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      Genome-Wide Analysis Reveals PADI4 Cooperates with Elk-1 to Activate c-Fos Expression in Breast Cancer Cells

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          Abstract

          Peptidylarginine deiminase IV (PADI4) catalyzes the conversion of positively charged arginine and methylarginine residues to neutrally charged citrulline, and this activity has been linked to the repression of a limited number of target genes. To broaden our knowledge of the regulatory potential of PADI4, we utilized chromatin immunoprecipitation coupled with promoter tiling array (ChIP-chip) analysis to more comprehensively investigate the range of PADI4 target genes across the genome in MCF-7 breast cancer cells. Results showed that PADI4 is enriched in gene promoter regions near transcription start sites (TSSs); and, surprisingly, this pattern of binding is primarily associated with actively transcribed genes. Computational analysis found potential binding sites for Elk-1, a member of the ETS oncogene family, to be highly enriched around PADI4 binding sites; and coimmunoprecipitation analysis then confirmed that Elk-1 physically associates with PADI4. To better understand how PADI4 may facilitate gene transactivation, we then show that PADI4 interacts with Elk-1 at the c-Fos promoter and that, following Epidermal Growth Factor (EGF) stimulation, PADI4 catalytic activity facilitates Elk-1 phosphorylation, histone H4 acetylation, and c-Fos transcriptional activation. These results define a novel role for PADI4 as a transcription factor co-activator.

          Author Summary

          Peptidylarginine deiminase 4 (PADI4) converts positively charged arginine and methylarginine residues on histones to the neutrally charged non-standard amino acid citrulline. We and others have previously shown that citrullination of a small subset of gene promoters, such as the estrogen receptor target, TFF1, appears to downregulate gene expression. In this study, we looked across the human genome using ChIP-chip to better define the full repertoire of genes that are regulated by PADI4 in breast cancer cells. Surprisingly, we found that PADI4 appears to primarily be involved in gene activation, as opposed to gene repression. Further, we found that PADI4 is likely recruited as a co-activator to these target genes by a range of well-defined transcription factors, such as Elk-1. With respect to how PADI4 activates gene transcription, we show that PADI4 directly interacts with Elk-1 at its well-defined target, the c-Fos oncogene. Additionally, we found that, following stimulation with epidermal growth factor, PADI4 appears to directly target Elk-1 for citrullination, which in turn leads to increased histone acetylation and gene transcription. These novel genome-wide and gene-specific findings suggest that PADI4 plays a much broader role in gene activation than previously thought.

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          Most cited references45

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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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            Normalization of cDNA microarray data.

            Normalization means to adjust microarray data for effects which arise from variation in the technology rather than from biological differences between the RNA samples or between the printed probes. This paper describes normalization methods based on the fact that dye balance typically varies with spot intensity and with spatial position on the array. Print-tip loess normalization provides a well-tested general purpose normalization method which has given good results on a wide range of arrays. The method may be refined by using quality weights for individual spots. The method is best combined with diagnostic plots of the data which display the spatial and intensity trends. When diagnostic plots show that biases still remain in the data after normalization, further normalization steps such as plate-order normalization or scale-normalization between the arrays may be undertaken. Composite normalization may be used when control spots are available which are known to be not differentially expressed. Variations on loess normalization include global loess normalization and two-dimensional normalization. Detailed commands are given to implement the normalization techniques using freely available software.
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              Genome-wide analysis of estrogen receptor binding sites.

              The estrogen receptor is the master transcriptional regulator of breast cancer phenotype and the archetype of a molecular therapeutic target. We mapped all estrogen receptor and RNA polymerase II binding sites on a genome-wide scale, identifying the authentic cis binding sites and target genes, in breast cancer cells. Combining this unique resource with gene expression data demonstrates distinct temporal mechanisms of estrogen-mediated gene regulation, particularly in the case of estrogen-suppressed genes. Furthermore, this resource has allowed the identification of cis-regulatory sites in previously unexplored regions of the genome and the cooperating transcription factors underlying estrogen signaling in breast cancer.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                June 2011
                June 2011
                2 June 2011
                : 7
                : 6
                : e1002112
                Affiliations
                [1 ]Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America
                [2 ]Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, United States of America
                [3 ]Laboratory of Chromatin Biology, Rockefeller University, New York, New York, United States of America
                [4 ]Department of Chemistry and Biochemistry, University of South Carolina, Columbia, South Carolina, United States of America
                [5 ]Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America
                Max-Planck-Institute of Immunobiology, Germany
                Author notes

                ¤: Current address: Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, New York, United States of America

                Conceived and designed the experiments: XZ MJG MSR WLK SAC. Performed the experiments: XZ BDC. Analyzed the data: XZ MJG MSR WLK SAC. Contributed reagents/materials/analysis tools: SS CPC PRT MSR. Wrote the paper: XZ SAC.

                Article
                PGENETICS-D-10-00162
                10.1371/journal.pgen.1002112
                3107201
                21655091
                4739c47a-fe19-4227-8106-9cb15e692ec6
                Zhang et al. 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
                : 19 October 2010
                : 13 April 2011
                Page count
                Pages: 15
                Categories
                Research Article
                Biology
                Genomics
                Genome Expression Analysis
                Molecular Cell Biology
                Gene Expression
                DNA transcription

                Genetics
                Genetics

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