Expression-based monitoring of transcription factor activity: the TELiS database
Abstract
Motivation: In microarray studies it is often of interest to identify upstream transcription control pathways mediating observed changes in gene expression. The Transcription Element Listening System (TELiS) combines sequence-based analysis of gene regulatory regions with statistical prevalence analyses to identify transcription-factor binding motifs (TFBMs) that are over-represented among the promoters of up- or down-regulated genes. Efficiency is maximized by decomposing the problem into two steps: (1) a priori compilation of prevalence matrices specifying the number of putative binding sites for a variety of transcription factors in promoters from all genes assayed by a given microarray, and (2) real-time statistical analysis of pre-compiled prevalence matrices to identify TFBMs that are over- or under-represented in promoters of differentially expressed genes. The interlocking JAVA applications namely, PromoterScan and PromoterStats carry out these tasks, and together constitute the TELiS database for reverse inference of transcription factor activity. Results: In two validation studies, TELiS accurately detected in vivo activation of NF-κB and the Type I interferon system by HIV-1 infection and pharmacologic activation of the glucocorticoid receptor in peripheral blood mononuclear cells. The population-based statistical inference underlying TELiS out-performed conventional statistical tests in analytic sensitivity, with parametric studies demonstrating accurate identification of transcription factor activity from as few as 20 differentially expressed genes. TELiS thus provides a simple, rapid and sensitive tool for identifying transcription control pathways mediating observed gene expression dynamics. Availability: http://www.telis.ucla.edu Contact: coles@ucla.edu
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TELiS can accurately identify the activation of specific hormone or cytokine signaling pathways based on the resulting pattern of gene induction which occurs selectively in genes bearing TFBMs responsive to transcription factors activated through that pathway.
“This approach can accurately identify the activation of specific hormone or cytokine signaling pathways based on the resulting pattern of gene induction which occurs selectively in genes bearing TFBMs responsive to transcription factors activated through that pathway (23).”
From A Functional Genomic Fingerprint of Chronic Stress in Humans: Blunted Glucocorticoid and Increased NF-κB Signaling (2008) · cites this paper as [23]
The TELiS primary analyses utilized default parameter settings shown to be optimal in previous studies.
“Primary analyses utilized default parameter settings shown to be optimal in previous studies (analysis of −600 bp sequence upstream of transcription start site, with a .90 MatInspector match stringency; 23).”
From A Functional Genomic Fingerprint of Chronic Stress in Humans: Blunted Glucocorticoid and Increased NF-κB Signaling (2008) · cites this paper as [23]
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- Authors
- Cole, S. W., Yan, W., Galic, Z., Arevalo, J., & Zack, J. A.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Cole, Steve W.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2004-09-16
- Volume
- 21
- Issue
- 6
- Pages
- 803-810
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2130675837
- Cited by
- 185
- References
- 0
- Citations by year
- 2026: 3 · 2025: 21 · 2024: 8 · 2023: 7 · 2022: 7 · 2021: 11 · 2020: 10 · 2019: 17 · 2018: 10 · 2017: 6 · 2016: 7 · 2015: 4 · 2014: 11 · 2013: 5 · 2012: 11
- FWCI
- 1.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Allergy and Infectious Diseases (AI 49135, AI152737, R29AI033259, AI-33259, R21AI049135)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- transcription factor activity, transcription factor binding motifs, promoter analysis, gene expression microarrays, gene regulatory regions, NF-κB activation, HIV-1 infection, glucocorticoid receptor, transcriptional regulation
- MeSH terms
- Algorithms, Computer Systems, Database Management Systems, Promoter Regions, Genetic, Transcription Factors, Information Storage and Retrieval, Oligonucleotide Array Sequence Analysis, Sequence Analysis, Protein, Proteome, Gene Expression Profiling, Databases, Genetic
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