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Andreas R. Pfenning

Bio: Andreas R. Pfenning is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Biology & Enhancer. The author has an hindex of 21, co-authored 46 publications receiving 12096 citations. Previous affiliations of Andreas R. Pfenning include Massachusetts Institute of Technology & Duke University.
Topics: Biology, Enhancer, Medicine, Chromatin, Genome


Papers
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Journal ArticleDOI
Anshul Kundaje1, Wouter Meuleman1, Wouter Meuleman2, Jason Ernst3, Misha Bilenky4, Angela Yen2, Angela Yen1, Alireza Heravi-Moussavi4, Pouya Kheradpour1, Pouya Kheradpour2, Zhizhuo Zhang1, Zhizhuo Zhang2, Jianrong Wang1, Jianrong Wang2, Michael J. Ziller2, Viren Amin5, John W. Whitaker, Matthew D. Schultz6, Lucas D. Ward2, Lucas D. Ward1, Abhishek Sarkar1, Abhishek Sarkar2, Gerald Quon2, Gerald Quon1, Richard Sandstrom7, Matthew L. Eaton2, Matthew L. Eaton1, Yi-Chieh Wu1, Yi-Chieh Wu2, Andreas R. Pfenning2, Andreas R. Pfenning1, Xinchen Wang2, Xinchen Wang1, Melina Claussnitzer1, Melina Claussnitzer2, Yaping Liu2, Yaping Liu1, Cristian Coarfa5, R. Alan Harris5, Noam Shoresh2, Charles B. Epstein2, Elizabeta Gjoneska1, Elizabeta Gjoneska2, Danny Leung8, Wei Xie8, R. David Hawkins8, Ryan Lister6, Chibo Hong9, Philippe Gascard9, Andrew J. Mungall4, Richard A. Moore4, Eric Chuah4, Angela Tam4, Theresa K. Canfield7, R. Scott Hansen7, Rajinder Kaul7, Peter J. Sabo7, Mukul S. Bansal1, Mukul S. Bansal2, Mukul S. Bansal10, Annaick Carles4, Jesse R. Dixon8, Kai How Farh2, Soheil Feizi2, Soheil Feizi1, Rosa Karlic11, Ah Ram Kim1, Ah Ram Kim2, Ashwinikumar Kulkarni12, Daofeng Li13, Rebecca F. Lowdon13, Ginell Elliott13, Tim R. Mercer14, Shane Neph7, Vitor Onuchic5, Paz Polak2, Paz Polak15, Nisha Rajagopal8, Pradipta R. Ray12, Richard C Sallari2, Richard C Sallari1, Kyle Siebenthall7, Nicholas A Sinnott-Armstrong1, Nicholas A Sinnott-Armstrong2, Michael Stevens13, Robert E. Thurman7, Jie Wu16, Bo Zhang13, Xin Zhou13, Arthur E. Beaudet5, Laurie A. Boyer1, Philip L. De Jager15, Philip L. De Jager2, Peggy J. Farnham17, Susan J. Fisher9, David Haussler18, Steven J.M. Jones4, Steven J.M. Jones19, Wei Li5, Marco A. Marra4, Michael T. McManus9, Shamil R. Sunyaev2, Shamil R. Sunyaev15, James A. Thomson20, Thea D. Tlsty9, Li-Huei Tsai1, Li-Huei Tsai2, Wei Wang, Robert A. Waterland5, Michael Q. Zhang21, Lisa Helbling Chadwick22, Bradley E. Bernstein15, Bradley E. Bernstein2, Bradley E. Bernstein6, Joseph F. Costello9, Joseph R. Ecker11, Martin Hirst4, Alexander Meissner2, Aleksandar Milosavljevic5, Bing Ren8, John A. Stamatoyannopoulos7, Ting Wang13, Manolis Kellis1, Manolis Kellis2 
19 Feb 2015-Nature
TL;DR: It is shown 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.
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.

5,037 citations

01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
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.

