21 results on '"Rynes E"'
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2. Updated description of quarkonium by power-law potentials
- Author
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Rynes, E [Enrico Fermi Institute and Department of Physics, University of Chicago, Chicago, Illinois 60637 (United States)]
- Published
- 1993
- Full Text
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3. An integrated encyclopedia of DNA elements in the human genome
- Author
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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
- Subjects
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
4. A User's Guide to the Encyclopedia of DNA Elements (ENCODE)
- Author
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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
5. The ENCODE Uniform Analysis Pipelines.
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Hitz BC, Lee JW, Jolanki O, Kagda MS, Graham K, Sud P, Gabdank I, Strattan JS, Sloan CA, Dreszer T, Rowe LD, Podduturi NR, Malladi VS, Chan ET, Davidson JM, Ho M, Miyasato S, Simison M, Tanaka F, Luo Y, Whaling I, Hong EL, Lee BT, Sandstrom R, Rynes E, Nelson J, Nishida A, Ingersoll A, Buckley M, Frerker M, Kim DS, Boley N, Trout D, Dobin A, Rahmanian S, Wyman D, Balderrama-Gutierrez G, Reese F, Durand NC, Dudchenko O, Weisz D, Rao SSP, Blackburn A, Gkountaroulis D, Sadr M, Olshansky M, Eliaz Y, Nguyen D, Bochkov I, Shamim MS, Mahajan R, Aiden E, Gingeras T, Heath S, Hirst M, Kent WJ, Kundaje A, Mortazavi A, Wold B, and Cherry JM
- Abstract
The Encyclopedia of DNA elements (ENCODE) project is a collaborative effort to create a comprehensive catalog of functional elements in the human genome. The current database comprises more than 19000 functional genomics experiments across more than 1000 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the Homo sapiens and Mus musculus genomes. All experimental data, metadata, and associated computational analyses created by the ENCODE consortium are submitted to the Data Coordination Center (DCC) for validation, tracking, storage, and distribution to community resources and the scientific community. The ENCODE project has engineered and distributed uniform processing pipelines in order to promote data provenance and reproducibility as well as allow interoperability between genomic resources and other consortia. All data files, reference genome versions, software versions, and parameters used by the pipelines are captured and available via the ENCODE Portal. The pipeline code, developed using Docker and Workflow Description Language (WDL; https://openwdl.org/) is publicly available in GitHub, with images available on Dockerhub (https://hub.docker.com), enabling access to a diverse range of biomedical researchers. ENCODE pipelines maintained and used by the DCC can be installed to run on personal computers, local HPC clusters, or in cloud computing environments via Cromwell. Access to the pipelines and data via the cloud allows small labs the ability to use the data or software without access to institutional compute clusters. Standardization of the computational methodologies for analysis and quality control leads to comparable results from different ENCODE collections - a prerequisite for successful integrative analyses., Competing Interests: Conflict of interest. None declared
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- 2023
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6. Differences in nanoscale organization of regulatory active and inactive human chromatin.
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Brandstetter K, Zülske T, Ragoczy T, Hörl D, Guirao-Ortiz M, Steinek C, Barnes T, Stumberger G, Schwach J, Haugen E, Rynes E, Korber P, Stamatoyannopoulos JA, Leonhardt H, Wedemann G, and Harz H
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- DNA genetics, Humans, In Situ Hybridization, Fluorescence methods, Molecular Conformation, Chromatin, Nucleosomes
- Abstract
Methodological advances in conformation capture techniques have fundamentally changed our understanding of chromatin architecture. However, the nanoscale organization of chromatin and its cell-to-cell variance are less studied. Analyzing genome-wide data from 733 human cell and tissue samples, we identified 2 prototypical regions that exhibit high or absent hypersensitivity to deoxyribonuclease I, respectively. These regulatory active or inactive regions were examined in the lymphoblast cell line K562 by using high-throughput super-resolution microscopy. In both regions, we systematically measured the physical distance of 2 fluorescence in situ hybridization spots spaced by only 5 kb of DNA. Unexpectedly, the resulting distance distributions range from very compact to almost elongated configurations of more than 200-nm length for both the active and inactive regions. Monte Carlo simulations of a coarse-grained model of these chromatin regions based on published data of nucleosome occupancy in K562 cells were performed to understand the underlying mechanisms. There was no parameter set for the simulation model that can explain the microscopically measured distance distributions. Obviously, the chromatin state given by the strength of internucleosomal interaction, nucleosome occupancy, or amount of histone H1 differs from cell to cell, which results in the observed broad distance distributions. This large variability was not expected, especially in inactive regions. The results for the mechanisms for different distance distributions on this scale are important for understanding the contacts that mediate gene regulation. Microscopic measurements show that the inactive region investigated here is expected to be embedded in a more compact chromatin environment. The simulation results of this region require an increase in the strength of internucleosomal interactions. It may be speculated that the higher density of chromatin is caused by the increased internucleosomal interaction strength., (Copyright © 2022 Biophysical Society. Published by Elsevier Inc. All rights reserved.)
