Cicer super-pangenome provides insights into species evolution and agronomic trait loci for crop improvement in chickpea.

Chickpea (Cicer arietinum L.)-an important legume crop cultivated in arid and semiarid regions-has limited genetic diversity. Efforts are being undertaken to broaden its diversity by utilizing its wild relatives, which remain largely unexplored. Here, we present the Cicer super-pangenome based on the de novo genome assemblies of eight annual Cicer wild species. We identified 24,827 gene families, including 14,748 core, 2,958 softcore, 6,212 dispensable and 909 species-specific gene families. The dispensable genome was enriched for genes related to key agronomic traits. Structural variations between cultivated and wild genomes were used to construct a graph-based genome, revealing variations in genes affecting traits such as flowering time, vernalization and disease resistance. These variations will facilitate the transfer of valuable traits from wild Cicer species into elite chickpea varieties through marker-assisted selection or gene-editing. This study offers valuable insights into the genetic diversity and potential avenues for crop improvement in chickpea.

The era of panomics-driven gene discovery in plants.

Panomics is an approach to integrate multiple 'omics' datasets, generated using different individuals or natural variations. Considering their diverse phenotypic spectrum, the phenome is inherently associated with panomics-based science, which is further combined with genomics, transcriptomics, metabolomics, and other omics techniques, either independently or collectively. Panomics has been accelerated through recent technological advancements in the field of genomics that enable the detection of population-wide structural variations (SVs) and hence offer unprecedented insights into the genetic variations contributing to important agronomic traits. The present review provides the recent trends of panomics-driven gene discovery toward various traits related to plant development, stress tolerance, accumulation of specialized metabolites, and domestication/dedomestication. In addition, the success stories are highlighted in the broader context of enhancing crop productivity.

High-throughput diagnostic markers for foliar fungal disease resistance and high oleic acid content in groundnut.

BACKGROUND: Foliar diseases namely late leaf spot (LLS) and leaf rust (LR) reduce yield and deteriorate fodder quality in groundnut. Also the high oleic acid content has emerged as one of the most important traits for industries and consumers due to its increased shelf life and health benefits. RESULTS: Genetic mapping combined with pooled sequencing approaches identified candidate resistance genes (LLSR1 and LLSR2 for LLS and LR1 for LR) for both foliar fungal diseases. The LLS-A02 locus housed LLSR1 gene for LLS resistance, while, LLS-A03 housed LLSR2 and LR1 genes for LLS and LR resistance, respectively. A total of 49 KASPs markers were developed from the genomic regions of important disease resistance genes, such as NBS-LRR, purple acid phosphatase, pentatricopeptide repeat-containing protein, and serine/threonine-protein phosphatase. Among the 49 KASP markers, 41 KASPs were validated successfully on a validation panel of contrasting germplasm and breeding lines. Of the 41 validated KASPs, 39 KASPs were designed for rust and LLS resistance, while two KASPs were developed using fatty acid desaturase (FAD) genes to control high oleic acid levels. These validated KASP markers have been extensively used by various groundnut breeding programs across the world which led to development of thousands of advanced breeding lines and few of them also released for commercial cultivation. CONCLUSION: In this study, high-throughput and cost-effective KASP assays were developed, validated and successfully deployed to improve the resistance against foliar fungal diseases and oleic acid in groundnut. So far deployment of allele-specific and KASP diagnostic markers facilitated development and release of two rust- and LLS-resistant varieties and five high-oleic acid groundnut varieties in India. These validated markers provide opportunities for routine deployment in groundnut breeding programs.

Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea.

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.

Near-gapless genome assemblies of Williams 82 and Lee cultivars for accelerating global soybean research.

