Population genomic and genome-wide association studies of agroclimatic traits in sorghum

Accelerating crop improvement in sorghum, a staple food for people in semiarid regions across the developing world, is key to ensuring global food security in the context of climate change. To facilitate gene discovery and molecular breeding in sorghum, we have characterized ~265,000 single nucleotide polymorphisms (SNPs) in 971 worldwide accessions that have adapted to diverse agroclimatic conditions. Using this genome-wide SNP map, we have characterized population structure with respect to geographic origin and morphological type and identified patterns of ancient crop diffusion to diverse agroclimatic regions across Africa and Asia. To better understand the genomic patterns of diversification in sorghum, we quantified variation in nucleotide diversity, linkage disequilibrium, and recombination rates across the genome. Analyzing nucleotide diversity in landraces, we find evidence of selective sweeps around starch metabolism genes, whereas in landrace-derived introgression lines, we find introgressions around known height and maturity loci. To identify additional loci underlying variation in major agroclimatic traits, we performed genome-wide association studies (GWAS) on plant height components and inflorescence architecture. GWAS maps several classical loci for plant height, candidate genes for inflorescence architecture. Finally, we trace the independent spread of multiple haplotypes carrying alleles for short stature or long inflorescence branches. This genome-wide map of SNP variation in sorghum provides a basis for crop improvement through marker-assisted breeding and genomic selection.

Draft genome sequence of pigeonpea (Cajanus cajan), an orphan legume crop of resource-poor farmers

Pigeonpea is an important legume food crop grown primarily by smallholder farmers in many semi-arid tropical regions of the world. We used the Illumina next-generation sequencing platform to generate 237.2 Gb of sequence, which along with Sanger-based bacterial artificial chromosome end sequences and a genetic map, we assembled into scaffolds representing 72.7% (605.78 Mb) of the 833.07 Mb pigeonpea genome. Genome analysis predicted 48,680 genes for pigeonpea and also showed the potential role that certain gene families, for example, drought tolerance-related genes, have played throughout the domestication of pigeonpea and the evolution of its ancestors. Although we found a few segmental duplication events, we did not observe the recent genome-wide duplication events observed in soybean. This reference genome sequence will facilitate the identification of the genetic basis of agronomically important traits, and accelerate the development of improved pigeonpea varieties that could improve food security in many developing countries.

Pearl millet genome sequence provides a resource to improve agronomic traits in arid environments

Draft genome, 994 re-sequenced lines and GWAS for yield-traits provide a resource of genetics and genomics tools for pearl millet researchers and breeders.

Pearl millet [Cenchrus americanus (L.) Morrone] is a staple food for more than 90 million farmers in arid and semi-arid regions of sub-Saharan Africa, India and South Asia. We report the ∼1.79 Gb draft whole genome sequence of reference genotype Tift 23D₂B₁-P1-P5, which contains an estimated 38,579 genes. We highlight the substantial enrichment for wax biosynthesis genes, which may contribute to heat and drought tolerance in this crop. We resequenced and analyzed 994 pearl millet lines, enabling insights into population structure, genetic diversity and domestication. We use these resequencing data to establish marker trait associations for genomic selection, to define heterotic pools, and to predict hybrid performance. We believe that these resources should empower researchers and breeders to improve this important staple crop.

Genome-environment associations in sorghum landraces predict adaptive traits

Improving environmental adaptation in crops is essential for food security under global change, but phenotyping adaptive traits remains a major bottleneck. If associations between single-nucleotide polymorphism (SNP) alleles and environment of origin in crop landraces reflect adaptation, then these could be used to predict phenotypic variation for adaptive traits. We tested this proposition in the global food crop Sorghum bicolor, characterizing 1943 georeferenced landraces at 404,627 SNPs and quantifying allelic associations with bioclimatic and soil gradients. Environment explained a substantial portion of SNP variation, independent of geographical distance, and genic SNPs were enriched for environmental associations. Further, environment-associated SNPs predicted genotype-by-environment interactions under experimental drought stress and aluminum toxicity. Our results suggest that genomic signatures of environmental adaptation may be useful for crop improvement, enhancing germplasm identification and marker-assisted selection. Together, genome-environment associations and phenotypic analyses may reveal the basis of environmental adaptation.

