The cell adhesion molecule Sdk1 shapes assembly of a retinal circuit that detects localized edges.

Pierre-Luc Rochon,Aline Giselle Rangel Olguin,Arjun Krishnaswamy,Catherine Theriault

doi:10.7554/elife.70870

Abstract

Nearly 50 different mouse retinal ganglion cell (RGC) types sample the visual scene for distinct features. RGC feature selectivity arises from their synapses with a specific subset of amacrine (AC) and bipolar cell (BC) types, but how RGC dendrites arborize and collect input from these specific subsets remains poorly understood. Here we examine the hypothesis that RGCs employ molecular recognition systems to meet this challenge. By combining calcium imaging and type-specific histological stains, we define a family of circuits that express the recognition molecule Sidekick-1 (Sdk1), which include a novel RGC type (S1-RGC) that responds to local edges. Genetic and physiological studies revealed that Sdk1 loss selectively disrupts S1-RGC visual responses, which result from a loss of excitatory and inhibitory inputs and selective dendritic deficits on this neuron. We conclude that Sdk1 shapes dendrite growth and wiring to help S1-RGCs become feature selective.

Highlights

In the retina, each of the ~46 types of retinal ganglion cell (RGC) synapses with a unique subset of amacrine (AC) and bipolar cell (BC) types to create circuits that detect a unique aspect of the visual scene (Clark and Demb, 2016; Gollisch and Meister, 2010; Jadzinsky and Baccus, 2013; Sanes and Masland, 2015; Shekhar et al, 2016; Tran et al, 2019; Yan et al, 2020)
We found that most S1-RGCs showed responses to axial bar motion, similar to what we saw in our calcium imaging experiments
In the first section of this study, we molecularly, anatomically, and functionally defined 5 Sidekick 1 (Sdk1) interneurons (ACs and BCs) and 5 Sdk1-RGCs that target an inner set of inner plexiform layer (IPL) lamina

Summary

Introduction

Each of the ~46 types of retinal ganglion cell (RGC) synapses with a unique subset of amacrine (AC) and bipolar cell (BC) types to create circuits that detect a unique aspect of the visual scene (Clark and Demb, 2016; Gollisch and Meister, 2010; Jadzinsky and Baccus, 2013; Sanes and Masland, 2015; Shekhar et al, 2016; Tran et al, 2019; Yan et al, 2020). Recent connectomic studies of the IPL demonstrate no obvious relationship between contact frequency and synapse number (Briggman et al, 2011; Helmstaedter et al, 2013). Instead, these connectomic data support a model in which neurons recognize targets in their immediate vicinity and synapse with them. These connectomic data support a model in which neurons recognize targets in their immediate vicinity and synapse with them Key molecules in this recognition process are thought to be members of the immunoglobulin superfamily (IgSFs)

Methods

Results

Conclusion