Complete, gapless telomere-to-telomere chromosome assemblies are a prerequisite for comprehensively investigating the architecture of complex regions, like centromeres or telomeres and removing uncertainties in the order, spacing, and orientation of genes. Using complementary genomics technologies and assembly algorithms, we developed highly contiguous, nearly gapless, genome assemblies for two economically important soybean [Glycine max (L.) Merr] cultivars (Williams 82 and Lee). The centromeres were distinctly annotated on all the chromosomes of both assemblies. We further found that the canonical telomeric repeats were present at the telomeres of all chromosomes of both Williams 82 and Lee genomes. A total of 10 chromosomes in Williams 82 and eight in Lee were entirely reconstructed in single contigs without any gap. Using the combination of ab initio prediction, protein homology, and transcriptome evidence, we identified 58,287 and 56,725 protein-coding genes in Williams 82 and Lee, respectively. The genome assemblies and annotations will serve as a valuable resource for studying soybean genomics and genetics and accelerating soybean improvement.

Whole-genome sequencing based discovery of candidate genes and diagnostic markers for seed weight in groundnut.

Seed weight in groundnut (Arachis hypogaea L.) has direct impact on yield as well as market price because of preference for bold seeds by consumers and industry, thereby making seed-size improvement as one of the most important objectives of groundnut breeding programs globally. Marker-based early generation selection can accelerate the process of breeding for developing large-seeded varieties. In this context, we deployed the quantitative trait locus-sequencing (QTL-seq) approach on a biparental mapping population (Chico × ICGV 02251) to identify candidate genes and develop markers for seed weight in groundnut. A total of 289.4-389.4 million reads sequencing data were generated from three libraries (ICGV 02251 and two extreme bulks) achieving 93.9-95.1% genome coverage and 8.34-9.29× average read depth. The analysis of sequencing data using QTL-seq pipeline identified five genomic regions (three on chromosome B06 and one each on chromosomes B08 and B09) for seed weight. Detailed analysis of above associated genomic regions detected 182 single-nucleotide polymorphisms (SNPs) in genic and intergenic regions, and 11 of these SNPs were nonsynonymous in the genomic regions of 10 candidate genes including Ulp proteases and BIG SEED locus genes. Kompetitive allele specific polymerase chain reaction (KASP) markers for 14 SNPs were developed, and four of these markers (snpAH0031, snpAH0033, snpAH0037, and snpAH0038) were successfully validated for deployment in breeding for large-seeded groundnut varieties.

Chromosome-length genome assemblies of six legume species provide insights into genome organization, evolution, and agronomic traits for crop improvement.

INTRODUCTION: Legume crops are an important source of protein and oil for human health and in fixing atmospheric N2 for soil enrichment. With an objective to accelerate much-needed genetic analyses and breeding applications, draft genome assemblies were generated in several legume crops; many of them are not high quality because they are mainly based on short reads. However, the superior quality of genome assembly is crucial for a detailed understanding of genomic architecture, genome evolution, and crop improvement. OBJECTIVES: Present study was undertaken with an objective of developing improved chromosome-length genome assemblies in six different legumes followed by their systematic investigation to unravel different aspects of genome organization and legume evolution. METHODS: We employed in situ Hi-C data to improve the existing draft genomes and performed different evolutionary and comparative analyses using improved genome assemblies. RESULTS: We have developed chromosome-length genome assemblies in chickpea, pigeonpea, soybean, subterranean clover, and two wild progenitor species of cultivated groundnut (A. duranensis and A. ipaensis). A comprehensive comparative analysis of these genome assemblies offered improved insights into various evolutionary events that shaped the present-day legume species. We highlighted the expansion of gene families contributing to unique traits such as nodulation in legumes, gravitropism in groundnut, and oil biosynthesis in oilseed legume crops such as groundnut and soybean. As examples, we have demonstrated the utility of improved genome assemblies for enhancing the resolution of "QTL-hotspot" identification for drought tolerance in chickpea and marker-trait associations for agronomic traits in pigeonpea through genome-wide association study. Genomic resources developed in this study are publicly available through an online repository, 'Legumepedia'. CONCLUSION: This study reports chromosome-length genome assemblies of six legume species and demonstrates the utility of these assemblies in crop improvement. The genomic resources developed here will have significant role in accelerating genetic improvement applications of legume crops.

