Abstract
Obtaining a catalog of cell types is a fundamental building block for understanding the brain. The ideal classification of cell-types is based on the profile of molecules expressed by a cell, in particular, the profile of genes expressed. One strategy is, therefore, to obtain as many single-cell transcriptomes as possible and isolate clusters of neurons with similar gene expression profiles. In this study, we explored an alternative strategy. We explored whether cell-types can be algorithmically derived by combining protein tissue stains with transcript expression profiles. We developed an algorithm that aims to distribute cell-types in the different layers of somatosensory cortex of the developing rat constrained by the tissue- and cellular level data. We found that the spatial distribution of major inhibitory cell types can be approximated using the available data. The result is a depth-wise atlas of inhibitory cell-types of the rat somatosensory cortex. In principle, any data that constrains what can occur in a particular part of the brain can also strongly constrain the derivation of cell-types. This draft inhibitory cell-type mapping is therefore dynamic and can iteratively converge towards the ground truth as further data is integrated.
Highlights
Mapping the anatomical location of interneurons subtypes within the cerebral cortex is an unsolved problem
Interneurons exhibit different morphological and electrophysiological properties and each type of interneuron plays a unique role in nervous system function (Markram et al, 2004)
We focus on interneurons because there is a clearly-identified subset of proteins known to be expressed in separate populations of interneurons: calbindin (CB), calretinin (CR), neuropeptide Y (NPY), parvalbumin (PV), somatostatin (SOM) and vasointestinal peptide (VIP; Rudy et al, 2011; Tremblay et al, 2012)
Summary
Mapping the anatomical location of interneurons subtypes within the cerebral cortex is an unsolved problem. Interneurons exhibit different morphological and electrophysiological properties and each type of interneuron plays a unique role in nervous system function (Markram et al, 2004). Simulations of the cortex, for example, can potentially use the resulting cell type-specific densities (Markram et al, 2015; Schmidt et al, 2018). The definition of what constitutes particular cell types is not yet fully established, though standards are emerging (Petilla Interneuron Nomenclature Group, 2008). Neurons in the cortex can be classified in terms of their electrical and morphological properties, the projection patterns, and the proteins and genes they express (ibid.). As many as 50 cortical interneuron types may exist (Lim et al, 2018). A definitive classification together with a distribution approach will allow establishment
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