Abstract
INTRODUCTION: Chickpea (Cicer arietinum L.) is a key legume crop and a major source of dietary protein in developing countries, yet its productivity is constrained by multiple biotic and abiotic stresses. Advances in RNA-seq and whole-genome sequencing enable detailed exploration of stress-responsive gene expression, but existing resources lack integrated, user-friendly tools for multi-omics analysis in chickpea. METHODS: This study analyzed transcriptomic responses to six stress conditions-drought, heat, cold, salinity, Fusarium infection, and developmental stages-using publicly available RNA-seq datasets. We identified differentially expressed genes (DEGs), enriched gene ontology (GO) terms, and protein-protein interaction (PPI) networks. Critically, we developed ChickpeaOmicsR, the first comprehensive R package that automates the integration of transcriptomic, genomic, and proteomic data and standardizes fragmented chickpea gene nomenclature; enables breeders without bioinformatics expertise to perform complex analyses (e.g., DEG identification, PPI visualization, GWAS integration) in minutes; and provides pre-validated datasets and analytical workflows unavailable in existing tools. RESULTS: Each stress triggered distinct molecular pathways. Drought and heat stress affected cell wall organization and defense responses, while cold stress influenced circadian rhythm genes. Fusarium stress involved pathways related to innate immunity and secondary metabolism. Developmental stages showed the highest transcriptome variability among the conditions tested. DISCUSSION: The development of ChickpeaOmicsR addresses critical gaps in chickpea research infrastructure. By providing an integrated and accessible tool that enables complex analyses for breeders without bioinformatics expertise, it accelerates the discovery of stress-resilient genes and the development of improved chickpea varieties.