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210 results on '"Ward, Lucas D."'

1. Plasma proteomic associations with genetics and health in the UK Biobank

Author

Sun, Benjamin B., Chiou, Joshua, Traylor, Matthew, Benner, Christian, Hsu, Yi-Hsiang, Richardson, Tom G., Surendran, Praveen, Mahajan, Anubha, Robins, Chloe, Vasquez-Grinnell, Steven G., Hou, Liping, Kvikstad, Erika M., Burren, Oliver S., Davitte, Jonathan, Ferber, Kyle L., Gillies, Christopher E., Hedman, Åsa K., Hu, Sile, Lin, Tinchi, Mikkilineni, Rajesh, Pendergrass, Rion K., Pickering, Corran, Prins, Bram, Baird, Denis, Chen, Chia-Yen, Ward, Lucas D., Deaton, Aimee M., Welsh, Samantha, Willis, Carissa M., Lehner, Nick, Arnold, Matthias, Wörheide, Maria A., Suhre, Karsten, Kastenmüller, Gabi, Sethi, Anurag, Cule, Madeleine, Raj, Anil, Burkitt-Gray, Lucy, Melamud, Eugene, Black, Mary Helen, Fauman, Eric B., Howson, Joanna M. M., Kang, Hyun Min, McCarthy, Mark I., Nioi, Paul, Petrovski, Slavé, Scott, Robert A., Smith, Erin N., Szalma, Sándor, Waterworth, Dawn M., Mitnaul, Lyndon J., Szustakowski, Joseph D., Gibson, Bradford W., Miller, Melissa R., and Whelan, Christopher D.

Published
2023
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7. Nonclinical cardiovascular safety evaluation of romosozumab, an inhibitor of sclerostin for the treatment of osteoporosis in postmenopausal women at high risk of fracture

Author

Turk, James R., Deaton, Aimee M., Yin, Jun, Stolina, Marina, Felx, Melanie, Boyd, Gabrielle, Bienvenu, Jean-Guy, Varela, Aurore, Guillot, Martin, Holdsworth, Gill, Wolfreys, Alison, Dwyer, Denise, Kumar, Sheetal V., de Koning, Emily M., Qu, Yusheng, Engwall, Michael, Locher, Kathrin, Ward, Lucas D., Glaus, Charles, He, Yudong D., and Boyce, Rogely Waite

Published
2020
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9. Association of the transthyretin variant V122I with polyneuropathy among individuals of African ancestry

Author

Parker, Margaret M., Damrauer, Scott M., Tcheandjieu, Catherine, Erbe, David, Aldinc, Emre, Hawkins, Philip N., Gillmore, Julian D., Hull, Leland E., Lynch, Julie A., Joseph, Jacob, Ticau, Simina, Flynn-Carroll, Alexander O., Deaton, Aimee M., Ward, Lucas D., Assimes, Themistocles L., Tsao, Philip S., Chang, Kyong-Mi, Rader, Daniel J., Fitzgerald, Kevin, Vaishnaw, Akshay K., Hinkle, Gregory, and Nioi, Paul

Published
2021
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11. Classification of Saccharomyces cerevisiae promoter regions into distinct chromatin classes reveals the existence of nucleosome-depleted hotspots of transcription factor occupancy

Author

Wang, Junbai, Ward, Lucas D., and Bussemaker, Harmen J.

Subjects
Quantitative Biology - Genomics
Abstract

Transcription factors (TF) play an essential role in the cell as locus- and condition-specific recruiters of transcriptional machinery or chromatin-modifying complexes. However, predicting the in vivo profile of TF occupancy along the genome, which depends on complex interactions with other chromatin-associated proteins, from the DNA sequence remains a major challenge. Through careful reanalysis of ChIP-chip data for 138 TFs obtained in rich media, we were able to classify the upstream promoter regions of S. cerevisiae into 15 distinct chromatin types. One of these encompasses 5% of all promoters and is unique in that it is highly occupied by (essentially) all TFs expressed in rich media. These "hotspots" of TF occupancy are strongly nucleosome-depleted and preferentially targeted by chromatin-remodeling complexes and the origin-of-replication complex (ORC). They are also the only chromatin type enriched for predicted Rap1p and Pdr1p binding sites, which we found to work cooperatively with AAA/TTT motifs, known to affect local DNA structure, to reduce nucleosome occupancy. Taken together, our results reveal and characterize a new type of local chromatin structure in yeast., Comment: This paper has been withdrawn by the author due to a crucial error in the text

Published
2010

12. Common Genetic Variants Modulate Pathogen-Sensing Responses in Human Dendritic Cells

Author

Lee, Mark N, Ye, Chun, Villani, Alexandra-Chloé, Raj, Towfique, Li, Weibo, Eisenhaure, Thomas M, Imboywa, Selina H, Chipendo, Portia I, Ran, F Ann, Slowikowski, Kamil, Ward, Lucas D, Raddassi, Khadir, McCabe, Cristin, Lee, Michelle H, Frohlich, Irene Y, Hafler, David A, Kellis, Manolis, Raychaudhuri, Soumya, Zhang, Feng, Stranger, Barbara E, Benoist, Christophe O, De Jager, Philip L, Regev, Aviv, and Hacohen, Nir

Subjects
Infectious Diseases, Influenza, Genetics, Biodefense, Emerging Infectious Diseases, Vaccine Related, Prevention, Pneumonia & Influenza, Aetiology, 2.1 Biological and endogenous factors, Infection, Inflammatory and immune system, Adult, Autoimmune Diseases, Communicable Diseases, Dendritic Cells, Escherichia coli, Female, Gene-Environment Interaction, Genetic Loci, Genome-Wide Association Study, HEK293 Cells, Host-Pathogen Interactions, Humans, Influenza A virus, Interferon Regulatory Factor-7, Interferon-beta, Lipopolysaccharides, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, STAT Transcription Factors, Transcriptome, Young Adult, General Science & Technology
Abstract

Little is known about how human genetic variation affects the responses to environmental stimuli in the context of complex diseases. Experimental and computational approaches were applied to determine the effects of genetic variation on the induction of pathogen-responsive genes in human dendritic cells. We identified 121 common genetic variants associated in cis with variation in expression responses to Escherichia coli lipopolysaccharide, influenza, or interferon-β (IFN-β). We localized and validated causal variants to binding sites of pathogen-activated STAT (signal transducer and activator of transcription) and IRF (IFN-regulatory factor) transcription factors. We also identified a common variant in IRF7 that is associated in trans with type I IFN induction in response to influenza infection. Our results reveal common alleles that explain interindividual variation in pathogen sensing and provide functional annotation for genetic variants that alter susceptibility to inflammatory diseases.

