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      Genome-wide analysis of ETS-family DNA-binding in vitro and in vivo

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          Abstract

          Members of the large ETS family of transcription factors (TFs) have highly similar DNA-binding domains (DBDs)—yet they have diverse functions and activities in physiology and oncogenesis. Some differences in DNA-binding preferences within this family have been described, but they have not been analysed systematically, and their contributions to targeting remain largely uncharacterized. We report here the DNA-binding profiles for all human and mouse ETS factors, which we generated using two different methods: a high-throughput microwell-based TF DNA-binding specificity assay, and protein-binding microarrays (PBMs). Both approaches reveal that the ETS-binding profiles cluster into four distinct classes, and that all ETS factors linked to cancer, ERG, ETV1, ETV4 and FLI1, fall into just one of these classes. We identify amino-acid residues that are critical for the differences in specificity between all the classes, and confirm the specificities in vivo using chromatin immunoprecipitation followed by sequencing (ChIP-seq) for a member of each class. The results indicate that even relatively small differences in in vitro binding specificity of a TF contribute to site selectivity in vivo.

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          An algorithm for progressive multiple alignment of sequences with insertions.

          Dynamic programming algorithms guarantee to find the optimal alignment between two sequences. For more than a few sequences, exact algorithms become computationally impractical, and progressive algorithms iterating pairwise alignments are widely used. These heuristic methods have a serious drawback because pairwise algorithms do not differentiate insertions from deletions and end up penalizing single insertion events multiple times. Such an unrealistically high penalty for insertions typically results in overmatching of sequences and an underestimation of the number of insertion events. We describe a modification of the traditional alignment algorithm that can distinguish insertion from deletion and avoid repeated penalization of insertions and illustrate this method with a pair hidden Markov model that uses an evolutionary scoring function. In comparison with a traditional progressive alignment method, our algorithm infers a greater number of insertion events and creates gaps that are phylogenetically consistent but spatially less concentrated. Our results suggest that some insertion/deletion "hot spots" may actually be artifacts of traditional alignment algorithms.
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            Gene fusion with an ETS DNA-binding domain caused by chromosome translocation in human tumours.

            Ewing's sarcoma and related subtypes of primitive neuroectodermal tumours share a recurrent and specific t(11;22) (q24;q12) chromosome translocation, the breakpoints of which have recently been cloned. Phylogenetically conserved restriction fragments in the vicinity of EWSR1 and EWSR2, the genomic regions where the breakpoints of chromosome 22 and chromosome 11 are, respectively, have allowed identification of transcribed sequences from these regions and has indicated that a hybrid transcript might be generated by the translocation. Here we use these fragments to screen human complementary DNA libraries to show that the translocation alters the open reading frame of an expressed gene on chromosome 22 gene by substituting a sequence encoding a putative RNA-binding domain for that of the DNA-binding domain of the human homologue of murine Fli-1.
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              An atlas of combinatorial transcriptional regulation in mouse and man.

              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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                Author and article information

                Journal
                EMBO J
                The EMBO Journal
                Nature Publishing Group
                0261-4189
                1460-2075
                07 July 2010
                01 June 2010
                01 June 2010
                : 29
                : 13
                : 2147-2160
                Affiliations
                [1 ]simplePublic Health Genomics Unit, National Institute for Health and Welfare (THL) and Genome-Scale Biology Program, Institute of Biomedicine and High Throughput Center, University of Helsinki , Biomedicum, Helsinki, Finland
                [2 ]simpleDepartment of Molecular Genetics and Banting and Best Department of Medical Research, University of Toronto , Toronto, Ontario, Canada
                [3 ]simpleDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School , Boston, MA, USA
                [4 ]simpleDepartment of Pathology, Brigham and Women's Hospital and Harvard Medical School , Boston, MA, USA
                [5 ]simpleCommittee on Higher Degrees in Biophysics, Harvard University , Cambridge, MA, USA
                [6 ]simpleHarvard-MIT Division of Health Sciences and Technology (HST), Harvard Medical School , Boston, MA, USA
                [7 ]simpleDepartment of Computer Science, University of Helsinki , Helsinki, Finland
                [8 ]simpleDepartment of Biosciences and Medical Nutrition, Karolinska Institutet , Sweden
                [9 ]simpleDepartment of Molecular Biology, Radboud University Nijmegen , Nijmegen, The Netherlands
                Author notes
                [a ]Department of Biosciences and Medical Nutrition, Karolinska Institutet, Sweden. Tel.: +46 858 583 833; E-mail: jussi.taipale@ 123456ki.se
                Article
                emboj2010106
                10.1038/emboj.2010.106
                2905244
                20517297
                9f245677-d820-4edb-bde5-2839816c4baf
                Copyright © 2010, European Molecular Biology Organization

                This is an open-access article distributed under the terms of the Creative Commons Attribution Noncommercial Share Alike 3.0 Unported License, which allows readers to alter, transform, or build upon the article and then distribute the resulting work under the same or similar license to this one. The work must be attributed back to the original author and commercial use is not permitted without specific permission.

                History
                : 09 December 2009
                : 04 May 2010
                Categories
                Article

                Molecular biology
                transcription factor-dna binding assay,dna-binding specificity,cancer,ets family of transcription factors,chip-seq

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