Droplet barcoding for single cell transcriptomics applied to embryonic stem cells

By Allon M. Klein, L. Mazutis, Ilke Akartuna, Naren P. Tallapragada, A. Veres, V. Li, Leonid Peshkin, David A. Weitz, Marc Kirschner. Cell, 2015

3,144 citations recorded by the source corpus.

Summary 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 LIF withdrawal. The reproducibility of these high-throughput single cell data allowed us to deconstruct cell populations and infer gene expression relationships.

Subfields: Biomedical Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/86b9f94094ca16831814ef36c4e46190ed512661

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Citations in the corpus

Mapping the Mouse Cell Atlas by Microwell-Seq. (2018, methodology): “To establish a cost-effective single-cell technology that is widely accessible, we combined the advantages of existing methodologies (Fan et al., 2015; Klein et al., 2015; Macosko et al., 2015) in designing the Microwell-seq method.”
Splatter: simulation of single-cell RNA sequencing data (2017, background): “Klein [46] Human K562 cells InDrop CEL-Seq Yes 213”
Gene co-expression analysis for functional classification and gene–disease predictions (2017, methodology): “This is particularly useful when such information is not available, as can be the case for large-scale single-cell RNA-seq experiments like those using the Drop-seq system [139] or inDrop [140].”
Integrating single-cell transcriptomic data across different conditions, technologies, and species (2018, neutral): “maxu, vu T X T Yv subject to uXXu ≤ 1, vYYv ≤ 1 (1)”
Scaling by shrinking: empowering single-cell ‘omics’ with microfluidic devices (2017, neutral): “a | InDrop, developed by Klein et al.(32), is a droplet-”
A multiplexed single-cell CRISPR screening platform enables systematic dissection of the unfolded protein response (2016, background): “Along with previous successes (Jaitin et al., 2014; Klein et al., 2015; Macosko et al., 2015), and other novel analytical approaches (Dixit et al., co-submitted manuscript), large-scale analyses of single cell behavior should enable systematic understanding of the complex regulatory programs at…”