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

ScRNA-seq reveals dark- and light-induced differentially expressed gene atlases of seedling leaves in Arachis hypogaea L

Although the regulatory mechanisms of dark and light-induced plant morphogenesis have been broadly investigated, the biological process in peanuts has not been systematically explored on single-cell resolution. Herein, 10 cell clusters were characterized using scRNA-seq-identified marker genes, based on 13 409 and 11 296 single cells from 1-week-old peanut seedling leaves grown under dark and light conditions. 6104 genes and 50 transcription factors (TFs) displayed significant expression patterns in distinct cell clusters, which provided gene resources for profiling dark/light-induced candidate genes. Further pseudo-time trajectory and cell cycle evidence supported that dark repressed the cell division and perturbed normal cell cycle, especially the PORA abundances correlated with 11 TFs highly enriched in mesophyll to restrict the chlorophyllide synthesis. Additionally, light repressed the epidermis cell developmental trajectory extending by inhibiting the growth hormone pathway, and 21 TFs probably contributed to the different genes transcriptional dynamic. Eventually, peanut AHL17 was identified from the profile of differentially expressed TFs, which encoded protein located in the nucleus promoted leaf epidermal cell enlargement when ectopically overexpressed in Arabidopsis through the regulatory phytohormone pathway. Overall, our study presents the different gene atlases in peanut etiolated and green seedlings, providing novel biological insights to elucidate light-induced leaf cell development at the single-cell level.

Celebrating Professor Rajeev K. Varshney's transformative research odyssey from genomics to the field on his induction as Fellow of the Royal Society

Professor Rajeev K. Varshney's transformative impact on crop genomics, genetics, and agriculture is the result of his passion, dedication, and unyielding commitment to harnessing the potential of genomics to address the most pressing challenges faced by the global agricultural community. Starting from a small town in India and reaching the global stage, Professor Varshney's academic and professional trajectory has inspired many scientists active in research today. His ground-breaking work, especially his effort to list orphan tropical crops to genomic resource-rich entities, has been transformative. Beyond his scientific achievements, Professor Varshney is recognized by his colleagues as an exemplary mentor, fostering the growth of future researchers, building institutional capacity, and strengthening scientific capability. His focus on translational genomics and strengthening seed system in developing countries for the improvement of agriculture has made a tangible impact on farmers' lives. His skills have been best utilized in roles at leading research centres where he has applied his expertise to deliver a new vision for crop improvement. These efforts have now been recognized by the Royal Society with the award of the Fellowship (FRS). As we mark this significant milestone in his career, we not only celebrate Professor Varshney's accomplishments but also his wider contributions that continue to transform the agricultural landscape.

Identification of candidate genes associated with peanut pod length by combined analysis of QTL-seq and RNA-seq

Pod length (PL) is one of the major traits determining pod size and yield of peanut. Discovering the quantitative trait loci (QTL) and identifying candidate genes associated with PL are essential for breeding high-yield peanut. In this study, quantitative trait loci sequencing (QTL-seq) was performed using the F2 population constructed by a short-pod variety Tifrunner (Tif) and a long-pod line Lps, and a 0.77 Mb genomic region on chromosome 07 was identified as the candidate region for PL. Then, the candidate region was narrowed to a 265.93 kb region by traditional QTL approach. RNA-seq analysis showed that there were four differentially expressed genes (DEGs) in the candidate region, among which Arahy.PF2L6F (AhCDC48) and Arahy.P4LK2T (AhTAA1) were speculated to be PL-related candidate genes. These results were informative for the elucidation of the underlying regulatory mechanism in peanut pod length and would facilitate further identification of valuable target genes.

Genome-wide identification and characterization of NAC transcription factor family members in Trifolium pratense and expression analysis under lead stress

BACKGROUND

The NAC TF family is widely involved in plant responses to various types of stress. Red clover (Trifolium pratense) is a high-quality legume, and the study of NAC genes in red clover has not been comprehensive. The aim of this study was to analyze the NAC gene family of red clover at the whole-genome level and explore its potential role in the Pb stress response.

RESULTS

In this study, 72 TpNAC genes were identified from red clover; collinearity analysis showed that there were 5 pairs of large fragment replicators of TpNAC genes, and red clover was found to be closely related to Medicago truncatula. Interestingly, the TpNAC genes have more homologs in Arabidopsis thaliana than in soybean (Glycine max). There are many elements in the TpNAC genes promoters that respond to stress. Gene expression analysis showed that all the TpNAC genes responded to Pb stress. qRT-PCR showed that the expression levels of TpNAC29 and TpNAC42 were significantly decreased after Pb stress. Protein interaction network analysis showed that 21 TpNACs and 23 other genes participated in the interaction. In addition, the TpNAC proteins had three possible 3D structures, and the secondary structure of these proteins were mainly of other types. These results indicated that most TpNAC members were involved in the regulation of Pb stress in red clover.

