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      Genome-wide Analysis of Transcription Factor E2F1 Mutant Proteins Reveals That N- and C-terminal Protein Interaction Domains Do Not Participate in Targeting E2F1 to the Human Genome*

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          Abstract

          Previous studies of E2F family members have suggested that protein-protein interactions may be the mechanism by which E2F proteins are recruited to specific genomic regions. We have addressed this hypothesis on a genome-wide scale using ChIP-seq analysis of MCF7 cell lines that express tagged wild type and mutant E2F1 proteins. First, we performed ChIP-seq for tagged WT E2F1. Then, we analyzed E2F1 proteins that lacked the N-terminal SP1 and cyclin A binding domains, the C-terminal transactivation and pocket protein binding domains, and the internal marked box domain. Surprisingly, we found that the ChIP-seq patterns of the mutant proteins were identical to that of WT E2F1. However, mutation of the DNA binding domain abrogated all E2F1 binding to the genome. These results suggested that the interaction between the E2F1 DNA binding domain and a consensus motif may be the primary determinant of E2F1 recruitment. To address this possibility, we analyzed the in vivo binding sites for the in vitro-derived consensus E2F1 motif (TTTSSCGC) and also performed de novo motif analysis. We found that only 12% of the ChIP-seq peaks contained the TTTSSCGC motif. De novo motif analysis indicated that most of the in vivo sites lacked the 5′ half of the in vitro-derived consensus, having instead the in vivo consensus of CGCGC. In summary, our findings do not provide support for the model that protein-protein interactions are involved in recruiting E2F1 to the genome, but rather suggest that recognition of a motif found at most human promoters is the critical determinant.

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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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            Connecting microRNA genes to the core transcriptional regulatory circuitry of embryonic stem cells.

            MicroRNAs (miRNAs) are crucial for normal embryonic stem (ES) cell self-renewal and cellular differentiation, but how miRNA gene expression is controlled by the key transcriptional regulators of ES cells has not been established. We describe here the transcriptional regulatory circuitry of ES cells that incorporates protein-coding and miRNA genes based on high-resolution ChIP-seq data, systematic identification of miRNA promoters, and quantitative sequencing of short transcripts in multiple cell types. We find that the key ES cell transcription factors are associated with promoters for miRNAs that are preferentially expressed in ES cells and with promoters for a set of silent miRNA genes. This silent set of miRNA genes is co-occupied by Polycomb group proteins in ES cells and shows tissue-specific expression in differentiated cells. These data reveal how key ES cell transcription factors promote the ES cell miRNA expression program and integrate miRNAs into the regulatory circuitry controlling ES cell identity.
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              Genome-wide identification of in vivo protein–DNA binding sites from ChIP-Seq data

              ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with ultra high-throughput massively parallel sequencing, is increasingly being used for mapping protein–DNA interactions in-vivo on a genome scale. Typically, short sequence reads from ChIP-Seq are mapped to a reference genome for further analysis. Although genomic regions enriched with mapped reads could be inferred as approximate binding regions, short read lengths (∼25–50 nt) pose challenges for determining the exact binding sites within these regions. Here, we present SISSRs (Site Identification from Short Sequence Reads), a novel algorithm for precise identification of binding sites from short reads generated from ChIP-Seq experiments. The sensitivity and specificity of SISSRs are demonstrated by applying it on ChIP-Seq data for three widely studied and well-characterized human transcription factors: CTCF (CCCTC-binding factor), NRSF (neuron-restrictive silencer factor) and STAT1 (signal transducer and activator of transcription protein 1). We identified 26 814, 5813 and 73 956 binding sites for CTCF, NRSF and STAT1 proteins, respectively, which is 32, 299 and 78% more than that inferred previously for the respective proteins. Motif analysis revealed that an overwhelming majority of the identified binding sites contained the previously established consensus binding sequence for the respective proteins, thus attesting for SISSRs’ accuracy. SISSRs’ sensitivity and precision facilitated further analyses of ChIP-Seq data revealing interesting insights, which we believe will serve as guidance for designing ChIP-Seq experiments to map in vivo protein–DNA interactions. We also show that tag densities at the binding sites are a good indicator of protein–DNA binding affinity, which could be used to distinguish and characterize strong and weak binding sites. Using tag density as an indicator of DNA-binding affinity, we have identified core residues within the NRSF and CTCF binding sites that are critical for a stronger DNA binding.
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                Author and article information

                Journal
                J Biol Chem
                jbc
                jbc
                JBC
                The Journal of Biological Chemistry
                American Society for Biochemistry and Molecular Biology (9650 Rockville Pike, Bethesda, MD 20814, U.S.A. )
                0021-9258
                1083-351X
                8 April 2011
                10 February 2011
                10 February 2011
                : 286
                : 14
                : 11985-11996
                Affiliations
                From the []Genome Center, University of California, Davis, California 95616,
                the [§ ]Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio 43210, and
                the []Department of Biochemistry & Molecular Biology, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California 90089
                Author notes
                [2 ] To whom correspondence should be addressed: Dept. of Biochemistry & Molecular Biology, Norris Comprehensive Cancer Center, 1450 Biggy St., NRT 6503, mail code 9601, University of Southern California, Los Angeles, CA 90089. Tel.: 323-442-8015; E-mail: pfarnham@ 123456usc.edu .
                [1]

                Supported in part by National Institutes of Health Molecular and Cellular Biology Training Grant GM007377.

                Article
                M110.217158
                10.1074/jbc.M110.217158
                3069401
                21310950
                a4c07375-7716-4ec2-826a-02d886b7f6bf
                © 2011 by The American Society for Biochemistry and Molecular Biology, Inc.

                Author's Choice—Final version full access.

                Creative Commons Attribution Non-Commercial License applies to Author Choice Articles

                History
                : 29 December 2010
                : 10 February 2011
                Funding
                Funded by: National Institutes of Health
                Award ID: GM007377
                Categories
                Genomics and Proteomics

                Biochemistry
                transcription regulation,transcription promoter,e2f transcription factor,dna binding protein,chromatin immunoprecipitation (chip)

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