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- 2022
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7. Index and biological spectrum of human DNase I hypersensitive sites.
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Meuleman W, Muratov A, Rynes E, Halow J, Lee K, Bates D, Diegel M, Dunn D, Neri F, Teodosiadis A, Reynolds A, Haugen E, Nelson J, Johnson A, Frerker M, Buckley M, Sandstrom R, Vierstra J, Kaul R, and Stamatoyannopoulos J
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- Chromatin chemistry, Chromatin metabolism, DNA chemistry, DNA genetics, Gene Expression Regulation, Genes genetics, Genome, Human genetics, Humans, Promoter Regions, Genetic genetics, Regulatory Sequences, Nucleic Acid genetics, Chromatin genetics, DNA metabolism, Deoxyribonuclease I metabolism, Molecular Sequence Annotation
- Abstract
DNase I hypersensitive sites (DHSs) are generic markers of regulatory DNA
1-5 and contain genetic variations associated with diseases and phenotypic traits6-8 . We created high-resolution maps of DHSs from 733 human biosamples encompassing 438 cell and tissue types and states, and integrated these to delineate and numerically index approximately 3.6 million DHSs within the human genome sequence, providing a common coordinate system for regulatory DNA. Here we show that these maps highly resolve the cis-regulatory compartment of the human genome, which encodes unexpectedly diverse cell- and tissue-selective regulatory programs at very high density. These programs can be captured comprehensively by a simple vocabulary that enables the assignment to each DHS of a regulatory barcode that encapsulates its tissue manifestations, and global annotation of protein-coding and non-coding RNA genes in a manner orthogonal to gene expression. Finally, we show that sharply resolved DHSs markedly enhance the genetic association and heritability signals of diseases and traits. Rather than being confined to a small number of distal elements or promoters, we find that genetic signals converge on congruently regulated sets of DHSs that decorate entire gene bodies. Together, our results create a universal, extensible coordinate system and vocabulary for human regulatory DNA marked by DHSs, and provide a new global perspective on the architecture of human gene regulation.- Published
- 2020
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8. Global reference mapping of human transcription factor footprints.
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Vierstra J, Lazar J, Sandstrom R, Halow J, Lee K, Bates D, Diegel M, Dunn D, Neri F, Haugen E, Rynes E, Reynolds A, Nelson J, Johnson A, Frerker M, Buckley M, Kaul R, Meuleman W, and Stamatoyannopoulos JA
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- Consensus Sequence, DNA genetics, DNA metabolism, Deoxyribonuclease I metabolism, Genetics, Population, Genome-Wide Association Study, Humans, Models, Molecular, Polymorphism, Single Nucleotide, Regulatory Sequences, Nucleic Acid genetics, DNA Footprinting standards, Genome, Human genetics, Transcription Factors metabolism
- Abstract
Combinatorial binding of transcription factors to regulatory DNA underpins gene regulation in all organisms. Genetic variation in regulatory regions has been connected with diseases and diverse phenotypic traits
1 , but it remains challenging to distinguish variants that affect regulatory function2 . Genomic DNase I footprinting enables the quantitative, nucleotide-resolution delineation of sites of transcription factor occupancy within native chromatin3-6 . However, only a small fraction of such sites have been precisely resolved on the human genome sequence6 . Here, to enable comprehensive mapping of transcription factor footprints, we produced high-density DNase I cleavage maps from 243 human cell and tissue types and states and integrated these data to delineate about 4.5 million compact genomic elements that encode transcription factor occupancy at nucleotide resolution. We map the fine-scale structure within about 1.6 million DNase I-hypersensitive sites and show that the overwhelming majority are populated by well-spaced sites of single transcription factor-DNA interaction. Cell-context-dependent cis-regulation is chiefly executed by wholesale modulation of accessibility at regulatory DNA rather than by differential transcription factor occupancy within accessible elements. We also show that the enrichment of genetic variants associated with diseases or phenotypic traits in regulatory regions1,7 is almost entirely attributable to variants within footprints, and that functional variants that affect transcription factor occupancy are nearly evenly partitioned between loss- and gain-of-function alleles. Unexpectedly, we find increased density of human genetic variation within transcription factor footprints, revealing an unappreciated driver of cis-regulatory evolution. Our results provide a framework for both global and nucleotide-precision analyses of gene regulatory mechanisms and functional genetic variation.- Published
- 2020
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9. Integrated epigenomic profiling reveals endogenous retrovirus reactivation in renal cell carcinoma.
