Millets: a nutritional powerhouse for ensuring food security.

MAIN CONCLUSION: Millets are important food source to ensure global food and nutritional security and are associated with health benefits. Millets have emerged as a nutritional powerhouse with the potential to address food security challenges worldwide. These ancient grains, which come in various forms, including finger millet, proso millet, and pearl millet, among others, are essential to a balanced diet, since they provide a wide range of nutritional advantages. Millets have a well-rounded nutritional profile with a high protein, dietary fiber, vitamin, and mineral content for optimal health and wellness. In addition to their nutritional advantages, millets exhibit remarkable adaptability and durability to various agroecological conditions, making them a valuable resource for smallholder farmers functioning in resource-poor regions. Promoting the growth and use of millet can lead to several benefits that researchers and development experts may discover, including improved nutrition, increased food security, and sustainable agricultural methods. Therefore, millets are food crops, that are climate smart, nutritional, and food secured to feed the increasing global population, and everyone could have a healthier, more resilient future.

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

The present study used a whole-genome, NGS resequencing-based mQTL-seq (multiple QTL-seq) strategy in two inter-specific mapping populations (Pusa 1103 × ILWC 46 and Pusa 256 × ILWC 46) to scan the major genomic region(s) underlying QTL(s) governing pod number trait in chickpea. Essentially, the whole-genome resequencing of low and high pod number-containing parental accessions and homozygous individuals (constituting bulks) from each of these two mapping populations discovered >8 million high-quality homozygous SNPs with respect to the reference kabuli chickpea. The functional significance of the physically mapped SNPs was apparent from the identified 2,264 non-synonymous and 23,550 regulatory SNPs, with 8-10% of these SNPs-carrying genes corresponding to transcription factors and disease resistance-related proteins. The utilization of these mined SNPs in Δ (SNP index)-led QTL-seq analysis and their correlation between two mapping populations based on mQTL-seq, narrowed down two (Caq(a)PN4.1: 867.8 kb and Caq(a)PN4.2: 1.8 Mb) major genomic regions harbouring robust pod number QTLs into the high-resolution short QTL intervals (Caq(b)PN4.1: 637.5 kb and Caq(b)PN4.2: 1.28 Mb) on chickpea chromosome 4. The integration of mQTL-seq-derived one novel robust QTL with QTL region-specific association analysis delineated the regulatory (C/T) and coding (C/A) SNPs-containing one pentatricopeptide repeat (PPR) gene at a major QTL region regulating pod number in chickpea. This target gene exhibited anther, mature pollen and pod-specific expression, including pronounced higher up-regulated (∼3.5-folds) transcript expression in high pod number-containing parental accessions and homozygous individuals of two mapping populations especially during pollen and pod development. The proposed mQTL-seq-driven combinatorial strategy has profound efficacy in rapid genome-wide scanning of potential candidate gene(s) underlying trait-associated high-resolution robust QTL(s), thereby expediting genomics-assisted breeding and genetic enhancement of crop plants, including chickpea.

A genome-scale integrated approach aids in genetic dissection of complex flowering time trait in chickpea.

A combinatorial approach of candidate gene-based association analysis and genome-wide association study (GWAS) integrated with QTL mapping, differential gene expression profiling and molecular haplotyping was deployed in the present study for quantitative dissection of complex flowering time trait in chickpea. Candidate gene-based association mapping in a flowering time association panel (92 diverse desi and kabuli accessions) was performed by employing the genotyping information of 5724 SNPs discovered from 82 known flowering chickpea gene orthologs of Arabidopsis and legumes as well as 832 gene-encoding transcripts that are differentially expressed during flower development in chickpea. GWAS using both genome-wide GBS- and candidate gene-based genotyping data of 30,129 SNPs in a structured population of 92 sequenced accessions (with 200-250 kb LD decay) detected eight maximum effect genomic SNP loci (genes) associated (34% combined PVE) with flowering time. Six flowering time-associated major genomic loci harbouring five robust QTLs mapped on a high-resolution intra-specific genetic linkage map were validated (11.6-27.3% PVE at 5.4-11.7 LOD) further by traditional QTL mapping. The flower-specific expression, including differential up- and down-regulation (>three folds) of eight flowering time-associated genes (including six genes validated by QTL mapping) especially in early flowering than late flowering contrasting chickpea accessions/mapping individuals during flower development was evident. The gene haplotype-based LD mapping discovered diverse novel natural allelic variants and haplotypes in eight genes with high trait association potential (41% combined PVE) for flowering time differentiation in cultivated and wild chickpea. Taken together, eight potential known/candidate flowering time-regulating genes [efl1 (early flowering 1), FLD (Flowering locus D), GI (GIGANTEA), Myb (Myeloblastosis), SFH3 (SEC14-like 3), bZIP (basic-leucine zipper), bHLH (basic helix-loop-helix) and SBP (SQUAMOSA promoter binding protein)], including novel markers, QTLs, alleles and haplotypes delineated by aforesaid genome-wide integrated approach have potential for marker-assisted genetic improvement and unravelling the domestication pattern of flowering time in chickpea.

