Nucleic Acids Research, Vol 25, Issue 18 3594-3604, Copyright © 1997 by Oxford University Press
A Wagner
To delineate the astronomical number of possible interactions of all genes
in a genome is a task for which conventional experimental techniques are
ill-suited. Sorely needed are rapid and inexpensive methods that identify
candidates for interacting genes, candidates that can be further
investigated by experiment. Such a method is introduced here for an
important class of gene interactions, i.e., transcriptional regulation via
transcription factors (TFs) that bind to specific enhancer or silencer
sites. The method addresses the question: which of the genes in a genome
are likely to be regulated by one or more TFs with known DNA binding
specificity? It takes advantage of the fact that many TFs show
cooperativity in transcriptional activation which manifests itself in
closely spaced TF binding sites. Such 'clusters' of binding sites are very
unlikely to occur by chance alone, as opposed to individual sites, which
are often abundant in the genome. Here, statistical information about
binding site clusters in the genome, is complemented by information about
(i) known biochemical functions of the TF, (ii) the structure of its
binding site, and (iii) function of the genes near the cluster, to identify
genes likely to be regulated by a given transcription factor. Several
applications are illustrated with the genome of Saccharomyces cerevisiae ,
and four different DNA binding activities, SBF, MBF, a sub-class of bHLH
proteins and NBF. The technique may aid in the discovery of interactions
between genes of known function, and the assignment of biological functions
to putative open reading frames.
ARTICLES
A computational genomics approach to the identification of gene networks
The Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA. aw@santafe.edu
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