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Kuroda MI, Alekseyenko AA, Walsh EM, Wang X, Grayson A, Hsi PT, Kharchenko PV, French CA. Abstract 2655: Oncogenic chromatin factors drive cell type-specific transcription within megadomains in NUT midline carcinoma. Cancer Res 2016. [DOI: 10.1158/1538-7445.am2016-2655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
NUT midline carcinoma (NMC), a subtype of squamous cell cancer, is one of the most aggressive human solid malignancies known. NMC is driven by the creation of a translocation oncoprotein, BRD4-NUT, which blocks differentiation and drives growth of NMC cells. BRD4-NUT forms distinctive nuclear foci in patient tumors, which we find correlate with ∼100 unprecedented, hyperacetylated expanses of chromatin that reach up to 2 Mb in size. These ‘megadomains’ appear to be the result of aberrant, feed-forward loops of acetylation and binding of acetylated histones. Megadomains drive transcription of underlying DNA in NMC patient cells and in naïve cells induced to express BRD4-NUT. Here we characterize the constituents of BRD4-NUT chromatin complexes using a crosslinking approach, BioTAP-XL. We find many transcriptional activating proteins known to associate with BRD4, along with novel interactors including p300/CBP and a previously uncharacterized BRD4-NUT Megadomain Associated Protein (BMAP1). BMAP1 is expressed in primary NMC tissue and a subset of more common head and neck squamous cell carcinomas (HNSQC). Concurrently, we discovered a patient-derived NMC harboring a novel BMAP1-NUT fusion. BMAP-NUT blocks differentiation, and like BRD4-NUT recruits p300 to form hyperacetylated megadomains, including at the MYC locus. Thus, our proteomic and genetic approaches have converged on a novel mechanism that involves reprogramming very large regulatory regions to drive oncogenic transcription.
Citation Format: Mitzi I. Kuroda, Artyom A. Alekseyenko, Erica M. Walsh, Xin Wang, Adlai Grayson, Peter T. Hsi, Peter V. Kharchenko, Christopher A. French. Oncogenic chromatin factors drive cell type-specific transcription within megadomains in NUT midline carcinoma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2655.
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Affiliation(s)
| | | | | | - Xin Wang
- 2Harvard Medical School, Boston, MA
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52
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Masuda T, Wang X, Maeda M, Canver MC, Sher F, Funnell APW, Fisher C, Suciu M, Martyn GE, Norton LJ, Zhu C, Kurita R, Nakamura Y, Xu J, Higgs DR, Crossley M, Bauer DE, Orkin SH, Kharchenko PV, Maeda T. Transcription factors LRF and BCL11A independently repress expression of fetal hemoglobin. Science 2016; 351:285-9. [PMID: 26816381 DOI: 10.1126/science.aad3312] [Citation(s) in RCA: 231] [Impact Index Per Article: 28.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Genes encoding human β-type globin undergo a developmental switch from embryonic to fetal to adult-type expression. Mutations in the adult form cause inherited hemoglobinopathies or globin disorders, including sickle cell disease and thalassemia. Some experimental results have suggested that these diseases could be treated by induction of fetal-type hemoglobin (HbF). However, the mechanisms that repress HbF in adults remain unclear. We found that the LRF/ZBTB7A transcription factor occupies fetal γ-globin genes and maintains the nucleosome density necessary for γ-globin gene silencing in adults, and that LRF confers its repressive activity through a NuRD repressor complex independent of the fetal globin repressor BCL11A. Our study may provide additional opportunities for therapeutic targeting in the treatment of hemoglobinopathies.
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Affiliation(s)
- Takeshi Masuda
- Division of Hematology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Xin Wang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - Manami Maeda
- Division of Hematology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Matthew C Canver
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Falak Sher
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Alister P W Funnell
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Chris Fisher
- Medical Research Council, Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, Oxford University, Oxford, UK
| | - Maria Suciu
- Medical Research Council, Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, Oxford University, Oxford, UK
| | - Gabriella E Martyn
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Laura J Norton
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Catherine Zhu
- Division of Hematology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Ryo Kurita
- Cell Engineering Division, RIKEN BioResource Center, Tsukuba, Ibaraki, Japan
| | - Yukio Nakamura
- Cell Engineering Division, RIKEN BioResource Center, Tsukuba, Ibaraki, Japan. Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Jian Xu
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA. Children's Research Institute, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Douglas R Higgs
- Medical Research Council, Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, Oxford University, Oxford, UK
| | - Merlin Crossley
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Daniel E Bauer
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Stuart H Orkin
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA. Howard Hughes Medical Institute, Boston, MA 02115, USA
| | - Peter V Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.
| | - Takahiro Maeda
- Division of Hematology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
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53
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Fan J, Salathia N, Liu R, Kaeser GE, Yung YC, Herman JL, Kaper F, Fan JB, Zhang K, Chun J, Kharchenko PV. Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis. Nat Methods 2016; 13:241-4. [PMID: 26780092 PMCID: PMC4772672 DOI: 10.1038/nmeth.3734] [Citation(s) in RCA: 307] [Impact Index Per Article: 38.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2015] [Accepted: 12/16/2015] [Indexed: 12/23/2022]
Abstract
The transcriptional state of a cell reflects a variety of biological factors, from persistent cell-type specific features to transient processes such as cell cycle. Depending on biological context, all such aspects of transcriptional heterogeneity may be of interest, but detecting them from noisy single-cell RNA-seq data remains challenging. We developed PAGODA to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability amongst measured cells.
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Affiliation(s)
- Jean Fan
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Rui Liu
- Department of Bioengineering, University of California, San Diego, California, USA
| | - Gwendolyn E Kaeser
- Department of Molecular and Cellular Neuroscience, Dorris Neuroscience Center, The Scripps Research Institute, La Jolla, California, USA
| | - Yun C Yung
- Department of Molecular and Cellular Neuroscience, Dorris Neuroscience Center, The Scripps Research Institute, La Jolla, California, USA
| | - Joseph L Herman
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Jian-Bing Fan
- Illumina Inc., San Diego, California, USA.,Present address: AnchorDx Corporation, International Biotech Island, Guangzhou, Guangdong, China
| | - Kun Zhang
- Department of Bioengineering, University of California, San Diego, California, USA
| | - Jerold Chun
- Department of Molecular and Cellular Neuroscience, Dorris Neuroscience Center, The Scripps Research Institute, La Jolla, California, USA
| | - Peter V Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
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54
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Bersani F, Lee E, Kharchenko PV, Xu AW, Liu M, Xega K, MacKenzie OC, Brannigan BW, Wittner BS, Jung H, Ramaswamy S, Park PJ, Maheswaran S, Ting DT, Haber DA. Pericentromeric satellite repeat expansions through RNA-derived DNA intermediates in cancer. Proc Natl Acad Sci U S A 2015; 112:15148-53. [PMID: 26575630 PMCID: PMC4679016 DOI: 10.1073/pnas.1518008112] [Citation(s) in RCA: 109] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Aberrant transcription of the pericentromeric human satellite II (HSATII) repeat is present in a wide variety of epithelial cancers. In deriving experimental systems to study its deregulation, we observed that HSATII expression is induced in colon cancer cells cultured as xenografts or under nonadherent conditions in vitro, but it is rapidly lost in standard 2D cultures. Unexpectedly, physiological induction of endogenous HSATII RNA, as well as introduction of synthetic HSATII transcripts, generated cDNA intermediates in the form of DNA/RNA hybrids. Single molecule sequencing of tumor xenografts showed that HSATII RNA-derived DNA (rdDNA) molecules are stably incorporated within pericentromeric loci. Suppression of RT activity using small molecule inhibitors reduced HSATII copy gain. Analysis of whole-genome sequencing data revealed that HSATII copy number gain is a common feature in primary human colon tumors and is associated with a lower overall survival. Together, our observations suggest that cancer-associated derepression of specific repetitive sequences can promote their RNA-driven genomic expansion, with potential implications on pericentromeric architecture.