Published
2014

14. A high-resolution map of human evolutionary constraint using 29 mammals.

Author

Lindblad-Toh, Kerstin, Garber, Manuel, Zuk, Or, Lin, Michael F, Parker, Brian J, Washietl, Stefan, Kheradpour, Pouya, Ernst, Jason, Jordan, Gregory, Mauceli, Evan, Ward, Lucas D, Lowe, Craig B, Holloway, Alisha K, Clamp, Michele, Gnerre, Sante, Alföldi, Jessica, Beal, Kathryn, Chang, Jean, Clawson, Hiram, Cuff, James, Di Palma, Federica, Fitzgerald, Stephen, Flicek, Paul, Guttman, Mitchell, Hubisz, Melissa J, Jaffe, David B, Jungreis, Irwin, Kent, W James, Kostka, Dennis, Lara, Marcia, Martins, Andre L, Massingham, Tim, Moltke, Ida, Raney, Brian J, Rasmussen, Matthew D, Robinson, Jim, Stark, Alexander, Vilella, Albert J, Wen, Jiayu, Xie, Xiaohui, Zody, Michael C, Broad Institute Sequencing Platform and Whole Genome Assembly Team, Baldwin, Jen, Bloom, Toby, Chin, Chee Whye, Heiman, Dave, Nicol, Robert, Nusbaum, Chad, Young, Sarah, Wilkinson, Jane, Worley, Kim C, Kovar, Christie L, Muzny, Donna M, Gibbs, Richard A, Baylor College of Medicine Human Genome Sequencing Center Sequencing Team, Cree, Andrew, Dihn, Huyen H, Fowler, Gerald, Jhangiani, Shalili, Joshi, Vandita, Lee, Sandra, Lewis, Lora R, Nazareth, Lynne V, Okwuonu, Geoffrey, Santibanez, Jireh, Warren, Wesley C, Mardis, Elaine R, Weinstock, George M, Wilson, Richard K, Genome Institute at Washington University, Delehaunty, Kim, Dooling, David, Fronik, Catrina, Fulton, Lucinda, Fulton, Bob, Graves, Tina, Minx, Patrick, Sodergren, Erica, Birney, Ewan, Margulies, Elliott H, Herrero, Javier, Green, Eric D, Haussler, David, Siepel, Adam, Goldman, Nick, Pollard, Katherine S, Pedersen, Jakob S, Lander, Eric S, and Kellis, Manolis

Subjects
Broad Institute Sequencing Platform and Whole Genome Assembly Team, Baylor College of Medicine Human Genome Sequencing Center Sequencing Team, Genome Institute at Washington University, Animals, Mammals, Humans, Disease, RNA, Sequence Alignment, Sequence Analysis, DNA, Genomics, Evolution, Molecular, Phylogeny, Genome, Genome, Human, Exons, Health, Selection, Genetic, Molecular Sequence Annotation, Sequence Analysis, DNA, Evolution, Molecular, Human, Selection, Genetic, General Science & Technology
Abstract

The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ∼4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ∼60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease.

Published
2011

15. Mapping and analysis of chromatin state dynamics in nine human cell types

Author

Ernst, Jason, Kheradpour, Pouya, Mikkelsen, Tarjei S, Shoresh, Noam, Ward, Lucas D, Epstein, Charles B, Zhang, Xiaolan, Wang, Li, Issner, Robbyn, Coyne, Michael, Ku, Manching, Durham, Timothy, Kellis, Manolis, and Bernstein, Bradley E

Subjects
Genetics, Biotechnology, Cancer, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Binding Sites, Cell Line, Cell Line, Tumor, Cell Physiological Phenomena, Cells, Cultured, Chromatin, Chromosome Mapping, Gene Expression Regulation, Genome, Human, Hep G2 Cells, Humans, Promoter Regions, Genetic, Reproducibility of Results, Transcription Factors, General Science & Technology
Abstract

Chromatin profiling has emerged as a powerful means of genome annotation and detection of regulatory activity. The approach is especially well suited to the characterization of non-coding portions of the genome, which critically contribute to cellular phenotypes yet remain largely uncharted. Here we map nine chromatin marks across nine cell types to systematically characterize regulatory elements, their cell-type specificities and their functional interactions. Focusing on cell-type-specific patterns of promoters and enhancers, we define multicell activity profiles for chromatin state, gene expression, regulatory motif enrichment and regulator expression. We use correlations between these profiles to link enhancers to putative target genes, and predict the cell-type-specific activators and repressors that modulate them. The resulting annotations and regulatory predictions have implications for the interpretation of genome-wide association studies. Top-scoring disease single nucleotide polymorphisms are frequently positioned within enhancer elements specifically active in relevant cell types, and in some cases affect a motif instance for a predicted regulator, thus suggesting a mechanism for the association. Our study presents a general framework for deciphering cis-regulatory connections and their roles in disease.

Published
2011

19. Defining functional DNA elements in the human genome

Author

Kellis, Manolis, Wold, Barbara, Snyderd, Michael P., Bernstein, Bradley E., Kundaje, Anshul, Marinov, Georgi K., Ward, Lucas D., Birney, Ewan, Crawford, Gregory E., Dekker, Job, Dunham, Ian, Elnitski, Laura L., Farnham, Peggy J., Feingold, Elise A., Gerstein, Mark, Giddings, Morgan C., Gilbert, David M., Gingeras, Thomas R., Green, Eric D., Guigo, Roderic, Hubbard, Tim, Kent, Jim, Lieb, Jason D., Myerst, Richard M., Pazin, Michael J., Ren, Bing, Stamatoyannopoulos, John A., Weng, Zhiping, White, Kevin P., and Hardison, Ross C.

Published
2014

20. Using human genetics to improve safety assessment of therapeutics

Author

Carss, Keren J., primary, Deaton, Aimee M., additional, Del Rio-Espinola, Alberto, additional, Diogo, Dorothée, additional, Fielden, Mark, additional, Kulkarni, Diptee A., additional, Moggs, Jonathan, additional, Newham, Peter, additional, Nelson, Matthew R., additional, Sistare, Frank D., additional, Ward, Lucas D., additional, and Yuan, Jing, additional

Published
2022
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21. Parental influence on human germline de novo mutations in 1,548 trios from Iceland

Author

Jónsson, Hákon, Sulem, Patrick, Kehr, Birte, Kristmundsdottir, Snaedis, Zink, Florian, Hjartarson, Eirikur, Hardarson, Marteinn T., Hjorleifsson, Kristjan E., Eggertsson, Hannes P., Gudjonsson, Sigurjon Axel, Ward, Lucas D., Arnadottir, Gudny A., Helgason, Einar A., Helgason, Hannes, Gylfason, Arnaldur, Jonasdottir, Adalbjorg, Jonasdottir, Aslaug, Rafnar, Thorunn, Frigge, Mike, Stacey, Simon N., Th. Magnusson, Olafur, Thorsteinsdottir, Unnur, Masson, Gisli, Kong, Augustine, Halldorsson, Bjarni V., Helgason, Agnar, Gudbjartsson, Daniel F., and Stefansson, Kari

