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Center for Genomics of Neurodegenerative Disease Phatnani Lab

The Center for Genomics of Neurodegenerative Disease (CGND) is dedicated to the study of neurodegenerative diseases such as ALS, dementia, Alzheimer’s disease, frontotemporal dementia, Parkinson’s disease, and Huntington’s disease. CGND’s vision is to establish a center for applying state of the art genetics, genomics and bioinformatics to the study of neurodegenerative disease mechanisms.

CGND’s goals are to use whole genome sequencing to identify mutations that cause neurodegenerative disease. To gain insights into the relationship between mutations, gene expression and disease mechanisms, whole genome sequencing data will ultimately be integrated with other genomic-scale data such as RNA-SEQ, RNA-protein interactions, and DNA methylation patterns.

CGND is helping to create a uniform system of collecting clinical annotation to better enable the integration of genomic data with clinical profiles. This information will be freely available to the research community in a data warehouse for whole genome sequencing and RNA-SEQ analyses.



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    Hemali Phatnani, PhD


    Hemali Phatnani, PhD, serves as the Director, Center for Genomics of Neurodegenerative Disease (CGND) at NYGC. She has a joint appointment as Adjunct Assistant Professor of Neurogenetics in the Department of Neurology and the Institute for Genomic Medicine at Columbia University. Her research focuses on gene regulatory mechanisms that underlie the complex interactions between motor neurons and non-neuronal cells in the spinal cord of ALS mouse models, including astrocytes, microglia and oligodendrocytes. The goal of Dr. Phatnani’s research is to apply state-of-the-art genomics and bioinformatics to understand the role of cell-cell interactions in ALS pathophysiology.

    Dr. Phatnani carried out her postdoctoral studies in Dr. Tom Maniatis’ Lab at Harvard and Columbia Universities, where she studied ALS disease mechanisms using stem cell-derived motor neurons and genomic profiling methods. She established a novel cell culture system to study cell intrinsic and cell extrinsic effects of astrocytes on motor neuron gene expression, and discovered a complex interplay between the two cell types during ALS disease progression.

    Dr. Phatnani received her PhD in biochemistry and molecular biology at Duke University, where she characterized the interactions between RNA polymerase and proteins involved in the mechanistic coupling of RNA transcription and processing. She earned a B.Sc. in life sciences from Bombay (Mumbai) University.




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    Genetics and Genomics of ALS

    8dd56f_f15f686f6e0b48fea725d0773b9b077cThe vision of the Center for Genomics of Neurodegenerative Disease (CGND) at NYGC is to establish a framework to apply state-of-the-art genomics and bioinformatics to the study of neurodegenerative disease mechanisms, by building partnerships with clinicians, basic scientists, geneticists, and computational biologists.

    The CGND’s research program in Amyotrophic Lateral Sclerosis (ALS) was established with the help of generous support from The Tow Foundation and The ALS Association’s (ALSA) Greater New York Chapter. The CGND’s partners include not only NYGC’s founding members such as Columbia and Rockefeller, but also ALS centers throughout the northeast, such as the University of Pennsylvania, Massachusetts General Hospital and Hershey Medical Center at Penn State University, among others. Through the support of ALSA, our efforts also synergize with other ALSA-funded consortia, such as Answer ALS, and the GTAC (“Genomics Translation for ALS Clinical care”) consortium. In addition, we work in close partnership with Target ALS’s Post Mortem Core, iPS core, and Biospecimen Collection.

    Through a multidisciplinary collaborative effort that spans multiple ALS centers and bridges ALS clinicians and scientists, we are using whole genome sequencing to discover and study mutations and mechanisms underlying ALS. Broadly stated, the goals of this consortium are the following:

    Integrate whole genome sequencing with RNA sequencing to interrogate relationships between mutations, gene expression and disease mechanisms

    RNA sequencing analyses combined with whole genome sequencing will help us to identify how changes in DNA are expressed in the brain and spinal cord, and how this affects the presentation and course of disease.

