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      ELK1 Uses Different DNA Binding Modes to Regulate Functionally Distinct Classes of Target Genes

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      PLoS Genetics
      Public Library of Science

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          Abstract

          Eukaryotic transcription factors are grouped into families and, due to their similar DNA binding domains, often have the potential to bind to the same genomic regions. This can lead to redundancy at the level of DNA binding, and mechanisms are required to generate specific functional outcomes that enable distinct gene expression programmes to be controlled by a particular transcription factor. Here we used ChIP–seq to uncover two distinct binding modes for the ETS transcription factor ELK1. In one mode, other ETS transcription factors can bind regulatory regions in a redundant fashion; in the second, ELK1 binds in a unique fashion to another set of genomic targets. Each binding mode is associated with different binding site features and also distinct regulatory outcomes. Furthermore, the type of binding mode also determines the control of functionally distinct subclasses of genes and hence the phenotypic response elicited. This is demonstrated for the unique binding mode where a novel role for ELK1 in controlling cell migration is revealed. We have therefore uncovered an unexpected link between the type of binding mode employed by a transcription factor, the subsequent gene regulatory mechanisms used, and the functional categories of target genes controlled.

          Author Summary

          One of the major outstanding questions in eukaryotic gene regulation is how transcription factors with seemingly very similar DNA binding specificities elicit specific biological responses. The ETS transcription factor family provides a paradigm for investigating this phenomenon. Here, we have focused on the ETS transcription factor ELK1, and by combining genome-wide binding analysis coupled with gene expression analysis we have dissected two distinct gene regulatory activities for this transcription factor. In each of these regulatory modes, ELK1 exhibits distinct DNA binding characteristics which correlate with either positive or negative transcriptional activities and give rise to functionally distinct gene expression programmes. We demonstrate a novel function for ELK1 in controlling cell migration through one of these regulatory modes. Thus, we have demonstrated a clear link between the types of regulatory region bound by a transcription factor and its ability to control gene expression (i.e. in a positive or negative manner) and the functional downstream consequences of its target gene cohort. This work has implications for understanding how members of other multi-protein transcription factor families might function to generate different downstream functional consequences through engaging with different types of regulatory regions.

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          Most cited references36

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          DAVID: Database for Annotation, Visualization, and Integrated Discovery.

          Functional annotation of differentially expressed genes is a necessary and critical step in the analysis of microarray data. The distributed nature of biological knowledge frequently requires researchers to navigate through numerous web-accessible databases gathering information one gene at a time. A more judicious approach is to provide query-based access to an integrated database that disseminates biologically rich information across large datasets and displays graphic summaries of functional information. Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) addresses this need via four web-based analysis modules: 1) Annotation Tool - rapidly appends descriptive data from several public databases to lists of genes; 2) GoCharts - assigns genes to Gene Ontology functional categories based on user selected classifications and term specificity level; 3) KeggCharts - assigns genes to KEGG metabolic processes and enables users to view genes in the context of biochemical pathway maps; and 4) DomainCharts - groups genes according to PFAM conserved protein domains. Analysis results and graphical displays remain dynamically linked to primary data and external data repositories, thereby furnishing in-depth as well as broad-based data coverage. The functionality provided by DAVID accelerates the analysis of genome-scale datasets by facilitating the transition from data collection to biological meaning.
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            Is Open Access

            Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences

            Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy http://usegalaxy.org, an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis.
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              Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection.

              Recent advances in cDNA and oligonucleotide DNA arrays have made it possible to measure the abundance of mRNA transcripts for many genes simultaneously. The analysis of such experiments is nontrivial because of large data size and many levels of variation introduced at different stages of the experiments. The analysis is further complicated by the large differences that may exist among different probes used to interrogate the same gene. However, an attractive feature of high-density oligonucleotide arrays such as those produced by photolithography and inkjet technology is the standardization of chip manufacturing and hybridization process. As a result, probe-specific biases, although significant, are highly reproducible and predictable, and their adverse effect can be reduced by proper modeling and analysis methods. Here, we propose a statistical model for the probe-level data, and develop model-based estimates for gene expression indexes. We also present model-based methods for identifying and handling cross-hybridizing probes and contaminating array regions. Applications of these results will be presented elsewhere.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                May 2012
                May 2012
                10 May 2012
                : 8
                : 5
                : e1002694
                Affiliations
                [1]Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom
                Institut de Biologie de Lille, France
                Author notes

                Conceived and designed the experiments: ZO ADS. Performed the experiments: ZO. Analyzed the data: ZO ADS. Contributed reagents/materials/analysis tools: ZO. Wrote the paper: ZO ADS.

                Article
                PGENETICS-D-12-00027
                10.1371/journal.pgen.1002694
                3349735
                22589737
                ff715944-44ab-4c87-8741-c3640967da47
                Odrowaz, Sharrocks. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 4 January 2012
                : 22 March 2012
                Page count
                Pages: 16
                Categories
                Research Article
                Biology
                Biochemistry
                Genomics
                Genome Expression Analysis
                Molecular Cell Biology
                Cellular Structures
                Cytoskeleton
                Gene Expression
                DNA transcription
                Systems Biology

                Genetics
                Genetics

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