REFINEMENT: A search framework for the identification of interferon-responsive elements in DNA sequences - a case study with ISRE and GAS

Authors:
Takuma Tsukahara;Sun Kim;Milton W. Taylor
Affiliations:
Department of Biology, Indiana University, Bloomington, IN 47401, USA;School of Informatics, Indiana University, Bloomington, IN 47401, USA and The Center for Genomics and Bioinformatics, Indiana University, Bloomington, IN 47401, USA;Department of Biology, Indiana University, Bloomington, IN 47401, USA
Venue:
Computational Biology and Chemistry
Year:
2006

Citing 4
Cited 0

Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization

Machine Learning - Special issue on applications in molecular biology
An algorithm for finding novel gapped motifs in DNA sequences

RECOMB '98 Proceedings of the second annual international conference on Computational molecular biology
A Statistical Method for Finding Transcription Factor Binding Sites

Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
BioOptimizer: a Bayesian scoring function approach to motif discovery

Bioinformatics

Quantified Score

Hi-index	0.01

Visualization

Abstract

Interferons (IFN) are a family of pleiotropic secreted proteins that play a key role in mediating antiviral and apoptotic responses, and in immune modulation. Interferons induce a large number of genes through activating the janus tyrosine kinase (JAK)-signal transducers and activators of transcription proteins (STAT) pathway, and the binding of transcription factors to upstream regions of the inducible genes (interferon-stimulated gene, ISG) at specific DNA regulatory elements known as interferon-stimulated response element (ISRE) and gamma-activated sequence (GAS). We have previously performed DNA micro-arrays on peripheral blood mononuclear cells (PBMC) treated with interferon-@a in culture and showed that approximately 700 genes are significantly modulated (P@?0.001). In order to search for ISRE and GAS we have developed a framework called regulatory element finding with iteration and effective model refinement (REFINEMENT) using an existing program (HMMER) and a standard discriminating scoring technique. Although REFINEMENT uses existing programs, our framework itself is novel as it effectively discriminates occurrences using an iterative model refinement technique. REFINEMENT has detected either ISRE or GAS sequence in all of the genes shown to be induced at a P-value@?0.001. There were far more functional occurrences in ISRE than in GAS, suggesting that ISRE plays a greater role in response to interferon-@a than GAS sequences. This method can be used to identify such sequences in any set of genes. REFINEMENT is non-commercial and is accessible at http://cancer.informatics.indiana.edu/ttsukaha/miltonlab/refinement/.