Seed-based systematic discovery of specific transcription factor target genes

Paul-Ehrlich-Zentrum für Experimentelle Medizin, AG Systems Biology-Computational Physiology, Tucholskystrasse 2, Berlin, Germany.
FEBS Journal (Impact Factor: 4). 07/2008; 275(12):3178-92. DOI: 10.1111/j.1742-4658.2008.06471.x
Source: PubMed


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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Available from: Ralf Mrowka, Jul 30, 2015
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    • "The data contain a collection of different independent investigations, including expression profiles from tumor samples, cancer cell lines, and different organ-specific tissue samples, as well as expression data from studies of diverse biological processes such as cell cycle, stress, signaling, and apoptosis . We correlated HIF-1α mRNA levels with randomly chosen genes or with verified HIF-1 target genes (Semenza, 2003), as described earlier (Mrowka et al., 2008). Of note, we found a significant positive correlation between HIF-1α mRNA levels and HIF-1 target gene expression (Figure 1C), supporting the view that HIF-1α mRNA level, and thus mRNA stability, is important for HIF-1 function. "
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    • "interaction in this pathway. Interestingly, Sudhakar and colleagues characterized optineurin itself as a target gene of NF-κB [23], [24]. Optineurin recruitment to TNFR1 has been postulated to negatively regulate TNF-induced NF-κB activation due to competition of optineurin with the regulatory subunit of IκB kinase (NF-κB essential modulator, NEMO) for ubiquitinated RIP1 [11]. "
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    PLoS ONE 06/2012; 7(6):e38348. DOI:10.1371/journal.pone.0038348 · 3.23 Impact Factor
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    • "These genes were used as input for the web interface TargetFinder ( [50], which uses a seed-based sorting algorithm [80] to rank all genes in the human genome according to their similarity to a given input set of genes. The sorted list of all genes showed a strong enrichment with regard to positive EMT genes as indicated by a recovery test (p<10e-20). "
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