Retinal neurons have evolved spatial topographies that facilitate information processing, which in many species, results in gross specializations like foveas, area centralis, and streaks1,2,3. In contrast to the well-understood diversity of photoreceptor distribution, spatial specialization of retinal output, formed by Retinal Ganglion Cells (RGCs), is less clear. For most species, the RGCs' spatial distributions are entirely unknown. Even for the mouse, arguably one if not the best-studied vertebrate model of visual function, less than a third of RGC subtypes have been mapped with traditional techniques like whole mount immunohistochemistry2. These techniques fail because most RGC subtypes do not have a specific genetic marker. Instead, higher-dimensional molecular information is needed for accurate RGC classification4 via single-cell RNA sequencing5,6,7.
Information about RGC distribution is important, as the topographies observed in the mouse demonstrate clear ecological correlates between RGC placement and visual function. The most striking example is the spatial organization of the ɑON-S RGCs, which cluster in the temporal retina. This region receives the image of the prey8 during hunting behaviors9. It is also well appreciated that RGC subtypes are differentially susceptible to disease10, and some common diseases like glaucoma have a spatial component to their progression11,12. Thus, an important question facing the field is: what is the spatial organization of RGC subtypes as they tile the retina1? This gap in knowledge is currently limiting insights into other visually guided behaviors and diseases.
The focus of the present method is to address these molecular knowledge gaps through an en face cryosectioning approach that preserves spatial relationships while enabling high-resolution molecular analysis. Modern spatial sequencing platforms like 10X's Xenium represent a transformative advancement in molecular profiling, offering unprecedented insights into tissue organization and cellular interactions. However, these platforms, along with lower-plex techniques like RNAscope and spatially barcoded sequencing methods like Visium, share a critical technical constraint: they require tissue sections thinner than 20 µm. This requirement presents a particular challenge for retinal tissue, which typically measures 200 µm in thickness.
To date, researchers have primarily relied on cross sections when applying these technologies to retinal tissue13. While cross sections effectively reveal molecular relationships within nuclear and plexiform layers in the context of vertical circuits, they are less suited to capturing the broader spatial distributions of retinal cells that whole mount preparations have traditionally revealed8. Recent attempts at en face sectioning have been limited by section thickness constraints, with studies achieving only 50 µm sections14-too thick for modern high-plex molecular analysis platforms. Other historical approaches that have been deployed to study individual retinal lamina but are not compatible with modern spatial sequencing techniques include enzymatic digestion, combined with mechanical dissociation15,16, or mechanical dissociations alone17,18,19,20. Here, we present a novel cryosectioning technique specifically designed for thin, curved retinal tissue that overcomes these limitations. Briefly, our method involves extracting the posterior chamber of the eye, creating relief cuts through both the retina and sclera, flattening the tissue with inner retina against a coverglass, embedding the tissue in OCT, and finally, cryosectioning from outer to inner retina (Figure 1). Our method maintains spatial relationships while producing sections thin enough (<20 µm) for high-dimensional spatial biology tools, as validated through successful implementation with both manual RNAscope (12 targets) and the automated Xenium platform (300 targets), demonstrating compatibility across different complexity scales of molecular analysis.