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Affiliation(s)
- Francesca Bersani
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129
| | - Eunjung Lee
- Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115; Division of Genetics, Brigham and Women's Hospital, Boston, MA 02115
| | - Peter V Kharchenko
- Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115; Hematology/Oncology Program, Children's Hospital, Boston, MA 02115
| | - Andrew W Xu
- Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115
| | - Mingzhu Liu
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129; Howard Hughes Medical Institute, Chevy Chase, MD 20815
| | - Kristina Xega
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129
| | - Olivia C MacKenzie
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129
| | - Brian W Brannigan
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129
| | - Ben S Wittner
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129
| | | | - Sridhar Ramaswamy
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129; Department of Medicine, Massachusetts General Hospital, Boston, MA 02114
| | - Peter J Park
- Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115; Division of Genetics, Brigham and Women's Hospital, Boston, MA 02115; Informatics Program, Children's Hospital, Boston, MA 02115
| | - Shyamala Maheswaran
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129; Department of Surgery, Massachusetts General Hospital, Boston, MA 02114
| | - David T Ting
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129; Department of Medicine, Massachusetts General Hospital, Boston, MA 02114;
| | - Daniel A Haber
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129; Howard Hughes Medical Institute, Chevy Chase, MD 20815; Department of Medicine, Massachusetts General Hospital, Boston, MA 02114;
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55
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Alekseyenko AA, Walsh EM, Wang X, Grayson AR, Hsi PT, Kharchenko PV, Kuroda MI, French CA. The oncogenic BRD4-NUT chromatin regulator drives aberrant transcription within large topological domains. Genes Dev 2015. [PMID: 26220994 PMCID: PMC4526735 DOI: 10.1101/gad.267583.115] [Citation(s) in RCA: 133] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
NUT midline carcinoma (NMC), a subtype of squamous cell cancer, is one of the most aggressive human solid malignancies known. NMC is driven by the creation of a translocation oncoprotein, BRD4-NUT, which blocks differentiation and drives growth of NMC cells. BRD4-NUT forms distinctive nuclear foci in patient tumors, which we found correlate with ∼100 unprecedented, hyperacetylated expanses of chromatin that reach up to 2 Mb in size. These "megadomains" appear to be the result of aberrant, feed-forward loops of acetylation and binding of acetylated histones that drive transcription of underlying DNA in NMC patient cells and naïve cells induced to express BRD4-NUT. Megadomain locations are typically cell lineage-specific; however, the cMYC and TP63 regions are targeted in all NMCs tested and play functional roles in tumor growth. Megadomains appear to originate from select pre-existing enhancers that progressively broaden but are ultimately delimited by topologically associating domain (TAD) boundaries. Therefore, our findings establish a basis for understanding the powerful role played by large-scale chromatin organization in normal and aberrant lineage-specific gene transcription.
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Affiliation(s)
- Artyom A Alekseyenko
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA; Department of Genetics, Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Erica M Walsh
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Xin Wang
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Adlai R Grayson
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Peter T Hsi
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Peter V Kharchenko
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02115, USA; Hematology/Oncology Program, Children's Hospital, Boston, Massachusetts 02115, USA; Harvard Stem Cell Institute, Cambridge, Massachusetts 02138, USA
| | - Mitzi I Kuroda
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA; Department of Genetics, Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Christopher A French
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
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56
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Welling M, Chen HH, Muñoz J, Musheev MU, Kester L, Junker JP, Mischerikow N, Arbab M, Kuijk E, Silberstein L, Kharchenko PV, Geens M, Niehrs C, van de Velde H, van Oudenaarden A, Heck AJR, Geijsen N. DAZL regulates Tet1 translation in murine embryonic stem cells. EMBO Rep 2015; 16:791-802. [PMID: 26077710 DOI: 10.15252/embr.201540538] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Accepted: 05/08/2015] [Indexed: 11/09/2022] Open
Abstract
Embryonic stem cell (ESC) cultures display a heterogeneous gene expression profile, ranging from a pristine naïve pluripotent state to a primed epiblast state. Addition of inhibitors of GSK3β and MEK (so-called 2i conditions) pushes ESC cultures toward a more homogeneous naïve pluripotent state, but the molecular underpinnings of this naïve transition are not completely understood. Here, we demonstrate that DAZL, an RNA-binding protein known to play a key role in germ-cell development, marks a subpopulation of ESCs that is actively transitioning toward naïve pluripotency. Moreover, DAZL plays an essential role in the active reprogramming of cytosine methylation. We demonstrate that DAZL associates with mRNA of Tet1, a catalyst of 5-hydroxylation of methyl-cytosine, and enhances Tet1 mRNA translation. Overexpression of DAZL in heterogeneous ESC cultures results in elevated TET1 protein levels as well as increased global hydroxymethylation. Conversely, null mutation of Dazl severely stunts 2i-mediated TET1 induction and hydroxymethylation. Our results provide insight into the regulation of the acquisition of naïve pluripotency and demonstrate that DAZL enhances TET1-mediated cytosine hydroxymethylation in ESCs that are actively reprogramming to a pluripotent ground state.
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Affiliation(s)
- Maaike Welling
- Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hsu-Hsin Chen
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA Harvard Stem Cell Institute, Cambridge, MA, USA
| | - Javier Muñoz
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands Netherlands Proteomics Centre, Utrecht, The Netherlands
| | | | - Lennart Kester
- Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jan Philipp Junker
- Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, The Netherlands
| | - Nikolai Mischerikow
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands Netherlands Proteomics Centre, Utrecht, The Netherlands
| | - Mandana Arbab
- Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, The Netherlands
| | - Ewart Kuijk
- Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lev Silberstein
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA Harvard Stem Cell Institute, Cambridge, MA, USA
| | - Peter V Kharchenko
- Center for Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Mieke Geens
- Research Group Reproduction and Genetics, Vrije Universiteit Brussel, Brussels, Belgium
| | - Christof Niehrs
- Institute of Molecular Biology, Mainz, Germany Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Hilde van de Velde
- Research Group Reproduction and Genetics, Vrije Universiteit Brussel, Brussels, Belgium
| | | | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands Netherlands Proteomics Centre, Utrecht, The Netherlands
| | - Niels Geijsen
- Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, The Netherlands Department of Companion Animals, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
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57
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Alekseyenko AA, McElroy KA, Kang H, Zee BM, Kharchenko PV, Kuroda MI. BioTAP-XL: Cross-linking/Tandem Affinity Purification to Study DNA Targets, RNA, and Protein Components of Chromatin-Associated Complexes. ACTA ACUST UNITED AC 2015; 109:21.30.1-21.30.32. [PMID: 25559106 DOI: 10.1002/0471142727.mb2130s109] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
In order to understand how chromatin complexes function in the nucleus, it is important to obtain a comprehensive picture of their protein, DNA, and RNA components, as well as their mutual interactions. This unit presents a chromatin cross-linking approach (BioTAP-XL) that utilizes a special BioTAP-tagged transgenic protein bait along with mass spectrometry to identify protein complex components, and high-throughput sequencing to identify RNA components and DNA binding sites. Full protocols are provided for Drosophila cells and for human cells in culture, along with an additional protocol for Drosophila embryos as the source material. A key element of the approach in all cases is the generation of control data from input chromatin samples.
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Affiliation(s)
- Artyom A Alekseyenko
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.,Department of Genetics, Harvard Medical School, Boston, Massachusetts
| | - Kyle A McElroy
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.,Department of Genetics, Harvard Medical School, Boston, Massachusetts.,Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts
| | - Hyuckjoon Kang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.,Department of Genetics, Harvard Medical School, Boston, Massachusetts
| | - Barry M Zee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.,Department of Genetics, Harvard Medical School, Boston, Massachusetts
| | - Peter V Kharchenko
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts.,Hematology/Oncology Program, Children's Hospital, Boston, Massachusetts
| | - Mitzi I Kuroda
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.,Department of Genetics, Harvard Medical School, Boston, Massachusetts
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58
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Landau DA, Clement K, Ziller MJ, Boyle P, Fan J, Gu H, Stevenson K, Sougnez C, Wang L, Li S, Kotliar D, Zhang W, Ghandi M, Garraway L, Fernandes SM, Livak KJ, Gabriel S, Gnirke A, Lander ES, Brown JR, Neuberg D, Kharchenko PV, Hacohen N, Getz G, Meissner A, Wu CJ. Locally disordered methylation forms the basis of intratumor methylome variation in chronic lymphocytic leukemia. Cancer Cell 2014; 26:813-825. [PMID: 25490447 PMCID: PMC4302418 DOI: 10.1016/j.ccell.2014.10.012] [Citation(s) in RCA: 266] [Impact Index Per Article: 26.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2014] [Revised: 09/16/2014] [Accepted: 10/24/2014] [Indexed: 01/01/2023]
Abstract
Intratumoral heterogeneity plays a critical role in tumor evolution. To define the contribution of DNA methylation to heterogeneity within tumors, we performed genome-scale bisulfite sequencing of 104 primary chronic lymphocytic leukemias (CLLs). Compared with 26 normal B cell samples, CLLs consistently displayed higher intrasample variability of DNA methylation patterns across the genome, which appears to arise from stochastically disordered methylation in malignant cells. Transcriptome analysis of bulk and single CLL cells revealed that methylation disorder was linked to low-level expression. Disordered methylation was further associated with adverse clinical outcome. We therefore propose that disordered methylation plays a similar role to that of genetic instability, enhancing the ability of cancer cells to search for superior evolutionary trajectories.