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Siebenthall KT, Miller CP, Vierstra JD, Mathieu J, Tretiakova M, Reynolds A, Sandstrom R, Rynes E, Haugen E, Johnson A, Nelson J, Bates D, Diegel M, Dunn D, Frerker M, Buckley M, Kaul R, Zheng Y, Himmelfarb J, Ruohola-Baker H, and Akilesh S
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- Basic Helix-Loop-Helix Transcription Factors genetics, Binding Sites, Carcinoma, Renal Cell genetics, Carcinoma, Renal Cell mortality, Carcinoma, Renal Cell pathology, Cell Line, Tumor, Cytochrome Reductases genetics, Endogenous Retroviruses physiology, Gene Expression Regulation, Neoplastic, Humans, Hypoxia-Inducible Factor 1 genetics, Kidney Neoplasms genetics, Kidney Neoplasms mortality, Kidney Neoplasms pathology, Octamer Transcription Factor-3 genetics, Octamer Transcription Factor-3 metabolism, Oxidoreductases Acting on Sulfur Group Donors, Phosphoric Diester Hydrolases genetics, Promoter Regions, Genetic, Proteins genetics, Pyrophosphatases genetics, RNA, Long Noncoding, Survival Rate, Terminal Repeat Sequences genetics, Ubiquitin-Conjugating Enzymes genetics, Endogenous Retroviruses genetics, Epigenomics
- Abstract
Background: Transcriptional dysregulation drives cancer formation but the underlying mechanisms are still poorly understood. Renal cell carcinoma (RCC) is the most common malignant kidney tumor which canonically activates the hypoxia-inducible transcription factor (HIF) pathway. Despite intensive study, novel therapeutic strategies to target RCC have been difficult to develop. Since the RCC epigenome is relatively understudied, we sought to elucidate key mechanisms underpinning the tumor phenotype and its clinical behavior., Methods: We performed genome-wide chromatin accessibility (DNase-seq) and transcriptome profiling (RNA-seq) on paired tumor/normal samples from 3 patients undergoing nephrectomy for removal of RCC. We incorporated publicly available data on HIF binding (ChIP-seq) in a RCC cell line. We performed integrated analyses of these high-resolution, genome-scale datasets together with larger transcriptomic data available through The Cancer Genome Atlas (TCGA)., Findings: Though HIF transcription factors play a cardinal role in RCC oncogenesis, we found that numerous transcription factors with a RCC-selective expression pattern also demonstrated evidence of HIF binding near their gene body. Examination of chromatin accessibility profiles revealed that some of these transcription factors influenced the tumor's regulatory landscape, notably the stem cell transcription factor POU5F1 (OCT4). Elevated POU5F1 transcript levels were correlated with advanced tumor stage and poorer overall survival in RCC patients. Unexpectedly, we discovered a HIF-pathway-responsive promoter embedded within a endogenous retroviral long terminal repeat (LTR) element at the transcriptional start site of the PSOR1C3 long non-coding RNA gene upstream of POU5F1. RNA transcripts are induced from this promoter and read through PSOR1C3 into POU5F1 producing a novel POU5F1 transcript isoform. Rather than being unique to the POU5F1 locus, we found that HIF binds to several other transcriptionally active LTR elements genome-wide correlating with broad gene expression changes in RCC., Interpretation: Integrated transcriptomic and epigenomic analysis of matched tumor and normal tissues from even a small number of primary patient samples revealed remarkably convergent shared regulatory landscapes. Several transcription factors appear to act downstream of HIF including the potent stem cell transcription factor POU5F1. Dysregulated expression of POU5F1 is part of a larger pattern of gene expression changes in RCC that may be induced by HIF-dependent reactivation of dormant promoters embedded within endogenous retroviral LTRs., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)
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- 2019
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10. Cell-of-origin chromatin organization shapes the mutational landscape of cancer.
