mQTL-seq delineates functionally relevant candidate gene harbouring a major QTL regulating pod number in chickpea

Unraveling the genetics of heat tolerance in chickpea landraces (Cicer arietinum L.) using genome-wide association studies

Chickpea, being an important grain legume crop, is often confronted with the adverse effects of high temperatures at the reproductive stage of crop growth, drastically affecting yield and overall productivity. The current study deals with an extensive evaluation of chickpea genotypes, focusing on the traits associated with yield and their response to heat stress. Notably, we observed significant variations for these traits under both normal and high-temperature conditions, forming a robust basis for genetic research and breeding initiatives. Furthermore, the study revealed that yield-related traits exhibited high heritability, suggesting their potential suitability for marker-assisted selection. We carried out single-nucleotide polymorphism (SNP) genotyping using the genotyping-by-sequencing (GBS) method for a genome-wide association study (GWAS). Overall, 27 marker-trait associations (MTAs) linked to yield-related traits, among which we identified five common MTAs displaying pleiotropic effects after applying a stringent Bonferroni-corrected p-value threshold of <0.05 [-log10(p) > 4.95] using the BLINK (Bayesian-information and linkage-disequilibrium iteratively nested keyway) model. Through an in-depth in silico analysis of these markers against the CDC Frontier v1 reference genome, we discovered that the majority of the SNPs were located at or in proximity to gene-coding regions. We further explored candidate genes situated near these MTAs, shedding light on the molecular mechanisms governing heat stress tolerance and yield enhancement in chickpeas such as indole-3-acetic acid-amido synthetase GH3.1 with GH3 auxin-responsive promoter and pentatricopeptide repeat-containing protein, etc. The harvest index (HI) trait was associated with marker Ca3:37444451 encoding aspartic proteinase ortholog sequence of Oryza sativa subsp. japonica and Medicago truncatula, which is known for contributing to heat stress tolerance. These identified MTAs and associated candidate genes may serve as valuable assets for breeding programs dedicated to tailoring chickpea varieties resilient to heat stress and climate change.

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.

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.

Genetic Augmentation of Legume Crops Using Genomic Resources and Genotyping Platforms for Nutritional Food Security

Recent advances in next generation sequencing (NGS) technologies have led the surge of genomic resources for the improvement legume crops. Advances in high throughput genotyping (HTG) and high throughput phenotyping (HTP) enable legume breeders to improve legume crops more precisely and efficiently. Now, the legume breeder can reshuffle the natural gene combinations of their choice to enhance the genetic potential of crops. These genomic resources are efficiently deployed through molecular breeding approaches for genetic augmentation of important legume crops, such as chickpea, cowpea, pigeonpea, groundnut, common bean, lentil, pea, as well as other underutilized legume crops. In the future, advances in NGS, HTG, and HTP technologies will help in the identification and assembly of superior haplotypes to tailor the legume crop varieties through haplotype-based breeding. This review article focuses on the recent development of genomic resource databases and their deployment in legume molecular breeding programmes to secure global food security.

Capturing Wheat Phenotypes at the Genome Level

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

Harnessing the hidden allelic diversity of wild Cicer to accelerate genomics-assisted chickpea crop improvement

Chickpea, commonly called Bengal gram or Garbanzo bean, faces a productivity crisis around the globe due to numerous biotic and abiotic stresses. The eroded genetic base of the cultivated Cicer gene pool is becoming a significant bottleneck in developing stress-resilient chickpea cultivars. In this scenario, the crop wild relatives (CWR) of chickpea, with the useful genomic wealth of their wild adaptation, give a ray of hope to improve the genetic background of the cultivated Cicer gene pool. To extrapolate these unearthed genomic diversities of wild, we require a thorough understanding of the pre-historic domestication episodes that are changing their shape with the expansion of the available scientific evidence. Keeping aforesaid in view, the current review article provides a glimpsed overview on several efforts done so far to reveal the mysterious origin and evolution of the Cicer gene pool, along with the constraints in their utilization for chickpea crop improvement. It encapsulates various stress-resilient CWR of chickpea and their use in several pre-breeding programs to develop numerous breeding populations for crop genetic enhancement. Further, this review will recapitulate the significant contributions of structural, functional and comparative genomics, pan-genomics and diverse genomics-assisted breeding strategy in dissecting the untapped trait-specific allelic/gene diversity and domestication pattern behind the CWR of chickpea, along with their potential and promises. We expect the newly explored genetic variations may be used in the breeding programs for re-wilding the cultigens' genomic background to open a new avenue for genetic gain and crop improvement capacity of chickpea.