Published
2017
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23. A rare missense variant in NR1H4 associates with lower cholesterol levels

Author

Deaton, Aimee M., Sulem, Patrick, Nioi, Paul, Benonisdottir, Stefania, Ward, Lucas D., Davidsson, Olafur B., Lao, Socheata, Helgadottir, Anna, Fan, Fan, Jensson, Brynjar O., Norddahl, Gudmundur L., Jonasdottir, Aslaug, Jonasdottir, Adalbjorg, Sigurdsson, Asgeir, Kristjansson, Ragnar P., Oddsson, Asmundur, Arnadottir, Gudny A., Jonsson, Hakon, Olafsson, Isleifur, Eyjolfsson, Gudmundur I., Sigurdardottir, Olof, Bjornsson, Einar S., Olafsson, Sigurdur, Steingrimsdottir, Thora, Rafnar, Thorunn, Thorgeirsson, Gudmundur, Masson, Gisli, Thorleifsson, Gudmar, Gudbjartsson, Daniel F., Holm, Hilma, Thorsteinsdottir, Unnur, and Stefansson, Kari

Published
2018
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26. An integrated encyclopedia of DNA elements in the human genome

Author

Dunham, Ian, Kundaje, Anshul, Aldred, Shelley F., Collins, Patrick J., Davis, Carrie A., Doyle, Francis, Epstein, Charles B., Frietze, Seth, Harrow, Jennifer, Kaul, Rajinder, Khatun, Jainab, Lajoie, Bryan R., Landt, Stephen G., Lee, Bum-Kyu, Pauli, Florencia, Rosenbloom, Kate R., Sabo, Peter, Safi, Alexias, Sanyal, Amartya, Shoresh, Noam, Simon, Jeremy M., Song, Lingyun, Trinklein, Nathan D., Altshuler, Robert C., Birney, Ewan, Brown, James B., Cheng, Chao, Djebali, Sarah, Dong, Xianjun, Ernst, Jason, Furey, Terrence S., Gerstein, Mark, Giardine, Belinda, Greven, Melissa, Hardison, Ross C., Harris, Robert S., Herrero, Javier, Hoffman, Michael M., Iyer, Sowmya, Kellis, Manolis, Kheradpour, Pouya, Lassmann, Timo, Li, Qunhua, Lin, Xinying, Marinov, Georgi K., Merkel, Angelika, Mortazavi, Ali, Parker, Stephen C. J., Reddy, Timothy E., Rozowsky, Joel, Schlesinger, Felix, Thurman, Robert E., Wang, Jie, Ward, Lucas D., Whitfield, Troy W., Wilder, Steven P., Wu, Weisheng, Xi, Hualin S., Yip, Kevin Y., Zhuang, Jiali, Bernstein, Bradley E., Green, Eric D., Gunter, Chris, Snyder, Michael, Pazin, Michael J., Lowdon, Rebecca F., Dillon, Laura A. L., Adams, Leslie B., Kelly, Caroline J., Zhang, Julia, Wexler, Judith R., Good, Peter J., Feingold, Elise A., Crawford, Gregory E., Dekker, Job, Elnitski, Laura, Farnham, Peggy J., Giddings, Morgan C., Gingeras, Thomas R., Guigo, Roderic, Hubbard, Timothy J., Kent, W. James, Lieb, Jason D., Margulies, Elliott H., Myers, Richard M., Stamatoyannopoulos, John A., Tenenbaum, Scott A., Weng, Zhiping, White, Kevin P., Wold, Barbara, Yu, Yanbao, Wrobel, John, Risk, Brian A., Gunawardena, Harsha P., Kuiper, Heather C., Maier, Christopher W., Xie, Ling, Chen, Xian, Mikkelsen, Tarjei S., Gillespie, Shawn, Goren, Alon, Ram, Oren, Zhang, Xiaolan, Wang, Li, Issner, Robbyn, Coyne, Michael J., Durham, Timothy, Ku, Manching, Truong, Thanh, Eaton, Matthew L., Dobin, Alex, Tanzer, Andrea, Lagarde, Julien, Lin, Wei, Xue, Chenghai, Williams, Brian A., Zaleski, Chris, Roder, Maik, Kokocinski, Felix, Abdelhamid, Rehab F., Alioto, Tyler, Antoshechkin, Igor, Baer, Michael T., Batut, Philippe, Bell, Ian, Bell, Kimberly, Chakrabortty, Sudipto, Chrast, Jacqueline, Curado, Joao, Derrien, Thomas, Drenkow, Jorg, Dumais, Erica, Dumais, Jackie, Duttagupta, Radha, Fastuca, Megan, Fejes-Toth, Kata, Ferreira, Pedro, Foissac, Sylvain, Fullwood, Melissa J., Gao, Hui, Gonzalez, David, Gordon, Assaf, Howald, Cedric, Jha, Sonali, Johnson, Rory, Kapranov, Philipp, King, Brandon, Kingswood, Colin, Li, Guoliang, Luo, Oscar J., Park, Eddie, Preall, Jonathan B., Presaud, Kimberly, Ribeca, Paolo, Robyr, Daniel, Ruan, Xiaoan, Sammeth, Michael, Sandhu, Kuljeet Singh, Schaeffer, Lorain, See, Lei-Hoon, Shahab, Atif, Skancke, Jorgen, Suzuki, Ana Maria, Takahashi, Hazuki, Tilgner, Hagen, Trout, Diane, Walters, Nathalie, Wang, Huaien, Hayashizaki, Yoshihide, Reymond, Alexandre, Antonarakis, Stylianos E., Hannon, Gregory J., Ruan, Yijun, Carninci, Piero, Sloan, Cricket A., Learned, Katrina, Malladi, Venkat S., Wong, Matthew C., Barber, Galt P., Cline, Melissa S., Dreszer, Timothy R., Heitner, Steven G., Karolchik, Donna, Kirkup, Vanessa M., Meyer, Laurence R., Long, Jeffrey C., Maddren, Morgan, Raney, Brian J., Grasfeder, Linda L., Giresi, Paul G., Battenhouse, Anna, Sheffield, Nathan C., Showers, Kimberly A., London, Darin, Bhinge, Akshay A., Shestak, Christopher, Schaner, Matthew R., Ki Kim, Seul, Zhang, Zhuzhu Z., Mieczkowski, Piotr A., Mieczkowska, Joanna O., Liu, Zheng, McDaniell, Ryan M., Ni, Yunyun, Rashid, Naim U., Kim, Min