Genome-Wide Scans for Delineation of Candidate Genes Regulating Seed-Protein Content in Chickpea

Unlocking the nutritional potential of chickpea: strategies for biofortification and enhanced multinutrient quality

Chickpea (Cicer arietinum L.) is a vital grain legume, offering an excellent balance of protein, carbohydrates, fats, fiber, essential micronutrients, and vitamins that can contribute to addressing the global population's increasing food and nutritional demands. Chickpea protein offers a balanced source of amino acids with high bioavailability. Moreover, due to its balanced nutrients and affordable price, chickpea is an excellent alternative to animal protein, offering a formidable tool for combating hidden hunger and malnutrition, particularly prevalent in low-income countries. This review examines chickpea's nutritional profile, encompassing protein, amino acids, carbohydrates, fatty acids, micronutrients, vitamins, antioxidant properties, and bioactive compounds of significance in health and pharmaceutical domains. Emphasis is placed on incorporating chickpeas into diets for their myriad health benefits and nutritional richness, aimed at enhancing human protein and micronutrient nutrition. We discuss advances in plant breeding and genomics that have facilitated the discovery of diverse genotypes and key genomic variants/regions/quantitative trait loci contributing to enhanced macro- and micronutrient contents and other quality parameters. Furthermore, we explore the potential of innovative breeding tools such as CRISPR/Cas9 in enhancing chickpea's nutritional profile. Envisioning chickpea as a nutritionally smart crop, we endeavor to safeguard food security, combat hunger and malnutrition, and promote dietary diversity within sustainable agrifood systems.

MicroRNA164e suppresses NAC100 transcription factor-mediated synthesis of seed storage proteins in chickpea

Development of protein-enriched chickpea varieties necessitates an understanding of specific genes and key regulatory circuits that govern the synthesis of seed storage proteins (SSPs). Here, we demonstrated the novel involvement of Ca-miR164e-CaNAC100 in regulating SSP synthesis in chickpea. Ca-miRNA164e was significantly decreased during seed maturation, especially in high-protein accessions. The miRNA was found to directly target the transactivation conferring C-terminal region of a nuclear-localized transcription factor, CaNAC100 as revealed using RNA ligase-mediated-rapid amplification of cDNA ends and target mimic assays. The functional role of CaNAC100 was demonstrated through seed-specific overexpression (NACOE) resulting in significantly augmented seed protein content (SPC) consequential to increased SSP transcription. Further, NACOE lines displayed conspicuously enhanced seed weight but reduced numbers and yield. Conversely, a downregulation of CaNAC100 and SSP transcripts was evident in seed-specific overexpression lines of Ca-miR164e that culminated in significantly lowered SPC. CaNAC100 was additionally demonstrated to transactivate the SSP-encoding genes by directly binding to their promoters as demonstrated using electrophoretic mobility shift and dual-luciferase reporter assays. Taken together, our study for the first time established a distinct role of CaNAC100 in positively influencing SSP synthesis and its critical regulation by CamiR164e, thereby serving as an understanding that can be utilized for developing SPC-rich chickpea varieties.

Dissecting chickpea genomic loci associated with the root penetration responsive traits in compacted soil

MAIN CONCLUSION

Soil compaction reduces root exploration in chickpea. We found genes related to root architectural traits in chickpea that can help understand and improve root growth in compacted soils. Soil compaction is a major concern for modern agriculture, as it constrains plant root growth, leading to reduced resource acquisition. Phenotypic variation for root system architecture (RSA) traits in compacted soils is present for various crops; however, studies on genetic associations with these traits are lacking. Therefore, we investigated RSA traits in different soil compaction levels and identified significant genomic associations in chickpea. We conducted a Genome-Wide Association Study (GWAS) of 210 chickpea accessions for 13 RSA traits under three bulk densities (BD) (1.1BD, 1.6BD, and 1.8BD). Soil compaction decreases root exploration by reducing 12 RSA traits, except average diameter (AD). Further, AD is negatively correlated with lateral root traits, and this correlation increases in 1.8BD, suggesting the negative effect of AD on lateral root traits. Interestingly, we identified probable candidate genes such as GLP3 and LRX for lateral root traits and CRF1-like for total length (TL) in 1.6BD soil. In heavy soil compaction, DGK2 is associated with lateral root traits. Reduction in laterals during soil compaction is mainly due to delayed seedling establishment, thus making lateral root number a critical trait. Interestingly, we also found a higher contribution of the  GxE component of the number of root tips (Tips) to the total variation than the other lateral traits. We also identified a pectin esterase, PPE8B, associated with Tips in high soil compaction and a significantly associated SNP with the relative change in Tips depicting a trade-off between Tips and AD. Identified genes and loci would help develop soil-compaction-resistant chickpea varieties.

