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Peanut pods develop underground, which is the most salient characteristic in peanut. However, its developmental transcriptome remains largely unknown. In the present study, we sequenced over one billion transcripts to explore the developmental transcriptome of peanut pod using Illumina sequencing. Moreover, we identified and quantified the abundances of 165,689 transcripts in seed and shell tissues along with a pod developmental gradient. The dynamic changes of differentially expressed transcripts (DETs) were described in seed and shell. Additionally, we found that photosynthetic genes were not only pronouncedly enriched in aerial pod, but also played roles in developing pod under dark condition. Genes functioning in photomorphogenesis showed distinct expression profiles along subterranean pod development. Clustering analysis unraveled a dynamic transcriptome, in which transcripts for DNA synthesis and cell division during pod expansion were transitioning to transcripts for cell expansion and storage activity during seed filling. Collectively, our study formed a transcriptional baseline for peanut fruit development under dark condition.

The genome sequences of 16 Streptomyces strains, showing potential for plant growth-promotion (PGP) activities in rice, sorghum, chickpea and pigeonpea, isolated from herbal vermicompost, have been decoded. The genome assemblies of the 16 Streptomyces strains ranged from 6.8 Mb to 8.31 Mb, with a GC content of 72 to 73%. The extent of sequence similarity (in terms of shared ortholog) in 16 Streptomyces strains showed 70 to 85% common genes to the closest publicly available Streptomyces genomes. It was possible to identify ~1,850 molecular functions across these 16 strains, of which close to 50% were conserved across the genomes of Streptomyces strains, whereas, ~10% were strain specific and the rest were present in various combinations. Genome assemblies of the 16 Streptomyces strains have also provided genes involved in key pathways related to PGP and biocontrol traits such as siderophores, auxin, hydrocyanic acid, chitinase and cellulase. Further, the genome assemblies provided better understanding of genetic similarity among target strains and with the publically available Streptomyces strains.

Tomato spotted wilt virus (TSWV) is a devastating disease to peanut growers in the South-eastern region of the United States. Newly released peanut cultivars in recent years are crucial as they have some levels of resistance to TSWV. One mapping population of recombinant inbred line (RIL) used in this study was derived from peanut lines of SunOleic 97R and NC94022. A whole genome re-sequencing approach was used to sequence these two parents and 140 RILs. A recombination bin-based genetic map was constructed, with 5,816 bins and 20 linkage groups covering a total length of 2004 cM. Using this map, we identified three QTLs which were colocalized on chromosome A01. One QTL had the largest effect of 36.51% to the phenotypic variation and encompassed 89.5 Kb genomic region. This genome region had a cluster of genes, which code for chitinases, strictosidine synthase-like, and NBS-LRR proteins. SNPs linked to this QTL were used to develop Kompetitive allele specific PCR (KASP) markers, and the validated KASP markers showed expected segregation of alleles coming from resistant and susceptible parents within the population. Therefore, this bin-map and QTL associated with TSWV resistance made it possible for functional gene mapping, map-based cloning, and marker-assisted breeding. This study identified the highest number of SNP makers and demonstrated recombination bin-based map for QTL identification in peanut. The chitinase gene clusters and NBS-LRR disease resistance genes in this region suggest the possible involvement in peanut resistance to TSWV.

