PReMod: A database of genome-wide mammalian cis-regulatory module predictions

McGill University and Genome Quebec Innovation Center, 740 Dr Penfield, Montreal, Qc, Canada H3A 1A4.
Nucleic Acids Research (Impact Factor: 9.11). 02/2007; 35(Database issue):D122-6. DOI: 10.1093/nar/gkl879
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We describe PReMod, a new database of genome-wide cis-regulatory module (CRM) predictions for both the human and the mouse genomes. The prediction algorithm, described previously in Blanchette et al. (2006) Genome Res., 16, 656-668, exploits the fact that many known CRMs are made of clusters of phylogenetically conserved and repeated transcription factors (TF) binding sites. Contrary to other existing databases, PReMod is not restricted to modules located proximal to genes, but in fact mostly contains distal predicted CRMs (pCRMs). Through its web interface, PReMod allows users to (i) identify pCRMs around a gene of interest; (ii) identify pCRMs that have binding sites for a given TF (or a set of TFs) or (iii) download the entire dataset for local analyses. Queries can also be refined by filtering for specific chromosomal regions, for specific regions relative to genes or for the presence of CpG islands. The output includes information about the binding sites predicted within the selected pCRMs, and a graphical display of their distribution within the pCRMs. It also provides a visual depiction of the chromosomal context of the selected pCRMs in terms of neighboring pCRMs and genes, all of which are linked to the UCSC Genome Browser and the NCBI. PReMod:

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Available from: Francois Robert,
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    • "PReMod database predicts relationships between TFs and their TGs based on the binding affinity and conservation of CRM. It consists of more than 100,000 computationally predicted modules within the human genome [16]. These modules give a description of 229 potential transcription factor families and are the first genome-wide collection of predicted regulatory modules for the human genome [17]. "
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    ABSTRACT: Background: Chronic myelogenous leukemia (CML) is characterized by tremendous amount of immature myeloid cells in the blood circulation. E2F1-3 and MYC are important transcription factors that form positive feedback loops by reciprocal regulation in their own transcription processes. Since genes regulated by E2F1-3 or MYC are related to cell proliferation and apoptosis, we wonder if there exists difference in the coexpression patterns of genes regulated concurrently by E2F1-3 and MYC between the normal and the CML states. Results: We proposed a method to explore the difference in the coexpression patterns of those candidate target genes between the normal and the CML groups. A disease-specific cutoff point for coexpression levels that classified the coexpressed gene pairs into strong and weak coexpression classes was identified. Our developed method effectively identified the coexpression pattern differences from the overall structure. Moreover, we found that genes related to the cell adhesion and angiogenesis properties were more likely to be coexpressed in the normal group when compared to the CML group. Conclusion: Our findings may be helpful in exploring the underlying mechanisms of CML and provide useful information in cancer treatment.
    BioMed Research International 08/2014; 2014:439840. DOI:10.1155/2014/439840 · 3.17 Impact Factor
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    • "Prediction of transcription factor binding and transcription regulatory module prediction by PReMOD. The genes of interest were subjected to PReMod (Ferretti et al., 2007) ( module) and TFSEARCH: Searching Transcription Factor Binding Sites (ver 1.3) ( to predict potential ER binding sites and other transcription factors. "
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    ABSTRACT: Malignant immature ovarian teratomas (IOT) most often occur in women of reproductive age. It is unclear, however, what roles estrogenic signaling plays in the development of IOT. In this study, we examined whether estrogen receptors (ERα and β) promote the cellular malignancy of IOT. Estradiol (E2), PPT (propylpyrazole), and DPN (diarylpropionitrile) (ERα- and β-specific agonists, respectively), as well as ERα- or ERβ-specific short hairpin (sh)RNA were applied to PA-1 cells, a well-characterized IOT cell line. Cellular tumorigenic characteristics, e.g., cell migration/invasion, expression of the cancer stem/progenitor cell marker CD133, and evidence for epithelial-mesenchymal transition (EMT) were examined. In PA-1 cells that expressed ERα and ERβ, we found that ERα promoted cell migration and invasion. We also found that E2/ERα signaling altered cell behavior through non-classical transactivation function. Our data show non-genomic E2/ERα activations of focal adhesion kinase-Ras homolog gene family member A (FAK-RhoA) and ERK governed cell mobility capacity. Moreover, E2/ERα signaling induces EMT and overexpression of CD133 through upregulation micro-RNA 21 (miR21; IOT stem/progenitor promoter), and ERK phosphorylations. Furthermore, E2/ERα signaling triggers a positive feedback regulatory loop within miR21 and ERK. At last, expression levels of ERα, CD133, and EMT markers in IOT tissue samples were examined by immunohistochemistry. We found that cytosolic ERα was co-expressed with CD133 and mesenchymal cell markers but not epithelial cell markers. In conclusion, estrogenic signals exert malignant transformation capacity of cancer cells, exclusively through non-genomic regulation in female germ cell tumors. J. Cell. Physiol. © 2013 Wiley Periodicals, Inc.
    Journal of Cellular Physiology 06/2014; 229(6). DOI:10.1002/jcp.24495 · 3.84 Impact Factor
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    • "We hypothesized that the global coincident association of both MIRs and enhancers to tissue-specific gene expression is at least in part a consequence of MIR sequences frequently acting either as enhancers and/or constituting fragments of enhancer sequences. This would be consistent with previously reported individual cases of TE-derived enhancers [21,30-32]. We also reasoned that the enhancer-characteristic chromatin environment could serve as a useful proxy to identify putative MIR-derived enhancers. "
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    ABSTRACT: Background Mammalian-wide interspersed repeats (MIRs) are the most ancient family of transposable elements (TEs) in the human genome. The deep conservation of MIRs initially suggested the possibility that they had been exapted to play functional roles for their host genomes. MIRs also happen to be the only TEs whose presence in-and-around human genes is positively correlated to tissue-specific gene expression. Similar associations of enhancer prevalence within genes and tissue-specific expression, along with MIRs’ previous implication as providing regulatory sequences, suggested a possible link between MIRs and enhancers. Results To test the possibility that MIRs contribute functional enhancers to the human genome, we evaluated the relationship between MIRs and human tissue-specific enhancers in terms of genomic location, chromatin environment, regulatory function, and mechanistic attributes. This analysis revealed MIRs to be highly concentrated in enhancers of the K562 and HeLa human cell-types. Significantly more enhancers were found to be linked to MIRs than would be expected by chance, and putative MIR-derived enhancers are characterized by a chromatin environment highly similar to that of canonical enhancers. MIR-derived enhancers show strong associations with gene expression levels, tissue-specific gene expression and tissue-specific cellular functions, including a number of biological processes related to erythropoiesis. MIR-derived enhancers were found to be a rich source of transcription factor binding sites, underscoring one possible mechanistic route for the element sequences co-option as enhancers. There is also tentative evidence to suggest that MIR-enhancer function is related to the transcriptional activity of non-coding RNAs. Conclusions Taken together, these data reveal enhancers to be an important cis-regulatory platform from which MIRs can exercise a regulatory function in the human genome and help to resolve a long-standing conundrum as to the reason for MIRs’ deep evolutionary conservation.
    Mobile DNA 05/2014; 5(1):14. DOI:10.1186/1759-8753-5-14 · 2.11 Impact Factor
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