Natural alleles of Mediator subunit genes modulate plant height in chickpea

Plant height (PH) is an important plant architectural trait targeted during Green Revolution to enhance crop yields. Identification of genes and natural alleles governing plant height without compromising agronomic performance can fill the lacuna of knowledge connecting ideal plant architecture with maximum achievable yield in chickpea. Through coherent strategy involving genome‐wide association study, QTL/fine mapping, map‐based cloning, molecular haplotyping, and downstream functional genomics, the current study identified two Mediator subunit genes namely, CaMED23 and CaMED5b and their derived natural alleles/haplotypes underlying the major QTLs and trans‐acting eQTLs regulating plant height in chickpea. Differential accumulation of haplotype‐specific transcripts of these two Mediator genes in corresponding haplotype‐introgressed near‐isogenic lines (NILs) correlates negatively with the plant height trait. Quantitative as well as qualitative estimation based on histology, scanning electron microscopy, and histochemical assay unraveled the reduced lengths and cell sizes of internodes along with compromised lignin levels in dwarf/semi‐dwarf chickpea NILs introgressed with superior CaMED23 and CaMED5b gene haplotypes. This observation, supported by global transcriptome profiling‐based diminished expression of various phenylpropanoid pathway genes upstream of lignin biosynthesis in dwarf/semi‐dwarf NILs, essentially links plant height with lignin accumulation. The identified molecular signatures in the Mediator subunit genes can be efficiently utilized to develop desirable dwarf/semi‐dwarf‐type chickpea cultivars without affecting their yield per plant via modulating lignin/phenylpropanoid biosynthesis.

Fatty acid composition and genome-wide associations of a chickpea (Cicer arietinum L.) diversity panel for biofortification efforts

Chickpea is a nutritionally dense pulse crop with high levels of protein, carbohydrates, micronutrients and low levels of fats. Chickpea fatty acids are associated with a reduced risk of obesity, blood cholesterol, and cardiovascular diseases in humans. We measured four primary chickpea fatty acids; palmitic acid (PA), linoleic acid (LA), alpha-linolenic acid (ALA), and oleic acid (OA), which are crucial for human health and plant stress responses in a chickpea diversity panel with 256 accessions (Kabuli and desi types). A wide concentration range was found for PA (450.7-912.6 mg/100 g), LA (1605.7-3459.9 mg/100 g), ALA (416.4-864.5 mg/100 g), and OA (1035.5-1907.2 mg/100 g). The percent recommended daily allowances also varied for PA (3.3-6.8%), LA (21.4-46.1%), ALA (34.7-72%), and OA (4.3-7.9%). Weak correlations were found among fatty acids. Genome-wide association studies (GWAS) were conducted using genotyping-by-sequencing data. Five significant single nucleotide polymorphisms (SNPs) were identified for PA. Admixture population structure analysis revealed seven subpopulations based on ancestral diversity in this panel. This is the first reported study to characterize fatty acid profiles across a chickpea diversity panel and perform GWAS to detect associations between genetic markers and concentrations of selected fatty acids. These findings demonstrate biofortification of chickpea fatty acids is possible using conventional and genomic breeding techniques, to develop superior cultivars with better fatty acid profiles for improved human health and plant stress responses.

Genome-wide association study as a powerful tool for dissecting competitive traits in legumes

Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.

A Genome-Wide Association Study Reveals Region Associated with Seed Protein Content in Cowpea

Cowpea (Vigna unguiculata L. Walp., 2n = 2x = 22) is a protein-rich crop that complements staple cereals for humans and serves as fodder for livestock. It is widely grown in Africa and other developing countries as the primary source of protein in the diet; therefore, it is necessary to identify the protein-related loci to improve cowpea breeding. In the current study, we conducted a genome-wide association study (GWAS) on 161 cowpea accessions (151 USDA germplasm plus 10 Arkansas breeding lines) with a wide range of seed protein contents (21.8~28.9%) with 110,155 high-quality whole-genome single-nucleotide polymorphisms (SNPs) to identify markers associated with protein content, then performed genomic prediction (GP) for future breeding. A total of seven significant SNP markers were identified using five GWAS models (single-marker regression (SMR), the general linear model (GLM), Mixed Linear Model (MLM), Fixed and Random Model Circulating Probability Unification (FarmCPU), and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), which are located at the same locus on chromosome 8 for seed protein content. This locus was associated with the gene Vigun08g039200, which was annotated as the protein of the thioredoxin superfamily, playing a critical function for protein content increase and nutritional quality improvement. In this study, a genomic prediction (GP) approach was employed to assess the accuracy of predicting seed protein content in cowpea. The GP was conducted using cross-prediction with five models, namely ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB), and Bayesian least absolute shrinkage and selection operator (BL), applied to seven random whole genome marker sets with different densities (10 k, 5 k, 2 k, 1 k, 500, 200, and 7), as well as significant markers identified through GWAS. The accuracies of the GP varied between 42.9% and 52.1% across the seven SNPs considered, depending on the model used. These findings not only have the potential to expedite the breeding cycle through early prediction of individual performance prior to phenotyping, but also offer practical implications for cowpea breeding programs striving to enhance seed protein content and nutritional quality.

The developmental dynamics in cool season legumes with focus on chickpea

Chickpea is one of the most widely consumed grain legume world-wide. Advances in next-generation sequencing and genomics tools have led to genetic dissection and identification of potential candidate genes regulating agronomic traits in chickpea. However, the developmental particularities and its potential in reforming the yield and nutritional value remain largely unexplored. Studies in crops such as rice, maize, tomato and pea have highlighted the contribution of key regulator of developmental events in yield related traits. A comprehensive knowledge on the development aspects of a crop can pave way for new vistas to explore. Pea and Medicago are the close relatives of genus Cicer and the basic developmental events in these legumes are similar. However, there are some distinct developmental features in chickpea which hold potential for future crop improvement endeavours. The global chickpea germplasm encompasses wide range of diversities in terms of morphology at both vegetative and reproductive stages. There is an immediate need for understanding the genetic and molecular basis of this diversity and utilizing them for the yield contributing trait improvement. The review discusses some of the key developmental events which have potential in yield enhancement and the lessons which can be learnt from model legumes in this regard.

