Simple Combinations of Lineage-Determining Transcription Factors Prime cis-Regulatory Elements Required for Macrophage and B Cell Identities

doi:10.1016/J.MOLCEL.2010.05.004

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Simple Combinations of Lineage-Determining Transcription Factors Prime cis-Regulatory Elements Required for Macrophage and B Cell Identities

Journal Article•DOI•

Simple Combinations of Lineage-Determining Transcription Factors Prime cis-Regulatory Elements Required for Macrophage and B Cell Identities

Sven Heinz¹, Christopher Benner¹, Nathanael J. Spann¹, Eric Bertolino², Yin C. Lin¹, Peter Laslo³, Jason X. Cheng², Cornelis Murre¹, Harinder Singh⁴, Harinder Singh², Christopher K. Glass¹ - Show less +7 more•Institutions (4)

University of California, San Diego¹, University of Chicago², University of Leeds³, Genentech⁴

28 May 2010-Molecular Cell (NIH Public Access)-Vol. 38, Iss: 4, pp 576-589

TL;DR: It is demonstrated 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.

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About: This article is published in Molecular Cell.The article was published on 2010-05-28 and is currently open access. It has received 9620 citations till now. The article focuses on the topics: Pioneer factor & General transcription factor.

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Journal Article•DOI•

An atlas of active enhancers across human cell types and tissues

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Robin Andersson¹, Claudia Gebhard², Irene Miguel-Escalada³, Ilka Hoof¹, Jette Bornholdt¹, Mette Boyd¹, Yun Chen¹, Xiaobei Zhao⁴, Xiaobei Zhao¹, Christian Schmidl², Takahiro Suzuki, Evgenia Ntini, Erik Arner, Eivind Valen⁵, Eivind Valen¹, Kang Li¹, Lucia Schwarzfischer², Dagmar Glatz², Johanna Raithel², Berit Lilje¹, Nicolas Rapin¹, Frederik Otzen Bagger¹, Mette Rose Jørgensen¹, Peter Refsing Andersen⁶, Nicolas Bertin, Owen J. L. Rackham, A. Maxwell Burroughs, J Kenneth Baillie⁷, Yuri Ishizu, Yuri Shimizu, Erina Furuhata, Shiori Maeda, Yutaka Negishi, Christopher J. Mungall⁸, Terrence F. Meehan⁹, Timo Lassmann, Masayoshi Itoh, Hideya Kawaji, Naoto Kondo, Jun Kawai, Andreas Lennartsson¹⁰, Carsten O. Daub¹⁰, Peter Heutink¹¹, David A. Hume⁷, Torben Heick Jensen⁶, Harukazu Suzuki, Yoshihide Hayashizaki, Ferenc Müller³, Alistair R. R. Forrest, Piero Carninci, Michael Rehli², Albin Sandelin¹ - Show less +48 more•Institutions (11)

University of Copenhagen¹, University Hospital Regensburg², University of Birmingham³, University of North Carolina at Chapel Hill⁴, Harvard University⁵, Aarhus University⁶, University of Edinburgh⁷, Lawrence Berkeley National Laboratory⁸, European Bioinformatics Institute⁹, Karolinska Institutet¹⁰, VU University Medical Center¹¹

27 Mar 2014-Nature

TL;DR: It is shown that enhancers share properties with CpG-poor messenger RNA promoters but produce bidirectional, exosome-sensitive, relatively short unspliced RNAs, the generation of which is strongly related to enhancer activity.

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Abstract: Enhancers control the correct temporal and cell-type-specific activation of gene expression in multicellular eukaryotes. Knowing their properties, regulatory activity and targets is crucial to understand the regulation of differentiation and homeostasis. Here we use the FANTOM5 panel of samples, covering the majority of human tissues and cell types, to produce an atlas of active, in vivo-transcribed enhancers. We show that enhancers share properties with CpG-poor messenger RNA promoters but produce bidirectional, exosome-sensitive, relatively short unspliced RNAs, the generation of which is strongly related to enhancer activity. The atlas is used to compare regulatory programs between different cells at unprecedented depth, to identify disease-associated regulatory single nucleotide polymorphisms, and to classify cell-type-specific and ubiquitous enhancers. We further explore the utility of enhancer redundancy, which explains gene expression strength rather than expression patterns. The online FANTOM5 enhancer atlas represents a unique resource for studies on cell-type-specific enhancers and gene regulation.