4,409 citations

Journal ArticleDOI
Guojie Zhang1, Guojie Zhang2, Cai Li1, Qiye Li1, Bo Li1, Denis M. Larkin3, Chul Hee Lee4, Jay F. Storz5, Agostinho Antunes6, Matthew J. Greenwold7, Robert W. Meredith8, Anders Ödeen9, Jie Cui10, Qi Zhou11, Luohao Xu1, Hailin Pan1, Zongji Wang12, Lijun Jin1, Pei Zhang1, Haofu Hu1, Wei Yang1, Jiang Hu1, Jin Xiao1, Zhikai Yang1, Yang Liu1, Qiaolin Xie1, Hao Yu1, Jinmin Lian1, Ping Wen1, Fang Zhang1, Hui Li1, Yongli Zeng1, Zijun Xiong1, Shiping Liu12, Long Zhou1, Zhiyong Huang1, Na An1, Jie Wang13, Qiumei Zheng1, Yingqi Xiong1, Guangbiao Wang1, Bo Wang1, Jingjing Wang1, Yu Fan14, Rute R. da Fonseca2, Alonzo Alfaro-Núñez2, Mikkel Schubert2, Ludovic Orlando2, Tobias Mourier2, Jason T. Howard15, Ganeshkumar Ganapathy15, Andreas R. Pfenning15, Osceola Whitney15, Miriam V. Rivas15, Erina Hara15, Julia Smith15, Marta Farré3, Jitendra Narayan16, Gancho T. Slavov16, Michael N Romanov17, Rui Borges6, João Paulo Machado6, Imran Khan6, Mark S. Springer18, John Gatesy18, Federico G. Hoffmann19, Juan C. Opazo20, Olle Håstad21, Roger H. Sawyer7, Heebal Kim4, Kyu-Won Kim4, Hyeon Jeong Kim4, Seoae Cho4, Ning Li22, Yinhua Huang22, Michael William Bruford23, Xiangjiang Zhan13, Andrew Dixon, Mads F. Bertelsen24, Elizabeth P. Derryberry25, Wesley C. Warren26, Richard K. Wilson26, Shengbin Li27, David A. Ray19, Richard E. Green28, Stephen J. O'Brien29, Darren K. Griffin17, Warren E. Johnson30, David Haussler28, Oliver A. Ryder, Eske Willerslev2, Gary R. Graves31, Per Alström21, Jon Fjeldså32, David P. Mindell33, Scott V. Edwards34, Edward L. Braun35, Carsten Rahbek32, David W. Burt36, Peter Houde37, Yong Zhang1, Huanming Yang38, Jian Wang1, Erich D. Jarvis15, M. Thomas P. Gilbert2, M. Thomas P. Gilbert39, Jun Wang 
12 Dec 2014-Science
TL;DR: This work explored bird macroevolution using full genomes from 48 avian species representing all major extant clades to reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits.
Abstract: Birds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields. We explored bird macroevolution using full genomes from 48 avian species representing all major extant clades. The avian genome is principally characterized by its constrained size, which predominantly arose because of lineage-specific erosion of repetitive elements, large segmental deletions, and gene loss. Avian genomes furthermore show a remarkably high degree of evolutionary stasis at the levels of nucleotide sequence, gene synteny, and chromosomal structure. Despite this pattern of conservation, we detected many non-neutral evolutionary changes in protein-coding genes and noncoding regions. These analyses reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits.

872 citations

Journal ArticleDOI
01 Apr 2010-Nature
TL;DR: This work shows that song behaviour engages gene regulatory networks in the zebra finch brain, altering the expression of long non-coding RNAs, microRNAs, transcription factors and their targets and shows evidence for rapid molecular evolution in the songbird lineage of genes that are regulated during song experience.
Abstract: The zebra finch is an important model organism in several fields with unique relevance to human neuroscience. Like other songbirds, the zebra finch communicates through learned vocalizations, an ability otherwise documented only in humans and a few other animals and lacking in the chicken-the only bird with a sequenced genome until now. Here we present a structural, functional and comparative analysis of the genome sequence of the zebra finch (Taeniopygia guttata), which is a songbird belonging to the large avian order Passeriformes. We find that the overall structures of the genomes are similar in zebra finch and chicken, but they differ in many intrachromosomal rearrangements, lineage-specific gene family expansions, the number of long-terminal-repeat-based retrotransposons, and mechanisms of sex chromosome dosage compensation. We show that song behaviour engages gene regulatory networks in the zebra finch brain, altering the expression of long non-coding RNAs, microRNAs, transcription factors and their targets. We also show evidence for rapid molecular evolution in the songbird lineage of genes that are regulated during song experience. These results indicate an active involvement of the genome in neural processes underlying vocal communication and identify potential genetic substrates for the evolution and regulation of this behaviour.

