Rutwik Barmukh

Adzuki bean (Vigna angularis), a globally important legume crop, faces breeding bottlenecks due to limited genomic resources and an insufficient understanding of its genetic basis for key traits, which constrains the efficient utilization of its genetic diversity in breeding programs. To address this, a high-quality genome assembly is developed for the elite cultivar ZH20 and a comprehensive genetic variation map is constructed by resequencing of 546 diverse adzuki bean accessions. Genomic and phenotypic analyses of this diversity panel reveal distinct population structures and identify genomic variations underlying key agronomic traits, including seed coat color, size, shape, and flowering time, linked to adaptation and selection. This analysis pinpointed 251 loci significantly associated with eight key agronomic traits, highlighting promising candidate genes, such as ANKRD50 and NAC73 for seed morphology, ANR1 for flavonoid content, and NPF5.4 for flowering time. Furthermore, comparative genomics provides insights into domestication processes. These datasets are integrated to develop AdzukiBeanAtlas (https://www.cgris.net/AdzukiBeanAtlas), a versatile toolkit to facilitate breeding strategies. These resources provide a valuable foundation for understanding adzuki bean diversity, while AdzukiBeanAtlas serves as a user-friendly, cross-platform tool for molecular marker development, helping to accelerate future breeding programs.

Background
Chickpea (Cicer arietinum L.) is vital for global food security; however, its productivity is limited by genotype-environment interactions and restricted genetic diversity. This study dissected the genetic architecture of six agronomic traits in chickpea using genome-wide association studies (GWAS) to identify stable quantitative trait loci (QTLs).

Results
Phenotypic analysis of 238 chickpea accessions across three growing seasons revealed significant variation in plant height (PH), height to lowest pod (HLP), number of lateral branches (NLB), number of seeds per plant (NSP), thousand-seed weight (TSW), and yield per plant (YP). Broad-sense heritability (h2) ranged from 0.15 (NSP) to 0.88 (TSW). GWAS identified 40 stable QTLs, including major-effect loci on chromosomes 2 (Q_YP_2.1, R² = 0.45) and 4 (Q_TSW_4.1, R² = 0.22). Candidate genes linked to polyamine biosynthesis (LOC101508792) and carbohydrate metabolism (LOC101492955) were implicated.

Conclusions
The study highlights the potential of marker-assisted selection for enhancing chickpea resilience and productivity, particularly in drought-prone regions such as Kazakhstan.

Spatial omics technologies enable unraveling of single-cell heterogeneity and characterizing diverse cell types in plants while preserving their spatial arrangement.Spatial transcriptomics facilitates visualization and quantification of gene expression across the entire transcriptome in plant tissue cryosections, using strategies such as barcoded oligo(dT) arrays and high-throughput sequencing.Spatial proteomics and metabolomics are advancing in resolution, field of view, and cost-efficiency. Achieving single-cell resolution in plants requires overcoming challenges in both experimental techniques and computational analysis.Spatially resolved multiomics profiling and 3D spatial omics hold potential to shape future crop improvement strategies by providing a holistic understanding of molecular and cellular features that control agronomically important traits.
Plant cells communicate information to regulate developmental processes and respond to environmental stresses. This communication spans various ‘omics’ layers within a cell and operates through intricate regulatory networks. The emergence of spatial omics presents a promising approach to thoroughly analyze cells, allowing the combined analysis of diverse modalities either in parallel or on the same tissue section. Here, we provide an overview of recent advancements in spatial omics and delineate scientific discoveries in plant research enabled by these technologies. We delve into experimental and computational challenges and outline strategies to navigate these challenges for advancing breeding efforts. With ongoing insightful discoveries and improved accessibility, spatial omics stands on the brink of playing a crucial role in designing future crops.
Plant cells communicate information to regulate developmental processes and respond to environmental stresses. This communication spans various ‘omics’ layers within a cell and operates through intricate regulatory networks. The emergence of spatial omics presents a promising approach to thoroughly analyze cells, allowing the combined analysis of diverse modalities either in parallel or on the same tissue section. Here, we provide an overview of recent advancements in spatial omics and delineate scientific discoveries in plant research enabled by these technologies. We delve into experimental and computational challenges and outline strategies to navigate these challenges for advancing breeding efforts. With ongoing insightful discoveries and improved accessibility, spatial omics stands on the brink of playing a crucial role in designing future crops.

