Andreas Pfenning
Associate Professor, Ray and Stephanie Lane Computational Biology Department Carnegie Mellon University
- Pittsburgh PA
Andreas Pfenning has published a number of high-impact papers on genomic tools to study sequence differences.
Biography
Areas of Expertise
Media Appearances
Similar genetic elements underlie vocal learning in mammals
Phys.org online
2024-02-29
"New artificial intelligence methods were needed to help find evolutionary signals in regulatory elements across hundreds of genomes," said Pfenning, a corresponding author on the new study and an associate professor in CMU's Ray and Stephanie Lane Computational Biology Department affiliated with the Neuroscience Institute and Department of Biological Sciences. "We're entering an exciting era where AI is improving our ability to trace human evolutionary history. Studying the gene regulatory elements requires building a map of which ones are active in the relevant brain region of species with vocal learning behavior."
What bats can teach us about the evolution of human speech
UC Berkeley News online
2024-02-29
“We found that the types of cells that form long range connections in the human and bat brain are the same ones that we discovered as most relevant to vocal learning based on the genetic analysis,” Pfenning said. “The anatomy and genetics are both pointing to the same mechanism underlying the evolution of vocal learning across mammals and speech production in humans.”
Expanding set of viral tools targets almost any brain cell type
The Transmitter online
2024-11-19
What’s more, transgenic mice aren’t always the most appropriate model organism. Rodents don’t naturally develop the plaques and tangles associated with Alzheimer’s disease, for example, but scientists use them anyway because the genetic tools to investigate the condition in them are established, says Andreas Pfenning, associate professor of computational biology at Carnegie Mellon University, who was not involved in the work. “What would be really cool is to move beyond mice and into these more appropriate models for certain things,” Pfenning says.
New Technique Isolates Brain Cells Associated With Parkinson's Disease
CMU News online
2020-11-30
"Even a small portion of the brain can have dozens of different cell types," said Andreas Pfenning, an assistant professor in CMU's Computational Biology Department. "Each of these cell types has different roles in the behavior of an animal and also in disease." Separating cells of a certain type from their neighbors is thus a critical first step for researchers who want to study them.
Science and Diversity In Film: Behind The Scenes Of ANYA
Forbes online
2019-05-31
The film ANYA centers on a couple in New York City who are struggling with infertility. When they turn to their scientist friend for advice, he discovers a possible genetic reason, which affects an entire community of immigrants from the fictional island of Narval.
The lab scenes in ANYA were filmed in Andreas Pfenning’s lab at Carnegie Mellon University, where McCole was further supported by PhD student Alyssa Lawler. They kept an eye to make sure the experiments looked realistic.
Media
Social
Industry Expertise
Education
Duke University
Ph.D.
Computational Biology
Carnegie Mellon University
B.S.
Computer Science
Languages
- English
- German
Articles
The Vertebrate Genomes Project Phase I: A global reference genome resource
bioRxivGiulio Formenti, Dominic E Absolon, Linelle Ann L Abueg, Francine Ackerman, Farooq Omar Al-Ajli, Alexandre Aleixo, Agostinho Antunes, Dahiana Arcila, Jean-Nicolas Audet, Jennifer R Balacco, Alan James Stephen Beavan, Katherine Belov, Ricardo Betancur-R, Shelby L Bidwell, Matthew T Biegler, Iliana Bista, Mark Blaxter, Kevin Boyer, Ingo Braasch, Ian R Bradbury, Nadolina Brajuka, Anne M Bronikowski, Tom Brown, George Butler, Shuo Cao, Eduardo Charvel, Ying Chen, Claudio Ciofi, Hiram M Clawson, Joanna Clare Collins, Solenne Correard, Shannon Corrigan, Melanie Couture, Andrew J Crawford, Nathalia DR D'Alessandre, Helena