Evan Z. Macosko

TL;DR: Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together.

TL;DR: Drop-seq as discussed by the authors analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin, and identifies 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes.

TL;DR: Slide-seq provides a scalable method for obtaining spatially resolved gene expression data at resolutions comparable to the sizes of individual cells, and defines the temporal evolution of cell type–specific responses in a mouse model of traumatic brain injury.

TL;DR: The analysis of RNA expression patterns of more than 76,000 individual microglia in mice during development, in old age, and after brain injury uncovered at least nine transcriptionally distinct microglial states, which expressed unique sets of genes and were localized in the brain using specific markers.

TL;DR: Features of brain organization are revealed, including a gene-expression module for synthesizing axonal and presynaptic components, patterns in the co-deployment of voltage-gated ion channels, functional distinctions among the cells of the vasculature and specialization of glutamatergic neurons across cortical regions.