Jae, Adar, Sheera, Zhang, Zhancheng, Wang, Tianyuan, Winter, Deborah, Keefe, Damian, Iyer, Vishwanath R., Zheng, Meizhen, Wang, Ping, Gertz, Jason, Vielmetter, Jost, Partridge, E., Varley, Katherine E., Gasper, Clarke, Bansal, Anita, Pepke, Shirley, Jain, Preti, Amrhein, Henry, Bowling, Kevin M., Anaya, Michael, Cross, Marie K., Muratet, Michael A., Newberry, Kimberly M., McCue, Kenneth, Nesmith, Amy S., Fisher-Aylor, Katherine I., Pusey, Barbara, DeSalvo, Gilberto, Parker, Stephanie L., Balasubramanian, Sreeram, Davis, Nicholas S., Meadows, Sarah K., Eggleston, Tracy, Newberry, J. Scott, Levy, Shawn E., Absher, Devin M., Wong, Wing H., Blow, Matthew J., Visel, Axel, Pennachio, Len A., Petrykowska, Hanna M., Abyzov, Alexej, Aken, Bronwen, Barrell, Daniel, Barson, Gemma, Berry, Andrew, Bignell, Alexandra, Boychenko, Veronika, Bussotti, Giovanni, Davidson, Claire, Despacio-Reyes, Gloria, Diekhans, Mark, Ezkurdia, Iakes, Frankish, Adam, Gilbert, James, Gonzalez, Jose Manuel, Griffiths, Ed, Harte, Rachel, Hendrix, David A., Hunt, Toby, Jungreis, Irwin, Kay, Mike, Khurana, Ekta, Leng, Jing, Lin, Michael F., Loveland, Jane, Lu, Zhi, Manthravadi, Deepa, Mariotti, Marco, Mudge, Jonathan, Mukherjee, Gaurab, Notredame, Cedric, Pei, Baikang, Rodriguez, Jose Manuel, Saunders, Gary, Sboner, Andrea, Searle, Stephen, Sisu, Cristina, Snow, Catherine, Steward, Charlie, Tapanari, Electra, Tress, Michael L., van Baren, Marijke J., Washietl, Stefan, Wilming, Laurens, Zadissa, Amonida, Zhang, Zhengdong, Brent, Michael, Haussler, David, Valencia, Alfonso, Addleman, Nick, Alexander, Roger P., Auerbach, Raymond K., Balasubramanian, Suganthi, Bettinger, Keith, Bhardwaj, Nitin, Boyle, Alan P., Cao, Alina R., Cayting, Philip, Charos, Alexandra, Cheng, Yong, Eastman, Catharine, Euskirchen, Ghia, Fleming, Joseph D., Grubert, Fabian, Habegger, Lukas, Hariharan, Manoj, Harmanci, Arif, Iyengar, Sushma, Jin, Victor X., Karczewski, Konrad J., Kasowski, Maya, Lacroute, Phil, Lam, Hugo, Lamarre-Vincent, Nathan, Lian, Jin, Lindahl-Allen, Marianne, Min, Renqiang, Miotto, Benoit, Monahan, Hannah, Moqtaderi, Zarmik, Mu, Xinmeng J., Ouyang, Zhengqing, Patacsil, Dorrelyn, Raha, Debasish, Ramirez, Lucia, Reed, Brian, Shi, Minyi, Slifer, Teri, Witt, Heather, Wu, Linfeng, Xu, Xiaoqin, Yan, Koon-Kiu, Yang, Xinqiong, Struhl, Kevin, Weissman, Sherman M., Penalva, Luiz O., Karmakar, Subhradip, Bhanvadia, Raj R., Choudhury, Alina, Domanus, Marc, Ma, Lijia, Moran, Jennifer, Victorsen, Alec, Auer, Thomas, Centanin, Lazaro, Eichenlaub, Michael, Gruhl, Franziska, Heermann, Stephan, Hoeckendorf, Burkhard, Inoue, Daigo, Kellner, Tanja, Kirchmaier, Stephan, Mueller, Claudia, Reinhardt, Robert, Schertel, Lea, Schneider, Stephanie, Sinn, Rebecca, Wittbrodt, Beate, Wittbrodt, Jochen, Partridge, E. Christopher, Jain, Gaurav, Balasundaram, Gayathri, Bates, Daniel L., Byron, Rachel, Canfield, Theresa K., Diegel, Morgan J., Dunn, Douglas, Ebersol, Abigail K., Frum, Tristan, Garg, Kavita, Gist, Erica, Hansen, R. Scott, Boatman, Lisa, Haugen, Eric, Humbert, Richard, Johnson, Audra K., Johnson, Ericka M., Kutyavin, Tattyana V., Lee, Kristen, Lotakis, Dimitra, Maurano, Matthew T., Neph, Shane J., Neri, Fiedencio V., Nguyen, Eric D., Qu, Hongzhu, Reynolds, Alex P., Roach, Vaughn, Rynes, Eric, Sanchez, Minerva E., Sandstrom, Richard S., Shafer, Anthony O., Stergachis, Andrew B., Thomas, Sean, Vernot, Benjamin, Vierstra, Jeff, Vong, Shinny, Weaver, Molly A., Yan, Yongqi, Zhang, Miaohua, Akey, Joshua M., Bender, Michael, Dorschner, Michael O., Groudine, Mark, MacCoss, Michael J., Navas, Patrick, Stamatoyannopoulos, George, Beal, Kathryn, Brazma, Alvis, Flicek, Paul, Johnson, Nathan, Lukk, Margus, Luscombe, Nicholas M., Sobral, Daniel, Vaquerizas, Juan M., Batzoglou, Serafim, Sidow, Arend, Hussami, Nadine, Kyriazopoulou-Panagiotopoulou, Sofia, Libbrecht, Max W., Schaub, Marc A., Miller, Webb, Bickel, Peter J., Banfai, Balazs, Boley, Nathan P., Huang, Haiyan, Li, Jingyi Jessica, Noble, William Stafford, Bilmes, Jeffrey A., Buske, Orion J., Sahu, Avinash D., Kharchenko, Peter V., Park, Peter J., Baker, Dannon, Taylor, James, and Lochovsky, Lucas

Subjects
Research, Genetic research, Transcription (Genetics) -- Research, Human genome -- Research, Genetic transcription -- Research
Abstract

Author(s): The ENCODE Project Consortium; Overall coordination (data analysis coordination); Ian Dunham [2]; Anshul Kundaje [3, 82]; Data production leads (data production); Shelley F. Aldred [4]; Patrick J. Collins [4]; [...], 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.

Published
2012
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27. Integrative analysis of 111 reference human epigenomes

Author

Consortium, Roadmap Epigenomics, Kundaje, Anshul, Meuleman, Wouter, Ernst, Jason, Bilenky, Misha, Yen, Angela, Heravi-Moussavi, Alireza, Kheradpour, Pouya, Zhang, Zhizhuo, Wang, Jianrong, Ziller, Michael J., Whitaker, John W., Ward, Lucas D., Sarkar, Abhishek, Sandstrom, Richard S., Wu, Yi-Chieh, Pfenning, Andreas R., Wang, Xinchen, Claussnitzer, Melina, Liu, Yaping, Harris, Alan R., Epstein, Charles B., Leung, Danny, Hawkins, David R., Hong, Chibo, Mungall, Andrew J., Chuah, Eric, Hansen, Scott R., Bansal, Mukul S., Dixon, Jesse R., Feizi, Soheil, Kim, Ah-Ram, Li, Daofeng, Elliott, GiNell, Neph, Shane J., Polak, Paz, Ray, Pradipta, Siebenthall, Kyle T., Thurman, Robert E., Zhou, Xin, Boyer, Laurie A., De Jager, Philip L., Fisher, Susan J., Li, Wei, McManus, Michael T., Sunyaev, Shamil, Tlsty, Thea D., Wang, Wei, Waterland, Robert A., Costello, Joseph F., Hirst, Martin, Stamatoyannopoulos, John A., Wang, Ting, Amin, Viren, Schultz, Matthew D., Quon, Gerald, Eaton, Matthew L., Pfenning, Andreas, Liu, Melina ClaussnitzerYaping, Coarfa, Cristian, Shoresh, Noam, Gjoneska, Elizabeta, Xie, Wei, Lister, Ryan, Moore, Richard, Tam, Angela, Canfield, Theresa K., Kaul, Rajinder, Sabo, Peter J., Carles, Annaick, Farh, Kai-How, Karlic, Rosa, Kulkarni, Ashwinikumar, Lowdon, Rebecca, Mercer, Tim R., Onuchic, Vitor, Rajagopal, Nisha, Sallari, Richard C., Sinnott-Armstrong, Nicholas A., Stevens, Michael, Wu, Jie, Zhang, Bo, Abdennur, Nezar, Adli, Mazhar, Akerman, Martin, Barrera, Luis, Antosiewicz-Bourget, Jessica, Ballinger, Tracy, Barnes, Michael J., Bates, Daniel, Bell, Robert J. A., Bennett, David A., Bianco, Katherine, Bock, Christoph, Boyle, Patrick, Brinchmann, Jan, Caballero-Campo, Pedro, Camahort, Raymond, Carrasco-Alfonso, Marlene J., Charnecki, Timothy, Chen, Huaming, Chen, Zhao, Cheng, Jeffrey B., Cho, Stephanie, Chu, Andy, Chung, Wen-Yu, Cowan, Chad, Deng, Qixia Athena, Deshpande, Vikram, Diegel, Morgan, Ding, Bo, Durham, Timothy, Echipare, Lorigail, Edsall, Lee, Flowers, David, Genbacev-Krtolica, Olga, Gifford, Casey, Gillespie, Shawn, Giste, Erika, Glass, Ian A., Gnirke, Andreas, Gormley, Matthew, Gu, Hongcang, Gu, Junchen, Hafler, David A., Hangauer, Matthew J., Hariharan, Manoj, Hatan, Meital, Haugen, Eric, He, Yupeng, Heimfeld, Shelly, Herlofsen, Sarah, Hou, Zhonggang, Humbert, Richard, Issner, Robbyn, Jackson, Andrew R., Jia, Haiyang, Jiang, Peng, Johnson, Audra K., Kadlecek, Theresa, Kamoh, Baljit, Kapidzic, Mirhan, Kent, Jim, Kim, Audrey, Kleinewietfeld, Markus, Klugman, Sarit, Krishnan, Jayanth, Kuan, Samantha, Kutyavin, Tanya, Lee, Ah-Young, Lee, Kristen, Li, Jian, Li, Nan, Li, Yan, Ligon, Keith L., Lin, Shin, Lin, Yiing, Liu, Jie, Liu, Yuxuan, Luckey, John C., Ma, Yussanne P., Maire, Cecile, Marson, Alexander, Mattick, John S., Mayo, Michael, McMaster, Michael, Metsky, Hayden, Mikkelsen, Tarjei, Miller, Diane, Miri, Mohammad, Mukame, Eran, Nagarajan, Raman P., Neri, Fidencio, Nery, Joseph, Nguyen, Tung, OʼGeen, Henriette, Paithankar, Sameer, Papayannopoulou, Thalia, Pelizzola, Mattia, Plettner, Patrick, Propson, Nicholas E., Raghuraman, Sriram, Raney, Brian J., Raubitschek, Anthony, Reynolds, Alex P., Richards, Hunter, Riehle, Kevin, Rinaudo, Paolo, Robinson, Joshua F., Rockweiler, Nicole B., Rosen, Evan, Rynes, Eric, Schein, Jacqueline, Sears, Renee, Sejnowski, Terrence, Shafer, Anthony, Shen, Li, Shoemaker, Robert, Sigaroudinia, Mahvash, Slukvin, Igor, Stehling-Sun, Sandra, Stewart, Ron, Subramanian, Sai Lakshmi, Suknuntha, Kran, Swanson, Scott, Tian, Shulan, Tilden, Hannah, Tsai, Linus, Urich, Mark, Vaughn, Ian, Vierstra, Jeff, Vong, Shinny, Wagner, Ulrich, Wang, Hao, Wang, Tao, Wang, Yunfei, Weiss, Arthur, Whitton, Holly, Wildberg, Andre, Witt, Heather, Won, Kyoung-Jae, Xie, Mingchao, Xing, Xiaoyun, Xu, Iris, Xuan, Zhenyu, Ye, Zhen, Yen, Chia-an, Yu, Pengzhi, Zhang, Xian, Zhang, Xiaolan, Zhao, Jianxin, Zhou, Yan, Zhu, Jiang, Zhu, Yun, Ziegler, Steven, Beaudet, Arthur E., Farnham, Peggy J., Haussler, David, Jones, Steven J. M., Marra, Marco A., Thomson, James A., Tsai, Li-Huei, Zhang, Michael Q., Chadwick, Lisa H., Bernstein, Bradley E., Ecker, Joseph R., Meissner, Alexander, Milosavljevic, Aleksandar, Ren, Bing, and Kellis, Manolis

Published
2015
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30. Dissecting complex transcriptional responses using pathway-level scores based on prior information

Author

Ward Lucas D, Bussemaker Harmen J, and Boorsma Andre

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background The genomewide pattern of changes in mRNA expression measured using DNA microarrays is typically a complex superposition of the response of multiple regulatory pathways to changes in the environment of the cells. The use of prior information, either about the function of the protein encoded by each gene, or about the physical interactions between regulatory factors and the sequences controlling its expression, has emerged as a powerful approach for dissecting complex transcriptional responses. Results We review two different approaches for combining the noisy expression levels of multiple individual genes into robust pathway-level differential expression scores. The first is based on a comparison between the distribution of expression levels of genes within a predefined gene set and those of all other genes in the genome. The second starts from an estimate of the strength of genomewide regulatory network connectivities based on sequence information or direct measurements of protein-DNA interactions, and uses regression analysis to estimate the activity of gene regulatory pathways. The statistical methods used are explained in detail. Conclusion By avoiding the thresholding of individual genes, pathway-level analysis of differential expression based on prior information can be considerably more sensitive to subtle changes in gene expression than gene-level analysis. The methods are technically straightforward and yield results that are easily interpretable, both biologically and statistically.