Broadening the horizon of crop research: a decade of advancements in plant molecular genetics to divulge phenotype governing genes

Advancements in sequencing, genotyping, and computational technologies during the last decade (2011-2020) enabled new forward-genetic approaches, which subdue the impediments of precise gene mapping in varied crops. The modern crop improvement programs rely heavily on two major steps-trait-associated QTL/gene/marker's identification and molecular breeding. Thus, it is vital for basic and translational crop research to identify genomic regions that govern the phenotype of interest. Until the advent of next-generation sequencing, the forward-genetic techniques were laborious and time-consuming. Over the last 10 years, advancements in the area of genome assembly, genotyping, large-scale data analysis, and statistical algorithms have led faster identification of genomic variations regulating the complex agronomic traits and pathogen resistance. In this review, we describe the latest developments in genome sequencing and genotyping along with a comprehensive evaluation of the last 10-year headways in forward-genetic techniques that have shifted the focus of plant research from model plants to diverse crops. We have classified the available molecular genetic methods under bulk-segregant analysis-based (QTL-seq, GradedPool-Seq, QTG-Seq, Exome QTL-seq, and RapMap), target sequence enrichment-based (RenSeq, AgRenSeq, and TACCA), and mutation-based groups (MutMap, NIKS algorithm, MutRenSeq, MutChromSeq), alongside improvements in classical mapping and genome-wide association analyses. Newer methods for outcrossing, heterozygous, and polyploid plant genetics have also been discussed. The use of k-mers has enriched the nature of genetic variants which can be utilized to identify the phenotype-causing genes, independent of reference genomes. We envisage that the recent methods discussed herein will expand the repertoire of useful alleles and help in developing high-yielding and climate-resilient crops.

Genomic Approaches to Identify Molecular Bases of Crop Resistance to Diseases and to Develop Future Breeding Strategies

Plant diseases are responsible for substantial crop losses each year and affect food security and agricultural sustainability. The improvement of crop resistance to pathogens through breeding represents an environmentally sound method for managing disease and minimizing these losses. The challenge is to breed varieties with a stable and broad-spectrum resistance. Different approaches, from markers to recent genomic and 'post-genomic era' technologies, will be reviewed in order to contribute to a better understanding of the complexity of host-pathogen interactions and genes, including those with small phenotypic effects and mechanisms that underlie resistance. An efficient combination of these approaches is herein proposed as the basis to develop a successful breeding strategy to obtain resistant crop varieties that yield higher in increasing disease scenarios.

Cytological Observations and Bulked-Segregant Analysis Coupled Global Genome Sequencing Reveal Two Genes Associated with Pollen Fertility in Tetraploid Rice

Neo-tetraploid rice with high fertility is a useful germplasm for polyploid rice breeding, which was developed from the crossing of different autotetraploid rice lines. However, little information is available on the molecular mechanism underlying the fertility of neo-tetraploid rice. Here, two contrasting populations of tetraploid rice, including one with high fertility (hereafter referred to as JG) and another with low fertility (hereafter referred to as JD), were generated by crossing Huaduo 3 (H3), a high fertility neo-tetraploid rice that was developed by crossing Jackson-4x with 96025-4x, and Huajingxian74-4x (T452), a low fertility autotetraploid rice parent. Cytological, global genome sequencing-based bulked-segregant (BSA-seq) and CRISPR/Cas9 technology were employed to study the genes associated with pollen fertility in neo-tetraploid rice. The embryo sacs of JG and JD lines were normal; however, pollen fertility was low in JD, which led to scarce fertilization and low seed setting. Cytological observations displayed low pollen fertility (25.1%) and approximately 31.3 and 27.2% chromosome lagging at metaphase I and II, and 28.8 and 24.8% chromosome straggling at anaphase I and II in JD, respectively. BSA-seq of F_2–3 generations and RNA-seq of F₄ generation detected a common fragment, i.e., 18,915,234–19,500,000, at chromosome 7, which was comprised of 78 genes associated with fertility. Among 78 genes, 9 genes had been known to be involved in meiosis and pollen development. Two mutants ny1 (LOC_Os07g32406) and ny2 (LOC_Os07g32040) were generated by CRISPR/Cas9 knockout in neo-tetraploid rice, and which exhibited low pollen fertility and abnormal chromosome behavior. Our study revealed that two unknown genes, LOC_Os07g32406 (NY1) and LOC_Os07g32040 (NY2) play an important role in pollen development of neo-tetraploid rice and provides a new perspective about the genetic mechanisms of fertility in polyploid rice.

