195 results on '"Farnham PJ"'
Search Results
2. ZNF217, a candidate breast cancer oncogene amplified at 20q13, regulates expression of the ErbB3 receptor tyrosine kinase in breast cancer cells
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Krig, SR, Miller, JK, Frietze, S, Beckett, LA, Neve, RM, Farnham, PJ, Yaswen, PI, and Sweeney, CA
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Biochemistry and Cell Biology ,Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Biological Sciences ,Genetics ,Women's Health ,Biotechnology ,Cancer ,Breast Cancer ,2.1 Biological and endogenous factors ,Animals ,Breast Neoplasms ,Cell Line ,Tumor ,Chromatin Immunoprecipitation ,Chromosomes ,Human ,Pair 20 ,Female ,Gene Expression ,Gene Expression Regulation ,Neoplastic ,Genes ,erbB ,Humans ,Mice ,Mice ,Transgenic ,Oligonucleotide Array Sequence Analysis ,Oncogenes ,Promoter Regions ,Genetic ,Receptor ,ErbB-3 ,Reverse Transcriptase Polymerase Chain Reaction ,Signal Transduction ,Trans-Activators ,ZNF217 ,ErbB3 ,CtBP2 ,20q13 ,breast cancer ,Receptor ,erbB-3 ,Clinical Sciences ,Oncology & Carcinogenesis ,Biochemistry and cell biology ,Oncology and carcinogenesis - Abstract
Understanding the mechanisms underlying ErbB3 overexpression in breast cancer will facilitate the rational design of therapies to disrupt ErbB2-ErbB3 oncogenic function. Although ErbB3 overexpression is frequently observed in breast cancer, the factors mediating its aberrant expression are poorly understood. In particular, the ErbB3 gene is not significantly amplified, raising the question as to how ErbB3 overexpression is achieved. In this study we showed that the ZNF217 transcription factor, amplified at 20q13 in ∼20% of breast tumors, regulates ErbB3 expression. Analysis of a panel of human breast cancer cell lines (n = 50) and primary human breast tumors (n = 15) showed a strong positive correlation between ZNF217 and ErbB3 expression. Ectopic expression of ZNF217 in human mammary epithelial cells induced ErbB3 expression, whereas ZNF217 silencing in breast cancer cells resulted in decreased ErbB3 expression. Although ZNF217 has previously been linked with transcriptional repression because of its close association with C-terminal-binding protein (CtBP)1/2 repressor complexes, our results show that ZNF217 also activates gene expression. We showed that ZNF217 recruitment to the ErbB3 promoter is CtBP1/2-independent and that ZNF217 and CtBP1/2 have opposite roles in regulating ErbB3 expression. In addition, we identify ErbB3 as one of the mechanisms by which ZNF217 augments PI-3K/Akt signaling.
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- 2010
3. Large-scale manipulation of promoter DNA methylation reveals context-specific transcriptional responses and stability
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de Mendoza, A, Trung, VN, Ford, E, Poppe, D, Buckberry, S, Pflueger, J, Grimmer, MR, Stolzenburg, S, Bogdanovic, O, Oshlack, A, Farnham, PJ, Blancafort, P, Lister, R, de Mendoza, A, Trung, VN, Ford, E, Poppe, D, Buckberry, S, Pflueger, J, Grimmer, MR, Stolzenburg, S, Bogdanovic, O, Oshlack, A, Farnham, PJ, Blancafort, P, and Lister, R
- Abstract
BACKGROUND: Cytosine DNA methylation is widely described as a transcriptional repressive mark with the capacity to silence promoters. Epigenome engineering techniques enable direct testing of the effect of induced DNA methylation on endogenous promoters; however, the downstream effects have not yet been comprehensively assessed. RESULTS: Here, we simultaneously induce methylation at thousands of promoters in human cells using an engineered zinc finger-DNMT3A fusion protein, enabling us to test the effect of forced DNA methylation upon transcription, chromatin accessibility, histone modifications, and DNA methylation persistence after the removal of the fusion protein. We find that transcriptional responses to DNA methylation are highly context-specific, including lack of repression, as well as cases of increased gene expression, which appears to be driven by the eviction of methyl-sensitive transcriptional repressors. Furthermore, we find that some regulatory networks can override DNA methylation and that promoter methylation can cause alternative promoter usage. DNA methylation deposited at promoter and distal regulatory regions is rapidly erased after removal of the zinc finger-DNMT3A fusion protein, in a process combining passive and TET-mediated demethylation. Finally, we demonstrate that induced DNA methylation can exist simultaneously on promoter nucleosomes that possess the active histone modification H3K4me3, or DNA bound by the initiated form of RNA polymerase II. CONCLUSIONS: These findings have important implications for epigenome engineering and demonstrate that the response of promoters to DNA methylation is more complex than previously appreciated.
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- 2022
4. Functional DNA methylation differences between tissues, cell types, and across individuals discovered using the M&M algorithm
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Zhang, B, Zhou, Y, Lin, N, Lowdon, RF, Hong, C, Nagarajan, RP, Cheng, JB, Li, D, Stevens, M, Lee, HJ, Xing, X, Zhou, J, Sundaram, V, Elliott, G, Gu, J, Shi, T, Gascard, P, Sigaroudinia, M, Tlsty, TD, Kadlecek, T, Weiss, A, O'Geen, H, Farnham, PJ, Maire, CL, Ligon, KL, Madden, PAF, Tam, A, Moore, R, Hirst, M, Marra, MA, Costello, JF, and Wang, T
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Data Interpretation ,Genome ,Bioinformatics ,genetic processes ,Human Genome ,High-Throughput Nucleotide Sequencing ,DNA ,Statistical ,DNA Methylation ,Biological Sciences ,Medical and Health Sciences ,Organ Specificity ,Genetics ,Humans ,2.1 Biological and endogenous factors ,natural sciences ,Generic health relevance ,Aetiology ,Sequence Analysis ,Algorithms ,Human ,Biotechnology - Abstract
DNA methylation plays key roles in diverse biological processes such as X chromosome inactivation, transposable element repression, genomic imprinting, and tissue-specific gene expression. Sequencing-based DNA methylation profiling provides an unprecedented opportunity to map and compare complete DNA methylomes. This includes one of the most widely applied technologies for measuring DNA methylation: methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq), coupled with a complementary method, methylation-sensitive restriction enzyme sequencing (MRE-seq). A computational approach that integrates data from these two different but complementary assays and predicts methylation differences between samples has been unavailable. Here, we present a novel integrative statistical framework M&M (for integration of MeDIP-seq and MRE-seq) that dynamically scales, normalizes, and combines MeDIPseq and MRE-seq data to detect differentially methylated regions. Using sample-matched whole-genome bisulfite sequencing (WGBS) as a gold standard, we demonstrate superior accuracy and reproducibility of M&M compared to existing analytical methods for MeDIP-seq data alone. M&M leverages the complementary nature of MeDIP-seq and MREseq data to allow rapid comparative analysis between whole methylomes at a fraction of the cost of WGBS. Comprehensive analysis of nineteen human DNA methylomes with M&M reveals distinct DNA methylation patterns among different tissue types, cell types, and individuals, potentially underscoring divergent epigenetic regulation at different scales of phenotypic diversity. We find that differential DNA methylation at enhancer elements, with concurrent changes in histone modifications and transcription factor binding, is common at the cell, tissue, and individual levels, whereas promoter methylation is more prominent in reinforcing fundamental tissue identities. © 2013, Published by Cold Spring Harbor Laboratory Press.
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- 2013
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5. An integrated encyclopedia of DNA elements in the human genome
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Dunham, I, Kundaje, A, Aldred, SF, Collins, PJ, Davis, CA, Doyle, F, Epstein, CB, Frietze, S, Harrow, J, Kaul, R, Khatun, J, Lajoie, BR, Landt, SG, Lee, BK, Pauli, F, Rosenbloom, KR, Sabo, P, Safi, A, Sanyal, A, Shoresh, N, Simon, JM, Song, L, Trinklein, ND, Altshuler, RC, Birney, E, Brown, JB, Cheng, C, Djebali, S, Dong, X, Ernst, J, Furey, TS, Gerstein, M, Giardine, B, Greven, M, Hardison, RC, Harris, RS, Herrero, J, Hoffman, MM, Iyer, S, Kellis, M, Kheradpour, P, Lassmann, T, Li, Q, Lin, X, Marinov, GK, Merkel, A, Mortazavi, A, Parker, SCJ, Reddy, TE, Rozowsky, J, Schlesinger, F, Thurman, RE, Wang, J, Ward, LD, Whitfield, TW, Wilder, SP, Wu, W, Xi, HS, Yip, KY, Zhuang, J, Bernstein, BE, Green, ED, Gunter, C, Snyder, M, Pazin, MJ, Lowdon, RF, Dillon, LAL, Adams, LB, Kelly, CJ, Zhang, J, Wexler, JR, Good, PJ, Feingold, EA, Crawford, GE, Dekker, J, Elnitski, L, Farnham, PJ, Giddings, MC, Gingeras, TR, Guigó, R, Hubbard, TJ, Kent, WJ, Lieb, JD, Margulies, EH, and Myers, RM
- Abstract
The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research. © 2012 Macmillan Publishers Limited. All rights reserved.
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- 2012
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6. The Transcription Factor Encyclopedia
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Yusuf, D, Butland, SL, Swanson, MI, Bolotin, E, Ticoll, A, Cheung, WA, Zhang, XYC, Dickman, CTD, Fulton, DL, Lim, JS, Schnabl, JM, Ramos, OHP, Vasseur-Cognet, M, de Leeuw, CN, Simpson, EM, Ryffel, GU, Lam, EW-F, Kist, R, Wilson, MSC, Marco-Ferreres, R, Brosens, JJ, Beccari, LL, Bovolenta, P, Benayoun, BA, Monteiro, LJ, Schwenen, HDC, Grontved, L, Wederell, E, Mandrup, S, Veitia, RA, Chakravarthy, H, Hoodless, PA, Mancarelli, MM, Torbett, BE, Banham, AH, Reddy, SP, Cullum, RL, Liedtke, M, Tschan, MP, Vaz, M, Rizzino, A, Zannini, M, Frietze, S, Farnham, PJ, Eijkelenboom, A, Brown, PJ, Laperriere, D, Leprince, D, de Cristofaro, T, Prince, KL, Putker, M, del Peso, L, Camenisch, G, Wenger, RH, Mikula, M, Rozendaal, M, Mader, S, Ostrowski, J, Rhodes, SJ, Van Rechem, C, Boulay, G, Olechnowicz, SWZ, Breslin, MB, Lan, MS, Nanan, KK, Wegner, M, Hou, J, Mullen, RD, Colvin, SC, Noy, PJ, Webb, CF, Witek, ME, Ferrell, S, Daniel, JM, Park, J, Waldman, SA, Peet, DJ, Taggart, M, Jayaraman, P-S, Karrich, JJ, Blom, B, Vesuna, F, O'Geen, H, Sun, Y, Gronostajski, RM, Woodcroft, MW, Hough, MR, Chen, E, Europe-Finner, GN, Karolczak-Bayatti, M, Bailey, J, Hankinson, O, Raman, V, LeBrun, DP, Biswal, S, Harvey, CJ, DeBruyne, JP, Hogenesch, JB, Hevner, RF, Heligon, C, Luo, XM, Blank, MC, Millen, KJ, Sharlin, DS, Forrest, D, Dahlman-Wright, K, Zhao, C, Mishima, Y, Sinha, S, Chakrabarti, R, Portales-Casamar, E, Sladek, FM, Bradley, PH, Wasserman, WW, Yusuf, D, Butland, SL, Swanson, MI, Bolotin, E, Ticoll, A, Cheung, WA, Zhang, XYC, Dickman, CTD, Fulton, DL, Lim, JS, Schnabl, JM, Ramos, OHP, Vasseur-Cognet, M, de Leeuw, CN, Simpson, EM, Ryffel, GU, Lam, EW-F, Kist, R, Wilson, MSC, Marco-Ferreres, R, Brosens, JJ, Beccari, LL, Bovolenta, P, Benayoun, BA, Monteiro, LJ, Schwenen, HDC, Grontved, L, Wederell, E, Mandrup, S, Veitia, RA, Chakravarthy, H, Hoodless, PA, Mancarelli, MM, Torbett, BE, Banham, AH, Reddy, SP, Cullum, RL, Liedtke, M, Tschan, MP, Vaz, M, Rizzino, A, Zannini, M, Frietze, S, Farnham, PJ, Eijkelenboom, A, Brown, PJ, Laperriere, D, Leprince, D, de Cristofaro, T, Prince, KL, Putker, M, del Peso, L, Camenisch, G, Wenger, RH, Mikula, M, Rozendaal, M, Mader, S, Ostrowski, J, Rhodes, SJ, Van Rechem, C, Boulay, G, Olechnowicz, SWZ, Breslin, MB, Lan, MS, Nanan, KK, Wegner, M, Hou, J, Mullen, RD, Colvin, SC, Noy, PJ, Webb, CF, Witek, ME, Ferrell, S, Daniel, JM, Park, J, Waldman, SA, Peet, DJ, Taggart, M, Jayaraman, P-S, Karrich, JJ, Blom, B, Vesuna, F, O'Geen, H, Sun, Y, Gronostajski, RM, Woodcroft, MW, Hough, MR, Chen, E, Europe-Finner, GN, Karolczak-Bayatti, M, Bailey, J, Hankinson, O, Raman, V, LeBrun, DP, Biswal, S, Harvey, CJ, DeBruyne, JP, Hogenesch, JB, Hevner, RF, Heligon, C, Luo, XM, Blank, MC, Millen, KJ, Sharlin, DS, Forrest, D, Dahlman-Wright, K, Zhao, C, Mishima, Y, Sinha, S, Chakrabarti, R, Portales-Casamar, E, Sladek, FM, Bradley, PH, and Wasserman, WW
- Abstract
Here we present the Transcription Factor Encyclopedia (TFe), a new web-based compendium of mini review articles on transcription factors (TFs) that is founded on the principles of open access and collaboration. Our consortium of over 100 researchers has collectively contributed over 130 mini review articles on pertinent human, mouse and rat TFs. Notable features of the TFe website include a high-quality PDF generator and web API for programmatic data retrieval. TFe aims to rapidly educate scientists about the TFs they encounter through the delivery of succinct summaries written and vetted by experts in the field. TFe is available at http://www.cisreg.ca/tfe.
