@article {Datlinger2019.12.17.879304, author = {Paul Datlinger and Andr{\'e} F Rendeiro and Thorina Boenke and Thomas Krausgruber and Daniele Barreca and Christoph Bock}, title = {Ultra-high throughput single-cell RNA sequencing by combinatorial fluidic indexing}, elocation-id = {2019.12.17.879304}, year = {2019}, doi = {10.1101/2019.12.17.879304}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Cell atlas projects and single-cell CRISPR screens hit the limits of current technology, as they require cost-effective profiling for millions of individual cells. To satisfy these enormous throughput requirements, we developed {\textquotedblleft}single-cell combinatorial fluidic indexing{\textquotedblright} (scifi) and applied it to single-cell RNA sequencing. The resulting scifi-RNA-seq assay combines one-step combinatorial pre-indexing of single-cell transcriptomes with subsequent single-cell RNA-seq using widely available droplet microfluidics. Pre-indexing allows us to load multiple cells per droplet, which increases the throughput of droplet-based single-cell RNA-seq up to 15-fold, and it provides a straightforward way of multiplexing hundreds of samples in a single scifi-RNA-seq experiment. Compared to multi-round combinatorial indexing, scifi-RNA-seq provides an easier, faster, and more efficient workflow, thereby enabling massive-scale scRNA-seq experiments for a broad range of applications ranging from population genomics to drug screens with scRNA-seq readout. We benchmarked scifi-RNA-seq on various human and mouse cell lines, and we demonstrated its feasibility for human primary material by profiling TCR activation in T cells.}, URL = {https://www.biorxiv.org/content/early/2019/12/18/2019.12.17.879304}, eprint = {https://www.biorxiv.org/content/early/2019/12/18/2019.12.17.879304.full.pdf}, journal = {bioRxiv} }