    Integrate genomic and clinical data to identify genetic modifiers of disease onset/progression/presentation

    Our partners’ clinical phenotyping efforts will enable us to sequence well-stratified patient cohorts, so that we can eventually identify mutations that are associated with different forms of the disease, or gene variants that can modify the presentation of the disease and could be further studied to identify pathways for the targeted development of therapies.

    Create and maintain a data warehouse for genomic data that can be broadly accessed by the academic community

    Our sequencing data will be made freely available to the research community. Resource and data sharing is an integral aspect of our efforts, because we want the data that we generate to be as useful as possible to as many researchers as possible. Broad sharing will only accelerate the pace of discovery and therapeutics, which are crucially needed in ALS.

    Such broad sharing and collaborative efforts are ultimately geared towards making the best use of sequencing data. For example, comparing clinical profiles to genomic profiles can enable us to determine whether specific mutations are associated with specific clinical outcomes – this may ultimately make truly “personalized” medicine possible.

    8dd56f_137bc4273c4d4143b9b803ef64662163Design and create ALS models to test effects of mutations in stem cell derived neurons and in mouse models using state-of-the-art genomic manipulation methods.

    To study the function of any sequence variants that we identify and to understand how they affect disease mechanisms, we collaborate with our research partners to make new models of disease such as iPS cells and mouse models. We use these models to study, for example, how mutations affect the different cell types that are known to play a role in ALS, such as astrocytes, microglia, and oligodendrocytes, all of which are known to affect motor neurons in ALS. Using these models, we examine regulatory mechanisms affecting the transcriptome, as well as mechanisms underlying intercellular interactions in disease. To further these analyses, we are developing tools to integrate the experimental and computational analysis of large-scale data that includes transcriptomes of specific cell types in the Central Nervous System, profiles of RNA-binding proteins implicated in disease, and high-resolution imaging. The combination of new deep sequencing methods, sample acquisition, data analysis pipelines, and molecular and phenotypic characterizations using new mouse models will provide mechanistic insights that were previously not possible.

    Any models that we develop through our collaborative efforts will be made freely available to the research community – this is in fact a condition of any partnerships that we undertake. In addition, the conceptual framework and infrastructure should be widely applicable to other neurodegenerative diseases.

    The CGND’s ALS Consortium at-a-glance:


    1. Academic Medical Center, Amsterdam
    2. Atlantic Health System
    3. Barrow Neurological Institute
    4. Brigham and Women’s Hospital
    5. Cedars-Sinai Medical Center
    6. Columbia University
    7. Cold Spring Harbor Laboratory
    8. Gladstone Institute
    9. Hadassah Hebrew University
    10. Henry Ford Health System
    11. Hospital for Special Surgery
    12. Icahn School of Medicine at Mount Sinai
    13. The Jackson Lab
    14. Johns Hopkins University
    15. Massachusetts General Hospital
    16. Massachusetts Institute of Technology
    17. National Institutes of Health’s National Institute of Neurological Disorders and Stroke
    18. New York Genome Center
    19. Stony Brook University
    20. Temple University
    21. The Pennsylvania State University
    22. University College London / Queen Mary University of London
    23. University of Athens
    24. University of California at Irvine
    25. University of California at San Francisco
    26. University of Edinburgh
    27. University of Maryland, Baltimore
    28. University of Pennsylvania
    29. University of Thessaly
    30. Washington University in St. Louis
    31. Weizmann Institute of Science


    Pre-competitive Data Sharing with all Consortium Members, samples consented for broad sharing for all medical research

    Partnerships: Answer ALS Consortium, GTAC Consortium, Target ALS – Post Mortem Core, Project MinE, iPS Core, Biospecimen Collection

    Target Groups: FALS, SALS, C9 carriers

    Data being collected now: DNA, autopsy tissue RNA, some iPS, clinical data (longitudinal clinical data targeted for ~1300 of a total of 1800 patients)


    1. ALS gene discovery efforts: unexplained familial ALS, increasing power through increased numbers of sporadic patients for co-analysis with existing datasets
    2. Genotype-phenotype correlations
    3. Integrating WGS with tissue-specific transcriptomics for understanding the impact of regulatory variation and cell type-specific contributions
    4. C9 promoter methylation (QTLs of this phenotype)


    Data Access:

    Consortium data is being deposited in MetroNome, NYGC’s clinical genomics database.
    To access data that is publicly available now, click here.