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- 2012
7. Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications
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Harris, R, Wang, T, Coarfa, C, Nagarajan, R, Hong, C, Downey, S, Johnson, B, Fouse, S, Delaney, A, Zhao, Y, Olshen, A, Ballinger, T, Zhou, X, Forsberg, K, Gu, J, Echipare, L, O'Geen, H, Lister, R, Pelizzola, M, Xi, Y, Epstein, C, Bernstein, B, Hawkins, R, Ren, B, Chung, W, Gu, H, Bock, C, Gnirke, A, Zhang, M, Haussler, D, Ecker, J, Li, W, Farnham, P, Waterland, R, Meissner, A, Marra, M, Hirst, M, Milosavljevic, A, Costello, J, Harris RA, Wang T, Coarfa C, Nagarajan RP, Hong C, Downey SL, Johnson BE, Fouse SD, Delaney A, Zhao Y, Olshen A, Ballinger T, Zhou X, Forsberg KJ, Gu J, Echipare L, O'Geen H, Lister R, Pelizzola M, Xi Y, Epstein CB, Bernstein BE, Hawkins RD, Ren B, Chung WY, Gu H, Bock C, Gnirke A, Zhang MQ, Haussler D, Ecker JR, Li W, Farnham PJ, Waterland RA, Meissner A, Marra MA, Hirst M, Milosavljevic A, Costello JF, Harris, R, Wang, T, Coarfa, C, Nagarajan, R, Hong, C, Downey, S, Johnson, B, Fouse, S, Delaney, A, Zhao, Y, Olshen, A, Ballinger, T, Zhou, X, Forsberg, K, Gu, J, Echipare, L, O'Geen, H, Lister, R, Pelizzola, M, Xi, Y, Epstein, C, Bernstein, B, Hawkins, R, Ren, B, Chung, W, Gu, H, Bock, C, Gnirke, A, Zhang, M, Haussler, D, Ecker, J, Li, W, Farnham, P, Waterland, R, Meissner, A, Marra, M, Hirst, M, Milosavljevic, A, Costello, J, Harris RA, Wang T, Coarfa C, Nagarajan RP, Hong C, Downey SL, Johnson BE, Fouse SD, Delaney A, Zhao Y, Olshen A, Ballinger T, Zhou X, Forsberg KJ, Gu J, Echipare L, O'Geen H, Lister R, Pelizzola M, Xi Y, Epstein CB, Bernstein BE, Hawkins RD, Ren B, Chung WY, Gu H, Bock C, Gnirke A, Zhang MQ, Haussler D, Ecker JR, Li W, Farnham PJ, Waterland RA, Meissner A, Marra MA, Hirst M, Milosavljevic A, and Costello JF
- Abstract
Analysis of DNA methylation patterns relies increasingly on sequencing-based profiling methods. The four most frequently used sequencing-based technologies are the bisulfite-based methods MethylC-seq and reduced representation bisulfite sequencing (RRBS), and the enrichment-based techniques methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylated DNA binding domain sequencing (MBD-seq). We applied all four methods to biological replicates of human embryonic stem cells to assess their genome-wide CpG coverage, resolution, cost, concordance and the influence of CpG density and genomic context. The methylation levels assessed by the two bisulfite methods were concordant (their difference did not exceed a given threshold) for 82% for CpGs and 99% of the non-CpG cytosines. Using binary methylation calls, the two enrichment methods were 99% concordant and regions assessed by all four methods were 97% concordant. We combined MeDIP-seq with methylation-sensitive restriction enzyme (MRE-seq) sequencing for comprehensive methylome coverage at lower cost. This, along with RNA-seq and ChIP-seq of the ES cells enabled us to detect regions with allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression.
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- 2010
8. An integrated encyclopedia of DNA elements in the human genome
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Robert Altshuler, Laura Elnitski, Michael Anaya, Alec Victorsen, Deborah Winter, Javier Herrero, Katherine Varley, Andrea Sboner, Oscar Junhong Luo, Marco Mariotti, Cristina Sisu, Mike Kay, Timothy Dreszer, Jane Loveland, Alexandra Bignell, Ewan Birney, Tim @timjph Hubbard, Kuljeet Sandhu, Eric Haugen, Chris Gunter, Alexej Abyzov, Lucas Ward, Georgi Marinov, Michael Pazin, Thomas Gingeras, Alexander Dobin, Kimberly Foss, Xianjun Dong, Benoit Miotto, Piotr Mieczkowski, Cedric Notredame, Andrew Berry, Shawn Gillespie, Axel Visel, Shawn Levy, Richard Sandstrom, Jose M Gonzalez, Melissa Fullwood, Timo Lassmann, Michael Tress, Julien Lagarde, Kevin Yip, Leslie Adams, Sylvain Foissac, Bronwen Aken, Piero Carninci, Suganthi Balasubramanian, Andrea Tanzer, Sarah Djebali, Michael Hoffman, Gloria Despacio-Reyes, Peter Park, Felix Kokocinski, Katherine Fisher-Aylor, Juan M Vaquerizas, Peggy Farnham, Patrick Collins, Amonida Zadissa, Pedro Ferreira, Philippe Batut, Michael Snyder, Electra Tapanari, Adam Frankish, Paul Flicek, AMARTYA SANYAL, Tyler Alioto, Giovanni Bussotti, Laurence Meyer, Jingyi Jessica Li, Matthew Blow, Tristan FRUM, Roger Alexander, Rory Johnson, Charles Steward, Meizhen Zheng, Margus Lukk, Ross Hardison, Claire Davidson, Gary Saunders, Alan Boyle, Luiz Penalva, Rajinder Kaul, Lazaro Centanin, Florencia Pauli Behn, Thomas Derrien, Nathan Sheffield, Toby Hunt, Eric Nguyen, Jeff Vierstra, Konrad Karczewski, Kimberly Bell, Yanbao Yu, Hagen U Tilgner, James Taylor, Balázs Bánfai, Catherine Snow, Benjamin Vernot, Stephan Kirchmaier, Michael Sammeth, Steven Wilder, Angelika Merkel, Joanna Mieczkowska, Guoliang Li, Wei Lin, Jennifer Harrow, Thomas Oliver Auer, Daniel Barrell, Eddie Park, Alvis Brazma, Hazuki Takahashi, Nathan Johnson, Daniel Sobral, Terry Furey, Alexandre Reymond, Jonathan Mudge, Anshul Kundaje, Jose Rodriguez, Akshay Bhinge, James Gilbert, Jakub Karczewski, Venkat Malladi, Troy Whitfield, Orion Buske, Ian Dunham, Jennifer Moran, Joachim Wittbrodt, Charles B. Epstein, Laurens Wilming, Jason Gertz, Joshua Akey, Joel Rozowsky, Laboratoire de Génétique Cellulaire (LGC), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), National Human Genome Research Institute (NHGRI), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Antonarakis, Stylianos, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Altshuler, Robert Charles, Ernst, Jason, Kellis, Manolis, Kheradpour, Pouya, Ward, Lucas D., Eaton, Matthew Lucas, Hendrix, David A., Jungreis, Irwin, Lin, Michael F., Washietl, Stefan, Lists of participants and their affiliations appear at the end of the paper and in the 'Collaboration/Projet' field., The Consortium is funded by grants from the NHGRI as follows: production grants: U54HG004570 (B. E. Bernstein), U01HG004695 (E. Birney), U54HG004563 (G. E. Crawford), U54HG004557 (T. R. Gingeras), U54HG004555 (T. J. Hubbard), U41HG004568 (W. J. Kent), U54HG004576 (R. M. Myers), U54HG004558 (M. Snyder), U54HG004592 (J. A. Stamatoyannopoulos). Pilot grants: R01HG003143 (J. Dekker), RC2HG005591 and R01HG003700 (M. C. Giddings), R01HG004456-03 (Y. Ruan), U01HG004571 (S. A. Tenenbaum), U01HG004561 (Z. Weng), RC2HG005679 (K. P. White). This project was supported in part by American Recovery and Reinvestment Act (ARRA) funds from the NHGRI through grants U54HG004570, U54HG004563, U41HG004568, U54HG004592, R01HG003143, RC2HG005591, R01HG003541,U01HG004561,RC2HG005679andR01HG003988(L. Pennacchio). In addition, work from NHGRI Groups was supported by the Intramural Research Program of the NHGRI (L. Elnitski, ZIAHG200323, E. H. Margulies, ZIAHG200341). Research in the Pennachio laboratory was performed at Lawrence Berkeley National Laboratory and at the United States Department of Energy Joint Genome Institute, Department of Energy Contract DE-AC02-05CH11231, University of California., Dunham I, Kundaje A, Aldred SF, Collins PJ, Davis CA, Doyle F, Epstein CB, Frietze S, Harrow J, Kaul R, Khatun J, Lajoie BR, Landt SG, Lee BK, Pauli F, Rosenbloom KR, Sabo P, Safi A, Sanyal A, Shoresh N, Simon JM, Song L, Trinklein ND, Altshuler RC, Birney E, Brown JB, Cheng C, Djebali S, Dong X, Dunham I, Ernst J, Furey TS, Gerstein M, Giardine B, Greven M, Hardison RC, Harris RS, Herrero J, Hoffman MM, Iyer S, Kellis M, Khatun J, Kheradpour P, Kundaje A, Lassmann T, Li Q, Lin X, Marinov GK, Merkel A, Mortazavi A, Parker SC, Reddy TE, Rozowsky J, Schlesinger F, Thurman RE, Wang J, Ward LD, Whitfield TW, Wilder SP, Wu W, Xi HS, Yip KY, Zhuang J, Pazin MJ, Lowdon RF, Dillon LA, Adams LB, Kelly CJ, Zhang J, Wexler JR, Green ED, Good PJ, Feingold EA, Bernstein BE, Birney E, Crawford GE, Dekker J, Elnitski L, Farnham PJ, Gerstein M, Giddings MC, Gingeras TR, Green ED, Guigó R, Hardison RC, Hubbard TJ, Kellis M, Kent W, Lieb JD, Margulies EH, Myers RM, Snyder M, Stamatoyannopoulos JA, Tenenbaum SA, Weng Z, White KP, Wold B, Khatun J, Yu Y, Wrobel J, Risk BA, Gunawardena HP, Kuiper HC, Maier CW, Xie L, Chen X, Giddings MC, Bernstein BE, Epstein CB, Shoresh N, Ernst J, Kheradpour P, Mikkelsen TS, Gillespie S, Goren A, Ram O, Zhang X, Wang L, Issner R, Coyne MJ, Durham T, Ku M, Truong T, Ward LD, Altshuler RC, Eaton ML, Kellis M, Djebali S, Davis CA, Merkel A, Dobin A, Lassmann T, Mortazavi A, Tanzer A, Lagarde J, Lin W, Schlesinger F, Xue C, Marinov GK, Khatun J, Williams BA, Zaleski C, Rozowsky J, Röder M, Kokocinski F, Abdelhamid RF, Alioto T, Antoshechkin I, Baer MT, Batut P, Bell I, Bell K, Chakrabortty S, Chen X, Chrast J, Curado J, Derrien T, Drenkow J, Dumais E, Dumais J, Duttagupta R, Fastuca M, Fejes-Toth K, Ferreira P, Foissac S, Fullwood MJ, Gao H, Gonzalez D, Gordon A, Gunawardena HP, Howald C, Jha S, Johnson R, Kapranov P, King B, Kingswood C, Li G, Luo OJ, Park E, Preall JB, Presaud K, Ribeca P, Risk BA, Robyr D, Ruan X, Sammeth M, Sandhu KS, Schaeffer L, See LH, Shahab A, Skancke J, Suzuki AM, Takahashi H, Tilgner H, Trout D, Walters N, Wang H, Wrobel J, Yu Y, Hayashizaki Y, Harrow J, Gerstein M, Hubbard TJ, Reymond A, Antonarakis SE, Hannon GJ, Giddings MC, Ruan Y, Wold B, Carninci P, Guigó R, Gingeras TR, Rosenbloom KR, Sloan CA, Learned K, Malladi VS, Wong MC, Barber GP, Cline MS, Dreszer TR, Heitner SG, Karolchik D, Kent W, Kirkup VM, Meyer LR, Long JC, Maddren M, Raney BJ, Furey TS, Song L, Grasfeder LL, Giresi PG, Lee BK, Battenhouse A, Sheffield NC, Simon JM, Showers KA, Safi A, London D, Bhinge AA, Shestak C, Schaner MR, Kim SK, Zhang ZZ, Mieczkowski PA, Mieczkowska JO, Liu Z, McDaniell RM, Ni Y, Rashid NU, Kim MJ, Adar S, Zhang Z, Wang T, Winter D, Keefe D, Birney E, Iyer VR, Lieb JD, Crawford GE, Li G, Sandhu KS, Zheng M, Wang P, Luo OJ, Shahab A, Fullwood MJ, Ruan X, Ruan Y, Myers RM, Pauli F, Williams BA, Gertz J, Marinov GK, Reddy TE, Vielmetter J, Partridge E, Trout D, Varley KE, Gasper C, Bansal A, Pepke S, Jain P, Amrhein H, Bowling KM, Anaya M, Cross MK, King B, Muratet MA, Antoshechkin I, Newberry KM, McCue K, Nesmith AS, Fisher-Aylor KI, Pusey B, DeSalvo G, Parker SL, Balasubramanian S, Davis NS, Meadows SK, Eggleston T, Gunter C, Newberry J, Levy SE, Absher DM, Mortazavi A, Wong WH, Wold B, Blow MJ, Visel A, Pennachio LA, Elnitski L, Margulies EH, Parker SC, Petrykowska HM, Abyzov A, Aken B, Barrell D, Barson G, Berry A, Bignell A, Boychenko V, Bussotti G, Chrast J, Davidson C, Derrien T, Despacio-Reyes G, Diekhans M, Ezkurdia I, Frankish A, Gilbert J, Gonzalez JM, Griffiths E, Harte R, Hendrix DA, Howald C, Hunt T, Jungreis I, Kay M, Khurana E, Kokocinski F, Leng J, Lin MF, Loveland J, Lu Z, Manthravadi D, Mariotti M, Mudge J, Mukherjee G, Notredame C, Pei B, Rodriguez JM, Saunders G, Sboner A, Searle S, Sisu C, Snow C, Steward C, Tanzer A, Tapanari E, Tress ML, van Baren MJ, Walters N, Washietl S, Wilming L, Zadissa A, Zhang Z, Brent M, Haussler D, Kellis M, Valencia A, Gerstein M, Reymond A, Guigó R, Harrow J, Hubbard TJ, Landt SG, Frietze S, Abyzov A, Addleman N, Alexander RP, Auerbach RK, Balasubramanian S, Bettinger K, Bhardwaj N, Boyle AP, Cao AR, Cayting P, Charos A, Cheng Y, Cheng C, Eastman C, Euskirchen G, Fleming JD, Grubert F, Habegger L, Hariharan M, Harmanci A, Iyengar S, Jin VX, Karczewski KJ, Kasowski M, Lacroute P, Lam H, Lamarre-Vincent N, Leng J, Lian J, Lindahl-Allen M, Min R, Miotto B, Monahan H, Moqtaderi Z, Mu XJ, O'Geen H, Ouyang Z, Patacsil D, Pei B, Raha D, Ramirez L, Reed B, Rozowsky J, Sboner A, Shi M, Sisu C, Slifer T, Witt H, Wu L, Xu X, Yan KK, Yang X, Yip KY, Zhang Z, Struhl K, Weissman SM, Gerstein M, Farnham PJ, Snyder M, Tenenbaum SA, Penalva LO, Doyle F, Karmakar S, Landt SG, Bhanvadia RR, Choudhury A, Domanus M, Ma L, Moran J, Patacsil D, Slifer T, Victorsen A, Yang X, Snyder M, Auer T, Centanin L, Eichenlaub M, Gruhl F, Heermann S, Hoeckendorf B, Inoue D, Kellner T, Kirchmaier S, Mueller C, Reinhardt R, Schertel L, Schneider S, Sinn R, Wittbrodt B, Wittbrodt J, Weng Z, Whitfield TW, Wang J, Collins PJ, Aldred SF, Trinklein ND, Partridge EC, Myers RM, Dekker J, Jain G, Lajoie BR, Sanyal A, Balasundaram G, Bates DL, Byron R, Canfield TK, Diegel MJ, Dunn D, Ebersol AK, Frum T, Garg K, Gist E, Hansen R, Boatman L, Haugen E, Humbert R, Jain G, Johnson AK, Johnson EM, Kutyavin TV, Lajoie BR, Lee K, Lotakis D, Maurano MT, Neph SJ, Neri FV, Nguyen ED, Qu H, Reynolds AP, Roach V, Rynes E, Sabo P, Sanchez ME, Sandstrom RS, Sanyal A, Shafer AO, Stergachis AB, Thomas S, Thurman RE, Vernot B, Vierstra J, Vong S, Wang H, Weaver MA, Yan Y, Zhang M, Akey JM, Bender M, Dorschner MO, Groudine M, MacCoss MJ, Navas P, Stamatoyannopoulos G, Kaul R, Dekker J, Stamatoyannopoulos JA, Dunham I, Beal K, Brazma A, Flicek P, Herrero J, Johnson N, Keefe D, Lukk M, Luscombe NM, Sobral D, Vaquerizas JM, Wilder SP, Batzoglou S, Sidow A, Hussami N, Kyriazopoulou-Panagiotopoulou S, Libbrecht MW, Schaub MA, Kundaje A, Hardison RC, Miller W, Giardine B, Harris RS, Wu W, Bickel PJ, Banfai B, Boley NP, Brown JB, Huang H, Li Q, Li JJ, Noble WS, Bilmes JA, Buske OJ, Hoffman MM, Sahu AD, Kharchenko PV, Park PJ, Baker D, Taylor J, Weng Z, Iyer S, Dong X, Greven M, Lin X, Wang J, Xi HS, Zhuang J, Gerstein M, Alexander RP, Balasubramanian S, Cheng C, Harmanci A, Lochovsky L, Min R, Mu XJ, Rozowsky J, Yan KK, Yip KY, Birney E., and Miotto, Benoit
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Encyclopedias as Topic ,[SDV]Life Sciences [q-bio] ,DNA Footprinting ,Genoma humà ,Binding Sites/genetics ,Histones/chemistry/metabolism ,0302 clinical medicine ,Exons/genetics ,ddc:576.5 ,0303 health sciences ,Multidisciplinary ,[SDV.MHEP] Life Sciences [q-bio]/Human health and pathology ,[SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] ,DNA-Binding Proteins/metabolism ,region ,Chemistry ,Genetic Predisposition to Disease/genetics ,Genomics ,Polymorphism, Single Nucleotide/genetics ,[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] ,Neoplasms/genetics ,Chromatin ,Cell biology ,in vivo ,Genetic Variation/genetics ,030220 oncology & carcinogenesis ,Deoxyribonuclease I/metabolism ,Proteins/genetics ,transcription factor-binding ,chromosome conformation capture ,DNA Methylation/genetics ,Chromosomes, Human/genetics/metabolism ,Chromatin Immunoprecipitation ,Mammals/genetics ,DNA/genetics ,determinant ,Article ,03 medical and health sciences ,map ,Animals ,Humans ,Transcription Factors/metabolism ,Alleles ,mouse ,030304 developmental biology ,Transcription, Genetic/genetics ,Chromatin/genetics/metabolism ,Sequence Analysis, RNA ,human cell ,Molecular Sequence Annotation ,Regulatory Sequences, Nucleic Acid/genetics ,Promoter Regions, Genetic/genetics ,DNA binding site ,Genòmica ,Genome, Human/genetics ,chromatin ,[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology ,Genètica ,Genome-Wide Association Study - Abstract
The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research. The Consortium is funded by grants from the NHGRI as follows: production grants: U54HG004570 (B. E. Bernstein); U01HG004695 (E. Birney); U54HG004563 (G. E. Crawford); U54HG004557 (T. R. Gingeras); U54HG004555 (T. J. Hubbard); U41HG004568 /n(W. J. Kent); U54HG004576 (R. M. Myers); U54HG004558 (M. Snyder);/nU54HG004592 (J. A. Stamatoyannopoulos). Pilot grants: R01HG003143 (J. Dekker); RC2HG005591 and R01HG003700 (M. C. Giddings); R01HG004456-03 (Y. Ruan); U01HG004571 (S. A. Tenenbaum); U01HG004561 (Z. Weng); RC2HG005679 (K. P. White). This project was supported in part by American Recovery and/nReinvestment Act (ARRA) funds from the NHGRI through grants U54HG004570, U54HG004563, U41HG004568, U54HG004592, R01HG003143, RC2HG005591,R01HG003541, U01HG004561, RC2HG005679andR01HG003988(L. Pennacchio). In addition, work from NHGRI Groups was supported by the Intramural Research/nProgram of the NHGRI (L. Elnitski, ZIAHG200323; E. H. Margulies, ZIAHG200341). Research in the Pennachio laboratory was performed at Lawrence Berkeley National Laboratory and at the United States Department of Energy Joint Genome Institute, Department of Energy Contract DE-AC02-05CH11231, University of California.
