The mammalian brain is composed of various cell populations that differ based on their molecular, morphological, electrophysiological and functional characteristics. Classifying these cells into types is one of the essential approaches to defining the diversity of brain’s building blocks.
We created a cellular taxonomy of the mouse primary visual cortex by analyzing gene expression patterns, at the single cell level, of >1600 cells. Using transgenic mice, we isolated fluorescently labeled cells from their brains and then sequenced the transcriptomes of individual cells. To identify the different cell types, we employed an iterative unbiased classification method (cluster analysis) that examined all expressed genes and was blind to the origin of cells.
In the first iteration of our cluster analysis, two major cell types present themselves: neuronal and non-neuronal cells.
The non-neuronal cells further segregate into endothelial cell types (in pinkish gray shades), and several glial types (e.g., microglia, astrocytes, oligodendrocyte precursor cells (OPCs) and oligodendrocytes, in gray shades).
The neuronal cells segregate into two major types: the excitatory neurons (in the cooler green and blue colors) and the inhibitory neurons (in the warmer, orange and pink colors).
Most inhibitory neurons segregate into four major clusters in agreement with specific molecular markers: parvalbumin (Pvalb), somatostatin (Sst), vasoactive intestinal polypeptide (Vip) and neuron-derived neurotrophic factor (Ndnf). Each of these major cell types further segregates into subtypes.
Excitatory neurons segregate into types that correspond to cortical layers. In each layer, cell types further segregate into subtypes.
Finally, the analysis of >1600 single cell transcriptomes from the primary visual
area yields 49 transcriptionally defined cell types in a completely data-driven way.
Additional analysis reveals that some cells have mixed identity as their gene expression
falls between two or more clusters. We assign them a primary identity, but label them as
‘transitional’ cells (white in this view ) to distinguish
them from the ‘core’ cells, which firmly belong to only one cluster.
We can also portray the data in a graphical format that allows you to explore gene expression in the cell types, as well as the transgenic lines and cortical layers.
This view of the data shows the transcriptionally defined cell types along the x-axis and the transgenic lines and dissected layer(s) along the y-axis.
The transgenic mouse lines from which the cells were dissected are denoted here
The dissected regions of the primary visual cortex from which the cells were obtained are represented here
Each colored disc in the grid represents the percentage of cells of a particular cell type within the specific transgenic line and dissection combination.
This dataset is yours to explore:
You can select a specific cell type (or several types) by clicking on the x-axis or an individual transgenic line/dissection combination by clicking on the y-axis.
You can start with one of our suggested gene sets that are best for distinguishing cell types. Alternatively, you can simply enter a gene by typing its symbol in the text box, or you can paste an entire list of gene symbols from a text file or spreadsheet.
To explore this dataset further, you can also download it for offline use. Ready to explore?