CONCLUSION

These results suggest that most TpNAC members are involved in the regulation of Pb stress in red clover. TpNAC members play an important role in the response of red clover to Pb stress.

Genome-Wide Mapping of Quantitative Trait Loci for Yield-Attributing Traits of Peanut

Peanuts (Arachis hypogaea L.) are important high-protein and oil-containing legume crops adapted to arid to semi-arid regions. The yield and quality of peanuts are complex quantitative traits that show high environmental influence. In this study, a recombinant inbred line population (RIL) (Valencia-C × JUG-03) was developed and phenotyped for nine traits under two environments. A genetic map was constructed using 1323 SNP markers spanning a map distance of 2003.13 cM. Quantitative trait loci (QTL) analysis using this genetic map and phenotyping data identified seventeen QTLs for nine traits. Intriguingly, a total of four QTLs, two each for 100-seed weight (HSW) and shelling percentage (SP), showed major and consistent effects, explaining 10.98% to 14.65% phenotypic variation. The major QTLs for HSW and SP harbored genes associated with seed and pod development such as the seed maturation protein-encoding gene, serine-threonine phosphatase gene, TIR-NBS-LRR gene, protein kinase superfamily gene, bHLH transcription factor-encoding gene, isopentyl transferase gene, ethylene-responsive transcription factor-encoding gene and cytochrome P450 superfamily gene. Additionally, the identification of 76 major epistatic QTLs, with PVE ranging from 11.63% to 72.61%, highlighted their significant role in determining the yield- and quality-related traits. The significant G × E interaction revealed the existence of the major role of the environment in determining the phenotype of yield-attributing traits. Notably, the seed maturation protein-coding gene in the vicinity of major QTLs for HSW can be further investigated to develop a diagnostic marker for HSW in peanut breeding. This study provides understanding of the genetic factor governing peanut traits and valuable insights for future breeding efforts aimed at improving yield and quality.

Genetic mapping identified major main-effect and three co-localized quantitative trait loci controlling high iron and zinc content in groundnut

Malnutrition is a major challenge globally, and groundnut is a highly nutritious self-pollinated legume crop blessed with ample genomic resources, including the routine deployment of genomic-assisted breeding. This study aimed to identify genomic regions and candidate genes for high iron (Fe) and zinc (Zn) content, utilizing a biparental mapping population (ICGV 00440 × ICGV 06040;). Genetic mapping and quantitative trait locus (QTL) analysis (474 mapped single-nucleotide polymorphism loci; 1536.33 cM) using 2 seasons of phenotypic data together with genotypic data identified 5 major main-effect QTLs for Fe content. These QTLs exhibited log-of-odds (LOD) scores ranging from 6.5 to 7.4, explaining phenotypic variation (PVE) ranging from 22% (qFe-Ah01) to 30.0% (qFe-Ah14). Likewise, four major main effect QTLs were identified for Zn content, with LOD score ranging from 4.4 to 6.8 and PVE ranging from 21.8% (qZn-Ah01) to 32.8% (qZn-Ah08). Interestingly, three co-localized major and main effect QTLs (qFe-Ah01, qZn-Ah03, and qFe-Ah11) were identified for both Fe and Zn contents. These genomic regions harbored key candidate genes, including zinc/iron permease transporter, bZIP transcription factor, and vacuolar iron transporter which likely play pivotal roles in the accumulation of Fe and Zn contents in seeds. The findings of this study hold potential for fine mapping and diagnostic marker development for high Fe and Zn contents in groundnut.

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.

Genetic mapping identified three hotspot genomic regions and candidate genes controlling heat tolerance-related traits in groundnut

Groundnut productivity and quality have been impeded by rising temperatures in semi-arid environments. Hence, understanding the effects and molecular mechanisms of heat stress tolerance will aid in tackling yield losses. In this context, a recombinant inbred line (RIL) population was developed and phenotyped for eight seasons at three locations for agronomic, phenological, and physiological traits under heat stress. A genetic map was constructed using genotyping-by-sequencing with 478 single-nucleotide polymorphism (SNP) loci spanning a map distance of 1,961.39 cM. Quantitative trait locus (QTL) analysis using phenotypic and genotypic data identified 45 major main-effect QTLs for 21 traits. Intriguingly, three QTL clusters (Cluster-1-Ah03, Cluster-2-Ah12, and Cluster-3-Ah20) harbor more than half of the major QTLs (30/45, 66.6%) for various heat tolerant traits, explaining 10.4%-38.6%, 10.6%-44.6%, and 10.1%-49.5% of phenotypic variance, respectively. Furthermore, important candidate genes encoding DHHC-type zinc finger family protein (arahy.J0Y6Y5), peptide transporter 1 (arahy.8ZMT0C), pentatricopeptide repeat-containing protein (arahy.4A4JE9), Ulp1 protease family (arahy.X568GS), Kelch repeat F-box protein (arahy.I7X4PC), FRIGIDA-like protein (arahy.0C3V8Z), and post-illumination chlorophyll fluorescence increase (arahy.92ZGJC) were the underlying three QTL clusters. The putative functions of these genes suggested their involvement in seed development, regulating plant architecture, yield, genesis and growth of plants, flowering time regulation, and photosynthesis. Our results could provide a platform for further fine mapping, gene discovery, and developing markers for genomics-assisted breeding to develop heat-tolerant groundnut varieties.