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- 2012
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9. A User's Guide to the Encyclopedia of DNA Elements (ENCODE)
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Zhi Lu, Giltae Song, Troy W. Whitfield, Vishwanath R. Iyer, Teresa Vales, Angelika Merkel, Max Libbrecht, David Haussler, Ting Wang, Kristen Lee, Lingyun Song, Richard M. Myers, Alfonso Valencia, Rachel A. Harte, Xiaoqin Xu, Lucas D. Ward, Hazuki Takahashi, Nathan C. Sheffield, Thomas Derrien, Georgi K. Marinov, Eric D. Nguyen, Bernard B. Suh, Brian J. Raney, Richard Sandstrom, Thomas D. Tullius, Benoit Miotto, Alexander Dobin, Youhan Xu, Lukas Habegger, Ian Dunham, Brian A. Risk, Paul G. Giresi, Morgan C. Giddings, Hualin Xi, Anshul Kundaje, Robert S. Harris, Devin Absher, Peter J. Bickel, Yanbao Yu, Browen Aken, Colin Kingswood, Bryan R. Lajoie, Peter J. Good, Katrina Learned, Laura Elnitski, Shirley Pepke, Brandon King, Piero Carninci, Xinqiong Yang, Ghia Euskirchen, Kathryn Beal, Christelle Borel, Michael Muratet, Robert L. Grossman, David G. Knowles, Zarmik Moqtaderi, Veronika Boychenko, Steven P. Wilder, Michael L. Tress, Florencia Pauli, Alan P. Boyle, Andrea Tanzer, Philipp Kapranov, Serafim Batzoglou, Audra K. Johnson, Jun Neri, Nitin Bhardwaj, Elise A. Feingold, Venkat S. Malladi, Michael M. Hoffman, William Stafford Noble, Andrea Sboner, Mark Gerstein, Stephanie L. Parker, Jacqueline Dumais, Felix Schlesinger, Deborah R. Winter, Randall H. Brown, Thanh Truong, Rebecca F. Lowdon, Paolo Ribeca, Brooke Rhead, Peggy J. Farnham, Krista Thibeault, Terrence S. Furey, Donna Karolchik, Alec Victorsen, Xiaoan Ruan, Rehab F. Abdelhamid, Amy S. Nesmith, Jing Wang, Nicholas M. Luscombe, Alina R. Cao, Diane Trout, Teri Slifer, Peter E. Newburger, Cricket A. Sloan, Dimitra Lotakis, Stephen M. J. Searle, Ali Mortazavi, Alexandra Bignell, Alex Reynolds, Orion J. Buske, Chris Zaleski, Theresa K. Canfield, Ian Bell, Jin Lian, Vanessa K. Swing, Katalin Toth Fejes, Catherine Ucla, Robert E. Thurman, Jacqueline Chrast, Wei Lin, Tim Hubbard, Gary Saunders, Minyi Shi, Vihra Sotirova, Sherman M. Weissman, Jason D. Lieb, Richard Humbert, Kevin M. Bowling, Assaf Gordon, Tarjei S. Mikkelsen, Jing Leng, Thomas R. Gingeras, Fabian Grubert, Nader Jameel, Jost Vielmetter, Hannah Monahan, Preti Jain, Lindsay L. Waite, Tony Shafer, Joel Rozowsky, Michael Coyne, Brian Reed, M. Kay, Harsha P. Gunawardena, Ross C. Hardison, Gavin Sherlock, Alexandra Charos, Joseph D. Fleming, Ann S. Zweig, Jason Gertz, Rajinder Kaul, Xianjun Dong, Alexandre Reymond, Carrie A. Davis, Haiyan Huang, Chao Cheng, Marco Mariotti, Phil Lacroute, Jason A. Dilocker, Kenneth McCue, R. Robilotto, Stylianos E. Antonarakis, Sridar V. Chittur, Justin Jee, Barbara J. Wold, Sudipto K. Chakrabortty, Erica Dumais, Amartya Sanyal, Nathan Boley, Tianyuan Wang, Julien Lagarde, Anthony Kirilusha, Jonathan B. Preall, Kevin Roberts, Erika Giste, Hugo Y. K. Lam, Alvis Brazma, Gregory J. Hannon, Eric Rynes, Philippe Batut, Kevin Struhl, Margus Lukk, Manching Ku, Suganthi Balasubramanian, Sonali Jha, Jorg Drenkow, W. James Kent, Michael Snyder, Jie Wang, Anna Battenhouse, Charles B. Epstein, Rami Rauch, Christopher Shestak, John A. Stamatoyannopoulos, Gaurab Mukherjee, Cédric Howald, Tanya Kutyavin, Huaien Wang, Scott A. Tenenbaum, Wan Ting Poh, Kate R. Rosenbloom, Manolis Kellis, Pauline A. Fujita, Linfeng Wu, Anita Bansal, Molly Weaver, Linda L. Grasfeder, Peter J. Sabo, Qiang Li, Melissa S. Cline, Robert M. Kuhn, Darin London, Seth Frietze, Atif Shahab, Shane Neph, Damian Keefe, James B. Brown, Mark Diekhans, Webb Miller, Katherine Aylor Fisher, Jiang Du, Hadar H. Sheffer, Sarah Djebali, Frank Doyle, Nathan Lamarre-Vincent, Chia-Lin Wei, Laura A.L. Dillon, Jennifer Harrow, Robert C. Altshuler, Tyler Alioto, Raymond K. Auerbach, Adam Frankish, Rebekka O. Sprouse, Patrick J. Collins, E. Christopher Partridge, Zheng Liu, Yoichiro Shibata, Elliott H. Margulies, Abigail K. Ebersol, Kimberly A. Showers, Eric D. Green, Krishna M. Roskin, Job Dekker, Barbara N. Pusey, Ekta Khurana, Gilberto DeSalvo, Yijun Ruan, Hao Wang, Jainab Khatun, Henriette O'Geen, Alexej Abyzov, Brian Williams, Ryan M. McDaniell, Maya Kasowski, Manoj Hariharan, Felix Kokocinski, Gloria Despacio-Reyes, Zhancheng Zhang, Subhradip Karmakar, Ewan Birney, Koon-Kiu Yan, Xian Chen, Shinny Vong, Daniel Sobral, Nick Bild, Seul K.C. Kim, Timo Lassmann, Li Wang, Minerva E. Sanchez, Vaughan Roach, Theodore Gibson, Stephen C. J. Parker, Michael F. Lin, Patrick A. Navas, Laurence R. Meyer, Luiz O. F. Penalva, Bradley E. Bernstein, Kevin P. White, Emilie Aït Yahya Graison, Juan M. Vaquerizas, Sushma Iyengar, Kimberly M. Newberry, Akshay Bhinge, Xiaolan Zhang, Kim Bell, Yoshihide Hayashizaki, Lucas Lochovsky, Noam Shoresh, Hagen Tilgner, Philip Cayting, Dorrelyn Patacsil, Timothy E. Reddy, Eric Haugen, Katherine E. Varley, M. van Baren, Nathan D. Trinklein, Bum Kyu Lee, Tristan Frum, Marianne Lindahl-Allen, Timothy Durham, Roderic Guigó, Christopher W. Maier, Micha Sammeth, Debasish Raha, Timothy R. Dreszer, Benedict Paten, Robbyn Issner, Michael R. Brent, Kevin Y. Yip, Kim Blahnik, Jason Ernst, Zhiping Weng, Henry Amrhein, Arend Sidow, Javier Herrero, Hui Gao, Stephen G. Landt, Pouya Kheradpour, Galt P. Barber, Gregory E. Crawford, Toby Hunt, HudsonAlpha Institute for Biotechnology [Huntsville, AL], ENCODE Project Consortium : Myers RM, Stamatoyannopoulos J, Snyder M, Dunham I, Hardison RC, Bernstein BE, Gingeras TR, Kent WJ, Birney E, Wold B, Crawford GE, Bernstein BE, Epstein CB, Shoresh N, Ernst J, Mikkelsen TS, Kheradpour P, Zhang X, Wang L, Issner R, Coyne MJ, Durham T, Ku M, Truong T, Ward LD, Altshuler RC, Lin MF, Kellis M, Gingeras TR, Davis CA, Kapranov P, Dobin A, Zaleski C, Schlesinger F, Batut P, Chakrabortty S, Jha S, Lin W, Drenkow J, Wang H, Bell K, Gao H, Bell I, Dumais E, Dumais J, Antonarakis SE, Ucla C, Borel C, Guigo R, Djebali S, Lagarde J, Kingswood C, Ribeca P, Sammeth M, Alioto T, Merkel A, Tilgner H, Carninci P, Hayashizaki Y, Lassmann T, Takahashi H, Abdelhamid RF, Hannon G, Fejes-Toth K, Preall J, Gordon A, Sotirova V, Reymond A, Howald C, Graison E, Chrast J, Ruan Y, Ruan X, Shahab A, Ting Poh W, Wei CL, Crawford GE, Furey TS, Boyle AP, Sheffield NC, Song L, Shibata Y, Vales T, Winter D, Zhang Z, London D, Wang T, Birney E, Keefe D, Iyer VR, Lee BK, McDaniell RM, Liu Z, Battenhouse A, Bhinge AA, Lieb JD, Grasfeder LL, Showers KA, Giresi PG, Kim SK, Shestak C, Myers RM, Pauli F, Reddy TE, Gertz J, Partridge EC, Jain P, Sprouse RO, Bansal A, Pusey B, Muratet MA, Varley KE, Bowling KM, Newberry KM, Nesmith AS, Dilocker JA, Parker SL, Waite LL, Thibeault K, Roberts K, Absher DM, Wold B, Mortazavi A, Williams B, Marinov G, Trout D, Pepke S, King B, McCue K, Kirilusha A, DeSalvo G, Fisher-Aylor K, Amrhein H, Vielmetter J, Sherlock G, Sidow A, Batzoglou S, Rauch R, Kundaje A, Libbrecht M, Margulies EH, Parker SC, Elnitski L, Green ED, Hubbard T, Harrow J, Searle S, Kokocinski F, Aken B, Frankish A, Hunt T, Despacio-Reyes G, Kay M, Mukherjee G, Bignell A, Saunders G, Boychenko V, Van Baren M, Brown RH, Khurana E, Balasubramanian S, Zhang Z, Lam H, Cayting P, Robilotto R, Lu Z, Guigo R, Derrien T, Tanzer A, Knowles DG, Mariotti M, James Kent W, Haussler D, Harte R, Diekhans M, Kellis M, Lin M, Kheradpour P, Ernst J, Reymond A, Howald C, Graison EA, Chrast J, Tress M, Rodriguez JM, Snyder M, Landt SG, Raha D, Shi M, Euskirchen G, Grubert F, Kasowski M, Lian J, Cayting P, Lacroute P, Xu Y, Monahan H, Patacsil D, Slifer T, Yang X, Charos A, Reed B, Wu L, Auerbach RK, Habegger L, Hariharan M, Rozowsky J, Abyzov A, Weissman SM, Gerstein M, Struhl K, Lamarre-Vincent N, Lindahl-Allen M, Miotto B, Moqtaderi Z, Fleming JD, Newburger P, Farnham PJ, Frietze S, O'Geen H, Xu X, Blahnik KR, Cao AR, Iyengar S, Stamatoyannopoulos JA, Kaul R, Thurman RE, Wang H, Navas PA, Sandstrom R, Sabo PJ, Weaver M, Canfield T, Lee K, Neph S, Roach V, Reynolds A, Johnson A, Rynes E, Giste E, Vong S, Neri J, Frum T, Johnson EM, Nguyen ED, Ebersol AK, Sanchez ME, Sheffer HH, Lotakis D, Haugen E, Humbert R, Kutyavin T, Shafer T, Dekker J, Lajoie BR, Sanyal A, James Kent W, Rosenbloom KR, Dreszer TR, Raney BJ, Barber GP, Meyer LR, Sloan CA, Malladi VS, Cline MS, Learned K, Swing VK, Zweig AS, Rhead B, Fujita PA, Roskin K, Karolchik D, Kuhn RM, Haussler D, Birney E, Dunham I, Wilder SP, Keefe D, Sobral D, Herrero J, Beal K, Lukk M, Brazma A, Vaquerizas JM, Luscombe NM, Bickel PJ, Boley N, Brown JB, Li Q, Huang H, Gerstein M, Habegger L, Sboner A, Rozowsky J, Auerbach RK, Yip KY, Cheng C, Yan KK, Bhardwaj N, Wang J, Lochovsky L, Jee J, Gibson T, Leng J, Du J, Hardison RC, Harris RS, Song G, Miller W, Haussler D, Roskin K, Suh B, Wang T, Paten B, Noble WS, Hoffman MM, Buske OJ, Weng Z, Dong X, Wang J, Xi H, Tenenbaum SA, Doyle F, Penalva LO, Chittur S, Tullius TD, Parker SC, White KP, Karmakar S, Victorsen A, Jameel N, Bild N, Grossman RL, Snyder M, Landt SG, Yang X, Patacsil D, Slifer T, Dekker J, Lajoie BR, Sanyal A, Weng Z, Whitfield TW, Wang J, Collins PJ, Trinklein ND, Partridge EC, Myers RM, Giddings MC, Chen X, Khatun J, Maier C, Yu Y, Gunawardena H, Risk B, Feingold EA, Lowdon RF, Dillon LA, Good PJ, Harrow J, Searle S., Becker, Peter B, Broad Institute of MIT and Harvard, Lincoln Laboratory, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology. Department of Physics, Kellis, Manolis, Epstein, Charles B., Bernstein, Bradley E., Shoresh, Noam, Ernst, Jason, Mikkelsen, Tarjei Sigurd, Kheradpour, Pouya, Zhang, Xiaolan, Wang, Li, Issner, Robbyn, Coyne, Michael J., Durham, Timothy, Ku, Manching, Truong, Thanh, Ward, Lucas D., Altshuler, Robert Charles, Lin, Michael F., ENCODE Project Consortium, Antonarakis, Stylianos, and Miotto, Benoit
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RNA, Messenger/genetics ,[SDV]Life Sciences [q-bio] ,Messenger ,Genoma humà ,Genome ,Medical and Health Sciences ,0302 clinical medicine ,Models ,ddc:576.5 ,Biology (General) ,Conserved Sequence ,Genetics ,0303 health sciences ,General Neuroscience ,RNA-Binding Proteins ,Genomics ,Biological Sciences ,Chromatin ,3. Good health ,[SDV] Life Sciences [q-bio] ,DNA-Binding Proteins ,Gene Components ,030220 oncology & carcinogenesis ,DNA methylation ,Encyclopedia ,HIV/AIDS ,Proteïnes de la sang -- Aspectes genètics ,General Agricultural and Biological Sciences ,Databases, Nucleic Acid ,Human ,Research Article ,Quality Control ,Process (engineering) ,QH301-705.5 ,1.1 Normal biological development and functioning ,Computational biology ,Biology ,ENCODE ,General Biochemistry, Genetics and Molecular Biology ,Chromatin/metabolism ,Vaccine Related ,03 medical and health sciences ,Databases ,Genetic ,Underpinning research ,Humans ,RNA, Messenger ,RNA-Binding Proteins/genetics/metabolism ,Vaccine Related (AIDS) ,Gene ,030304 developmental biology ,Internet ,General Immunology and Microbiology ,Nucleic Acid ,Agricultural and Veterinary Sciences ,Base Sequence ,Models, Genetic ,Genome, Human ,Prevention ,Human Genome ,Computational Biology ,DNA Methylation ,ENCODE Project Consortium ,Gene Expression Regulation ,DNA-Binding Proteins/genetics/metabolism ,RNA ,Human genome ,Immunization ,Generic health relevance ,Developmental Biology - Abstract
The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome., National Human Genome Research Institute (U.S.), National Institutes of Health (U.S.)
