Abstract
BackgroundThe use of global gene expression profiling is a well established approach to understand biological processes. One of the major goals of these investigations is to identify sets of genes with similar expression patterns. Such gene signatures may be very informative and reveal new aspects of particular biological processes. A logical and systematic next step is to reduce the identified gene signatures to the regulatory components that induce the relevant gene expression changes. A central issue in this context is to identify transcription factors, or transcription factor binding sites (TFBS), likely to be of importance for the expression of the gene signatures.ResultsWe develop a strategy that efficiently produces TFBS/promoter databases based on user-defined criteria. The resulting databases constitute all genes in the Santa Cruz database and the positions for all TFBS provided by the user as position weight matrices. These databases are then used for two purposes, to identify significant TFBS in the promoters in sets of genes and to identify clusters of co-occurring TFBS. We use two criteria for significance, significantly enriched TFBS in terms of total number of binding sites for the promoters, and significantly present TFBS in terms of the fraction of promoters with binding sites. Significant TFBS are identified by a re-sampling procedure in which the query gene set is compared with typically 105 gene lists of similar size randomly drawn from the TFBS/promoter database. We apply this strategy to a large number of published ChIP-Chip data sets and show that the proposed approach faithfully reproduces ChIP-Chip results. The strategy also identifies relevant TFBS when analyzing gene signatures obtained from the MSigDB database. In addition, we show that several TFBS are highly correlated and that co-occurring TFBS define functionally related sets of genes.ConclusionsThe presented approach of promoter analysis faithfully reproduces the results from several ChIP-Chip and MigDB derived gene sets and hence may prove to be an important method in the analysis of gene signatures obtained through ChIP-Chip or global gene expression experiments. We show that TFBS are organized in clusters of co-occurring TFBS that together define highly coherent sets of genes.
Highlights
The use of global gene expression profiling is a well established approach to understand biological processes
These databases are used for two purposes, to identify significant transcription factor binding sites (TFBS) in the promoters of gene sets and to identify clusters of cooccurring TFBS on a genome-wide scale
A second TFBS/promoter database aimed for phylogenic foot printing analyses was created by using the corresponding orthologous genes listed in the NCBI HomoloGene database based on human and mouse
Summary
The use of global gene expression profiling is a well established approach to understand biological processes. The first step in this effort is to identify putative TFBSs in a set of gene promoters This is normally accomplished by searching the DNA sequence for matches to generalized sequence patterns obtained from experimentally characterized binding sites. In the first application significant TFBS are identified by a re-sampling procedure in which the query gene set is compared with typically 105 independent gene lists of similar size randomly drawn from the TFBS/promoter database. For these purposes two criteria for significance are used; significant enrichment and significant presence. We show that several groups of TFBS are highly correlated and that correlated TFBS define functionally related sets of genes
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