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Expanding Single-Cell RNA-Sequencing in Scale and Dimension

Abstract

Multicellular organisms rely on diverse cell types to carry out the multitude of tasks necessary

for complex life. Understanding the interplay between cell populations within a tissue

or organism is a major goal of biological and medical research. In pursuit of this aim, recent

advances in micro

uidics and molecular biology have propelled single-cell RNA-sequencing

(scRNA-seq) to the forefront of cell population analysis. Routine scRNA-seq experiments

can prole tens of thousands of genes from tens of thousands of cells in parallel, oering a

platform ripe for technological development, a sandbox in which a clever molecular biologist

may develop more varied experiments at unprecedented scale and depth. Accordingly, we

have made signicant inroads toward the goals of simultaneous RNA/epitope quantication

and ultra-low-cost library preparation, and we have expanded the capacity of scRNA-seq

with a novel sample multiplexing method. We demonstrate the power of parallel cell population

analysis with a high-resolution screen of experimental perturbations, introducing a

new paradigm in which scRNA-seq is used to understand a cell population at multiple scales

with unprecedented depth of information.

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