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A harmonized atlas of mouse spinal cord cell types and their spatial organization.
Russ, Daniel E; Cross, Ryan B Patterson; Li, Li; Koch, Stephanie C; Matson, Kaya J E; Yadav, Archana; Alkaslasi, Mor R; Lee, Dylan I; Le Pichon, Claire E; Menon, Vilas; Levine, Ariel J.
Afiliación
  • Russ DE; Division of Cancer Epidemiology and Genetics, Data Science Research Group, National Cancer Institute, NIH, Rockville, MD, USA.
  • Cross RBP; Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA.
  • Li L; Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA.
  • Koch SC; Department of Neuroscience, Physiology and Pharmacology, Division of Biosciences, University College London, London, UK.
  • Matson KJE; Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA.
  • Yadav A; Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, USA.
  • Alkaslasi MR; Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD, USA.
  • Lee DI; Department of Neuroscience, Brown University, Providence, RI, USA.
  • Le Pichon CE; Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, USA.
  • Menon V; Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD, USA.
  • Levine AJ; Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, USA.
Nat Commun ; 12(1): 5722, 2021 09 29.
Article en En | MEDLINE | ID: mdl-34588430
ABSTRACT
Single-cell RNA sequencing data can unveil the molecular diversity of cell types. Cell type atlases of the mouse spinal cord have been published in recent years but have not been integrated together. Here, we generate an atlas of spinal cell types based on single-cell transcriptomic data, unifying the available datasets into a common reference framework. We report a hierarchical structure of postnatal cell type relationships, with location providing the highest level of organization, then neurotransmitter status, family, and finally, dozens of refined populations. We validate a combinatorial marker code for each neuronal cell type and map their spatial distributions in the adult spinal cord. We also show complex lineage relationships among postnatal cell types. Additionally, we develop an open-source cell type classifier, SeqSeek, to facilitate the standardization of cell type identification. This work provides an integrated view of spinal cell types, their gene expression signatures, and their molecular organization.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Médula Espinal / Transcriptoma / Neuronas Límite: Animals Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Médula Espinal / Transcriptoma / Neuronas Límite: Animals Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos