Abstract:

Protein kinases regulate virtually all cellular processes, but it remains challenging to determine the functions of all protein kinases, collectively called the “kinome”, in any species. We developed a computational approach called EXPLICIT-Kinase to predict the functions of the Arabidopsis kinome. Because the activities of many kinases can be regulated transcriptionally, their gene expression patterns provide clues to their functions. A universal gene expression predictor for Arabidopsis was constructed to predict the expression of 30,172 non-kinase genes based on the expression of 994 kinases. The model reconstituted highly accurate transcriptomes for diverse Arabidopsis samples. It identified the significant kinases as predictor kinases for predicting the expression of Arabidopsis genes and pathways. Strikingly, these predictor kinases were often regulators of related pathways, as exemplified by those involved in cytokinesis, tissue development, and stress responses. Comparative analyses revealed that portions of these predictor kinases are shared and conserved between Arabidopsis and maize. As an example, we identified a conserved predictor kinase, RAF6, from a stomatal movement module. We verified that RAF6 regulates stomatal closure. It can directly interact with SLAC1, a key anion channel for stomatal closure, and modulate its channel activity. Our approach enables a systematic dissection of the functions of the Arabidopsis kinome.