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    Astrocytes in ALS

    8dd56f_6e0eb389fda444d4b6ebfbcbbd0bb306How neurons and glia communicate and depend on each other is still a largely open question in neuroscience. Perturbations in this interdependence underlie many neurodegenerative diseases including Amyotrophic Lateral Sclerosis (ALS). Motor neuron death in ALS is a culmination of pathological processes affecting both glia, such as astrocytes, and neurons. Although astrocytes are known to contribute to motor neuron death in ALS, the mechanisms through which they do so are not well understood. Our lab has pioneered a motor neuron-astrocyte co-culture platform (‘sandwich culture’) that allows us to dissect how motor neurons and astrocytes interact over time and how these interactions are affected in disease. It is known that expressing an ALS causing human transgene (SOD1 G93A) in either cell type causes a reciprocal up-regulation of Transforming Growth Factor Beta (TGF-ß) signaling genes between the two cell types. TGF-ß signaling is implicated in many neurodegenerative diseases including sporadic and familial ALS. We are currently investigating the pathological significance of dysregulation of this pathway is SOD1 G93A and FUS ALS models.

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    Detecting Repeat Expansions

    8dd56f_85454bdd654f452ebe746b8735857cb1Several recent studies have identified a specific type of genetic mutation called a repeat expansion (RE) in chromosome 9 open reading frame 72 (C9orf72) to be the most common cause of familial amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). This type of mutation is common in neurodegenerative diseases; the RE in ALS-FTLD consists of six base pairs (GGGGCC) repeated 100’s to 1000’s of times. Among C9orf72 RE patients, there is considerable heterogeneity in age of onset, disease severity, phenotypic presentation, and the total length of the RE. Several potential mechanisms of disease related to the C9orf72 RE have been proposed: aberrant RNA splicing and translocation, aggregation of dipeptides resulting from non-ATG mediated translation, nucleocytoplasmic export dysfunction, and neuronal branching defects. The length of RE necessary to cause these functional abnormalities and its relationship to disease presentation, however, remain unclear. At NYGC, James is using cutting edge molecular biology and next generation sequencing to investigate the C9orf72 RE and its contribution to ALS-FTLD.

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    Cell Type Specific Translatomics


    We are also taking ‘functional genomics’ approach to ALS disease progression  in vivo by developing  biochemical protocols and bioinformatics pipelines to interrogate transcriptome, translatome and epigenome dynamics in a cell type-specific manner in mouse models of ALS. The computational integration of these datasets will decipher the inter-cellular communication and intra-cellular responses during disease advancement at high temporal resolution. These molecular insights will form a fundamental basis for the discovery of new disease biomarkers, and to identify targets for next-generation therapeutics including antisense oligonucleotides to modulate RNA levels, splicing or post-transcriptional regulation.


