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Abstract
A major challenge in the post-genome era is to reconstruct regulatory networks from the biological knowledge accumulated up to date. The development of tools for identifying direct target genes of transcription factors (TFs) is critical to this endeavor. Given a set of microarray experiments, a probabilistic model called TRANSMODIS has been developed which can infer the direct targets of a TF by integrating sequence motif, gene expression and ChIP-chip data. The performance of TRANSMODIS was first validated on a set of transcription factor perturbation experiments (TFPEs) involving Pho4p, a well studied TF in Saccharomyces cerevisiae. TRANSMODIS removed elements of arbitrariness in manual target gene selection process and produced results that concur with one's intuition. TRANSMODIS was further validated on a genome-wide scale by comparing it with two other methods in Saccharomyces cerevisiae. The usefulness of TRANSMODIS was then demonstrated by applying it to the identification of direct targets of DAF-16, a critical TF regulating ageing in Caenorhabditis elegans. We found that 189 genes were tightly regulated by DAF-16. In addition, DAF-16 has differential preference for motifs when acting as an activator or repressor, which awaits experimental verification. TRANSMODIS is computationally efficient and robust, making it a useful probabilistic framework for finding immediate targets.
Highlights
One of the major goals in the post-genome era is to establish a connectivity diagram of transcription network, which requires identification of direct targets of transcription factors (TFs)
To determine genes that are regulated by a specific TF, the TF is constitutively activated or inhibited such that the target genes of the TF should have significant expression changes in most of these experiments, which we call transcription factor perturbation experiments (TFPEs)[3]
TRANSMODIS is a generalization of MODEM[22], a model we developed previously that is applicable only to a single gene expression microarray or chromatin immunoprecipitation (ChIP)-chip experiment
Summary
One of the major goals in the post-genome era is to establish a connectivity diagram of transcription network, which requires identification of direct targets of transcription factors (TFs). One commonly used approach to detect regulatory interactions between TFs and genes is chromatin immunoprecipitation followed by microarray hybridization (ChIP-chip)[1,2], which is a binding assay. Binding of a TF to regulatory sequences does not necessarily imply regulation of gene expression. ChIP-chip experiment is often complemented by functional assays using gene microarray. To determine genes that are regulated by a specific TF, the TF is constitutively activated or inhibited such that the target genes of the TF should have significant expression changes in most of these experiments, which we call transcription factor perturbation experiments (TFPEs)[3]. In TFPEs, a combination of thresholds, e.g. the least amount of fold change considered to be significant and the minimum number of experiments in which the gene expression changes are required to be significant, need to be pre-specified. Direct and indirect targets of the TF cannot be discriminated by expression alone
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