A systematic model to predict transcriptional regulatory mechanisms based on overrepresentation of transcription factor binding profiles.

Abstract:

:An important aspect of understanding a biological pathway is to delineate the transcriptional regulatory mechanisms of the genes involved. Two important tasks are often encountered when studying transcription regulation, i.e., (1) the identification of common transcriptional regulators of a set of coexpressed genes; (2) the identification of genes that are regulated by one or several transcription factors. In this study, a systematic and statistical approach was taken to accomplish these tasks by establishing an integrated model considering all of the promoters and characterized transcription factors (TFs) in the genome. A promoter analysis pipeline (PAP) was developed to implement this approach. PAP was tested using coregulated gene clusters collected from the literature. In most test cases, PAP identified the transcription regulators of the input genes accurately. When compared with chromatin immunoprecipitation experiment data, PAP's predictions are consistent with the experimental observations. When PAP was used to analyze one published expression-profiling data set and two novel coregulated gene sets, PAP was able to generate biologically meaningful hypotheses. Therefore, by taking a systematic approach of considering all promoters and characterized TFs in our model, we were able to make more reliable predictions about the regulation of gene expression in mammalian organisms.

journal_name

Genome Res

journal_title

Genome research

authors

Chang LW,Nagarajan R,Magee JA,Milbrandt J,Stormo GD

doi

10.1101/gr.4303406

subject

Has Abstract

pub_date

2006-03-01 00:00:00

pages

405-13

issue

3

eissn

1088-9051

issn

1549-5469

pii

gr.4303406

journal_volume

16

pub_type

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