The root-lesion nematode, Pratylenchus thornei, is one of the major plant-parasitic nematode species causing significant yield losses in chickpea (Cicer arietinum). In order to identify the underlying mechanisms of resistance to P. thornei, the transcriptomes of control and inoculated roots of three chickpea genotypes viz. D05253 > F3TMWR2AB001 (resistant advanced breeding line), PBA HatTrick (moderately resistant cultivar), and Kyabra (susceptible cultivar) were studied at 20 and 50 days post inoculation using the RNA-seq approach. On analyzing the 633.3 million reads generated, 962 differentially expressed genes (DEGs) were identified. Comparative analysis revealed that the majority of DEGs upregulated in the resistant genotype were downregulated in the moderately resistant and susceptible genotypes. Transcription factor families WRKY and bZIP were uniquely expressed in the resistant genotype. The genes Cysteine-rich receptor-like protein kinase 10, Protein lifeguard-like, Protein detoxification, Bidirectional sugar transporter Sugars Will Eventually be Exported Transporters1 (SWEET1), and Subtilisin-like protease were found to play cross-functional roles in the resistant chickpea genotype against P. thornei. The identified candidate genes for resistance to P. thornei in chickpea can be explored further to develop markers and accelerate the introgression of P. thornei resistance into elite chickpea cultivars.

Recombination hot spots (RHP), caused by meiosis, are considered to play crucial roles in improvement and domestication of crop. Cultivated peanut is one of the most important rich-source of oil and protein crops. However, no direct scale of recombination events and RHP have been estimated for peanut. To examine the scale of recombination events and RHP in peanut, a RIL population with 200 lines and a natural population with 49 cultivars were evaluated. The precise integrated map comprises 4837 SLAF markers with genetic length of 2915.46 cM and density of 1.66 markers per cM in whole genome. An average of 30.0 crossover (2.06 cMMb−1) events was detected per RIL plant. The crossover events (CE) showed uneven distribution among B sub-genome (2.32) and A sub-genome (1.85). There were 4.34% and 7.86% of the genome contained large numbers of CE (> 50 cMMb−1) along chromosomes in F6 and natural population, respectively. High density of CE regions called RHP, showed negative relationship to marker haplotypes conservative region but positive to heatmap of recombination. The genes located within the RHP regions by GO categories showed the responding of environmental stimuli, which suggested that recombination plays a crucial role in peanut adaptation to changing environments

Drought is one of the main constraints in peanut production in West Texas and eastern New Mexico regions due to the depletion of groundwater. A multi-seasonal phenotypic analysis of 10 peanut genotypes revealed C76-16 (C-76) and Valencia-C (Val-C) as the best and poor performers under deficit irrigation (DI) in West Texas, respectively. In order to decipher transcriptome changes under DI, RNA-seq was performed in C-76 and Val-C. Approximately 369 million raw reads were generated from 12 different libraries of two genotypes subjected to fully irrigated (FI) and DI conditions, of which ~329 million (90.2%) filtered reads were mapped to the diploid ancestors of peanut. The transcriptome analysis detected 4,508 differentially expressed genes (DEGs), 1554 genes encoding transcription factors (TFs) and a total of 514 single nucleotide polymorphisms (SNPs) among the identified DEGs. The comparative analysis between the two genotypes revealed higher and integral tolerance in C-76 through activation of key genes involved in ABA and sucrose metabolic pathways. Interestingly, one SNP from the gene coding F-box protein (Araip.3WN1Q) and another SNP from gene coding for the lipid transfer protein (Aradu.03ENG) showed polymorphism in selected contrasting genotypes. These SNPs after further validation may be useful for performing early generation selection for selecting drought-responsive genotypes.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Fusarium wilt (FW) is one of the most important biotic stresses causing yield losses in pigeonpea. Genetic improvement of pigeonpea through genomics-assisted breeding (GAB) is an economically feasible option for the development of high yielding FW resistant genotypes. In this context, two recombinant inbred lines (RILs) (ICPB 2049 × ICPL 99050 designated as PRIL_A and ICPL 20096 × ICPL 332 designated as PRIL_B) and one F2 (ICPL 85063 × ICPL 87119) populations were used for the development of high density genetic maps. Genotyping-by-sequencing (GBS) approach was used to identify and genotype SNPs in three mapping populations. As a result, three high density genetic maps with 964, 1101 and 557 SNPs with an average marker distance of 1.16, 0.84 and 2.60 cM were developed in PRIL_A, PRIL_B and F2, respectively. Based on the multi-location and multi-year phenotypic data of FW resistance a total of 14 quantitative trait loci (QTLs) including six major QTLs explaining >10% phenotypic variance explained (PVE) were identified. Comparative analysis across the populations has revealed three important QTLs (qFW11.1, qFW11.2 and qFW11.3) with upto 56.45% PVE for FW resistance. This is the first report of QTL mapping for FW resistance in pigeonpea and identified genomic region could be utilized in GAB.