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.

QTL sequencing strategy to map genomic regions associated with resistance to ascochyta blight in chickpea

Whole-genome sequencing-based bulked segregant analysis (BSA) for mapping quantitative trait loci (QTL) provides an efficient alternative approach to conventional QTL analysis as it significantly reduces the scale and cost of analysis with comparable power to QTL detection using full mapping population. We tested the application of next-generation sequencing (NGS)-based BSA approach for mapping QTLs for ascochyta blight resistance in chickpea using two recombinant inbred line populations CPR-01 and CPR-02. Eleven QTLs in CPR-01 and six QTLs in CPR-02 populations were mapped on chromosomes Ca1, Ca2, Ca4, Ca6 and Ca7. The QTLs identified in CPR-01 using conventional biparental mapping approach were used to compare the efficiency of NGS-based BSA in detecting QTLs for ascochyta blight resistance. The QTLs on chromosomes Ca1, Ca4, Ca6 and Ca7 overlapped with the QTLs previously detected in CPR-01 using conventional QTL mapping method. The QTLs on chromosome Ca4 were detected in both populations and overlapped with the previously reported QTLs indicating conserved region for ascochyta blight resistance across different chickpea genotypes. Six candidate genes in the QTL regions identified using NGS-based BSA on chromosomes Ca2 and Ca4 were validated for their association with ascochyta blight resistance in the CPR-02 population. This study demonstrated the efficiency of NGS-based BSA as a rapid and cost-effective method to identify QTLs associated with ascochyta blight in chickpea.

Genome-wide generation and genotyping of informative SNPs to scan molecular signatures for seed yield in chickpea

We discovered 2150 desi and 2199 kabuli accessions-derived SNPs by cultivar-wise individual assembling of sequence-reads generated through genotyping-by-sequencing of 92 chickpea accessions. Subsequent large-scale validation and genotyping of these SNPs discovered 619 desi accessions-derived (DAD) SNPs, 531 kabuli accessions-derived (KAD) SNPs, 884 multiple accessions-derived (MAD) SNPs and 1083 two accessions (desi ICC 4958 and kabuli CDC Frontier)-derived (TAD) SNPs that were mapped on eight chromosomes. These informative SNPs were annotated in coding/non-coding regulatory sequence components of genes. The MAD-SNPs were efficient to detect high intra-specific polymorphic potential and wide natural allelic diversity level including high-resolution admixed-population genetic structure and precise phylogenetic relationship among 291 desi and kabuli accessions. This signifies their effectiveness in introgression breeding and varietal improvement studies targeting useful agronomic traits of chickpea. Six trait-associated genes with SNPs including quantitative trait nucleotides (QTNs) in combination explained 27.5% phenotypic variation for seed yield per plant (SYP). A pentatricopeptide repeat (PPR) gene with a synonymous-coding SNP/QTN significantly associated with SYP trait was found most-promising in chickpea. The essential information delineated can be of immense utility in genomics-assisted breeding applications to develop high-yielding chickpea cultivars.

Current advances in chickpea genomics: applications and future perspectives

Chickpea genomics promises to illuminate our understanding of genome organization, structural variations, evolutionary and domestication-related insights and fundamental biology of legume crops. Unprecedented advancements of next generation sequencing (NGS) technologies have enabled in decoding of multiple chickpea genome sequences and generating huge genomic resources in chickpea both at functional and structural level. This review is aimed to update the current progress of chickpea genomics ranging from high density linkage map development, genome-wide association studies (GWAS), functional genomics resources for various traits, emerging role of abiotic stress responsive coding and non-coding RNAs after the completion of draft chickpea genome sequences. Additionally, the current efforts of whole genome re-sequencing (WGRS) approach of global chickpea germplasm to capture the global genetic diversity existing in the historically released varieties across the world and increasing the resolution of the previously identified candidate gene(s) of breeding importance have been discussed. Thus, the outcomes of these genomics resources will assist in genomics-assisted selection and facilitate breeding of climate-resilient chickpea cultivars for sustainable agriculture.

