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Title: Updated rice kinase database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes

Author
item KUMAR NALINI CHANDRA, ANIL - Kyung Hee University
item YOO, YO-HAN - Kyung Hee University
item CAO, PEIJIAN - Zhengzhou University
item SHARMA, RITA - Jawaharlal Nehru University
item SHARMA, MANOJ - Jawaharlal Nehru University
item Dardick, Christopher - Chris
item RONALD, PAMELA - University Of California
item JUNG, KI-HONG - Kyung Hee University

Submitted to: Rice
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/8/2016
Publication Date: 8/19/2016
Citation: Kumar Nalini Chandra, A., Yoo, Y., Cao, P., Sharma, R., Sharma, M., Dardick, C.D., Ronald, P.C., Jung, K. 2016. Updated rice kinase database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes. Rice. DOI: 10.1186/s12284-016-0106-5.

Interpretive Summary: Protein kinases are a large family of enzyme that play critical roles in the biology of cells. Plant genomes contain more than 1,000 genes that encode kinases and very little is known about what most of them do. A major obstacle to understanding the roles individual kinases play in plant biology is that there are sometimes multiple kinases with the same or similar functions. Therefore, if you eliminate one kinase at a time, the resulting plants often show no differences. At the same time, altering more than one kinase at a time is technically difficult. To solve this problem, we previously developed the rice kinase database (RKD) that integrates different types of genomic datasets to anticipate which kinases are likely to have the same or similar biological functions. Here, we report an updated version, RKD 2.0, and used it to estimate kinase functions. Compared with the previous version of RKD, we found that RKD 2.0 enables more effective estimations of kinase function. The public availability of RKD 2.0 provides a valuable tool for the scientific community to predict which kinases are involved in particular crop traits and systematically study them.

Technical Abstract: Protein kinases catalyze the transfer of a phosphate moiety from a phosphate donor to the substrate molecule, thus, playing critical roles in cell signaling and metabolism. Although plant genomes contain more than 1,000 genes that encode kinases, knowledge is limited about the precise roles for the vast majority of these kinases. A major obstacle that hinders the progress in functional validation of kinases is functional redundancy. To elucidate gene functions and evolution of the rice kinase superfamily, we previously developed the rice kinase database (RKD) that integrated omics-scale data within a phylogenetics context. An updated version of RKD, which contains metadata derived from NCBI GEO expression datasets, have been developed. RKD 2.0 is efficient in performing in-depth transcriptomic analyses of kinase-encoding genes in diverse rice tissues and in response to biotic and abiotic stresses, and hormone treatments. Overall, 261 kinases specifically expressed in particular tissues, 130 that are significantly up-regulated in response to biotic stress, 296 in response to abiotic stress, and 260 in response to hormones have been identified. Furthermore, based on this updated database and Pearson correlation coefficient (PCC) analysis, functional dominance for 19 of 26 characterized kinase genes through loss-of-function studies have been estimated. These were selected because they either had paralogous members with PCC values of <0.5 or had no paralog. Compared with the previous version of RKD, RKD 2.0 enables more effective estimations of functional redundancy or dominance because it uses comprehensive expression profiles rather than individual profiles. The integrated analysis of RKD with PCC enables scientific community to select the potential rice kinases for functional study in a single platform.