The genetic architecture of seed protein content (SPC) and its relationships to agronomic traits in pigeonpea is poorly understood. Accordingly, five F2 populations segregating for SPC and four agronomic traits (seed weight (SW), seed yield (SY), growth habit (GH) and days to first flowering (DFF)) were phenotyped and genotyped using genotyping-by-sequencing approach. Five high-density population-specific genetic maps were constructed with an average inter-marker distance of 1.6 to 3.5 cM, and subsequently, integrated into a consensus map with average marker spacing of 1.6 cM. Based on analysis of phenotyping data and genotyping data, 192 main effect QTLs (M-QTLs) with phenotypic variation explained (PVE) of 0.7 to 91.3% were detected for the five traits across the five populations. Major effect (PVE ≥ 10%) M-QTLs included 14 M-QTLs for SPC, 16 M-QTLs for SW, 17 M-QTLs for SY, 19 M-QTLs for GH and 24 M-QTLs for DFF. Also, 573 epistatic QTLs (E-QTLs) were detected with PVE ranging from 6.3 to 99.4% across traits and populations. Colocalization of M-QTLs and E-QTLs explained the genetic basis of the significant (P

In the face of global water scarcity, a successful transition of rice cultivation from puddled to dry direct-seeded rice (DDSR) is a future need. A genome-wide association study was performed on a complex mapping population for 39 traits: 9 seedling-establishment traits, 14 root and nutrient-uptake traits, 5 plant morphological traits, 4 lodging resistance traits, and 7 yield and yield-contributing traits. A total of 10 significant marker-trait associations (MTAs) were found along with 25 QTLs associated with 25 traits. The percent phenotypic variance explained by SNPs ranged from 8% to 84%. Grain yield was found to be significantly and positively correlated with seedling-establishment traits, root morphological traits, nutrient uptake-related traits, and grain yield-contributing traits. The genomic colocation of different root morphological traits, nutrient uptake-related traits, and grain-yield-contributing traits further supports the role of root morphological traits in improving nutrient uptake and grain yield under DDSR. The QTLs/candidate genes underlying the significant MTAs were identified. The identified promising progenies carrying these QTLs may serve as potential donors to be exploited in genomics-assisted breeding programs for improving grain yield and adaptability under DDSR.

Napiergrass (Cenchrus purpureus Schumach) is a tropical forage grass and a promising lignocellulosic biofuel feedstock due to its high biomass yield, persistence, and nutritive value. However, its utilization for breeding has lagged behind other crops due to limited genetic and genomic resources. In this study, next-generation sequencing was first used to survey the genome of napiergrass. Napiergrass sequences displayed high synteny to the pearl millet genome and showed expansions in the pearl millet genome along with genomic rearrangements between the two genomes. An average repeat content of 27.5% was observed in napiergrass including 5,339 simple sequence repeats (SSRs). Furthermore, to construct a high-density genetic map of napiergrass, genotyping-by-sequencing (GBS) was employed in a bi-parental population of 185 F1 hybrids. A total of 512 million high quality reads were generated and 287,093 SNPs were called by using multiple de-novo and reference-based SNP callers. Single dose SNPs were used to construct the first high-density linkage map that resulted in 1,913 SNPs mapped to 14 linkage groups, spanning a length of 1,410 cM and a density of 1 marker per 0.73 cM. This map can be used for many further genetic and genomic studies in napiergrass and related species.