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Polak P, Karlić R, Koren A, Thurman R, Sandstrom R, Lawrence M, Reynolds A, Rynes E, Vlahoviček K, Stamatoyannopoulos JA, and Sunyaev SR
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- Cell Line, Tumor, Chromatin chemistry, DNA Replication Timing, Epigenomics, Genome, Human genetics, Humans, Melanocytes metabolism, Melanocytes pathology, Melanoma genetics, Melanoma pathology, Organ Specificity genetics, Chromatin genetics, Chromatin metabolism, Epigenesis, Genetic genetics, Mutation genetics, Neoplasms genetics, Neoplasms pathology
- Abstract
Cancer is a disease potentiated by mutations in somatic cells. Cancer mutations are not distributed uniformly along the human genome. Instead, different human genomic regions vary by up to fivefold in the local density of cancer somatic mutations, posing a fundamental problem for statistical methods used in cancer genomics. Epigenomic organization has been proposed as a major determinant of the cancer mutational landscape. However, both somatic mutagenesis and epigenomic features are highly cell-type-specific. We investigated the distribution of mutations in multiple independent samples of diverse cancer types and compared them to cell-type-specific epigenomic features. Here we show that chromatin accessibility and modification, together with replication timing, explain up to 86% of the variance in mutation rates along cancer genomes. The best predictors of local somatic mutation density are epigenomic features derived from the most likely cell type of origin of the corresponding malignancy. Moreover, we find that cell-of-origin chromatin features are much stronger determinants of cancer mutation profiles than chromatin features of matched cancer cell lines. Furthermore, we show that the cell type of origin of a cancer can be accurately determined based on the distribution of mutations along its genome. Thus, the DNA sequence of a cancer genome encompasses a wealth of information about the identity and epigenomic features of its cell of origin.
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- 2015
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11. Mouse regulatory DNA landscapes reveal global principles of cis-regulatory evolution.
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Vierstra J, Rynes E, Sandstrom R, Zhang M, Canfield T, Hansen RS, Stehling-Sun S, Sabo PJ, Byron R, Humbert R, Thurman RE, Johnson AK, Vong S, Lee K, Bates D, Neri F, Diegel M, Giste E, Haugen E, Dunn D, Wilken MS, Josefowicz S, Samstein R, Chang KH, Eichler EE, De Bruijn M, Reh TA, Skoultchi A, Rudensky A, Orkin SH, Papayannopoulou T, Treuting PM, Selleri L, Kaul R, Groudine M, Bender MA, and Stamatoyannopoulos JA
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- Animals, Base Sequence, Deoxyribonuclease I, Genome, Human, Humans, Mice, Restriction Mapping, Conserved Sequence, DNA genetics, Evolution, Molecular, Regulatory Sequences, Nucleic Acid genetics, Transcription Factors metabolism
- Abstract
To study the evolutionary dynamics of regulatory DNA, we mapped >1.3 million deoxyribonuclease I-hypersensitive sites (DHSs) in 45 mouse cell and tissue types, and systematically compared these with human DHS maps from orthologous compartments. We found that the mouse and human genomes have undergone extensive cis-regulatory rewiring that combines branch-specific evolutionary innovation and loss with widespread repurposing of conserved DHSs to alternative cell fates, and that this process is mediated by turnover of transcription factor (TF) recognition elements. Despite pervasive evolutionary remodeling of the location and content of individual cis-regulatory regions, within orthologous mouse and human cell types the global fraction of regulatory DNA bases encoding recognition sites for each TF has been strictly conserved. Our findings provide new insights into the evolutionary forces shaping mammalian regulatory DNA landscapes., (Copyright © 2014, American Association for the Advancement of Science.)
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- 2014
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12. A comparative encyclopedia of DNA elements in the mouse genome.
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Yue F, Cheng Y, Breschi A, Vierstra J, Wu W, Ryba T, Sandstrom R, Ma Z, Davis C, Pope BD, Shen Y, Pervouchine DD, Djebali S, Thurman RE, Kaul R, Rynes E, Kirilusha A, Marinov GK, Williams BA, Trout D, Amrhein H, Fisher-Aylor K, Antoshechkin I, DeSalvo G, See LH, Fastuca M, Drenkow J, Zaleski C, Dobin A, Prieto P, Lagarde J, Bussotti G, Tanzer A, Denas O, Li K, Bender MA, Zhang M, Byron R, Groudine MT, McCleary D, Pham L, Ye Z, Kuan S, Edsall L, Wu YC, Rasmussen MD, Bansal MS, Kellis M, Keller CA, Morrissey CS, Mishra T, Jain D, Dogan N, Harris RS, Cayting P, Kawli T, Boyle AP, Euskirchen G, Kundaje A, Lin S, Lin Y, Jansen C, Malladi VS, Cline MS, Erickson DT, Kirkup VM, Learned K, Sloan CA, Rosenbloom KR, Lacerda de Sousa B, Beal K, Pignatelli M, Flicek P, Lian J, Kahveci T, Lee D, Kent WJ, Ramalho Santos M, Herrero J, Notredame C, Johnson A, Vong S, Lee K, Bates D, Neri F, Diegel M, Canfield T, Sabo PJ, Wilken MS, Reh TA, Giste E, Shafer A, Kutyavin T, Haugen E, Dunn D, Reynolds AP, Neph S, Humbert R, Hansen RS, De Bruijn M, Selleri L, Rudensky A, Josefowicz S, Samstein R, Eichler EE, Orkin SH, Levasseur D, Papayannopoulou T, Chang KH, Skoultchi A, Gosh S, Disteche C, Treuting P, Wang Y, Weiss MJ, Blobel GA, Cao X, Zhong S, Wang T, Good PJ, Lowdon RF, Adams LB, Zhou XQ, Pazin MJ, Feingold EA, Wold B, Taylor J, Mortazavi A, Weissman SM, Stamatoyannopoulos JA, Snyder MP, Guigo R, Gingeras TR, Gilbert DM, Hardison RC, Beer MA, and Ren B
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- Animals, Cell Lineage genetics, Chromatin genetics, Chromatin metabolism, Conserved Sequence genetics, DNA Replication genetics, Deoxyribonuclease I metabolism, Gene Expression Regulation genetics, Gene Regulatory Networks genetics, Genome-Wide Association Study, Humans, RNA genetics, Regulatory Sequences, Nucleic Acid genetics, Species Specificity, Transcription Factors metabolism, Transcriptome genetics, Genome genetics, Genomics, Mice genetics, Molecular Sequence Annotation
- Abstract
The laboratory mouse shares the majority of its protein-coding genes with humans, making it the premier model organism in biomedical research, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases.