Identification and genetic mapping for rht-DM, a dominant dwarfing gene in mutant semi-dwarf maize using QTL-seq approach

Semi-dwarfism is an agronomically important trait in breeding for stable high yields and for resistance to damage by wind and rain (lodging resistance). Many QTLs and genes causing dwarf phenotype have been found in maize. However, because of the yield loss associated with these QTLs and genes, they have been difficult to use in breeding for dwarf stature in maize. Therefore, it is important to find the new dwarfing genes or materials without undesirable characters. The objectives of this study were: (1) to figure out the inheritance of semi-dwarfism in mutants; (2) mapping dwarfing gene or QTL. Maize inbred lines '18599' and 'DM173', which is the dwarf mutant derived from the maize inbred line '173' through ⁶⁰Co-γ ray irradiation. F₂ and BC₁F₁ population were used for genetic analysis. Whole genome resequencing-based technology (QTL-seq) were performed to map dwarfing gene and figured out the SNP markers in predicted region using dwarf bulk and tall bulk from F₂ population. Based on the polymorphic SNP markers from QTL-seq, we were fine-mapping the dwarfing gene using F₂ population. In F₂ population, 398 were dwarf plants and 135 were tall plants. Results of χ² tests indicated that the ratio of dwarf plants to tall plants was fitted to 3:1 ratio. Furthermore, the χ² tests of BC₁F₁ population showed that the ratio was fitted to 1:1 ratio. Based on QTL-seq, the dwarfing gene was located at the region from 111.07 to 124.56 Mb of chromosome 9, and we named it rht-DM. Using traditional QTL mapping with SNP markers, the rht-DM was narrowed down to 400 kb region between SNP-21 and SNP-24. The two SNPs were located at 0.43 and 0.11 cM. Segregation analysis of F₂ and BC₁F₁ indicated that the dwarfing gene was likely a dominant gene. This dwarfing gene was located in the region between 115.02 and 115.42 Mb on chromosome 9.

Identification and Validation of New Alleles of FALSIFLORA and COMPOUND INFLORESCENCE Genes Controlling the Number of Branches in Tomato Inflorescence

The architecture of inflorescences shows extensive diversity in both branching frequency and flower number, which eventually, determines agricultural productivity. In this study, F₂ (second filial) populations derived from a cross between Solanum lycopersicum 10AS111A (highly-branched inflorescence) and the S. pimpinellifolium PI124039 (inflorescence having a single branch) were used to decipher the genetic control of branch number (BN) of inflorescence in plants bearing small-sized tomato fruits. The segregation ratio of single- and moderately-branched types to the highly-branched type was significantly different from 3:1 but not different from 15:1 at p < 0.05, suggesting that more than one gene controls the branch number of the inflorescences. Through genome-wide comparison of single-nucleotide polymorphism (SNP) profiles between the highly-branched type bulk and the single-branch type bulk constructed using the F₂ plants, we identified a major quantitative trait locus (QTL) on chromosome 3 (58.75-61.4 Mb) and a minor QTL on chromosome 2 (32.95-37.1 Mb), which explained 15.7% and 6.1% of the BN variation, respectively. FALSIFLORA (FA) and COMPOUND INFLORESCENCE (S) genes, located in the QTL peak regions, caught our attention. Sequence comparison of the FA and S genes and their promoter regions from the two parental lines revealed that both contain missense mutations in the coding regions. Segregation analysis of FA and S alleles by high-resolution melting (HRM) method confirmed that alleles for both genes from 10AS111A significantly increased the BN and the size of inflorescence. In conclusion, we propose that SNPs in coding sequences might cause changes in the function of FA and S genes, which might be important determinants of BN.