Genetic mapping identifies genomic regions and candidate genes for seed weight and shelling percentage in groundnut

Seed size is not only a yield-related trait but also an important measure to determine the commercial value of groundnut in the international market. For instance, small size is preferred in oil production, whereas large-sized seeds are preferred in confectioneries. In order to identify the genomic regions associated with 100-seed weight (HSW) and shelling percentage (SHP), the recombinant inbred line (RIL) population (Chico × ICGV 02251) of 352 individuals was phenotyped for three seasons and genotyped with an Axiom_Arachis array containing 58K SNPs. A genetic map with 4199 SNP loci was constructed, spanning a map distance of 2708.36 cM. QTL analysis identified six QTLs for SHP, with three consistent QTLs on chromosomes A05, A08, and B10. Similarly, for HSW, seven QTLs located on chromosomes A01, A02, A04, A10, B05, B06, and B09 were identified. BIG SEED locus and spermidine synthase candidate genes associated with seed weight were identified in the QTL region on chromosome B09. Laccase, fibre protein, lipid transfer protein, senescence-associated protein, and disease-resistant NBS-LRR proteins were identified in the QTL regions associated with shelling percentage. The associated markers for major-effect QTLs for both traits successfully distinguished between the small- and large-seeded RILs. QTLs identified for HSW and SHP can be used for developing potential selectable markers to improve the cultivars with desired seed size and shelling percentage to meet the demands of confectionery industries.

Genome-wide identification of germin-like proteins in peanut (Arachis hypogea L.) and expression analysis under different abiotic stresses

Peanut is an important food and feed crop, providing oil and protein nutrients. Germins and germin-like proteins (GLPs) are ubiquitously present in plants playing numerous roles in defense, growth and development, and different signaling pathways. However, the GLP members have not been comprehensively studied in peanut at the genome-wide scale. We carried out a genome-wide identification of the GLP genes in peanut genome. GLP members were identified comprehensively, and gene structure, genomic positions, motifs/domains distribution patterns, and phylogenetic history were studied in detail. Promoter Cis-elements, gene duplication, collinearity, miRNAs, protein-protein interactions, and expression were determined. A total of 84 GLPs (AhGLPs ) were found in the genome of cultivated peanut. These GLP genes were clustered into six groups. Segmental duplication events played a key role in the evolution of AhGLPs, and purifying selection pressure was underlying the duplication process. Most AhGLPs possessed a well-maintained gene structure and motif organization within the same group. The promoter regions of AhGLPs contained several key cis-elements responsive to 'phytohormones', 'growth and development', defense, and 'light induction'. Seven microRNAs (miRNAs) from six families were found targeting 25 AhGLPs. Gene Ontology (GO) enrichment analysis showed that AhGLPs are highly enriched in nutrient reservoir activity, aleurone grain, external encapsulating structure, multicellular organismal reproductive process, and response to acid chemicals, indicating their important biological roles. AhGLP14, AhGLP38, AhGLP54, and AhGLP76 were expressed in most tissues, while AhGLP26, AhGLP29, and AhGLP62 showed abundant expression in the pericarp. AhGLP7, AhGLP20, and AhGLP21, etc., showed specifically high expression in embryo, while AhGLP12, AhGLP18, AhGLP40, AhGLP78, and AhGLP82 were highly expressed under different hormones, water, and temperature stress. The qRT-PCR results were in accordance with the transcriptome expression data. In short, these findings provided a foundation for future functional investigations on the AhGLPs for peanut breeding programs.