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MESH Headings
- B-Lymphocytes/metabolism
- CpG Islands
- DNA Methylation
- Epigenesis, Genetic
- Gene Expression Regulation, Leukemic
- Genetic Variation
- Genome, Human
- Humans
- Leukemia, Lymphocytic, Chronic, B-Cell/genetics
- Leukemia, Lymphocytic, Chronic, B-Cell/pathology
- Molecular Sequence Data
- Sequence Analysis, DNA
- Sulfites/chemistry
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Affiliation(s)
- Dan A Landau
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Broad Institute, Cambridge, MA 02139, USA
| | - Kendell Clement
- Broad Institute, Cambridge, MA 02139, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA 02139, USA
| | - Michael J Ziller
- Broad Institute, Cambridge, MA 02139, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA
| | | | - Jean Fan
- Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | | | - Kristen Stevenson
- Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA 02115, USA
| | | | - Lili Wang
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Shuqiang Li
- Fluidigm, South San Francisco, CA 94080, USA
| | - Dylan Kotliar
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Wandi Zhang
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | | | - Levi Garraway
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Broad Institute, Cambridge, MA 02139, USA
| | - Stacey M Fernandes
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | | | | | | | | | - Jennifer R Brown
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Donna Neuberg
- Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA 02115, USA
| | - Peter V Kharchenko
- Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA; Division of Hematology/Oncology, Children's Hospital, Boston, MA 02115, USA
| | - Nir Hacohen
- Broad Institute, Cambridge, MA 02139, USA; Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Gad Getz
- Broad Institute, Cambridge, MA 02139, USA; Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Alexander Meissner
- Broad Institute, Cambridge, MA 02139, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA.
| | - Catherine J Wu
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Division of Hematology/Oncology, Children's Hospital, Boston, MA 02115, USA.
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59
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Usoskin D, Furlan A, Islam S, Abdo H, Lönnerberg P, Lou D, Hjerling-Leffler J, Haeggström J, Kharchenko O, Kharchenko PV, Linnarsson S, Ernfors P. Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing. Nat Neurosci 2014; 18:145-53. [PMID: 25420068 DOI: 10.1038/nn.3881] [Citation(s) in RCA: 1321] [Impact Index Per Article: 132.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2014] [Accepted: 10/22/2014] [Indexed: 12/17/2022]
Abstract
The primary sensory system requires the integrated function of multiple cell types, although its full complexity remains unclear. We used comprehensive transcriptome analysis of 622 single mouse neurons to classify them in an unbiased manner, independent of any a priori knowledge of sensory subtypes. Our results reveal eleven types: three distinct low-threshold mechanoreceptive neurons, two proprioceptive, and six principal types of thermosensitive, itch sensitive, type C low-threshold mechanosensitive and nociceptive neurons with markedly different molecular and operational properties. Confirming previously anticipated major neuronal types, our results also classify and provide markers for new, functionally distinct subtypes. For example, our results suggest that itching during inflammatory skin diseases such as atopic dermatitis is linked to a distinct itch-generating type. We demonstrate single-cell RNA-seq as an effective strategy for dissecting sensory responsive cells into distinct neuronal types. The resulting catalog illustrates the diversity of sensory types and the cellular complexity underlying somatic sensation.
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Affiliation(s)
- Dmitry Usoskin
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Alessandro Furlan
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Saiful Islam
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Hind Abdo
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Peter Lönnerberg
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Daohua Lou
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Jens Hjerling-Leffler
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Jesper Haeggström
- Division of Physiological Chemistry, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Olga Kharchenko
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Peter V Kharchenko
- 1] Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA. [2] Division of Hematology/Oncology, Children's Hospital, Boston, Massachusetts, USA
| | - Sten Linnarsson
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Patrik Ernfors
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
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60
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Alekseyenko AA, Gorchakov AA, Zee BM, Fuchs SM, Kharchenko PV, Kuroda MI. Heterochromatin-associated interactions of Drosophila HP1a with dADD1, HIPP1, and repetitive RNAs. Genes Dev 2014; 28:1445-60. [PMID: 24990964 PMCID: PMC4083088 DOI: 10.1101/gad.241950.114] [Citation(s) in RCA: 74] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Heterochromatin protein 1 (HP1a) plays conserved roles in gene silencing and heterochromatin and is also implicated in transcription, DNA replication, and repair. Using BioTAP-XL mass spectrometry and sequencing across multiple life stages of Drosophila, Alekseyenko et al. identify HP1a chromatin-associated protein and RNA interactions. They discover 13 novel candidates among the top interactions. Furthermore, HP1a selectively associates with a broad set of RNAs transcribed from repetitive regions. The validation of several novel HP1a protein interactors reveals new HP1a links to chromatin organization and function. Heterochromatin protein 1 (HP1a) has conserved roles in gene silencing and heterochromatin and is also implicated in transcription, DNA replication, and repair. Here we identify chromatin-associated protein and RNA interactions of HP1a by BioTAP-XL mass spectrometry and sequencing from Drosophila S2 cells, embryos, larvae, and adults. Our results reveal an extensive list of known and novel HP1a-interacting proteins, of which we selected three for validation. A strong novel interactor, dADD1 (Drosophila ADD1) (CG8290), is highly enriched in heterochromatin, harbors an ADD domain similar to human ATRX, displays selective binding to H3K9me2 and H3K9me3, and is a classic genetic suppressor of position-effect variegation. Unexpectedly, a second hit, HIPP1 (HP1 and insulator partner protein-1) (CG3680), is strongly connected to CP190-related complexes localized at putative insulator sequences throughout the genome in addition to its colocalization with HP1a in heterochromatin. A third interactor, the histone methyltransferase MES-4, is also enriched in heterochromatin. In addition to these protein–protein interactions, we found that HP1a selectively associated with a broad set of RNAs transcribed from repetitive regions. We propose that this rich network of previously undiscovered interactions will define how HP1a complexes perform their diverse functions in cells and developing organisms.
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Affiliation(s)
- Artyom A Alekseyenko
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA; Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Andrey A Gorchakov
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA; Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA; Institute of Molecular and Cellular Biology, Novosibirsk 630090, Russia
| | - Barry M Zee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA; Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Stephen M Fuchs
- Department of Biology, Tufts University, Medford, Massachusetts 02155, USA
| | - Peter V Kharchenko
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02115, USA; Hematology/Oncology Program, Children's Hospital, Boston, Massachusetts 02115, USA
| | - Mitzi I Kuroda
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA; Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
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61
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Kharchenko PV, Silberstein L, Scadden DT. Bayesian approach to single-cell differential expression analysis. Nat Methods 2014. [PMID: 24836921 DOI: 10.1038/nmeth.2967.] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Single-cell data provide a means to dissect the composition of complex tissues and specialized cellular environments. However, the analysis of such measurements is complicated by high levels of technical noise and intrinsic biological variability. We describe a probabilistic model of expression-magnitude distortions typical of single-cell RNA-sequencing measurements, which enables detection of differential expression signatures and identification of subpopulations of cells in a way that is more tolerant of noise.
