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      Transcriptional Regulation by CHIP/LDB Complexes

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          Abstract

          It is increasingly clear that transcription factors play versatile roles in turning genes “on” or “off” depending on cellular context via the various transcription complexes they form. This poses a major challenge in unraveling combinatorial transcription complex codes. Here we use the powerful genetics of Drosophila combined with microarray and bioinformatics analyses to tackle this challenge. The nuclear adaptor CHIP/LDB is a major developmental regulator capable of forming tissue-specific transcription complexes with various types of transcription factors and cofactors, making it a valuable model to study the intricacies of gene regulation. To date only few CHIP/LDB complexes target genes have been identified, and possible tissue-dependent crosstalk between these complexes has not been rigorously explored. SSDP proteins protect CHIP/LDB complexes from proteasome dependent degradation and are rate-limiting cofactors for these complexes. By using mutations in SSDP, we identified 189 down-stream targets of CHIP/LDB and show that these genes are enriched for the binding sites of APTEROUS (AP) and PANNIER (PNR), two well studied transcription factors associated with CHIP/LDB complexes. We performed extensive genetic screens and identified target genes that genetically interact with components of CHIP/LDB complexes in directing the development of the wings (28 genes) and thoracic bristles (23 genes). Moreover, by in vivo RNAi silencing we uncovered novel roles for two of the target genes, xbp1 and Gs-alpha, in early development of these structures. Taken together, our results suggest that loss of SSDP disrupts the normal balance between the CHIP-AP and the CHIP-PNR transcription complexes, resulting in down-regulation of CHIP-AP target genes and the concomitant up-regulation of CHIP-PNR target genes. Understanding the combinatorial nature of transcription complexes as presented here is crucial to the study of transcription regulation of gene batteries required for development.

          Author Summary

          Different cell types in multi-cellular organisms are determined by the repertoire of genes active in each cell. This repertoire, or transcriptome, is established by the coordinated activity of transcription factors and cofactors that form modular transcription complexes. The modular nature of transcription complexes complicates our understanding of how transcription factors shape the transcriptome. CHIP/LDB transcription complexes direct formation of various cell types including blood and nerve cells. CHIP/LDB malfunction leads to developmental defects and cancer. The function of these complexes depends critically on the docking of specific transcription factors and co-factors at a specific time and in a specific cell type, making them outstanding models for intricate transcriptional regulation. Here we demonstrate that loss of SSDP, a key regulatory component of CHIP/LDB transcription complexes, alters transcription of a large group of genes. We used bioinformatics tools and genetic tests to examine the function of additional components of CHIP/LDB transcription complexes and their target genes during the development of specific organs. We demonstrate how differences in the availability of transcription factors in different cells can affect the function and composition of CHIP/LDB transcription complexes.

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          Most cited references61

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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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              XBP1 controls diverse cell type- and condition-specific transcriptional regulatory networks.

              Using genome-wide approaches, we have elucidated the regulatory circuitry governed by the XBP1 transcription factor, a key effector of the mammalian unfolded protein response (UPR), in skeletal muscle and secretory cells. We identified a core group of genes involved in constitutive maintenance of ER function in all cell types and tissue- and condition-specific targets. In addition, we identified a cadre of unexpected targets that link XBP1 to neurodegenerative and myodegenerative diseases, as well as to DNA damage and repair pathways. Remarkably, we found that XBP1 regulates functionally distinct targets through different sequence motifs. Further, we identified Mist1, a critical regulator of differentiation, as an important target of XBP1, providing an explanation for developmental defects associated with XBP1 loss of function. Our results provide a detailed picture of the regulatory roadmap governed by XBP1 in distinct cell types as well as insight into unexplored functions of XBP1.
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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
                August 2010
                August 2010
                12 August 2010
                : 6
                : 8
                : e1001063
                Affiliations
                [1 ]Department of Microbiology and Biotechnology, Tel Aviv University, Tel Aviv, Israel
                [2 ]Department of Physiology and Pharmacology, Tel Aviv University, Tel Aviv, Israel
                [3 ]Balvatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
                [4 ]Section on Mammalian Molecular Genetics, Program in Genomics of Development, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, United States of America
                [5 ]Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
                Harvard Medical School, Howard Hughes Medical Institute, United States of America
                Author notes

                Conceived and designed the experiments: RB ER RS HW BO DS. Performed the experiments: RB MY. Analyzed the data: RB LL NY BO DS. Contributed reagents/materials/analysis tools: ER RS HW BO DS. Wrote the paper: RB BO DS.

                Article
                09-PLGE-RA-1587R2
                10.1371/journal.pgen.1001063
                2921152
                20730086
                32425112-2acf-433f-b4af-ddae40e3ebbd
                This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
                History
                : 7 September 2009
                : 12 July 2010
                Page count
                Pages: 14
                Categories
                Research Article
                Computational Biology/Genomics
                Computational Biology/Molecular Genetics
                Developmental Biology/Developmental Molecular Mechanisms
                Genetics and Genomics/Gene Expression

                Genetics
                Genetics

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