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2,260 citations

Cites methods from "Simple Combinations of Lineage-Dete..."

...These were grouped according to Hela-S3 expression tertiles: low (36), mid-level (41) and strong (46)....
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Journal Article•DOI•

N6-methyladenosine Modulates Messenger RNA Translation Efficiency

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Xiao Wang¹, Xiao Wang², Boxuan Simen Zhao¹, Boxuan Simen Zhao², Ian A Roundtree², Ian A Roundtree¹, Zhike Lu², Zhike Lu¹, Dali Han², Dali Han¹, Honghui Ma², Honghui Ma¹, Xiaocheng Weng¹, Xiaocheng Weng², Kai Chen², Kai Chen¹, Hailing Shi², Hailing Shi¹, Chuan He¹, Chuan He² - Show less +16 more•Institutions (2)

University of Chicago¹, Howard Hughes Medical Institute²

04 Jun 2015-Cell

TL;DR: In a unified mechanism of m(6)A-based regulation in the cytoplasm, YTHDF2-mediated degradation controls the lifetime of target transcripts, whereasYTHDF1-mediated translation promotion increases translation efficiency, ensuring effective protein production from dynamic transcripts that are marked by m( 6)A.

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2,179 citations

Master Transcription Factors and Mediator Establish Super-Enhancers at Key Cell Identity Genes

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Warren A. Whyte¹, David A. Orlando¹, Denes Hnisz¹, Brian J. Abraham¹, Charles Y. Lin², Charles Y. Lin¹, Michael H. Kagey¹, Peter B. Rahl¹, Tong Ihn Lee¹, Richard A. Young¹ - Show less +6 more•Institutions (2)

Massachusetts Institute of Technology¹, Harvard University²

01 Apr 2013

TL;DR: It is reported here that the ESC master transcription factors form unusual enhancer domains at most genes that control the pluripotent state, which consist of clusters of enhancers that are densely occupied by the master regulators and Mediator.

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Abstract: Master transcription factors Oct4, Sox2, and Nanog bind enhancer elements and recruit Mediator to activate much of the gene expression program of pluripotent embryonic stem cells (ESCs). We report here that the ESC master transcription factors form unusual enhancer domains at most genes that control the pluripotent state. These domains, which we call super-enhancers, consist of clusters of enhancers that are densely occupied by the master regulators and Mediator. Super-enhancers differ from typical enhancers in size, transcription factor density and content, ability to activate transcription, and sensitivity to perturbation. Reduced levels of Oct4 or Mediator cause preferential loss of expression of super-enhancer-associated genes relative to other genes, suggesting how changes in gene expression programs might be accomplished during development. In other more differentiated cells, super-enhancers containing cell-type-specific master transcription factors are also found at genes that define cell identity. Super-enhancers thus play key roles in the control of mammalian cell identity.

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2,075 citations

Posted Content•DOI•

Comprehensive integration of single cell data

[...]

Tim Stuart, Andrew Butler¹, Paul J. Hoffman, Christoph Hafemeister, Efthymia Papalexi¹, William M. Mauck¹, Marlon Stoeckius², Peter Smibert², Rahul Satija¹ - Show less +5 more•Institutions (2)

New York University¹, Harvard University²

02 Nov 2018-bioRxiv

TL;DR: This work presents a strategy for comprehensive integration of single cell data, including the assembly of harmonized references, and the transfer of information across datasets, and demonstrates how anchoring can harmonize in-situ gene expression and scRNA-seq datasets.

