Integrated omics and machine learning-assisted profiling of cysteine-rich-receptor-like kinases from three peanut spp. revealed their role in multiple stresses - Fatima, Kinza; Sadaqat, Muhammad; Azeem, Farrukh; Rao, Muhammad Junaid; Albekairi, Norah A.; Alshammari, Abdulrahman; Tahir ul Qamar, Muhammad (Frontiers in Genetics, 2023)
Arachis hypogaea (peanut) is a leading oil and protein-providing crop with a major food source in many countries. It is mostly grown in tropical regions and is largely affected by abiotic and biotic stresses. Cystine-Rich-Receptor-like Kinases (CRK) is a family of transmembrane proteins that play important roles in regulating stress-signaling, and defense mechanisms, enabling plants to tolerate stress conditions. However, almost no information is available regarding this gene family in A. hypogaea and its progenitors. This study conducts a pangenome-wide investigation of A. hypogaea and its two progenitors, A. duranensis and A. ipaensis CRK genes (AhCRKs, AdCRKs, and AiCRKs). Gene structure, conserved motif patterns, phylogenetic history, chromosomal distribution, and duplication were studied in detail, showing the intraspecies structural conservation and evolutionary patterns. Promoter cis-elements, protein-protein interactions, GO enrichment, and miRNA targets were also predicted, showing their potential functional conservation. Their expression in salt and drought stresses was also studied comprehensively. The CRKs identified were divided into three groups, phylogenetically. The expansion of this gene family in peanut was caused by both types of duplication: tandem and segmental. Further, positive as well as negative selection pressure directed the duplication process. The peanut CRK genes were also enriched in hormone, light, development, and stress-related elements. MicroRNA (miRNA) also targeted the AhCRK genes, which suggests the regulatory association of miRNAs in the expression of these genes. Transcriptome datasets showed that AhCRKs have varying expression levels in different abiotic stress conditions. Further, the multi-stress responsiveness of the AhCRK genes was evaluated using a machine learning-based method, Random Forest (RF) classifier. The 3D structures of AhCRKs were also predicted. Our study can be utilized in developing a detailed understanding of stress regulatory mechanisms of the CRK gene family in peanut and its further studies to improve the genetic makeup of peanut to thrive better in stress conditions.