Identification of plant protein kinases in response to abiotic and biotic stresses using SuperSAGE
Plants are sessile organisms subjected to many environmental adversities. For their survival they must sense and respond to biotic and abiotic stresses efficiently. During this process, protein kinases are essential in the perception of environmental stimuli, triggering signaling cascades. Kinases a...
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| Published in: | Current protein & peptide science Vol. 12; no. 7; p. 643 |
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| Main Authors: | , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
United Arab Emirates
01-11-2011
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| Subjects: | |
| Online Access: | Get more information |
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| Summary: | Plants are sessile organisms subjected to many environmental adversities. For their survival they must sense and respond to biotic and abiotic stresses efficiently. During this process, protein kinases are essential in the perception of environmental stimuli, triggering signaling cascades. Kinases are among the largest and most important gene families for biotechnological purposes, bringing many challenges to the bioinformaticians due to the combination of conserved domains besides diversified regions. Cowpea [Vigna unguiculata (L.) Walp.] is an important legume that is adapted to different agroclimatic conditions, including drought, humidity and a range of temperatures. For this crop, the association of the SuperSAGE method with high-throughput sequencing technology would generate reliable transcriptome profiles with millions of tags counted and statistically analyzed. An approach evaluating biotic and abiotic stresses was carried out generating over 13 million cowpea SuperSAGE tags available from leaves/roots of plants under abiotic (mechanical injury and salinity) or biotic (CABMV, Cowpea aphid born mosaic virus) stresses. The annotation and identification of tags linked by BlastN to previously well described ESTs, allowed the posterior identification of kinases. The annotation efficiency depended on the database used, with the KEGG figuring as a good source for annotated ESTs especially when complemented by an independent Gene Ontology categorization, as well as the Gene Index using selected species. The use of different approaches allowed the identification of 1,350 kinase candidates considering biotic libraries and 2,268 regarding abiotic libraries, based on a combination of both, adequate descriptions and GO terms. Additional searches in kinase specific databases allowed the identification of a relatively low number of additional kinases, uncovering the lack of kinase databases for non-model organisms, especially plants. Concerning the kinase families, a total of 713 potential kinases were classified into 13 families of the CMGC and STE groups. Concerning the differentially expressed kinases, 169 of the 713 potential kinases were identified (p < 0.05), 100 up- and 69 down-regulated when comparing distinct libraries, allowing the generation of a comprehensive panel of the differentially expressed kinases under biotic and abiotic stresses in a non-model plant as cowpea. |
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| ISSN: | 1875-5550 |
| DOI: | 10.2174/1389203711109070643 |