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Abstract: Single cell transcriptomics (scRNA-seq) has transformed our ability to discover and annotate cell types and states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, including high-dimensional immunophenotypes, chromatin accessibility, and spatial positioning, a key analytical challenge is to integrate these datasets into a harmonized atlas that can be used to better understand cellular identity and function. Here, we develop a computational strategy to "anchor" diverse datasets together, enabling us to integrate and compare single cell measurements not only across scRNA-seq technologies, but different modalities as well. After demonstrating substantial improvement over existing methods for data integration, we anchor scRNA-seq experiments with scATAC-seq datasets to explore chromatin differences in closely related interneuron subsets, and project single cell protein measurements onto a human bone marrow atlas to annotate and characterize lymphocyte populations. Lastly, we demonstrate how anchoring can harmonize in-situ gene expression and scRNA-seq datasets, allowing for the transcriptome-wide imputation of spatial gene expression patterns, and the identification of spatial relationships between mapped cell types in the visual cortex. Our work presents a strategy for comprehensive integration of single cell data, including the assembly of harmonized references, and the transfer of information across datasets. Availability: Installation instructions, documentation, and tutorials are available at: https://www.satijalab.org/seurat

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2,037 citations

Cites methods from "Simple Combinations of Lineage-Dete..."

...We searched for overrepresented DNA sequence motifs in accessible regions using the Homer package [Heinz et al., 2010], using the findMotifsGenome....
[...]

Journal Article•DOI•

ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia

[...]

Stephen G. Landt¹, Georgi K. Marinov², Anshul Kundaje¹, Pouya Kheradpour³, Florencia Pauli, Serafim Batzoglou¹, Bradley E. Bernstein⁴, Peter J. Bickel⁵, James B. Brown⁵, Philip Cayting¹, Yiwen Chen⁶, Gilberto DeSalvo², Charles B. Epstein⁴, Katherine I. Fisher-Aylor², Ghia Euskirchen¹, Mark Gerstein⁷, Jason Gertz, Alexander J. Hartemink⁸, Michael M. Hoffman⁹, Vishwanath R. Iyer¹⁰, Youngsook L. Jung⁶, Subhradip Karmakar¹¹, Manolis Kellis³, Peter V. Kharchenko¹⁰, Qiang Li¹², Tao Liu⁶, X. Shirley Liu⁶, Lijia Ma¹¹, Aleksandar Milosavljevic¹³, Richard M. Myers, Peter J. Park⁶, Michael J. Pazin¹⁴, Marc D. Perry¹⁵, Debasish Raha⁷, Timothy E. Reddy⁸, Joel Rozowsky⁷, Noam Shoresh⁴, Arend Sidow¹, Matthew Slattery¹¹, John A. Stamatoyannopoulos⁹, Michael Y. Tolstorukov⁶, Kevin P. White¹¹, Simon Xi¹⁶, Peggy J. Farnham¹⁷, Jason D. Lieb¹⁸, Barbara J. Wold², Michael Snyder¹ - Show less +43 more•Institutions (18)

Stanford University¹, California Institute of Technology², Massachusetts Institute of Technology³, Broad Institute⁴, University of California, Berkeley⁵, Harvard University⁶, Yale University⁷, Duke University⁸, University of Washington⁹, University of Texas at Austin¹⁰, University of Chicago¹¹, Pennsylvania State University¹², Baylor College of Medicine¹³, National Institutes of Health¹⁴, Ontario Institute for Cancer Research¹⁵, University of Massachusetts Medical School¹⁶, University of Southern California¹⁷, University of North Carolina at Chapel Hill¹⁸

01 Sep 2012-Genome Research

TL;DR: This work discusses how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data and develops a set of working standards and guidelines for ChIP experiments that are updated routinely.

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Abstract: Chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) has become a valuable and widely used approach for mapping the genomic location of transcription-factor binding and histone modifications in living cells. Despite its widespread use, there are considerable differences in how these experiments are conducted, how the results are scored and evaluated for quality, and how the data and metadata are archived for public use. These practices affect the quality and utility of any global ChIP experiment. Through our experience in performing ChIP-seq experiments, the ENCODE and modENCODE consortia have developed a set of working standards and guidelines for ChIP experiments that are updated routinely. The current guidelines address antibody validation, experimental replication, sequencing depth, data and metadata reporting, and data quality assessment. We discuss how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data. All data sets used in the analysis have been deposited for public viewing and downloading at the ENCODE (http://encodeproject.org/ENCODE/) and modENCODE (http://www.modencode.org/) portals.