Landrace Germplasm for Improving Yield and Abiotic Stress Adaptation

Plant landraces represent heterogeneous, local adaptations of domesticated species, and thereby provide genetic resources that meet current and new challenges for farming in stressful environments. These local ecotypes can show variable phenology and low-to-moderate edible yield, but are often highly nutritious. The main contributions of landraces to plant breeding have been traits for more efficient nutrient uptake and utilization, as well as useful genes for adaptation to stressful environments such as water stress, salinity, and high temperatures. We propose that a systematic landrace evaluation may define patterns of diversity, which will facilitate identifying alleles for enhancing yield and abiotic stress adaptation, thus raising the productivity and stability of staple crops in vulnerable environments.

Advances in Arachis genomics for peanut improvement

Peanut genomics is very challenging due to its inherent problem of genetic architecture. Blockage of gene flow from diploid wild relatives to the tetraploid; cultivated peanut, recent polyploidization combined with self pollination, and the narrow genetic base of the primary genepool have resulted in low genetic diversity that has remained a major bottleneck for genetic improvement of peanut. Harnessing the rich source of wild relatives has been negligible due to differences in ploidy level as well as genetic drag and undesirable alleles for low yield. Lack of appropriate genomic resources has severely hampered molecular breeding activities, and this crop remains among the less-studied crops. The last five years, however, have witnessed accelerated development of genomic resources such as development of molecular markers, genetic and physical maps, generation of expressed sequenced tags (ESTs), development of mutant resources, and functional genomics platforms that facilitate the identification of QTLs and discovery of genes associated with tolerance/resistance to abiotic and biotic stresses and agronomic traits. Molecular breeding has been initiated for several traits for development of superior genotypes. The genome or at least gene space sequence is expected to be available in near future and this will further accelerate use of biotechnological approaches for peanut improvement.

Large-scale development of cost-effective SNP marker assays for diversity assessment and genetic mapping in chickpea and comparative mapping in legumes

A set of 2486 single nucleotide polymorphisms (SNPs) were compiled in chickpea using four approaches, namely (i) Solexa/Illumina sequencing (1409), (ii) amplicon sequencing of tentative orthologous genes (TOGs) (604), (iii) mining of expressed sequence tags (ESTs) (286) and (iv) sequencing of candidate genes (187). Conversion of these SNPs to the cost-effective and flexible throughput Competitive Allele Specific PCR (KASPar) assays generated successful assays for 2005 SNPs. These marker assays have been designated as Chickpea KASPar Assay Markers (CKAMs). Screening of 70 genotypes including 58 diverse chickpea accessions and 12 BC(3) F(2) lines showed 1341 CKAMs as being polymorphic. Genetic analysis of these data clustered chickpea accessions based on geographical origin. Genotyping data generated for 671 CKAMs on the reference mapping population (Cicer arietinum ICC 4958 × Cicer reticulatum PI 489777) were compiled with 317 unpublished TOG-SNPs and 396 published markers for developing the genetic map. As a result, a second-generation genetic map comprising 1328 marker loci including novel 625 CKAMs, 314 TOG-SNPs and 389 published marker loci with an average inter-marker distance of 0.59 cM was constructed. Detailed analyses of 1064 mapped loci of this second-generation chickpea genetic map showed a higher degree of synteny with genome of Medicago truncatula, followed by Glycine max, Lotus japonicus and least with Vigna unguiculata. Development of these cost-effective CKAMs for SNP genotyping will be useful not only for genetics research and breeding applications in chickpea, but also for utilizing genome information from other sequenced or model legumes.