Genomic selection (GS) by selecting lines prior to field phenotyping using genotyping data has the potential to enhance the rate of genetic gains. Genotype × environment (G × E) interaction inclusion in GS models can improve prediction accuracy hence aid in selection of lines across target environments. Phenotypic data on 320 chickpea breeding lines for eight traits for three seasons at two locations were recorded. These lines were genotyped using DArTseq (1.6 K SNPs) and Genotyping-by-Sequencing (GBS; 89 K SNPs). Thirteen models were fitted including main effects of environment and lines, markers, and/or naïve and informed interactions to estimate prediction accuracies. Three cross-validation schemes mimicking real scenarios that breeders might encounter in the fields were considered to assess prediction accuracy of the models (CV2: incomplete field trials or sparse testing; CV1: newly developed lines; and CV0: untested environments). Maximum prediction accuracies for different traits and different models were observed with CV2. DArTseq performed better than GBS and the combined genotyping set (DArTseq and GBS) regardless of the cross validation scheme with most of the main effect marker and interaction models. Improvement of GS models and application of various genotyping platforms are key factors for obtaining accurate and precise prediction accuracies, leading to more precise selection of candidates.

Aspergillus flavus is an opportunistic pathogen of plants such as maize and peanut under conducive conditions such as drought stress resulting in significant aflatoxin production. Drought-associated oxidative stress also exacerbates aflatoxin production by A. flavus. The objectives of this study were to use proteomics to provide insights into the pathogen responses to H2O2-derived oxidative stress, and to identify potential biomarkers and targets for host resistance breeding. Three isolates, AF13, NRRL3357, and K54A with high, moderate, and no aflatoxin production, were cultured in medium supplemented with varying levels of H2O2, and examined using an iTRAQ (Isobaric Tags for Relative and Absolute Quantification) approach. Overall, 1,173 proteins were identified and 220 were differentially expressed (DEPs). Observed DEPs encompassed metabolic pathways including antioxidants, carbohydrates, pathogenicity, and secondary metabolism. Increased lytic enzyme, secondary metabolite, and developmental pathway expression in AF13 was correlated with oxidative stress tolerance, likely assisting in plant infection and microbial competition. Elevated expression of energy and cellular component production in NRRL3357 and K54A implies a focus on oxidative damage remediation. These trends explain isolate-to-isolate variation in oxidative stress tolerance and provide insights into mechanisms relevant to host plant interactions under drought stress allowing for more targeted efforts in host resistance research.

Salinity is a major constraint for intrinsically salt sensitive grain legume chickpea. Chickpea exhibits large genetic variation amongst cultivars, which show better yields in saline conditions but still need to be improved further for sustainable crop production. Based on previous multi-location physiological screening, JG 11 (salt tolerant) and ICCV 2 (salt sensitive) were subjected to salt stress to evaluate their physiological and transcriptional responses. A total of ~480 million RNA-Seq reads were sequenced from root tissues which resulted in identification of 3,053 differentially expressed genes (DEGs) in response to salt stress. Reproductive stage shows high number of DEGs suggesting major transcriptional reorganization in response to salt to enable tolerance. Importantly, cationic peroxidase, Aspartic ase, NRT1/PTR, phosphatidylinositol phosphate kinase, DREB1E and ERF genes were significantly up-regulated in tolerant genotype. In addition, we identified a suite of important genes involved in cell wall modification and root morphogenesis such as dirigent proteins, expansin and casparian strip membrane proteins that could potentially confer salt tolerance. Further, phytohormonal cross-talk between ERF and PIN-FORMED genes which modulate the root growth was observed. The gene set enrichment analysis and functional annotation of these genes suggests they may be utilised as potential candidates for improving chickpea salt tolerance.