A genome-wide SNP scan accelerates trait-regulatory genomic loci identification in chickpea.

We identified 44844 high-quality SNPs by sequencing 92 diverse chickpea accessions belonging to a seed and pod trait-specific association panel using reference genome- and de novo-based GBS (genotyping-by-sequencing) assays. A GWAS (genome-wide association study) in an association panel of 211, including the 92 sequenced accessions, identified 22 major genomic loci showing significant association (explaining 23-47% phenotypic variation) with pod and seed number/plant and 100-seed weight. Eighteen trait-regulatory major genomic loci underlying 13 robust QTLs were validated and mapped on an intra-specific genetic linkage map by QTL mapping. A combinatorial approach of GWAS, QTL mapping and gene haplotype-specific LD mapping and transcript profiling uncovered one superior haplotype and favourable natural allelic variants in the upstream regulatory region of a CesA-type cellulose synthase (Ca_Kabuli_CesA3) gene regulating high pod and seed number/plant (explaining 47% phenotypic variation) in chickpea. The up-regulation of this superior gene haplotype correlated with increased transcript expression of Ca_Kabuli_CesA3 gene in the pollen and pod of high pod/seed number accession, resulting in higher cellulose accumulation for normal pollen and pollen tube growth. A rapid combinatorial genome-wide SNP genotyping-based approach has potential to dissect complex quantitative agronomic traits and delineate trait-regulatory genomic loci (candidate genes) for genetic enhancement in crop plants, including chickpea.

Ultra-high density intra-specific genetic linkage maps accelerate identification of functionally relevant molecular tags governing important agronomic traits in chickpea.

We discovered 26785 and 16573 high-quality SNPs differentiating two parental genotypes of a RIL mapping population using reference desi and kabuli genome-based GBS assay. Of these, 3625 and 2177 SNPs have been integrated into eight desi and kabuli chromosomes, respectively in order to construct ultra-high density (0.20-0.37 cM) intra-specific chickpea genetic linkage maps. One of these constructed high-resolution genetic map has potential to identify 33 major genomic regions harbouring 35 robust QTLs (PVE: 17.9-39.7%) associated with three agronomic traits, which were mapped within <1 cM mean marker intervals on desi chromosomes. The extended LD (linkage disequilibrium) decay (~15 cM) in chromosomes of genetic maps have encouraged us to use a rapid integrated approach (comparative QTL mapping, QTL-region specific haplotype/LD-based trait association analysis, expression profiling and gene haplotype-based association mapping) rather than a traditional QTL map-based cloning method to narrow-down one major seed weight (SW) robust QTL region. It delineated favourable natural allelic variants and superior haplotype-containing one seed-specific candidate embryo defective gene regulating SW in chickpea. The ultra-high-resolution genetic maps, QTLs/genes and alleles/haplotypes-related genomic information generated and integrated strategy for rapid QTL/gene identification developed have potential to expedite genomics-assisted breeding applications in crop plants, including chickpea for their genetic enhancement.

Development and Integration of Genome-Wide Polymorphic Microsatellite Markers onto a Reference Linkage Map for Constructing a High-Density Genetic Map of Chickpea.