Genetic dissection of drought and heat tolerance in chickpea through genome-wide and candidate gene-based association mapping approaches

To understand the genetic basis of tolerance to drought and heat stresses in chickpea, a comprehensive association mapping approach has been undertaken. Phenotypic data were generated on the reference set (300 accessions, including 211 mini-core collection accessions) for drought tolerance related root traits, heat tolerance, yield and yield component traits from 1-7 seasons and 1-3 locations in India (Patancheru, Kanpur, Bangalore) and three locations in Africa (Nairobi, Egerton in Kenya and Debre Zeit in Ethiopia). Diversity Array Technology (DArT) markers equally distributed across chickpea genome were used to determine population structure and three sub-populations were identified using admixture model in STRUCTURE. The pairwise linkage disequilibrium (LD) estimated using the squared-allele frequency correlations (r2; when r2<0.20) was found to decay rapidly with the genetic distance of 5 cM. For establishing marker-trait associations (MTAs), both genome-wide and candidate gene-sequencing based association mapping approaches were conducted using 1,872 markers (1,072 DArTs, 651 single nucleotide polymorphisms [SNPs], 113 gene-based SNPs and 36 simple sequence repeats [SSRs]) and phenotyping data mentioned above employing mixed linear model (MLM) analysis with optimum compression with P3D method and kinship matrix. As a result, 312 significant MTAs were identified and a maximum number of MTAs (70) was identified for 100-seed weight. A total of 18 SNPs from 5 genes (ERECTA, 11 SNPs; ASR, 4 SNPs; DREB, 1 SNP; CAP2 promoter, 1 SNP and AMDH, 1SNP) were significantly associated with different traits. This study provides significant MTAs for drought and heat tolerance in chickpea that can be used, after validation, in molecular breeding for developing superior varieties with enhanced drought and heat tolerance.

Development and Evaluation of a High Density Genotyping 'Axiom_Arachis' Array with 58 K SNPs for Accelerating Genetics and Breeding in Groundnut

Single nucleotide polymorphisms (SNPs) are the most abundant DNA sequence variation in the genomes which can be used to associate genotypic variation to the phenotype. Therefore, availability of a high-density SNP array with uniform genome coverage can advance genetic studies and breeding applications. Here we report the development of a high-density SNP array 'Axiom_Arachis' with 58 K SNPs and its utility in groundnut genetic diversity study. In this context, from a total of 163,782 SNPs derived from DNA resequencing and RNA-sequencing of 41 groundnut accessions and wild diploid ancestors, a total of 58,233 unique and informative SNPs were selected for developing the array. In addition to cultivated groundnuts (Arachis hypogaea), fair representation was kept for other diploids (A. duranensis, A. stenosperma, A. cardenasii, A. magna and A. batizocoi). Genotyping of the groundnut 'Reference Set' containing 300 genotypes identified 44,424 polymorphic SNPs and genetic diversity analysis provided in-depth insights into the genetic architecture of this material. The availability of the high-density SNP array 'Axiom_Arachis' with 58 K SNPs will accelerate the process of high resolution trait genetics and molecular breeding in cultivated groundnut.