Aflatoxin contamination, caused by fungal pathogen Aspergillus flavus, is a major quality and health problem delimiting the trade and consumption of groundnut (Arachis hypogaea L.) worldwide. RNA-seq approach was deployed to understand the host-pathogen interaction by identifying differentially expressed genes (DEGs) for resistance to in-vitro seed colonization (IVSC) at four critical stages after inoculation in J 11 (resistant) and JL 24 (susceptible) genotypes of groundnut. About 1,344.04 million sequencing reads have been generated from sixteen libraries representing four stages in control and infected conditions. About 64% and 67% of quality filtered reads (1,148.09 million) were mapped onto A (A. duranensis) and B (A. ipaёnsis) subgenomes of groundnut respectively. About 101 million unaligned reads each from J 11 and JL 24 were used to map onto A. flavus genome. As a result, 4,445 DEGs including defense-related genes like senescence-associated proteins, resveratrol synthase, 9s-lipoxygenase, pathogenesis-related proteins were identified. In A. flavus, about 578 DEGs coding for growth and development of fungus, aflatoxin biosynthesis, binding, transport, and signaling were identified in compatible interaction. Besides identifying candidate genes for IVSC resistance in groundnut, the study identified the genes involved in host-pathogen cross-talks and markers that can be used in breeding resistant varieties.

Soil salinity results in reduced productivity in chickpea. However, breeding for salinity tolerance is challenging because of limited knowledge of the key traits affecting performance under elevated salt and the difficulty of high-throughput phenotyping for large, diverse germplasm collections. This study utilised image-based phenotyping to study genetic variation in chickpea for salinity tolerance in 245 diverse accessions. On average salinity reduced plant growth rate (obtained from tracking leaf expansion through time) by 20%, plant height by 15% and shoot biomass by 28%. Additionally, salinity induced pod abortion and inhibited pod filling, which consequently reduced seed number and seed yield by 16% and 32%, respectively. Importantly, moderate to strong correlation was observed for different traits measured between glasshouse and two field sites indicating that the glasshouse assays are relevant to field performance. Using image-based phenotyping, we measured plant growth rate under salinity and subsequently elucidated the role of shoot ion independent stress (resulting from hydraulic resistance and osmotic stress) in chickpea. Broad genetic variation for salinity tolerance was observed in the diversity panel with seed number being the major determinant for salinity tolerance measured as yield. This study proposes seed number as a selection trait in breeding salt tolerant chickpea cultivars.

Delta-1-pyrroline-5-carboxylate synthase gene1 (P5CS1) is the key gene involved in the biosynthesis of proline and is significantly induced by drought stress. The exploration of genetic variation in HvP5CS1 may facilitate a better understanding of the mechanism of drought adaptation in barley. In the current study, 41 polymorphisms including 16 single nucleotide polymorphisms (SNPs) and 25 insertions/deletions (indels) were detected in HvP5CS1 among 287 barley (Hordeum vulgare L.) accessions collected worldwide, with 13 distinct haplotypes identified in the barley collection. Five polymorphisms in HvP5CS1 were significantly (P P HvP5CS1_H1 and HvP5CS1_H4, which contained desired alleles of the two variations mentioned above, were significantly (P

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.

Plant height is one of the most important architecture traits in crop plants. In peanut, the genetic basis of plant height remains ambiguous. In this context, we genotyped a recombinant inbred line (RIL) population with 140 individuals developed from a cross between two peanut varieties varying in plant height, Zhonghua 10 and ICG 12625. Genotyping data was generated for 1,175 SSR and 42 transposon polymorphic markers and a high-density genetic linkage map was constructed with 1,219 mapped loci covering total map length of 2,038.75 cM i.e., accounted for nearly 80% of the peanut genome. Quantitative trait locus (QTL) analysis using genotyping and phenotyping data for three environments identified 8 negative-effect QTLs and 10 positive-effect QTLs for plant height. Among these QTLs, 8 QTLs had a large contribution to plant height that explained ≥10% phenotypic variation. Two major-effect consensus QTLs namely cqPHA4a and cqPHA4b were identified with stable performance across three environments. Further, the allelic recombination of detected QTLs proved the existence of the phenomenon of transgressive segregation for plant height in the RIL population. Therefore, this study not only successfully reported a high-density genetic linkage map of peanut and identified genomic region controlling plant height but also opens opportunities for further gene discovery and molecular breeding for plant height in peanut.

