Correlating Anatomy and Function with Gene Expression in Individual Neurons by Combining in Vivo Labeling, Patch Clamp, and Single Cell RNA-seq.

Carsten K Pfeffer,Riccardo Beltramo

doi:10.3389/fncel.2017.00376

Carsten K Pfeffer, Riccardo Beltramo

Open Access

https://doi.org/10.3389/fncel.2017.00376

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Abstract

The classification of neurons into distinct types is an ongoing effort aimed at revealing and understanding the diversity of the components of the nervous system. Recently available methods allow us to determine the gene expression pattern of individual neurons in the mammalian cerebral cortex to generate powerful categorization schemes. For a thorough understanding of neuronal diversity such genetic categorization schemes need to be combined with traditional classification parameters like position, axonal projection or response properties to sensory stimulation. Here we describe a method to link the gene expression of individual neurons with their position, axonal projection, or sensory response properties. Neurons are labeled in vivo based on their anatomical or functional properties and, using patch clamp pipettes, their RNA individually harvested in vitro for RNAseq. We validate the methodology using multiple established molecularly and anatomically distinct cell populations and explore molecular differences between uncharacterized neurons in mouse visual cortex. Gene expression patterns between L5 neurons projecting to frontal or contralateral cortex are distinct while L2 neurons differing in position, projection, or function are molecularly similar. With this method we can determine the genetic expression pattern of functionally and anatomically identified individual neurons.

Highlights

The classification of neurons into distinct cell-types is an ongoing effort that began in the nineteenth century (Ramón y Cajal, 1995)
We describe an approach to determine the gene expression pattern of individual neurons with specific locations, axonal projection patterns and responses to sensory stimulation determined in vivo
First we identified highly variable genes (Brennecke et al, 2013) which were used to assess the similarity of gene expression in individual cells using t-distributed stochastic neighbor embedding (t-SNE), principal component analysis (PCA) and Pearson correlation

Summary

Introduction

The classification of neurons into distinct cell-types is an ongoing effort that began in the nineteenth century (Ramón y Cajal, 1995). Contemporary classification of neurons is based on anatomical parameters, (e.g., where the cell body is located), morphological parameters (e.g., where the neurites project), molecular properties (e.g., what proteins are expressed or transmitters released), and functional properties (e.g., what conditions are necessary for their activation; Ascoli et al, 2008; Defelipe et al, 2013; Fishell and Heintz, 2013). Bulk isolation methods cannot be combined with precise positional information about individual neurons. These methods are not suitable to determine the gene expression pattern of individual neurons in combination with information relative to their activity pattern observed in vivo, for example their specific response to sensory stimulation. Approaches need to be developed where the precise positional, anatomical, and functional identity of individual neurons can be combined with their transcriptional profile

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