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

A rapid high-resolution genome-wide strategy for molecular mapping of major QTL(s)/gene(s) regulating important agronomic traits is vital for in-depth dissection of complex quantitative traits and genetic enhancement in chickpea. The present study for the first time employed a NGS-based whole-genome QTL-seq strategy to identify one major genomic region harbouring a robust 100-seed weight QTL using an intra-specific 221 chickpea mapping population (desi cv. ICC 7184 × desi cv. ICC 15061). The QTL-seq-derived major SW QTL (CaqSW1.1) was further validated by single-nucleotide polymorphism (SNP) and simple sequence repeat (SSR) marker-based traditional QTL mapping (47.6% R² at higher LOD >19). This reflects the reliability and efficacy of QTL-seq as a strategy for rapid genome-wide scanning and fine mapping of major trait regulatory QTLs in chickpea. The use of QTL-seq and classical QTL mapping in combination narrowed down the 1.37 Mb (comprising 177 genes) major SW QTL (CaqSW1.1) region into a 35 kb genomic interval on desi chickpea chromosome 1 containing six genes. One coding SNP (G/A)-carrying constitutive photomorphogenic9 (COP9) signalosome complex subunit 8 (CSN8) gene of these exhibited seed-specific expression, including pronounced differential up-/down-regulation in low and high seed weight mapping parents and homozygous individuals during seed development. The coding SNP mined in this potential seed weight-governing candidate CSN8 gene was found to be present exclusively in all cultivated species/genotypes, but not in any wild species/genotypes of primary, secondary and tertiary gene pools. This indicates the effect of strong artificial and/or natural selection pressure on target SW locus during chickpea domestication. The proposed QTL-seq-driven integrated genome-wide strategy has potential to delineate major candidate gene(s) harbouring a robust trait regulatory QTL rapidly with optimal use of resources. This will further assist us to extrapolate the molecular mechanism underlying complex quantitative traits at a genome-wide scale leading to fast-paced marker-assisted genetic improvement in diverse crop plants, including chickpea.

Novel SSR markers from BAC-end sequences, DArT arrays and a comprehensive genetic map with 1,291 marker loci for chickpea (Cicer arietinum L.)

Chickpea (Cicer arietinum L.) is the third most important cool season food legume, cultivated in arid and semi-arid regions of the world. The goal of this study was to develop novel molecular markers such as microsatellite or simple sequence repeat (SSR) markers from bacterial artificial chromosome (BAC)-end sequences (BESs) and diversity arrays technology (DArT) markers, and to construct a high-density genetic map based on recombinant inbred line (RIL) population ICC 4958 (C. arietinum)×PI 489777 (C. reticulatum). A BAC-library comprising 55,680 clones was constructed and 46,270 BESs were generated. Mining of these BESs provided 6,845 SSRs, and primer pairs were designed for 1,344 SSRs. In parallel, DArT arrays with ca. 15,000 clones were developed, and 5,397 clones were found polymorphic among 94 genotypes tested. Screening of newly developed BES-SSR markers and DArT arrays on the parental genotypes of the RIL mapping population showed polymorphism with 253 BES-SSR markers and 675 DArT markers. Segregation data obtained for these polymorphic markers and 494 markers data compiled from published reports or collaborators were used for constructing the genetic map. As a result, a comprehensive genetic map comprising 1,291 markers on eight linkage groups (LGs) spanning a total of 845.56 cM distance was developed (http://cmap.icrisat.ac.in/cmap/sm/cp/thudi/). The number of markers per linkage group ranged from 68 (LG 8) to 218 (LG 3) with an average inter-marker distance of 0.65 cM. While the developed resource of molecular markers will be useful for genetic diversity, genetic mapping and molecular breeding applications, the comprehensive genetic map with integrated BES-SSR markers will facilitate its anchoring to the physical map (under construction) to accelerate map-based cloning of genes in chickpea and comparative genome evolution studies in legumes.

Genetic structure, diversity, and allelic richness in composite collection and reference set in chickpea (Cicer arietinum L.)

BACKGROUND

Plant genetic resources (PGR) are the basic raw materials for future genetic progress and an insurance against unforeseen threats to agricultural production. An extensive characterization of PGR provides an opportunity to dissect structure, mine allelic variations, and identify diverse accessions for crop improvement. The Generation Challenge Program http://www.generationcp.org conceptualized the development of "composite collections" and extraction of "reference sets" from these for more efficient tapping of global crop-related genetic resources. In this study, we report the genetic structure, diversity and allelic richness in a composite collection of chickpea using SSR markers, and formation of a reference set of 300 accessions.

