Abstract

The mammalian retina harbors over 100 different cell types. To understand how retinal circuits work, it is essential to systematically access each type. A widely used approach for achieving targeted transgene expression exploits promoter-driven Cre lines. However, Cre expression in a given transgenic line in the retina and elsewhere in the brain is rarely confined to a single cell type, contributing ambiguity to the interpretation of results from broadly applied manipulations. To obtain unambiguous information about retinal processing, it is desirable to have strategies for further restricting transgene expression to a few or even to a single cell type. We employed an intersectional strategy based on a Cre/Flp double recombinase system to target amacrine and ganglion cell types in the inner retina. We analyzed expression patterns in seven Flp drivers and then created combinational mouse lines by selective cross breeding with Cre drivers. Breeding with Flp drivers can routinely remove labeling from more than 90% of the cells in Cre drivers, leading to only a handful cell types, typically 2–3, remaining in the intersection. Cre/Flp combinatorial mouse lines enabled us to identify and anatomically characterize retinal cell types with greater ease and demonstrated the feasibility of intersectional strategies in retinal research. In addition to the retina, we examined Flp expression in the lateral geniculate nucleus and superior colliculus. Our results establish a foundation for future application of intersectional strategies in the retina and retino-recipient regions.

Highlights

  • The retina is an experimentally tractable preparation for understanding how nervous systems abstract complex information from the environment, including information about object motion, orientation, and permanence under different light conditions (Wassle, 2004; Masland, 2012; Demb and Singer, 2015)

  • While Cre drivers have been screened for their expression patterns in the retina (Ivanova et al, 2010; Lu et al, 2013; Zhu et al, 2014; Martersteck et al, 2017), no Flp drivers have been screened

  • As in many other brain circuits, there are two major challenges for dissecting retinal circuits: (Demb and Singer, 2015) to increase the specificity of cell-type targeting and (Masland, 2012) to discover new cell types involved in the circuits

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Summary

Introduction

The retina is an experimentally tractable preparation for understanding how nervous systems abstract complex information from the environment, including information about object motion, orientation, and permanence under different light conditions (Wassle, 2004; Masland, 2012; Demb and Singer, 2015). A diversity of cell types in the retina provides the infrastructure necessary for visual signal processing. There are at least 40 types of RGCs, 50 types of ACs, 14 types of bipolar cells, 2 types of horizontal cells, and 3 types of glial cells (Masland, 2012; Demb and Singer, 2015). An RGC type receives excitatory inputs from a subset of the cone bipolar cell types and inhibitory inputs from a subset of AC types (Masland, 2012; Demb and Singer, 2015). Due to the large number of cell types involved and their extensive process ramifications in the innerplexiform layer (IPL), a connectivity diagram containing both functional and anatomical information for the bipolar and AC circuits that feed into each ganglion cell type is unresolved

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