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- 2011
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10. Reduction of ZFX levels decreases histone H4 acetylation and increases Pol2 pausing at target promoters.
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Hsu E, Hutchison K, Liu Y, Nicolet CM, Schreiner S, Zemke NR, and Farnham PJ
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- Acetylation, Humans, RNA Polymerase II metabolism, Zinc Fingers, Protein Binding, Transcriptional Activation, Mice, Transcription Factors metabolism, Transcription Factors genetics, CpG Islands, Animals, Promoter Regions, Genetic, Histones metabolism, Chromatin metabolism
- Abstract
The ZFX transcriptional activator binds to CpG island promoters, with a major peak at ∼200-250 bp downstream from transcription start sites. Because ZFX binds within the transcribed region, we investigated whether it regulates transcriptional elongation. We used GRO-seq to show that loss or reduction of ZFX increased Pol2 pausing at ZFX-regulated promoters. To further investigate the mechanisms by which ZFX regulates transcription, we determined regions of the protein needed for transactivation and for recruitment to the chromatin. Interestingly, although ZFX has 13 grouped zinc fingers, deletion of the first 11 fingers produces a protein that can still bind to chromatin and activate transcription. We next used TurboID-MS to detect ZFX-interacting proteins, identifying ZNF593, as well as proteins that interact with the N-terminal transactivation domain (which included histone modifying proteins), and proteins that interact with ZFX when it is bound to the chromatin (which included TAFs and other histone modifying proteins). Our studies support a model in which ZFX enhances elongation at target promoters by recruiting H4 acetylation complexes and reducing pausing., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)
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- 2024
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11. Variants in ZFX are associated with an X-linked neurodevelopmental disorder with recurrent facial gestalt.
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Shepherdson JL, Hutchison K, Don DW, McGillivray G, Choi TI, Allan CA, Amor DJ, Banka S, Basel DG, Buch LD, Carere DA, Carroll R, Clayton-Smith J, Crawford A, Dunø M, Faivre L, Gilfillan CP, Gold NB, Gripp KW, Hobson E, Holtz AM, Innes AM, Isidor B, Jackson A, Katsonis P, Amel Riazat Kesh L, Küry S, Lecoquierre F, Lockhart P, Maraval J, Matsumoto N, McCarrier J, McCarthy J, Miyake N, Moey LH, Németh AH, Østergaard E, Patel R, Pope K, Posey JE, Schnur RE, Shaw M, Stolerman E, Taylor JP, Wadman E, Wakeling E, White SM, Wong LC, Lupski JR, Lichtarge O, Corbett MA, Gecz J, Nicolet CM, Farnham PJ, Kim CH, and Shinawi M
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- Male, Female, Animals, Humans, Zebrafish genetics, Mutation, Missense genetics, Transcription Factors genetics, Phenotype, Intellectual Disability pathology, Hyperparathyroidism, Neurodevelopmental Disorders genetics
- Abstract
Pathogenic variants in multiple genes on the X chromosome have been implicated in syndromic and non-syndromic intellectual disability disorders. ZFX on Xp22.11 encodes a transcription factor that has been linked to diverse processes including oncogenesis and development, but germline variants have not been characterized in association with disease. Here, we present clinical and molecular characterization of 18 individuals with germline ZFX variants. Exome or genome sequencing revealed 11 variants in 18 subjects (14 males and 4 females) from 16 unrelated families. Four missense variants were identified in 11 subjects, with seven truncation variants in the remaining individuals. Clinical findings included developmental delay/intellectual disability, behavioral abnormalities, hypotonia, and congenital anomalies. Overlapping and recurrent facial features were identified in all subjects, including thickening and medial broadening of eyebrows, variations in the shape of the face, external eye abnormalities, smooth and/or long philtrum, and ear abnormalities. Hyperparathyroidism was found in four families with missense variants, and enrichment of different tumor types was observed. In molecular studies, DNA-binding domain variants elicited differential expression of a small set of target genes relative to wild-type ZFX in cultured cells, suggesting a gain or loss of transcriptional activity. Additionally, a zebrafish model of ZFX loss displayed an altered behavioral phenotype, providing additional evidence for the functional significance of ZFX. Our clinical and experimental data support that variants in ZFX are associated with an X-linked intellectual disability syndrome characterized by a recurrent facial gestalt, neurocognitive and behavioral abnormalities, and an increased risk for congenital anomalies and hyperparathyroidism., Competing Interests: Declaration of interests D.A.C. and R.E.S. are employees of GeneDx, LLC. A.C. and J.P.T. are employees and shareholders of Illumina, Inc. L.D.B. performs advisory board, consulting, and speaking arrangement work unrelated to the present study for Sanofi S.A., Horizon Therapeutics, Amicus Therapeutics, and Chiesi Farmaceutici S.p.A. N.B.G. has received personal fees from Pfizer Inc. and RCG Consulting for work unrelated to the present study. J.R.L. has stock ownership in 23andMe and is a paid consultant to Genome International., (Copyright © 2024 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)
- Published
- 2024
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12. m 6 A epitranscriptome analysis reveals differentially methylated transcripts that drive early chemoresistance in bladder cancer.
- Author
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Hodara E, Mades A, Swartz L, Iqbal M, Xu T, Bsteh D, Farnham PJ, Rhie SK, and Goldkorn A
- Abstract
N
6 -Methyladenosine (m6 A) RNA modifications dynamically regulate messenger RNA processing, differentiation and cell fate. Given these functions, we hypothesized that m6 A modifications play a role in the transition to chemoresistance. To test this, we took an agnostic discovery approach anchored directly to chemoresistance rather than to any particular m6 A effector protein. Specifically, we used methyl-RNA immunoprecipitation followed by sequencing (MeRIP-seq) in parallel with RNA sequencing to identify gene transcripts that were both differentially methylated and differentially expressed between cisplatin-sensitive and cisplatin-resistant bladder cancer (BC) cells. We filtered and prioritized these genes using clinical and functional database tools, and then validated several of the top candidates via targeted quantitative polymerase chain reaction (qPCR) and MeRIP-PCR. In cisplatin-resistant cells, SLC7A11 transcripts had decreased methylation associated with decreased m6 A reader YTHDF3 binding, prolonged RNA stability, and increased RNA and protein levels, leading to reduced ferroptosis and increased survival. Consistent with this, cisplatin-sensitive BC cell lines and patient-derived organoids exposed to cisplatin for as little as 48 h exhibited similar mechanisms of SLC7A11 upregulation and chemoresistance, trends that were also reflected in public cancer survival databases. Collectively, these findings highlight epitranscriptomic plasticity as a mechanism of rapid chemoresistance and a potential therapeutic target., (© The Author(s) 2023. Published by Oxford University Press on behalf of NAR Cancer.)- Published
- 2023
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13. Large-scale manipulation of promoter DNA methylation reveals context-specific transcriptional responses and stability.
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de Mendoza A, Nguyen TV, Ford E, Poppe D, Buckberry S, Pflueger J, Grimmer MR, Stolzenburg S, Bogdanovic O, Oshlack A, Farnham PJ, Blancafort P, and Lister R
- Subjects
- Chromatin, CpG Islands, DNA metabolism, Humans, Promoter Regions, Genetic, Transcription Factors metabolism, DNA (Cytosine-5-)-Methyltransferases genetics, DNA (Cytosine-5-)-Methyltransferases metabolism, DNA Methylation
- Abstract
Background: Cytosine DNA methylation is widely described as a transcriptional repressive mark with the capacity to silence promoters. Epigenome engineering techniques enable direct testing of the effect of induced DNA methylation on endogenous promoters; however, the downstream effects have not yet been comprehensively assessed., Results: Here, we simultaneously induce methylation at thousands of promoters in human cells using an engineered zinc finger-DNMT3A fusion protein, enabling us to test the effect of forced DNA methylation upon transcription, chromatin accessibility, histone modifications, and DNA methylation persistence after the removal of the fusion protein. We find that transcriptional responses to DNA methylation are highly context-specific, including lack of repression, as well as cases of increased gene expression, which appears to be driven by the eviction of methyl-sensitive transcriptional repressors. Furthermore, we find that some regulatory networks can override DNA methylation and that promoter methylation can cause alternative promoter usage. DNA methylation deposited at promoter and distal regulatory regions is rapidly erased after removal of the zinc finger-DNMT3A fusion protein, in a process combining passive and TET-mediated demethylation. Finally, we demonstrate that induced DNA methylation can exist simultaneously on promoter nucleosomes that possess the active histone modification H3K4me3, or DNA bound by the initiated form of RNA polymerase II., Conclusions: These findings have important implications for epigenome engineering and demonstrate that the response of promoters to DNA methylation is more complex than previously appreciated., (© 2022. The Author(s).)
- Published
- 2022
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14. Author Correction: Expanded encyclopaedias of DNA elements in the human and mouse genomes.
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Moore JE, Purcaro MJ, Pratt HE, Epstein CB, Shoresh N, Adrian J, Kawli T, Davis CA, Dobin A, Kaul R, Halow J, Van Nostrand EL, Freese P, Gorkin DU, Shen Y, He Y, Mackiewicz M, Pauli-Behn F, Williams BA, Mortazavi A, Keller CA, Zhang XO, Elhajjajy SI, Huey J, Dickel DE, Snetkova V, Wei X, Wang X, Rivera-Mulia JC, Rozowsky J, Zhang J, Chhetri SB, Zhang J, Victorsen A, White KP, Visel A, Yeo GW, Burge CB, Lécuyer E, Gilbert DM, Dekker J, Rinn J, Mendenhall EM, Ecker JR, Kellis M, Klein RJ, Noble WS, Kundaje A, Guigó R, Farnham PJ, Cherry JM, Myers RM, Ren B, Graveley BR, Gerstein MB, Pennacchio LA, Snyder MP, Bernstein BE, Wold B, Hardison RC, Gingeras TR, Stamatoyannopoulos JA, and Weng Z
- Published
- 2022
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15. FOXC1 Binds Enhancers and Promotes Cisplatin Resistance in Bladder Cancer.
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Lu YT, Xu T, Iqbal M, Hsieh TC, Luo Z, Liang G, Farnham PJ, Rhie SK, and Goldkorn A
- Abstract
Chemotherapy resistance is traditionally attributed to DNA mutations that confer a survival advantage under drug selection pressure. However, in bladder cancer and other malignancies, we and others have previously reported that cancer cells can convert spontaneously to an aggressive drug-resistant phenotype without prior drug selection or mutational events. In the current work, we explored possible epigenetic mechanisms behind this phenotypic plasticity. Using Hoechst dye exclusion and flow cytometry, we isolated the aggressive drug-resistant cells and analyzed their chromatin accessibility at regulatory elements. Compared to the rest of the cancer cell population, the aggressive drug-resistant cells exhibited enhancer accessibility changes. In particular, we found that differentially accessible enhancers were enriched for the FOXC1 transcription factor motif, and that FOXC1 was the most significantly overexpressed gene in aggressive drug-resistant cells. ChIP-seq analysis revealed that differentially accessible enhancers in aggressive drug-resistant cells had a higher FOXC1 binding, which regulated the expression of adjacent cancer-relevant genes like ABCB1 and ID3 . Accordingly, cisplatin treatment of bladder cancer cells led to an increased FOXC1 expression, which mediated cell survival and conversion to a drug-resistant phenotype. Collectively, these findings suggest that FOXC1 contributes to phenotypic plasticity by binding enhancers and promoting a mutation-independent shift towards cisplatin resistance in bladder cancer.
- Published
- 2022
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16. TENET 2.0: Identification of key transcriptional regulators and enhancers in lung adenocarcinoma.
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Mullen DJ, Yan C, Kang DS, Zhou B, Borok Z, Marconett CN, Farnham PJ, Offringa IA, and Rhie SK
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- Adenocarcinoma genetics, Adult, Aged, Cell Cycle Proteins genetics, Epigenomics, Forkhead Box Protein M1 genetics, Gene Expression Regulation, Neoplastic genetics, Genes, Homeobox, Humans, Lung metabolism, Lung Neoplasms genetics, Male, Middle Aged, Regulatory Sequences, Nucleic Acid genetics, Adenocarcinoma of Lung genetics, Epigenesis, Genetic genetics, Regulatory Elements, Transcriptional genetics
- Abstract
Lung cancer is the leading cause of cancer-related death and lung adenocarcinoma is its most common subtype. Although genetic alterations have been identified as drivers in subsets of lung adenocarcinoma, they do not fully explain tumor development. Epigenetic alterations have been implicated in the pathogenesis of tumors. To identify epigenetic alterations driving lung adenocarcinoma, we used an improved version of the Tracing Enhancer Networks using Epigenetic Traits method (TENET 2.0) in primary normal lung and lung adenocarcinoma cells. We found over 32,000 enhancers that appear differentially activated between normal lung and lung adenocarcinoma. Among the identified transcriptional regulators inactivated in lung adenocarcinoma vs. normal lung, NKX2-1 was linked to a large number of silenced enhancers. Among the activated transcriptional regulators identified, CENPA, FOXM1, and MYBL2 were linked to numerous cancer-specific enhancers. High expression of CENPA, FOXM1, and MYBL2 is particularly observed in a subgroup of lung adenocarcinomas and is associated with poor patient survival. Notably, CENPA, FOXM1, and MYBL2 are also key regulators of cancer-specific enhancers in breast adenocarcinoma of the basal subtype, but they are associated with distinct sets of activated enhancers. We identified individual lung adenocarcinoma enhancers linked to CENPA, FOXM1, or MYBL2 that were associated with poor patient survival. Knockdown experiments of FOXM1 and MYBL2 suggest that these factors regulate genes involved in controlling cell cycle progression and cell division. For example, we found that expression of TK1, a potential target gene of a MYBL2-linked enhancer, is associated with poor patient survival. Identification and characterization of key transcriptional regulators and associated enhancers in lung adenocarcinoma provides important insights into the deregulation of lung adenocarcinoma epigenomes, highlighting novel potential targets for clinical intervention., Competing Interests: The authors have declared that no competing interests exist.