Genome-wide association mapping of nutritional traits for designing superior chickpea varieties

Micronutrient malnutrition is a serious concern in many parts of the world; therefore, enhancing crop nutrient content is an important challenge. Chickpea (Cicer arietinum L.), a major food legume crop worldwide, is a vital source of protein and minerals in the vegetarian diet. This study evaluated a diverse set of 258 chickpea germplasm accessions for 12 key nutritional traits. A significant variation was observed for several nutritional traits, including crude protein (16.56-24.64/100 g), β-Carotene (0.003-0.104 mg/100 g), calcium (60.69-176.55 mg/100 g), and folate (0.413-6.537 mg/kg). These data, combined with the available whole-genome sequencing data for 318,644 SNPs, were used in genome-wide association studies comprising single-locus and multi-locus models. We also explored the effect of varying the minor allele frequency (MAF) levels and heterozygosity. We identified 62 significant marker-trait associations (MTAs) explaining up to 28.63% of the phenotypic variance (PV), of which nine were localized within genes regulating G protein-coupled receptor signaling pathway, proteasome assembly, intracellular signal transduction, and oxidation-reduction process, among others. The significant effect MTAs were located primarily on Ca1, Ca3, Ca4, and Ca6. Importantly, varying the level of heterozygosity was found to significantly affect the detection of associations contributing to traits of interest. We further identified seven promising accessions (ICC10399, ICC1392, ICC1710, ICC2263, ICC1431, ICC4182, and ICC16915) with superior agronomic performance and high nutritional content as potential donors for developing nutrient-rich, high-yielding chickpea varieties. Validation of the significant MTAs with higher PV could identify factors controlling the nutrient acquisition and facilitate the design of biofortified chickpeas for the future.

Genome-Wide Association Analysis Reveals Trait-Linked Markers for Grain Nutrient and Agronomic Traits in Diverse Set of Chickpea Germplasm

Chickpea is an inexpensive source of protein, minerals, and vitamins to the poor people living in arid and semi-arid regions of Southern Asia and Sub-Saharan Africa. New chickpea cultivars with enhanced levels of protein, Fe and Zn content are a medium-term strategy for supplying essential nutrients for human health and reducing malnutrition. In the current study, a chickpea reference set of 280 accessions, including landraces, breeding lines, and advanced cultivars, was evaluated for grain protein, Fe, Zn content and agronomic traits over two seasons. Using a mid-density 5k SNP array, 4603 highly informative SNPs distributed across the chickpea genome were used for GWAS analysis. Population structure analysis revealed three subpopulations (K = 3). Linkage disequilibrium (LD) was extensive, and LD decay was relatively low. A total of 20 and 46 marker-trait associations (MTAs) were identified for grain nutrient and agronomic traits, respectively, using FarmCPU and BLINK models. Of which seven SNPs for grain protein, twelve for Fe, and one for Zn content were distributed on chromosomes 1, 4, 6, and 7. The marker S4_4477846 on chr4 was found to be co-associated with grain protein over seasons. The markers S1_11613376 and S1_2772537 co-associated with grain Fe content under NSII and pooled seasons and S7_9379786 marker under NSI and pooled seasons. The markers S4_31996956 co-associated with grain Fe and days to maturity. SNP annotation of associated markers were found to be related to gene functions of metal ion binding, transporters, protein kinases, transcription factors, and many more functions involved in plant metabolism along with Fe and protein homeostasis. The identified significant MTAs has potential use in marker-assisted selection for developing nutrient-rich chickpea cultivars after validation in the breeding populations.

Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and 'Omics' Tools

Grain legumes are a rich source of dietary protein for millions of people globally and thus a key driver for securing global food security. Legume plant-based 'dietary protein' biofortification is an economic strategy for alleviating the menace of rising malnutrition-related problems and hidden hunger. Malnutrition from protein deficiency is predominant in human populations with an insufficient daily intake of animal protein/dietary protein due to economic limitations, especially in developing countries. Therefore, enhancing grain legume protein content will help eradicate protein-related malnutrition problems in low-income and underprivileged countries. Here, we review the exploitable genetic variability for grain protein content in various major grain legumes for improving the protein content of high-yielding, low-protein genotypes. We highlight classical genetics-based inheritance of protein content in various legumes and discuss advances in molecular marker technology that have enabled us to underpin various quantitative trait loci controlling seed protein content (SPC) in biparental-based mapping populations and genome-wide association studies. We also review the progress of functional genomics in deciphering the underlying candidate gene(s) controlling SPC in various grain legumes and the role of proteomics and metabolomics in shedding light on the accumulation of various novel proteins and metabolites in high-protein legume genotypes. Lastly, we detail the scope of genomic selection, high-throughput phenotyping, emerging genome editing tools, and speed breeding protocols for enhancing SPC in grain legumes to achieve legume-based dietary protein security and thus reduce the global hunger risk.

