Neuronal diversity is observed throughout the central nervous system, particularly in the vertebrate retina, a highly specialized tissue consisting of 1 glial and 6 neuronal cell types that arise from one population of retinal progenitor cells1,2,3. Many subtypes of cells can be classified functionally, morphologically, and genetically. The goal of this protocol is to tie the genetic variability of cell types to their identifiable functional and/or morphological characteristics. A number of genes have been identified for the classification of cells, but many subtypes continue to go uncharacterized, as they represent a small fraction of the overall population. The identification of genes within these specific subtypes will allow for a greater understanding of neuronal diversity within the retina and may also shed light on the diversification of neural cells elsewhere. Furthermore, single-cell studies allow for the uncovering of new cell types, which may have been overlooked due to their low representation among the overall population4,5,6,7.
One of the benefits of single-cell transcriptomics is that unique markers or combinations of markers that define a particular cellular subtype can be discovered. These can then be used to gain genetic access to that cell type for different manipulations. For example, we are using this protocol to characterize the cell type-specific genes of a subset of retinal ganglion cells that express the photopigment melanopsin. The use of a fluorescent marker in melanopsin-expressing retinal ganglion cells enables the study of these cells, as they are clustered together due to their expression of a known gene. Interestingly, there are five known subtypes of this cell population in the mouse retina8. Thus, in order to isolate RNA from cells of each type, we have used established morphological classifications within the transgenic model to identify each subtype prior to cell isolation. This technique allows for the characterization of cells as well as for their isolation directly from the retina, without the need for tissue dissociation, which may cause a stress response within cells and contamination due to severed dendrites9.
A multitude of new techniques have come to light in the past few years as the RNA-Seq method continues to develop. These tools allow for maximized cell acquisition and greater cost efficiency while approaching the question at hand4,7,10,11,12,13. However, while these techniques have been excellent stepping stones, there are a number of hurdles still encountered that this protocol is able to address. First, many of the current procedures isolate cells from dissociated tissue and attempt to use either principal component analysis or hierarchical clustering post-hoc to determine cell classification. Relying on these tools to classify subtypes may not produce reliable results and may force one to find new ways to validate this data for the correlation of a genetic marker to a functional cell type. The requirement for dissociation in other protocols can sometimes result in tissue damage and can cause neuronal processes to be severed, resulting in a potential loss of mRNA. Furthermore, in dissociated cell preparations, the stress responses may begin to affect the transcriptomes of these cells14. This protocol overcomes these challenges by determining the functional cell type prior to isolation, and it better maintains the health of the cells by keeping the retinal tissue intact.
One technique was introduced in 2014 and consisted of the in vivo analysis of the transcriptome of live cells15. While this technique allows for the examination of the transcriptome with minimal mechanical disruption to the tissue, it lacks the ability to classify specific cell types within the tissue before examining their transcriptomes without using a very specific reporter mouse. Our protocol does not require a specific reporter, as we utilize cell filling and electrophysiology to characterize cells before their isolation. Another limitation of this previous protocol is that it requires a specific wavelength to excite the photoactivatable element, whereas our protocol allows for the use of a fluorescent reporter and fluorescent dye, which are readily available or can be chosen by each lab individually. Still, other laboratories have married the two methods of electrophysiology and transcriptomics for the study of cellular diversity. The use of patch-clamp recordings to characterize the function of a cell prior to its isolation has been performed on dissociated neurons16 and, in some cases, it has preceded the use of microarray analysis17 for these studies. The same complications are encountered by those approaches, as they require tissue dissociation or the use of microarray technology, which relies on the hybridization of samples to available probes. One of the most recent advances has been the development of Patch-Seq, a technique that combines the use of patch-clamp recordings and RNA-Seq technology to understand cells from whole-brain slices18. While this technique has its similarities to the protocol presented here, it is again important to note that our approach allows the tissue to remain intact for the health of the cells. Here, we present a protocol for the optimization of this alliance, which generates high-quality, single-cell libraries for the use of RNA-Seq to obtain a high read depth and mapping coverage.