- Published
- 2020
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17. Expanded encyclopaedias of DNA elements in the human and mouse genomes.
- Author
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Moore JE, Purcaro MJ, Pratt HE, Epstein CB, Shoresh N, Adrian J, Kawli T, Davis CA, Dobin A, Kaul R, Halow J, Van Nostrand EL, Freese P, Gorkin DU, Shen Y, He Y, Mackiewicz M, Pauli-Behn F, Williams BA, Mortazavi A, Keller CA, Zhang XO, Elhajjajy SI, Huey J, Dickel DE, Snetkova V, Wei X, Wang X, Rivera-Mulia JC, Rozowsky J, Zhang J, Chhetri SB, Zhang J, Victorsen A, White KP, Visel A, Yeo GW, Burge CB, Lécuyer E, Gilbert DM, Dekker J, Rinn J, Mendenhall EM, Ecker JR, Kellis M, Klein RJ, Noble WS, Kundaje A, Guigó R, Farnham PJ, Cherry JM, Myers RM, Ren B, Graveley BR, Gerstein MB, Pennacchio LA, Snyder MP, Bernstein BE, Wold B, Hardison RC, Gingeras TR, Stamatoyannopoulos JA, and Weng Z
- Subjects
- Animals, Chromatin genetics, Chromatin metabolism, DNA chemistry, DNA Footprinting, DNA Methylation genetics, DNA Replication Timing, Deoxyribonuclease I metabolism, Genome, Human, Histones metabolism, Humans, Mice, Mice, Transgenic, RNA-Binding Proteins genetics, Transcription, Genetic genetics, Transposases metabolism, DNA genetics, Databases, Genetic, Genome genetics, Genomics, Molecular Sequence Annotation, Registries, Regulatory Sequences, Nucleic Acid genetics
- Abstract
The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (https://www.encodeproject.org), including phase II ENCODE
1 and Roadmap Epigenomics2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; http://screen.encodeproject.org) to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes.- Published
- 2020
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18. Characterization of the ZFX family of transcription factors that bind downstream of the start site of CpG island promoters.
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Ni W, Perez AA, Schreiner S, Nicolet CM, and Farnham PJ
- Subjects
- Alleles, Base Pairing, Base Sequence, DNA-Binding Proteins genetics, Female, Gene Deletion, HEK293 Cells, Humans, Kruppel-Like Transcription Factors genetics, Male, Transcriptome, Zinc Fingers, CpG Islands genetics, DNA-Binding Proteins metabolism, Kruppel-Like Transcription Factors metabolism, Promoter Regions, Genetic, Transcription Initiation Site
- Abstract
Our study focuses on a family of ubiquitously expressed human C2H2 zinc finger proteins comprised of ZFX, ZFY and ZNF711. Although their protein structure suggests that ZFX, ZFY and ZNF711 are transcriptional regulators, the mechanisms by which they influence transcription have not yet been elucidated. We used CRISPR-mediated deletion to create bi-allelic knockouts of ZFX and/or ZNF711 in female HEK293T cells (which naturally lack ZFY). We found that loss of either ZFX or ZNF711 reduced cell growth and that the double knockout cells have major defects in proliferation. RNA-seq analysis revealed that thousands of genes showed altered expression in the double knockout clones, suggesting that these TFs are critical regulators of the transcriptome. To gain insight into how these TFs regulate transcription, we created mutant ZFX proteins and analyzed them for DNA binding and transactivation capability. We found that zinc fingers 11-13 are necessary and sufficient for DNA binding and, in combination with the N terminal region, constitute a functional transactivator. Our functional analyses of the ZFX family provides important new insights into transcriptional regulation in human cells by members of the large, but under-studied family of C2H2 zinc finger proteins., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)
- Published
- 2020
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19. Genome-wide analysis of HOXC4 and HOXC6 regulated genes and binding sites in prostate cancer cells.
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Luo Z and Farnham PJ
- Subjects
- Cell Line, Tumor, Homeodomain Proteins genetics, Humans, Male, Prostatic Neoplasms metabolism, Protein Binding, Transcriptional Activation, Transcriptome, Gene Expression Regulation, Neoplastic, Homeodomain Proteins metabolism, Prostatic Neoplasms genetics, Regulatory Elements, Transcriptional
- Abstract
Aberrant expression of HOXC6 and HOXC4 is commonly detected in prostate cancer. The high expression of these transcription factors is associated with aggressive prostate cancer and can predict cancer recurrence after treatment. Thus, HOXC4 and HOXC6 are clinically relevant biomarkers of aggressive prostate cancer. However, the molecular mechanisms by which these HOXC genes contribute to prostate cancer is not yet understood. To begin to address the role of HOXC4 and HOXC6 in prostate cancer, we performed RNA-seq analyses before and after siRNA-mediated knockdown of HOXC4 and/or HOXC6 and also performed ChIP-seq to identify genomic binding sites for both of these transcription factors. Our studies demonstrate that HOXC4 and HOXC6 co-localize with HOXB13, FOXA1 and AR, three transcription factors previously shown to contribute to the development of prostate cancer. We suggest that the aberrantly upregulated HOXC4 and HOXC6 proteins may compete with HOXB13 for binding sites, thus altering the prostate transcriptome. This competition model may be applicable to many different human cancers that display increased expression of a HOX transcription factor., Competing Interests: The authors have declared that no competing interests exist.
- Published
- 2020
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20. A high-resolution 3D epigenomic map reveals insights into the creation of the prostate cancer transcriptome.
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Rhie SK, Perez AA, Lay FD, Schreiner S, Shi J, Polin J, and Farnham PJ
- Subjects
- Cell Line, Tumor, Chromatin metabolism, Enhancer Elements, Genetic, Epigenesis, Genetic, Genetic Loci, Histone Code genetics, Humans, Male, Promoter Regions, Genetic, Receptors, Androgen genetics, Epigenomics, Prostatic Neoplasms genetics, Transcriptome genetics
- Abstract
To better understand the impact of chromatin structure on regulation of the prostate cancer transcriptome, we develop high-resolution chromatin interaction maps in normal and prostate cancer cells using in situ Hi-C. By combining the in situ Hi-C data with active and repressive histone marks, CTCF binding sites, nucleosome-depleted regions, and transcriptome profiling, we identify topologically associating domains (TADs) that change in size and epigenetic states between normal and prostate cancer cells. Moreover, we identify normal and prostate cancer-specific enhancer-promoter loops and involved transcription factors. For example, we show that FOXA1 is enriched in prostate cancer-specific enhancer-promoter loop anchors. We also find that the chromatin structure surrounding the androgen receptor (AR) locus is altered in the prostate cancer cells with many cancer-specific enhancer-promoter loops. This creation of 3D epigenomic maps enables a better understanding of prostate cancer biology and mechanisms of gene regulation.
- Published
- 2019
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21. The prostate cancer risk variant rs55958994 regulates multiple gene expression through extreme long-range chromatin interaction to control tumor progression.
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Qian Y, Zhang L, Cai M, Li H, Xu H, Yang H, Zhao Z, Rhie SK, Farnham PJ, Shi J, and Lu W
- Subjects
- Alleles, Base Sequence, Carcinogenesis genetics, Carcinogenesis pathology, Cell Line, Tumor, Enhancer Elements, Genetic, Humans, Male, Phenotype, Risk Factors, Sequence Deletion genetics, Transcriptome genetics, Chromatin metabolism, Disease Progression, Gene Expression Regulation, Neoplastic, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide genetics, Prostatic Neoplasms genetics, Prostatic Neoplasms pathology
- Abstract
Genome-wide association studies identified single-nucleotide polymorphism (SNP) rs55958994 as a significant variant associated with increased susceptibility to prostate cancer. However, the mechanisms by which this SNP mediates increased risk to cancer are still unknown. In this study, we show that this variant is located in an enhancer active in prostate cancer cells. Deletion of this enhancer from prostate tumor cells resulted in decreased tumor initiation, tumor growth, and invasive migration, as well as a loss of stem-like cells. Using a combination of capture chromosome conformation capture (Capture-C) and RNA sequencing, we identified genes on the same and different chromosomes as targets regulated by the enhancer. Furthermore, we show that expression of individual candidate target genes in an enhancer-deleted cell line rescued different aspects of tumorigenesis. Our data suggest that the rs55958994-associated enhancer affects prostate cancer progression by influencing expression of multiple genes via long-range chromatin interactions.
- Published
- 2019
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22. Ezh2-dCas9 and KRAB-dCas9 enable engineering of epigenetic memory in a context-dependent manner.
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O'Geen H, Bates SL, Carter SS, Nisson KA, Halmai J, Fink KD, Rhie SK, Farnham PJ, and Segal DJ
- Subjects
- Animals, CRISPR-Cas Systems, DNA (Cytosine-5-)-Methyltransferases genetics, DNA (Cytosine-5-)-Methyltransferases metabolism, DNA Methylation, DNA Methyltransferase 3A, Enhancer of Zeste Homolog 2 Protein metabolism, Epigenesis, Genetic, Gene Editing, Genetic Engineering methods, HCT116 Cells, Histone Methyltransferases genetics, Histone Methyltransferases metabolism, Histones metabolism, Humans, Mice, Promoter Regions, Genetic, RNA, Guide, CRISPR-Cas Systems genetics, Receptor, ErbB-2 genetics, Receptor, ErbB-2 metabolism, Repressor Proteins metabolism, Transcription Factors metabolism, Enhancer of Zeste Homolog 2 Protein genetics, Repressor Proteins genetics
- Abstract
Background: Rewriting of the epigenome has risen as a promising alternative to gene editing for precision medicine. In nature, epigenetic silencing can result in complete attenuation of target gene expression over multiple mitotic divisions. However, persistent repression has been difficult to achieve in a predictable manner using targeted systems., Results: Here, we report that persistent epigenetic memory required both a DNA methyltransferase (DNMT3A-dCas9) and a histone methyltransferase (Ezh2-dCas9 or KRAB-dCas9). We demonstrate that the histone methyltransferase requirement can be locus specific. Co-targeting Ezh2-dCas9, but not KRAB-dCas9, with DNMT3A-dCas9 and DNMT3L induced long-term HER2 repression over at least 50 days (approximately 57 cell divisions) and triggered an epigenetic switch to a heterochromatic environment. An increase in H3K27 trimethylation and DNA methylation was stably maintained and accompanied by a sustained loss of H3K27 acetylation. Interestingly, substitution of Ezh2-dCas9 with KRAB-dCas9 enabled long-term repression at some target genes (e.g., SNURF) but not at HER2, at which H3K9me3 and DNA methylation were transiently acquired and subsequently lost. Off-target DNA hypermethylation occurred at many individual CpG sites but rarely at multiple CpGs in a single promoter, consistent with no detectable effect on transcription at the off-target loci tested. Conversely, robust hypermethylation was observed at HER2. We further demonstrated that Ezh2-dCas9 required full-length DNMT3L for maximal activity and that co-targeting DNMT3L was sufficient for persistent repression by Ezh2-dCas9 or KRAB-dCas9., Conclusions: These data demonstrate that targeting different combinations of histone and DNA methyltransferases is required to achieve maximal repression at different loci. Fine-tuning of targeting tools is a necessity to engineer epigenetic memory at any given locus in any given cell type.
- Published
- 2019
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23. The Enigmatic HOX Genes: Can We Crack Their Code?
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Luo Z, Rhie SK, and Farnham PJ
- Abstract
Homeobox genes (HOX) are a large family of transcription factors that direct the formation of many body structures during early embryonic development. There are 39 genes in the subgroup of homeobox genes that constitute the human HOX gene family. Correct embryonic development of flies and vertebrates is, in part, mediated by the unique and highly regulated expression pattern of the HOX genes. Disruptions in these fine-tuned regulatory mechanisms can lead to developmental problems and to human diseases such as cancer. Unfortunately, the molecular mechanisms of action of the HOX family of transcription factors are severely under-studied, likely due to idiosyncratic details of their structure, expression, and function. We suggest that a concerted and collaborative effort to identify interacting protein partners, produce genome-wide binding profiles, and develop HOX network inhibitors in a variety of human cell types will lead to a deeper understanding of human development and disease. Within, we review the technological challenges and possible approaches needed to achieve this goal.
- Published
- 2019
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24. Three-dimensional analysis reveals altered chromatin interaction by enhancer inhibitors harbors TCF7L2-regulated cancer gene signature.
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Gerrard DL, Wang Y, Gaddis M, Zhou Y, Wang J, Witt H, Lin S, Farnham PJ, Jin VX, and Frietze SE
- Subjects
- Cell Line, Tumor, Chromatin chemistry, Chromatin genetics, Chromatin Assembly and Disassembly, Chromosome Mapping, Epigenesis, Genetic drug effects, Epigenomics, Gene Expression Regulation, Neoplastic drug effects, Humans, Nitrobenzenes, Pancreatic Neoplasms metabolism, Pyrazolones, Transcription Factor 7-Like 2 Protein genetics, Benzoates pharmacology, Bridged Bicyclo Compounds, Heterocyclic pharmacology, Chromatin metabolism, Gene Regulatory Networks drug effects, Pancreatic Neoplasms genetics, Pyrazoles pharmacology, Pyrimidinones pharmacology, Transcription Factor 7-Like 2 Protein metabolism
- Abstract
Distal regulatory elements influence the activity of gene promoters through chromatin looping. Chromosome conformation capture (3C) methods permit identification of chromatin contacts across different regions of the genome. However, due to limitations in the resolution of these methods, the detection of functional chromatin interactions remains a challenge. In the current study, we employ an integrated approach to define and characterize the functional chromatin contacts of human pancreatic cancer cells. We applied tethered chromatin capture to define classes of chromatin domains on a genome-wide scale. We identified three types of structural domains (topologically associated, boundary, and gap) and investigated the functional relationships of these domains with respect to chromatin state and gene expression. We uncovered six distinct sub-domains associated with epigenetic states. Interestingly, specific epigenetically active domains are sensitive to treatment with histone acetyltransferase (HAT) inhibitors and decrease in H3K27 acetylation levels. To examine whether the subdomains that change upon drug treatment are functionally linked to transcription factor regulation, we compared TCF7L2 chromatin binding and gene regulation to HAT inhibition. We identified a subset of coding RNA genes that together can stratify pancreatic cancer patients into distinct survival groups. Overall, this study describes a process to evaluate the functional features of chromosome architecture and reveals the impact of epigenetic inhibitors on chromosome architecture and identifies genes that may provide insight into disease outcome., (© 2018 Wiley Periodicals, Inc.)
- Published
- 2019
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25. Using 3D epigenomic maps of primary olfactory neuronal cells from living individuals to understand gene regulation.
