The world is facing rapid climate change and a fast-growing global population. It is believed that the world population will be 9.7 billion in 2050. However, recent agriculture production is not enough to feed the current population of 7.9 billion people, which is causing a huge hunger problem. Therefore, feeding the 9.7 billion population in 2050 will be a huge target. Climate change is becoming a huge threat to global agricultural production, and it is expected to become the worst threat to it in the upcoming years. Keeping this in view, it is very important to breed climate-resilient plants. Legumes are considered an important pillar of the agriculture production system and a great source of high-quality protein, minerals, and vitamins. During the last two decades, advancements in OMICs technology revolutionized plant breeding and emerged as a crop-saving tool in wake of the climate change. Various OMICs approaches like Next-Generation sequencing (NGS), Transcriptomics, Proteomics, and Metabolomics have been used in legumes under abiotic stresses. The scientific community successfully utilized these platforms and investigated the Quantitative Trait Loci (QTL), linked markers through genome-wide association studies, and developed KASP markers that can be helpful for the marker-assisted breeding of legumes. Gene-editing techniques have been successfully proven for soybean, cowpea, chickpea, and model legumes such as Medicago truncatula and Lotus japonicus. A number of efforts have been made to perform gene editing in legumes. Moreover, the scientific community did a great job of identifying various genes involved in the metabolic pathways and utilizing the resulted information in the development of climate-resilient legume cultivars at a rapid pace. Keeping in view, this review highlights the contribution of OMICs approaches to abiotic stresses in legumes. We envisage that the presented information will be helpful for the scientific community to develop climate-resilient legume cultivars.

Arbuscular mycorrhizal fungi (AMF) are the basis symbionts in terrestrial ecosystems, profoundly influencing plant development, nutrient acquisition, and resilience to biotic and abiotic stresses. This review synthesizes current systematic understandings of AMF-mediated augmentation of plant growth and disease resistance, with a particular emphasis on their role in sustainable crop production. AMF improves host plant performance through enhanced phosphorus, nitrogen, and water uptake via extensive extraradical hyphal networks. Moreover, AMF colonization modulates phytohormonal signaling pathways, including salicylic acid, jasmonic acid, abscisic acid, and nitric oxide, priming SR and upregulating defense-related gene expression. Increased biosynthesis of secondary metabolites, reinforcement of cell walls, and activation of antioxidant enzyme systems often accompany these responses. AMF also engage in synergistic interactions with rhizosphere microbiota such as Trichoderma, Pseudomonas, and Bacillus, enhancing their collective biocontrol efficacy against a broad spectrum of soil-borne pathogens, including fungi, bacteria, and nematodes. Through modulation of root exudates, glomalin-mediated soil aggregation, and microbiome restructuring, AMF contributes to the establishment of disease-suppressive soils. Genomic and transcriptomic studies have elucidated key components of the common symbiosis-signaling pathway, supporting AMF-host specificity and functional outcomes. AMF is a promising biotechnological tool for integrated pest, disease, and nutrient management. Advancing their application in field settings requires targeted research on strain-host-environment interactions, formulation technologies, and long-term ecosystem impacts, aligning AMF-based strategies with the goals of resilient and sustainable agriculture.

Molecular markers play a crucial role in modern plant breeding by enabling the precise identification of genetic loci associated with important agronomic traits. This article focuses on the advancements in Quantitative Trait Locus (QTL) mapping and Genome-Wide Association Studies (GWAS), which are pivotal in identifying and dissecting complex traits such as stress tolerance, yield improvement, and nutrient efficiency. Through QTL mapping, significant genetic regions linked to desired traits are identified, while GWAS leverages larger populations for higher resolution in genetic association studies. The integration of next-generation sequencing, CRISPR, and transcriptomics technologies has revolutionized the precision and efficiency of these methods, offering deeper insights into gene function and regulation. Single-cell RNA sequencing further enhances our understanding of plant responses at the cellular level, particularly under environmental stressors. Despite the progress, challenges remain in optimizing methodologies, refining training populations, and ensuring the application of these tools in breeding programs. Future directions will focus on improving genetic prediction models, incorporating advanced molecular technologies, and refining functional marker development to address the challenges of sustainable agriculture.

Research endeavors focused on examining genetic diversity play a pivotal role in advancing agricultural practices, as they furnish valuable insights for breeding programs and the preservation of germplasm. Wheat holds significant global importance as a cereal crop, serving as a primary source of sustenance for almost one-third of the global human population. In the current study, a total of 80 bread wheat genotypes were characterized using the start codon targeted (SCoT) marker system. A set of 14 polymorphic primers yielded a cumulative count of 399 bands with an average of 28.05 bands per primer. The range of diversity markers, such as polymorphism information content (0.26–0.59), effective numbers of alleles (1.27–1.59), Shannon’s information index (0.30–0.51), and gene diversity (0.18–0.34), provided evidence of elevated genetic differences within the examined germplasm. According to the findings of the molecular variance analysis, greater genetic variations are found within populations (92%). The model-based structural approach partitioned the 80 bread wheat genotypes into two distinct populations (Population A and B). The diversity indices based on the structures of the populations revealed that population A had greater diversity compared to population B. Both the principal coordinate analysis and the neighbor-joining analysis also differentiated the 80 different bread wheat genotypes based on their respective collection points. The present crop diversity offers great opportunities for enhancing crop quality and increasing tolerance to environmental challenges, both of which will lead to a reduction in the problem of food insecurity.