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1,801 citations

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References

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Journal Article•DOI•

High-resolution profiling of histone methylations in the human genome.

[...]

Artem Barski¹, Suresh Cuddapah¹, Kairong Cui¹, Tae-Young Roh¹, Dustin E. Schones¹, Zhibin Wang¹, Gang Wei¹, Iouri Chepelev², Keji Zhao¹ - Show less +5 more•Institutions (2)

National Institutes of Health¹, University of California, Los Angeles²

18 May 2007-Cell

TL;DR: High-resolution maps for the genome-wide distribution of 20 histone lysine and arginine methylations as well as histone variant H2A.Z, RNA polymerase II, and the insulator binding protein CTCF across the human genome using the Solexa 1G sequencing technology are generated.

...read moreread less

6,488 citations

"Simple Combinations of Lineage-Dete..." refers background or methods in this paper

...…positions, DNase hypersensitivity, and mononucleosomal ChIP-Seq for a wide range of histone modifications are available, allowing precise determination of nucleosome positions, chromatin accessibility, and histone modifications (Barski et al., 2007; Boyle et al., 2008; Schones et al., 2008)....
[...]
...In this cell type, genome-wide data for nucleosome positions, DNase hypersensitivity, and mononucleosomal ChIP-Seq for a wide range of histone modifications are available, allowing precise determination of nucleosome positions, chromatin accessibility, and histone modifications (Barski et al., 2007; Boyle et al., 2008; Schones et al., 2008)....
[...]
...1 Binding Programs in Macrophages and B Cells We initially performed chromatin immunoprecipitation-coupled deep sequencing (ChIP-Seq) (Barski et al., 2007) to define the PU....
[...]
..., 2008), human CD4 T cells (Barski et al., 2007), and CD36 erythrocyte precursors (Cui et al....
[...]
...…other cell types, we performed de novo motif analysis on H3K4me1/H3K4me3 ChIP-Seq data sets from mouse embryonic stem cells (Meissner et al., 2008; Mikkelsen et al., 2007), liver (Wederell et al., 2008), human CD4+ T cells (Barski et al., 2007), and CD36+ erythrocyte precursors (Cui et al., 2009)....
[...]

Journal Article•DOI•

Genome-wide maps of chromatin state in pluripotent and lineage-committed cells

[...]

Tarjei S. Mikkelsen¹, Manching Ku¹, Manching Ku², David B. Jaffe¹, Biju Issac¹, Biju Issac², Erez Lieberman Aiden¹, Erez Lieberman Aiden³, Georgia Giannoukos¹, Pablo Alvarez¹, William Brockman¹, Tae Kyung Kim⁴, Richard Koche², Richard Koche¹, Richard Koche³, William Lee¹, Eric M. Mendenhall¹, Eric M. Mendenhall², Aisling O'Donovan², Aviva Presser¹, Carsten Russ¹, Xiaohui Xie¹, Alexander Meissner³, Marius Wernig³, Rudolf Jaenisch³, Chad Nusbaum¹, Eric S. Lander¹, Eric S. Lander³, Bradley E. Bernstein¹, Bradley E. Bernstein² - Show less +26 more•Institutions (4)

Broad Institute¹, Harvard University², Massachusetts Institute of Technology³, Boston Children's Hospital⁴

02 Aug 2007-Nature

TL;DR: The application of single-molecule-based sequencing technology for high-throughput profiling of histone modifications in mammalian cells is reported and it is shown that chromatin state can be read in an allele-specific manner by using single nucleotide polymorphisms.

...read moreread less

Abstract: We report the application of single-molecule-based sequencing technology for high-throughput profiling of histone modifications in mammalian cells By obtaining over four billion bases of sequence from chromatin immunoprecipitated DNA, we generated genome-wide chromatin-state maps of mouse embryonic stem cells, neural progenitor cells and embryonic fibroblasts We find that lysine 4 and lysine 27 trimethylation effectively discriminates genes that are expressed, poised for expression, or stably repressed, and therefore reflect cell state and lineage potential Lysine 36 trimethylation marks primary coding and non-coding transcripts, facilitating gene annotation Trimethylation of lysine 9 and lysine 20 is detected at satellite, telomeric and active long-terminal repeats, and can spread into proximal unique sequences Lysine 4 and lysine 9 trimethylation marks imprinting control regions Finally, we show that chromatin state can be read in an allele-specific manner by using single nucleotide polymorphisms This study provides a framework for the application of comprehensive chromatin profiling towards characterization of diverse mammalian cell populations