Chickpea (Cicer arietinum L.) is an important legume crop that has been subjected to intensive breeding, resulting in limited genetic diversity. Australia is the world's second largest producer and the leading exporter of chickpea; the genomic architecture of its cultivars remains largely unexplored. This knowledge gap hinders efforts to enhance their genetic potential for production, protection, and stress adaptation. To address this, we generated high-quality genome assemblies and annotations for 15 leading Australian chickpea cultivars using single-tube long-fragment read technology. The pan-genome analysis identified 34 345 gene families, including 13 986 dispensable families enriched for genes associated with key agronomic traits. Comparative genomic analysis revealed ~2.5 million single-nucleotide polymorphisms, nearly 200 000 insertions/deletions, and over 280 000 structural variations. These variations were found in key flowering time genes, seed weight-related genes, and disease resistance genes, providing insights into the genetic diversity underlying these critical traits. Haplotype analysis of key genes within the 'QTL-hotspot' region revealed the absence of superior haplotypes in Australian cultivars. Validation using Kompetitive allele-specific PCR markers confirmed these findings, highlighting the need to introduce beneficial haplotypes from diverse accessions to enhance drought tolerance in Australian chickpea cultivars. The genomic resources generated in this study provide valuable insights into chickpea genetic diversity and offer potential avenues for crop improvement.

A comprehensive study of the genome and genetics of superior germplasms is fundamental for crop improvement. As a widely adapted protein crop with high yield potential, the improvement in breeding and development of the seeds industry of faba bean have been greatly hindered by its giant genome size and high outcrossing rate.
To fully explore the genomic diversity and genetic basis of important agronomic traits, we first generate a de novo genome assembly and perform annotation of a special short-wing petal faba bean germplasm (VF8137) exhibiting a low outcrossing rate. Comparative genome and pan-genome analyses reveal the genome evolution characteristics and unique pan-genes among the three different faba bean genomes. In addition, the genome diversity of 558 accessions of faba bean germplasm reveals three distinct genetic groups and remarkable genetic differences between the southern and northern germplasms. Genome-wide association analysis identifies several candidate genes associated with adaptation- and yield-related traits. We also identify one candidate gene related to short-wing petals by combining quantitative trait locus mapping and bulked segregant analysis. We further elucidate its function through multiple lines of evidence from functional annotation, sequence variation, expression differences, and protein structure variation.
Our study provides new insights into the genome evolution of Leguminosae and the genomic diversity of faba bean. It offers valuable genomic and genetic resources for breeding and improvement of faba bean.

Bacterial wilt caused by Ralstonia solanacearum is a devastating disease affecting a great many crops including peanut. The pathogen damages plants via secreting type Ш effector proteins (T3Es) into hosts for pathogenicity. Here, we characterized RipAU was among the most toxic effectors as ΔRipAU completely lost its pathogenicity to peanuts. A serine residue of RipAU is the critical site for cell death. The RipAU targeted a subtilisin‐like protease (AhSBT1.7) in peanut and both protein moved into nucleus. Heterotic expression of AhSBT1.7 in transgenic tobacco and Arabidopsis thaliana significantly improved the resistance to R. solanacearum . The enhanced resistance was linked with the upregulating ERF1 defense marker genes and decreasing pectin methylesterase (PME) activity like PME2&4 in cell wall pathways. The RipAU played toxic effect by repressing R‐gene, defense hormone signaling, and AhSBTs metabolic pathways but increasing PMEs expressions. Furthermore, we discovered AhSBT1.7 interacted with AhPME4 and was colocalized at nucleus. The AhPME speeded plants susceptibility to pathogen via mediated cell wall degradation, which inhibited by AhSBT1.7 but upregulated by RipAU. Collectively, RipAU impaired AhSBT1.7 defense for pathogenicity by using PME‐mediated cell wall degradation. This study reveals the mechanism of RipAU pathogenicity and AhSBT1.7 resistance, highlighting peanut immunity to bacterial wilt for future improvement.

This chapter offers a thorough examination of sorghum breeding in Asia, covering its history, distribution, and domestication. It addresses challenges in breeding, particularly cytoplasmic male sterility, and extensively explores the application of omics approaches such as transcriptomics, genomics, proteomics, metabolomics, and bioinformatics. Emphasis is placed on climate resilience, utilizing genomics to develop sorghum varieties adapted to biotic and abiotic stresses. We summarized biotic and abiotic stresses, along with biotechnological interventions to enhance important agronomic traits. This chapter also delves into modifying flowering, plant height, and the brown midrib structure’s implications for animal feed. Throughout, the significance of these tools and techniques in understanding sorghum genetics and aiding breeding programs is highlighted. In conclusion, we discussed addressing current challenges in sorghum breeding in Asia and advocating ongoing research and collaboration to ensure regional food security and sustainable agriculture. Overall, it provides a comprehensive, up-to-date account of sorghum breeding, showcasing genomics and biotechnology’s pivotal role in enhancing resilience and productivity.