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Rhie SK, Schreiner S, Witt H, Armoskus C, Lay FD, Camarena A, Spitsyna VN, Guo Y, Berman BP, Evgrafov OV, Knowles JA, and Farnham PJ
- Subjects
- Binding Sites, Chromatin Immunoprecipitation, Chromosome Mapping, Computational Biology methods, Enhancer Elements, Genetic, Gene Expression Profiling, Genetic Variation, Heterochromatin genetics, High-Throughput Nucleotide Sequencing, Humans, Nucleotide Motifs, Protein Binding, Regulatory Sequences, Nucleic Acid, Transcription Factors metabolism, Transcriptome, Workflow, Epigenesis, Genetic, Epigenomics methods, Gene Expression Regulation, Olfactory Receptor Neurons metabolism
- Abstract
As part of PsychENCODE, we developed a three-dimensional (3D) epigenomic map of primary cultured neuronal cells derived from olfactory neuroepithelium (CNON). We mapped topologically associating domains and high-resolution chromatin interactions using Hi-C and identified regulatory elements using chromatin immunoprecipitation and nucleosome positioning assays. Using epigenomic datasets from biopsies of 63 living individuals, we found that epigenetic marks at distal regulatory elements are more variable than marks at proximal regulatory elements. By integrating genotype and metadata, we identified enhancers that have different levels corresponding to differences in genetic variation, gender, smoking, and schizophrenia. Motif searches revealed that many CNON enhancers are bound by neuronal-related transcription factors. Last, we combined 3D epigenomic maps and gene expression profiles to predict enhancer-target gene interactions on a genome-wide scale. This study not only provides a framework for understanding individual epigenetic variation using a primary cell model system but also contributes valuable data resources for epigenomic studies of neuronal epithelium.
- Published
- 2018
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26. CRISPR-mediated deletion of prostate cancer risk-associated CTCF loop anchors identifies repressive chromatin loops.
- Author
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Guo Y, Perez AA, Hazelett DJ, Coetzee GA, Rhie SK, and Farnham PJ
- Subjects
- Acetylation, Cell Line, Tumor, Enhancer Elements, Genetic genetics, Histones metabolism, Humans, Lysine metabolism, Male, Polymorphism, Single Nucleotide genetics, Risk Factors, Small-Conductance Calcium-Activated Potassium Channels genetics, Up-Regulation genetics, CCCTC-Binding Factor metabolism, Chromatin metabolism, Clustered Regularly Interspaced Short Palindromic Repeats genetics, Gene Deletion, Prostatic Neoplasms genetics
- Abstract
Background: Recent genome-wide association studies (GWAS) have identified more than 100 loci associated with increased risk of prostate cancer, most of which are in non-coding regions of the genome. Understanding the function of these non-coding risk loci is critical to elucidate the genetic susceptibility to prostate cancer., Results: We generate genome-wide regulatory element maps and performed genome-wide chromosome confirmation capture assays (in situ Hi-C) in normal and tumorigenic prostate cells. Using this information, we annotate the regulatory potential of 2,181 fine-mapped prostate cancer risk-associated SNPs and predict a set of target genes that are regulated by prostate cancer risk-related H3K27Ac-mediated loops. We next identify prostate cancer risk-associated CTCF sites involved in long-range chromatin loops. We use CRISPR-mediated deletion to remove prostate cancer risk-associated CTCF anchor regions and the CTCF anchor regions looped to the prostate cancer risk-associated CTCF sites, and we observe up to 100-fold increases in expression of genes within the loops when the prostate cancer risk-associated CTCF anchor regions are deleted., Conclusions: We identify GWAS risk loci involved in long-range loops that function to repress gene expression within chromatin loops. Our studies provide new insights into the genetic susceptibility to prostate cancer.
- Published
- 2018
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27. ZFX acts as a transcriptional activator in multiple types of human tumors by binding downstream from transcription start sites at the majority of CpG island promoters.
- Author
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Rhie SK, Yao L, Luo Z, Witt H, Schreiner S, Guo Y, Perez AA, and Farnham PJ
- Subjects
- Humans, Binding Sites, Cell Line, Tumor, DNA Methylation, Neoplasms genetics, Neoplasms metabolism, Protein Binding, Transcriptional Activation, CpG Islands, Gene Expression Regulation, Neoplastic, Promoter Regions, Genetic, Transcription Initiation Site, Kruppel-Like Transcription Factors genetics, Kruppel-Like Transcription Factors metabolism
- Abstract
High expression of the transcription factor ZFX is correlated with proliferation, tumorigenesis, and patient survival in multiple types of human cancers. However, the mechanism by which ZFX influences transcriptional regulation has not been determined. We performed ChIP-seq in four cancer cell lines (representing kidney, colon, prostate, and breast cancers) to identify ZFX binding sites throughout the human genome. We identified roughly 9000 ZFX binding sites and found that most of the sites are in CpG island promoters. Moreover, genes with promoters bound by ZFX are expressed at higher levels than genes with promoters not bound by ZFX. To determine if ZFX contributes to regulation of the promoters to which it is bound, we performed RNA-seq analysis after knockdown of ZFX by siRNA in prostate and breast cancer cells. Many genes with promoters bound by ZFX were down-regulated upon ZFX knockdown, supporting the hypothesis that ZFX acts as a transcriptional activator. Surprisingly, ZFX binds at +240 bp downstream from the TSS of the responsive promoters. Using Nucleosome Occupancy and Methylome Sequencing (NOMe-seq), we show that ZFX binds between the open chromatin region at the TSS and the first downstream nucleosome, suggesting that ZFX may play a critical role in promoter architecture. We have also shown that a closely related zinc finger protein ZNF711 has a similar binding pattern at CpG island promoters, but ZNF711 may play a subordinate role to ZFX. This functional characterization of ZFX provides important new insights into transcription, chromatin structure, and the regulation of the cancer transcriptome., (© 2018 Rhie et al.; Published by Cold Spring Harbor Laboratory Press.)
- Published
- 2018
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28. Defining Regulatory Elements in the Human Genome Using Nucleosome Occupancy and Methylome Sequencing (NOMe-Seq).
- Author
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Rhie SK, Schreiner S, and Farnham PJ
- Subjects
- Cell Nucleus chemistry, Cell Nucleus genetics, Chromatin chemistry, Chromatin genetics, CpG Islands, Humans, Nucleosomes chemistry, Promoter Regions, Genetic, Sequence Analysis, DNA, Sulfites chemistry, DNA Methylation, Enhancer Elements, Genetic genetics, Genome, Human genetics, Insulator Elements genetics, Nucleosomes genetics
- Abstract
NOMe-seq (nucleosome occupancy and methylome sequencing) identifies nucleosome-depleted regions that correspond to promoters, enhancers, and insulators. The NOMe-seq method is based on the treatment of chromatin with the M.CviPI methyltransferase, which methylates GpC dinucleotides that are not protected by nucleosomes or other proteins that are tightly bound to the chromatin (GpC
m does not occur in the human genome and therefore there is no endogenous background of GpCm ). Following bisulfite treatment of the M.CviPI-methylated chromatin (which converts unmethylated Cs to Ts and thus allows the distinction of GpC from GpCm ) and subsequent genomic sequencing, nucleosome-depleted regions can be ascertained on a genome-wide scale. The bisulfite treatment also allows the distinction of CpG from Cm pG (most endogenous methylation occurs at CpG dinucleotides) and thus the endogenous methylation status of the genome can also be obtained in the same sequencing reaction. Importantly, open chromatin is expected to have high levels of GpCm but low levels of Cm pG; thus, each of the two separate methylation analyses serve as independent (but opposite) measures which provide matching chromatin designations for each regulatory element.NOMe-seq has advantages over ChIP-seq for identification of regulatory elements because it is not reliant upon knowing the exact modifications on the surrounding nucleosomes. Also, NOMe-seq has advantages over DHS (DNase hypersensitive site)-seq, FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements)-seq, and ATAC (Assay for Transposase-Accessible Chromatin)-seq because it also gives positioning information for several nucleosomes on either side of each open regulatory element. Here, we provide a detailed protocol for NOMe-seq that begins with the isolation of chromatin, followed by methylation of GpCs with M.CviPI and treatment with bisulfite, and ending with the creation of next generation sequencing libraries. We also include sequencing QC analysis metrics and bioinformatics steps that can be used to identify nucleosome-depleted regions throughout the genome.- Published
- 2018
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29. A Prostate Cancer Risk Element Functions as a Repressive Loop that Regulates HOXA13.
- Author
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Luo Z, Rhie SK, Lay FD, and Farnham PJ
- Subjects
- CRISPR-Cas Systems genetics, Cell Line, Tumor, Co-Repressor Proteins, DNA-Binding Proteins, Genetic Loci, Homeodomain Proteins genetics, Humans, Male, Neoplasm Proteins genetics, Polymorphism, Single Nucleotide, Prostatic Neoplasms genetics, Prostatic Neoplasms metabolism, Prostatic Neoplasms pathology, RNA chemistry, RNA isolation & purification, RNA metabolism, RNA, Long Noncoding genetics, RNA, Long Noncoding metabolism, Risk, Sequence Analysis, RNA, Transcriptome, Homeodomain Proteins metabolism
- Abstract
Prostate cancer (PCa) is the leading cancer among men in the United States, with genetic factors contributing to ∼42% of the susceptibility to PCa. We analyzed a PCa risk region located at 7p15.2 to gain insight into the mechanisms by which this noncoding region may affect gene regulation and contribute to PCa risk. We performed Hi-C analysis and demonstrated that this region has long-range interactions with the HOXA locus, located ∼873 kb away. Using the CRISPR/Cas9 system, we deleted a 4-kb region encompassing several PCa risk-associated SNPs and performed RNA-seq to investigate transcriptomic changes in prostate cells lacking the regulatory element. Our results suggest that the risk element affects the expression of HOXA13 and HOTTIP, but not other genes in the HOXA locus, via a repressive loop. Forced expression of HOXA13 was performed to gain further insight into the mechanisms by which this risk element affects PCa risk., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)
- Published
- 2017
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30. dCas9-based epigenome editing suggests acquisition of histone methylation is not sufficient for target gene repression.
- Author
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O'Geen H, Ren C, Nicolet CM, Perez AA, Halmai J, Le VM, Mackay JP, Farnham PJ, and Segal DJ
- Subjects
- Chromatin metabolism, DNA (Cytosine-5-)-Methyltransferases genetics, DNA (Cytosine-5-)-Methyltransferases metabolism, DNA Methyltransferase 3A, Endonucleases metabolism, Gene Editing, HCT116 Cells, HEK293 Cells, Histocompatibility Antigens genetics, Histocompatibility Antigens metabolism, Histone-Lysine N-Methyltransferase genetics, Histone-Lysine N-Methyltransferase metabolism, Histones metabolism, Humans, Methylation, Methyltransferases genetics, Methyltransferases metabolism, Nuclear Proteins genetics, Nuclear Proteins metabolism, Promoter Regions, Genetic, RNA, Messenger genetics, RNA, Messenger metabolism, Receptor, ErbB-2 genetics, Receptor, ErbB-2 metabolism, Recombinant Fusion Proteins genetics, Recombinant Fusion Proteins metabolism, Repressor Proteins genetics, Repressor Proteins metabolism, Transcription Factors genetics, Transcription Factors metabolism, Chromatin chemistry, Endonucleases genetics, Epigenomics methods, Gene Silencing, Histones genetics
- Abstract
Distinct epigenomic profiles of histone marks have been associated with gene expression, but questions regarding the causal relationship remain. Here we investigated the activity of a broad collection of genomically targeted epigenetic regulators that could write epigenetic marks associated with a repressed chromatin state (G9A, SUV39H1, Krüppel-associated box (KRAB), DNMT3A as well as the first targetable versions of Ezh2 and Friend of GATA-1 (FOG1)). dCas9 fusions produced target gene repression over a range of 0- to 10-fold that varied by locus and cell type. dCpf1 fusions were unable to repress gene expression. The most persistent gene repression required the action of several effector domains; however, KRAB-dCas9 did not contribute to persistence in contrast to previous reports. A 'direct tethering' strategy attaching the Ezh2 methyltransferase enzyme to dCas9, as well as a 'recruitment' strategy attaching the N-terminal 45 residues of FOG1 to dCas9 to recruit the endogenous nucleosome remodeling and deacetylase complex, were both successful in targeted deposition of H3K27me3. Surprisingly, however, repression was not correlated with deposition of either H3K9me3 or H3K27me3. Our results suggest that so-called repressive histone modifications are not sufficient for gene repression. The easily programmable dCas9 toolkit allowed precise control of epigenetic information and dissection of the relationship between the epigenome and gene regulation., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)
- Published
- 2017
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31. Identification of activated enhancers and linked transcription factors in breast, prostate, and kidney tumors by tracing enhancer networks using epigenetic traits.
- Author
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Rhie SK, Guo Y, Tak YG, Yao L, Shen H, Coetzee GA, Laird PW, and Farnham PJ
- Subjects
- Breast Neoplasms genetics, Breast Neoplasms metabolism, Breast Neoplasms pathology, Cell Line, Tumor, DNA Methylation, DNA-Binding Proteins genetics, Female, GATA3 Transcription Factor genetics, Gene Expression Regulation, Neoplastic, Gene Regulatory Networks, Histones genetics, Histones metabolism, Homeodomain Proteins antagonists & inhibitors, Homeodomain Proteins genetics, Homeodomain Proteins metabolism, Humans, Kidney Neoplasms genetics, Kidney Neoplasms metabolism, Kidney Neoplasms pathology, Male, Prostatic Neoplasms genetics, Prostatic Neoplasms metabolism, Prostatic Neoplasms pathology, RNA Interference, RNA, Small Interfering metabolism, Transcription Factors antagonists & inhibitors, Transcription Factors metabolism, Enhancer Elements, Genetic genetics, Epigenomics, Transcription Factors genetics
- Abstract
Background: Although technological advances now allow increased tumor profiling, a detailed understanding of the mechanisms leading to the development of different cancers remains elusive. Our approach toward understanding the molecular events that lead to cancer is to characterize changes in transcriptional regulatory networks between normal and tumor tissue. Because enhancer activity is thought to be critical in regulating cell fate decisions, we have focused our studies on distal regulatory elements and transcription factors that bind to these elements., Results: Using DNA methylation data, we identified more than 25,000 enhancers that are differentially activated in breast, prostate, and kidney tumor tissues, as compared to normal tissues. We then developed an analytical approach called Tracing Enhancer Networks using Epigenetic Traits that correlates DNA methylation levels at enhancers with gene expression to identify more than 800,000 genome-wide links from enhancers to genes and from genes to enhancers. We found more than 1200 transcription factors to be involved in these tumor-specific enhancer networks. We further characterized several transcription factors linked to a large number of enhancers in each tumor type, including GATA3 in non-basal breast tumors, HOXC6 and DLX1 in prostate tumors, and ZNF395 in kidney tumors. We showed that HOXC6 and DLX1 are associated with different clusters of prostate tumor-specific enhancers and confer distinct transcriptomic changes upon knockdown in C42B prostate cancer cells. We also discovered de novo motifs enriched in enhancers linked to ZNF395 in kidney tumors., Conclusions: Our studies characterized tumor-specific enhancers and revealed key transcription factors involved in enhancer networks for specific tumor types and subgroups. Our findings, which include a large set of identified enhancers and transcription factors linked to those enhancers in breast, prostate, and kidney cancers, will facilitate understanding of enhancer networks and mechanisms leading to the development of these cancers.
- Published
- 2016
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32. Effects on the transcriptome upon deletion of a distal element cannot be predicted by the size of the H3K27Ac peak in human cells.
- Author
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Tak YG, Hung Y, Yao L, Grimmer MR, Do A, Bhakta MS, O'Geen H, Segal DJ, and Farnham PJ
- Subjects
- Acetylation, Cell Proliferation, Colorectal Neoplasms genetics, Colorectal Neoplasms metabolism, Enhancer Elements, Genetic, Genome-Wide Association Study, HCT116 Cells, HEK293 Cells, Humans, Papillomavirus E7 Proteins genetics, Polymorphism, Single Nucleotide, Protein Processing, Post-Translational, Sequence Deletion, Gene Expression Regulation, Neoplastic, Histones metabolism, Transcriptome
- Abstract
Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with increased risk for colorectal cancer (CRC). A molecular understanding of the functional consequences of this genetic variation is complicated because most GWAS SNPs are located in non-coding regions. We used epigenomic information to identify H3K27Ac peaks in HCT116 colon cancer cells that harbor SNPs associated with an increased risk for CRC. Employing CRISPR/Cas9 nucleases, we deleted a CRC risk-associated H3K27Ac peak from HCT116 cells and observed large-scale changes in gene expression, resulting in decreased expression of many nearby genes. As a comparison, we showed that deletion of a robust H3K27Ac peak not associated with CRC had minimal effects on the transcriptome. Interestingly, although there is no H3K27Ac peak in HEK293 cells in the E7 region, deletion of this region in HEK293 cells decreased expression of several of the same genes that were downregulated in HCT116 cells, including the MYC oncogene. Accordingly, deletion of E7 causes changes in cell culture assays in HCT116 and HEK293 cells. In summary, we show that effects on the transcriptome upon deletion of a distal regulatory element cannot be predicted by the size or presence of an H3K27Ac peak., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)
- Published
- 2016
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33. 4C-seq revealed long-range interactions of a functional enhancer at the 8q24 prostate cancer risk locus.