Identification of genes controlling compatible and incompatible reactions of pearl millet (Pennisetum glaucum) against blast (Magnaporthe grisea) pathogen through RNA-Seq.

Blast [Magnaporthe grisea (Herbert) Barr] is an economically important disease in Asian pearl millet production ecologies. The recurrent occurrence of blast in the past one decade has caused enormous strain on grain and forage production. Identification of resistance genes is an important step to develop durable varieties. The present study is the first attempt to use RNA-Seq to investigate the transcript dynamics in a pearl millet inbred ICMB 93333, which had a unique differential reaction to two isolates-Pg 45 (avirulent) and Pg 174 (virulent) of M. grisea. The inbred was inoculated by both isolates and samples taken at six different time intervals for genome-wide RNA-Seq experiment. The transcriptome results revealed the differential expression of more than 2,300 genes. The time-specific comparison showed activation or repression of specific genes in various pathways. Genes and transcriptions factors related to pathogenesis-related proteins, reactive oxygen species generating and its scavenging genes, cell wall defense, primary and secondary metabolic pathways, and signaling pathways were identified by comparing the host-plant compatible and incompatible interactions. The genes identified from this experiment could be useful to understand the host-plant resistance and design novel strategies to manage blast disease in pearl millet.

Genetic variation in CaTIFY4b contributes to drought adaptation in chickpea.

Chickpea production is vulnerable to drought stress. Identifying the genetic components underlying drought adaptation is crucial for enhancing chickpea productivity. Here, we present the fine mapping and characterization of 'QTL-hotspot', a genomic region controlling chickpea growth with positive consequences on crop production under drought. We report that a non-synonymous substitution in the transcription factor CaTIFY4b regulates seed weight and organ size in chickpea. Ectopic expression of CaTIFY4b in Medicago truncatula enhances root growth under water deficit. Our results suggest that allelic variation in 'QTL-hotspot' improves pre-anthesis water use, transpiration efficiency, root architecture and canopy development, enabling high-yield performance under terminal drought conditions. Gene expression analysis indicated that CaTIFY4b may regulate organ size under water deficit by modulating the expression of GRF-INTERACTING FACTOR1 (GIF1), a transcriptional co-activator of Growth-Regulating Factors. Taken together, our study offers new insights into the role of CaTIFY4b and on diverse physiological and molecular mechanisms underpinning chickpea growth and production under specific drought scenarios.

QTL-seq for the identification of candidate genes for days to flowering and leaf shape in pigeonpea.

To identify genomic segments associated with days to flowering (DF) and leaf shape in pigeonpea, QTL-seq approach has been used in the present study. Genome-wide SNP profiling of extreme phenotypic bulks was conducted for both the traits from the segregating population (F2) derived from the cross combination- ICP 5529 × ICP 11605. A total of 126.63 million paired-end (PE) whole-genome resequencing data were generated for five samples, including one parent ICP 5529 (obcordate leaf and late-flowering plant), early and late flowering pools (EF and LF) and obcordate and lanceolate leaf shape pools (OLF and LLS). The QTL-seq identified two significant genomic regions, one on CcLG03 (1.58 Mb region spanned from 19.22 to 20.80 Mb interval) for days to flowering (LF and EF pools) and another on CcLG08 (2.19 Mb region spanned from 6.69 to 8.88 Mb interval) for OLF and LLF pools, respectively. Analysis of genomic regions associated SNPs with days to flowering and leaf shape revealed 5 genic SNPs present in the unique regions. The identified genomic regions for days to flowering were also validated with the genotyping-by-sequencing based classical QTL mapping method. A comparative analysis of the identified seven genes associated with days to flowering on 12 Fabaceae genomes, showed synteny with 9 genomes. A total of 153 genes were identified through the synteny analysis ranging from 13 to 36. This study demonstrates the usefulness of QTL-seq approach in precise identification of candidate gene(s) for days to flowering and leaf shape which can be deployed for pigeonpea improvement.