B da Conceicao, Rute R da Fonseca, Minoli Daigavane, Jeronymo Dalapicolla, Mark de Bruyn, Emma de Jong, Diego N De Panis, H William Detrich III, Carol DeWeese Scott, Mark Diekhans, Erick Duarte, Richard Durbin, Merly Escalona, Michel Eschenbrenner, Olivier Fedrigo, Jonathan Fenn, Patrick Flannery, Niamh Forde, Simone M Gable, Pedro AF Galante, Rajee Ganesan, Amanda Gardiner, Erik Garrison, Neil J Gemmell, M Thomas P Gilbert, Francois Giudicelli, Tassia Mangetti Goncalves, Gabriela Der Agopian Guardia, Andrea Guarracino, Anshu Gupta, Bettina Haase, Delson Hays, Glenn Hickey, Michael Hiller, Paul M Hime, Carolyn J Hogg, Kathleen M Horan, Kerstin Howe, Danny Jackson, Nivesh Jain, Lin Kang, Sergei Kliver, Byung June Ko, Klaus-Peter Koepfli, Aleksey Komissarov, Lisa M Komoroske, Bonhwang Koo, Sergey Koren, Jonas Korlach, Iva Kovacic, Ksenia Krasheninnikova, Lukas FK Kuderna, Ryan A Langlois, Delphine Lariviere, Denis M Larkin, Chul Lee, Young Ho Lee, Harris A Lewin, Daven Lim, Runyang Nicolas Lou, Sarah ST Mak, Kateryna D Makova, Laia Marin-Gual, Tomas Marques-Bonet, Fergal James Martin, Thomas C Mathers, Camila J Mazzoni, Kirsty McCaffrey, Shane A McCarthy, Jack A Medico, Rafael Luiz Vieira Mercuri, Axel Meyer, Pawel Michalak, Siavash Mirarab, Phillip A Morin, Jacquelyn Mountcastle, Robert W Murphy, Terence D Murphy, Eugene W Myers, Gavin JP Naylor, Thomas Near, Anton Nekrutenko, Zemin Ning, Ben J Novak, M
2026-06-26
The Vertebrate Genomes Project (VGP) aims to produce complete and near-error-free reference genomes for all ∼70,000 extant vertebrate species. Organized in four phases, it progressively targets all vertebrate orders, families, genera, and eventually all species. Here we present the completion of VGP Phase I, delivering reference genomes for ∼97% of vertebrate orders, along with additional lineages within those orders, totaling 815 species and 1.6 trillion base pairs of main haplotype sequence. These genomes were assembled and annotated over an 8-year period (2018-2026) of rapid advances in genome sequencing, assembly, and annotation methods, alongside the growth of associated consortium initiatives and international collaborations. They represent some of the highest-quality vertebrate genomes currently available, and most have become the primary reference for their respective species in public databases. Comparative analyses across a subset of 579 species when we reached a threshold of 85% of orders allowed us to reconstruct the genome of the last common ancestor of all vertebrates 500 million years ago, identify diverse modes of sex chromosome evolution, reveal clade-specific three-dimensional genome architecture, discover methylated epigenetic landscapes across vertebrates, and provide a framework for studying gene and pseudogene evolution, immune loci, cancer-associated genes, and other trait-associated loci.
An in vivo systemic massively parallel platform for deciphering animal tissue-specific regulatory function
Frontiers of GeneticsAshley R Brown, Grant A Fox, Irene M Kaplow, Alyssa J Lawler, BaDoi N Phan, Lahari Gadey, Morgan E Wirthlin, Easwaran Ramamurthy, Gemma E May, Ziheng Chen, Qiao Su, C Joel McManus, Robert Van De Weerd, Andreas R Pfenning
2025-04-09
Introduction: Transcriptional regulation is an important process wherein non-protein coding enhancer sequences play a key role in determining cell type identity and phenotypic diversity. In neural tissue, these gene regulatory processes are crucial for coordinating a plethora of interconnected and regionally specialized cell types, ensuring their synchronized activity in generating behavior. Recognizing the intricate interplay of gene regulatory processes in the brain is imperative, as mounting evidence links neurodevelopment and neurological disorders to non-coding genome regions. While genome-wide association studies are swiftly identifying non-coding human disease-associated loci, decoding regulatory mechanisms is challenging due to causal variant ambiguity and their specific tissue impacts.
