RT Journal Article
SR Electronic
T1 Multiplexed single-cell profiling of post-perturbation transcriptional responses to define cancer vulnerabilities and therapeutic mechanism of action
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 868752
DO 10.1101/868752
A1 James M. McFarland
A1 Brenton R. Paolella
A1 Allison Warren
A1 Kathryn Geiger-Schuller
A1 Tsukasa Shibue
A1 Michael Rothberg
A1 Olena Kuksenko
A1 Andrew Jones
A1 Emily Chambers
A1 Danielle Dionne
A1 Samantha Bender
A1 Brian M. Wolpin
A1 Mahmoud Ghandi
A1 Itay Tirosh
A1 Orit Rozenblatt-Rosen
A1 Jennifer A. Roth
A1 Todd R. Golub
A1 Aviv Regev
A1 Andrew J. Aguirre
A1 Francisca Vazquez
A1 Aviad Tsherniak
YR 2019
UL http://biorxiv.org/content/early/2019/12/08/868752.abstract
AB Assays to study cancer cell responses to pharmacologic or genetic perturbations are typically restricted to using simple phenotypic readouts such as proliferation rate or the expression of a marker gene. Information-rich assays, such as gene-expression profiling, are generally not amenable to efficient profiling of a given perturbation across multiple cellular contexts. Here, we developed MIX-Seq, a method for multiplexed transcriptional profiling of post-perturbation responses across a mixture of samples with single-cell resolution, using SNP-based computational demultiplexing of single-cell RNA-sequencing data. We show that MIX-Seq can be used to profile responses to chemical or genetic perturbations across pools of 100 or more cancer cell lines, and combine it with Cell Hashing to further multiplex additional experimental conditions, such as multiple post-treatment time points or drug doses. Analyzing the high-content readout of scRNA-seq reveals both shared and context-specific transcriptional response components that can identify drug mechanism of action and can be used to predict long-term cell viability from short-term transcriptional responses to treatment.