Protein Biofortification in Lentils (Lens culinaris Medik.) Toward Human Health

Lentil (Lens culinaris Medik.) is a nutritionally dense crop with significant quantities of protein, low-digestible carbohydrates, minerals, and vitamins. The amino acid composition of lentil protein can impact human health by maintaining amino acid balance for physiological functions and preventing protein-energy malnutrition and non-communicable diseases (NCDs). Thus, enhancing lentil protein quality through genetic biofortification, i.e., conventional plant breeding and molecular technologies, is vital for the nutritional improvement of lentil crops across the globe. This review highlights variation in protein concentration and quality across Lens species, genetic mechanisms controlling amino acid synthesis in plants, functions of amino acids, and the effect of antinutrients on the absorption of amino acids into the human body. Successful breeding strategies in lentils and other pulses are reviewed to demonstrate robust breeding approaches for protein biofortification. Future lentil breeding approaches will include rapid germplasm selection, phenotypic evaluation, genome-wide association studies, genetic engineering, and genome editing to select sequences that improve protein concentration and quality.

Genome-wide association study and population structure analysis of seed-bound amino acids and total protein in watermelon

BACKGROUND

Watermelon seeds are a powerhouse of value-added traits such as proteins, free amino acids, vitamins, and essential minerals, offering a paleo-friendly dietary option. Despite the availability of substantial genetic variation, there is no sufficient information on the natural variation in seed-bound amino acids or proteins across the watermelon germplasm. This study aimed to analyze the natural variation in watermelon seed amino acids and total protein and explore underpinning genetic loci by genome-wide association study (GWAS).

METHODS

The study evaluated the distribution of seed-bound free amino acids and total protein in 211 watermelon accessions of Citrullus spp, including 154 of Citrullus lanatus, 54 of Citrullus mucosospermus (egusi) and three of Citrullus amarus. We used the GWAS approach to associate seed phenotypes with 11,456 single nucleotide polymorphisms (SNPs) generated by genotyping-by-sequencing (GBS).

RESULTS

Our results demonstrate a significant natural variation in different free amino acids and total protein content across accessions and geographic regions. The accessions with high protein content and proportion of essential amino acids warrant its use for value-added benefits in the food and feed industries via biofortification. The GWAS analysis identified 188 SNPs coinciding with 167 candidate genes associated with watermelon seed-bound amino acids and total protein. Clustering of SNPs associated with individual amino acids found by principal component analysis was independent of the speciation or cultivar groups and was not selected during the domestication of sweet watermelon. The identified candidate genes were involved in metabolic pathways associated with amino acid metabolism, such as Argininosuccinate synthase, explaining 7% of the variation in arginine content, which validate their functional relevance and potential for marker-assisted analysis selection. This study provides a platform for exploring potential gene loci involved in seed-bound amino acids metabolism, useful in genetic analysis and development of watermelon varieties with superior seed nutritional values.

Chickpea (Cicer arietinum L.) as a Source of Essential Fatty Acids - A Biofortification Approach

Chickpea is a highly nutritious pulse crop with low digestible carbohydrates (40-60%), protein (15-22%), essential fats (4-8%), and a range of minerals and vitamins. The fatty acid composition of the seed adds value because fats govern the texture, shelf-life, flavor, aroma, and nutritional composition of chickpea-based food products. Therefore, the biofortification of essential fatty acids has become a nutritional breeding target for chickpea crop improvement programs worldwide. This paper examines global chickpea production, focusing on plant lipids, their functions, and their benefits to human health. In addition, this paper also reviews the chemical analysis of essential fatty acids and possible breeding targets to enrich essential fatty acids in chickpea (Cicer arietinum) biofortification. Biofortification of chickpea for essential fatty acids within safe levels will improve human health and support food processing to retain the quality and flavor of chickpea-based food products. Essential fatty acid biofortification is possible by phenotyping diverse chickpea germplasm over suitable locations and years and identifying the candidate genes responsible for quantitative trait loci mapping using genome-wide association mapping.

Recent Advances in Molecular Marker-Assisted Breeding for Quality Improvement of Traditional Chinese Medicine

BACKGROUND

The quality of Traditional Chinese Medicine (TCM), reflected by its bioactive compounds and associated contents, is directly linked to its clinical efficacy. Therefore, it is of great importance to improve the quality of TCM by increasing the bioactive compound content.

METHODS

Mapping the active component content-associated QTLs in TCM and further markerassisted breeding has enabled us to rapidly and effectively cultivate new varieties with high bioactive compound contents, which has opened the door for genetic breeding studies on medicinal plants.

RESULTS

In this paper, a strategy and technical molecular breeding method for TCM are discussed. The development of four methods and progress in functional marker development, as well as the applications of such markers in TCM, are reviewed.

CONCLUSION

The progress in, challenges of, and future of marker-assisted breeding for quality improvement of TCM are discussed, which provide valuable scientific references for future molecular breeding.

