Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes.
Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes.
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DOI：
10.1186/s12284-016-0106-5
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发表时间：
2016-12
期刊：
影响因子：
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通讯作者：
Jung KH
中科院分区：
文献类型：
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作者：
Chandran AKN;Yoo YH;Cao P;Sharma R;Sharma M;Dardick C;Ronald PC;Jung KH
蛋白激酶催化磷酸部分从磷酸供体转移到底物分子，因此在细胞信号传导和代谢中起关键作用。虽然植物基因组包含1000多个编码激酶的基因，但对这些激酶中每一种的功能的了解有限。阻碍激酶表征进展的一个主要障碍是功能冗余。为了应对这一挑战，我们先前开发了水稻激酶数据库（RKD），该数据库将组学规模的数据整合到遗传学背景下。水稻激酶数据库（RKD）的更新版本，包含来自NCBI GEO表达数据集的元数据已经开发。RKD 2.0有助于深入转录组学分析不同水稻组织中的激酶编码基因，以及对生物和非生物胁迫和激素处理的响应。我们鉴定了261种在特定组织中特异性表达的激酶，其中130种响应于生物胁迫而显著上调，296种响应于非生物胁迫，260种响应于激素。基于这一更新和皮尔逊相关系数（PCC）分析，我们估计，通过功能丧失研究表征的26个基因中有19个赋予显性功能。选择这些是因为它们具有PCC值<0.5的旁系同源成员或没有旁系同源。与之前版本的RKD相比，RKD 2.0能够更有效地估计功能冗余或优势，因为它使用综合表达谱而不是单个谱。RKD与PCC的集成分析为研究人员选择用于功能分析的水稻激酶建立了单一平台。本文的在线版本（doi：10.1186/s12284-016-0106-5）包含补充材料，可供授权用户使用。
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 1000 genes that encode kinases, knowledge is limited about the function of each of these kinases. A major obstacle that hinders progress towards kinase characterization is functional redundancy. To address this challenge, we previously developed the rice kinase database (RKD) that integrated omics-scale data within a phylogenetics context. An updated version of rice kinase database (RKD) that contains metadata derived from NCBI GEO expression datasets has been developed. RKD 2.0 facilitates in-depth transcriptomic analyses of kinase-encoding genes in diverse rice tissues and in response to biotic and abiotic stresses and hormone treatments. We identified 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. Based on this update and Pearson correlation coefficient (PCC) analysis, we estimated that 19 out of 26 genes characterized through loss-of-function studies confer dominant functions. 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 establishes a single platform for researchers to select rice kinases for functional analyses. The online version of this article (doi:10.1186/s12284-016-0106-5) contains supplementary material, which is available to authorized users.