Single nuclei transcriptomics in human and non-human primate striatum in opioid use disorder
Nature CommunicationsBaDoi N Phan, Madelyn H Ray, Xiangning Xue, Chen Fu, Robert J Fenster, Stephen J Kohut, Jack Bergman, Suzanne N Haber, Kenneth M McCullough, Madeline K Fish, Jill R Glausier, Qiao Su, Allison E Tipton, David A Lewis, Zachary Freyberg, George C Tseng, Shelley J Russek, Yuriy Alekseyev, Kerry J Ressler, Marianne L Seney, Andreas R Pfenning, Ryan W Logan
2024-01-31
In brain, the striatum is a heterogenous region involved in reward and goal-directed behaviors. Striatal dysfunction is linked to psychiatric disorders, including opioid use disorder (OUD). Striatal subregions are divided based on neuroanatomy, each with unique roles in OUD. In OUD, the dorsal striatum is involved in altered reward processing, formation of habits, and development of negative affect during withdrawal. Using single nuclei RNA-sequencing, we identified both canonical (e.g., dopamine receptor subtype) and less abundant cell populations (e.g., interneurons) in human dorsal striatum. Pathways related to neurodegeneration, interferon response, and DNA damage were significantly enriched in striatal neurons of individuals with OUD.
Erratum: Loss of epigenetic information as a cause of mammalian aging (Cell (2023) 186 (2)(305–326. e27),(S0092867422015707),(10.1016/j. cell. 2022.12. 027))
Cell2024
(Cell 186, 305–326. e1–e14; January 19, 2023) Our paper used a system called “ICE”(inducible changes to the epigenome) to study whether a loss of epigenetic information leads to aging and whether the expression of a subset of Yamanka factors can reverse these age-associated changes, as tests of the Information Theory of Aging. We provide additional information about our experimental design and reference previous, relevant papers from our group and others that had not been cited in the original submission. We apologize for any confusion that may have arisen due to this information not being available in the original published paper. In our Correction, we add details about the transgenic construct design, tamoxifen administration, and temporal and spatial control of I-PpoI in the Results, Discussion, and STAR Methods sections.
Regression convolutional neural network models implicate peripheral immune regulatory variants in the predisposition to Alzheimer’s disease
PLOS Computational Biology2024
Alzheimer’s disease (AD) involves aggregation of amyloid β and tau, neuron loss, cognitive decline, and neuroinflammatory responses. Both resident microglia and peripheral immune cells have been associated with the immune component of AD. However, the relative contribution of resident and peripheral immune cell types to AD predisposition has not been thoroughly explored due to their similarity in gene expression and function. To study the effects of AD-associated variants on cis-regulatory elements, we train convolutional neural network (CNN) regression models that link genome sequence to cell type-specific levels of open chromatin, a proxy for regulatory element activity. We then use in silico mutagenesis of regulatory sequences to predict the relative impact of candidate variants across these cell types.
AI-designed DNA sequences regulate cell-type-specific gene expression
Nature2024
Different parts of a cell’s genome can be active or inactive depending on the cell’s function in the body, and whether it is in a disease state. The instructions for activating or repressing a gene are encoded in the genome, and each type of cell has its own genomic ‘language’ that is based on highly complex patterns of nucleotides that describe whether a gene will be expressed. Writing in Nature, Gosai et al.1 apply artificial intelligence (AI) methods to learn the ‘regulatory grammar’ of that language — that is, the patterns of nucleotides in the genome that relate to gene-regulatory activity — for different cell types. The authors then apply those models, along with experimental genomics techniques, to create synthetic DNA sequences that can drive gene expression in specific cell types, which has implications for targeted cell and gene therapy.
RERconverge expansion: using relative evolutionary rates to study complex categorical trait evolution
Molecular Biology and Evolution2024
Comparative genomics approaches seek to associate molecular evolution with the evolution of phenotypes across a phylogeny. Many of these methods lack the ability to analyze non-ordinal categorical traits with more than two categories. To address this limitation, we introduce an expansion to RERconverge that associates shifts in evolutionary rates with the convergent evolution of categorical traits. The categorical RERconverge expansion includes methods for performing categorical ancestral state reconstruction, statistical tests for associating relative evolutionary rates with categorical variables, and a new method for performing phylogeny-aware permutations, “permulations”, on categorical traits.
Spatial, transcriptomic, and epigenomic analyses link dorsal horn neurons to chronic pain genetic predisposition
Cell Reports2024
Key mechanisms underlying chronic pain occur within the dorsal horn. Genome-wide association studies (GWASs) have identified genetic variants predisposed to chronic pain. However, most of these variants lie within regulatory non-coding regions that have not been linked to spinal cord biology. Here, we take a multi-species approach to determine whether chronic pain variants impact the regulatory genomics of dorsal horn neurons. First, we generate a large rhesus macaque single-nucleus RNA sequencing (snRNA-seq) atlas and integrate it with available human and mouse datasets to produce a single unified, species-conserved atlas of neuron subtypes.