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    Cell Type Specific Transcriptomics


    Dynamic regulation of gene expression is a key feature of virtually all aspects of cellular function. Changes in gene expression patterns can reveal the presence of disease, and understanding such changes can yield insight into the basic biology of disease. Recent rapid advances in sequencing technologies have dramatically enhanced our ability to collect gene expression data. However, using the most widely available high throughput sequencing methods, measurement of gene expression in complex tissues is hampered by the need to homogenize or dissociate the tissues. In both cases, positional information is lost. The few high throughput methods for measuring gene expression while preserving spatial information that exist are prohibitively complex, labor intensive, expensive, and require specialized equipment. Thus, a need exists for technologies with which to capture high content spatial gene expression data, that are easier, cheaper, and more widely usable than existing technologies. Studies of neurodegenerative diseases in particular can benefit immensely from a better understanding of how gene expression differs across tissues, cell types, and sub-cellular domains. Motor neurons, the key affected cell type in ALS, can be on the order of a meter long. Such large cells must precisely control not only the amount, but also the localization of RNAs and proteins along that length to function properly. Moreover, subpopulations of motor neurons residing near each other can exhibit different levels of vulnerability to the disease. Substantial evidence now indicates that ALS disease progression involves signaling between neurons and glia, but the nature of this signaling and how it is involved in the spread of the disease state along the spinal cord remain poorly understood. Thus, a better view of how cells of the spinal cord alter the expression of their genes across both spatial and temporal dimensions during disease progression will inform our understanding of ALS. We are developing and utilizing microscopy and molecular techniques in efforts to understand the changes in gene expression patterns that occur in ALS.

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      Rawan Abdelaal

      rawan_thumbRawan Abdelaal worked on the interactions between motor neurons and glial cells in ALS pathology using mouse and iPS cell-based models combined with NGS technology. She mostly focused on iPSC culture systems including differentiation of iPSCs into ALS relevant cell types (e.g. motor neurons, astrocytes, etc.) as well as organization of multiple lines of ALS patient-derived iPSCs and differentiated cells. Rawan graduated with a BS in Biotechnology from the City College of New York in Fall 2015.

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      Jan Bergmann

      8dd56f_24a295eceef04f6bbc7f3edb059ac265Jan studied biology at the University of Heidelberg in Germany and obtained a M.Sc. by research in life sciences from the University of Edinburgh in Scotland. He joined the laboratory of Prof. William Earnshaw, also at Edinburgh University, where he received his Ph.D. in Cell- and Molecular Biology for his seminal work demonstrating the relationship between local chromatin state, non-coding transcription and the epigenetic inheritance of the centromere locus in mammalian cells. In 2010, Dr. Bergmann moved to New York as postdoctoral fellow in Prof. David Spector’s group at Cold Spring Harbor Laboratory. Here, he spear-headed next-generation sequencing and computational approaches to identify a series of long non-coding RNAs as developmental biomarkers and potential targets for antisense oligonucleotide therapeutics.

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      Isabel Hubbard

      Isabel Hubbard was an Associate Scientist II at the Center for Genomics of Neurodegenerative Disease (CGND). Prior to joining the NYGC, she was a development scientist at a clinical reference laboratory, where she developed targeted oncology assays for the Illumina MiSeqDx and Ion PGM NGS platforms for use in patient molecular diagnostics. Isabel received a BS in Biological Sciences-Neuroscience Track from Carnegie Mellon University in 2013 and an MSc in Biomedical Sciences from University College London in 2014, where her thesis work involved investigating the underlying molecular and genetic pathways of the neuronal ceroid lipofuscinoses (NCLs), a group of early onset neurodegenerative disorders, under the supervision of Dr. Sara Mole at the MRC Laboratory for Molecular Cell Biology.

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      Kenneth Li

      ken_liKenneth was an undergraduate student at Columbia University on the pre-medicine track and graduated in 2017. He volunteered his time to focus on using computational methods and working with ALS-relevant cell populations (e.g. motor neurons, astrocytes, etc.) to understand the cell-type specific transcriptomics of disease progression over time in the SOD1-G93A mouse model of ALS.

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      Ian Laster

      8dd56f_e4acea111cc746d69c69492c24e1a187Ian Laster graduated from Columbia University with a BS in May 2014 and chose to gain research experience in our lab before applying to medical school. He joined the lab in December 2014 and worked closely with Dr. Jan Bergmann on cell-type specific translatomics in the spinal cord.