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Affiliation(s)
- Peter V Kharchenko
- 1] Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA. [2] Hematology/Oncology Program, Children's Hospital, Boston, Massachusetts, USA. [3] Harvard Stem Cell Institute, Cambridge, Massachusetts, USA
| | - Lev Silberstein
- 1] Harvard Stem Cell Institute, Cambridge, Massachusetts, USA. [2] Center for Regenerative Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA. [3] Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA
| | - David T Scadden
- 1] Harvard Stem Cell Institute, Cambridge, Massachusetts, USA. [2] Center for Regenerative Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA. [3] Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA
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62
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Ferrari F, Plachetka A, Alekseyenko AA, Jung YL, Ozsolak F, Kharchenko PV, Park PJ, Kuroda MI. "Jump start and gain" model for dosage compensation in Drosophila based on direct sequencing of nascent transcripts. Cell Rep 2013; 5:629-36. [PMID: 24183666 DOI: 10.1016/j.celrep.2013.09.037] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2013] [Revised: 08/13/2013] [Accepted: 09/25/2013] [Indexed: 01/14/2023] Open
Abstract
Dosage compensation in Drosophila is mediated by the MSL complex, which increases male X-linked gene expression approximately 2-fold. The MSL complex preferentially binds the bodies of active genes on the male X, depositing H4K16ac with a 3' bias. Two models have been proposed for the influence of the MSL complex on transcription: one based on promoter recruitment of RNA polymerase II (Pol II), and a second featuring enhanced transcriptional elongation. Here, we utilize nascent RNA sequencing to document dosage compensation during transcriptional elongation. We also compare X and autosomes from published data on paused and elongating polymerase in order to assess the role of Pol II recruitment. Our results support a model for differentially regulated elongation, starting with release from 5' pausing and increasing through X-linked gene bodies. Our results highlight facilitated transcriptional elongation as a key mechanism for the coordinated regulation of a diverse set of genes.
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Affiliation(s)
- Francesco Ferrari
- Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
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63
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Apostolou E, Ferrari F, Walsh RM, Bar-Nur O, Stadtfeld M, Cheloufi S, Stuart HT, Polo JM, Ohsumi TK, Borowsky ML, Kharchenko PV, Park PJ, Hochedlinger K. Genome-wide chromatin interactions of the Nanog locus in pluripotency, differentiation, and reprogramming. Cell Stem Cell 2013; 12:699-712. [PMID: 23665121 DOI: 10.1016/j.stem.2013.04.013] [Citation(s) in RCA: 152] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2012] [Revised: 03/27/2013] [Accepted: 04/16/2013] [Indexed: 12/14/2022]
Abstract
The chromatin state of pluripotency genes has been studied extensively in embryonic stem cells (ESCs) and differentiated cells, but their potential interactions with other parts of the genome remain largely unexplored. Here, we identified a genome-wide, pluripotency-specific interaction network around the Nanog promoter by adapting circular chromosome conformation capture sequencing. This network was rearranged during differentiation and restored in induced pluripotent stem cells. A large fraction of Nanog-interacting loci were bound by Mediator or cohesin in pluripotent cells. Depletion of these proteins from ESCs resulted in a disruption of contacts and the acquisition of a differentiation-specific interaction pattern prior to obvious transcriptional and phenotypic changes. Similarly, the establishment of Nanog interactions during reprogramming often preceded transcriptional upregulation of associated genes, suggesting a causative link. Our results document a complex, pluripotency-specific chromatin "interactome" for Nanog and suggest a functional role for long-range genomic interactions in the maintenance and induction of pluripotency.
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Affiliation(s)
- Effie Apostolou
- Massachusetts General Hospital Cancer Center and Center for Regenerative Medicine, 185 Cambridge Street, Boston, MA 02114, USA
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Ferrari F, Jung YL, Kharchenko PV, Plachetka A, Alekseyenko AA, Kuroda MI, Park PJ. Comment on "Drosophila dosage compensation involves enhanced Pol II recruitment to male X-linked promoters". Science 2013; 340:273. [PMID: 23599463 DOI: 10.1126/science.1231815] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Conrad et al. (Reports, 10 August 2012, p. 742) reported a doubling of RNA polymerase II (Pol II) occupancy at X-linked promoters to support 5' recruitment as the key mechanism for dosage compensation in Drosophila. However, they employed an erroneous data-processing step, overestimating Pol II differences. Reanalysis of the data fails to support the authors' model for dosage compensation.
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Affiliation(s)
- F Ferrari
- Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
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65
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Woo CJ, Kharchenko PV, Daheron L, Park PJ, Kingston RE. Identification of regions in the HOX cluster that can confer repression in a Polycomb-dependent manner. Epigenetics Chromatin 2013. [PMCID: PMC3600710 DOI: 10.1186/1756-8935-6-s1-p86] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
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66
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Landt SG, Marinov GK, Kundaje A, Kheradpour P, Pauli F, Batzoglou S, Bernstein BE, Bickel P, Brown JB, Cayting P, Chen Y, DeSalvo G, Epstein C, Fisher-Aylor KI, Euskirchen G, Gerstein M, Gertz J, Hartemink AJ, Hoffman MM, Iyer VR, Jung YL, Karmakar S, Kellis M, Kharchenko PV, Li Q, Liu T, Liu XS, Ma L, Milosavljevic A, Myers RM, Park PJ, Pazin MJ, Perry MD, Raha D, Reddy TE, Rozowsky J, Shoresh N, Sidow A, Slattery M, Stamatoyannopoulos JA, Tolstorukov MY, White KP, Xi S, Farnham PJ, Lieb JD, Wold BJ, Snyder M. ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res 2013; 22:1813-31. [PMID: 22955991 PMCID: PMC3431496 DOI: 10.1101/gr.136184.111] [Citation(s) in RCA: 1280] [Impact Index Per Article: 116.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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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Affiliation(s)
- Stephen G Landt
- Department of Genetics, Stanford University, Stanford, California 94305, USA
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67
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Wang CI, Alekseyenko AA, LeRoy G, Elia AEH, Gorchakov AA, Britton LMP, Elledge SJ, Kharchenko PV, Garcia BA, Kuroda MI. Chromatin proteins captured by ChIP-mass spectrometry are linked to dosage compensation in Drosophila. Nat Struct Mol Biol 2013; 20:202-9. [PMID: 23295261 DOI: 10.1038/nsmb.2477] [Citation(s) in RCA: 94] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2012] [Accepted: 11/21/2012] [Indexed: 12/28/2022]
Abstract
X-chromosome dosage compensation by the MSL (male-specific lethal) complex is required in Drosophila melanogaster to increase gene expression from the single male X to equal that of both female X chromosomes. Instead of focusing solely on protein complexes released from DNA, here we used chromatin-interacting protein MS (ChIP-MS) to identify MSL interactions on cross-linked chromatin. We identified MSL-enriched histone modifications, including histone H4 Lys16 acetylation and histone H3 Lys36 methylation, and CG4747, a putative Lys36-trimethylated histone H3 (H3K36me3)-binding protein. CG4747 is associated with the bodies of active genes, coincident with H3K36me3, and is mislocalized in the Set2 mutant lacking H3K36me3. CG4747 loss of function in vivo results in partial mislocalization of the MSL complex to autosomes, and RNA interference experiments confirm that CG4747 and Set2 function together to facilitate targeting of the MSL complex to active genes, validating the ChIP-MS approach.