The identification of informative in silico polymorphic genomic and genic microsatellite markers by comparing the genome and transcriptome sequences of crop genotypes is a rapid, cost-effective and non-laborious approach for large-scale marker validation and genotyping applications, including construction of high-density genetic maps. We designed 1494 markers, including 1016 genomic and 478 transcript-derived microsatellite markers showing in-silico fragment length polymorphism between two parental genotypes (Cicer arietinum ICC4958 and C. reticulatum PI489777) of an inter-specific reference mapping population. High amplification efficiency (87%), experimental validation success rate (81%) and polymorphic potential (55%) of these microsatellite markers suggest their effective use in various applications of chickpea genetics and breeding. Intra-specific polymorphic potential (48%) detected by microsatellite markers in 22 desi and kabuli chickpea genotypes was lower than inter-specific polymorphic potential (59%). An advanced, high-density, integrated and inter-specific chickpea genetic map (ICC4958 x PI489777) having 1697 map positions spanning 1061.16 cM with an average inter-marker distance of 0.625 cM was constructed by assigning 634 novel informative transcript-derived and genomic microsatellite markers on eight linkage groups (LGs) of our prior documented, 1063 marker-based genetic map. The constructed genome map identified 88, including four major (7-23 cM) longest high-resolution genomic regions on LGs 3, 5 and 8, where the maximum number of novel genomic and genic microsatellite markers were specifically clustered within 1 cM genetic distance. It was for the first time in chickpea that in silico FLP analysis at genome-wide level was carried out and such a large number of microsatellite markers were identified, experimentally validated and further used in genetic mapping. To best of our knowledge, in the presently constructed genetic map, we mapped highest number of new sequence-based robust microsatellite markers (634) which is an advancement over the previously documented (~300 markers) inter-specific genetic maps. This advanced high-density map will serve as a foundation for large-scale marker validation and genotyping applications, including identification and targeted mapping of trait-specific genes/QTLs (quantitative trait loci) with sub-optimal use of resources and labour in chickpea.

Employing genome-wide SNP discovery and genotyping strategy to extrapolate the natural allelic diversity and domestication patterns in chickpea.

The genome-wide discovery and high-throughput genotyping of SNPs in chickpea natural germplasm lines is indispensable to extrapolate their natural allelic diversity, domestication, and linkage disequilibrium (LD) patterns leading to the genetic enhancement of this vital legume crop. We discovered 44,844 high-quality SNPs by sequencing of 93 diverse cultivated desi, kabuli, and wild chickpea accessions using reference genome- and de novo-based GBS (genotyping-by-sequencing) assays that were physically mapped across eight chromosomes of desi and kabuli. Of these, 22,542 SNPs were structurally annotated in different coding and non-coding sequence components of genes. Genes with 3296 non-synonymous and 269 regulatory SNPs could functionally differentiate accessions based on their contrasting agronomic traits. A high experimental validation success rate (92%) and reproducibility (100%) along with strong sensitivity (93-96%) and specificity (99%) of GBS-based SNPs was observed. This infers the robustness of GBS as a high-throughput assay for rapid large-scale mining and genotyping of genome-wide SNPs in chickpea with sub-optimal use of resources. With 23,798 genome-wide SNPs, a relatively high intra-specific polymorphic potential (49.5%) and broader molecular diversity (13-89%)/functional allelic diversity (18-77%) was apparent among 93 chickpea accessions, suggesting their tremendous applicability in rapid selection of desirable diverse accessions/inter-specific hybrids in chickpea crossbred varietal improvement program. The genome-wide SNPs revealed complex admixed domestication pattern, extensive LD estimates (0.54-0.68) and extended LD decay (400-500 kb) in a structured population inclusive of 93 accessions. These findings reflect the utility of our identified SNPs for subsequent genome-wide association study (GWAS) and selective sweep-based domestication trait dissection analysis to identify potential genomic loci (gene-associated targets) specifically regulating important complex quantitative agronomic traits in chickpea. The numerous informative genome-wide SNPs, natural allelic diversity-led domestication pattern, and LD-based information generated in our study have got multidimensional applicability with respect to chickpea genomics-assisted breeding.

Genome-wide conserved non-coding microsatellite (CNMS) marker-based integrative genetical genomics for quantitative dissection of seed weight in chickpea.