Published
2007
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33. Association of the transthyretin variant V122I with polyneuropathy among individuals of African descent

Author

Parker, Margaret M., primary, Damrauer, Scott M., additional, Tcheandjieu, Catherine, additional, Erbe, David, additional, Aldinc, Emre, additional, Hawkins, Philip N., additional, Gillmore, Julian D., additional, Hull, Leland E., additional, Lynch, Julie A., additional, Joseph, Jacob, additional, Ticau, Simina, additional, Flynn-Carroll, Alexander O., additional, Deaton, Aimee M., additional, Ward, Lucas D., additional, Assimes, Themistocles L., additional, Tsao, Philip S., additional, Chang, Kyong-Mi, additional, Rader, Daniel J., additional, Fitzgerald, Kevin, additional, Vaishnaw, Akshay K., additional, Hinkle, Gregory, additional, and Nioi, Paul, additional

Published
2020
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34. The V122I Variant in Hereditary Transthyretin-Mediated Amyloidosis is Significantly Associated with Polyneuropathy

Author

Parker, Margaret M., primary, Damrauer, Scott M., additional, Tcheandjieu, Catherine, additional, Erbe, David, additional, Aldinc, Emre, additional, Hawkins, Philip N., additional, Gillmore, Julian, additional, Hull, Leland E., additional, Lynch, Julie A., additional, Joseph, Jacob, additional, Ticau, Simina, additional, Flynn-Carroll, Alexander O., additional, Deaton, Aimee M., additional, Ward, Lucas D., additional, Assimes, Themistocles L., additional, Tsao, Philip S., additional, Chang, Kyong-Mi, additional, Rader, Daniel J., additional, Fitzgerald, Kevin, additional, Vaishnaw, Akshay K., additional, Hinkle, Gregory, additional, and Nioi, Paul, additional

Published
2020
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36. Gene-level analysis of rare variants in 379,066 whole exome sequences identifies an association of GIGYF1 loss of function with type 2 diabetes.

Author

Deaton, Aimee M., Parker, Margaret M., Ward, Lucas D., Flynn-Carroll, Alexander O., BonDurant, Lucas, Hinkle, Gregory, Akbari, Parsa, Lotta, Luca A., Regeneron Genetics Center, RGC Management and Leadership Team, Abecasis, Goncalo, Baras, Aris, Cantor, Michael, Coppola, Giovanni, Economides, Aris, Overton, John D., Reid, Jeffrey G., Shuldiner, Alan, Karalis, Katia, and Deubler, Andrew

Subjects
TYPE 2 diabetes, GENETIC variation, HUMAN genetics, DIABETES, DIAGNOSIS, EXOMES
Abstract

Sequencing of large cohorts offers an unprecedented opportunity to identify rare genetic variants and to find novel contributors to human disease. We used gene-based collapsing tests to identify genes associated with glucose, HbA1c and type 2 diabetes (T2D) diagnosis in 379,066 exome-sequenced participants in the UK Biobank. We identified associations for variants in GCK, HNF1A and PDX1, which are known to be involved in Mendelian forms of diabetes. Notably, we uncovered novel associations for GIGYF1, a gene not previously implicated by human genetics in diabetes. GIGYF1 predicted loss of function (pLOF) variants associated with increased levels of glucose (0.77 mmol/L increase, p = 4.42 × 10–12) and HbA1c (4.33 mmol/mol, p = 1.28 × 10–14) as well as T2D diagnosis (OR = 4.15, p = 6.14 × 10–11). Multiple rare variants contributed to these associations, including singleton variants. GIGYF1 pLOF also associated with decreased cholesterol levels as well as an increased risk of hypothyroidism. The association of GIGYF1 pLOF with T2D diagnosis replicated in an independent cohort from the Geisinger Health System. In addition, a common variant association for glucose and T2D was identified at the GIGYF1 locus. Our results highlight the role of GIGYF1 in regulating insulin signaling and protecting from diabetes. [ABSTRACT FROM AUTHOR]

Published
2021
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37. The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans

Author

Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Ward, Lucas D., Kheradpour, Pouya, Iriarte, Benjamin, Kamvysselis, Manolis, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Ward, Lucas D., Kheradpour, Pouya, Iriarte, Benjamin, and Kamvysselis, Manolis

Abstract

Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysis of RNA sequencing data from 1641 samples across 43 tissues from 175 individuals, generated as part of the pilot phase of the Genotype-Tissue Expression (GTEx) project. We describe the landscape of gene expression across tissues, catalog thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants, describe complex network relationships, and identify signals from genome-wide association studies explained by eQTLs. These findings provide a systematic understanding of the cellular and biological consequences of human genetic variation and of the heterogeneity of such effects among a diverse set of human tissues.

Published
2019

38. Data Descriptor: Whole genome characterization of sequence diversity of 15,220 Icelanders

Author

Jónsson, Hakon, Sulem, Patrick, Kehr, Birte, Kristmundsdottir, Snaedis, Zink, Florian, Hjartarson, Eirikur, Hardarson, Marteinn T., Hjorleifsson, Kristjan E., Eggertsson, Hannes P., Gudjonsson, Sigurjon Axel, Ward, Lucas D., Arnadottir, Gudny A., Helgason, Einar A., Helgason, Hannes, Gylfason, Arnaldur, Jonasdottir, Adalbjorg, Jonasdottir, Aslaug, Rafnar, Thorunn, Besenbacher, Soren, Frigge, Michael L., Stacey, Simon N., Magnusson, Olafur Th, Thorsteinsdottir, Unnur, Masson, Gisli, Kong, Augustine, Halldorsson, Bjarni V., Helgason, Agnar, Gudbjartsson, Daniel F., and Stefansson, Kari

Abstract

© The Author(s) 2017. Understanding of sequence diversity is the cornerstone of analysis of genetic disorders, population genetics, and evolutionary biology. Here, we present an update of our sequencing set to 15,220 Icelanders who we sequenced to an average genome-wide coverage of 34X. We identified 39,020,168 autosomal variants passing GATK filters: 31,079,378 SNPs and 7,940,790 indels. Calling de novo mutations (DNMs) is a formidable challenge given the high false positive rate in sequencing datasets relative to the mutation rate. Here we addressed this issue by using segregation of alleles in three-generation families. Using this transmission assay, we controlled the false positive rate and identified 108,778 high quality DNMs. Furthermore, we used our extended family structure and read pair tracing of DNMs to a panel of phased SNPs, to determine the parent of origin of 42,961 DNMs.