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- 2014
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13. Hematopoietic protein-1 regulates the actin membrane skeleton and membrane stability in murine erythrocytes.
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Chan MM, Wooden JM, Tsang M, Gilligan DM, Hirenallur-S DK, Finney GL, Rynes E, Maccoss M, Ramirez JA, Park H, and Iritani BM
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- Actins chemistry, Adaptor Proteins, Signal Transducing deficiency, Adaptor Proteins, Signal Transducing genetics, Animals, Gene Deletion, Mice, Phosphorylation, Stem Cells cytology, Stem Cells metabolism, Time Factors, Transcriptome, Wiskott-Aldrich Syndrome Protein Family genetics, Wiskott-Aldrich Syndrome Protein Family metabolism, Actins metabolism, Adaptor Proteins, Signal Transducing metabolism, Erythrocyte Membrane metabolism
- Abstract
Hematopoietic protein-1 (Hem-1) is a hematopoietic cell specific member of the WAVE (Wiskott-Aldrich syndrome verprolin-homologous protein) complex, which regulates filamentous actin (F-actin) polymerization in many cell types including immune cells. However, the roles of Hem-1 and the WAVE complex in erythrocyte biology are not known. In this study, we utilized mice lacking Hem-1 expression due to a non-coding point mutation in the Hem1 gene to show that absence of Hem-1 results in microcytic, hypochromic anemia characterized by abnormally shaped erythrocytes with aberrant F-actin foci and decreased lifespan. We find that Hem-1 and members of the associated WAVE complex are normally expressed in wildtype erythrocyte progenitors and mature erythrocytes. Using mass spectrometry and global proteomics, Coomassie staining, and immunoblotting, we find that the absence of Hem-1 results in decreased representation of essential erythrocyte membrane skeletal proteins including α- and β- spectrin, dematin, p55, adducin, ankyrin, tropomodulin 1, band 3, and band 4.1. Hem1⁻/⁻ erythrocytes exhibit increased protein kinase C-dependent phosphorylation of adducin at Ser724, which targets adducin family members for dissociation from spectrin and actin, and subsequent proteolysis. Increased adducin Ser724 phosphorylation in Hem1⁻/⁻ erythrocytes correlates with decreased protein expression of the regulatory subunit of protein phosphatase 2A (PP2A), which is required for PP2A-dependent dephosphorylation of PKC targets. These results reveal a novel, critical role for Hem-1 in the homeostasis of structural proteins required for formation and stability of the actin membrane skeleton in erythrocytes.