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Affiliation(s)
- Charlotte I Wang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
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68
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Lee E, Iskow R, Yang L, Gokcumen O, Haseley P, Luquette LJ, Lohr JG, Harris CC, Ding L, Wilson RK, Wheeler DA, Gibbs RA, Kucherlapati R, Lee C, Kharchenko PV, Park PJ. Analysis of somatic retrotransposition in human cancers. BMC Proc 2012. [PMCID: PMC3467675 DOI: 10.1186/1753-6561-6-s6-o23] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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69
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Schwartz YB, Linder-Basso D, Kharchenko PV, Tolstorukov MY, Kim M, Li HB, Gorchakov AA, Minoda A, Shanower G, Alekseyenko AA, Riddle NC, Jung YL, Gu T, Plachetka A, Elgin SCR, Kuroda MI, Park PJ, Savitsky M, Karpen GH, Pirrotta V. Nature and function of insulator protein binding sites in the Drosophila genome. Genome Res 2012; 22:2188-98. [PMID: 22767387 PMCID: PMC3483548 DOI: 10.1101/gr.138156.112] [Citation(s) in RCA: 145] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Chromatin insulator elements and associated proteins have been proposed to partition eukaryotic genomes into sets of independently regulated domains. Here we test this hypothesis by quantitative genome-wide analysis of insulator protein binding to Drosophila chromatin. We find distinct combinatorial binding of insulator proteins to different classes of sites and uncover a novel type of insulator element that binds CP190 but not any other known insulator proteins. Functional characterization of different classes of binding sites indicates that only a small fraction act as robust insulators in standard enhancer-blocking assays. We show that insulators restrict the spreading of the H3K27me3 mark but only at a small number of Polycomb target regions and only to prevent repressive histone methylation within adjacent genes that are already transcriptionally inactive. RNAi knockdown of insulator proteins in cultured cells does not lead to major alterations in genome expression. Taken together, these observations argue against the concept of a genome partitioned by specialized boundary elements and suggest that insulators are reserved for specific regulation of selected genes.
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Affiliation(s)
- Yuri B Schwartz
- Department of Molecular Biology, Umeå University, Umeå, 901 87, Sweden.
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70
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Lee E, Iskow R, Yang L, Gokcumen O, Haseley P, Luquette LJ, Lohr JG, Harris CC, Ding L, Wilson RK, Wheeler DA, Gibbs RA, Kucherlapati R, Lee C, Kharchenko PV, Park PJ. Landscape of somatic retrotransposition in human cancers. Science 2012; 337:967-71. [PMID: 22745252 DOI: 10.1126/science.1222077] [Citation(s) in RCA: 526] [Impact Index Per Article: 43.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Transposable elements (TEs) are abundant in the human genome, and some are capable of generating new insertions through RNA intermediates. In cancer, the disruption of cellular mechanisms that normally suppress TE activity may facilitate mutagenic retrotranspositions. We performed single-nucleotide resolution analysis of TE insertions in 43 high-coverage whole-genome sequencing data sets from five cancer types. We identified 194 high-confidence somatic TE insertions, as well as thousands of polymorphic TE insertions in matched normal genomes. Somatic insertions were present in epithelial tumors but not in blood or brain cancers. Somatic L1 insertions tend to occur in genes that are commonly mutated in cancer, disrupt the expression of the target genes, and are biased toward regions of cancer-specific DNA hypomethylation, highlighting their potential impact in tumorigenesis.
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Affiliation(s)
- Eunjung Lee
- Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
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71
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Alekseyenko AA, Ho JWK, Peng S, Gelbart M, Tolstorukov MY, Plachetka A, Kharchenko PV, Jung YL, Gorchakov AA, Larschan E, Gu T, Minoda A, Riddle NC, Schwartz YB, Elgin SCR, Karpen GH, Pirrotta V, Kuroda MI, Park PJ. Sequence-specific targeting of dosage compensation in Drosophila favors an active chromatin context. PLoS Genet 2012; 8:e1002646. [PMID: 22570616 PMCID: PMC3343056 DOI: 10.1371/journal.pgen.1002646] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2011] [Accepted: 02/22/2012] [Indexed: 11/23/2022] Open
Abstract
The Drosophila MSL complex mediates dosage compensation by increasing transcription of the single X chromosome in males approximately two-fold. This is accomplished through recognition of the X chromosome and subsequent acetylation of histone H4K16 on X-linked genes. Initial binding to the X is thought to occur at “entry sites” that contain a consensus sequence motif (“MSL recognition element” or MRE). However, this motif is only ∼2 fold enriched on X, and only a fraction of the motifs on X are initially targeted. Here we ask whether chromatin context could distinguish between utilized and non-utilized copies of the motif, by comparing their relative enrichment for histone modifications and chromosomal proteins mapped in the modENCODE project. Through a comparative analysis of the chromatin features in male S2 cells (which contain MSL complex) and female Kc cells (which lack the complex), we find that the presence of active chromatin modifications, together with an elevated local GC content in the surrounding sequences, has strong predictive value for functional MSL entry sites, independent of MSL binding. We tested these sites for function in Kc cells by RNAi knockdown of Sxl, resulting in induction of MSL complex. We show that ectopic MSL expression in Kc cells leads to H4K16 acetylation around these sites and a relative increase in X chromosome transcription. Collectively, our results support a model in which a pre-existing active chromatin environment, coincident with H3K36me3, contributes to MSL entry site selection. The consequences of MSL targeting of the male X chromosome include increase in nucleosome lability, enrichment for H4K16 acetylation and JIL-1 kinase, and depletion of linker histone H1 on active X-linked genes. Our analysis can serve as a model for identifying chromatin and local sequence features that may contribute to selection of functional protein binding sites in the genome. The genomes of complex organisms encompass hundreds of millions of base pairs of DNA, and regulatory molecules must distinguish specific targets within this vast landscape. In general, regulatory factors find target genes through sequence-specific interactions with the underlying DNA. However, sequence-specific factors typically bind only a fraction of the candidate genomic regions containing their specific target sequence motif. Here we identify potential roles for chromatin environment and flanking sequence composition in helping regulatory factors find their appropriate binding sites, using targeting of the Drosophila dosage compensation complex as a model. The initial stage of dosage compensation involves binding of the Male Specific Lethal (MSL) complex to a sequence motif called the MSL recognition element [1]. Using data from a large chromatin mapping effort (the modENCODE project), we successfully identify an active chromatin environment as predictive of selective MRE binding by the MSL complex. Our study provides a framework for using genome-wide datasets to analyze and predict functional protein–DNA binding site selection.
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Affiliation(s)
- Artyom A. Alekseyenko
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Joshua W. K. Ho
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Shouyong Peng
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Marnie Gelbart
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Michael Y. Tolstorukov
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Annette Plachetka
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Peter V. Kharchenko
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Youngsook L. Jung
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Andrey A. Gorchakov
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Erica Larschan
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, Rhode Island, United States of America
| | - Tingting Gu
- Department of Biology, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Aki Minoda
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, California, United States of America
- Department of Genome Dynamics, Lawrence Berkeley National Lab, Berkeley, California, United States of America
| | - Nicole C. Riddle
- Department of Biology, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | | | - Sarah C. R. Elgin
- Department of Biology, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Gary H. Karpen
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, California, United States of America
| | - Vincenzo Pirrotta
- Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, New Jersey, United States of America
| | - Mitzi I. Kuroda
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
- * E-mail: (MIK); (PJP)
| | - Peter J. Park
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
- * E-mail: (MIK); (PJP)
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Kharchenko PV, Xi R, Park PJ. Evidence for dosage compensation between the X chromosome and autosomes in mammals. Nat Genet 2011; 43:1167-9; author reply 1171-2. [PMID: 22120048 DOI: 10.1038/ng.991] [Citation(s) in RCA: 75] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Larschan E, Bishop EP, Kharchenko PV, Core LJ, Lis JT, Park PJ, Kuroda MI. X chromosome dosage compensation via enhanced transcriptional elongation in Drosophila. Nature 2011; 471:115-8. [PMID: 21368835 PMCID: PMC3076316 DOI: 10.1038/nature09757] [Citation(s) in RCA: 145] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2010] [Accepted: 12/14/2010] [Indexed: 11/15/2022]
Abstract
The evolution of sex chromosomes has resulted in numerous species in which females inherit two X chromosomes but males have a single X, thus requiring dosage compensation. MSL (Male-specific lethal) complex increases transcription on the single X chromosome of Drosophila males to equalize expression of X-linked genes between the sexes1. The biochemical mechanisms utilized for dosage compensation must function over a wide dynamic range of transcription levels and differential expression patterns. Lucchesi (1998)2 proposed that MSL complex regulates transcriptional elongation to control dosage compensation, a model subsequently supported by mapping of MSL complex and MSL-dependent H4K16 acetylation to the bodies of X-linked genes in males, with a bias towards 3′ ends3-7. However, experimental analysis of MSL function at the mechanistic level has been challenging due to the small magnitude of the chromosome-wide effect and the lack of an in vitro system for biochemical analysis. In this study, we use global run-on sequencing (GRO-seq)8 to examine the specific effect of MSL complex on RNA Polymerase II (RNAP II) on a genome-wide level. Results indicate that MSL complex enhances transcription by facilitating the progression of RNAP II across the bodies of active X-linked genes. Improving transcriptional output downstream of typical gene-specific control may explain how dosage compensation can be imposed on the diverse set of genes along an entire chromosome.