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      Ariel Shepley-McTaggart

      8dd56f_ece4c4a131124cf298ed803bed04b57eAriel Shepley-McTaggart graduated from Columbia University with a BA in May 2014. Ariel split her time between her life as a professional ballerina and personal trainer and volunteering in our lab several days a week. She worked closely with Catherine Braine, investigating the role of TGF-B in a mouse model of ALS. Ariel will attend University of Pennsylvania School of Veterinary Medicine in Fall 2016.

  • Recent Publications

    • Exome sequencing in amyotrophic lateral sclerosis implicates a novel gene, DNAJC7, encoding a heat-shock protein.

      Farhan SMK, Howrigan DP, Abbott LE, Klim JR, Topp SD, Byrnes AE, Churchhouse C, Phatnani H, Smith BN, Rampersaud E, Wu G, Wuu J, Shatunov A, Iacoangeli A, Al Khleifat A, Mordes DA, Ghosh S; ALSGENS Consortium; FALS Consortium; Project MinE Consortium; CReATe Consortium, Eggan K, Rademakers R, McCauley JL, Schüle R, Züchner S, Benatar M, Taylor JP, Nalls M, Gotkine M, Shaw PJ, Morrison KE, Al-Chalabi A, Traynor B, Shaw CE, Goldstein DB, Harms MB, Daly MJ, Neale BM.

      Nature Neuroscience. 2019 Nov. 25.

    • Postmortem Cortex Samples Identify Distinct Molecular Subtypes of ALS: Retrotransposon Activation, Oxidative Stress, and Activated Glia

      Oliver H. Tam, Nikolay V. Rozhkov, Regina Shaw, Duyang Kim, Isabel Hubbard, Samantha Fennessey, Nadia Propp, The NYGC ALS Consortium, Delphine Fagegaltier, Brent T. Harris, Lyle W. Ostrow, Hemali Phatnani, John Ravits, Josh Dubnau, and Molly Gale Hammell

      Cell Reports. 2019 Oct. 29.

    • Synergistic effects of common schizophrenia risk variants.

      Schrode N, Ho SM, Yamamuro K, Dobbyn A, Huckins L, Matos MR, Cheng E, Deans PJM, Flaherty E, Barretto N, Topol A, Alganem K, Abadali S, Gregory J, Hoelzli E, Phatnani H, Singh V, Girish D, Aronow B, Mccullumsmith R, Hoffman GE, Stahl EA, Morishita H, Sklar P, Brennand KJ.

      Nature Genetics. 2019 Sep. 23.

    • Examining the relationship between astrocyte dysfunction and neurodegeneration in ALS using hiPSCs.

      Halpern M, Brennand KJ, Gregory J.

      Neurobiol Dis. 2019 Aug 2.

    • Spatiotemporal Dynamics of Molecular Pathology in Amyotrophic Lateral Sclerosis.

      Maniatis S, Tarmo Äijö, Sanja Vickovic, Catherine Braine, Kristy Kang, Annelie Mollbrink, Delphine Fagegaltier, Žaneta Andrusivová, Sami Saarenpää,Gonzalo Saiz-Castro, Miguel Cuevas, Aaron Watters, Joakim Lundeberg, Richard Bonneau, and Phatnani H.

      Science. 2019 Apr 4.

    • A new approach for rare variation collapsing on functional protein domains implicates specific genic regions in ALS.

      Gelfman S, Dugger SA, Araujo Martins Moreno C, Ren Z, Wolock CJ, Shneider N, Phatnani H, Cirulli ET, Lasseigne BN, Harris T, Maniatis T, Rouleau G, Brown RH, Gitler AD, Myers RM, Petrovski S, Allen A, Goldstein DB, Harms MB.

      Genome Res. 2019 Apr 2.

    • The human brainome: network analysis identifies HSPA2 as a novel Alzheimer’s disease target.

