A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

Zizhen Yao(Allen Institute for Brain Science), Cindy T. J. van Velthoven(Allen Institute for Brain Science), Michael Kunst(Allen Institute for Brain Science), Meng Zhang(Howard Hughes Medical Institute), Delissa McMillen(Allen Institute for Brain Science), Changkyu Lee(Allen Institute for Brain Science), Won Jung(Howard Hughes Medical Institute), Jeff Goldy(Allen Institute for Brain Science), Aliya Abdelhak(Allen Institute for Brain Science), Pamela Baker(Allen Institute for Brain Science), Eliza Barkan(Allen Institute for Brain Science), Darren Bertagnolli(Allen Institute for Brain Science), Jazmin Campos(Allen Institute for Brain Science), Daniel Carey(Allen Institute for Brain Science), Tamara Casper(Allen Institute for Brain Science), Anish Bhaswanth Chakka(Allen Institute for Brain Science), Rushil Chakrabarty(Allen Institute for Brain Science), Sakshi Chavan(Allen Institute for Brain Science), Min Chen(University of Pennsylvania), Michael Clark(Allen Institute for Brain Science), Jennie Close(Allen Institute for Brain Science), Kirsten Crichton(Allen Institute for Brain Science), Scott Daniel(Allen Institute for Brain Science), Tim Dolbeare(Allen Institute for Brain Science), Lauren Ellingwood(Allen Institute for Brain Science), James C. Gee(University of Pennsylvania), Alexandra Glandon(Allen Institute for Brain Science), Jessica Gloe(Allen Institute for Brain Science), Joshua Gould, J. Gray(Allen Institute for Brain Science), Nathan Guilford(Allen Institute for Brain Science), Junitta Guzman(Allen Institute for Brain Science), Daniel Hirschstein(Allen Institute for Brain Science), Windy Ho(Allen Institute for Brain Science), Kelly Jin(Allen Institute for Brain Science), Matthew Kroll(Allen Institute for Brain Science), Kanan Lathia(Allen Institute for Brain Science), Arielle Leon(Allen Institute for Brain Science), Brian Long(Allen Institute for Brain Science), Zoe Maltzer(Allen Institute for Brain Science), Naomi Martin(Allen Institute for Brain Science), Rachel McCue(Allen Institute for Brain Science), Emma Meyerdierks(Allen Institute for Brain Science), Thuc Nghi Nguyen(Allen Institute for Brain Science), Trangthanh Pham(Allen Institute for Brain Science), Christine Rimorin(Allen Institute for Brain Science), Augustin Ruiz(Allen Institute for Brain Science), Nadiya V. Shapovalova(Allen Institute for Brain Science), Cliff Slaughterbeck(Allen Institute for Brain Science), Josef Šulc(Allen Institute for Brain Science), Michael Tieu(Allen Institute for Brain Science), Amy Torkelson(Allen Institute for Brain Science), Herman Tung(Allen Institute for Brain Science), Nasmil Valera Cuevas(Allen Institute for Brain Science), Katherine Wadhwani(Allen Institute for Brain Science), Katelyn Ward(Allen Institute for Brain Science), Boaz P. Levi(Allen Institute for Brain Science), Colin Farrell(Allen Institute for Brain Science), Carol L. Thompson(Allen Institute for Brain Science), Shoaib Mufti(Allen Institute for Brain Science), Chelsea M. Pagan(Allen Institute for Brain Science), Lauren Kruse(Allen Institute for Brain Science), Nick Dee(Allen Institute for Brain Science), Susan M. Sunkin(Allen Institute for Brain Science), Luke Esposito(Allen Institute for Brain Science), Michael Hawrylycz(Allen Institute for Brain Science), Jack Waters(Allen Institute for Brain Science), Lydia Ng(Allen Institute for Brain Science), Kimberly A. Smith(Allen Institute for Brain Science), Bosiljka Tasic(Allen Institute for Brain Science), Xiaowei Zhuang(Howard Hughes Medical Institute), Hongkui Zeng(Allen Institute for Brain Science)
bioRxiv (Cold Spring Harbor Laboratory)
March 6, 2023
Cited by 138Open Access
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Abstract

The mammalian brain is composed of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single-cell RNA-sequencing (scRNA-seq) dataset of ~7 million cells profiled, and a spatially resolved transcriptomic dataset of ~4.3 million cells using MERFISH. The atlas is hierarchically organized into five nested levels of classification: 7 divisions, 32 classes, 306 subclasses, 1,045 supertypes and 5,200 clusters. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate a myriad of modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cell type and circuit function, development, and evolution of the mammalian brain.


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