Published
2017
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41. Interpreting non-coding variation in complex disease genetics

Author

Ward, Lucas D. and Kellis, Manolis

Subjects
RNA, Untranslated, Quantitative Trait Loci, Animals, Chromosome Mapping, Genetic Variation, Humans, Genetic Predisposition to Disease, Genetic Testing, Sequence Analysis, DNA, Article
Abstract

Association studies provide genome-wide information about the genetic basis of complex disease, but medical research has focused primarily on protein-coding variants, owing to the difficulty of interpreting noncoding mutations. This picture has changed with advances in the systematic annotation of functional noncoding elements. Evolutionary conservation, functional genomics, chromatin state, sequence motifs and molecular quantitative trait loci all provide complementary information about the function of noncoding sequences. These functional maps can help with prioritizing variants on risk haplotypes, filtering mutations encountered in the clinic and performing systems-level analyses to reveal processes underlying disease associations. Advances in predictive modeling can enable data-set integration to reveal pathways shared across loci and alleles, and richer regulatory models can guide the search for epistatic interactions. Lastly, new massively parallel reporter experiments can systematically validate regulatory predictions. Ultimately, advances in regulatory and systems genomics can help unleash the value of whole-genome sequencing for personalized genomic risk assessment, diagnosis and treatment.

Published
2012

42. Whole genome characterization of sequence diversity of 15,220 Icelanders

Author

Jónsson, Hákon, primary, Sulem, Patrick, additional, Kehr, Birte, additional, Kristmundsdottir, Snaedis, additional, Zink, Florian, additional, Hjartarson, Eirikur, additional, Hardarson, Marteinn T., additional, Hjorleifsson, Kristjan E., additional, Eggertsson, Hannes P., additional, Gudjonsson, Sigurjon Axel, additional, Ward, Lucas D., additional, Arnadottir, Gudny A., additional, Helgason, Einar A., additional, Helgason, Hannes, additional, Gylfason, Arnaldur, additional, Jonasdottir, Adalbjorg, additional, Jonasdottir, Aslaug, additional, Rafnar, Thorunn, additional, Besenbacher, Soren, additional, Frigge, Michael L., additional, Stacey, Simon N., additional, Magnusson, Olafur Th., additional, Thorsteinsdottir, Unnur, additional, Masson, Gisli, additional, Kong, Augustine, additional, Halldorsson, Bjarni V., additional, Helgason, Agnar, additional, Gudbjartsson, Daniel F., additional, and Stefansson, Kari, additional

Published
2017
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43. Synchronized age-related gene expression changes across multiple tissues in human and the link to complex diseases

Author

Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Ward, Lucas D., Kheradpour, Pouya, Iriarte, Benjamin, Kellis, Manolis, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Ward, Lucas D., Kheradpour, Pouya, Iriarte, Benjamin, and Kellis, Manolis

Abstract

Aging is one of the most important biological processes and is a known risk factor for many age-related diseases in human. Studying age-related transcriptomic changes in tissues across the whole body can provide valuable information for a holistic understanding of this fundamental process. In this work, we catalogue age-related gene expression changes in nine tissues from nearly two hundred individuals collected by the Genotype-Tissue Expression (GTEx) project. In general, we find the aging gene expression signatures are very tissue specific. However, enrichment for some well-known aging components such as mitochondria biology is observed in many tissues. Different levels of cross-tissue synchronization of age-related gene expression changes are observed, and some essential tissues (e.g., heart and lung) show much stronger “co-aging” than other tissues based on a principal component analysis. The aging gene signatures and complex disease genes show a complex overlapping pattern and only in some cases, we see that they are significantly overlapped in the tissues affected by the corresponding diseases. In summary, our analyses provide novel insights to the co-regulation of age-related gene expression in multiple tissues; it also presents a tissue-specific view of the link between aging and age-related diseases., National Cancer Institute (U.S.), National Human Genome Research Institute (U.S.), National Heart, Lung, and Blood Institute, National Institute on Drug Abuse (NIDA), National Institute of Mental Health (U.S.), National Institute of Neurological Disorders and Stroke (U.S.)

Published
2016

44. Integrative analysis of 111 reference human epigenomes

Author

Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Biology, Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Picower Institute for Learning and Memory, Kundaje, Anshul, Meuleman, Wouter, Ernst, Jason, Yen, Angela, Kheradpour, Pouya, Zhang, Zhizhuo, Wang, Jianrong, Ward, Lucas D., Sarkar, Abhishek Kulshreshtha, Quon, Gerald, Eaton, Matthew Lucas, Wu, Yi-Chieh, Pfenning, Andreas R., Wang, Xinchen, Claussnitzer, Melina, Liu, Yaping, Bansal, Mukul S., Feizi-Khankandi, Soheil, Kim, Ah Ram, Cowper Sal-lari, Richard, Sinnott-Armstrong, Nicholas A., Kellis, Manolis, Boyer, Laurie, Gjoneska, Elizabeta, Tsai, Li-Huei, Feizi- Khankandi, Soheil, Boyer, Laurie Ann, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Biology, Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Picower Institute for Learning and Memory, Kundaje, Anshul, Meuleman, Wouter, Ernst, Jason, Yen, Angela, Kheradpour, Pouya, Zhang, Zhizhuo, Wang, Jianrong, Ward, Lucas D., Sarkar, Abhishek Kulshreshtha, Quon, Gerald, Eaton, Matthew Lucas, Wu, Yi-Chieh, Pfenning, Andreas R., Wang, Xinchen, Claussnitzer, Melina, Liu, Yaping, Bansal, Mukul S., Feizi-Khankandi, Soheil, Kim, Ah Ram, Cowper Sal-lari, Richard, Sinnott-Armstrong, Nicholas A., Kellis, Manolis, Boyer, Laurie, Gjoneska, Elizabeta, Tsai, Li-Huei, Feizi- Khankandi, Soheil, and Boyer, Laurie Ann

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., National Human Genome Research Institute (U.S.) (RC1HG005334), National Human Genome Research Institute (U.S.) (R01HG004037), National Human Genome Research Institute (U.S.) (R01HG004037-S1), National Human Genome Research Institute (U.S.) (RO1NS078839), National Science Foundation (U.S.) (CAREER Award 1254200)

Published
2016

45. Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers

Author

Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Ward, Lucas D., Kundaje, Anshul, Kellis, Manolis, Onengut-Gumuscu, Suna, Chen, Wei-Min, Burren, Oliver, Farber, Emily, Szpak, Michal, Schofield, Ellen, Achuthan, Premanand, Guo, Hui, Stevens, Helen, Deloukas, Panos, Wallace, Chris, Concannon, Patrick, Cooper, Nick J., Quinlan, Aaron R., Mychaleckyj, Josyf C., Bonnie, Jessica K., Fortune, Mary D., Walker, Neil M., Daly, Mark J., Barrett, Jeffrey C., Cooper, Jason D., Todd, John A., Rich, Stephen S., Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Ward, Lucas D., Kundaje, Anshul, Kellis, Manolis, Onengut-Gumuscu, Suna, Chen, Wei-Min, Burren, Oliver, Farber, Emily, Szpak, Michal, Schofield, Ellen, Achuthan, Premanand, Guo, Hui, Stevens, Helen, Deloukas, Panos, Wallace, Chris, Concannon, Patrick, Cooper, Nick J., Quinlan, Aaron R., Mychaleckyj, Josyf C., Bonnie, Jessica K., Fortune, Mary D., Walker, Neil M., Daly, Mark J., Barrett, Jeffrey C., Cooper, Jason D., Todd, John A., and Rich, Stephen S.

