Molecular identification of sixty-three amacrine cell types completes a mouse retinal cell atlas

Abstract

Amacrine cells (ACs) are a diverse class of interneurons that modulate input from photoreceptors to retinal ganglion cells (RGCs), rendering each RGC type selectively sensitive to particular visual features, which are then relayed to the brain. While many AC types have been identified morphologically and physiologically, they have not been comprehensively classified or molecularly characterized. We used high-throughput single-cell RNA sequencing (scRNA-seq) to profile >32,000 ACs from mouse retina, and applied computational methods to identify 63 AC types. We identified molecular markers for each type, and used them to characterize the morphology of multiple types. We show that they include nearly all previously known AC types as well as many that had not been described. Consistent with previous studies, most of the AC types express markers for the canonical inhibitory neurotransmitters GABA or glycine, but several express neither or both. In addition, many express one or more neuropeptides, and two express glutamatergic markers. We also explored transcriptomic relationships among AC types and identified transcription factors expressed by individual or multiple closely related types. Noteworthy among these were Meis2 and Tcf4, expressed by most GABAergic and most glycinergic types, respectively. Together, these results provide a foundation for developmental and functional studies of ACs, as well as means for genetically accessing them. Along with previous molecular, physiological and morphological analyses, they establish the existence of at least 130 neuronal types and nearly 140 cell types in mouse retina. SIGNIFICANCE STATEMENTThe mouse retina is a leading model for analyzing the development, structure, function and pathology of neural circuits. A complete molecular atlas of retinal cell types provides an important foundation for these studies. We used high-throughput single-cell RNA sequencing (scRNA-seq) to characterize the most heterogeneous class of retinal interneurons, amacrine cells, identifying 63 distinct types. The atlas includes types identified previously as well as many novel types. We provide evidence for use of multiple neurotransmitters and neuropeptides and identify transcription factors expressed by groups of closely related types. Combining these results with those obtained previously, we proposed that the mouse retina contains 130 neuronal types, and is therefore comparable in complexity to other regions of the brain.

Gbx2 identifies two amacrine cell subtypes with distinct molecular, morphological, and physiological properties

“…Therefore, S3-Gbx2+ ACs are a subtype of non-Glycinergic, non-GABAergic (nGnG) AC. These results are consistent with previous scRNAseq analysis that showed a cluster of ACs identified by their expression of Gbx2 lacked expression of Slc6a9 or Gad1/2 (Macosko et al, 2015;Yan et al, 2020). When we examined other neurotransmitter markers known to be expressed in specific AC subtypes, we found little (<1%) or no co-localization with Gbx2+ ACs (Fig.…”

“…Previous studies have hinted at the presence of at least two nGnG AC subtypes (Cherry et al, 2009;Macosko et al, 2015;Yan et al, 2020). One nGnG AC subtype is defined by expression of the transcription factor NeuroD6 (Kay et al, 2011).…”

“…Amacrine cells (ACs) exhibit the greatest diversity in number and variance between subtypes. Morphological analysis of ACs predicts there are ~45 AC subtypes (MacNeil et al, 1999;Badea & Nathans, 2004;Lin & Masland, 2006;Helmstaedter et al, 2013) while recent single cell transcriptomic analysis predicts more than 60 distinct AC types (Peng et al, 2019;Yan et al, 2020). The data from these scRNAseq studies can provide potential markers for identifying neuronal subtypes in mouse (Macosko et al, 2015;Shekhar et al, 2016;Rheaume et al, 2018;Tran et al, 2019) and primate retinas (Peng et al, 2019).…”

System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina

“…To be able to compare the learned connectivity structure, which is represented by the different weight matrices W , with the connectivity structure found in electronmicroscopy data, we took the number of ACs from [14] (45 ACs in total) and matched the ratio of local to global ACs to the ones identified in [3]…”

“…shaped by a complex network of more than 45 different types of mostly inhibitory amacrine cells (ACs) [1,2,3] and passed on to the retinal ganglion cells (RGCs), which in turn transmit the signals to visual areas in the brain. Already at the level of BCs, different parallel pathways emerge, which are tuned for specific features of the stimulus.…”