Integrated data models on Receptor-Like Kinases for novel domain discovery and functional inference in the plant kingdom

Receptor-like kinases (RLKs) are the largest signal transduction component in plants, determining how different plants adapt to their ecological environment, resulting in plant-specific ecological niches. Current research on RLKs has focused mainly on a small number of typical RLK members of a few model plants. There is an urgent need to study the composition, distribution, and evolution of RLKs at the holistic level to accelerate the understanding of how RLK assists in the ecological adaptation of different plants. In this study, we have collected 528 plant genomes and established an RLK data model, resulting in the discovery and characterization of 524,948 RLK members. Each member is subject to systematic topology classification and coherent gene ID assignment. Using this data model, we discovered two novel families (Xiao and Xiang) of RLKs. Evolutionary analysis of the RLK families indicates that RLCK-XVII and RLCK-XII-2 exist exclusively in dicots, suggesting that the diversification in RLKs between monocots and dicots could cause differences in downstream cytoplasmic responses. We also use interaction proteome to help empower the data mining of inferring new functions of RLK from a global perspective, with the ultimate goal of understanding how RLKs shape the adaptation of different plants to the environment/ecology. The RLK data model compiled herein, together with the annotations and analytic tools, form an integrated data foundation involving multi-omics data and is publicly accessible via the web portal (http://metaRLK.biocloud.top).