Seed-based systematic discovery of specific transcription factor target genes.
ABSTRACT Reliable prediction of specific transcription factor target genes is a major challenge in systems biology and functional genomics. Current sequence-based methods yield many false predictions, due to the short and degenerated DNA-binding motifs. Here, we describe a new systematic genome-wide approach, the seed-distribution-distance method, that searches large-scale genome-wide expression data for genes that are similarly expressed as known targets. This method is used to identify genes that are likely targets, allowing sequence-based methods to focus on a subset of genes, giving rise to fewer false-positive predictions. We show by cross-validation that this method is robust in recovering specific target genes. Furthermore, this method identifies genes with typical functions and binding motifs of the seed. The method is illustrated by predicting novel targets of the transcription factor nuclear factor kappaB (NF-kappaB). Among the new targets is optineurin, which plays a key role in the pathogenesis of acquired blindness caused by adult-onset primary open-angle glaucoma. We show experimentally that the optineurin gene and other predicted genes are targets of NF-kappaB. Thus, our data provide a missing link in the signalling of NF-kappaB and the damping function of optineurin in signalling feedback of NF-kappaB. We present a robust and reliable method to enhance the genome-wide prediction of specific transcription factor target genes that exploits the vast amount of expression information available in public databases today.
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ABSTRACT: We have taken an integrated approach in which expression profiling has been combined with the use of small molecule inhibitors and computational analysis of transcription factor binding sites to characterize regulatory sequences of genes that are targets of specific signaling pathways in growth factor-stimulated human cells. T98G cells were stimulated with platelet-derived growth factor (PDGF) and analyzed by DNA microarrays, which identified 74 immediate-early gene transcripts. Cells were then treated with inhibitors to identify subsets of genes that are targets of the phosphatidylinositol 3-kinase (PI3K) and MEK/ERK signaling pathways. Four groups of PDGF-induced genes were defined: independent of PI3K and MEK/ERK signaling, dependent on PI3K signaling, dependent on MEK/ERK signaling, and dependent on both pathways. The upstream regions of all genes in the four groups were scanned using TRANSFAC for putative cis-elements as compared with a background set of non-induced genes. Binding sites for 18 computationally predicted transcription factors were over-represented in the four groups of co-expressed genes compared with the background sequences (p < 0.01). Many of the cis-elements identified were conserved in orthologous mouse genes, and many of the predicted elements and their cognate transcription factors were consistent with previous experimental data. In addition, chromatin immunoprecipitation assays experimentally verified nine predicted SRF binding sites in T98G cells, including a previously unknown SRF site upstream of DUSP5. These results indicate that groups of human genes regulated by discrete intracellular signaling pathways share common cis-regulatory elements.Journal of Biological Chemistry 06/2004; 279(19):20167-77. · 4.65 Impact Factor
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ABSTRACT: Transcriptional regulation of all genes is initiated by the specific binding of regulatory proteins called transcription factors to specific sites on DNA called promoter regions. Transcription factors employ a variety of mechanisms to recognise their DNA target sites. In the last few decades, attempts have been made to describe these mechanisms by general sets of rules and associated models. We give an overview of these models, starting with a historical review of the somewhat controversial issue of a "recognition code" governing protein-DNA interaction. We then present a probabilistic framework in which advantages and disadvantages of various models can be discussed. Finally, we conclude that simplifying assumptions about additivity of interactions are sufficiently justified in many situations (and can be suitably extended in other situations) to allow a unifying concept of a "probabilistic code" for protein-DNA recognition to be defined.BioEssays 06/2002; 24(5):466-75. · 5.42 Impact Factor
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ABSTRACT: Glutamate and the proinflammatory cytokine, tumor necrosis factor alpha (TNF alpha), have been suggested to contribute to neurodegenerative diseases. We investigated the interaction of TNF alpha and glutamate on neuronal cell death using fluorescence propidium iodide uptake in rat organotypic hippocampal-entorhinal cortex (HEC) brain slice culture that maintains the cytoarchitecture of the intact brain. Time course and concentration studies indicate that glutamate produced significant neuronal cell death in all four brain areas examined, for example, entorhinal cortex, hippocampal CA1 and CA3 fields, and dentate gyrus. TNF alpha alone at concentration of 20 ng/ml caused little or no detectable neuronal cell death, however, when combined with submaximal glutamate (3.3 mM), TNF alpha significantly increased and accelerated glutamate neurotoxicity. TNF alpha potentiation of glutamate neurotoxicity is blocked by NMDA receptor antagonists but not by AMPA antagonists CNQX and NBQX. Studies directly measuring [14C]-glutamate uptake in HEC slices indicate that TNF alpha dose-dependently inhibited glutamate uptake. Further, inhibitors of glial glutamate transporters potentiated glutamate neurotoxicity similar to TNF alpha. The antioxidant butylated hydroxytoluene (BHT) and the NF kappa B inhibitor PTD-p65 peptide inhibit NF kappa B activation and TNF alpha potentiation of glutamate neurotoxicity. BHT prevented the inhibition of TNFalpha on glutamate transport in HEC slices and also blocked nuclear translocation of NF kappa B subunit p65. These data indicate that TNF alpha and glutamate can act synergistically to induce neuronal cell death. TNF alpha potentiation of glutamate neurotoxicity through the blockade of glutamate transporter activity may represent an important mechanism of neurodegeneration associated with neuroinflammation.Brain Research 03/2005; 1034(1-2):11-24. · 2.88 Impact Factor