A chickpea genetic variation map based on the sequencing of 3,366 genomes.

Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources1. So far, few chickpea (Cicer arietinum) germplasm accessions have been characterized at the genome sequence level2. Here we present a detailed map of variation in 3,171 cultivated and 195 wild accessions to provide publicly available resources for chickpea genomics research and breeding. We constructed a chickpea pan-genome to describe genomic diversity across cultivated chickpea and its wild progenitor accessions. A divergence tree using genes present in around 80% of individuals in one species allowed us to estimate the divergence of Cicer over the last 21 million years. Our analysis found chromosomal segments and genes that show signatures of selection during domestication, migration and improvement. The chromosomal locations of deleterious mutations responsible for limited genetic diversity and decreased fitness were identified in elite germplasm. We identified superior haplotypes for improvement-related traits in landraces that can be introgressed into elite breeding lines through haplotype-based breeding, and found targets for purging deleterious alleles through genomics-assisted breeding and/or gene editing. Finally, we propose three crop breeding strategies based on genomic prediction to enhance crop productivity for 16 traits while avoiding the erosion of genetic diversity through optimal contribution selection (OCS)-based pre-breeding. The predicted performance for 100-seed weight, an important yield-related trait, increased by up to 23% and 12% with OCS- and haplotype-based genomic approaches, respectively.

Characterization of heterosis and genomic prediction-based establishment of heterotic patterns for developing better hybrids in pigeonpea.

Whole-genome resequencing (WGRS) of 396 lines, consisting of 104 hybrid parental lines and 292 germplasm lines, were used to study the molecular basis of mid-parent heterosis (MPH) and to identify complementary heterotic patterns in pigeonpea [Cajanus cajan (L.) Millsp.] hybrids. The lines and hybrids were assessed for yield and yield-related traits in multiple environments. Our analysis showed positive MPH values in 78.6% of hybrids, confirming the potential of hybrid breeding in pigeonpea. By using genome-wide prediction and association mapping approaches, we identified 129 single nucleotide polymorphisms and 52 copy number variations with significant heterotic effects and also established a high-yielding heterotic pattern in pigeonpea. In summary, our study highlights the role of WGRS data in the study and use of heterosis in crops where hybrid breeding is expected to boost selection gain in order to ensure global food security.

MutMap Approach Enables Rapid Identification of Candidate Genes and Development of Markers Associated With Early Flowering and Enhanced Seed Size in Chickpea (Cicer arietinum L.).

Globally terminal drought is one of the major constraints to chickpea (Cicer arietinum L.) production. Early flowering genotypes escape terminal drought, and the increase in seed size compensates for yield losses arising from terminal drought. A MutMap population for early flowering and large seed size was developed by crossing the mutant line ICC4958-M3-2828 with wild-type ICC 4958. Based on the phenotyping of MutMap population, extreme bulks for days to flowering and 100-seed weight were sequenced using Hi-Seq2500 at 10X coverage. On aligning 47.41 million filtered reads to the CDC Frontier reference genome, 31.41 million reads were mapped and 332,395 single nucleotide polymorphisms (SNPs) were called. A reference genome assembly for ICC 4958 was developed replacing these SNPs in particular positions of the CDC Frontier genome. SNPs specific for each mutant bulk ranged from 3,993 to 5,771. We report a single unique genomic region on Ca6 (between 9.76 and 12.96 Mb) harboring 31, 22, 17, and 32 SNPs with a peak of SNP index = 1 for low bulk for flowering time, high bulk for flowering time, high bulk for 100-seed weight, and low bulk for 100-seed weight, respectively. Among these, 22 SNPs are present in 20 candidate genes and had a moderate allelic impact on the genes. Two markers, Ca6EF10509893 for early flowering and Ca6HSDW10099486 for 100-seed weight, were developed and validated using the candidate SNPs. Thus, the associated genes, candidate SNPs, and markers developed in this study are useful for breeding chickpea varieties that mitigate yield losses under drought stress.