- Published
- 2013
- Full Text
- View/download PDF
14. Systematic localization of common disease-associated variation in regulatory DNA.
- Author
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Maurano MT, Humbert R, Rynes E, Thurman RE, Haugen E, Wang H, Reynolds AP, Sandstrom R, Qu H, Brody J, Shafer A, Neri F, Lee K, Kutyavin T, Stehling-Sun S, Johnson AK, Canfield TK, Giste E, Diegel M, Bates D, Hansen RS, Neph S, Sabo PJ, Heimfeld S, Raubitschek A, Ziegler S, Cotsapas C, Sotoodehnia N, Glass I, Sunyaev SR, Kaul R, and Stamatoyannopoulos JA
- Subjects
- Alleles, Chromatin metabolism, Chromatin ultrastructure, Crohn Disease genetics, Deoxyribonuclease I metabolism, Electrocardiography, Fetal Development, Fetus metabolism, Gene Regulatory Networks, Genome, Human, Genome-Wide Association Study, Humans, Multiple Sclerosis genetics, Phenotype, Promoter Regions, Genetic, Transcription Factors chemistry, Transcription Factors genetics, DNA genetics, Disease genetics, Genetic Variation, Polymorphism, Single Nucleotide, Regulatory Elements, Transcriptional, Regulatory Sequences, Nucleic Acid, Transcription Factors metabolism
- Abstract
Genome-wide association studies have identified many noncoding variants associated with common diseases and traits. We show that these variants are concentrated in regulatory DNA marked by deoxyribonuclease I (DNase I) hypersensitive sites (DHSs). Eighty-eight percent of such DHSs are active during fetal development and are enriched in variants associated with gestational exposure-related phenotypes. We identified distant gene targets for hundreds of variant-containing DHSs that may explain phenotype associations. Disease-associated variants systematically perturb transcription factor recognition sequences, frequently alter allelic chromatin states, and form regulatory networks. We also demonstrated tissue-selective enrichment of more weakly disease-associated variants within DHSs and the de novo identification of pathogenic cell types for Crohn's disease, multiple sclerosis, and an electrocardiogram trait, without prior knowledge of physiological mechanisms. Our results suggest pervasive involvement of regulatory DNA variation in common human disease and provide pathogenic insights into diverse disorders.
- Published
- 2012
- Full Text
- View/download PDF
15. The accessible chromatin landscape of the human genome.
- Author
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Thurman RE, Rynes E, Humbert R, Vierstra J, Maurano MT, Haugen E, Sheffield NC, Stergachis AB, Wang H, Vernot B, Garg K, John S, Sandstrom R, Bates D, Boatman L, Canfield TK, Diegel M, Dunn D, Ebersol AK, Frum T, Giste E, Johnson AK, Johnson EM, Kutyavin T, Lajoie B, Lee BK, Lee K, London D, Lotakis D, Neph S, Neri F, Nguyen ED, Qu H, Reynolds AP, Roach V, Safi A, Sanchez ME, Sanyal A, Shafer A, Simon JM, Song L, Vong S, Weaver M, Yan Y, Zhang Z, Zhang Z, Lenhard B, Tewari M, Dorschner MO, Hansen RS, Navas PA, Stamatoyannopoulos G, Iyer VR, Lieb JD, Sunyaev SR, Akey JM, Sabo PJ, Kaul R, Furey TS, Dekker J, Crawford GE, and Stamatoyannopoulos JA
- Subjects
- DNA Footprinting, DNA Methylation, DNA-Binding Proteins metabolism, Deoxyribonuclease I metabolism, Evolution, Molecular, Genomics, Humans, Mutation Rate, Promoter Regions, Genetic genetics, Transcription Factors metabolism, Transcription Initiation Site, Transcription, Genetic, Chromatin genetics, Chromatin metabolism, DNA genetics, Encyclopedias as Topic, Genome, Human genetics, Molecular Sequence Annotation, Regulatory Sequences, Nucleic Acid genetics
- Abstract
DNase I hypersensitive sites (DHSs) are markers of regulatory DNA and have underpinned the discovery of all classes of cis-regulatory elements including enhancers, promoters, insulators, silencers and locus control regions. Here we present the first extensive map of human DHSs identified through genome-wide profiling in 125 diverse cell and tissue types. We identify ∼2.9 million DHSs that encompass virtually all known experimentally validated cis-regulatory sequences and expose a vast trove of novel elements, most with highly cell-selective regulation. Annotating these elements using ENCODE data reveals novel relationships between chromatin accessibility, transcription, DNA methylation and regulatory factor occupancy patterns. We connect ∼580,000 distal DHSs with their target promoters, revealing systematic pairing of different classes of distal DHSs and specific promoter types. Patterning of chromatin accessibility at many regulatory regions is organized with dozens to hundreds of co-activated elements, and the transcellular DNase I sensitivity pattern at a given region can predict cell-type-specific functional behaviours. The DHS landscape shows signatures of recent functional evolutionary constraint. However, the DHS compartment in pluripotent and immortalized cells exhibits higher mutation rates than that in highly differentiated cells, exposing an unexpected link between chromatin accessibility, proliferative potential and patterns of human variation.
