An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types
A. Sina Booeshaghi,
Ricky S. Adkins,
Andrew I. Aldridge,
Seth A. Ament,
M. Margarita Behrens,
Koen Van den Berge,
Héctor Corrada Bravo,
Elizabeth L. Dougherty,
Wayne I. Doyle,
Hector Roux de Bézieux,
Brian R. Herb,
Yang Eric Li,
Jacinta D. Lucero,
Naeem M. Nadaf,
Joseph R. Nery,
Julia K. Osteen,
Angeline C. Rivkin,
Thuc Nghi Nguyen,
Eeshit Dhaval Vaishnav,
Charles R. Vanderburg,
Cindy T.J. van Velthoven,
Z. Josh Huang,
Peter V. Kharchenko,
Joshua D. Welch,
Evan Z. Macosko,
Joseph R. Ecker,
Eran A. Mukamel
Posted 02 Mar 2020
bioRxiv DOI: 10.1101/2020.02.29.970558
Posted 02 Mar 2020
Single cell transcriptomics has transformed the characterization of brain cell identity by providing quantitative molecular signatures for large, unbiased samples of brain cell populations. With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp. Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis.
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