Expression-based monitoring of transcription factor activity: the TELiS database.

TitleExpression-based monitoring of transcription factor activity: the TELiS database.
Publication TypeJournal Article
Year of Publication2005
AuthorsCole SW, Yan W, Galic Z, Arevalo J, Zack JA
Date Published2005 Mar
KeywordsAlgorithms, Computer Systems, Database Management Systems, Databases, Genetic, Gene Expression Profiling, Information Storage and Retrieval, Oligonucleotide Array Sequence Analysis, Promoter Regions, Genetic, Proteome, Sequence Analysis, Protein, Transcription Factors

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-kappaB 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.

Alternate JournalBioinformatics
PubMed ID15374858
Grant ListAI152737 / AI / NIAID NIH HHS / United States
AI33259 / AI / NIAID NIH HHS / United States
AI49135 / AI / NIAID NIH HHS / United States