A community-based transcriptomics classification and nomenclature of neocortical cell types

Abstract

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

JSTA: joint cell segmentation and cell type annotation for spatial transcriptomics

“…Agreements between cell type taxonomies developed solely based on scRNAseq and other measurement modalities, i.e. spatial position, corroborates the relevance of the taxonomical definitions created for mouse brain 22 . At the same time, the spatial measurements demonstrate the limitation of scRNAseq.…”

“…We compared JSTA to watershed in assigning mRNAs to cells through simulation studies to evaluate their accuracy. Application of JSTA to MERFISH measurements of gene expression in the mouse hippocampus together with Neocortical Cell Type Taxonomy 22 (NCTT) provides a highly granular map of cell (sub)type spatial organization and identified many spatially differentially expressed genes (spDEGs) within these (sub)types 23 .…”

Light microscopy based approach for mapping connectivity with molecular specificity

“…Our definitions of cell types are constantly changing with the introduction of new technologies. We have progressed from using unimodal criteria (e.g., morphology, physiology, or molecular expression) to using a combination of these properties in a multimodal fashion 42 . Recent studies have demonstrated the power of this multimodal approach to curate and refine definitions of inhibitory and excitatory neuronal cell types in visual cortex 43,44 .…”

A multimodal cell census and atlas of the mammalian primary motor cortex

“…Understanding the principles of brain circuit organization requires a detailed understanding of its basic components, but the cellular diversity and complexity of the brain, including the neocortex, have defied a comprehensive and quantitative description. Single-cell transcriptomics and epigenomics, as well as spatially resolved single-cell transcriptomics, are accelerating efforts to classify all molecular cell types in many organ systems 40,99 , including the brain 5,6,100 . The current effort combines these technologies to derive a robust and comprehensive molecular cell type classification and census of the primary motor cortex of mouse, marmoset and human, coupled with a spatial atlas of cell types and an anatomical input/output wiring diagram in mouse.…”

“…However, microglia are not closely related to these neuroectoderm-derived populations based on transcriptomics or developmental origins 103 and should be grouped with other more similar non-neuronal cell types such as endothelial cells, VLMCs and pericytes. Substantial challenges remain for redefining data-driven cell ontologies and nomenclature systems 100,104 .…”