- Published
- 2012
- Full Text
- View/download PDF
16. An expansive human regulatory lexicon encoded in transcription factor footprints.
- Author
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Neph S, Vierstra J, Stergachis AB, Reynolds AP, Haugen E, Vernot B, Thurman RE, John S, Sandstrom R, Johnson AK, Maurano MT, Humbert R, Rynes E, Wang H, Vong S, Lee K, Bates D, Diegel M, Roach V, Dunn D, Neri J, Schafer A, Hansen RS, Kutyavin T, Giste E, Weaver M, Canfield T, Sabo P, Zhang M, Balasundaram G, Byron R, MacCoss MJ, Akey JM, Bender MA, Groudine M, Kaul R, and Stamatoyannopoulos JA
- Subjects
- DNA Methylation, DNA-Binding Proteins metabolism, Deoxyribonuclease I metabolism, Genomic Imprinting, Genomics, Humans, Polymorphism, Single Nucleotide genetics, Transcription Initiation Site, DNA genetics, DNA Footprinting, Encyclopedias as Topic, Genome, Human genetics, Molecular Sequence Annotation, Regulatory Sequences, Nucleic Acid genetics, Transcription Factors metabolism
- Abstract
Regulatory factor binding to genomic DNA protects the underlying sequence from cleavage by DNase I, leaving nucleotide-resolution footprints. Using genomic DNase I footprinting across 41 diverse cell and tissue types, we detected 45 million transcription factor occupancy events within regulatory regions, representing differential binding to 8.4 million distinct short sequence elements. Here we show that this small genomic sequence compartment, roughly twice the size of the exome, encodes an expansive repertoire of conserved recognition sequences for DNA-binding proteins that nearly doubles the size of the human cis-regulatory lexicon. We find that genetic variants affecting allelic chromatin states are concentrated in footprints, and that these elements are preferentially sheltered from DNA methylation. High-resolution DNase I cleavage patterns mirror nucleotide-level evolutionary conservation and track the crystallographic topography of protein-DNA interfaces, indicating that transcription factor structure has been evolutionarily imprinted on the human genome sequence. We identify a stereotyped 50-base-pair footprint that precisely defines the site of transcript origination within thousands of human promoters. Finally, we describe a large collection of novel regulatory factor recognition motifs that are highly conserved in both sequence and function, and exhibit cell-selective occupancy patterns that closely parallel major regulators of development, differentiation and pluripotency.
- Published
- 2012
- Full Text
- View/download PDF
17. BEDOPS: high-performance genomic feature operations.
- Author
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Neph S, Kuehn MS, Reynolds AP, Haugen E, Thurman RE, Johnson AK, Rynes E, Maurano MT, Vierstra J, Thomas S, Sandstrom R, Humbert R, and Stamatoyannopoulos JA
- Subjects
- Data Compression methods, Genomics methods, Software
- Abstract
Unlabelled: The large and growing number of genome-wide datasets highlights the need for high-performance feature analysis and data comparison methods, in addition to efficient data storage and retrieval techniques. We introduce BEDOPS, a software suite for common genomic analysis tasks which offers improved flexibility, scalability and execution time characteristics over previously published packages. The suite includes a utility to compress large inputs into a lossless format that can provide greater space savings and faster data extractions than alternatives., Availability: http://code.google.com/p/bedops/ includes binaries, source and documentation.
- Published
- 2012
- Full Text
- View/download PDF
18. Comparative proteomics reveals deficiency of NHE-1 (Slc9a1) in RBCs from the beta-adducin knockout mouse model of hemolytic anemia.
- Author
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Gilligan DM, Finney GL, Rynes E, Maccoss MJ, Lambert AJ, Peters LL, Robledo RF, and Wooden JM
- Subjects
- Amino Acid Sequence, Anemia, Hemolytic chemically induced, Anemia, Hemolytic metabolism, Anemia, Hemolytic pathology, Animals, Blotting, Western, Cation Transport Proteins deficiency, Disease Models, Animal, Erythrocyte Count, Erythrocyte Membrane genetics, Erythrocyte Membrane metabolism, Erythrocytes cytology, Gene Expression Profiling, Mice, Mice, Inbred C57BL, Mice, Knockout, Molecular Sequence Data, Phenylhydrazines pharmacology, Protein Isoforms metabolism, Reticulocyte Count, Reticulocytes cytology, Sodium-Hydrogen Exchanger 1, Tandem Mass Spectrometry, Anemia, Hemolytic genetics, Calmodulin-Binding Proteins deficiency, Calmodulin-Binding Proteins genetics, Cation Transport Proteins genetics, Erythrocytes metabolism, Osmotic Fragility genetics, Phenylhydrazines adverse effects, Protein Isoforms genetics, Proteomics methods, Reticulocytes metabolism, Sodium-Hydrogen Exchangers genetics
- Abstract
Hemolytic anemia is one of the most common inherited disorders. To identify candidate proteins involved in hemolytic anemia pathophysiology, we utilized a label-free comparative proteomic approach to detect differences in RBCs from normal and beta-adducin (Add2) knock-out mice. We detected 7 proteins that were decreased and 48 proteins that were increased in the beta-adducin knock-out RBC ghost. Since hemolytic anemias are characterized by reticulocytosis, we compared reticulocyte-enriched samples from phenylhydrazine-treated mice with mature RBCs from untreated mice. Label-free analysis identified 47 proteins that were increased in the reticulocyte-enriched samples and 21 proteins that were decreased. Among the proteins increased in Add2 knockout RBCs, only 11 were also found increased in reticulocytes. Among the proteins decreased in Add2 knockout RBCs, beta- and alpha-adducin showed the greatest intensity difference, followed by NHE-1 (Slc9a1), the sodium-hydrogen exchanger. We verified these mass spectrometry results by immunoblot. This is the first example of a deficiency of NHE-1 in hemolytic anemia and suggests new insights into the mechanisms leading to fragile RBCs. Our use of label-free comparative proteomics to make this discovery demonstrates the usefulness of this approach as opposed to metabolic or chemical isotopic labeling of mice., (Copyright © 2011 Elsevier Inc. All rights reserved.)
