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      Mapping the complexity of transcription control in higher eukaryotes

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      Author(s): 1 , 2 , 3 , 4 ,
      Publication date (Electronic):
      Journal: Genome Biology
      Publisher: BioMed Central

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          Abstract

          Recent large analyses suggest the importance of combinatorial regulation by broadly expressed transcription factors rather than expression domains characterized by highly specific factors.

          Abstract

          Recent genomic analyses suggest the importance of combinatorial regulation by broadly expressed transcription factors rather than expression domains characterized by highly specific factors.

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          An atlas of combinatorial transcriptional regulation in mouse and man.

          Timothy Ravasi, Harukazu Suzuki, Carlo Cannistraci … (2010)
          Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution. (c) 2010 Elsevier Inc. All rights reserved.
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            Analysis of homeodomain specificities allows the family-wide prediction of preferred recognition sites.

            Marcus B. Noyes, Ryan G. Christensen, Atsuya Wakabayashi … (2008)
            We describe the comprehensive characterization of homeodomain DNA-binding specificities from a metazoan genome. The analysis of all 84 independent homeodomains from D. melanogaster reveals the breadth of DNA sequences that can be specified by this recognition motif. The majority of these factors can be organized into 11 different specificity groups, where the preferred recognition sequence between these groups can differ at up to four of the six core recognition positions. Analysis of the recognition motifs within these groups led to a catalog of common specificity determinants that may cooperate or compete to define the binding site preference. With these recognition principles, a homeodomain can be reengineered to create factors where its specificity is altered at the majority of recognition positions. This resource also allows prediction of homeodomain specificities from other organisms, which is demonstrated by the prediction and analysis of human homeodomain specificities.
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              FlyTF: improved annotation and enhanced functionality of the Drosophila transcription factor database

              Ulrike Pfreundt, Daniel P. James, Susan Tweedie … (2010)
              FlyTF (http://www.flytf.org) is a database of computationally predicted and/or experimentally verified site-specific transcription factors (TFs) in the fruit fly Drosophila melanogaster. The manual classification of TFs in the initial version of FlyTF that concentrated primarily on the DNA-binding characteristics of the proteins has now been extended to a more fine-grained annotation of both DNA binding and regulatory properties in the new release. Furthermore, experimental evidence from the literature was classified into a defined vocabulary, and in collaboration with FlyBase, translated into Gene Ontology (GO) annotation. While our GO annotations will also be available through FlyBase as they will be incorporated into the genes’ official GO annotation in the future, the entire evidence used for classification including computational predictions and quotes from the literature can be accessed through FlyTF. The FlyTF website now builds upon the InterMine framework, which provides experimental and computational biologists with powerful search and filter functionality, list management tools and access to genomic information associated with the TFs.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Genome Biol
                Title: Genome Biology
                Publisher: BioMed Central
                ISSN (Print): 1465-6906
                ISSN (Electronic): 1465-6914
                Publication date (Print): 2010
                Publication date (Electronic): 30 April 2010
                Publication date PMC-release: 30 April 2011
                Volume: 11
                Issue: 4
                Page: 115
                Affiliations
                [1 ]Max Planck Institute for Molecular Cell Biology and Genetics, Pfotenhauerstr. 108, 01307 Dresden, Germany
                [2 ]Institute for Genome Sciences & Policy, Duke University Medical Center, 101 Science Drive, Durham, NC 27708, USA
                [3 ]Department of Biostatistics and Bioinformatics, Duke University School of Medicine, 2301 Erwin Road, Durham, NC 27710, USA
                [4 ]Department of Computer Science, Duke University, LSRC Building D101, 450 Research Drive, Durham, NC 27708, USA
                Article
                Publisher ID: gb-2010-11-4-115
                DOI: 10.1186/gb-2010-11-4-115
                PMC ID: 2884534
                PubMed ID: 20441601
                SO-VID: db637d8a-16af-41f7-84e7-50ac9a4b5e57
                Copyright © Copyright ©2010 BioMed Central Ltd
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                Subject: Research highlight

                ScienceOpen disciplines: Genetics
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                ScienceOpen disciplines: Genetics

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