      Petyuk VA, Chang R, Ramirez-Restrepo M, Beckmann ND, Henrion MYR, Piehowski PD, Zhu K, Wang S, Clarke J, Huentelman MJ, Xie F, Andreev V, Engel A, Guettoche T, Navarro L, De Jager P, Schneider JA, Morris CM, McKeith IG, Perry RH, Lovestone S, Woltjer RL, Beach TG, Sue LI, Serrano GE, Lieberman AP, Albin RL, Ferrer I, Mash DC, Hulette CM, Ervin JF, Reiman EM, Hardy JA, Bennett DA, Schadt E, Smith RD, Myers AJ.

      Brain. 2018 Sep 1.

    • Cell type-specific CLIP reveals that NOVA regulates cytoskeleton interactions in motoneurons.

      Yuan Y, Xie S, Darnell JC, Darnell AJ, Saito Y, Phatnani H, Murphy EA, Zhang C, Maniatis T, Darnell RB.

      Genome Biol. 2018 Aug 15.

    • Unexpected similarities between C9ORF72 and sporadic forms of ALS/FTD suggest a common disease mechanism.

      Unexpected similarities between C9ORF72 and sporadic forms of ALS/FTD suggest a common disease mechanism.

      Conlon EG, Fagegaltier D, Agius P, Davis-Porada J, Gregory J, Hubbard I, Kang K, Kim D; New York Genome Center ALS Consortium, Phatnani H, Kwan J, Sareen D, Broach JR, Simmons Z, Arcila-Londono X, Lee EB, Van Deerlin VM, Shneider NA, Fraenkel E, Ostrow LW, Baas F, Zaitlen N, Berry JD, Malaspina A, Fratta P, Cox GA, Thompson LM, Finkbeiner S, Dardiotis E, Miller TM, Chandran S, Pal S, Hornstein E, MacGowan DJ, Heiman-Patterson T, Hammell MG, Patsopoulos NA, Dubnau J, Nath A, Phatnani H, Shneider NA, Manley JL.

      Elife. 2018. Jul 13.

    • Genome-wide Analyses Identify KIF5A as a Novel ALS Gene.

