Computational strategies for the genome-wide identification of cis-regulatory elements and transcriptional targets.
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.
Laboratory of Computational Biology, Center for Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium.
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D000818:Animals; D001665:Binding Sites; D002843:Chromatin; D055106:Genome-Wide Association Study; D006801:Humans; D050436:Regulatory Elements, Transcriptional; D014158:Transcription, Genetic
D002843:Chromatin