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4,166 citations

"Simple Combinations of Lineage-Dete..." refers methods in this paper

...To determine whether there is an analogous relationship between promoter-distal H3K4me1 and binding sites for transcription factors in other cell types, we performed de novo motif analysis on H3K4me1/H3K4me3 ChIP-Seq data sets from mouse embryonic stem cells (Meissner et al., 2008; Mikkelsen et al., 2007), liver (Wederell et al....
[...]
...…other cell types, we performed de novo motif analysis on H3K4me1/H3K4me3 ChIP-Seq data sets from mouse embryonic stem cells (Meissner et al., 2008; Mikkelsen et al., 2007), liver (Wederell et al., 2008), human CD4+ T cells (Barski et al., 2007), and CD36+ erythrocyte precursors (Cui et al., 2009)....
[...]

Journal Article•DOI•

RAG-1-deficient mice have no mature B and T lymphocytes

[...]

Peter Mombaerts¹, John Iacomini¹, Randall S. Johnson², Karl Herrup, Susumu Tonegawa¹, Virginia E. Papaioannou³ - Show less +2 more•Institutions (3)

Massachusetts Institute of Technology¹, Harvard University², Tufts University³

06 Mar 1992-Cell

TL;DR: The introduction of a mutation in RAG-1 into the germline of mice via gene targeting in embryonic stem cells is described and it is shown that this mutation either activates or catalyzes the V(D)J recombination reaction of immunoglobulin and T cell receptor genes.

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2,821 citations

"Simple Combinations of Lineage-Dete..." refers background in this paper

...…in B lineage progenitors devoid of both E2A and EBF (E2A / ), EBF only (EBF / ), or control cells that express both factors (Rag1 / ), which are arrested at successive stages in B cell development (Dias et al., 2008; Ikawa et al., 2004; Lin and Grosschedl, 1995; Mombaerts et al., 1992) (Figure 1A)....
[...]
...We addressed this question in B lineage progenitors devoid of both E2A and EBF (E2A / ), EBF only (EBF / ), or control cells that express both factors (Rag1 / ), which are arrested at successive stages in B cell development (Dias et al., 2008; Ikawa et al., 2004; Lin and Grosschedl, 1995; Mombaerts et al., 1992) (Figure 1A)....
[...]

Journal Article•DOI•

Integration of External Signaling Pathways with the Core Transcriptional Network in Embryonic Stem Cells

[...]

Xi Chen¹, Han Xu¹, Ping Yuan¹, Fang Fang¹, Fang Fang², Mikael Huss¹, Vinsensius B. Vega¹, Eleanor Wong¹, Yuriy L. Orlov¹, Weiwei Zhang², Weiwei Zhang¹, Jianming Jiang², Jianming Jiang¹, Yuin-Han Loh¹, Yuin-Han Loh², Hock Chuan Yeo¹, Zhen Xuan Yeo¹, Vipin Narang¹, Kunde R Govindarajan¹, Bernard Leong¹, Atif Shahab¹, Yijun Ruan¹, Guillaume Bourque¹, Wing-Kin Sung¹, Neil D. Clarke¹, Chia-Lin Wei¹, Huck-Hui Ng², Huck-Hui Ng¹ - Show less +24 more•Institutions (2)

Genome Institute of Singapore¹, National University of Singapore²

13 Jun 2008-Cell

TL;DR: This study uses chromatin immunoprecipitation coupled with ultra-high-throughput DNA sequencing to map the locations of TF-binding sites and identifies important features of the transcriptional regulatory networks that define ES-cell identity.