Novel Genes and Genetic Loci Associated With Root Morphological Traits, Phosphorus-Acquisition Efficiency and Phosphorus-Use Efficiency in Chickpea

Chickpea-the second most important grain legume worldwide-is cultivated mainly on marginal soils. Phosphorus (P) deficiency often restricts chickpea yields. Understanding the genetics of traits encoding P-acquisition efficiency and P-use efficiency will help develop strategies to reduce P-fertilizer application. A genome-wide association mapping approach was used to determine loci and genes associated with root architecture, root traits associated with P-acquisition efficiency and P-use efficiency, and any associated proxy traits. Using three statistical models-a generalized linear model (GLM), a mixed linear model (MLM), and a fixed and random model circulating probability unification (FarmCPU) -10, 51, and 40 marker-trait associations (MTAs), respectively were identified. A single nucleotide polymorphism (SNP) locus (Ca1_12310101) on Ca1 associated with three traits, i.e., physiological P-use efficiency, shoot dry weight, and shoot P content was identified. Genes related to shoot P concentration (NAD kinase 2, dynamin-related protein 1C), physiological P-use efficiency (fasciclin-like arabinogalactan protein), specific root length (4-coumarate-CoA ligase 1) and manganese concentration in mature leaves (ABC1 family protein) were identified. The MTAs and novel genes identified in this study can be used to improve P-use efficiency in chickpea.

Cicer turcicum: A New Cicer Species and Its Potential to Improve Chickpea

Genetic resources of the genus Cicer L. are not only limited when compared to other important food legumes and major cereal crops but also, they include several endemic species with endangered status based on the criteria of the International Union for Conservation of Nature. The chief threats to endemic and endangered Cicer species are over-grazing and habitat change in their natural environments driven by climate changes. During a collection mission in east and south-east Anatolia (Turkey), a new Cicer species was discovered, proposed here as C. turcicum Toker, Berger & Gokturk. Here, we describe the morphological characteristics, images, and ecology of the species, and present preliminary evidence of its potential utility for chickpea improvement. C. turcicum is an annual species, endemic to southeast Anatolia and to date has only been located in a single population distant from any other known annual Cicer species. It belongs to section Cicer M. Pop. of the subgenus Pseudononis M. Pop. of the genus Cicer L. (Fabaceae) and on the basis of internal transcribed spacer (ITS) sequence similarity appears to be a sister species of C. reticulatum Ladiz. and C. echinospermum P.H. Davis, both of which are inter-fertile with domestic chickpea (C. arietinum L.). With the addition of C. turcicum, the genus Cicer now comprises 10 annual and 36 perennial species. As a preliminary evaluation of its potential for chickpea improvement two accessions of C. turcicum were field screened for reproductive heat tolerance and seeds were tested for bruchid resistance alongside a representative group of wild and domestic annual Cicer species. C. turcicum expressed the highest heat tolerance and similar bruchid resistance as C. judaicum Boiss. and C. pinnatifidum Juab. & Spach, neither of which are in the primary genepool of domestic chickpea. Given that C. arietinum and C. reticulatum returned the lowest and the second lowest tolerance and resistance scores, C. turcicum may hold much potential for chickpea improvement if its close relatedness supports interspecific hybridization with the cultigen. Crossing experiments are currently underway to explore this question.

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.

Genome-Wide SNP Discovery and Mapping QTLs for Seed Iron and Zinc Concentrations in Chickpea (Cicer arietinum L.)

Biofortification through plant breeding is a cost-effective and sustainable approach towards addressing micronutrient malnutrition prevailing across the globe. Screening cultivars for micronutrient content and identification of quantitative trait loci (QTLs)/genes and markers help in the development of biofortified varieties in chickpea (Cicer arietinum L.). With the aim of identifying the genomic regions controlling seed Fe and Zn concentrations, the F2:3 population derived from a cross between MNK-1 and Annigeri 1 was genotyped using genotyping by sequencing approach and evaluated for Fe and Zn concentration. An intraspecific genetic linkage map comprising 839 single nucleotide polymorphisms (SNPs) spanning a total distance of 1,088.04 cM with an average marker density of 1.30 cM was constructed. By integrating the linkage map data with the phenotypic data of the F2:3 population, a total of 11 QTLs were detected for seed Fe concentration on CaLG03, CaLG04, and CaLG05, with phenotypic variation explained ranging from 7.2% (CaqFe3.4) to 13.4% (CaqFe4.2). For seed Zn concentration, eight QTLs were identified on CaLG04, CaLG05, and CaLG08. The QTLs individually explained phenotypic variations ranging between 5.7% (CaqZn8.1) and 13.7% (CaqZn4.3). Three QTLs for seed Fe and Zn concentrations (CaqFe4.4, CaqFe4.5, and CaqZn4.1) were colocated in the "QTL-hotspot" region on CaLG04 that harbors several drought tolerance-related QTLs. We identified genes in the QTL regions that encode iron-sulfur metabolism and zinc-dependent alcohol dehydrogenase activity on CaLG03, iron ion binding oxidoreductase on CaLG04, and zinc-induced facilitator-like protein and ZIP zinc/iron transport family protein on CaLG05. These genomic regions and the associated markers can be used in marker-assisted selection to increase seed Fe and Zn concentrations in agronomically superior chickpea varieties.

A high-density SNP-based linkage map using genotyping-by-sequencing and its utilization for improved genome assembly of chickpea (Cicer arietinum L.)

