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Abstract
It has long been the dream of biologists to map gene expression at the single-cell
level. With such data one might track heterogeneous cell sub-populations, and infer
regulatory relationships between genes and pathways. Recently, RNA sequencing has
achieved single-cell resolution. What is limiting is an effective way to routinely
isolate and process large numbers of individual cells for quantitative in-depth sequencing.
We have developed a high-throughput droplet-microfluidic approach for barcoding the
RNA from thousands of individual cells for subsequent analysis by next-generation
sequencing. The method shows a surprisingly low noise profile and is readily adaptable
to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing
in detail the population structure and the heterogeneous onset of differentiation
after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput
single-cell data allowed us to deconstruct cell populations and infer gene expression
relationships. VIDEO ABSTRACT.