- Author
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Cai M, Kim S, Wang K, Farnham PJ, Coetzee GA, and Lu W
- Subjects
- Cell Line, Tumor, Genome-Wide Association Study, Humans, Male, Chromosomes, Human, Pair 8 genetics, Chromosomes, Human, Pair 8 metabolism, Enhancer Elements, Genetic, Genetic Loci, Neoplasm Proteins genetics, Neoplasm Proteins metabolism, Prostatic Neoplasms genetics, Prostatic Neoplasms metabolism, Prostatic Neoplasms pathology, Transcription Factors genetics, Transcription Factors metabolism
- Abstract
Genome-wide association studies (GWAS) have identified >100 independent susceptibility loci for prostate cancer, including the hot spot at 8q24. However, how genetic variants at this locus confer disease risk hasn't been fully characterized. Using circularized chromosome conformation capture (4C) coupled with next-generation sequencing and an enhancer at 8q24 as "bait", we identified genome-wide partners interacting with this enhancer in cell lines LNCaP and C4-2B. These 4C-identified regions are distributed in open nuclear compartments, featuring active histone marks (H3K4me1, H3K4me2 and H3K27Ac). Transcription factors NKX3-1, FOXA1 and AR (androgen receptor) tend to occupy these 4C regions. We identified genes located at the interacting regions, and found them linked to positive regulation of mesenchymal cell proliferation in LNCaP and C4-2B, and several pathways (TGF beta signaling pathway in LNCaP and p53 pathway in C4-2B). Common genes (e.g. MYC and POU5F1B) were identified in both prostate cancer cell lines. However, each cell line also had exclusive genes (e.g. ELAC2 and PTEN in LNCaP and BRCA2 and ZFHX3 in C4-2B). In addition, BCL-2 identified in C4-2B might contribute to the progression of androgen-refractory prostate cancer. Overall, our work reveals key genes and pathways involved in prostate cancer onset and progression.
- Published
- 2016
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34. Making sense of GWAS: using epigenomics and genome engineering to understand the functional relevance of SNPs in non-coding regions of the human genome.
- Author
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Tak YG and Farnham PJ
- Abstract
Considerable progress towards an understanding of complex diseases has been made in recent years due to the development of high-throughput genotyping technologies. Using microarrays that contain millions of single-nucleotide polymorphisms (SNPs), Genome Wide Association Studies (GWASs) have identified SNPs that are associated with many complex diseases or traits. For example, as of February 2015, 2111 association studies have identified 15,396 SNPs for various diseases and traits, with the number of identified SNP-disease/trait associations increasing rapidly in recent years. However, it has been difficult for researchers to understand disease risk from GWAS results. This is because most GWAS-identified SNPs are located in non-coding regions of the genome. It is important to consider that the GWAS-identified SNPs serve only as representatives for all SNPs in the same haplotype block, and it is equally likely that other SNPs in high linkage disequilibrium (LD) with the array-identified SNPs are causal for the disease. Because it was hoped that disease-associated coding variants would be identified if the true casual SNPs were known, investigators have expanded their analyses using LD calculation and fine-mapping. However, such analyses also identified risk-associated SNPs located in non-coding regions. Thus, the GWAS field has been left with the conundrum as to how a single-nucleotide change in a non-coding region could confer increased risk for a specific disease. One possible answer to this puzzle is that the variant SNPs cause changes in gene expression levels rather than causing changes in protein function. This review provides a description of (1) advances in genomic and epigenomic approaches that incorporate functional annotation of regulatory elements to prioritize the disease risk-associated SNPs that are located in non-coding regions of the genome for follow-up studies, (2) various computational tools that aid in identifying gene expression changes caused by the non-coding disease-associated SNPs, and (3) experimental approaches to identify target genes of, and study the biological phenotypes conferred by, non-coding disease-associated SNPs.
- Published
- 2015
- Full Text
- View/download PDF
35. The PsychENCODE project.
- Author
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Akbarian S, Liu C, Knowles JA, Vaccarino FM, Farnham PJ, Crawford GE, Jaffe AE, Pinto D, Dracheva S, Geschwind DH, Mill J, Nairn AC, Abyzov A, Pochareddy S, Prabhakar S, Weissman S, Sullivan PF, State MW, Weng Z, Peters MA, White KP, Gerstein MB, Amiri A, Armoskus C, Ashley-Koch AE, Bae T, Beckel-Mitchener A, Berman BP, Coetzee GA, Coppola G, Francoeur N, Fromer M, Gao R, Grennan K, Herstein J, Kavanagh DH, Ivanov NA, Jiang Y, Kitchen RR, Kozlenkov A, Kundakovic M, Li M, Li Z, Liu S, Mangravite LM, Mattei E, Markenscoff-Papadimitriou E, Navarro FC, North N, Omberg L, Panchision D, Parikshak N, Poschmann J, Price AJ, Purcaro M, Reddy TE, Roussos P, Schreiner S, Scuderi S, Sebra R, Shibata M, Shieh AW, Skarica M, Sun W, Swarup V, Thomas A, Tsuji J, van Bakel H, Wang D, Wang Y, Wang K, Werling DM, Willsey AJ, Witt H, Won H, Wong CC, Wray GA, Wu EY, Xu X, Yao L, Senthil G, Lehner T, Sklar P, and Sestan N
- Subjects
- Animals, Brain pathology, Chromosome Mapping methods, Humans, Mental Disorders diagnosis, Transcriptome genetics, Brain physiology, Chromosome Mapping trends, Epigenesis, Genetic genetics, Genetic Code genetics, Mental Disorders genetics
- Published
- 2015
- Full Text
- View/download PDF
36. Inferring regulatory element landscapes and transcription factor networks from cancer methylomes.
- Author
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Yao L, Shen H, Laird PW, Farnham PJ, and Berman BP
- Subjects
- Cell Line, Tumor, Core Binding Factor Alpha 2 Subunit genetics, Databases, Genetic, Enhancer Elements, Genetic, GATA3 Transcription Factor genetics, Hepatocyte Nuclear Factor 3-alpha genetics, Hepatocyte Nuclear Factor 3-beta genetics, Humans, MCF-7 Cells, NF-E2-Related Factor 2 genetics, Neoplasm Proteins genetics, SOXB1 Transcription Factors genetics, SOXF Transcription Factors genetics, Sequence Analysis, RNA, Transcription Factors metabolism, Tumor Suppressor Proteins genetics, DNA Methylation, Gene Expression Regulation, Neoplastic genetics, Gene Regulatory Networks, Neoplasms genetics, Transcription Factors genetics
- Abstract
Recent studies indicate that DNA methylation can be used to identify transcriptional enhancers, but no systematic approach has been developed for genome-wide identification and analysis of enhancers based on DNA methylation. We describe ELMER (Enhancer Linking by Methylation/Expression Relationships), an R-based tool that uses DNA methylation to identify enhancers and correlates enhancer state with expression of nearby genes to identify transcriptional targets. Transcription factor motif analysis of enhancers is coupled with expression analysis of transcription factors to infer upstream regulators. Using ELMER, we investigated more than 2,000 tumor samples from The Cancer Genome Atlas. We identified networks regulated by known cancer drivers such as GATA3 and FOXA1 (breast cancer), SOX17 and FOXA2 (endometrial cancer), and NFE2L2, SOX2, and TP63 (squamous cell lung cancer). We also identified novel networks with prognostic associations, including RUNX1 in kidney cancer. We propose ELMER as a powerful new paradigm for understanding the cis-regulatory interface between cancer-associated transcription factors and their functional target genes.
- Published
- 2015
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37. The role of DNA methylation in directing the functional organization of the cancer epigenome.
- Author
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Lay FD, Liu Y, Kelly TK, Witt H, Farnham PJ, Jones PA, and Berman BP
- Subjects
- Cell Line, Tumor, CpG Islands genetics, DNA (Cytosine-5-)-Methyltransferase 1, DNA (Cytosine-5-)-Methyltransferases biosynthesis, DNA (Cytosine-5-)-Methyltransferases genetics, Epigenesis, Genetic, HCT116 Cells, Histones genetics, Humans, Nucleosomes genetics, Promoter Regions, Genetic genetics, DNA Methyltransferase 3B, Chromatin genetics, Colonic Neoplasms genetics, DNA Methylation genetics
- Abstract
The holistic role of DNA methylation in the organization of the cancer epigenome is not well understood. Here we perform a comprehensive, high-resolution analysis of chromatin structure to compare the landscapes of HCT116 colon cancer cells and a DNA methylation-deficient derivative. The NOMe-seq accessibility assay unexpectedly revealed symmetrical and transcription-independent nucleosomal phasing across active, poised, and inactive genomic elements. DNA methylation abolished this phasing primarily at enhancers and CpG island (CGI) promoters, with little effect on insulators and non-CGI promoters. Abolishment of DNA methylation led to the context-specific reestablishment of the poised and active states of normal colon cells, which were marked in methylation-deficient cells by distinct H3K27 modifications and the presence of either well-phased nucleosomes or nucleosome-depleted regions, respectively. At higher-order genomic scales, we found that long, H3K9me3-marked domains had lower accessibility, consistent with a more compact chromatin structure. Taken together, our results demonstrate the nuanced and context-dependent role of DNA methylation in the functional, multiscale organization of cancer epigenomes., (© 2015 Lay et al.; Published by Cold Spring Harbor Laboratory Press.)
- Published
- 2015
- Full Text
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38. Altering cancer transcriptomes using epigenomic inhibitors.
- Author
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Gaddis M, Gerrard D, Frietze S, and Farnham PJ
- Abstract
Background: Due to the hyper-activation of WNT signaling in a variety of cancer types, there has been a strong drive to develop pathway-specific inhibitors with the eventual goal of providing a chemotherapeutic antagonist of WNT signaling to cancer patients. A new category of drugs, called epigenetic inhibitors, are being developed that hold high promise for inhibition of the WNT pathway. The canonical WNT signaling pathway initiates when WNT ligands bind to receptors, causing the nuclear localization of the co-activator β-catenin (CTNNB1), which leads to an association of β-catenin with a member of the TCF transcription factor family at regulatory regions of WNT-responsive genes. The TCF/β-catenin complex then recruits CBP (CREBBP) or p300 (EP300), leading to histone acetylation and gene activation. A current model in the field is that CBP-driven expression of WNT target genes supports proliferation whereas p300-driven expression of WNT target genes supports differentiation. The small molecule inhibitor ICG-001 binds to CBP, but not to p300, and competitively inhibits the interaction of CBP with β-catenin. Upon treatment of cancer cells, this should reduce expression of CBP-regulated transcription, leading to reduced tumorigenicity and enhanced differentiation., Results: We have compared the genome-wide effects on the transcriptome after treatment with ICG-001 (the specific CBP inhibitor) versus C646, a compound that competes with acetyl-coA for the Lys-coA binding pocket of both CBP and p300. We found that both drugs cause large-scale changes in the transcriptome of HCT116 colon cancer cells and PANC1 pancreatic cancer cells and reverse some tumor-specific changes in gene expression. Interestingly, although the epigenetic inhibitors affect cell cycle pathways in both the colon and pancreatic cancer cell lines, the WNT signaling pathway was affected only in the colon cancer cells. Notably, WNT target genes were similarly downregulated after treatment of HCT116 with C646 as with ICG-001., Conclusion: Our results suggest that treatment with a general HAT inhibitor causes similar effects on the transcriptome as does treatment with a CBP-specific inhibitor and that epigenetic inhibition affects the WNT pathway in HCT116 cells and the cholesterol biosynthesis pathway in PANC1 cells.
- Published
- 2015
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39. Integrative analysis of 111 reference human epigenomes.
- Author
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Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, Heravi-Moussavi A, Kheradpour P, Zhang Z, Wang J, Ziller MJ, Amin V, Whitaker JW, Schultz MD, Ward LD, Sarkar A, Quon G, Sandstrom RS, Eaton ML, Wu YC, Pfenning AR, Wang X, Claussnitzer M, Liu Y, Coarfa C, Harris RA, Shoresh N, Epstein CB, Gjoneska E, Leung D, Xie W, Hawkins RD, Lister R, Hong C, Gascard P, Mungall AJ, Moore R, Chuah E, Tam A, Canfield TK, Hansen RS, Kaul R, Sabo PJ, Bansal MS, Carles A, Dixon JR, Farh KH, Feizi S, Karlic R, Kim AR, Kulkarni A, Li D, Lowdon R, Elliott G, Mercer TR, Neph SJ, Onuchic V, Polak P, Rajagopal N, Ray P, Sallari RC, Siebenthall KT, Sinnott-Armstrong NA, Stevens M, Thurman RE, Wu J, Zhang B, Zhou X, Beaudet AE, Boyer LA, De Jager PL, Farnham PJ, Fisher SJ, Haussler D, Jones SJ, Li W, Marra MA, McManus MT, Sunyaev S, Thomson JA, Tlsty TD, Tsai LH, Wang W, Waterland RA, Zhang MQ, Chadwick LH, Bernstein BE, Costello JF, Ecker JR, Hirst M, Meissner A, Milosavljevic A, Ren B, Stamatoyannopoulos JA, Wang T, and Kellis M
- Subjects
- Base Sequence, Cell Lineage genetics, Cells, Cultured, Chromatin chemistry, Chromatin genetics, Chromatin metabolism, Chromosomes, Human chemistry, Chromosomes, Human genetics, Chromosomes, Human metabolism, DNA chemistry, DNA genetics, DNA metabolism, DNA Methylation, Datasets as Topic, Enhancer Elements, Genetic genetics, Genetic Variation genetics, Genome-Wide Association Study, Histones metabolism, Humans, Organ Specificity genetics, RNA genetics, Reference Values, Epigenesis, Genetic genetics, Epigenomics, Genome, Human genetics
- Abstract
The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
- Published
- 2015
- Full Text
- View/download PDF
40. Epigenetic and transcriptional determinants of the human breast.
- Author
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Gascard P, Bilenky M, Sigaroudinia M, Zhao J, Li L, Carles A, Delaney A, Tam A, Kamoh B, Cho S, Griffith M, Chu A, Robertson G, Cheung D, Li I, Heravi-Moussavi A, Moksa M, Mingay M, Hussainkhel A, Davis B, Nagarajan RP, Hong C, Echipare L, O'Geen H, Hangauer MJ, Cheng JB, Neel D, Hu D, McManus MT, Moore R, Mungall A, Ma Y, Plettner P, Ziv E, Wang T, Farnham PJ, Jones SJ, Marra MA, Tlsty TD, Costello JF, and Hirst M
- Subjects
- Breast cytology, Cell Cycle, Cell Differentiation, Cell Separation, Chromatin chemistry, Chromatin Immunoprecipitation, CpG Islands, Epigenomics, Epithelial Cells cytology, Exons, Female, Flow Cytometry, Genome, Human, Histones chemistry, Humans, Introns, Karyotyping, MicroRNAs metabolism, Sequence Analysis, RNA, Transcription, Genetic, Breast metabolism, Epigenesis, Genetic, Gene Expression Regulation
- Abstract
While significant effort has been dedicated to the characterization of epigenetic changes associated with prenatal differentiation, relatively little is known about the epigenetic changes that accompany post-natal differentiation where fully functional differentiated cell types with limited lifespans arise. Here we sought to address this gap by generating epigenomic and transcriptional profiles from primary human breast cell types isolated from disease-free human subjects. From these data we define a comprehensive human breast transcriptional network, including a set of myoepithelial- and luminal epithelial-specific intronic retention events. Intersection of epigenetic states with RNA expression from distinct breast epithelium lineages demonstrates that mCpG provides a stable record of exonic and intronic usage, whereas H3K36me3 is dynamic. We find a striking asymmetry in epigenomic reprogramming between luminal and myoepithelial cell types, with the genomes of luminal cells harbouring more than twice the number of hypomethylated enhancer elements compared with myoepithelial cells.