A Multiple QTL-Seq Strategy Delineates Potential Genomic Loci Governing Flowering Time in Chickpea

Identification of functionally relevant potential genomic loci using an economical, simpler and user-friendly genomics-assisted breeding strategy is vital for rapid genetic dissection of complex flowering time quantitative trait in chickpea. A high-throughput multiple QTL-seq strategy was employed in two inter (Cicer arietinum desi accession ICC 4958 × C reticulatum wild accession ICC 17160)- and intra (ICC 4958 × C. arietinum kabuli accession ICC 8261)-specific RIL mapping populations to identify the major QTL genomic regions governing flowering time in chickpea. The whole genome resequencing discovered 1635117 and 592486 SNPs exhibiting differentiation between early- and late-flowering mapping parents and bulks, constituted by pooling the homozygous individuals of extreme flowering time phenotypic trait from each of two aforesaid RIL populations. The multiple QTL-seq analysis using these mined SNPs in two RIL mapping populations narrowed-down two longer (907.1 kb and 1.99 Mb) major flowering time QTL genomic regions into the high-resolution shorter (757.7 kb and 1.39 Mb) QTL intervals on chickpea chromosome 4. This essentially identified regulatory as well as coding (non-synonymous/synonymous) novel SNP allelic variants from two efl1 (early flowering 1) and GI (GIGANTEA) genes regulating flowering time in chickpea. Interestingly, strong natural allelic diversity reduction (88-91%) of two known flowering genes especially mapped at major QTL intervals as compared to that of background genomic regions (where no flowering time QTLs were mapped; 61.8%) in cultivated vis-à-vis wild Cicer gene pools was evident inferring the significant impact of evolutionary bottlenecks on these loci during chickpea domestication. Higher association potential of coding non-synonymous and regulatory SNP alleles mined from efl1 (36-49%) and GI (33-42%) flowering genes for early and late flowering time differentiation among chickpea accessions was evident. The robustness and validity of two functional allelic variants-containing genes localized at major flowering time QTLs was apparent by their identification from multiple intra-/inter-specific mapping populations of chickpea. The functionally relevant molecular tags delineated can be of immense use for deciphering the natural allelic diversity-based domestication pattern of flowering time and expediting genomics-aided crop improvement to develop early flowering cultivars of chickpea.

Genetic dissection of plant growth habit in chickpea

A combinatorial genomics-assisted breeding strategy encompassing association analysis, genetic mapping and expression profiling is found most promising for quantitative dissection of complex traits in crop plants. The present study employed GWAS (genome-wide association study) using 24,405 SNPs (single nucleotide polymorphisms) obtained with genotyping-by-sequencing (GBS) of 92 sequenced desi and kabuli accessions of chickpea. This identified eight significant genomic loci associated with erect (E)/semi-erect (SE) vs. spreading (S)/semi-spreading (SS)/prostrate (P) plant growth habit (PGH) trait differentiation regardless of diverse desi and kabuli genetic backgrounds of chickpea. These associated SNPs in combination explained 23.8% phenotypic variation for PGH in chickpea. Five PGH-associated genes were validated successfully in E/SE and SS/S/P PGH-bearing parental accessions and homozygous individuals of three intra- and interspecific RIL (recombinant inbred line) mapping populations as well as 12 contrasting desi and kabuli chickpea germplasm accessions by selective genotyping through Sequenom MassARRAY. The shoot apical, inflorescence and floral meristems-specific expression, including upregulation (seven-fold) of five PGH-associated genes especially in germplasm accessions and homozygous RIL mapping individuals contrasting with E/SE PGH traits was apparent. Collectively, this integrated genomic strategy delineated diverse non-synonymous SNPs from five candidate genes with strong allelic effects on PGH trait variation in chickpea. Of these, two vernalization-responsive non-synonymous SNP alleles carrying SNF2 protein-coding gene and B3 transcription factor associated with PGH traits were found to be the most promising in chickpea. The SNP allelic variants associated with E/SE/SS/S PGH trait differentiation were exclusively present in all cultivated desi and kabuli chickpea accessions while wild species/accessions belonging to primary, secondary and tertiary gene pools mostly contained prostrate PGH-associated SNP alleles. This indicates strong adaptive natural/artificial selection pressure (Tajima's D 3.15 to 4.57) on PGH-associated target genomic loci during chickpea domestication. These vital leads thus have potential to decipher complex transcriptional regulatory gene function of PGH trait differentiation and for understanding the selective sweep-based PGH trait evolution and domestication pattern in cultivated and wild chickpea accessions adapted to diverse agroclimatic conditions. Collectively, the essential inputs generated will be of profound use in marker-assisted genetic enhancement to develop cultivars with desirable plant architecture of erect growth habit types in chickpea.