RESULTS

The 48 SSR markers detected 1683 alleles in 2915 accessions, of which, 935 were considered rare, 720 common and 28 most frequent. The alleles per locus ranged from 14 to 67, averaged 35, and the polymorphic information content was from 0.467 to 0.974, averaged 0.854. Marker polymorphism varied between groups of accessions in the composite collection and reference set. A number of group-specific alleles were detected: 104 in Kabuli, 297 in desi, and 69 in wild Cicer; 114 each in Mediterranean and West Asia (WA), 117 in South and South East Asia (SSEA), and 10 in African region accessions. Desi and kabuli shared 436 alleles, while wild Cicer shared 17 and 16 alleles with desi and kabuli, respectively. The accessions from SSEA and WA shared 74 alleles, while those from Mediterranean 38 and 33 alleles with WA and SSEA, respectively. Desi chickpea contained a higher proportion of rare alleles (53%) than kabuli (46%), while wild Cicer accessions were devoid of rare alleles. A genotype-based reference set captured 1315 (78%) of the 1683 composite collection alleles of which 463 were rare, 826 common, and 26 the most frequent alleles. The neighbour-joining tree diagram of this reference set represents diversity from all directions of the tree diagram of the composite collection.

CONCLUSION

The genotype-based reference set, reported here, is an ideal set of germplasm for allele mining, association genetics, mapping and cloning gene(s), and in applied breeding for the development of broad-based elite breeding lines/cultivars with superior yield and enhanced adaptation to diverse environments.

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.

Development and use of genic molecular markers (GMMs) for construction of a transcript map of chickpea (Cicer arietinum L.)

A transcript map has been constructed by the development and integration of genic molecular markers (GMMs) including single nucleotide polymorphism (SNP), genic microsatellite or simple sequence repeat (SSR) and intron spanning region (ISR)-based markers, on an inter-specific mapping population of chickpea, the third food legume crop of the world and the first food legume crop of India. For SNP discovery through allele re-sequencing, primer pairs were designed for 688 genes/expressed sequence tags (ESTs) of chickpea and 657 genes/ESTs of closely related species of chickpea. High-quality sequence data obtained for 220 candidate genic regions on 2-20 genotypes representing 9 Cicer species provided 1,893 SNPs with an average frequency of 1/35.83 bp and 0.34 PIC (polymorphism information content) value. On an average 2.9 haplotypes were present in 220 candidate genic regions with an average haplotype diversity of 0.6326. SNP2CAPS analysis of 220 sequence alignments, as mentioned above, provided a total of 192 CAPS candidates. Experimental analysis of these 192 CAPS candidates together with 87 CAPS candidates identified earlier through in silico mining of ESTs provided scorable amplification in 173 (62.01%) cases of which predicted assays were validated in 143 (82.66%) cases (CGMM). Alignments of chickpea unigenes with Medicago truncatula genome were used to develop 121 intron spanning region (CISR) markers of which 87 yielded scorable products. In addition, optimization of 77 EST-derived SSR (ICCeM) markers provided 51 scorable markers. Screening of easily assayable 281 markers including 143 CGMMs, 87 CISRs and 51 ICCeMs on 5 parental genotypes of three mapping populations identified 104 polymorphic markers including 90 markers on the inter-specific mapping population. Sixty-two of these GMMs together with 218 earlier published markers (including 64 GMM loci) and 20 other unpublished markers could be integrated into this genetic map. A genetic map developed here, therefore, has a total of 300 loci including 126 GMM loci and spans 766.56 cM, with an average inter-marker distance of 2.55 cM. In summary, this is the first report on the development of large-scale genic markers including development of easily assayable markers and a transcript map of chickpea. These resources should be useful not only for genome analysis and genetics and breeding applications of chickpea, but also for comparative legume genomics.