Multi-Omics Profiling Identifies Candidate Genes Controlling Seed Size in Peanut

Seed size is the major yield component and a key target trait that is selected during peanut breeding. However, the mechanisms that regulate peanut seed size are unknown. Two peanut mutants with bigger seed size were isolated in this study by ⁶⁰Co treatment of a common peanut landrace, Huayu 22, and were designated as the "big seed" mutant lines (hybs). The length and weight of the seed in hybs were about 118% and 170% of those in wild-type (WT), respectively. We adopted a multi-omics approach to identify the genomic locus underlying the hybs mutants. We performed whole genome sequencing (WGS) of WT and hybs mutants and identified thousands of large-effect variants (SNPs and indels) that occurred in about four hundred genes in hybs mutants. Seeds from both WT and hybs lines were sampled 20 days after flowering (DAF) and were used for RNA-Seq analysis; the results revealed about one thousand highly differentially expressed genes (DEGs) in hybs compared to WT. Using a method that combined large-effect variants with DEGs, we identified 45 potential candidate genes that shared gene product mutations and expression level changes in hybs compared to WT. Among the genes, two candidate genes encoding cytochrome P450 superfamily protein and NAC transcription factors may be associated with the increased seed size in hybs. The present findings provide new information on the identification and functional research into candidate genes responsible for the seed size phenotype in peanut.

An integrated transcriptome mapping the regulatory network of coding and long non-coding RNAs provides a genomics resource in chickpea

Large-scale transcriptome analysis can provide a systems-level understanding of biological processes. To accelerate functional genomic studies in chickpea, we perform a comprehensive transcriptome analysis to generate full-length transcriptome and expression atlas of protein-coding genes (PCGs) and long non-coding RNAs (lncRNAs) from 32 different tissues/organs via deep sequencing. The high-depth RNA-seq dataset reveal expression dynamics and tissue-specificity along with associated biological functions of PCGs and lncRNAs during development. The coexpression network analysis reveal modules associated with a particular tissue or a set of related tissues. The components of transcriptional regulatory networks (TRNs), including transcription factors, their cognate cis-regulatory motifs, and target PCGs/lncRNAs that determine developmental programs of different tissues/organs, are identified. Several candidate tissue-specific and abiotic stress-responsive transcripts associated with quantitative trait loci that determine important agronomic traits are also identified. These results provide an important resource to advance functional/translational genomic and genetic studies during chickpea development and environmental conditions.

A full-length transcriptome and expression atlas of protein-coding genes and long non-coding RNAs is generated in chickpea. Components of transcriptional regulatory networks and candidate tissue-specific transcripts associated with quantitative trait loci are identified.

Genome-Wide Characterization of Ascorbate Peroxidase Gene Family in Peanut (Arachis hypogea L.) Revealed Their Crucial Role in Growth and Multiple Stress Tolerance

Ascorbate peroxidase (APX), an important antioxidant enzyme, plays a significant role in ROS scavenging by catalyzing the decrease of hydrogen peroxide under various environmental stresses. Nevertheless, information about the APX gene family and their evolutionary and functional attributes in peanut (Arachis hypogea L.) was not reported. Therefore, a comprehensive genome-wide study was performed to discover the APX genes in cultivated peanut genome. This study identified 166 AhAPX genes in the peanut genome, classified into 11 main groups. The gene duplication analysis showed that AhAPX genes had experienced segmental duplications and purifying selection pressure. Gene structure and motif investigation indicated that most of the AhAPX genes exhibited a comparatively well-preserved exon-intron pattern and motif configuration contained by the identical group. We discovered five phytohormones-, six abiotic stress-, and five growth and development-related cis-elements in the promoter regions of AhAPX. Fourteen putative ah-miRNAs from 12 families were identified, targeting 33 AhAPX genes. Furthermore, we identified 3,257 transcription factors from 38 families (including AP2, ARF, B3, bHLH, bZIP, ERF, MYB, NAC, WRKY, etc.) in 162 AhAPX genes. Gene ontology and KEGG enrichment analysis confirm the role of AhAPX genes in oxidoreductase activity, catalytic activity, cell junction, cellular response to stimulus and detoxification, biosynthesis of metabolites, and phenylpropanoid metabolism. Based on transcriptome datasets, some genes such as AhAPX4/7/17/77/82/86/130/133 and AhAPX160 showed significantly higher expression in diverse tissues/organs, i.e., flower, leaf, stem, roots, peg, testa, and cotyledon. Likewise, only a few genes, including AhAPX4/17/19/55/59/82/101/102/137 and AhAPX140, were significantly upregulated under abiotic (drought and cold), and phytohormones (ethylene, abscisic acid, paclobutrazol, brassinolide, and salicylic acid) treatments. qRT-PCR-based expression profiling presented the parallel expression trends as generated from transcriptome datasets. Our discoveries gave new visions into the evolution of APX genes and provided a base for further functional examinations of the AhAPX genes in peanut breeding programs.