Drought is one of the major constraints limiting chickpea productivity. To unravel complex mechanisms regulating drought response in chickpea, we generated transcriptomics, proteomics, and metabolomics datasets from root tissues of four contrasting drought-responsive chickpea genotypes: ICC 4958, JG 11, and JG 11+ (drought-tolerant), and ICC 1882 (drought-sensitive) under control and drought stress conditions. Integration of transcriptomics and proteomics data identified enriched hub proteins encoding isoflavone 4′-O-methyltransferase, UDP-d-glucose/UDP-d-galactose 4-epimerase, and delta-1-pyrroline-5-carboxylate synthetase. These proteins highlighted the involvement of pathways such as antibiotic biosynthesis, galactose metabolism, and isoflavonoid biosynthesis in activating drought stress response mechanisms. Subsequently, the integration of metabolomics data identified six metabolites (fructose, galactose, glucose, myoinositol, galactinol, and raffinose) that showed a significant correlation with galactose metabolism. Integration of root-omics data also revealed some key candidate genes underlying the drought-responsive “QTL-hotspot” region. These results provided key insights into complex molecular mechanisms underlying drought stress response in chickpea.

Core Ideas
• Multi-omics analysis of chickpea roots revealed complex molecular mechanisms underpinning drought stress response.
• Integration of transcriptome and proteome data uncovered hub proteins involved in drought stress response pathways.
• Metabolomic profiling identified six metabolites showing a significant correlation with galactose metabolism.
• Transcriptome-proteome integration revealed prominent differential expression of key genes underlying the “QTL-hotspot” region.

The escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated by rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue because it significantly impacts crop productivity. The widespread threat of metal(loid) toxicity can jeopardize global food security due to contaminated food supplies and pose environmental risks, contributing to soil and water pollution and thus impacting the whole ecosystem. In this context, plants have evolved complex mechanisms to combat metal(loid) stress. Amid the array of innovative approaches, omics, notably transcriptomics, proteomics, and metabolomics, have emerged as transformative tools, shedding light on the genes, proteins, and key metabolites involved in metal(loid) stress responses and tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools like bioinformatics, biological databases, and analytical pipelines support these omics approaches by harnessing diverse information and facilitating the mapping of genotype-to-phenotype relationships under stress conditions. This review explores: (1) the multifaceted strategies that plants use to adapt to metal(loid) toxicity in their environment; (2) the latest findings in metal(loid)-mediated transcriptomics, proteomics, and metabolomics studies across various plant species; (3) the integration of omics data with artificial intelligence and high-throughput phenotyping; (4) the latest bioinformatics databases, tools and pipelines for single and/or multi-omics data integration; (5) the latest insights into stress adaptations and tolerance mechanisms for future outlooks; and (6) the capacity of omics advances for creating sustainable and resilient crop plants that can thrive in metal(loid)-contaminated environments.

Chickpea is the world's fourth largest grown legume crop, which significantly contributes to food security by providing calories and dietary protein globally. However, the increased frequency of drought stress has significantly reduced chickpea production in recent years. Here, we have performed a field experiment with 36 diverse chickpea genotypes to evaluate grain yield, photosynthetic activities and molecular traits related to drought stress. For metabolomics analysis, leaf tissue was collected at three time points representing different pod-filling stages. We identified L-threonic acid, fructose and sugar alcohols involved in chickpea adaptive drought response within the mid-pod-filling stage. A stress susceptibility index for each genotype was calculated to identify tolerance capacity under drought, distributing the 36 genotypes into four categories from best to worst performance. To understand how biochemical mechanisms control different traits for genetic improvement, we performed a differential Jacobian analysis, which unveiled the interplay between various metabolic pathways across three time points, including higher flux towards inositol interconversions, glycolysis for high-performing genotypes, fumarate to malate conversion, and carbon and nitrogen metabolism perturbations. Metabolic GWAS (mGWAS) analysis uncovered gene candidates involved in glycolysis and MEP pathway corroborating with the differential biochemical Jacobian results. Accordingly, this proposed data analysis strategy bridges the gap from pure statistical association to causal biochemical relations by exploiting natural variation. Our study offers new perspectives on the genetic and metabolic understanding of drought tolerance-associated diversity in the chickpea metabolome and led to the identification of metabolic control points that can be also tested in other legume crops.