A multimodal cell census and atlas of the mammalian primary motor cortex
BRAIN Initiative Cell Census Network (BICCN), BRAIN Initiative Cell Census Network (BICCN) Corresponding authors, Edward M. CallawayiD, Hong‐Wei DongiD, Joseph R. EckeriD, Michael HawrylycziD, Z. Josh HuangiD, Ed S. LeiniD, John NgaiiD, Pavel OsteniD, Bing ReniD, Andreas Savas ToliasiD, Owen R. WhiteiD, Hongkui ZengiD, Xiaowei ZhuangiD, BICCN contributing principal investigators, Giorgio A. AscoliiD, M. Margarita BehrensiD, Jerold J. M. ChuniD, Guoping FengiD, James C. GeeiD, Satrajit GhoshiD, Yaroslav O. HalchenkoiD, Ronna P. HertzanoiD, Byung Kook LimiD, , Cindy T. J. van VelthoveniD
Abstract
We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.
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