Cargando…

Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes

BACKGROUND: 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...

Descripción completa

Detalles Bibliográficos
Autores principales: Chandran, Anil Kumar Nalini, Yoo, Yo-Han, Cao, Peijian, Sharma, Rita, Sharma, Manoj, Dardick, Christopher, Ronald, Pamela C, Jung, Ki-Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4991984/
https://www.ncbi.nlm.nih.gov/pubmed/27540739
http://dx.doi.org/10.1186/s12284-016-0106-5
_version_ 1782448930417541120
author Chandran, Anil Kumar Nalini
Yoo, Yo-Han
Cao, Peijian
Sharma, Rita
Sharma, Manoj
Dardick, Christopher
Ronald, Pamela C
Jung, Ki-Hong
author_facet Chandran, Anil Kumar Nalini
Yoo, Yo-Han
Cao, Peijian
Sharma, Rita
Sharma, Manoj
Dardick, Christopher
Ronald, Pamela C
Jung, Ki-Hong
author_sort Chandran, Anil Kumar Nalini
collection PubMed
description BACKGROUND: 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. RESULTS: 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. CONCLUSION: 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12284-016-0106-5) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4991984
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Springer US
record_format MEDLINE/PubMed
spelling pubmed-49919842016-09-07 Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes Chandran, Anil Kumar Nalini Yoo, Yo-Han Cao, Peijian Sharma, Rita Sharma, Manoj Dardick, Christopher Ronald, Pamela C Jung, Ki-Hong Rice (N Y) Original Article BACKGROUND: 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. RESULTS: 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. CONCLUSION: 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12284-016-0106-5) contains supplementary material, which is available to authorized users. Springer US 2016-08-19 /pmc/articles/PMC4991984/ /pubmed/27540739 http://dx.doi.org/10.1186/s12284-016-0106-5 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Chandran, Anil Kumar Nalini
Yoo, Yo-Han
Cao, Peijian
Sharma, Rita
Sharma, Manoj
Dardick, Christopher
Ronald, Pamela C
Jung, Ki-Hong
Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes
title Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes
title_full Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes
title_fullStr Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes
title_full_unstemmed Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes
title_short Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes
title_sort updated rice kinase database rkd 2.0: enabling transcriptome and functional analysis of rice kinase genes
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4991984/
https://www.ncbi.nlm.nih.gov/pubmed/27540739
http://dx.doi.org/10.1186/s12284-016-0106-5
work_keys_str_mv AT chandrananilkumarnalini updatedricekinasedatabaserkd20enablingtranscriptomeandfunctionalanalysisofricekinasegenes
AT yooyohan updatedricekinasedatabaserkd20enablingtranscriptomeandfunctionalanalysisofricekinasegenes
AT caopeijian updatedricekinasedatabaserkd20enablingtranscriptomeandfunctionalanalysisofricekinasegenes
AT sharmarita updatedricekinasedatabaserkd20enablingtranscriptomeandfunctionalanalysisofricekinasegenes
AT sharmamanoj updatedricekinasedatabaserkd20enablingtranscriptomeandfunctionalanalysisofricekinasegenes
AT dardickchristopher updatedricekinasedatabaserkd20enablingtranscriptomeandfunctionalanalysisofricekinasegenes
AT ronaldpamelac updatedricekinasedatabaserkd20enablingtranscriptomeandfunctionalanalysisofricekinasegenes
AT jungkihong updatedricekinasedatabaserkd20enablingtranscriptomeandfunctionalanalysisofricekinasegenes