The Patch-seq approach is a powerful variation of the patch-clamp technique that allows for the combined electrophysiological, morphological, and transcriptomic characterization of individual neurons. To generate Patch-seq datasets at scale, we identified and refined key factors that contribute to the efficient collection of high-quality data. We developed patch-clamp electrophysiology software with analysis functions specifically designed to automate acquisition with online quality control.
We recognized the importance of extracting the nucleus for transcriptomic success and maximizing membrane integrity during nucleus extraction for morphology success.
The protocol is generalizable to different species and brain regions, as demonstrated by capturing multimodal data from human and macaque brain slices. This resource can be used by individual labs to generate data across diverse mammalian species and that is compatible with large publicly available Patch-seq datasets.
Describing and understanding the properties of neuronal cell types is a critical first step toward understanding circuit activity within the brain, and ultimately cognitive function. Neurons exhibit stereotyped yet diverse electrophysiological, morphological, and transcriptomic properties Tasic et al. Dissociated cells or nuclei are isolated in a high-throughput manner to provide a comprehensive analysis of the molecular underpinnings of a single cell.
Systematic and large-scale scRNA-seq approaches have been successful at characterizing brain cell types across mammalian species Yao et al. These large-scale studies often include data from tens of thousands to millions of neurons, whereas electrophysiological or morphological studies are limited to tens or hundreds of neurons.