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Affiliation(s)
- Erica Larschan
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA
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Riddle NC, Minoda A, Kharchenko PV, Alekseyenko AA, Schwartz YB, Tolstorukov MY, Gorchakov AA, Jaffe JD, Kennedy C, Linder-Basso D, Peach SE, Shanower G, Zheng H, Kuroda MI, Pirrotta V, Park PJ, Elgin SC, Karpen GH. Plasticity in patterns of histone modifications and chromosomal proteins in Drosophila heterochromatin. Genome Res 2011; 21:147-63. [PMID: 21177972 PMCID: PMC3032919 DOI: 10.1101/gr.110098.110] [Citation(s) in RCA: 214] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2010] [Accepted: 12/08/2010] [Indexed: 12/18/2022]
Abstract
Eukaryotic genomes are packaged in two basic forms, euchromatin and heterochromatin. We have examined the composition and organization of Drosophila melanogaster heterochromatin in different cell types using ChIP-array analysis of histone modifications and chromosomal proteins. As anticipated, the pericentric heterochromatin and chromosome 4 are on average enriched for the "silencing" marks H3K9me2, H3K9me3, HP1a, and SU(VAR)3-9, and are generally depleted for marks associated with active transcription. The locations of the euchromatin-heterochromatin borders identified by these marks are similar in animal tissues and most cell lines, although the amount of heterochromatin is variable in some cell lines. Combinatorial analysis of chromatin patterns reveals distinct profiles for euchromatin, pericentric heterochromatin, and the 4th chromosome. Both silent and active protein-coding genes in heterochromatin display complex patterns of chromosomal proteins and histone modifications; a majority of the active genes exhibit both "activation" marks (e.g., H3K4me3 and H3K36me3) and "silencing" marks (e.g., H3K9me2 and HP1a). The hallmark of active genes in heterochromatic domains appears to be a loss of H3K9 methylation at the transcription start site. We also observe complex epigenomic profiles of intergenic regions, repeated transposable element (TE) sequences, and genes in the heterochromatic extensions. An unexpectedly large fraction of sequences in the euchromatic chromosome arms exhibits a heterochromatic chromatin signature, which differs in size, position, and impact on gene expression among cell types. We conclude that patterns of heterochromatin/euchromatin packaging show greater complexity and plasticity than anticipated. This comprehensive analysis provides a foundation for future studies of gene activity and chromosomal functions that are influenced by or dependent upon heterochromatin.
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Affiliation(s)
- Nicole C. Riddle
- Department of Biology, Washington University St. Louis, Missouri 63130, USA
| | - Aki Minoda
- Department of Molecular and Cell Biology, University of California at Berkeley and Department of Genome Dynamics, Lawrence Berkeley National Lab, Berkeley, California 94720, USA
| | - Peter V. Kharchenko
- Center for Biomedical Informatics, Harvard Medical School and Informatics Program, Children's Hospital, Boston, Massachusetts 02115, USA
| | - Artyom A. Alekseyenko
- Division of Genetics, Department of Medicine, Brigham & Women's Hospital, and Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Yuri B. Schwartz
- Department of Molecular Biology & Biochemistry, Rutgers University, Piscataway, New Jersey 08901, USA
- Department of Molecular Biology, Umea University, 90187 Umea, Sweden
| | - Michael Y. Tolstorukov
- Center for Biomedical Informatics, Harvard Medical School and Informatics Program, Children's Hospital, Boston, Massachusetts 02115, USA
| | - Andrey A. Gorchakov
- Division of Genetics, Department of Medicine, Brigham & Women's Hospital, and Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Jacob D. Jaffe
- Proteomics Group, The Broad Institute, Cambridge, Massachusetts 02139, USA
| | - Cameron Kennedy
- Department of Molecular and Cell Biology, University of California at Berkeley and Department of Genome Dynamics, Lawrence Berkeley National Lab, Berkeley, California 94720, USA
| | - Daniela Linder-Basso
- Department of Molecular Biology & Biochemistry, Rutgers University, Piscataway, New Jersey 08901, USA
| | - Sally E. Peach
- Proteomics Group, The Broad Institute, Cambridge, Massachusetts 02139, USA
| | - Gregory Shanower
- Department of Molecular Biology & Biochemistry, Rutgers University, Piscataway, New Jersey 08901, USA
| | - Haiyan Zheng
- Biological Mass Spectrometry Resource, Center for Advanced Biotechnology and Medicine, University of Dentistry and Medicine of New Jersey, Piscataway, New Jersey 08854, USA
| | - Mitzi I. Kuroda
- Division of Genetics, Department of Medicine, Brigham & Women's Hospital, and Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Vincenzo Pirrotta
- Department of Molecular Biology & Biochemistry, Rutgers University, Piscataway, New Jersey 08901, USA
| | - Peter J. Park
- Center for Biomedical Informatics, Harvard Medical School and Informatics Program, Children's Hospital, Boston, Massachusetts 02115, USA
| | - Sarah C.R. Elgin
- Department of Biology, Washington University St. Louis, Missouri 63130, USA
| | - Gary H. Karpen
- Department of Molecular and Cell Biology, University of California at Berkeley and Department of Genome Dynamics, Lawrence Berkeley National Lab, Berkeley, California 94720, USA
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75
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Roy S, Ernst J, Kharchenko PV, Kheradpour P, Negre N, Eaton ML, Landolin JM, Bristow CA, Ma L, Lin MF, Washietl S, Arshinoff BI, Ay F, Meyer PE, Robine N, Washington NL, Di Stefano L, Berezikov E, Brown CD, Candeias R, Carlson JW, Carr A, Jungreis I, Marbach D, Sealfon R, Tolstorukov MY, Will S, Alekseyenko AA, Artieri C, Booth BW, Brooks AN, Dai Q, Davis CA, Duff MO, Feng X, Gorchakov AA, Gu T, Henikoff JG, Kapranov P, Li R, MacAlpine HK, Malone J, Minoda A, Nordman J, Okamura K, Perry M, Powell SK, Riddle NC, Sakai A, Samsonova A, Sandler JE, Schwartz YB, Sher N, Spokony R, Sturgill D, van Baren M, Wan KH, Yang L, Yu C, Feingold E, Good P, Guyer M, Lowdon R, Ahmad K, Andrews J, Berger B, Brenner SE, Brent MR, Cherbas L, Elgin SCR, Gingeras TR, Grossman R, Hoskins RA, Kaufman TC, Kent W, Kuroda MI, Orr-Weaver T, Perrimon N, Pirrotta V, Posakony JW, Ren B, Russell S, Cherbas P, Graveley BR, Lewis S, Micklem G, Oliver B, Park PJ, Celniker SE, Henikoff S, Karpen GH, Lai EC, MacAlpine DM, Stein LD, White KP, Kellis M. Identification of functional elements and regulatory circuits by Drosophila modENCODE. Science 2010; 330:1787-97. [PMID: 21177974 PMCID: PMC3192495 DOI: 10.1126/science.1198374] [Citation(s) in RCA: 899] [Impact Index Per Article: 64.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.