In order to understand the impact of breeding on genetic diversity and gain insights into temporal trends in diversity in chickpea, a set of 100 chickpea varieties released in 14 countries between 1948 and 2012 were re-sequenced. For analysis, the re-sequencing data for 29 varieties available from an earlier study was also included. Copy number variations and presence absence variations identified in the present study have potential to drive phenotypic variations for trait improvement. Re-sequencing of a large number of varieties has provided opportunities to inspect the genetic and genomic changes reflecting the history of breeding, which we consider as breeding signatures and the selected loci may provide targets for crop improvement. Our study also reports enhanced diversity in both desi and kabuli varieties as a result of recent chickpea breeding efforts. The current study will aid the explicit efforts to breed for local adaptation in the context of anticipated climate changes.

Vascular wilt caused by Fusarium oxysporum f. sp. ciceris (Foc) is a serious disease of chickpea (Cicer arietinum L.) accounting for approximately 10–15% annual crop loss. The fungus invades the plant via roots, colonizes the xylem vessels and prevents the upward translocation of water and nutrients. Infection is initiated by conidia that invade the host tissue often by penetration of intact epidermal cells. Here, we report the characterization of the transcriptome of Foc sequenced using Illumina Hiseq technology during its conidial germination at different time points. Genome-wide expression profiling revealed that genes linked to fungal development are transcribed in successive ways. Analysis showed that Foc have large sets of germination-related genes and families of genes encoding secreted effectors, cell wall/pectin-degrading enzymes, metabolism related enzymes, transporters and peptidases. We found that metabolism related enzymes are up-regulated at early time point whereas most transporters and secondary metabolites important for tissue colonization and pathogenicity are up-regulated later as evident from the qRT-PCR. The study demonstrated that early conidial germination in Foc is accompanied by rapid shifts in gene expression that prepare the fungus for germ tube outgrowth, host cell invasion and pathogenesis. This work lays the foundation for facilitating further research towards understanding this host-pathogen interaction.

Sterility mosaic disease (SMD) is one of the serious production constraints that may lead to complete yield loss in pigeonpea. Three mapping populations including two recombinant inbred lines and one F2, were used for phenotyping for SMD resistance at two locations in three different years. Genotyping-by-sequencing approach was used for simultaneous identification and genotyping of SNPs on above mentioned populations. In total, 212,464, 89,699 and 64,798 SNPs were identified in ICPL 20096 × ICPL 332 (PRIL_B), ICPL 20097 × ICP 8863 (PRIL_C) and ICP 8863 × ICPL 87119 (F2) respectively. By using high-quality SNPs, genetic maps were developed for PRIL_B (1,101 SNPs; 921.21 cM), PRIL_C (484 SNPs; 798.25 cM) and F2 (996 SNPs; 1,597.30 cM) populations. The average inter marker distance on these maps varied from 0.84 cM to 1.65 cM, which was lowest in all genetic mapping studies in pigeonpea. Composite interval mapping based QTL analysis identified a total of 10 QTLs including three major QTLs across the three populations. The phenotypic variance of the identified QTLs ranged from 3.6 to 34.3%. One candidate genomic region identified on CcLG11 seems to be promising QTL for molecular breeding in developing superior lines with enhanced resistance to SMD.