Accessing genetic diversity for crop improvement

Vast germplasm collections are accessible but their use for crop improvement is limited-efficiently accessing genetic diversity is still a challenge. Molecular markers have clarified the structure of genetic diversity in a broad range of crops. Recent developments have made whole-genome surveys and gene-targeted surveys possible, shedding light on population dynamics and on the impact of selection during domestication. Thanks to this new precision, germplasm description has gained analytical power for resolving the genetic basis of trait variation and adaptation in crops such as major cereals, chickpea, grapevine, cacao, or banana. The challenge now is to finely characterize all the facets of plant behavior in carefully chosen materials. We suggest broadening the use of 'core reference sets' so as to facilitate material sharing within the scientific community.

Haploids: Constraints and opportunities in plant breeding

The discovery of haploids in higher plants led to the use of doubled haploid (DH) technology in plant breeding. This article provides the state of the art on DH technology including the induction and identification of haploids, what factors influence haploid induction, molecular basis of microspore embryogenesis, the genetics underpinnings of haploid induction and its use in plant breeding, particularly to fix traits and unlock genetic variation. Both in vitro and in vivo methods have been used to induce haploids that are thereafter chromosome doubled to produce DH. Various heritable factors contribute to the successful induction of haploids, whose genetics is that of a quantitative trait. Genomic regions associated with in vitro and in vivo DH production were noted in various crops with the aid of DNA markers. It seems that F2 plants are the most suitable for the induction of DH lines than F1 plants. Identifying putative haploids is a key issue in haploid breeding. DH technology in Brassicas and cereals, such as barley, maize, rice, rye and wheat, has been improved and used routinely in cultivar development, while in other food staples such as pulses and root crops the technology has not reached to the stage leading to its application in plant breeding. The centromere-mediated haploid induction system has been used in Arabidopsis, but not yet in crops. Most food staples are derived from genomic resources-rich crops, including those with sequenced reference genomes. The integration of genomic resources with DH technology provides new opportunities for the improving selection methods, maximizing selection gains and accelerate cultivar development. Marker-aided breeding and DH technology have been used to improve host plant resistance in barley, rice, and wheat. Multinational seed companies are using DH technology in large-scale production of inbred lines for further development of hybrid cultivars, particularly in maize. The public sector provides support to national programs or small-medium private seed for the exploitation of DH technology in plant breeding.

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.

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.

Diversifying Food Systems in the Pursuit of Sustainable Food Production and Healthy Diets

Increasing demand for nutritious, safe, and healthy food because of a growing population, and the pledge to maintain biodiversity and other resources, pose a major challenge to agriculture that is already threatened by a changing climate. Diverse and healthy diets, largely based on plant-derived food, may reduce diet-related illnesses. Investments in plant sciences will be necessary to design diverse cropping systems balancing productivity, sustainability, and nutritional quality. Cultivar diversity and nutritional quality are crucial. We call for better cooperation between food and medical scientists, food sector industries, breeders, and farmers to develop diversified and nutritious cultivars that reduce soil degradation and dependence on external inputs, such as fertilizers and pesticides, and to increase adaptation to climate change and resistance to emerging pests.

Genomewide association studies for 50 agronomic traits in peanut using the 'reference set' comprising 300 genotypes from 48 countries of the semi-arid tropics of the world

