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Journal ArticleDOI

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

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.
Abstract: 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.
Citations
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Journal ArticleDOI
13 Jun 2019-Cell
TL;DR: A strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities.
Abstract: Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.

7,892 citations


Cites background or 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....

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  • ...10 Heinz et al., 2010 http://homer.ucsd.edu/homer/ R R Core https://www.r-project.org/ Python Python Software Foundation https://www.python.org/...

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  • ...We searched for overrepresented DNA sequence motifs in accessible regions using the Homer package [Heinz et al., 2010], using the findMotifsGenome.pl program with default parameters, and the mm9 genome....

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Journal ArticleDOI
TL;DR: An update to the Galaxy-based web server deepTools, which allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches, is presented.
Abstract: We present an update to our Galaxy-based web server for processing and visualizing deeply sequenced data. Its core tool set, deepTools, allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches. Since we first described our deepTools Galaxy server in 2014, we have implemented new solutions for many requests from the community and our users. Here, we introduce significant enhancements and new tools to further improve data visualization and interpretation. deepTools continue to be open to all users and freely available as a web service at deeptools.ie-freiburg.mpg.de The new deepTools2 suite can be easily deployed within any Galaxy framework via the toolshed repository, and we also provide source code for command line usage under Linux and Mac OS X. A public and documented API for access to deepTools functionality is also available.

4,359 citations


Additional excerpts

  • ...The rapidly increasing diversity of experimental assays using high-throughput sequencing has led to a concomitant increase in the number of analysis packages that allow for insightful visualization and downstream analyses (e.g. ChAsE (1), the ChIP-seq web server (http://ccg. vital-it.ch/chipseq), Genomation (2), Homer (3), ngs.plot (4))....

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  • ...ch/chipseq), Genomation (2), Homer (3), ngs....

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Journal ArticleDOI
TL;DR: The epigenetic landscape of enhancer elements in embryonic stem cells and several adult tissues in the mouse is interrogated and it is found that histone H3K27ac distinguishes active enhancers from inactive/poised enhancers and poised enhancer networks provide clues to unrealized developmental programs.
Abstract: Developmental programs are controlled by transcription factors and chromatin regulators, which maintain specific gene expression programs through epigenetic modification of the genome. These regulatory events at enhancers contribute to the specific gene expression programs that determine cell state and the potential for differentiation into new cell types. Although enhancer elements are known to be associated with certain histone modifications and transcription factors, the relationship of these modifications to gene expression and developmental state has not been clearly defined. Here we interrogate the epigenetic landscape of enhancer elements in embryonic stem cells and several adult tissues in the mouse. We find that histone H3K27ac distinguishes active enhancers from inactive/poised enhancer elements containing H3K4me1 alone. This indicates that the amount of actively used enhancers is lower than previously anticipated. Furthermore, poised enhancer networks provide clues to unrealized developmental programs. Finally, we show that enhancers are reset during nuclear reprogramming.

3,541 citations


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

  • ...Examination of ChIP-Seq data (7, 24) confirmed that both Foxa2 and PU....

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Journal ArticleDOI
11 Apr 2013-Cell
TL;DR: In this article, the ESC master transcription factors form unusual enhancer domains at most genes that control the pluripotent state, called super-enhancers, which consist of clusters of enhancers that are densely occupied by the master regulators and Mediator.
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.

2,978 citations

Journal ArticleDOI
TL;DR: Cellular and molecular mechanisms in the differentiation and function of regulatory T cells and their role in autoimmune and autoinflammatory disorders, allergy, acute and chronic infections, cancer, and metabolic inflammation are discussed.
Abstract: The immune system has evolved to mount an effective defense against pathogens and to minimize deleterious immune-mediated inflammation caused by commensal microorganisms, immune responses against self and environmental antigens, and metabolic inflammatory disorders. Regulatory T (Treg) cell–mediated suppression serves as a vital mechanism of negative regulation of immune-mediated inflammation and features prominently in autoimmune and autoinflammatory disorders, allergy, acute and chronic infections, cancer, and metabolic inflammation. The discovery that Foxp3 is the transcription factor that specifies the Treg cell lineage facilitated recent progress in understanding the biology of regulatory T cells. In this review, we discuss cellular and molecular mechanisms in the differentiation and function of these cells.

2,356 citations


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

  • ...1 is required for the maintenance of cell type– specific regulatory chromatin characteristics following macrophage and B cell differentiation (153, 154)....

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References
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Journal ArticleDOI
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.
Abstract: Histone modifications are implicated in influencing gene expression. We have generated 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. Typical patterns of histone methylations exhibited at promoters, insulators, enhancers, and transcribed regions are identified. The monomethylations of H3K27, H3K9, H4K20, H3K79, and H2BK5 are all linked to gene activation, whereas trimethylations of H3K27, H3K9, and H3K79 are linked to repression. H2A.Z associates with functional regulatory elements, and CTCF marks boundaries of histone methylation domains. Chromosome banding patterns are correlated with unique patterns of histone modifications. Chromosome breakpoints detected in T cell cancers frequently reside in chromatin regions associated with H3K4 methylations. Our data provide new insights into the function of histone methylation and chromatin organization in genome function.

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)....

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  • ...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)....

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  • ...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....

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  • ..., 2008), human CD4 T cells (Barski et al., 2007), and CD36 erythrocyte precursors (Cui et al....

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  • ...…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)....

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Journal ArticleDOI
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.
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

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....

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  • ...…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)....

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Journal ArticleDOI
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.
Abstract: The V(D)J recombination activation gene RAG-1 was isolated on the basis of its ability to activate V(D)J recombination on an artificial substrate in fibroblasts. This property and the expression pattern in tissues and cell lines indicate that RAG-1 either activates or catalyzes the V(D)J recombination reaction of immunoglobulin and T cell receptor genes. We here describe the introduction of a mutation in RAG-1 into the germline of mice via gene targeting in embryonic stem cells. RAG-1-deficient mice have small lymphoid organs that do not contain mature B and T lymphocytes. The arrest of B and T cell differentiation occurs at an early stage and correlates with the inability to perform V(D)J recombination. The immune system of the RAG-1 mutant mice can be described as that of nonleaky scid mice. Although RAG-1 expression has been reported in the central nervous system of the mouse, no obvious neuroanatomical or behavioral abnormalities have been found in the RAG-1-deficient mice.

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)....

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  • ...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)....

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Journal ArticleDOI
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.
Abstract: Transcription factors (TFs) and their specific interactions with targets are crucial for specifying gene-expression programs. To gain insights into the transcriptional regulatory networks in embryonic stem (ES) cells, we use chromatin immunoprecipitation coupled with ultra-high-throughput DNA sequencing (ChIP-seq) to map the locations of 13 sequence-specific TFs (Nanog, Oct4, STAT3, Smad1, Sox2, Zfx, c-Myc, n-Myc, Klf4, Esrrb, Tcfcp2l1, E2f1, and CTCF) and 2 transcription regulators (p300 and Suz12). These factors are known to play different roles in ES-cell biology as components of the LIF and BMP signaling pathways, self-renewal regulators, and key reprogramming factors. Our study provides insights into the integration of the signaling pathways into the ES-cell-specific transcription circuitries. Intriguingly, we find specific genomic regions extensively targeted by different TFs. Collectively, the comprehensive mapping of TF-binding sites identifies important features of the transcriptional regulatory networks that define ES-cell identity.

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....

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  • ...…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…...

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  • ...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....

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  • ...…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…...

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Journal ArticleDOI
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.
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.

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…...

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