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2,519 citations

"Simple Combinations of Lineage-Dete..." refers background in this paper

...This model offers an explanation for the extensive genome-wide and cell typespecific colocalization of transcription factors observed in various previous studies (Chen et al., 2008; MacArthur et al., 2009) and provides insights into how simple combinations of lineage-restricted transcription factors on a genome-wide scale can specify promoter-distal cis-regulatory elements ultimately responsible for both cell identity and cell type-specific responses to diverse signaling inputs....
[...]
...…an explanation for the extensive genome-wide and cell typespecific colocalization of transcription factors observed in various previous studies (Chen et al., 2008; MacArthur et al., 2009) and provides insights into how simple combinations of lineage-restricted transcription factors on a…...
[...]
...Comparisons of the genome-wide binding patterns of different transcription factors in a variety of species and cell types have generated two major insights regarding transcription factor binding patterns: (1) different factors in the same cell type tend to colocalize on a genome-wide scale (Chen et al., 2008; MacArthur et al., 2009), and (2) the same factor in different cell types or at different stages of development exhibits different genome-wide binding patterns (Lupien et al....
[...]
...…insights regarding transcription factor binding patterns: (1) different factors in the same cell type tend to colocalize on a genome-wide scale (Chen et al., 2008; MacArthur et al., 2009), and (2) the same factor in different cell types or at different stages of development exhibits different…...
[...]

Journal Article•DOI•

Genome-scale DNA methylation maps of pluripotent and differentiated cells

[...]

Alexander Meissner¹, Tarjei S. Mikkelsen², Tarjei S. Mikkelsen¹, Hongcang Gu², Marius Wernig¹, Jacob H. Hanna¹, Andrey Sivachenko², Xiaolan Zhang², Bradley E. Bernstein³, Bradley E. Bernstein², Chad Nusbaum², David B. Jaffe², Andreas Gnirke², Rudolf Jaenisch¹, Eric S. Lander - Show less +11 more•Institutions (3)

Massachusetts Institute of Technology¹, Broad Institute², Harvard University³

07 Aug 2008-Nature

TL;DR: Low-throughput reduced representation bisulphite sequencing is established as a powerful technology for epigenetic profiling of cell populations relevant to developmental biology, cancer and regenerative medicine.

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Abstract: DNA methylation is essential for normal development and has been implicated in many pathologies including cancer. Our knowledge about the genome-wide distribution of DNA methylation, how it changes during cellular differentiation and how it relates to histone methylation and other chromatin modifications in mammals remains limited. Here we report the generation and analysis of genome-scale DNA methylation profiles at nucleotide resolution in mammalian cells. Using high-throughput reduced representation bisulphite sequencing and single-molecule-based sequencing, we generated DNA methylation maps covering most CpG islands, and a representative sampling of conserved non-coding elements, transposons and other genomic features, for mouse embryonic stem cells, embryonic-stem-cell-derived and primary neural cells, and eight other primary tissues. Several key findings emerge from the data. First, DNA methylation patterns are better correlated with histone methylation patterns than with the underlying genome sequence context. Second, methylation of CpGs are dynamic epigenetic marks that undergo extensive changes during cellular differentiation, particularly in regulatory regions outside of core promoters. Third, analysis of embryonic-stem-cell-derived and primary cells reveals that 'weak' CpG islands associated with a specific set of developmentally regulated genes undergo aberrant hypermethylation during extended proliferation in vitro, in a pattern reminiscent of that reported in some primary tumours. More generally, the results establish reduced representation bisulphite sequencing as a powerful technology for epigenetic profiling of cell populations relevant to developmental biology, cancer and regenerative medicine.

...read moreread less

2,482 citations

"Simple Combinations of Lineage-Dete..." refers methods in this paper

...To determine whether there is an analogous relationship between promoter-distal H3K4me1 and binding sites for transcription factors in other cell types, we performed de novo motif analysis on H3K4me1/H3K4me3 ChIP-Seq data sets from mouse embryonic stem cells (Meissner et al., 2008; Mikkelsen et al., 2007), liver (Wederell et al....
[...]
...…factors in other cell types, we performed de novo motif analysis on H3K4me1/H3K4me3 ChIP-Seq data sets from mouse embryonic stem cells (Meissner et al., 2008; Mikkelsen et al., 2007), liver (Wederell et al., 2008), human CD4+ T cells (Barski et al., 2007), and CD36+ erythrocyte…...
[...]