Phylogenetic footprinting identified 666 genome-wide paralogous and orthologous CNMS (conserved non-coding microsatellite) markers from 5'-untranslated and regulatory regions (URRs) of 603 protein-coding chickpea genes. The (CT)n and (GA)n CNMS carrying CTRMCAMV35S and GAGA8BKN3 regulatory elements, respectively, are abundant in the chickpea genome. The mapped genic CNMS markers with robust amplification efficiencies (94.7%) detected higher intraspecific polymorphic potential (37.6%) among genotypes, implying their immense utility in chickpea breeding and genetic analyses. Seventeen differentially expressed CNMS marker-associated genes showing strong preferential and seed tissue/developmental stage-specific expression in contrasting genotypes were selected to narrow down the gene targets underlying seed weight quantitative trait loci (QTLs)/eQTLs (expression QTLs) through integrative genetical genomics. The integration of transcript profiling with seed weight QTL/eQTL mapping, molecular haplotyping, and association analyses identified potential molecular tags (GAGA8BKN3 and RAV1AAT regulatory elements and alleles/haplotypes) in the LOB-domain-containing protein- and KANADI protein-encoding transcription factor genes controlling the cis-regulated expression for seed weight in the chickpea. This emphasizes the potential of CNMS marker-based integrative genetical genomics for the quantitative genetic dissection of complex seed weight in chickpea.

An integrated genomic approach for rapid delineation of candidate genes regulating agro-morphological traits in chickpea.

The identification and fine mapping of robust quantitative trait loci (QTLs)/genes governing important agro-morphological traits in chickpea still lacks systematic efforts at a genome-wide scale involving wild Cicer accessions. In this context, an 834 simple sequence repeat and single-nucleotide polymorphism marker-based high-density genetic linkage map between cultivated and wild parental accessions (Cicer arietinum desi cv. ICC 4958 and Cicer reticulatum wild cv. ICC 17160) was constructed. This inter-specific genetic map comprising eight linkage groups spanned a map length of 949.4 cM with an average inter-marker distance of 1.14 cM. Eleven novel major genomic regions harbouring 15 robust QTLs (15.6-39.8% R(2) at 4.2-15.7 logarithm of odds) associated with four agro-morphological traits (100-seed weight, pod and branch number/plant and plant hairiness) were identified and mapped on chickpea chromosomes. Most of these QTLs showed positive additive gene effects with effective allelic contribution from ICC 4958, particularly for increasing seed weight (SW) and pod and branch number. One robust SW-influencing major QTL region (qSW4.2) has been narrowed down by combining QTL mapping with high-resolution QTL region-specific association analysis, differential expression profiling and gene haplotype-based association/LD mapping. This enabled to delineate a strong SW-regulating ABI3VP1 transcription factor (TF) gene at trait-specific QTL interval and consequently identified favourable natural allelic variants and superior high seed weight-specific haplotypes in the upstream regulatory region of this gene showing increased transcript expression during seed development. The genes (TFs) harbouring diverse trait-regulating QTLs, once validated and fine-mapped by our developed rapid integrated genomic approach and through gene/QTL map-based cloning, can be utilized as potential candidates for marker-assisted genetic enhancement of chickpea.

Natural allelic diversity, genetic structure and linkage disequilibrium pattern in wild chickpea.

Characterization of natural allelic diversity and understanding the genetic structure and linkage disequilibrium (LD) pattern in wild germplasm accessions by large-scale genotyping of informative microsatellite and single nucleotide polymorphism (SNP) markers is requisite to facilitate chickpea genetic improvement. Large-scale validation and high-throughput genotyping of genome-wide physically mapped 478 genic and genomic microsatellite markers and 380 transcription factor gene-derived SNP markers using gel-based assay, fluorescent dye-labelled automated fragment analyser and matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass array have been performed. Outcome revealed their high genotyping success rate (97.5%) and existence of a high level of natural allelic diversity among 94 wild and cultivated Cicer accessions. High intra- and inter-specific polymorphic potential and wider molecular diversity (11-94%) along with a broader genetic base (13-78%) specifically in the functional genic regions of wild accessions was assayed by mapped markers. It suggested their utility in monitoring introgression and transferring target trait-specific genomic (gene) regions from wild to cultivated gene pool for the genetic enhancement. Distinct species/gene pool-wise differentiation, admixed domestication pattern, and differential genome-wide recombination and LD estimates/decay observed in a six structured population of wild and cultivated accessions using mapped markers further signifies their usefulness in chickpea genetics, genomics and breeding.

Integrated genomics and molecular breeding approaches for dissecting the complex quantitative traits in crop plants.

