Journal Article

STIFDB2: An Updated Version of Plant Stress-Responsive TranscrIption Factor DataBase with Additional Stress Signals, Stress-Responsive Transcription Factor Binding Sites and Stress-Responsive Genes in Arabidopsis and Rice

Mahantesha Naika, Khader Shameer, Oommen K. Mathew, Ramanjini Gowda and Ramanathan Sowdhamini

in Plant and Cell Physiology

Published on behalf of Japanese Society of Plant Physiologists

Volume 54, issue 2, pages e8-e8
Published in print February 2013 | ISSN: 0032-0781
Published online January 2013 | e-ISSN: 1471-9053 | DOI:

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  • Biochemistry
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  • Plant Sciences and Forestry


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Understanding the principles of abiotic and biotic stress responses, tolerance and adaptation remains important in plant physiology research to develop better varieties of crop plants. Better understanding of plant stress response mechanisms and application of knowledge derived from integrated experimental and bioinformatics approaches are gaining importance. Earlier, we showed that compiling a database of stress-responsive transcription factors and their corresponding target binding sites in the form of Hidden Markov models at promoter, untranslated and upstream regions of stress-up-regulated genes from expression analysis can help in elucidating various aspects of the stress response in Arabidopsis. In addition to the extensive content in the first version, STIFDB2 is now updated with 15 stress signals, 31 transcription factors and 5,984 stress-responsive genes from three species (Arabidopsis thaliana, Oryza sativa subsp. japonica and Oryza sativa subsp. indica). We have employed an integrated biocuration and genomic data mining approach to characterize the data set of transcription factors and consensus binding sites from literature mining and stress-responsive genes from the Gene Expression Omnibus. STIFDB2 currently has 38,798 associations of stress signals, stress-responsive genes and transcription factor binding sites predicted using the Stress-responsive Transcription Factor (STIF) algorithm, along with various functional annotation data. As a unique plant stress regulatory genomics data platform, STIFDB2 can be utilized for targeted as well as high-throughput experimental and computational studies to unravel principles of the stress regulome in dicots and gramineae. STIFDB2 is available from the URL:

Keywords: Abiotic and biotic stress; Biocuration; Biological data mining; Stress response; Transcriptional regulatory cascade

Journal Article.  5946 words.  Illustrated.

Subjects: Biochemistry ; Molecular and Cell Biology ; Plant Sciences and Forestry

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