Potential Uses of Wild Germplasms of Grain Legumes for Crop Improvement

Challenged by population increase, climatic change, and soil deterioration, crop improvement is always a priority in securing food supplies. Although the production of grain legumes is in general lower than that of cereals, the nutritional value of grain legumes make them important components of food security. Nevertheless, limited by severe genetic bottlenecks during domestication and human selection, grain legumes, like other crops, have suffered from a loss of genetic diversity which is essential for providing genetic materials for crop improvement programs. Illustrated by whole-genome-sequencing, wild relatives of crops adapted to various environments were shown to maintain high genetic diversity. In this review, we focused on nine important grain legumes (soybean, peanut, pea, chickpea, common bean, lentil, cowpea, lupin, and pigeonpea) to discuss the potential uses of their wild relatives as genetic resources for crop breeding and improvement, and summarized the various genetic/genomic approaches adopted for these purposes.

Regional Association Analysis of MetaQTLs Delineates Candidate Grain Size Genes in Rice

Molecular mapping studies which aim to identify genetic basis of diverse agronomic traits are vital for marker-assisted crop improvement. Numerous Quantitative Trait Loci (QTLs) mapped in rice span long genomic intervals with hundreds to thousands of genes, which limits their utilization for marker-assisted genetic enhancement of rice. Although potent, fine mapping of QTLs is challenging task as it requires screening of large number of segregants to identify suitable recombination events. Association mapping offers much higher resolution as compared to QTL mapping, but detects considerable number of spurious QTLs. Therefore, combined use of QTL and association mapping strategies can provide advantages associated with both these methods. In the current study, we utilized meta-analysis approach to identify metaQTLs associated with grain size/weight in diverse Indian indica and aromatic rice accessions. Subsequently, attempt has been made to narrow-down identified grain size/weight metaQTLs through individual SNP- as well as haplotype-based regional association analysis. The study identified six different metaQTL regions, three of which were successfully revalidated, and substantially scaled-down along with GS3 QTL interval (positive control) by regional association analysis. Consequently, two potential candidate genes within two reduced metaQTLs were identified based on their differential expression profiles in different tissues/stages of rice accessions during seed development. The developed strategy has broader practical utility for rapid delineation of candidate genes and natural alleles underlying QTLs associated with complex agronomic traits in rice as well as major crop plants enriched with useful genetic and genomic information.

Physiological, genomic and transcriptional diversity in responses to boron deficiency in rapeseed genotypes

Allotetraploid rapeseed (Brassica napus L. A_nA_nC_nC_n, 2n=4x=38) is highly susceptible to boron (B) deficiency, a widespread limiting factor that causes severe losses in seed yield. The genetic variation in the sensitivity to B deficiency found in rapeseed genotypes emphasizes the complex response architecture. In this research, a B-inefficient genotype, 'Westar 10' ('W10'), responded to B deficiencies during vegetative and reproductive development with an over-accumulation of reactive oxygen species, severe lipid peroxidation, evident plasmolysis, abnormal floral organogenesis, and widespread sterility compared to a B-efficient genotype, 'Qingyou 10' ('QY10'). Whole-genome re-sequencing (WGS) of 'QY10' and 'W10' revealed a total of 1 605 747 single nucleotide polymorphisms and 218 755 insertions/deletions unevenly distributed across the allotetraploid rapeseed genome (~1130Mb). Digital gene expression (DGE) profiling identified more genes related to B transporters, antioxidant enzymes, and the maintenance of cell walls and membranes with higher transcript levels in the roots of 'QY10' than in 'W10' under B deficiency. Furthermore, based on WGS and bulked segregant analysis of the doubled haploid (DH) line pools derived from 'QY10' and 'W10', two significant quantitative trait loci (QTLs) for B efficiency were characterized on chromosome C2, and DGE-assisted QTL-seq analyses then identified a nodulin 26-like intrinsic protein gene and an ATP-binding cassette (ABC) transporter gene as the corresponding candidates regulating B efficiency. This research facilitates a more comprehensive understanding of the differential physiological and transcriptional responses to B deficiency and abundant genetic diversity in rapeseed genotypes, and the DGE-assisted QTL-seq analyses provide novel insights regarding the rapid dissection of quantitative trait genes in plant species with complex genomes.