      Nicolas A, Kenna KP, Renton AE, Ticozzi N, Faghri F, Chia R, Dominov JA, Kenna BJ, Nalls MA, Keagle P, Rivera AM, van Rheenen W, Murphy NA, van Vugt JJFA, Geiger JT, Van der Spek RA, Pliner HA, Shankaracharya, Smith BN, Marangi G, Topp SD, Abramzon Y, Gkazi AS, Eicher JD, Kenna A; ITALSGEN Consortium, Mora G, Calvo A, Mazzini L, Riva N, Mandrioli J, Caponnetto C, Battistini S, Volanti P, La Bella V, Conforti FL, Borghero G, Messina S, Simone IL, Trojsi F, Salvi F, Logullo FO, D’Alfonso S, Corrado L, Capasso M, Ferrucci L; Genomic Translation for ALS Care (GTAC) Consortium, Moreno CAM, Kamalakaran S, Goldstein DB; ALS Sequencing Consortium, Gitler AD, Harris T, Myers RM; NYGC ALS Consortium, Phatnani H, Musunuri RL, Evani US, Abhyankar A, Zody MC; Answer ALS Foundation, Kaye J, Finkbeiner S, Wyman SK, LeNail A, Lima L, Fraenkel E, Svendsen CN, Thompson LM, Van Eyk JE, Berry JD, Miller TM, Kolb SJ, Cudkowicz M, Baxi E; Clinical Research in ALS and Related Disorders for Therapeutic Development (CReATe) Consortium, Benatar M, Taylor JP, Rampersaud E, Wu G, Wuu J; SLAGEN Consortium, Lauria G, Verde F, Fogh I, Tiloca C, Comi GP, Sorarù G, Cereda C; French ALS Consortium, Corcia P, Laaksovirta H, Myllykangas L, Jansson L, Valori M, Ealing J, Hamdalla H, Rollinson S, Pickering-Brown S, Orrell RW, Sidle KC, Malaspina A, Hardy J, Singleton AB, Johnson JO, Arepalli S, Sapp PC, McKenna-Yasek D, Polak M, Asress S, Al-Sarraj S, King A, Troakes C, Vance C, de Belleroche J, Baas F, Ten Asbroek ALMA, Muñoz-Blanco JL, Hernandez DG, Ding J, Gibbs JR, Scholz SW, Floeter MK, Campbell RH, Landi F, Bowser R, Pulst SM, Ravits JM, MacGowan DJL, Kirby J, Pioro EP, Pamphlett R, Broach J, Gerhard G, Dunckley TL, Brady CB, Kowall NW, Troncoso JC, Le Ber I, Mouzat K, Lumbroso S, Heiman-Patterson TD, Kamel F, Van Den Bosch L, Baloh RH, Strom TM, Meitinger T, Shatunov A, Van Eijk KR, de Carvalho M, Kooyman M, Middelkoop B, Moisse M, McLaughlin RL, Van Es MA, Weber M, Boylan KB, Van Blitterswijk M, Rademakers R, Morrison KE, Basak AN, Mora JS, Drory VE, Shaw PJ, Turner MR, Talbot K, Hardiman O, Williams KL, Fifita JA, Nicholson GA, Blair IP, Rouleau GA, Esteban-Pérez J, García-Redondo A, Al-Chalabi A; Project MinE ALS Sequencing Consortium, Rogaeva E, Zinman L, Ostrow LW, Maragakis NJ, Rothstein JD, Simmons Z, Cooper-Knock J, Brice A, Goutman SA, Feldman EL, Gibson SB, Taroni F, Ratti A, Gellera C, Van Damme P, Robberecht W, Fratta P, Sabatelli M, Lunetta C, Ludolph AC, Andersen PM, Weishaupt JH, Camu W, Trojanowski JQ, Van Deerlin VM, Brown RH Jr., van den Berg LH, Veldink JH, Harms MB, Glass JD, Stone DJ, Tienari P, Silani V, Chiò A, Shaw CE, Traynor BJ, Landers JE.

      Neuron. 2018 Mar. 21.

    • Whole Genome Sequencing-Based Discovery of Structural Variants in Glioblastoma.

      Wrzeszczynski KO, Felice V, Shah M, Rahman S, Emde AK, Jobanputra V, O Frank M, Darnell RB.

      Methods Mol Biol. 2018 Feb. 2.

    • Astrocytes in Neurodegenerative Disease.

      Phatnani H, Maniatis T.

      Cold Spring Harb Perspect Biol. 2015.

    • Dendritic cell vaccines containing lymphocytes produce improved immunogenicity in patients with cancer.

      Frank, M. O., Kaufman, J., Parveen, S., Blachère, N. E., Orange, D. E., Darnell, R. B.

      Journal of Translational Medicine, 2014. (PMID 25475068)

    • Genome Wide Mapping of Foxo1 Binding-sites in Murine T Lymphocytes

      Liao W, Ouyang W, Zhang MQ, Li MO.

      Genome Wide Mapping of Foxo1 Binding-sites in Murine
      T Lymphocytes. Genomics Data 2: 280-281, 2014.

  • Preprints

    • Enrichment of rare protein truncating variants in amyotrophic lateral sclerosis patients.

      Farhan SMKHowrigan DPAbbott LByrnes AChurchhouse C, Phatnani HSmith BTopp SRampersaud EWu GWuu JGubitz AKilm JMordes DGhosh SCReATe ConsortiumFALS ConsortiumALSGENS ConsortiumEggan KRademakers RMcCauley JSchule RZuchner SBenatar MTaylor JPNalls MTraynor BShaw CGoldstein DHarms MDaly MNeale B.

      bioRxiv. 2018 Apr. 25.

This work was partially supported by a gift from the Simons Foundation.