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Affiliation(s)
| | - Sushmita Roy
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Jason Ernst
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Peter V. Kharchenko
- Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Pouya Kheradpour
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Nicolas Negre
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - Matthew L. Eaton
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Jane M. Landolin
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Christopher A. Bristow
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Lijia Ma
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - Michael F. Lin
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Stefan Washietl
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Bradley I. Arshinoff
- Department of Molecular Genetics, University of Toronto, 27 King’s College Circle, Toronto, Ontario M5S 1A1, Canada
- Ontario Institute for Cancer Research, 101 College Street, Suite 800, Toronto, Ontario M5G 0A3, Canada
| | - Ferhat Ay
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Patrick E. Meyer
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Machine Learning Group, Université Libre de Bruxelles, CP212, Brussels 1050, Belgium
| | - Nicolas Robine
- Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, NY 10065, USA
| | | | - Luisa Di Stefano
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129, USA
| | - Eugene Berezikov
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Utrecht, Netherlands
| | - Christopher D. Brown
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - Rogerio Candeias
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Joseph W. Carlson
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Adrian Carr
- Department of Genetics and Cambridge Systems Biology Centre, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
| | - Irwin Jungreis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Daniel Marbach
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Rachel Sealfon
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Michael Y. Tolstorukov
- Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Sebastian Will
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Artyom A. Alekseyenko
- Department of Medicine and Department of Genetics, Brigham and Women’s Hospital, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Carlo Artieri
- Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Benjamin W. Booth
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Angela N. Brooks
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
| | - Qi Dai
- Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, NY 10065, USA
| | - Carrie A. Davis
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Michael O. Duff
- Department of Genetics and Developmental Biology, University of Connecticut Stem Cell Institute, 263 Farmington, CT 06030–6403, USA
| | - Xin Feng
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
- Ontario Institute for Cancer Research, 101 College Street, Suite 800, Toronto, Ontario M5G 0A3, Canada
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA
| | - Andrey A. Gorchakov
- Department of Medicine and Department of Genetics, Brigham and Women’s Hospital, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Tingting Gu
- Department of Biology CB-1137, Washington University, Saint Louis, MO 63130, USA
| | - Jorja G. Henikoff
- Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, NY 10065, USA
| | | | - Renhua Li
- Division of Extramural Research, National Human Genome Research Institute, NIH, 5635 Fishers Lane, Suite 4076, Bethesda, MD 20892–9305, USA
| | - Heather K. MacAlpine
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - John Malone
- Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Aki Minoda
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | | | - Katsutomo Okamura
- Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, NY 10065, USA
| | - Marc Perry
- Ontario Institute for Cancer Research, 101 College Street, Suite 800, Toronto, Ontario M5G 0A3, Canada
| | - Sara K. Powell
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Nicole C. Riddle
- Department of Biology CB-1137, Washington University, Saint Louis, MO 63130, USA
| | - Akiko Sakai
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA
| | - Anastasia Samsonova
- Department of Genetics and Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Jeremy E. Sandler
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Yuri B. Schwartz
- Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Noa Sher
- White-head Institute, Cambridge, MA 02142, USA
| | - Rebecca Spokony
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - David Sturgill
- Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Marijke van Baren
- Center for Genome Sciences, Washington University, 4444 Forest Park Boulevard, Saint Louis, MO 63108, USA
| | - Kenneth H. Wan
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Li Yang
- Department of Genetics and Developmental Biology, University of Connecticut Stem Cell Institute, 263 Farmington, CT 06030–6403, USA
| | - Charles Yu
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Elise Feingold
- Division of Extramural Research, National Human Genome Research Institute, NIH, 5635 Fishers Lane, Suite 4076, Bethesda, MD 20892–9305, USA
| | - Peter Good
- Division of Extramural Research, National Human Genome Research Institute, NIH, 5635 Fishers Lane, Suite 4076, Bethesda, MD 20892–9305, USA
| | - Mark Guyer
- Division of Extramural Research, National Human Genome Research Institute, NIH, 5635 Fishers Lane, Suite 4076, Bethesda, MD 20892–9305, USA
| | - Rebecca Lowdon
- Division of Extramural Research, National Human Genome Research Institute, NIH, 5635 Fishers Lane, Suite 4076, Bethesda, MD 20892–9305, USA
| | - Kami Ahmad
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA
| | - Justen Andrews
- Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
| | - Bonnie Berger
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Steven E. Brenner
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
- Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA
| | - Michael R. Brent
- Center for Genome Sciences, Washington University, 4444 Forest Park Boulevard, Saint Louis, MO 63108, USA
| | - Lucy Cherbas
- Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
- Center for Genomics and Bioinformatics, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
| | - Sarah C. R. Elgin
- Department of Biology CB-1137, Washington University, Saint Louis, MO 63130, USA
| | - Thomas R. Gingeras
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
- Affymetrix, Santa Clara, CA 95051, USA
| | - Robert Grossman
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - Roger A. Hoskins
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Thomas C. Kaufman
- Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
| | - William Kent
- Center for Biomolecular Science and Engineering, School of Engineering and Howard Hughes Medical Institute (HHMI), University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Mitzi I. Kuroda
- Department of Medicine and Department of Genetics, Brigham and Women’s Hospital, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | | | - Norbert Perrimon
- Department of Genetics and Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Vincenzo Pirrotta
- Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, NJ 08854, USA
| | - James W. Posakony
- Division of Biological Sciences, Section of Cell and Developmental Biology, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Bing Ren
- Division of Biological Sciences, Section of Cell and Developmental Biology, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Steven Russell
- Department of Genetics and Cambridge Systems Biology Centre, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
| | - Peter Cherbas
- Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
- Center for Genomics and Bioinformatics, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
| | - Brenton R. Graveley
- Department of Genetics and Developmental Biology, University of Connecticut Stem Cell Institute, 263 Farmington, CT 06030–6403, USA
| | - Suzanna Lewis
- Genome Sciences Division, LBNL, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Gos Micklem
- Department of Genetics and Cambridge Systems Biology Centre, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
| | - Brian Oliver
- Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Peter J. Park
- Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Susan E. Celniker
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Steven Henikoff
- Basic Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109, USA
| | - Gary H. Karpen
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
| | - Eric C. Lai
- Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, NY 10065, USA
| | - David M. MacAlpine
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Lincoln D. Stein
- Ontario Institute for Cancer Research, 101 College Street, Suite 800, Toronto, Ontario M5G 0A3, Canada
| | - Kevin P. White
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
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Abstract
DNA replication initiates from thousands of start sites throughout the Drosophila genome and must be coordinated with other ongoing nuclear processes such as transcription to ensure genetic and epigenetic inheritance. Considerable progress has been made toward understanding how chromatin modifications regulate the transcription program; in contrast, we know relatively little about the role of the chromatin landscape in defining how start sites of DNA replication are selected and regulated. Here, we describe the Drosophila replication program in the context of the chromatin and transcription landscape for multiple cell lines using data generated by the modENCODE consortium. We find that while the cell lines exhibit similar replication programs, there are numerous cell line-specific differences that correlate with changes in the chromatin architecture. We identify chromatin features that are associated with replication timing, early origin usage, and ORC binding. Primary sequence, activating chromatin marks, and DNA-binding proteins (including chromatin remodelers) contribute in an additive manner to specify ORC-binding sites. We also generate accurate and predictive models from the chromatin data to describe origin usage and strength between cell lines. Multiple activating chromatin modifications contribute to the function and relative strength of replication origins, suggesting that the chromatin environment does not regulate origins of replication as a simple binary switch, but rather acts as a tunable rheostat to regulate replication initiation events.
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Affiliation(s)
- Matthew L Eaton
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina 27710, USA
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77
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Kharchenko PV, Alekseyenko AA, Schwartz YB, Minoda A, Riddle NC, Ernst J, Sabo PJ, Larschan E, Gorchakov AA, Gu T, Linder-Basso D, Plachetka A, Shanower G, Tolstorukov MY, Luquette LJ, Xi R, Jung YL, Park RW, Bishop EP, Canfield TK, Sandstrom R, Thurman RE, MacAlpine DM, Stamatoyannopoulos JA, Kellis M, Elgin SCR, Kuroda MI, Pirrotta V, Karpen GH, Park PJ. Comprehensive analysis of the chromatin landscape in Drosophila melanogaster. Nature 2010; 471:480-5. [PMID: 21179089 PMCID: PMC3109908 DOI: 10.1038/nature09725] [Citation(s) in RCA: 647] [Impact Index Per Article: 46.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2010] [Accepted: 12/06/2010] [Indexed: 12/17/2022]
Abstract
Chromatin is composed of DNA and a variety of modified histones and non-histone proteins, which have an impact on cell differentiation, gene regulation and other key cellular processes. Here we present a genome-wide chromatin landscape for Drosophila melanogaster based on eighteen histone modifications, summarized by nine prevalent combinatorial patterns. Integrative analysis with other data (non-histone chromatin proteins, DNase I hypersensitivity, GRO-Seq reads produced by engaged polymerase, short/long RNA products) reveals discrete characteristics of chromosomes, genes, regulatory elements and other functional domains. We find that active genes display distinct chromatin signatures that are correlated with disparate gene lengths, exon patterns, regulatory functions and genomic contexts. We also demonstrate a diversity of signatures among Polycomb targets that include a subset with paused polymerase. This systematic profiling and integrative analysis of chromatin signatures provides insights into how genomic elements are regulated, and will serve as a resource for future experimental investigations of genome structure and function.
