Title

STIF: Identification of stress-upregulated transcription factor binding sites in Arabidopsis thaliana

Authors

Ambika Shyam Sundar¹, Susan Mary Varghese², Khader Shameer¹, Nataraja Karaba², Makarla Udayakumar² and Ramanathan Sowdhamini^1,*

Affiliation

¹National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK Campus, Bellary Road, Bangalore 560 065, India; ²Department of Crop Physiology, UAS-GKVK Campus, Bellary Road, Bangalore 560 065, India

Email

mini@ncbs.res.in; * Corresponding author

Article Type

Hypothesis

Date

received May 22, 2008; revised July 12, 2008; accepted July 14, 2008; published July 30, 2008

Abstract

The expressions of proteins in the cell are carefully regulated by transcription factors that interact with their downstream targets in specific signal transduction cascades. Our understanding of the regulation of functional genes responsive to stress signals is still nascent. Plants like Arabidopsis thaliana, are convenient model systems to study fundamental questions related to regulation of the stress transcriptome in response to stress challenges. Microarray results of the Arabidopsis transcriptome indicate that several genes could be upregulated during multiple stresses, such as cold, salinity, drought etc. Experimental biochemical validations have proved the involvement of several transcription factors could be involved in the upregulation of these stress responsive genes. In order to follow the intricate and complicated networks of transcription factors and genes that respond to stress situations in plants, we have developed a computer algorithm that can identify key transcription factor binding sites upstream of a gene of interest. Hidden Markov models of the transcription factor binding sites enable the identification of predicted sites upstream of plant stress genes. The search algorithm, STIF, performs very well, with more than 90% sensitivity, when tested on experimentally validated positions of transcription factor binding sites on a dataset of 60 stress upregulated genes.

Keywords

transcription factor binding site prediction; gene regulation; stress genes; Arabidopsis thaliana; HMM based algorithm

Availability

Supplementary data is available at http://caps.ncbs.res.in/download/stif

Citation

Ambika et al., Bioinformation 2(10): 431-437 (2008)

Edited by

P. Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.