Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types

Abstract

AbstractNeural circuit function is shaped both by the cell types that comprise the circuit and the connections between those cell types1. Neural cell types have previously been defined by morphology2, 3, electrophysiology4, 5, transcriptomic expression6–8, connectivity9–13, or even a combination of such modalities14–16. More recently, the Patch-seq technique has enabled the characterization of morphology (M), electrophysiology (E), and transcriptomic (T) properties from individual cells17–20. Using this technique, these properties were integrated to define 28, inhibitory multimodal, MET-types in mouse primary visual cortex21. It is unknown how these MET-types connect within the broader cortical circuitry however. Here we show that we can predict the MET-type identity of inhibitory cells within a large-scale electron microscopy (EM) dataset and these MET-types have distinct ultrastructural features and synapse connectivity patterns. We found that EM Martinotti cells, a well defined morphological cell type22, 23known to be Somatostatin positive (Sst+)24, 25, were successfully predicted to belong to Sst+ MET-types. Each identified MET-type had distinct axon myelination patterns and synapsed onto specific excitatory targets. Our results demonstrate that morphological features can be used to link cell type identities across imaging modalities, which enables further comparison of connectivity in relation to transcriptomic or electrophysiological properties. Furthermore, our results show that MET-types have distinct connectivity patterns, supporting the use of MET-types and connectivity to meaningfully define cell types.