Abstract

Genetic studies of type 1 diabetes (T1D) have identified 50 susceptibility regions, finding major pathways contributing to risk, with some loci shared across immune disorders. To make genetic comparisons across autoimmune disorders as informative as possible, a dense genotyping array, the Immunochip, was developed, from which we identified four new T1D-associated regions (P < 5 × 10[superscript −8]). A comparative analysis with 15 immune diseases showed that T1D is more similar genetically to other autoantibody-positive diseases, significantly most similar to juvenile idiopathic arthritis and significantly least similar to ulcerative colitis, and provided support for three additional new T1D risk loci. Using a Bayesian approach, we defined credible sets for the T1D-associated SNPs. The associated SNPs localized to enhancer sequences active in thymus, T and B cells, and CD34[superscript +] stem cells. Enhancer-promoter interactions can now be analyzed in these cell types to identify which particular genes and regulatory sequences are causal.

Published
2016

46. HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease

Author

Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Ward, Lucas D., Kellis, Manolis, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Ward, Lucas D., and Kellis, Manolis

Abstract

More than 90% of common variants associated with complex traits do not affect proteins directly, but instead the circuits that control gene expression. This has increased the urgency of understanding the regulatory genome as a key component for translating genetic results into mechanistic insights and ultimately therapeutics. To address this challenge, we developed HaploReg (http://compbio.mit.edu/HaploReg) to aid the functional dissection of genome-wide association study (GWAS) results, the prediction of putative causal variants in haplotype blocks, the prediction of likely cell types of action, and the prediction of candidate target genes by systematic mining of comparative, epigenomic and regulatory annotations. Since first launching the website in 2011, we have greatly expanded HaploReg, increasing the number of chromatin state maps to 127 reference epigenomes from ENCODE 2012 and Roadmap Epigenomics, incorporating regulator binding data, expanding regulatory motif disruption annotations, and integrating expression quantitative trait locus (eQTL) variants and their tissue-specific target genes from GTEx, Geuvadis, and other recent studies. We present these updates as HaploReg v4, and illustrate a use case of HaploReg for attention deficit hyperactivity disorder (ADHD)-associated SNPs with putative brain regulatory mechanisms., National Institutes of Health (U.S.) (R01-HG004037), National Institutes of Health (U.S.) (RC1-HG005334), National Institutes of Health (U.S.) (R01-HG008155)

Published
2016

47. Evidence of Abundant Purifying Selection in Humans for Recently Acquired Regulatory Functions

Author

Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Ward, Lucas D., Kellis, Manolis, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Ward, Lucas D., and Kellis, Manolis

Abstract

Although only 5% of the human genome is conserved across mammals, a substantially larger portion is biochemically active, raising the question of whether the additional elements evolve neutrally or confer a lineage-specific fitness advantage. To address this question, we integrate human variation information from the 1000 Genomes Project and activity data from the ENCODE Project. A broad range of transcribed and regulatory nonconserved elements show decreased human diversity, suggesting lineage-specific purifying selection. Conversely, conserved elements lacking activity show increased human diversity, suggesting that some recently became nonfunctional. Regulatory elements under human constraint in nonconserved regions were found near color vision and nerve-growth genes, consistent with purifying selection for recently evolved functions. Our results suggest continued turnover in regulatory regions, with at least an additional 4% of the human genome subject to lineage-specific constraint., National Institutes of Health (U.S.) (Grant R01HG004037), National Institutes of Health (U.S.) (Grant RC1HG005334), National Science Foundation (U.S.) (CAREER Grant 0644282)

Published
2016

48. Epigenetic and genetic components of height regulation

Author

Benonisdottir, Stefania, primary, Oddsson, Asmundur, additional, Helgason, Agnar, additional, Kristjansson, Ragnar P., additional, Sveinbjornsson, Gardar, additional, Oskarsdottir, Arna, additional, Thorleifsson, Gudmar, additional, Davidsson, Olafur B., additional, Arnadottir, Gudny A., additional, Sulem, Gerald, additional, Jensson, Brynjar O., additional, Holm, Hilma, additional, Alexandersson, Kristjan F., additional, Tryggvadottir, Laufey, additional, Walters, G. Bragi, additional, Gudjonsson, Sigurjon A., additional, Ward, Lucas D., additional, Sigurdsson, Jon K., additional, Iordache, Paul D., additional, Frigge, Michael L., additional, Rafnar, Thorunn, additional, Kong, Augustine, additional, Masson, Gisli, additional, Helgason, Hannes, additional, Thorsteinsdottir, Unnur, additional, Gudbjartsson, Daniel F., additional, Sulem, Patrick, additional, and Stefansson, Kari, additional

Published
2016
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50. Rationalizing Secondary Pharmacology Screening Using Human Genetic and Pharmacological Evidence.

Author

Deaton, Aimee M, Fan, Fan, Zhang, Wei, Nguyen, Phuong A, Ward, Lucas D, and Nioi, Paul

Subjects
DRUG monitoring, HUMAN genetics, PHARMACOLOGY, DRUG side effects, PHENOTYPES
Abstract

Safety-related drug failures remain a major challenge for the pharmaceutical industry. One approach to ensuring drug safety involves assessing small molecule drug specificity by examining the ability of a drug candidate to interact with a panel of "off-target" proteins, referred to as secondary pharmacology screening. Information from human genetics and pharmacology can be used to select proteins associated with adverse effects for such screening. In an analysis of marketed drugs, we found a clear relationship between the genetic and pharmacological phenotypes of a drug's off-target proteins and the observed drug side effects. In addition to using this phenotypic information for the selection of secondary pharmacology screens, we also show that it can be used to help identify drug off-target protein interactions responsible for drug-related adverse events. We anticipate that this phenotype-driven approach to secondary pharmacology screening will help to reduce safety-related drug failures due to drug off-target protein interactions. [ABSTRACT FROM AUTHOR]

Published
2019
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