- Published
- 2011
- Full Text
- View/download PDF
19. Comparative proteomics reveals deficiency of SLC9A1 (sodium/hydrogen exchanger NHE1) in β-adducin null red cells.
- Author
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Wooden JM, Finney GL, Rynes E, Maccoss MJ, Lambert AJ, Robledo RF, Peters LL, and Gilligan DM
- Subjects
- Animals, Blood Proteins metabolism, Cation Transport Proteins blood, Cytoskeletal Proteins, Erythrocyte Membrane metabolism, Mice, Mice, Knockout, Microfilament Proteins blood, Proteomics methods, Reticulocytes metabolism, Sodium-Hydrogen Exchanger 1, Sodium-Hydrogen Exchangers blood, Cation Transport Proteins deficiency, Erythrocytes metabolism, Microfilament Proteins deficiency
- Abstract
Spherocytosis is one of the most common inherited disorders, yet presents with a wide range of clinical severity. While several genes have been found mutated in patients with spherocytosis, the molecular basis for the variability in severity of haemolytic anaemia is not entirely understood. To identify candidate proteins involved in haemolytic anaemia pathophysiology, we utilized a label-free comparative proteomic approach to detect differences in red blood cells (RBCs) from normal and β-adducin (Add2) knock-out mice. We detected seven proteins that were decreased and 48 proteins that were increased in β-adducin null RBC ghosts. Since haemolytic anaemias are characterized by reticulocytosis, we compared reticulocyte-enriched samples from phenylhydrazine-treated mice with mature RBCs from untreated mice. Among the 48 proteins increased in Add2 knockout RBCs, only 11 were also increased in reticulocytes. Of the proteins decreased in Add2 knockout RBCs, α-adducin showed the greatest intensity difference, followed by SLC9A1, the sodium-hydrogen exchanger previously termed NHE1. We verified these mass spectrometry results by immunoblot. This is the first example of SLC9A1deficiency in haemolytic anaemia and suggests new insights into the mechanisms leading to fragile RBCs., (© 2011 Blackwell Publishing Ltd.)
- Published
- 2011
- Full Text
- View/download PDF
20. DNA evidence for historic population size and past ecosystem impacts of gray whales.
- Author
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Alter SE, Rynes E, and Palumbi SR
- Subjects
- Animals, Computer Simulation, Molecular Sequence Data, Mutation, Pacific Ocean, Population Dynamics, Sequence Analysis, DNA, Ecosystem, Genetic Variation, Genetics, Population, Whales genetics
- Abstract
Ecosystem restoration may require returning threatened populations of ecologically pivotal species to near their former abundances, but it is often difficult to estimate historic population size of species that have been heavily exploited. Eastern Pacific gray whales play a key ecological role in their Arctic feeding grounds and are widely thought to have returned to their prewhaling abundance. Recent mortality spikes might signal that the population has reached long-term carrying capacity, but an alternative is that this decline was due to shifting climatic conditions on Arctic feeding grounds. We used a genetic approach to estimate prewhaling abundance of gray whales and report DNA variability at 10 loci that is typical of a population of approximately 76,000-118,000 individuals, approximately three to five times more numerous than today's average census size of 22,000. Coalescent simulations indicate these estimates may include the entire Pacific metapopulation, suggesting that our average measurement of approximately 96,000 individuals was probably distributed between the eastern and currently endangered western Pacific populations. These levels of genetic variation suggest the eastern population is at most at 28-56% of its historical abundance and should be considered depleted. If used to inform management, this would halve acceptable human-caused mortality for this population from 417 to 208 per year. Potentially profound ecosystem impacts may have resulted from a decline from 96,000 gray whales to the current population. At previous levels, gray whales may have seasonally resuspended 700 million cubic meters of sediment, as much as 12 Yukon Rivers, and provided food to a million sea birds.
- Published
- 2007
- Full Text
- View/download PDF
21. Updated description of quarkonium by power-law potentials.
- Author
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Grant AK, Rosner JL, and Rynes E
- Published
- 1993
- Full Text
- View/download PDF
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