CRISPR/Cas9 Based Site-Specific Modification of FAD2 cis-Regulatory Motifs in Peanut (Arachis hypogaea L)

Peanut (Arachis hypogaea L.) seed is a rich source of edible oil, comprised primarily of monounsaturated oleic acid and polyunsaturated linoleic acid, accounting for 80% of its fatty acid repertoire. The conversion of oleic acid to linoleic acid, catalyzed by Fatty Acid Desaturase 2 (FAD2) enzymes, is an important regulatory point linked to improved abiotic stress responses while the ratio of these components is a significant determinant of commercial oil quality. Specifically, oleic acid has better oxidative stability leading to longer shelf life and better taste qualities while also providing nutritional based health benefits. Naturally occurring FAD2 gene knockouts that lead to high oleic acid levels improve oil quality at the potential expense of plant health though. We undertook a CRISPR/Cas9 based site-specific genome modification approach designed to downregulate the expression of two homeologous FAD2 genes in seed while maintaining regulation in other plant tissues. Two cis-regulatory elements the RY repeat motif and 2S seed protein motif in the 5′UTR and associated intron of FAD2 genes are potentially important for regulating seed-specific gene expression. Using hairy root and stable germ line transformation, differential editing efficiencies were observed at both CREs when targeted by single gRNAs using two different gRNA scaffolds. The editing efficiencies also differed when two gRNAs were expressed simultaneously. Additionally, stably transformed seed exhibited an increase in oleic acid levels relative to wild type. Taken together, the results demonstrate the immense potential of CRISPR/Cas9 based approaches to achieve high frequency targeted edits in regulatory sequences for the generation of novel transcriptional alleles, which may lead to fine tuning of gene expression and functional genomic studies in peanut.

Transcriptome analysis of pod mutant reveals plant hormones are important regulators in controlling pod size in peanut (Arachis hypogaea L.)

Pod size is an important yield-influencing trait in peanuts. It is affected by plant hormones and identifying the genes related to these hormones may contribute to pod-related trait improvements in peanut breeding programs. However, there is limited information on the molecular mechanisms of plant hormones that regulate pod size in peanuts. We identified a mutant with an extremely small pod (spm) from Yuanza 9102 (WT) by ⁶⁰Co γ-radiation mutagenesis. The length and width of the natural mature pod in spm were only 71.34% and 73.36% of those in WT, respectively. We performed comparative analyses for morphological characteristics, anatomy, physiology, and global transcriptome between spm and WT pods. Samples were collected at 10, 20, and 30 days after peg elongation into the soil, representing stages S1, S2, and S3, respectively. The differences in pod size between WT and spm were seen at stage S1 and became even more striking at stages S2 and S3. The cell sizes of the pods were significantly smaller in spm than in WT at stages S1, S2, and S3. These results suggested that reduced cell size may be one of the important contributors for the small pod in spm. The contents of indole-3-acetic acid (IAA), gibberellin (GA), and brassinosteroid (BR) were also significantly lower in spm pods than those in WT pods at all three stages. RNA-Seq analyses showed that 1,373, 8,053, and 3,358 differently expressed genes (DEGs) were identified at stages S1, S2, and S3, respectively. Functional analyses revealed that a set of DEGs was related to plant hormone biosynthesis, plant hormone signal transduction pathway, and cell wall biosynthesis and metabolism. Furthermore, several hub genes associated with plant hormone biosynthesis and signal transduction pathways were identified through weighted gene co-expression network analysis. Our results revealed that IAA, GA, and BR may be important regulators in controlling pod size by regulating cell size in peanuts. This study provides helpful information for the understanding of the complex mechanisms of plant hormones in controlling pod size by regulating the cell size in peanuts and will facilitate the improvement of peanut breeding.

Transcriptome Analysis Reveals Key Pathways and Candidate Genes Controlling Seed Development and Size in Ricebean (Vigna umbellata)

Ricebean (Vigna umbellata) is a lesser known pulse with well-recognized potential. Recently, it has emerged as a legume with endowed nutritional potential because of high concentration of quality protein and other vital nutrients in its seeds. However, the genes and pathways involved in regulating seed development and size are not understood in this crop. In our study, we analyzed the transcriptome of two genotypes with contrasting grain size (IC426787: large seeded and IC552985: small seeded) at two different time points, namely, 5 and 10 days post-anthesis (DPA). The bold seeded genotype across the time points (B5_B10) revealed 6,928 differentially expressed genes (DEGs), whereas the small seeded genotype across the time point (S5_S10) contributed to 14,544 DEGs. We have also identified several candidate genes for seed development-related traits like seed size and 100-seed weight. On the basis of similarity search and domain analysis, some candidate genes (PHO1, cytokinin dehydrogenase, A-type cytokinin, and ARR response negative regulator) related to 100-seed weight and seed size showed downregulation in the small seeded genotype. The MapMan and KEGG analysis confirmed that auxin and cytokinin pathways varied in both the contrasting genotypes and can therefore be the regulators of the seed size and other seed development-related traits in ricebeans. A total of 51 genes encoding SCF TIR1/AFB , Aux/IAA, ARFs, E3 ubiquitin transferase enzyme, and 26S proteasome showing distinct expression dynamics in bold and small genotypes were also identified. We have also validated randomly selected SSR markers in eight accessions of the Vigna species (V. umbellata: 6; Vigna radiata: 1; and Vigna mungo: 1). Cross-species transferability pattern of ricebean-derived SSR markers was higher in V. radiata (73.08%) than V. mungo (50%). To the best of our knowledge, this is the first transcriptomic study conducted in this crop to understand the molecular basis of any trait. It would provide us a comprehensive understanding of the complex transcriptome dynamics during the seed development and gene regulatory mechanism of the seed size determination in ricebeans.

