Global brain analyses at cellular resolution using massively high-throughput single cell transcriptomics

Understanding how brains vary across species or during disease necessitates defining and comparing cell types, the building blocks of neural circuits. Single-cell measurements of gene expression take advantage of the fact that cellular specialization is controlled transcriptionally, allowing an unbiased picture of intra- and inter-cell type variation. Due to the experimental noise, analyses with only hundreds or even thousands of measurements can be hard to interpret. Here we apply a system developed in our lab for massively high-throughput single-cell transcriptomics („Drop-seq“) to mouse and marmoset brains. Our first project has generated an atlas of cellular variation from the adult mice. This dataset consists of >750K single-cell transcriptomes from n=9 different brain regions. We illustrate this single-cell approach by comparing 28K interneurons and describe our ongoing efforts to compare brains across species and throughout development.