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An anatomically comprehensive atlas of the adult human brain transcriptome

Author

Listed:
  • Michael J. Hawrylycz

    (Allen Institute for Brain Science)

  • Ed S. Lein

    (Allen Institute for Brain Science)

  • Angela L. Guillozet-Bongaarts

    (Allen Institute for Brain Science)

  • Elaine H. Shen

    (Allen Institute for Brain Science)

  • Lydia Ng

    (Allen Institute for Brain Science)

  • Jeremy A. Miller

    (Allen Institute for Brain Science)

  • Louie N. van de Lagemaat

    (Genes to Cognition Programme, Edinburgh University)

  • Kimberly A. Smith

    (Allen Institute for Brain Science)

  • Amanda Ebbert

    (Allen Institute for Brain Science)

  • Zackery L. Riley

    (Allen Institute for Brain Science)

  • Chris Abajian

    (Allen Institute for Brain Science)

  • Christian F. Beckmann

    (MIRA Institute, University of Twente & Donders Institute, Radboud University Nijmegen)

  • Amy Bernard

    (Allen Institute for Brain Science)

  • Darren Bertagnolli

    (Allen Institute for Brain Science)

  • Andrew F. Boe

    (Allen Institute for Brain Science)

  • Preston M. Cartagena

    (University of California)

  • M. Mallar Chakravarty

    (Allen Institute for Brain Science
    Kimel Family Translational Imaging-Genetics Laboratory, Centre for Addiction and Mental Health Toronto, Ontario M5S 2S1, Canada)

  • Mike Chapin

    (Allen Institute for Brain Science)

  • Jimmy Chong

    (Allen Institute for Brain Science)

  • Rachel A. Dalley

    (Allen Institute for Brain Science)

  • Barry David Daly

    (University of Maryland School of Medicine, University of Maryland Medical Center)

  • Chinh Dang

    (Allen Institute for Brain Science)

  • Suvro Datta

    (Allen Institute for Brain Science)

  • Nick Dee

    (Allen Institute for Brain Science)

  • Tim A. Dolbeare

    (Allen Institute for Brain Science)

  • Vance Faber

    (Allen Institute for Brain Science)

  • David Feng

    (Allen Institute for Brain Science)

  • David R. Fowler

    (University of Maryland School of Medicine)

  • Jeff Goldy

    (Allen Institute for Brain Science)

  • Benjamin W. Gregor

    (Allen Institute for Brain Science)

  • Zeb Haradon

    (Allen Institute for Brain Science)

  • David R. Haynor

    (University of Washington)

  • John G. Hohmann

    (Allen Institute for Brain Science)

  • Steve Horvath

    (Gonda Research Center, David Geffen School of Medicine)

  • Robert E. Howard

    (Allen Institute for Brain Science)

  • Andreas Jeromin

    (Banyan Biomarkers, Inc.)

  • Jayson M. Jochim

    (Allen Institute for Brain Science)

  • Marty Kinnunen

    (Allen Institute for Brain Science)

  • Christopher Lau

    (Allen Institute for Brain Science)

  • Evan T. Lazarz

    (Allen Institute for Brain Science)

  • Changkyu Lee

    (Allen Institute for Brain Science)

  • Tracy A. Lemon

    (Allen Institute for Brain Science)

  • Ling Li

    (Office of the Chief Medical Examiner, Baltimore, MD, University of Maryland)

  • Yang Li

    (Allen Institute for Brain Science)

  • John A. Morris

    (Allen Institute for Brain Science)

  • Caroline C. Overly

    (Allen Institute for Brain Science)

  • Patrick D. Parker

    (Allen Institute for Brain Science)

  • Sheana E. Parry

    (Allen Institute for Brain Science)

  • Melissa Reding

    (Allen Institute for Brain Science)

  • Joshua J. Royall

    (Allen Institute for Brain Science)

  • Jay Schulkin

    (Georgetown University, School of Medicine)

  • Pedro Adolfo Sequeira

    (Functional Genomics Laboratory, School of Medicine, University of California)

  • Clifford R. Slaughterbeck

    (Allen Institute for Brain Science)

  • Simon C. Smith

    (Histion LLC)

  • Andy J. Sodt

    (Allen Institute for Brain Science)

  • Susan M. Sunkin

    (Allen Institute for Brain Science)

  • Beryl E. Swanson

    (Allen Institute for Brain Science)

  • Marquis P. Vawter

    (Functional Genomics Laboratory, School of Medicine, University of California)

  • Derric Williams

    (Allen Institute for Brain Science)

  • Paul Wohnoutka

    (Allen Institute for Brain Science)

  • H. Ronald Zielke

    (The Eunice Kennedy Shriver NICHD Brain and Tissue Bank for Developmental Disorders, University of Maryland)

  • Daniel H. Geschwind

    (Program in Neurogenetics, and Semel Institute, David Geffen School of Medicine-UCLA)

  • Patrick R. Hof

    (Mount Sinai School of Medicine)

  • Stephen M. Smith

    (FMRIB, Oxford University)

  • Christof Koch

    (Allen Institute for Brain Science
    Computation & Neural Systems, California Institute of Technology)

  • Seth G. N. Grant

    (Genes to Cognition Programme, Edinburgh University)

  • Allan R. Jones

    (Allen Institute for Brain Science)

Abstract

Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ∼900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography—the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function.

Suggested Citation

  • Michael J. Hawrylycz & Ed S. Lein & Angela L. Guillozet-Bongaarts & Elaine H. Shen & Lydia Ng & Jeremy A. Miller & Louie N. van de Lagemaat & Kimberly A. Smith & Amanda Ebbert & Zackery L. Riley & Chr, 2012. "An anatomically comprehensive atlas of the adult human brain transcriptome," Nature, Nature, vol. 489(7416), pages 391-399, September.
  • Handle: RePEc:nat:nature:v:489:y:2012:i:7416:d:10.1038_nature11405
    DOI: 10.1038/nature11405
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