Systems biology for crop improvement

In recent years, generation of large-scale data from genome, transcriptome, proteome, metabolome, epigenome, and others, has become routine in several plant species. Most of these datasets in different crop species, however, were studied independently and as a result, full insight could not be gained on the molecular basis of complex traits and biological networks. A systems biology approach involving integration of multiple omics data, modeling, and prediction of the cellular functions is required to understand the flow of biological information that underlies complex traits. In this context, systems biology with multiomics data integration is crucial and allows a holistic understanding of the dynamic system with the different levels of biological organization interacting with external environment for a phenotypic expression. Here, we present recent progress made in the area of various omics studies-integrative and systems biology approaches with a special focus on application to crop improvement. We have also discussed the challenges and opportunities in multiomics data integration, modeling, and understanding of the biology of complex traits underpinning yield and stress tolerance in major cereals and legumes.

Designing Future Crops: Genomics-Assisted Breeding Comes of Age

Over the past decade, genomics-assisted breeding (GAB) has been instrumental in harnessing the potential of modern genome resources and characterizing and exploiting allelic variation for germplasm enhancement and cultivar development. Sustaining GAB in the future (GAB 2.0) will rely upon a suite of new approaches that fast-track targeted manipulation of allelic variation for creating novel diversity and facilitate their rapid and efficient incorporation in crop improvement programs. Genomic breeding strategies that optimize crop genomes with accumulation of beneficial alleles and purging of deleterious alleles will be indispensable for designing future crops. In coming decades, GAB 2.0 is expected to play a crucial role in breeding more climate-smart crop cultivars with higher nutritional value in a cost-effective and timely manner.

Genomics and breeding innovations for enhancing genetic gain for climate resilience and nutrition traits

KEY MESSAGE

Integrating genomics technologies and breeding methods to tweak core parameters of the breeder's equation could accelerate delivery of climate-resilient and nutrient rich crops for future food security. Accelerating genetic gain in crop improvement programs with respect to climate resilience and nutrition traits, and the realization of the improved gain in farmers' fields require integration of several approaches. This article focuses on innovative approaches to address core components of the breeder's equation. A prerequisite to enhancing genetic variance (σ2g) is the identification or creation of favorable alleles/haplotypes and their deployment for improving key traits. Novel alleles for new and existing target traits need to be accessed and added to the breeding population while maintaining genetic diversity. Selection intensity (i) in the breeding program can be improved by testing a larger population size, enabled by the statistical designs with minimal replications and high-throughput phenotyping. Selection priorities and criteria to select appropriate portion of the population too assume an important role. The most important component of breeder's equation is heritability (h2). Heritability estimates depend on several factors including the size and the type of population and the statistical methods. The present article starts with a brief discussion on the potential ways to enhance σ2g in the population. We highlight statistical methods and experimental designs that could improve trait heritability estimation. We also offer a perspective on reducing the breeding cycle time (t), which could be achieved through the selection of appropriate parents, optimizing the breeding scheme, rapid fixation of target alleles, and combining speed breeding with breeding programs to optimize trials for release. Finally, we summarize knowledge from multiple disciplines for enhancing genetic gains for climate resilience and nutritional traits.

Comprehensive analysis and identification of drought-responsive candidate NAC genes in three semi-arid tropics (SAT) legume crops

Background

Chickpea, pigeonpea, and groundnut are the primary legume crops of semi-arid tropics (SAT) and their global productivity is severely affected by drought stress. The plant-specific NAC (NAM - no apical meristem, ATAF - Arabidopsis transcription activation factor, and CUC - cup-shaped cotyledon) transcription factor family is known to be involved in majority of abiotic stresses, especially in the drought stress tolerance mechanism. Despite the knowledge available regarding NAC function, not much information is available on NAC genes in SAT legume crops.

