in the F₂ and BC₁ populations derived from a cross between subgynoecious LOSUAS and monoecious BMB suggested the quantitative nature of subgynoecy in cucumbers. Both genome-wide SNP profiling of subgynoecious and monoecious bulks constructed from F₂ and BC₁ plants consistently identified three significant genomic regions, one on chromosome 3 (sg3.1) and another two on short and long arms of chromosome 1 (sg1.1 and sg1.2). Classical QTL analysis using the F₂ confirmed sg3.1 (R² = 42%), sg1.1 (R² = 29%) and sg1.2 (R² = 18%) as major QTLs. These results revealed the unique genetic inheritance of subgynoecious line LOSUAS through two distinct major QTLs, sg3.1 and sg1.1, which mainly increase degree of femaleness, while another QTL, sg1.2, contributes to decrease it. This study demonstrated that QTL-seq allows rapid and powerful detection of QTLs using preliminary generation mapping populations such as F₂ or BC₁ population and further that the identified QTLs could be useful for molecular breeding of cucumber lines with high yield potential.

ABC Transporter-Mediated Transport of Glutathione Conjugates Enhances Seed Yield and Quality in Chickpea

The identification of functionally relevant molecular tags is vital for genomics-assisted crop improvement and enhancement of seed yield, quality, and productivity in chickpea (Cicer arietinum). The simultaneous improvement of yield/productivity as well as quality traits often requires pyramiding of multiple genes, which remains a major hurdle given various associated epistatic and pleotropic effects. Unfortunately, no single gene that can improve yield/productivity along with quality and other desirable agromorphological traits is known, hampering the genetic enhancement of chickpea. Using a combinatorial genomics-assisted breeding and functional genomics strategy, this study identified natural alleles and haplotypes of an ABCC3-type transporter gene that regulates seed weight, an important domestication trait, by transcriptional regulation and modulation of the transport of glutathione conjugates in seeds of desi and kabuli chickpea. The superior allele/haplotype of this gene introgressed in desi and kabuli near-isogenic lines enhances the seed weight, yield, productivity, and multiple desirable plant architecture and seed-quality traits without compromising agronomic performance. These salient findings can expedite crop improvement endeavors and the development of nutritionally enriched high-yielding cultivars in chickpea.

Genetic Mapping and Molecular Characterization of a Broad-spectrum Phytophthora sojae Resistance Gene in Chinese Soybean

Phytophthora root rot (PRR) causes serious annual soybean yield losses worldwide. The most effective method to prevent PRR involves growing cultivars that possess genes conferring resistance to Phytophthora sojae (Rps). In this study, QTL-sequencing combined with genetic mapping was used to identify RpsX in soybean cultivar Xiu94-11 resistance to all P. sojae isolates tested, exhibiting broad-spectrum PRR resistance. Subsequent analysis revealed RpsX was located in the 242-kb genomic region spanning the RpsQ locus. However, a phylogenetic investigation indicated Xiu94-11 carrying RpsX is distantly related to the cultivars containing RpsQ, implying RpsX and RpsQ have different origins. An examination of candidate genes revealed RpsX and RpsQ share common nonsynonymous SNP and a 144-bp insertion in the Glyma.03g027200 sequence encoding a leucine-rich repeat (LRR) region. Glyma.03g027200 was considered to be the likely candidate gene of RpsQ and RpsX. Sequence analyses confirmed that the 144-bp insertion caused by an unequal exchange resulted in two additional LRR-encoding fragments in the candidate gene. A marker developed based on the 144-bp insertion was used to analyze the genetic population and germplasm, and proved to be useful for identifying the RpsX and RpsQ alleles. This study implies that the number of LRR units in the LRR domain may be important for PRR resistance in soybean.