837 citations

Journal ArticleDOI
19 Feb 2015-Nature
TL;DR: This work profiles transcriptional and chromatin state dynamics across early and late pathology in the hippocampus of an inducible mouse model of AD-like neurodegeneration and establishes the mouse as a useful model for functional studies of AD regulatory regions.
Abstract: Analysis of transcriptional and epigenomic changes in the hippocampus of a mouse model of Alzheimer’s disease shows that immune function genes and regulatory regions are upregulated, whereas genes and regulatory regions involved in synaptic plasticity, learning and memory are downregulated; genetic variants associated with Alzheimer’s disease are only enriched in orthologues of upregulated immune regions, suggesting that dysregulation of immune processes may underlie Alzheimer’s disease predisposition. Recent genome-wide association studies have shown substantial genetic variation in non-coding regions associated with Alzheimer's disease, suggesting the involvement of aberrant gene regulation. However, the functional significance of these variants remained unclear. By profiling transcriptional and chromatin state dynamics in a mouse model, Elizabeta Gjoneska and colleagues now show that the immune response genes and their regulatory regions are upregulated, whereas those involved in synaptic plasticity and learning and memory are downregulated. These changes are highly conserved between the mouse model and the human disease. Surprisingly, Alzheimer's disease-associated genetic variants are mainly enriched in higher-activity, immune-related enhancers, and are depleted in lower-activity, neural enhancers. This suggests that genetic predisposition to Alzheimer's may be primarily associated with immune functions, while neuronal plasticity may be affected primarily by non-genetic effects. Alzheimer’s disease (AD) is a severe1 age-related neurodegenerative disorder characterized by accumulation of amyloid-β plaques and neurofibrillary tangles, synaptic and neuronal loss, and cognitive decline. Several genes have been implicated in AD, but chromatin state alterations during neurodegeneration remain uncharacterized. Here we profile transcriptional and chromatin state dynamics across early and late pathology in the hippocampus of an inducible mouse model of AD-like neurodegeneration. We find a coordinated downregulation of synaptic plasticity genes and regulatory regions, and upregulation of immune response genes and regulatory regions, which are targeted by factors that belong to the ETS family of transcriptional regulators, including PU.1. Human regions orthologous to increasing-level enhancers show immune-cell-specific enhancer signatures as well as immune cell expression quantitative trait loci, while decreasing-level enhancer orthologues show fetal-brain-specific enhancer activity. Notably, AD-associated genetic variants are specifically enriched in increasing-level enhancer orthologues, implicating immune processes in AD predisposition. Indeed, increasing enhancers overlap known AD loci lacking protein-altering variants, and implicate additional loci that do not reach genome-wide significance. Our results reveal new insights into the mechanisms of neurodegeneration and establish the mouse as a useful model for functional studies of AD regulatory regions.

509 citations


Cited by
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Journal ArticleDOI
Anshul Kundaje1, Wouter Meuleman1, Wouter Meuleman2, Jason Ernst3, Misha Bilenky4, Angela Yen2, Angela Yen1, Alireza Heravi-Moussavi4, Pouya Kheradpour2, Pouya Kheradpour1, Zhizhuo Zhang1, Zhizhuo Zhang2, Jianrong Wang2, Jianrong Wang1, Michael J. Ziller2, Viren Amin5, John W. Whitaker, Matthew D. Schultz6, Lucas D. Ward1, Lucas D. Ward2, Abhishek Sarkar1, Abhishek Sarkar2, Gerald Quon1, Gerald Quon2, Richard Sandstrom7, Matthew L. Eaton2, Matthew L. Eaton1, Yi-Chieh Wu2, Yi-Chieh Wu1, Andreas R. Pfenning2, Andreas R. Pfenning1, Xinchen Wang2, Xinchen Wang1, Melina Claussnitzer2, Melina Claussnitzer1, Yaping Liu1, Yaping Liu2, Cristian Coarfa5, R. Alan Harris5, Noam Shoresh2, Charles B. Epstein2, Elizabeta Gjoneska2, Elizabeta Gjoneska1, Danny Leung8, Wei Xie8, R. David Hawkins8, Ryan Lister6, Chibo Hong9, Philippe Gascard9, Andrew J. Mungall4, Richard A. Moore4, Eric Chuah4, Angela Tam4, Theresa K. Canfield7, R. Scott Hansen7, Rajinder Kaul7, Peter J. Sabo7, Mukul S. Bansal2, Mukul S. Bansal1, Mukul S. Bansal10, Annaick Carles4, Jesse R. Dixon8, Kai How Farh2, Soheil Feizi1, Soheil Feizi2, Rosa Karlic11, Ah Ram Kim2, Ah Ram Kim1, Ashwinikumar Kulkarni12, Daofeng Li13, Rebecca F. Lowdon13, Ginell Elliott13, Tim R. Mercer14, Shane Neph7, Vitor Onuchic5, Paz Polak2, Paz Polak15, Nisha Rajagopal8, Pradipta R. Ray12, Richard C Sallari2, Richard C Sallari1, Kyle Siebenthall7, Nicholas A Sinnott-Armstrong2, Nicholas A Sinnott-Armstrong1, Michael Stevens13, Robert E. Thurman7, Jie Wu16, Bo Zhang13, Xin Zhou13, Arthur E. Beaudet5, Laurie A. Boyer1, Philip L. De Jager15, Philip L. De Jager2, Peggy J. Farnham17, Susan J. Fisher9, David Haussler18, Steven J.M. Jones19, Steven J.M. Jones4, Wei Li5, Marco A. Marra4, Michael T. McManus9, Shamil R. Sunyaev15, Shamil R. Sunyaev2, James A. Thomson20, Thea D. Tlsty9, Li-Huei Tsai2, Li-Huei Tsai1, Wei Wang, Robert A. Waterland5, Michael Q. Zhang21, Lisa Helbling Chadwick22, Bradley E. Bernstein6, Bradley E. Bernstein15, Bradley E. Bernstein2, Joseph F. Costello9, Joseph R. Ecker11, Martin Hirst4, Alexander Meissner2, Aleksandar Milosavljevic5, Bing Ren8, John A. Stamatoyannopoulos7, Ting Wang13, Manolis Kellis1, Manolis Kellis2 
19 Feb 2015-Nature
TL;DR: It is shown 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.
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.

