|Chen, Johann - UNIV OF CALIFORNIA-DAVIS|
|Richter, Todd - UNIV OF CALIFORNIA-DAVIS|
|Shu, Ouyang - INST FOR GENOMIC RES, MD|
|Ronald, Pamela - UNIV OF CALIFORNIA-DAVIS|
Submitted to: Plant Physiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 17, 2006
Publication Date: February 10, 2007
Citation: Dardick, C.D., Chen, J., Richter, T., Shu, O., Ronald, P. 2007. The rice kinase database (rkd): a phylogenomic database for the rice kinome. Plant Physiology. 143:579-586. Interpretive Summary: The presence of large gene families in plant and animal genomes, and the varying levels of functional redundancy associated with such families create a considerable challenge to the understanding of a function of an individual gene. For example, removing (knock-out) a single gene within a gene family often produce little or no observable change in a plant. Although newer technologies, such as RNAi, provide enhanced capability to knock-down multiple genes simultaneously, this technology requires rational selection of targets, because there are limits on the number of genes that can be simultaneously knocked-down. In the absence of phenotypic information, functional information can be inferred from comparative genomic or systems biological studies that incorporate bioinformatic, genomic, gene expression and proteomic data. These approaches are hampered by current database formats that typically permit displays of only one gene or one field at a time and are, therefore, not amenable to simultaneous comparisons of multiple data sets and/or multi-gene families. The "scattered" nature of genomic data across multiple databases creates additional challenges to data integration. A new field of study that is at least in part resolving these limitations is phylogenomics. Phylogenomics represents a merger between phylogenetics and genomics, and can be used to analyze genomic data in a phylogenetic context. Phylogenetic trees provide a platform to sort and categorize genes into groups based on sequence similarity and are particularly valuable when studying large gene families. Consequently, phylogenetic trees provide a useful foundation for functional predictions based on limited phenotypic data. They also provide a context to identify members within gene families that have unique properties, such as the presence of novel domains, functional motifs or expression patterns. Thus, phylogenomic analyses can provide a more logical basis for rational selection of gene candidates for further detailed functional studies. One family of genes for which redundancy poses enormous challenges is protein kinases. Kinases comprise a highly conserved family of enzymes that control diverse cellular processes and are key components of virtually all biological systems. At the molecular level, kinases control cell signaling networks that allow plants to respond to environmental changes, such as biotic and abiotic stress with developmental, biochemical and physiological adaptations. The high degree of similarity found between even diverse protein kinases and the ability to generate robust phylogenetic groupings makes this gene family an excellent candidate for phylogenomic studies. The rice kinome (complete set of kinases) consists of over 1,400 kinases, and only a few of these have known functions. Previously, we have shown that most kinase families are conserved between monocots and dicots. Consequently, understanding the rice kinome should in large part translate to other plants. Here, we describe the development of the Rice Kinase Database (RKD), a phylogenomic database to facilitate the study of rice kinases.
Technical Abstract: The rice genome contains 1,429 protein kinases, the vast majority of which have unknown functions. We created a phylogenomic database (http://rkd.ucdavis.edu) to facilitate functional analysis of this large gene family. Sequence and genomic data, including gene expression data and protein-protein interaction maps, can be displayed for each selected kinase in the context of a phylogenetic tree allowing for comparative analysis both within and between large kinase subfamilies. Interaction maps are easily accessed through links and displayed using Cytoscape, an open source software platform. Chromosomal distribution of all rice kinases can also be explored via an interactive interface.