Genotyping-by-sequencing (GBS) allows rapid identification of markers for use in development of linkage maps, which expedite efficient breeding programs. In the present study, we have utilized GBS approach to identify and genotype single-nucleotide polymorphism (SNP) markers in an inter-specific RIL population of Cicer arietinum L. X C. reticulatum. A total of 141,639 raw SNPs were identified using the TASSEL-GBS pipeline. After stringent filtering, 8208 candidate SNPs were identified of which ~ 37% were localized in the intragenic regions followed by genic regions (~ 30%) and intergenic regions (~ 27%). We then utilized 6920 stringent selected SNPs from present study and 6714 SNPs and microsatellite markers available from previous studies for construction of linkage map. The resulting high-density linkage map comprising of eight linkage groups contained 13,590 markers which spanned 1299.14 cM of map length with an average marker density of 0.095 cM. Further, the derived linkage map was used to improve the available assembly of desi chickpea genome by anchoring 443 previously unplaced scaffolds onto eight linkage groups. The present efforts have refined anchoring of the desi chickpea genome assembly to 55.57% of the ~ 520 Mb of assembled desi genome. To the best of our knowledge, the linkage map generated in the present study represents one of the most dense linkage map developed for the crop till date. It will serve as a valuable resource for fine mapping and positional cloning of important quantitative trait loci (QTLs) associated with agronomical traits and also for anchoring and ordering of future genome sequence assemblies.

Genome-Wide Correlation of 36 Agronomic Traits in the 287 Pepper (Capsicum) Accessions Obtained from the SLAF-seq-Based GWAS

There are many agronomic traits of pepper (Capsicum L.) with abundant phenotypes that can benefit pepper growth. Using specific-locus amplified fragment sequencing (SLAF-seq), a genome-wide association study (GWAS) of 36 agronomic traits was carried out for 287 representative pepper accessions. To ensure the accuracy and reliability of the GWAS results, we analyzed the genetic diversity, distribution of labels (SLAF tags and single nucleotide polymorphisms (SNPs)) and population differentiation and determined the optimal statistical model. In our study, 1487 SNPs were highly significantly associated with 26 agronomic traits, and 2126 candidate genes were detected in the 100-kb region up- and down-stream near these SNPs. Furthermore, 13 major association peaks were identified for 11 key agronomic traits. Then we examined the correlations among the 36 agronomic traits and analyzed SNP distribution and found 37 SNP polymerization regions (total size: 264.69 Mbp) that could be selected areas in pepper breeding. We found that the stronger the correlation between the two traits, the greater the possibility of them being in more than one polymerization region, suggesting that they may be linked or that one pleiotropic gene controls them. These results provide a theoretical foundation for future multi-trait pyramid breeding of pepper. Finally, we found that the GWAS signals were highly consistent with those from the nuclear restorer-of-fertility (Rf) gene for cytoplasmic male sterility (CMS), verifying their reliability. We further identified Capana06g002967 and Capana06g002969 as Rf candidate genes by functional annotation and expression analysis, which provided a reference for the study of cytoplasmic male sterility in Capsicum.

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.

Genome-wide cis-regulatory signatures for modulation of agronomic traits as exemplified by drought yield index (DYI) in chickpea

Developing functional molecular tags from the cis-regulatory sequence components of genes is vital for their deployment in efficient genetic dissection of complex quantitative traits in crop plants including chickpea. The current study identified 431,194 conserved non-coding SNP (CNSNP) from the cis-regulatory element regions of genes which were annotated on a chickpea genome. These genome-wide CNSNP marker resources are made publicly accessible through a user-friendly web-database ( http://www.cnsnpcicarbase.com ). The CNSNP-based quantitative trait loci (QTL) and expression QTL (eQTL) mapping and genome-wide association study (GWAS) were further integrated with global gene expression landscapes, molecular haplotyping, and DNA-protein interaction study in the association panel and recombinant inbred lines (RIL) mapping population to decode complex genetic architecture of one of the vital seed yield trait under drought stress, drought yield index (DYI), in chickpea. This delineated two constituted natural haplotypes and alleles from a histone H3 protein-coding gene and its transcriptional regulator NAC transcription factor (TF) harboring the major QTLs and trans-acting eQTL governing DYI in chickpea. The effect of CNSNPs in TF-binding cis-element of a histone H3 gene in altering the binding affinity and transcriptional activity of NAC TF based on chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) assay was evident. The CNSNP-led promising molecular tags scanned will essentially have functional significance to decode transcriptional gene regulatory function and thus can drive translational genomic analysis in chickpea.

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.

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.

Co-localization of genomic regions associated with seed morphology and composition in a desi chickpea (Cicer arietinum L.) population varying in seed protein concentration