- Published
- 2015
- Full Text
- View/download PDF
41. Intermediate DNA methylation is a conserved signature of genome regulation.
- Author
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Elliott G, Hong C, Xing X, Zhou X, Li D, Coarfa C, Bell RJ, Maire CL, Ligon KL, Sigaroudinia M, Gascard P, Tlsty TD, Harris RA, Schalkwyk LC, Bilenky M, Mill J, Farnham PJ, Kellis M, Marra MA, Milosavljevic A, Hirst M, Stormo GD, Wang T, and Costello JF
- Subjects
- Animals, Epigenomics, Evolution, Molecular, Histone Code, Humans, Mice, DNA Methylation, Gene Expression Regulation, Genome, Human, Synteny
- Abstract
The role of intermediate methylation states in DNA is unclear. Here, to comprehensively identify regions of intermediate methylation and their quantitative relationship with gene activity, we apply integrative and comparative epigenomics to 25 human primary cell and tissue samples. We report 18,452 intermediate methylation regions located near 36% of genes and enriched at enhancers, exons and DNase I hypersensitivity sites. Intermediate methylation regions average 57% methylation, are predominantly allele-independent and are conserved across individuals and between mouse and human, suggesting a conserved function. These regions have an intermediate level of active chromatin marks and their associated genes have intermediate transcriptional activity. Exonic intermediate methylation correlates with exon inclusion at a level between that of fully methylated and unmethylated exons, highlighting gene context-dependent functions. We conclude that intermediate DNA methylation is a conserved signature of gene regulation and exon usage.
- Published
- 2015
- Full Text
- View/download PDF
42. Demystifying the secret mission of enhancers: linking distal regulatory elements to target genes.
- Author
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Yao L, Berman BP, and Farnham PJ
- Subjects
- Animals, Chromatin chemistry, Chromatin genetics, Epigenomics methods, Humans, Transcriptome, Enhancer Elements, Genetic, Gene Expression Regulation, Promoter Regions, Genetic
- Abstract
Enhancers are short regulatory sequences bound by sequence-specific transcription factors and play a major role in the spatiotemporal specificity of gene expression patterns in development and disease. While it is now possible to identify enhancer regions genomewide in both cultured cells and primary tissues using epigenomic approaches, it has been more challenging to develop methods to understand the function of individual enhancers because enhancers are located far from the gene(s) that they regulate. However, it is essential to identify target genes of enhancers not only so that we can understand the role of enhancers in disease but also because this information will assist in the development of future therapeutic options. After reviewing models of enhancer function, we discuss recent methods for identifying target genes of enhancers. First, we describe chromatin structure-based approaches for directly mapping interactions between enhancers and promoters. Second, we describe the use of correlation-based approaches to link enhancer state with the activity of nearby promoters and/or gene expression. Third, we describe how to test the function of specific enhancers experimentally by perturbing enhancer-target relationships using high-throughput reporter assays and genome editing. Finally, we conclude by discussing as yet unanswered questions concerning how enhancers function, how target genes can be identified, and how to distinguish direct from indirect changes in gene expression mediated by individual enhancers.
- Published
- 2015
- Full Text
- View/download PDF
43. Regulatory network decoded from epigenomes of surface ectoderm-derived cell types.
- Author
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Lowdon RF, Zhang B, Bilenky M, Mauro T, Li D, Gascard P, Sigaroudinia M, Farnham PJ, Bastian BC, Tlsty TD, Marra MA, Hirst M, Costello JF, Wang T, and Cheng JB
- Subjects
- Cell Differentiation, Cells, Cultured, DNA Methylation, Ectoderm cytology, Fibroblasts cytology, Fibroblasts metabolism, Humans, Keratinocytes cytology, Keratinocytes metabolism, Melanocytes cytology, Melanocytes metabolism, Promoter Regions, Genetic, Species Specificity, Ectoderm metabolism, Epigenesis, Genetic, Gene Regulatory Networks
- Abstract
Developmental history shapes the epigenome and biological function of differentiated cells. Epigenomic patterns have been broadly attributed to the three embryonic germ layers. Here we investigate how developmental origin influences epigenomes. We compare key epigenomes of cell types derived from surface ectoderm (SE), including keratinocytes and breast luminal and myoepithelial cells, against neural crest-derived melanocytes and mesoderm-derived dermal fibroblasts, to identify SE differentially methylated regions (SE-DMRs). DNA methylomes of neonatal keratinocytes share many more DMRs with adult breast luminal and myoepithelial cells than with melanocytes and fibroblasts from the same neonatal skin. This suggests that SE origin contributes to DNA methylation patterning, while shared skin tissue environment has limited effect on epidermal keratinocytes. Hypomethylated SE-DMRs are in proximity to genes with SE relevant functions. They are also enriched for enhancer- and promoter-associated histone modifications in SE-derived cells, and for binding motifs of transcription factors important in keratinocyte and mammary gland biology. Thus, epigenomic analysis of cell types with common developmental origin reveals an epigenetic signature that underlies a shared gene regulatory network.
- Published
- 2014
- Full Text
- View/download PDF
44. Functional annotation of colon cancer risk SNPs.
- Author
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Yao L, Tak YG, Berman BP, and Farnham PJ
- Subjects
- Enhancer Elements, Genetic, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Promoter Regions, Genetic, Colonic Neoplasms genetics, Polymorphism, Single Nucleotide
- Abstract
Colorectal cancer (CRC) is a leading cause of cancer-related deaths in the United States. Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with increased risk for CRC. A molecular understanding of the functional consequences of this genetic variation has been complicated because each GWAS SNP is a surrogate for hundreds of other SNPs, most of which are located in non-coding regions. Here we use genomic and epigenomic information to test the hypothesis that the GWAS SNPs and/or correlated SNPs are in elements that regulate gene expression, and identify 23 promoters and 28 enhancers. Using gene expression data from normal and tumour cells, we identify 66 putative target genes of the risk-associated enhancers (10 of which were also identified by promoter SNPs). Employing CRISPR nucleases, we delete one risk-associated enhancer and identify genes showing altered expression. We suggest that similar studies be performed to characterize all CRC risk-associated enhancers.
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- 2014
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45. Global loss of DNA methylation uncovers intronic enhancers in genes showing expression changes.
- Author
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Blattler A, Yao L, Witt H, Guo Y, Nicolet CM, Berman BP, and Farnham PJ
- Subjects
- CpG Islands, Gene Expression, Gene Expression Regulation, Neoplastic, HCT116 Cells, Humans, Introns, Sequence Analysis, DNA, DNA Methylation, Enhancer Elements, Genetic
- Abstract
Background: Gene expression is epigenetically regulated by a combination of histone modifications and methylation of CpG dinucleotides in promoters. In normal cells, CpG-rich promoters are typically unmethylated, marked with histone modifications such as H3K4me3, and are highly active. During neoplastic transformation, CpG dinucleotides of CG-rich promoters become aberrantly methylated, corresponding with the removal of active histone modifications and transcriptional silencing. Outside of promoter regions, distal enhancers play a major role in the cell type-specific regulation of gene expression. Enhancers, which function by bringing activating complexes to promoters through chromosomal looping, are also modulated by a combination of DNA methylation and histone modifications., Results: Here we use HCT116 colorectal cancer cells with and without mutations in DNA methyltransferases, the latter of which results in a 95% reduction in global DNA methylation levels. These cells are used to study the relationship between DNA methylation, histone modifications, and gene expression. We find that the loss of DNA methylation is not sufficient to reactivate most of the silenced promoters. In contrast, the removal of DNA methylation results in the activation of a large number of enhancer regions as determined by the acquisition of active histone marks., Conclusions: Although the transcriptome is largely unaffected by the loss of DNA methylation, we identify two distinct mechanisms resulting in the upregulation of distinct sets of genes. One is a direct result of DNA methylation loss at a set of promoter regions and the other is due to the presence of new intragenic enhancers.
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- 2014
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- View/download PDF
46. Reply to Brunet and Doolittle: Both selected effect and causal role elements can influence human biology and disease.
- Author
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Kellis M, Wold B, Snyder MP, Bernstein BE, Kundaje A, Marinov GK, Ward LD, Birney E, Crawford GE, Dekker J, Dunham I, Elnitski LL, Farnham PJ, Feingold EA, Gerstein M, Giddings MC, Gilbert DM, Gingeras TR, Green ED, Guigo R, Hubbard T, Kent J, Lieb JD, Myers RM, Pazin MJ, Ren B, Stamatoyannopoulos J, Weng Z, White KP, and Hardison RC
- Subjects
- Humans, DNA genetics, Genome, Human genetics
- Published
- 2014
- Full Text
- View/download PDF
47. Global analysis of ZNF217 chromatin occupancy in the breast cancer cell genome reveals an association with ERalpha.
- Author
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Frietze S, O'Geen H, Littlepage LE, Simion C, Sweeney CA, Farnham PJ, and Krig SR
- Subjects
- Binding Sites, Breast Neoplasms genetics, Breast Neoplasms mortality, Cluster Analysis, Female, GATA3 Transcription Factor physiology, Gene Expression Regulation, Neoplastic, Genes, Neoplasm, Genome, Human, Hepatocyte Nuclear Factor 3-alpha physiology, Humans, Kaplan-Meier Estimate, MCF-7 Cells, Protein Binding, Transcriptome, Breast Neoplasms metabolism, Chromatin metabolism, Estrogen Receptor alpha genetics, Trans-Activators physiology
- Abstract
Background: The ZNF217 gene, encoding a C2H2 zinc finger protein, is located at 20q13 and found amplified and overexpressed in greater than 20% of breast tumors. Current studies indicate ZNF217 drives tumorigenesis, yet the regulatory mechanisms of ZNF217 are largely unknown. Because ZNF217 associates with chromatin modifying enzymes, we postulate that ZNF217 functions to regulate specific gene signaling networks. Here, we present a large-scale functional genomic analysis of ZNF217, which provides insights into the regulatory role of ZNF217 in MCF7 breast cancer cells., Results: ChIP-seq analysis reveals that the majority of ZNF217 binding sites are located at distal regulatory regions associated with the chromatin marks H3K27ac and H3K4me1. Analysis of ChIP-seq transcription factor binding sites shows clustering of ZNF217 with FOXA1, GATA3 and ERalpha binding sites, supported by the enrichment of corresponding motifs for the ERalpha-associated cis-regulatory sequences. ERalpha expression highly correlates with ZNF217 in lysates from breast tumors (n = 15), and ERalpha co-precipitates ZNF217 and its binding partner CtBP2 from nuclear extracts. Transcriptome profiling following ZNF217 depletion identifies differentially expressed genes co-bound by ZNF217 and ERalpha; gene ontology suggests a role for ZNF217-ERalpha in expression programs associated with ER+ breast cancer studies found in the Molecular Signature Database. Data-mining of expression data from breast cancer patients correlates ZNF217 with reduced overall survival., Conclusions: Our genome-wide ZNF217 data suggests a functional role for ZNF217 at ERalpha target genes. Future studies will investigate whether ZNF217 expression contributes to aberrant ERalpha regulatory events in ER+ breast cancer and hormone resistance.
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- 2014
- Full Text
- View/download PDF
48. Defining functional DNA elements in the human genome.
- Author
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Kellis M, Wold B, Snyder MP, Bernstein BE, Kundaje A, Marinov GK, Ward LD, Birney E, Crawford GE, Dekker J, Dunham I, Elnitski LL, Farnham PJ, Feingold EA, Gerstein M, Giddings MC, Gilbert DM, Gingeras TR, Green ED, Guigo R, Hubbard T, Kent J, Lieb JD, Myers RM, Pazin MJ, Ren B, Stamatoyannopoulos JA, Weng Z, White KP, and Hardison RC
- Subjects
- Biological Evolution, Disease genetics, Humans, Regulatory Sequences, Nucleic Acid genetics, Software, DNA genetics, Genome, Human genetics
- Abstract
With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease.
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- 2014
- Full Text
- View/download PDF
49. Comprehensive functional annotation of 77 prostate cancer risk loci.
- Author
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Hazelett DJ, Rhie SK, Gaddis M, Yan C, Lakeland DL, Coetzee SG, Henderson BE, Noushmehr H, Cozen W, Kote-Jarai Z, Eeles RA, Easton DF, Haiman CA, Lu W, Farnham PJ, and Coetzee GA
- Subjects
- Alleles, Chromatin genetics, Gene Expression Regulation, Neoplastic, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide genetics, Prostatic Neoplasms metabolism, Prostatic Neoplasms pathology, Risk Factors, Transcription Factors genetics, Enhancer Elements, Genetic, Molecular Sequence Annotation classification, Prostatic Neoplasms genetics, Response Elements genetics
- Abstract
Genome-wide association studies (GWAS) have revolutionized the field of cancer genetics, but the causal links between increased genetic risk and onset/progression of disease processes remain to be identified. Here we report the first step in such an endeavor for prostate cancer. We provide a comprehensive annotation of the 77 known risk loci, based upon highly correlated variants in biologically relevant chromatin annotations--we identified 727 such potentially functional SNPs. We also provide a detailed account of possible protein disruption, microRNA target sequence disruption and regulatory response element disruption of all correlated SNPs at r(2) ≥ 0.88%. 88% of the 727 SNPs fall within putative enhancers, and many alter critical residues in the response elements of transcription factors known to be involved in prostate biology. We define as risk enhancers those regions with enhancer chromatin biofeatures in prostate-derived cell lines with prostate-cancer correlated SNPs. To aid the identification of these enhancers, we performed genomewide ChIP-seq for H3K27-acetylation, a mark of actively engaged enhancers, as well as the transcription factor TCF7L2. We analyzed in depth three variants in risk enhancers, two of which show significantly altered androgen sensitivity in LNCaP cells. This includes rs4907792, that is in linkage disequilibrium (r(2) = 0.91) with an eQTL for NUDT11 (on the X chromosome) in prostate tissue, and rs10486567, the index SNP in intron 3 of the JAZF1 gene on chromosome 7. Rs4907792 is within a critical residue of a strong consensus androgen response element that is interrupted in the protective allele, resulting in a 56% decrease in its androgen sensitivity, whereas rs10486567 affects both NKX3-1 and FOXA-AR motifs where the risk allele results in a 39% increase in basal activity and a 28% fold-increase in androgen stimulated enhancer activity. Identification of such enhancer variants and their potential target genes represents a preliminary step in connecting risk to disease process.
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- 2014
- Full Text
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50. Analysis of an artificial zinc finger epigenetic modulator: widespread binding but limited regulation.
- Author
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Grimmer MR, Stolzenburg S, Ford E, Lister R, Blancafort P, and Farnham PJ
- Subjects
- Binding Sites, DNA-Binding Proteins chemistry, DNA-Binding Proteins metabolism, Genome, Human, Humans, MCF-7 Cells, Promoter Regions, Genetic, Protein Binding, Transcription Factors chemistry, Epigenesis, Genetic, Transcription Factors metabolism, Zinc Fingers
- Abstract
Artificial transcription factors (ATFs) and genomic nucleases based on a DNA binding platform consisting of multiple zinc finger domains are currently being developed for clinical applications. However, no genome-wide investigations into their binding specificity have been performed. We have created six-finger ATFs to target two different 18 nt regions of the human SOX2 promoter; each ATF is constructed such that it contains or lacks a super KRAB domain (SKD) that interacts with a complex containing repressive histone methyltransferases. ChIP-seq analysis of the effector-free ATFs in MCF7 breast cancer cells identified thousands of binding sites, mostly in promoter regions; the addition of an SKD domain increased the number of binding sites ∼ 5-fold, with a majority of the new sites located outside of promoters. De novo motif analyses suggest that the lack of binding specificity is due to subsets of the finger domains being used for genomic interactions. Although the ATFs display widespread binding, few genes showed expression differences; genes repressed by the ATF-SKD have stronger binding sites and are more enriched for a 12 nt motif. Interestingly, epigenetic analyses indicate that the transcriptional repression caused by the ATF-SKD is not due to changes in active histone modifications., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)
- Published
- 2014
- Full Text
- View/download PDF
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