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      Positional specificity of different transcription factor classes within enhancers

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          Significance

          Gene expression is controlled by sequence-specific transcription factors (TFs), which bind to regulatory sequences in DNA. The degree to which the arrangement of motif sites within regulatory elements determines their function remains unclear. Here, we show that the positional distribution of TF motif sites within nucleosome-depleted regions of DNA fall into six distinct classes. These patterns are highly consistent across cell types and bring together factors that have similar functional and binding properties. Furthermore, the position of motif sites appears to be related to their known functions. Our results suggest that TFs play distinct roles in forming a functional enhancer, facilitated by their position within a regulatory sequence.

          Abstract

          Gene expression is controlled by sequence-specific transcription factors (TFs), which bind to regulatory sequences in DNA. TF binding occurs in nucleosome-depleted regions of DNA (NDRs), which generally encompass regions with lengths similar to those protected by nucleosomes. However, less is known about where within these regions specific TFs tend to be found. Here, we characterize the positional bias of inferred binding sites for 103 TFs within ∼500,000 NDRs across 47 cell types. We find that distinct classes of TFs display different binding preferences: Some tend to have binding sites toward the edges, some toward the center, and some at other positions within the NDR. These patterns are highly consistent across cell types, suggesting that they may reflect TF-specific intrinsic structural or functional characteristics. In particular, TF classes with binding sites at NDR edges are enriched for those known to interact with histones and chromatin remodelers, whereas TFs with central enrichment interact with other TFs and cofactors such as p300. Our results suggest distinct regiospecific binding patterns and functions of TF classes within enhancers.

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          Most cited references70

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          The BioGRID interaction database: 2017 update

          The Biological General Repository for Interaction Datasets (BioGRID: https://thebiogrid.org) is an open access database dedicated to the annotation and archival of protein, genetic and chemical interactions for all major model organism species and humans. As of September 2016 (build 3.4.140), the BioGRID contains 1 072 173 genetic and protein interactions, and 38 559 post-translational modifications, as manually annotated from 48 114 publications. This dataset represents interaction records for 66 model organisms and represents a 30% increase compared to the previous 2015 BioGRID update. BioGRID curates the biomedical literature for major model organism species, including humans, with a recent emphasis on central biological processes and specific human diseases. To facilitate network-based approaches to drug discovery, BioGRID now incorporates 27 501 chemical–protein interactions for human drug targets, as drawn from the DrugBank database. A new dynamic interaction network viewer allows the easy navigation and filtering of all genetic and protein interaction data, as well as for bioactive compounds and their established targets. BioGRID data are directly downloadable without restriction in a variety of standardized formats and are freely distributed through partner model organism databases and meta-databases.
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            The Xist lncRNA exploits three-dimensional genome architecture to spread across the X chromosome.

            Many large noncoding RNAs (lncRNAs) regulate chromatin, but the mechanisms by which they localize to genomic targets remain unexplored. We investigated the localization mechanisms of the Xist lncRNA during X-chromosome inactivation (XCI), a paradigm of lncRNA-mediated chromatin regulation. During the maintenance of XCI, Xist binds broadly across the X chromosome. During initiation of XCI, Xist initially transfers to distal regions across the X chromosome that are not defined by specific sequences. Instead, Xist identifies these regions by exploiting the three-dimensional conformation of the X chromosome. Xist requires its silencing domain to spread across actively transcribed regions and thereby access the entire chromosome. These findings suggest a model in which Xist coats the X chromosome by searching in three dimensions, modifying chromosome structure, and spreading to newly accessible locations.
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              Opening of compacted chromatin by early developmental transcription factors HNF3 (FoxA) and GATA-4.

              The transcription factors HNF3 (FoxA) and GATA-4 are the earliest known to bind the albumin gene enhancer in liver precursor cells in embryos. To understand how they access sites in silent chromatin, we assembled nucleosome arrays containing albumin enhancer sequences and compacted them with linker histone. HNF3 and GATA-4, but not NF-1, C/EBP, and GAL4-AH, bound their sites in compacted chromatin and opened the local nucleosomal domain in the absence of ATP-dependent enzymes. The ability of HNF3 to open chromatin is mediated by a high affinity DNA binding site and by the C-terminal domain of the protein, which binds histones H3 and H4. Thus, factors that potentiate transcription in development are inherently capable of initiating chromatin opening events.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                24 July 2018
                9 July 2018
                9 July 2018
                : 115
                : 30
                : E7222-E7230
                Affiliations
                [1] aBroad Institute of MIT and Harvard , Cambridge, MA 02142;
                [2] bDepartment of Biology, Massachusetts Institute of Technology , Cambridge, MA 02139;
                [3] cProgram in Health Sciences and Technology, Harvard Medical School , Boston, MA 02215;
                [4] dCancer Research, Massachusetts General Hospital , Boston, MA 02114;
                [5] eDepartment of Systems Biology, Harvard Medical School , Boston, MA 02215
                Author notes
                1To whom correspondence should be addressed. Email: lander@ 123456broadinstitute.org .

                Contributed by Eric S. Lander, June 19, 2018 (sent for review March 26, 2018; reviewed by Gioacchino Natoli and Alexander Stark)

                Author contributions: S.R.G. and E.S.L. designed research; S.R.G., J.P.R., and T.H.N. performed research; J.P.R. and N.H. contributed new reagents/analytic tools; S.R.G., J.E., and E.S.L. analyzed data; and S.R.G. and E.S.L. wrote the paper.

                Reviewers: G.N., Humanitas University; and A.S., Research Institute of Molecular Pathology.

                Author information
                http://orcid.org/0000-0001-6422-1134
                http://orcid.org/0000-0002-2349-2656
                Article
                201804663
                10.1073/pnas.1804663115
                6065035
                29987030
                7d5be890-f4cf-4c15-b68d-3f816c9b9b95
                Copyright © 2018 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                Page count
                Pages: 9
                Funding
                Funded by: HHS | NIH | National Human Genome Research Institute (NHGRI) 100000051
                Award ID: 2U54HG003067-10
                Award Recipient : Eric S. Lander
                Funded by: HHS | NIH | National Institute of General Medical Sciences (NIGMS) 100000057
                Award ID: T32GM007753
                Award Recipient : Eric S. Lander
                Categories
                PNAS Plus
                Biological Sciences
                Systems Biology
                PNAS Plus

                transcription factor binding,gene regulation,genomics,chromatin structure

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