Results

In this study, genome-wide NAC proteins – 72, 96, and 166 have been identified from the genomes of chickpea, pigeonpea, and groundnut, respectively, and later grouped into 10 clusters in chickpea and pigeonpea, while 12 clusters in groundnut. Phylogeny with well-known stress-responsive NACs in Arabidopsis thaliana, Oryza sativa (rice), Medicago truncatula, and Glycine max (soybean) enabled prediction of putative stress-responsive NACs in chickpea (22), pigeonpea (31), and groundnut (33). Transcriptome data revealed putative stress-responsive NACs at various developmental stages that showed differential expression patterns in the different tissues studied. Quantitative real-time PCR (qRT-PCR) was performed to validate the expression patterns of selected stress-responsive, Ca_NAC (Cicer arietinum - 14), Cc_NAC (Cajanus cajan - 15), and Ah_NAC (Arachis hypogaea - 14) genes using drought-stressed and well-watered root tissues from two contrasting drought-responsive genotypes of each of the three legumes. Based on expression analysis, Ca_06899, Ca_18090, Ca_22941, Ca_04337, Ca_04069, Ca_04233, Ca_12660, Ca_16379, Ca_16946, and Ca_21186; Cc_26125, Cc_43030, Cc_43785, Cc_43786, Cc_22429, and Cc_22430; Ah_ann1.G1V3KR.2, Ah_ann1.MI72XM.2, Ah_ann1.V0X4SV.1, Ah_ann1.FU1JML.2, and Ah_ann1.8AKD3R.1 were identified as potential drought stress-responsive candidate genes.

Conclusion

As NAC genes are known to play role in several physiological and biological activities, a more comprehensive study on genome-wide identification and expression analyses of the NAC proteins have been carried out in chickpea, pigeonpea and groundnut. We have identified a total of 21 potential drought-responsive NAC genes in these legumes. These genes displayed correlation between gene expression, transcriptional regulation, and better tolerance against drought. The identified candidate genes, after validation, may serve as a useful resource for molecular breeding for drought tolerance in the SAT legume crops.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07602-5.

Understanding Omics Driven Plant Improvement and de novo Crop Domestication: Some Examples

In the current era, one of biggest challenges is to shorten the breeding cycle for rapid generation of a new crop variety having high yield capacity, disease resistance, high nutrient content, etc. Advances in the "-omics" technology have revolutionized the discovery of genes and bio-molecules with remarkable precision, resulting in significant development of plant-focused metabolic databases and resources. Metabolomics has been widely used in several model plants and crop species to examine metabolic drift and changes in metabolic composition during various developmental stages and in response to stimuli. Over the last few decades, these efforts have resulted in a significantly improved understanding of the metabolic pathways of plants through identification of several unknown intermediates. This has assisted in developing several new metabolically engineered important crops with desirable agronomic traits, and has facilitated the de novo domestication of new crops for sustainable agriculture and food security. In this review, we discuss how "omics" technologies, particularly metabolomics, has enhanced our understanding of important traits and allowed speedy domestication of novel crop plants.

Comprehensive Transcriptome Analyses Reveal Candidate Genes for Variation in Seed Size/Weight During Peanut (Arachis hypogaea L.) Domestication

Seed size/weight, a key domestication trait, is also an important selection target during peanut breeding. However, the mechanisms that regulate peanut seed development are unknown. We re-sequenced 12 RNA samples from developing seeds of two cultivated peanut accessions (Lines 8106 and 8107) and wild Arachis monticola at 15, 30, 45, and 60 days past flowering (DPF). Transcriptome analyses showed that ∼36,000 gene loci were expressed in each of the 12 RNA samples, with nearly half exhibiting moderate (2 ≤ FPKM < 10) expression levels. Of these genes, 12.2% (4,523) were specifically expressed during seed development, mainly at 15 DPF. Also, ∼12,000 genes showed significant differential expression at 30, 45, and/or 60 DPF within each of the three peanut accessions, accounting for 31.8-34.1% of the total expressed genes. Using a method that combined comprehensive transcriptome analysis and previously mapped QTLs, we identified several candidate genes that encode transcription factor TGA7, topless-related protein 2, IAA-amino acid hydrolase ILR1-like 5, and putative pentatricopeptide repeat-containing (PPR) protein. Based on sequence variations identified in these genes, SNP markers were developed and used to genotype both 30 peanut landraces and a genetic segregated population, implying that EVM0025654 encoding a PPR protein may be associated with the increased seed size/weight of the cultivated accessions in comparison with the allotetraploid wild peanut. Our results provide additional knowledge for the identification and functional research into candidate genes responsible for the seed size/weight phenotype in peanut.

