Genome-wide characterization of the sunflower kinome: classification, evolutionary analysis and expression patterns under different stresses.

Protein kinases play a significant role in plant responses to biotic and abiotic stresses, as well as in growth and development. While the kinome has been extensively investigated in crops such as , soybean, common bean, and cotton, studies on protein kinases in sunflower remain limited. Our objective is to explore protein kinases in sunflower to bridge the research gap and enhance the understanding of their functions. We identified a total of 2,583 protein kinases from sunflower, which were classified into 22 families and 121 subfamilies. By comparing the subfamily members between sunflower and other species, we found that three subfamilies in sunflower-RLK-Pelle_CrRLK1L-1, RLK-Pelle_SD-2b, and RLK-Pelle_WAK-had undergone significant expansion. We then investigated the chromosomal distribution, molecular weight, isoelectric point, transmembrane domain, signal peptide, and structural and evolutionary diversity of the protein kinases. Through these studies, we have obtained a basic understanding of protein kinases in sunflower. To investigate the role of protein kinases in sunflower's response to biotic and abiotic stresses, we obtained 534 transcriptome datasets from various research groups, covering eight types of abiotic stress and two types of biotic stress. For the first time, we overcame the batch effects in the data and utilized a gene scoring system developed by our lab to perform a comprehensive analysis of multiple transcriptome datasets from different research groups. Ultimately, 73 key protein kinases were identified from numerous candidates, and functional annotation revealed that they are key members of signaling pathways such as ABA, MAPK, and SOS, actively participating in sunflower's response to biotic and abiotic stresses. In summary, through the exploration of protein kinases in sunflower, we have filled the gap in protein kinase research and provided a substantial amount of foundational data. By using the new scoring method to eliminate batch effects between transcriptome datasets, we achieved the first comprehensive analysis of large-scale transcriptome data. This method allows for a more thorough and detailed identification of key protein kinases that are widely regulated under various stress conditions, providing numerous candidate genes for sunflower stress resistance research.