A multimodal cell census and atlas of the mammalian primary motor cortex
Published in Nature, 598(7879), 86-102, 2021
Recommended citation: Principal manuscript editors, Analysis coordination, Integrated data analysis Armand Ethan 42 Yao Zizhen 5, ATAC-seq data generation and processing Fang Rongxin 45 Hou Xiaomeng 10 Lucero Jacinta D. 18 Osteen Julia K. 18 Pinto-Duarte Antonio 18 Poirion Olivier 10 Preissl Sebastian 10 Wang Xinxin 10 97, Epi-retro-seq data generation and processing Dominguez Bertha 53 Ito-Cole Tony 1 Jacobs Matthew 1 Jin Xin 54 99 100 Lee Cheng-Ta 53 Lee Kuo-Fen 53 Miyazaki Paula Assakura 1 Pang Yan 1 Rashid Mohammad 1 Smith Jared B. 54 Vu Minh 1 Williams Elora 54, OLST/STPT and other data generation Narasimhan Arun 6 Palaniswamy Ramesh 6, ... & Project management Kelly Kathleen 6 Mok Stephanie 5 Sunkin Susan 5. (2021). A multimodal cell census and atlas of the mammalian primary motor cortex. Nature, 598(7879), 86-102. ‘http://sd-jiang.github.io/files/Nature_BICCN_flagship.pdf’
Abstract:
Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex 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. 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 integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.