Peanut is an important and nutritious agricultural commodity and a livelihood of many small-holder farmers in the semi-arid tropics (SAT) of world which are facing serious production threats. Integration of genomics tools with on-going genetic improvement approaches is expected to facilitate accelerated development of improved cultivars. Therefore, high-resolution genotyping and multiple season phenotyping data for 50 important agronomic, disease and quality traits were generated on the ‘reference set’ of peanut. This study reports comprehensive analyses of allelic diversity, population structure, linkage disequilibrium (LD) decay and marker-trait association (MTA) in peanut. Distinctness of all the genotypes can be established by using either an unique allele detected by a single SSR or a combination of unique alleles by two or more than two SSR markers. As expected, DArT features (2.0 alleles/locus, 0.125 PIC) showed lower allele frequency and polymorphic information content (PIC) than SSRs (22.21 alleles /locus, 0.715 PIC). Both marker types clearly differentiated the genotypes of diploids from tetraploids. Multi-allelic SSRs identified three sub-groups (K = 3) while the LD simulation trend line based on squared-allele frequency correlations (r²) predicted LD decay of 15–20 cM in peanut genome. Detailed analysis identified a total of 524 highly significant MTAs (pvalue >2.1×10–6) with wide phenotypic variance (PV) range (5.81–90.09%) for 36 traits. These MTAs after validation may be deployed in improving biotic resistance, oil/ seed/ nutritional quality, drought tolerance related traits, and yield/ yield components.

Genetic dissection of seed-iron and zinc concentrations in chickpea

The SNP-based high-resolution QTL mapping mapped eight major genomic regions harbouring robust QTLs governing seed-Fe and Zn concentrations (39.4% combined phenotypic variation explained/PVE) on six chromosomes of an intra-specific high-density genetic linkage map (1.56 cM map-density). 24620 SNPs discovered from genome-wide GBS (genotyping-by-sequencing) and 13 known cloned Fe and Zn contents-related chickpea gene-orthologs were genotyped in a structured population of 92 sequenced desi and kabuli accessions. The large-scale 16591 SNP genotyping- and phenotyping-based GWAS (genome-wide association study) identified 16 genomic loci/genes associated (29% combined PVE) with seed-Fe and Zn concentrations. Of these, 11 trait-associated SNPs in the genes linked tightly with eight QTLs were validated by QTL mapping. The seed-specific expression, including pronounced differential-regulation of 16 trait-associated genes particularly in accessions/mapping individuals with contrasting level of seed-Fe and Zn contents was apparent. Collectively, the aforementioned rapid integrated genomic strategy led to delineate novel functional non-synonymous and regulatory SNP allelic-variants from 16 known/candidate genes, including three strong trait-associated genes (encoding late embryogenesis abundant and yellow stripe-like 1 protein, and vacuolar protein sorting-associated protein) and eight major QTLs regulating seed-Fe and Zn concentrations in chickpea. These essential inputs thus have potential to be deployed in marker-assisted genetic enhancement for developing nutritionally-rich iron/zinc-biofortified chickpea cultivars.

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.

Superior haplotypes for haplotype-based breeding for drought tolerance in pigeonpea (Cajanus cajan L.)

Haplotype-based breeding, a recent promising breeding approach to develop tailor-made crop varieties, deals with identification of superior haplotypes and their deployment in breeding programmes. In this context, whole genome re-sequencing data of 292 genotypes from pigeonpea reference set were mined to identify the superior haplotypes for 10 drought-responsive candidate genes. A total of 83, 132 and 60 haplotypes were identified in breeding lines, landraces and wild species, respectively. Candidate gene-based association analysis of these 10 genes on a subset of 137 accessions of the pigeonpea reference set revealed 23 strong marker-trait associations (MTAs) in five genes influencing seven drought-responsive component traits. Haplo-pheno analysis for the strongly associated genes resulted in the identification of most promising haplotypes for three genes regulating five component drought traits. The haplotype C. cajan_23080-H2 for plant weight (PW), fresh weight (FW) and turgid weight (TW), the haplotype C. cajan_30211-H6 for PW, FW, TW and dry weight (DW), the haplotype C. cajan_26230-H11 for FW and DW and the haplotype C. cajan_26230-H5 for relative water content (RWC) were identified as superior haplotypes under drought stress condition. Furthermore, 17 accessions containing superior haplotypes for three drought-responsive genes were identified. The identified superior haplotypes and the accessions carrying these superior haplotypes will be very useful for deploying haplotype-based breeding to develop next-generation tailor-made better drought-responsive pigeonpea cultivars.