Das, D , Nahlé, Z , Zhang, M. Q. (June 2006) Adaptively inferring human transcriptional subnetworks. Mol Syst Biol, 2. pp. 2006-2029. ISSN 1744-4292 (Electronic)
Abstract
Although the human genome has been sequenced, progress in understanding gene regulation in humans has been particularly slow. Many computational approaches developed for lower eukaryotes to identify cis-regulatory elements and their associated target genes often do not generalize to mammals, largely due to the degenerate and interactive nature of such elements. Motivated by the switch-like behavior of transcriptional responses, we present a systematic approach that allows adaptive determination of active transcriptional subnetworks (cis-motif combinations, the direct target genes and physiological processes regulated by the corresponding transcription factors) from microarray data in mammals, with accuracy similar to that achieved in lower eukaryotes. Our analysis uncovered several new subnetworks active in human liver and in cell-cycle regulation, with similar functional characteristics as the known ones. We present biochemical evidence for our predictions, and show that the recently discovered G2/M-specific E2F pathway is wider than previously thought; in particular, E2F directly activates certain mitotic genes involved in hepatocellular carcinomas. Additionally, we demonstrate that this method can predict subnetworks in a condition-specific manner, as well as regulatory crosstalk across multiple tissues. Our approach allows systematic understanding of how phenotypic complexity is regulated at the transcription level in mammals and offers marked advantage in systems where little or no prior knowledge of transcriptional regulation is available.
Item Type: | Paper |
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Subjects: | bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > transcription bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > cis-regulatory elements bioinformatics > computational biology organism description > animal > mammal > primates > hominids > human bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification > protein types > transcription factor |
CSHL Authors: | |
Communities: | CSHL labs > Zhang lab |
Depositing User: | CSHL Librarian |
Date: | 6 June 2006 |
Date Deposited: | 20 Dec 2011 16:32 |
Last Modified: | 13 Apr 2018 14:34 |
PMCID: | PMC1681499 |
Related URLs: | |
URI: | https://repository.cshl.edu/id/eprint/22778 |
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