Major QTL on LG 1 and 3 control seed filling and seed coat development, thereby affecting seed shape, size, color, composition and weight, key determinants of crop yield and quality. A chickpea (Cicer arietinum L.) population consisting of 189 recombinant inbred lines (RILs) derived from a cross between medium-protein ICC 995 and high-protein ICC 5912 genotypes of the desi market class was analyzed for seed properties. Seed from the parental lines and RILs was produced in four different environments for determination of seed shape (SS), 100-seed weight (100-SW), protein (PRO) and starch (STA) concentration. Polymorphic genetic markers for the population were identified by Genotyping by Sequencing and assembled into a 522.5 cM genetic map. Phenotype data from the different growth environments were analyzed by QTL mapping done by single and multi-environment analyses and in addition, single marker association mapping. The analyses identified in total 11 QTL, of which the most significant (P < 0.05) loci were located on LG 1 (q-1.1), LG 2 (q-2.1), LG 3 (q-3.2, q-3.3), LG 4 (q-4.2), and LG 5 (q-5.1). STA was mostly affected by q-1.1, which explained 19.0% of the phenotypic variance for the trait. The largest QTL effects were demonstrated by q-3.2 that explained 52.5% of the phenotypic variances for 100-SW, 44.3% for PRO, and 14.6% for SS. This locus was also highly associated with flower color (COL; 95.2% explained) and showed q-3.2 alleles from the ICC 5912 parent conferred the blue flower color and production of small, round seeds with relatively high protein concentration. Genes affecting seed filling at q-1.1 and seed coat development at q-3.2, respectively, were considered to underlie differences in seed composition and morphology in the RIL population.

Analysis of genes encoding seed storage proteins (SSPs) in chickpea (Cicer arietinum L.) reveals co-expressing transcription factors and a seed-specific promoter

Improvement of the quality and quantity of chickpea seed protein can be greatly facilitated by an understanding of the genic organization and the genetic architecture of the genes encoding seed storage proteins (SSPs). The aim of this study was to provide a comprehensive analysis of the chickpea SSP genes, putative co-expressing transcription factors (TFs), and to identify a seed-specific SSP gene promoter. A genome-wide identification of SSP genes in chickpea led to the identification of 21 non-redundant SSP encoding genes located on 6 chromosomes. Phylogenetic analysis grouped SSP genes into 3 subgroups where members within the same clade demonstrated similar motif composition and intron-exon organization. Tandem duplications were identified to be the major contributors to the expansion of the SSP gene family in chickpea. Co-expression analysis revealed 14 TFs having expression profiles similar to the SSP genes that included members of important TF families that are known to regulate seed development. Expression analysis of SSP genes and TFs revealed significantly higher expression in late stages of seed development as well as in high seed protein content (HPC) genotypes. In silico analysis of the promoter regions of the SSP encoding genes revealed several seed-specific cis-regulatory elements such as RY repeats, ACGT motifs, CAANTG, and GCN4. A candidate promoter was analyzed for seed specificity by generating stable transgenics in Arabidopsis. Overall, this study provides a useful resource to explore the regulatory networks involved in SSP synthesis and/or accumulation for utilization in developing nutritionally improved chickpea genotypes.

Using Genomic Sequence Information to Increase Conservation and Sustainable Use of Crop Diversity and Benefit-Sharing

This article describes how CGIAR centers and partners are using genomic sequence information to promote the conservation and sustainable use of crop genetic diversity, and to generate and share benefits derived from those uses. The article highlights combined institutional, and benefit-sharing-related challenges that need to be addressed to support expanded use of digital sequence information in agricultural research and development.

Development of sequence-based markers for seed protein content in pigeonpea

Pigeonpea is an important source of dietary protein to over a billion people globally, but genetic enhancement of seed protein content (SPC) in the crop has received limited attention for a long time. Use of genomics-assisted breeding would facilitate accelerating genetic gain for SPC. However, neither genetic markers nor genes associated with this important trait have been identified in this crop. Therefore, the present study exploited whole genome re-sequencing (WGRS) data of four pigeonpea genotypes (~ 12X coverage) to identify sequence-based markers and associated candidate genes for SPC. By combining a common variant filtering strategy on available WGRS data with knowledge of gene functions in relation to SPC, 108 sequence variants from 57 genes were identified. These genes were assigned to 19 GO molecular function categories with 56% belonging to only two categories. Furthermore, Sanger sequencing confirmed presence of 75.4% of the variants in 37 genes. Out of 30 sequence variants converted into CAPS/dCAPS markers, 17 showed high level of polymorphism between low and high SPC genotypes. Assay of 16 of the polymorphic CAPS/dCAPS markers on an F₂ population of the cross ICP 5529 (high SPC) × ICP 11605 (low SPC), resulted in four of the CAPS/dCAPS markers significantly (P < 0.05) co-segregated with SPC. In summary, four markers derived from mutations in four genes will be useful for enhancing/regulating SPC in pigeonpea crop improvement programs.

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.

QTL mapping and GWAS reveal candidate genes controlling capsaicinoid content in Capsicum

Capsaicinoids are unique compounds produced only in peppers (Capsicum spp.). Several studies using classical quantitative trait loci (QTLs) mapping and genomewide association studies (GWAS) have identified QTLs controlling capsaicinoid content in peppers; however, neither the QTLs common to each population nor the candidate genes underlying them have been identified due to the limitations of each approach used. Here, we performed QTL mapping and GWAS for capsaicinoid content in peppers using two recombinant inbred line (RIL) populations and one GWAS population. Whole-genome resequencing and genotyping by sequencing (GBS) were used to construct high-density single nucleotide polymorphism (SNP) maps. Five QTL regions on chromosomes 1, 2, 3, 4 and 10 were commonly identified in both RIL populations over multiple locations and years. Furthermore, a total of 109 610 SNPs derived from two GBS libraries were used to analyse the GWAS population consisting of 208 C. annuum-clade accessions. A total of 69 QTL regions were identified from the GWAS, 10 of which were co-located with the QTLs identified from the two biparental populations. Within these regions, we were able to identify five candidate genes known to be involved in capsaicinoid biosynthesis. Our results demonstrate that QTL mapping and GBS-GWAS represent a powerful combined approach for the identification of loci controlling complex traits.