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Affiliation(s)
- Peter V Kharchenko
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02115, USA
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78
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Gorchakov AA, Alekseyenko AA, Kharchenko PV, Park PJ, Kuroda MI. Dosage compensation in drosophila: Sequence-specific initiation and sequence-independent spreading of MSL complex to the active genes on the male X chromosome. RUSS J GENET+ 2010. [DOI: 10.1134/s1022795410100303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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79
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Gorchakov AA, Alekseenko AA, Kharchenko PV, Park P, Kuroda M. [Dosage compensation in drosophila: sequence-specific initiation and sequence-independent spreading of MSL complex to the active genes on the male X chromosome]. Genetika 2010; 46:1430-1434. [PMID: 21254570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
For the dosage compensation to occur, genes on the single male X chromosomes in Drosophila must be selectively bound and acetylated by the ribonucleoprotein complex called MSL complex. It remained unknown how such exquisite specificity is achieved, and whether specific DNA sequences were involved. In the present work we demonstrate that it is transcription of the gene on the X chromosome that is important for MSL targeting, irrespective of gene origin and DNA sequence.
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80
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Day DS, Luquette LJ, Park PJ, Kharchenko PV. Estimating enrichment of repetitive elements from high-throughput sequence data. Genome Biol 2010; 11:R69. [PMID: 20584328 PMCID: PMC2911117 DOI: 10.1186/gb-2010-11-6-r69] [Citation(s) in RCA: 82] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2010] [Revised: 06/15/2010] [Accepted: 06/28/2010] [Indexed: 11/13/2022] Open
Abstract
We describe computational methods for analysis of repetitive elements from short-read sequencing data, and apply them to study histone modifications associated with the repetitive elements in human and mouse cells. Our results demonstrate that while accurate enrichment estimates can be obtained for individual repeat types and small sets of repeat instances, there are distinct combinatorial patterns of chromatin marks associated with major annotated repeat families, including H3K27me3/H3K9me3 differences among the endogenous retroviral element classes.
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Affiliation(s)
- Daniel S Day
- Harvard-MIT Health Sciences and Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
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81
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Abstract
The recent development of next-generation sequencing technology has enabled significant progress in chromatin structure analysis. Here, we review the experimental and bioinformatic approaches to studying nucleosome positioning and histone modification profiles on a genome scale using this technology. These studies advanced our knowledge of the nucleosome positioning patterns of both epigenetically modified and bulk nucleosomes and elucidated the role of such patterns in regulation of gene expression. The identification and analysis of large sets of nucleosome-bound DNA sequences allowed better understanding of the rules that govern nucleosome positioning in organisms of various complexity. We also discuss the existing challenges and prospects of using next-generation sequencing for nucleosome positioning analysis and outline the importance of such studies for the entire chromatin structure field.
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Affiliation(s)
- Michael Y Tolstorukov
- Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck St., Boston, MA 02115 USA
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82
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Woo CJ, Kharchenko PV, Daheron L, Park PJ, Kingston RE. A region of the human HOXD cluster that confers polycomb-group responsiveness. Cell 2010; 140:99-110. [PMID: 20085705 DOI: 10.1016/j.cell.2009.12.022] [Citation(s) in RCA: 218] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2009] [Revised: 10/07/2009] [Accepted: 12/01/2009] [Indexed: 12/23/2022]
Abstract
Polycomb group (PcG) proteins are essential for accurate axial body patterning during embryonic development. PcG-mediated repression is conserved in metazoans and is targeted in Drosophila by Polycomb response elements (PREs). However, targeting sequences in humans have not been described. While analyzing chromatin architecture in the context of human embryonic stem cell (hESC) differentiation, we discovered a 1.8kb region between HOXD11 and HOXD12 (D11.12) that is associated with PcG proteins, becomes nuclease hypersensitive, and then shows alteration in nuclease sensitivity as hESCs differentiate. The D11.12 element repressed luciferase expression from a reporter construct and full repression required a highly conserved region and YY1 binding sites. Furthermore, repression was dependent on the PcG proteins BMI1 and EED and a YY1-interacting partner, RYBP. We conclude that D11.12 is a Polycomb-dependent regulatory region with similarities to Drosophila PREs, indicating conservation in the mechanisms that target PcG function in mammals and flies.
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Affiliation(s)
- Caroline J Woo
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA 02114, USA
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83
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Tolstorukov MY, Kharchenko PV, Goldman JA, Kingston RE, Park PJ. Comparative analysis of H2A.Z nucleosome organization in the human and yeast genomes. Genome Res 2009; 19:967-77. [PMID: 19246569 DOI: 10.1101/gr.084830.108] [Citation(s) in RCA: 84] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Eukaryotic DNA is wrapped around a histone protein core to constitute the fundamental repeating units of chromatin, the nucleosomes. The affinity of the histone core for DNA depends on the nucleotide sequence; however, it is unclear to what extent DNA sequence determines nucleosome positioning in vivo, and if the same rules of sequence-directed positioning apply to genomes of varying complexity. Using the data generated by high-throughput DNA sequencing combined with chromatin immunoprecipitation, we have identified positions of nucleosomes containing the H2A.Z histone variant and histone H3 trimethylated at lysine 4 in human CD4(+) T-cells. We find that the 10-bp periodicity observed in nucleosomal sequences in yeast and other organisms is not pronounced in human nucleosomal sequences. This result was confirmed for a broader set of mononucleosomal fragments that were not selected for any specific histone variant or modification. We also find that human H2A.Z nucleosomes protect only approximately 120 bp of DNA from MNase digestion and exhibit specific sequence preferences, suggesting a novel mechanism of nucleosome organization for the H2A.Z variant.
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Affiliation(s)
- Michael Y Tolstorukov
- Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02115, USA
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84
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Abstract
The distribution of nucleosomes along the genome is a significant aspect of chromatin structure and is thought to influence gene regulation through modulation of DNA accessibility. However, properties of nucleosome organization remain poorly understood, particularly in mammalian genomes. Toward this goal we used tiled microarrays to identify stable nucleosome positions along the HOX gene clusters in human cell lines. We show that nucleosome positions exhibit sequence properties and long-range organization that are different from those characterized in other organisms. Despite overall variability of internucleosome distances, specific loci contain regular nucleosomal arrays with 195-bp periodicity. Moreover, such arrays tend to occur preferentially toward the 3' ends of genes. Through comparison of different cell lines, we find that active transcription is correlated with increased positioning of nucleosomes, suggesting an unexpected role for transcription in the establishment of well-positioned nucleosomes.
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Affiliation(s)
- Peter V Kharchenko
- Harvard Partners Center for Genetics and Genomics, Boston, Massachusetts 02115, USA
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85
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Petrov SB, Kharchenko PV. [Diagnosis of localized cancer of the prostate]. Urologiia 2005:19-22. [PMID: 15776826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
The study was made to improve preoperative diagnosis of the stage of prostatic cancer (PC) to raise efficacy of subsequent treatment. A total of 152 patients entered the study who had undergone in 1997-2002 a radical prostatectomy for local PC. Basing on pathomorphological findings, the patients were divided into two groups: with localized CP (68 patients) and spread CP (84 patients). The comparison of clinical and pathomorphological diagnosis in the same patients demonstrated that there is a correlation between them, therefore it is possible to predict pathomorphological diagnosis at the stage of clinical diagnosis. The formula of establishment of a pathomorphological stage of the disease has been developed and its efficacy was tested in 30 control patients. The mathematical model of complex evaluation of the symptoms allows in 81% of cases to correctly determine the spread of CP while examination of separate symptoms provides a correct diagnosis in less than half the cases. The model can prognosticate radicality of the future operative intervention and duration of recurrence-free course and, consequently, to reduce the rate of intra- and postoperative complications and design further treatment policy.
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