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A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex

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  • Additional Information
    • Publication Information:
      Nature Publishing Group
    • Publication Date:
      2021
    • Collection:
      Caltech Authors (California Institute of Technology)
    • Abstract:
      Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas—containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities—is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis. ; © 2021 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by ...
    • Relation:
      https://doi.org/10.1101/2020.02.29.970558; https://assets.nemoarchive.org/dat-ch1nqb7; https://nemoanalytics.org/; https://brainome.ucsd.edu/annoj/BICCN_MOp; https://epiviz.nemoanalytics.org/biccn_mop; https://github.com/AllenInstitute/scrattch.hicat; https://github.com/r3fang/SnapTools; https://github.com/lhqing/cemba_data; https://lhqing.github.io/ALLCools; https://github.com/gillislab/MetaNeighbor-BICCN; https://github.com/welch-lab/liger; https://github.com/mukamel-lab/SingleCellFusion; https://github.com/kharchenkolab/conos; https://www.ncbi.nlm.nih.gov/pmc/PMC8494649; eprintid:101686
    • Accession Number:
      10.1038/s41586-021-03500-8
    • Online Access:
      https://doi.org/10.1038/s41586-021-03500-8
      https://www.ncbi.nlm.nih.gov/pmc/PMC8494649
    • Rights:
      info:eu-repo/semantics/openAccess ; Other
    • Accession Number:
      edsbas.EE6F61F1