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      DNA methylation at enhancers identifies distinct breast cancer lineages

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          Abstract

          Breast cancers exhibit genome-wide aberrant DNA methylation patterns. To investigate how these affect the transcriptome and which changes are linked to transformation or progression, we apply genome-wide expression–methylation quantitative trait loci (emQTL) analysis between DNA methylation and gene expression. On a whole genome scale, in cis and in trans, DNA methylation and gene expression have remarkably and reproducibly conserved patterns of association in three breast cancer cohorts ( n = 104, n = 253 and n = 277). The expression–methylation quantitative trait loci associations form two main clusters; one relates to tumor infiltrating immune cell signatures and the other to estrogen receptor signaling. In the estrogen related cluster, using ChromHMM segmentation and transcription factor chromatin immunoprecipitation sequencing data, we identify transcriptional networks regulated in a cell lineage-specific manner by DNA methylation at enhancers. These networks are strongly dominated by ERα, FOXA1 or GATA3 and their targets were functionally validated using knockdown by small interfering RNA or GRO-seq analysis after transcriptional stimulation with estrogen.

          Abstract

          Breast cancers are classified based on gene expression profiles but it is well known that DNA methylation patterns are also altered. Here the authors, by combining genome-wide DNA methylation and gene expression analysis, identify transcriptional networks regulated by DNA methylation at enhancers able to separate specific breast cancer subtypes.

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          Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

          Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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            Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities.

            Genome-scale studies have revealed extensive, cell type-specific colocalization of transcription factors, but the mechanisms underlying this phenomenon remain poorly understood. Here, we demonstrate in macrophages and B cells that collaborative interactions of the common factor PU.1 with small sets of macrophage- or B cell lineage-determining transcription factors establish cell-specific binding sites that are associated with the majority of promoter-distal H3K4me1-marked genomic regions. PU.1 binding initiates nucleosome remodeling, followed by H3K4 monomethylation at large numbers of genomic regions associated with both broadly and specifically expressed genes. These locations serve as beacons for additional factors, exemplified by liver X receptors, which drive both cell-specific gene expression and signal-dependent responses. Together with analyses of transcription factor binding and H3K4me1 patterns in other cell types, these studies suggest that simple combinations of lineage-determining transcription factors can specify the genomic sites ultimately responsible for both cell identity and cell type-specific responses to diverse signaling inputs. Copyright 2010 Elsevier Inc. All rights reserved.
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              Circos: an information aesthetic for comparative genomics.

              We created a visualization tool called Circos to facilitate the identification and analysis of similarities and differences arising from comparisons of genomes. Our tool is effective in displaying variation in genome structure and, generally, any other kind of positional relationships between genomic intervals. Such data are routinely produced by sequence alignments, hybridization arrays, genome mapping, and genotyping studies. Circos uses a circular ideogram layout to facilitate the display of relationships between pairs of positions by the use of ribbons, which encode the position, size, and orientation of related genomic elements. Circos is capable of displaying data as scatter, line, and histogram plots, heat maps, tiles, connectors, and text. Bitmap or vector images can be created from GFF-style data inputs and hierarchical configuration files, which can be easily generated by automated tools, making Circos suitable for rapid deployment in data analysis and reporting pipelines.
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                Author and article information

                Contributors
                Vessela.N.Kristensen@rr-research.no
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                9 November 2017
                9 November 2017
                2017
                : 8
                : 1379
                Affiliations
                [1 ]ISNI 0000 0004 0389 8485, GRID grid.55325.34, Department of Cancer Genetics, Institute for Cancer Research, , Oslo University Hospital, The Norwegian Radium Hospital, ; Oslo, Norway
                [4 ]ISNI 0000 0004 0389 8485, GRID grid.55325.34, Department of Pathology, , Oslo University Hospital, ; Oslo, Norway
                [6 ]ISNI 0000 0004 0389 8485, GRID grid.55325.34, Department of Oncology, , Oslo University Hospital, ; Oslo, Norway
                [11 ]ISNI 0000 0004 1936 8921, GRID grid.5510.1, Institute of Clinical Medicine, Faculty of Medicine, , University of Oslo, ; Oslo, Norway
                [12 ]ISNI 0000 0000 9637 455X, GRID grid.411279.8, Department of Pathology, Institute of Clinical Medicine, , Akershus University Hospital, ; Lørenskog, Norway
                [13 ]ISNI 0000 0000 9637 455X, GRID grid.411279.8, Department of Oncology, Institute for Clinical Medicine, , Akershus University Hospital, ; Lørenskog, Norway
                [14 ]ISNI 0000 0000 9637 455X, GRID grid.411279.8, Division of Medicine, , Akershus University Hospital, ; Lørenskog, Norway
                [15 ]ISNI 0000 0001 0727 140X, GRID grid.418941.1, Cancer Registry of Norway, ; Oslo, Norway
                [16 ]Oslo and Akershus University College of Applied Sciences, Faculty of Health Science, Oslo, Norway
                [17 ]ISNI 0000 0001 1516 2393, GRID grid.5947.f, Department of Circulation and Medical Imaging, , Norwegian University of Science and Technology (NTNU), ; Trondheim, Norway
                [18 ]ISNI 0000 0004 0389 8485, GRID grid.55325.34, Department of Tumor Biology, Institute for Cancer Research, , Oslo University Hospital, ; Oslo, Norway
                [19 ]ISNI 0000000122595234, GRID grid.10919.30, Department of Pharmacy, Faculty of Health Sciences, , University of Tromsø, ; Tromsø, Norway
                [20 ]ISNI 0000 0004 1936 8921, GRID grid.5510.1, Centre for Cancer Biomedicine, , University of Oslo, ; Oslo, Norway
                [21 ]ISNI 0000 0004 1936 8921, GRID grid.5510.1, Department of Computer Science, , University of Oslo, ; Oslo, Norway
                [22 ]ISNI 0000 0004 0389 7802, GRID grid.459157.b, Department of Breast and Endocrine Surgery, , Vestre Viken Hospital Trust, ; Drammen, Norway
                [23 ]ISNI 0000 0004 0389 7802, GRID grid.459157.b, Department of Pathology, , Vestre Viken Hospital Trust, ; Drammen, Norway
                [24 ]Østfold Hospital, Østfold, Norway
                [2 ]ISNI 0000 0000 9637 455X, GRID grid.411279.8, Department of Clinical Molecular Biology and Laboratory Science (EpiGen), , Akershus University hospital, Division of Medicine, ; Lørenskog, Norway
                [3 ]ISNI 0000 0004 1936 8921, GRID grid.5510.1, Centre for Molecular Medicine Norway (NCMM), , University of Oslo, ; Oslo, Norway
                [5 ]ISNI 0000 0004 0389 7802, GRID grid.459157.b, Department of Research, , Vestre Viken Hospital Trust, ; Drammen, Norway
                [7 ]ISNI 0000 0004 1936 8921, GRID grid.5510.1, Department of Biosciences, , University of Oslo, ; Oslo, Norway
                [8 ]ISNI 0000 0004 0389 8485, GRID grid.55325.34, Department of Immunology, , Norwegian Center for Stem Cell Research, Oslo University Hospital, ; Oslo, Norway
                [9 ]ISNI 0000 0004 0389 8485, GRID grid.55325.34, Department of Biostatistics, Oslo Centre for Biostatistics and Epidemiology, , University of Oslo and Research Support Services, Oslo University Hospital, ; Oslo, Norway
                [10 ]Laboratory for Epigenetics and Environment, Centre National de Génotypage, CEA–Institut de Génomique, Evry, France
                Author information
                http://orcid.org/0000-0001-5127-5459
                http://orcid.org/0000-0002-2683-0817
                Article
                510
                10.1038/s41467-017-00510-x
                5680222
                29123100
                fa42127b-8c2a-48b6-82bd-a7da022bb39d
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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                : 18 November 2016
                : 27 June 2017
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