An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice

Development and use of genome-wide informative simple sequence repeat (SSR) markers and novel integrated genomic strategies are vital to drive genomics-assisted breeding applications and for efficient dissection of quantitative trait loci (QTLs) underlying complex traits in rice. The present study developed 6244 genome-wide informative SSR markers exhibiting in silico fragment length polymorphism based on repeat-unit variations among genomic sequences of 11 indica, japonica, aus, and wild rice accessions. These markers were mapped on diverse coding and non-coding sequence components of known cloned/candidate genes annotated from 12 chromosomes and revealed a much higher amplification (97%) and polymorphic potential (88%) along with wider genetic/functional diversity level (16-74% with a mean 53%) especially among accessions belonging to indica cultivar group, suggesting their utility in large-scale genomics-assisted breeding applications in rice. A high-density 3791 SSR markers-anchored genetic linkage map (IR 64 × Sonasal) spanning 2060 cM total map-length with an average inter-marker distance of 0.54 cM was generated. This reference genetic map identified six major genomic regions harboring robust QTLs (31% combined phenotypic variation explained with a 5.7-8.7 LOD) governing grain weight on six rice chromosomes. One strong grain weight major QTL region (OsqGW5.1) was narrowed-down by integrating traditional QTL mapping with high-resolution QTL region-specific integrated SSR and single nucleotide polymorphism markers-based QTL-seq analysis and differential expression profiling. This led us to delineate two natural allelic variants in two known cis-regulatory elements (RAV1AAT and CARGCW8GAT) of glycosyl hydrolase and serine carboxypeptidase genes exhibiting pronounced seed-specific differential regulation in low (Sonasal) and high (IR 64) grain weight mapping parental accessions. Our genome-wide SSR marker resource (polymorphic within/between diverse cultivar groups) and integrated genomic strategy can efficiently scan functionally relevant potential molecular tags (markers, candidate genes and alleles) regulating complex agronomic traits (grain weight) and expedite marker-assisted genetic enhancement in rice.

A High-Resolution InDel (Insertion-Deletion) Markers-Anchored Consensus Genetic Map Identifies Major QTLs Governing Pod Number and Seed Yield in Chickpea

Development and large-scale genotyping of user-friendly informative genome/gene-derived InDel markers in natural and mapping populations is vital for accelerating genomics-assisted breeding applications of chickpea with minimal resource expenses. The present investigation employed a high-throughput whole genome next-generation resequencing strategy in low and high pod number parental accessions and homozygous individuals constituting the bulks from each of two inter-specific mapping populations [(Pusa 1103 × ILWC 46) and (Pusa 256 × ILWC 46)] to develop non-erroneous InDel markers at a genome-wide scale. Comparing these high-quality genomic sequences, 82,360 InDel markers with reference to kabuli genome and 13,891 InDel markers exhibiting differentiation between low and high pod number parental accessions and bulks of aforementioned mapping populations were developed. These informative markers were structurally and functionally annotated in diverse coding and non-coding sequence components of genome/genes of kabuli chickpea. The functional significance of regulatory and coding (frameshift and large-effect mutations) InDel markers for establishing marker-trait linkages through association/genetic mapping was apparent. The markers detected a greater amplification (97%) and intra-specific polymorphic potential (58-87%) among a diverse panel of cultivated desi, kabuli, and wild accessions even by using a simpler cost-efficient agarose gel-based assay implicating their utility in large-scale genetic analysis especially in domesticated chickpea with narrow genetic base. Two high-density inter-specific genetic linkage maps generated using aforesaid mapping populations were integrated to construct a consensus 1479 InDel markers-anchored high-resolution (inter-marker distance: 0.66 cM) genetic map for efficient molecular mapping of major QTLs governing pod number and seed yield per plant in chickpea. Utilizing these high-density genetic maps as anchors, three major genomic regions harboring each of pod number and seed yield robust QTLs (15-28% phenotypic variation explained) were identified on chromosomes 2, 4, and 6. The integration of genetic and physical maps at these QTLs mapped on chromosomes scaled-down the long major QTL intervals into high-resolution short pod number and seed yield robust QTL physical intervals (0.89-2.94 Mb) which were essentially got validated in multiple genetic backgrounds of two chickpea mapping populations. The genome-wide InDel markers including natural allelic variants and genomic loci/genes delineated at major six especially in one colocalized novel congruent robust pod number and seed yield robust QTLs mapped on a high-density consensus genetic map were found most promising in chickpea. These functionally relevant molecular tags can drive marker-assisted genetic enhancement to develop high-yielding cultivars with increased seed/pod number and yield in chickpea.