Improved Genetic Map Identified Major QTLs for Drought Tolerance- and Iron Deficiency Tolerance-Related Traits in Groundnut

A deep understanding of the genetic control of drought tolerance and iron deficiency tolerance is essential to hasten the process of developing improved varieties with higher tolerance through genomics-assisted breeding. In this context, an improved genetic map with 1205 loci was developed spanning 2598.3 cM with an average 2.2 cM distance between loci in the recombinant inbred line (TAG 24 × ICGV 86031) population using high-density 58K single nucleotide polymorphism (SNP) “Axiom_Arachis” array. Quantitative trait locus (QTL) analysis was performed using extensive phenotyping data generated for 20 drought tolerance- and two iron deficiency tolerance-related traits from eight seasons (2004–2015) at two locations in India, one in Niger, and one in Senegal. The genome-wide QTL discovery analysis identified 19 major main-effect QTLs with 10.0–33.9% phenotypic variation explained (PVE) for drought tolerance- and iron deficiency tolerance- related traits. Major main-effect QTLs were detected for haulm weight (20.1% PVE), SCMR (soil plant analytical development (SPAD) chlorophyll meter reading, 22.4% PVE), and visual chlorosis rate (33.9% PVE). Several important candidate genes encoding glycosyl hydrolases; malate dehydrogenases; microtubule-associated proteins; and transcription factors such as MADS-box, basic helix-loop-helix (bHLH), NAM, ATAF, and CUC (NAC), and myeloblastosis (MYB) were identified underlying these QTL regions. The putative function of these genes indicated their possible involvement in plant growth, development of seed and pod, and photosynthesis under drought or iron deficiency conditions in groundnut. These genomic regions and candidate genes, after validation, may be useful to develop molecular markers for deploying genomics-assisted breeding for enhancing groundnut yield under drought stress and iron-deficient soil conditions.

Transcriptome Analysis Identified Coordinated Control of Key Pathways Regulating Cellular Physiology and Metabolism upon Aspergillus flavus Infection Resulting in Reduced Aflatoxin Production in Groundnut

Aflatoxin-affected groundnut or peanut presents a major global health issue to both commercial and subsistence farming. Therefore, understanding the genetic and molecular mechanisms associated with resistance to aflatoxin production during host–pathogen interactions is crucial for breeding groundnut cultivars with minimal level of aflatoxin contamination. Here, we performed gene expression profiling to better understand the mechanisms involved in reduction and prevention of aflatoxin contamination resulting from Aspergillus flavus infection in groundnut seeds. RNA sequencing (RNA-Seq) of 16 samples from different time points during infection (24 h, 48 h, 72 h and the 7th day after inoculation) in U 4-7-5 (resistant) and JL 24 (susceptible) genotypes yielded 840.5 million raw reads with an average of 52.5 million reads per sample. A total of 1779 unique differentially expressed genes (DEGs) were identified. Furthermore, comprehensive analysis revealed several pathways, such as disease resistance, hormone biosynthetic signaling, flavonoid biosynthesis, reactive oxygen species (ROS) detoxifying, cell wall metabolism and catabolizing and seed germination. We also detected several highly upregulated transcription factors, such as ARF, DBB, MYB, NAC and C2H2 in the resistant genotype in comparison to the susceptible genotype after inoculation. Moreover, RNA-Seq analysis suggested the occurrence of coordinated control of key pathways controlling cellular physiology and metabolism upon A. flavus infection, resulting in reduced aflatoxin production.

Translational genomics for achieving higher genetic gains in groundnut

KEY MESSAGE

Groundnut has entered now in post-genome era enriched with optimum genomic and genetic resources to facilitate faster trait dissection, gene discovery and accelerated genetic improvement for developing climate-smart varieties. Cultivated groundnut or peanut (Arachis hypogaea), an allopolyploid oilseed crop with a large and complex genome, is one of the most nutritious food. This crop is grown in more than 100 countries, and the low productivity has remained the biggest challenge in the semiarid tropics. Recently, the groundnut research community has witnessed fast progress and achieved several key milestones in genomics research including genome sequence assemblies of wild diploid progenitors, wild tetraploid and both the subspecies of cultivated tetraploids, resequencing of diverse germplasm lines, genome-wide transcriptome atlas and cost-effective high and low-density genotyping assays. These genomic resources have enabled high-resolution trait mapping by using germplasm diversity panels and multi-parent genetic populations leading to precise gene discovery and diagnostic marker development. Furthermore, development and deployment of diagnostic markers have facilitated screening early generation populations as well as marker-assisted backcrossing breeding leading to development and commercialization of some molecular breeding products in groundnut. Several new genomics applications/technologies such as genomic selection, speed breeding, mid-density genotyping assay and genome editing are in pipeline. The integration of these new technologies hold great promise for developing climate-smart, high yielding and more nutritious groundnut varieties in the post-genome era.