Contamination of crops with aflatoxin is a serious global threat to food safety. Aflatoxin production by Aspergillus flavus is exacerbated by drought stress in the field and by oxidative stress in vitro. We examined transcriptomes of three toxigenic and three atoxigenic isolates of A. flavus in aflatoxin conducive and non-conducive media with varying levels of H2O2 to investigate the relationship of secondary metabolite production, carbon source, and oxidative stress. We found that toxigenic and atoxigenic isolates employ distinct mechanisms to remediate oxidative damage, and that carbon source affected the isolates’ expression profiles. Iron metabolism, monooxygenases, and secondary metabolism appeared to participate in isolate oxidative responses. The results suggest that aflatoxin and aflatrem biosynthesis may remediate oxidative stress by consuming excess oxygen and that kojic acid production may limit iron-mediated, non-enzymatic generation of reactive oxygen species. Together, secondary metabolite production may enhance A. flavus stress tolerance, and may be reduced by enhancing host plant tissue antioxidant capacity though genetic improvement by breeding selection.

A combination of two approaches, namely QTL analysis and gene enrichment analysis were used to identify candidate genes in the “QTL-hotspot” region for drought tolerance present on the Ca4 pseudomolecule in chickpea. In the first approach, a high-density bin map was developed using 53,223 single nucleotide polymorphisms (SNPs) identified in the recombinant inbred line (RIL) population of ICC 4958 (drought tolerant) and ICC 1882 (drought sensitive) cross. QTL analysis using recombination bins as markers along with the phenotyping data for 17 drought tolerance related traits obtained over 1–5 seasons and 1–5 locations split the “QTL-hotspot” region into two subregions namely “QTL-hotspot_a” (15 genes) and “QTL-hotspot_b” (11 genes). In the second approach, gene enrichment analysis using significant marker trait associations based on SNPs from the Ca4 pseudomolecule with the above mentioned phenotyping data and the candidate genes from the refined “QTL-hotspot” region showed enrichment for 23 genes. Twelve genes were found common in both approaches. Functional validation using quantitative real-time PCR (qRT-PCR) indicated four promising candidate genes having functional implications on the effect of “QTL-hotspot” for drought tolerance in chickpea.

Drought and salinity are the major factors that limit chickpea production worldwide. We performed whole transcriptome analyses of chickpea genotypes to investigate the molecular basis of drought and salinity stress response/adaptation. Phenotypic analyses confirmed the contrasting responses of the chickpea genotypes to drought or salinity stress. RNA-seq of the roots of drought and salinity related genotypes was carried out under control and stress conditions at vegetative and/or reproductive stages. Comparative analysis of the transcriptomes revealed divergent gene expression in the chickpea genotypes at different developmental stages. We identified a total of 4954 and 5545 genes exclusively regulated in drought-tolerant and salinity-tolerant genotypes, respectively. A significant fraction (~47%) of the transcription factor encoding genes showed differential expression under stress. The key enzymes involved in metabolic pathways, such as carbohydrate metabolism, photosynthesis, lipid metabolism, generation of precursor metabolites/energy, protein modification, redox homeostasis and cell wall component biogenesis, were affected by drought and/or salinity stresses. Interestingly, transcript isoforms showed expression specificity across the chickpea genotypes and/or developmental stages as illustrated by the AP2-EREBP family members. Our findings provide insights into the transcriptome dynamics and components of regulatory network associated with drought and salinity stress responses in chickpea.

Adzuki bean (Vigna angularis var. angularis) is a dietary legume crop in East Asia. The presumed progenitor (Vigna angularis var. nipponensis) is widely found in East Asia, suggesting speciation and domestication in these temperate climate regions. Here, we report a draft genome sequence of adzuki bean. The genome assembly covers 75% of the estimated genome and was mapped to 11 pseudo-chromosomes. Gene prediction revealed 26,857 high confidence protein-coding genes evidenced by RNAseq of different tissues. Comparative gene expression analysis with V. radiata showed that the tissue specificity of orthologous genes was highly conserved. Additional re-sequencing of wild adzuki bean, V. angularis var. nipponensis and V. nepalensis, was performed to analyze the variations between cultivated and wild adzuki bean. The determined divergence time of adzuki bean and the wild species predated archaeology-based domestication time. The present genome assembly will accelerate the genomics-assisted breeding of adzuki bean.