A diagnostic marker kit for Fusarium wilt and sterility mosaic diseases resistance in pigeonpea.

Fusarium wilt (FW) and sterility mosaic diseases (SMD) are key biotic constraints to pigeonpea production. Occurrence of these two diseases in congenial conditions is reported to cause complete yield loss in susceptible pigeonpea cultivars. Various studies to elucidate genomic architecture of the two traits have revealed significant marker-trait associations for use in breeding programs. However, these DNA markers could not be used effectively in genomics-assisted breeding for developing FW and SMD resistant varieties primarily due to pathogen variability, location or background specificity, lesser phenotypic variance explained by the reported QTL and cost-inefficiency of the genotyping assays. Therefore, in the present study, a novel approach has been used to develop a diagnostic kit for identification of suitable FW and SMD resistant lines. This kit was developed with 10 markers each for FW and SMD resistance. Investigation of the diversity of these loci has shown the role of different alleles in different resistant genotypes. Two genes (C.cajan_03691 and C.cajan_18888) for FW resistance and four genes (C.cajan_07858, C.cajan_20995, C.cajan_21801 and C.cajan_17341) for SMD resistance have been identified. More importantly, we developed a customized and cost-effective Kompetitive allele-specific PCR genotyping assay for the identified genes in order to encourage their downstream applications in pigeonpea breeding programs. The diagnostic marker kit developed here will offer great strength to pigeonpea varietal development program, since the resistance against these two diseases is essentially required for nominating an improved line in varietal release pipeline.

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.

Arachis hypogaea gene expression atlas for fastigiata subspecies of cultivated groundnut to accelerate functional and translational genomics applications.

Spatio-temporal and developmental stage-specific transcriptome analysis plays a crucial role in systems biology-based improvement of any species. In this context, we report here the Arachis hypogaea gene expression atlas (AhGEA) for the world's widest cultivated subsp. fastigiata based on RNA-seq data using 20 diverse tissues across five key developmental stages. Approximately 480 million paired-end filtered reads were generated followed by identification of 81 901 transcripts from an early-maturing, high-yielding, drought-tolerant groundnut variety, ICGV 91114. Further, 57 344 genome-wide transcripts were identified with ≥1 FPKM across different tissues and stages. Our in-depth analysis of the global transcriptome sheds light into complex regulatory networks namely gravitropism and photomorphogenesis, seed development, allergens and oil biosynthesis in groundnut. Importantly, interesting insights into molecular basis of seed development and nodulation have immense potential for translational genomics research. We have also identified a set of stable expressing transcripts across the selected tissues, which could be utilized as internal controls in groundnut functional genomics studies. The AhGEA revealed potential transcripts associated with allergens, which upon appropriate validation could be deployed in the coming years to develop consumer-friendly groundnut varieties. Taken together, the AhGEA touches upon various important and key features of cultivated groundnut and provides a reference for further functional, comparative and translational genomics research for various economically important traits.

Trait associations in the pangenome of pigeon pea (Cajanus cajan).

Pigeon pea (Cajanus cajan) is an important orphan crop mainly grown by smallholder farmers in India and Africa. Here, we present the first pigeon pea pangenome based on 89 accessions mainly from India and the Philippines, showing that there is significant genetic diversity in Philippine individuals that is not present in Indian individuals. Annotation of variable genes suggests that they are associated with self-fertilization and response to disease. We identified 225 SNPs associated with nine agronomically important traits over three locations and two different time points, with SNPs associated with genes for transcription factors and kinases. These results will lead the way to an improved pigeon pea breeding programme.