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Curr Top Dev Biol. 2012;98:121-45. doi: 10.1016/B978-0-12-386499-4.00005-7.

Computational strategies for the genome-wide identification of cis-regulatory elements and transcriptional targets.

Author information

  • Laboratory of Computational Biology, Center for Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium.

Abstract

Transcription factors (TFs) are key proteins that decode the information in our genome to express a precise and unique set of proteins and RNA molecules in each cell type in our body. These factors play a pivotal role in all biological processes, including the determination of a cell's fate during development and the maintenance of a cell's physiological function. To achieve this, a TF binds to specific DNA sequences in the noncoding part of the genome, recruits chromatin modifiers and cofactors, and directs the transcription initiation rate of its "target genes." Therefore, a key challenge in deciphering a transcriptional switch is to identify the direct target genes of the master regulators that control the switch, the cis-regulatory elements implementing (auto-)regulatory loops, and the target genes of all the TFs in the downstream regulatory network. A better knowledge of a TF's targetome during specification and differentiation of a particular cell type will generate mechanistic insight into its developmental program. Here, I review computational strategies and methods to predict transcriptional targets by genome-wide searches for TF binding sites using position weight matrices, motif clusters, phylogenetic footprinting, chromatin binding and accessibility data, enhancer classification, motif enrichment, and gene expression signatures.

Copyright © 2012 Elsevier Inc. All rights reserved.

PMID:
22305161
[PubMed - indexed for MEDLINE]
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