Transcriptional Architecture of Synaptic Communication Delineates GABAergic Neuron Identity

Abstract

SUMMARY Understanding the organizational logic of neural circuits requires deciphering the biological basis of neuronal diversity and identity, but there is no consensus on defining a neuron type. We analyzed single cell transcriptomes of a set of anatomically and physiologically characterized cortical GABAergic neurons and conducted a computational genomic screen for transcriptional profiles that distinguish them. We discovered that cardinal GABAergic neuron types are delineated by a transcriptional architecture that encodes their synaptic communication patterns. This architecture comprises 6 categories of ~40 gene families including cell adhesion molecules, transmitter-modulator receptors, ion channels, signaling proteins, neuropeptides and vesicular release components, and transcription factors. Combinatorial expression of select members across families shapes a multi-layered molecular scaffold along cell membrane that may customize synaptic connectivity patterns and input-output signaling properties. This molecular genetic framework of neuronal identity integrates cell phenotypes along multiple axes and provides a foundation for discovering and classifying neuron types.

Cell Type-Specific Gene Expression of Alpha 5 Subunit-Containing Gamma-Aminobutyric Acid Subtype A Receptors in Human and Mouse Frontal Cortex

“…Owing to the dense axonal arborization of SST cells that ascend towards, and innervate, nearby neurons across the corti cal column [34], this may represent an important tar get for extracellular GABA that activates extrasynaptic GABA A Rs. One study found neuronal nitric oxide-expressing SST cells localized to deep cortical layers dis­tinguished by coexpression of the γ1 subunit, which is thought to bias GABA A Rs to extrasynaptic localization [35], suggesting that these GABA A Rs may play an important role in regulating SST cell activity. Although anoth er study revealed α5-GABA A Rs present at synaptic sites [36], they are largely localized to extrasynaptic sites where they mediate tonic inhibition [37].…”

High-throughput mapping of long-range neuronal projection using in situ sequencing

“…The major classes of neocortical excitatory neurons-corticothalamic (CT), pyramidal tract (PT), and intratelencephalic (IT)-are defined by their long-range axonal projections, and are segregated within cortical laminae 9,10 . More recently, single cell sequencing has uncovered remarkable diversity in gene expression patterns [11][12][13][14] . Many classes of projection neurons identified by gene expression are restricted to specific laminae 13 , but it remains unclear whether projection patterns show comparable diversity, and whether projection diversity similarly respects laminar organization.…”

“…Such an intersectional organization, especially in the IT classes, is consistent with scRNAseq results of retrogradely labeled neurons 13 and could arise either from temporal changes in gene expression over development, or through probabilistic or activity-dependent pruning of projections during development. Thus downstream brain areas may receive information from multiple cell types through parallel pathways.Neuronal classes are defined by the combination of multiple features 14,19,21 , including anatomical characteristics such as morphology and connectivity 22,23 , molecular characteristics such as -13 or protein expression, and functional characteristics such as behaviorally-evoked activity 21 . Most current neuronal taxonomies focus on just a single feature, but partitioning based on one feature alone does not reveal the interaction among neuronal features that result in circuit functions.…”

“…Neuronal classes are defined by the combination of multiple features 14,19,21 , including anatomical characteristics such as morphology and connectivity 22,23 , molecular characteristics such as -13 or protein expression, and functional characteristics such as behaviorally-evoked activity 21 . Most current neuronal taxonomies focus on just a single feature, but partitioning based on one feature alone does not reveal the interaction among neuronal features that result in circuit functions.…”

“…Neuronal classes are defined by the combination of multiple features 14,19,21 , including anatomical characteristics such as morphology and connectivity 22,23 , molecular characteristics such as . CC-BY-NC 4.0 International license It is made available under a was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.…”