Abstract
Retinal neurons are remarkedly diverse based on structure, function and genetic identity. Classifying these cells is a challenging task, requiring multimodal methodology. Here, we introduce a novel approach for retinal ganglion cell (RGC) classification, based on pharmacogenetics combined with immunohistochemistry and large-scale retinal electrophysiology. Our novel strategy allows grouping of cells sharing gene expression and understanding how these cell classes respond to basic and complex visual scenes. Our approach consists of several consecutive steps. First, the spike firing frequency is increased in RGCs co-expressing a certain gene (Scnn1a or Grik4) using excitatory DREADDs (designer receptors exclusively activated by designer drugs) in order to single out activity originating specifically from these cells. Their spike location is then combined with post hoc immunostaining, to unequivocally characterize their anatomical and functional features. We grouped these isolated RGCs into multiple clusters based on spike train similarities. Using this novel approach, we were able to extend the pre-existing list of Grik4-expressing RGC types to a total of eight and, for the first time, we provide a phenotypical description of 13 Scnn1a-expressing RGCs. The insights and methods gained here can guide not only RGC classification but neuronal classification challenges in other brain regions as well.
Highlights
The retina contains two types of photoreceptors, rods for dim light and cones for daylight and colour vision
To functionally validate retinal ganglion cell (RGC) subgroups according to shared gene expression, we first established an immunocytochemical atlas of these cells
We first investigated the distribution of Grik4 and Scnn1a cells in the ganglion cell layer (GCL) in retinal whole mounts using an antibody against green fluorescent protein (GFP) to amplify the intrinsic mCitrine signal
Summary
The retina contains two types of photoreceptors, rods for dim light and cones for daylight and colour vision. Cone-contacting bipolar cells can be divided into ON and OFF types and further subdivided into more than a dozen different subpopulations [1]. These parallel-processed channels are further divided into a variety of functional output channels, so-called retinal ganglion cells (RGCs), which encode different features of the visual environment. Different types of RGCs extract very specific features from the visual scenery [4]. This code is transmitted to postsynaptic targets in the brain, leading to visual perception. RGC classification is typically based on common anatomical features [7,8], responses to light [5,9–11] or on shared gene expression [6,12–14]. Classification based on gene expression is relatively recent, and the majority of RGC groups sharing specific genes have not been phenotyped yet
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