5,037 citations

Journal ArticleDOI
Kristin G. Ardlie, David S. DeLuca, Ayellet V. Segrè, Timothy J. Sullivan, Taylor Young, Ellen Gelfand, Casandra A. Trowbridge, Julian Maller, Taru Tukiainen, Monkol Lek, Lucas D. Ward, Pouya Kheradpour, Benjamin Iriarte, Yan Meng, Cameron D. Palmer, Tõnu Esko, Wendy Winckler, Joel N. Hirschhorn, Manolis Kellis, Daniel G. MacArthur, Gad Getz, Andrey A. Shabalin, Gen Li, Yi-Hui Zhou, Andrew B. Nobel, Ivan Rusyn, Fred A. Wright, Tuuli Lappalainen, Pedro G. Ferreira, Halit Ongen, Manuel A. Rivas, Alexis Battle, Sara Mostafavi, Jean Monlong, Michael Sammeth, Marta Melé, Ferran Reverter, Jakob M. Goldmann, Daphne Koller, Roderic Guigó, Mark I. McCarthy, Emmanouil T. Dermitzakis, Eric R. Gamazon, Hae Kyung Im, Anuar Konkashbaev, Dan L. Nicolae, Nancy J. Cox, Timothée Flutre, Xiaoquan Wen, Matthew Stephens, Jonathan K. Pritchard, Zhidong Tu, Bin Zhang, Tao Huang, Quan Long, Luan Lin, Jialiang Yang, Jun Zhu, Jun Liu, Amanda Brown, Bernadette Mestichelli, Denee Tidwell, Edmund Lo, Mike Salvatore, Saboor Shad, Jeffrey A. Thomas, John T. Lonsdale, Michael T. Moser, Bryan Gillard, Ellen Karasik, Kimberly Ramsey, Christopher Choi, Barbara A. Foster, John Syron, Johnell Fleming, Harold Magazine, Rick Hasz, Gary Walters, Jason Bridge, Mark Miklos, Susan L. Sullivan, Laura Barker, Heather M. Traino, Maghboeba Mosavel, Laura A. Siminoff, Dana R. Valley, Daniel C. Rohrer, Scott D. Jewell, Philip A. Branton, Leslie H. Sobin, Mary Barcus, Liqun Qi, Jeffrey McLean, Pushpa Hariharan, Ki Sung Um, Shenpei Wu, David Tabor, Charles Shive, Anna M. Smith, Stephen A. Buia, Anita H. Undale, Karna Robinson, Nancy Roche, Kimberly M. Valentino, Angela Britton, Robin Burges, Debra Bradbury, Kenneth W. Hambright, John Seleski, Greg E. Korzeniewski, Kenyon Erickson, Yvonne Marcus, Jorge Tejada, Mehran Taherian, Chunrong Lu, Margaret J. Basile, Deborah C. Mash, Simona Volpi, Jeffery P. Struewing, Gary F. Temple, Joy T. Boyer, Deborah Colantuoni, Roger Little, Susan E. Koester, Latarsha J. Carithers, Helen M. Moore, Ping Guan, Carolyn C. Compton, Sherilyn Sawyer, Joanne P. Demchok, Jimmie B. Vaught, Chana A. Rabiner, Nicole C. Lockhart 
08 May 2015-Science
TL;DR: The landscape of gene expression across tissues is described, thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants are cataloged, complex network relationships are described, and signals from genome-wide association studies explained by eQTLs are identified.
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 analysi...

4,418 citations

01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
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.

4,409 citations

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

4,359 citations

Journal ArticleDOI
TL;DR: Some notable features of IQ-TREE version 2 are described and the key advantages over other software are highlighted.
Abstract: IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.

4,337 citations