The enormous population growth, climate change and global warming are now considered major threats to agriculture and world's food security. To improve the productivity and sustainability of agriculture, the development of highyielding and durable abiotic and biotic stress-tolerant cultivars and/climate resilient crops is essential. Henceforth, understanding the molecular mechanism and dissection of complex quantitative yield and stress tolerance traits is the prime objective in current agricultural biotechnology research. In recent years, tremendous progress has been made in plant genomics and molecular breeding research pertaining to conventional and next-generation whole genome, transcriptome and epigenome sequencing efforts, generation of huge genomic, transcriptomic and epigenomic resources and development of modern genomics-assisted breeding approaches in diverse crop genotypes with contrasting yield and abiotic stress tolerance traits. Unfortunately, the detailed molecular mechanism and gene regulatory networks controlling such complex quantitative traits is not yet well understood in crop plants. Therefore, we propose an integrated strategies involving available enormous and diverse traditional and modern -omics (structural, functional, comparative and epigenomics) approaches/resources and genomics-assisted breeding methods which agricultural biotechnologist can adopt/utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in crop plants. This would provide clues and much needed inputs for rapid selection of novel functionally relevant molecular tags regulating such complex traits to expedite traditional and modern marker-assisted genetic enhancement studies in target crop species for developing high-yielding stress-tolerant varieties.

Functionally relevant microsatellite markers from chickpea transcription factor genes for efficient genotyping applications and trait association mapping.

We developed 1108 transcription factor gene-derived microsatellite (TFGMS) and 161 transcription factor functional domain-associated microsatellite (TFFDMS) markers from 707 TFs of chickpea. The robust amplification efficiency (96.5%) and high intra-specific polymorphic potential (34%) detected by markers suggest their immense utilities in efficient large-scale genotyping applications, including construction of both physical and functional transcript maps and understanding population structure. Candidate gene-based association analysis revealed strong genetic association of TFFDMS markers with three major seed and pod traits. Further, TFGMS markers in the 5' untranslated regions of TF genes showing differential expression during seed development had higher trait association potential. The significance of TFFDMS markers was demonstrated by correlating their allelic variation with amino acid sequence expansion/contraction in the functional domain and alteration of secondary protein structure encoded by genes. The seed weight-associated markers were validated through traditional bi-parental genetic mapping. The determination of gene-specific linkage disequilibrium (LD) patterns in desi and kabuli based on single nucleotide polymorphism-microsatellite marker haplotypes revealed extended LD decay, enhanced LD resolution and trait association potential of genes. The evolutionary history of a strong seed-size/weight-associated TF based on natural variation and haplotype sharing among desi, kabuli and wild unravelled useful information having implication for seed-size trait evolution during chickpea domestication.

Comparative analysis of kabuli chickpea transcriptome with desi and wild chickpea provides a rich resource for development of functional markers.

Chickpea (Cicer arietinum L.) is an important crop legume plant with high nutritional value. The transcriptomes of desi and wild chickpea have already been sequenced. In this study, we sequenced the transcriptome of kabuli chickpea, C. arietinum (genotype ICCV2), having higher commercial value, using GS-FLX Roche 454 and Illumina technologies. The assemblies of both Roche 454 and Illumina datasets were optimized using various assembly programs and parameters. The final optimized hybrid assembly generated 43,389 transcripts with an average length of 1065 bp and N50 length of 1653 bp representing 46.2 Mb of kabuli chickpea transcriptome. We identified a total of 5409 simple sequence repeats (SSRs) in these transcript sequences. Among these, at least 130 and 493 SSRs were polymorphic with desi (ICC4958) and wild (PI489777) chickpea, respectively. In addition, a total of 1986 and 37,954 single nucleotide polymorphisms (SNPs) were predicted in kabuli/desi and kabuli/wild genotypes, respectively. The SNP frequency was 0.043 SNP per kb for kabuli/desi and 0.821 SNP per kb for kabuli/wild, reflecting very low genetic diversity in chickpea. Further, SSRs and SNPs present in tissue-specific and transcription factor encoding transcripts have been identified. The experimental validation of a selected set of polymorphic SSRs and SNPs exhibited high intra-specific polymorphism potential between desi and kabuli chickpea, suggesting their utility in large-scale genotyping applications. The kabuli chickpea gene index assembled, and SSRs and SNPs identified in this study will serve as useful genomic resource for genetic improvement of chickpea.