Analysis of stress related sequences in plant genomes
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Date
2013-09-16
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University of Agricultural Sciences, Bengaluru
Abstract
Understanding the principles of abiotic and biotic stress response
mechanisms and application of knowledge derived from integrated
experimental and bioinformatics approaches are gaining importance in
agriculture. The study employed an integrated biocuration and genomic
data mining approach to characterize the dataset of transcription factors
and consensus binding sites from literature mining and stress responsive
genes from expression studies. Study used an in-house developed STIF
algorithm for predicting the transcription factor binding sites in stress
responsive genes. In addition to the extensive content present in the first
version, STIFDB2 had now been updated with 15 stress signals, 31
transcription factors and 5984 stress-responsive genes from three
species (Arabidopsis thaliana, Oryza sativa L. ssp. japonica and Oryza
sativa L. ssp. indica) and also contain orthologs from other agricultural
important crop plants. STIFDB2 database is available at the URL
http://caps.ncbs.res.in/stifdb2. STIFDB2 also reports the stressresponsive
genes data analyzed using enrichment-based meta-analysis
framework consisting of Gene and Plant Ontology, biological pathway
and functional domain annotations in Arabidopsis thaliana. Study found
several ontologies, shared and unique ones, pathways, domains and
phenotypic characters associated with stress responsive genes. In the
protein-protein interaction network mediated by stress responsive genes,
study found the 26S proteasome subunits as a highly clustered module
using molecular complex detection algorithm and, Enrichment analysis
indicates that several biological processes including ‘flower development’
are associated with the network. Study performed homology modelling
and docking studies of corresponding protein products of the stress
responsive genes to gain better insights into their structure and function.
Results from these studies can be used to develop better varieties of crop
plants.
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Keywords
genes, planting, transcription, proteins, transcription factors, communication technology, enzymes, acidity, genomes, biological phenomena