Population structure and association analysis of heat stress relevant traits in chickpea (Cicer arietinum L.)

Understanding genetic diversity and population structure is prerequisite to broaden the cultivated base of any crop. In the current investigation, we report discovery of a total of 319 alleles by assaying 81 SSRs on 71 chickpea genotypes. The cluster analysis based on Jaccard coefficient and unweighted neighbor joining algorithm categorized all genotypes into two major clusters. Cultivars grown within the same agro-climatic zones were clustered together, whereas the remaining genotypes particularly advanced breeding lines and accessions assigned to another cluster. Population structure analysis separated the entire collection into two subpopulations (K = 2) and the clustering pattern remained in close agreement with those of distance-based methods. Importantly, we also discovered marker trait association for membrane stability index (MSI) and leaf chlorophyll content measured as SPAD chlorophyll meter reading (SCMR), the two important physiological parameters indicative of heat stress (HS) tolerance in chickpea. Association analysis using both general linear and mixed linear models of the mean phenotypic data of traits recorded in 2016 and 2017 uncovered significant association of NCPGR206 and H2L102 with the MSI trait. Likewise, SSR markers GA9, TR31 and TA113 exhibited significant association with SCMR trait. The genomic regions putatively linked with two traits may be investigated in greater detail to further improve knowledge about the genetic architecture of HS tolerance in chickpea.

Population structure and association analysis of heat stress relevant traits in chickpea (Cicer arietinum L.)

Understanding genetic diversity and population structure is prerequisite to broaden the cultivated base of any crop. In the current investigation, we report discovery of a total of 319 alleles by assaying 81 SSRs on 71 chickpea genotypes. The cluster analysis based on Jaccard coefficient and unweighted neighbor joining algorithm categorized all genotypes into two major clusters. Cultivars grown within the same agro-climatic zones were clustered together, whereas the remaining genotypes particularly advanced breeding lines and accessions assigned to another cluster. Population structure analysis separated the entire collection into two subpopulations (K = 2) and the clustering pattern remained in close agreement with those of distance-based methods. Importantly, we also discovered marker trait association for membrane stability index (MSI) and leaf chlorophyll content measured as SPAD chlorophyll meter reading (SCMR), the two important physiological parameters indicative of heat stress (HS) tolerance in chickpea. Association analysis using both general linear and mixed linear models of the mean phenotypic data of traits recorded in 2016 and 2017 uncovered significant association of NCPGR206 and H2L102 with the MSI trait. Likewise, SSR markers GA9, TR31 and TA113 exhibited significant association with SCMR trait. The genomic regions putatively linked with two traits may be investigated in greater detail to further improve knowledge about the genetic architecture of HS tolerance in 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.

Genome-wide development and deployment of informative intron-spanning and intron-length polymorphism markers for genomics-assisted breeding applications in chickpea

The discovery and large-scale genotyping of informative gene-based markers is essential for rapid delineation of genes/QTLs governing stress tolerance and yield component traits in order to drive genetic enhancement in chickpea. A genome-wide 119169 and 110491 ISM (intron-spanning markers) from 23129 desi and 20386 kabuli protein-coding genes and 7454 in silico InDel (insertion-deletion) (1-45-bp)-based ILP (intron-length polymorphism) markers from 3283 genes were developed that were structurally and functionally annotated on eight chromosomes and unanchored scaffolds of chickpea. A much higher amplification efficiency (83%) and intra-specific polymorphic potential (86%) detected by these markers than that of other sequence-based genetic markers among desi and kabuli chickpea accessions was apparent even by a cost-effective agarose gel-based assay. The genome-wide physically mapped 1718 ILP markers assayed a wider level of functional genetic diversity (19-81%) and well-defined phylogenetics among domesticated chickpea accessions. The gene-derived 1424 ILP markers were anchored on a high-density (inter-marker distance: 0.65cM) desi intra-specific genetic linkage map/functional transcript map (ICC 4958×ICC 2263) of chickpea. This reference genetic map identified six major genomic regions harbouring six robust QTLs mapped on five chromosomes, which explained 11-23% seed weight trait variation (7.6-10.5 LOD) in chickpea. The integration of high-resolution QTL mapping with differential expression profiling detected six including one potential serine carboxypeptidase gene with ILP markers (linked tightly to the major seed weight QTLs) exhibiting seed-specific expression as well as pronounced up-regulation especially in seeds of high (ICC 4958) as compared to low (ICC 2263) seed weight mapping parental accessions. The marker information generated in the present study was made publicly accessible through a user-friendly web-resource, "Chickpea ISM-ILP Marker Database". The designing of multiple ISM and ILP markers (2-5 markers/gene) from an individual gene (transcription factor) with numerous aforementioned desirable genetic attributes can widen the user-preference to select suitable primer combination for simultaneous large-scale assaying of functional allelic variation, natural allelic diversity, molecular mapping and expression profiling of genes among chickpea accessions. This will essentially accelerate the identification of functionally relevant molecular tags regulating vital agronomic traits for genomics-assisted crop improvement by optimal resource expenses in chickpea.