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DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery

Authors :
Robert J. Ihry
Nadezda Mostacci
Gregory McAllister
Martin Henault
Caroline Gubser Keller
Jeremy L. Jenkins
Steffen Renner
Daniel J. Ho
Chaoyang Ye
Ajamete Kaykas
Marilisa Neri
Chian Yang
Leandra Mansur
Marc Hild
Tripti Kulkarni
Pierre Farmer
Ranjit Randhawa
Source :
Nature Communications, Vol 9, Iss 1, Pp 1-9 (2018), Nature Communications
Publication Year :
2018
Publisher :
Springer Science and Business Media LLC, 2018.

Abstract

Here we report Digital RNA with pertUrbation of Genes (DRUG-seq), a high-throughput platform for drug discovery. Pharmaceutical discovery relies on high-throughput screening, yet current platforms have limited readouts. RNA-seq is a powerful tool to investigate drug effects using transcriptome changes as a proxy, yet standard library construction is costly. DRUG-seq captures transcriptional changes detected in standard RNA-seq at 1/100th the cost. In proof-of-concept experiments profiling 433 compounds across 8 doses, transcription profiles generated from DRUG-seq successfully grouped compounds into functional clusters by mechanism of actions (MoAs) based on their intended targets. Perturbation differences reflected in transcriptome changes were detected for compounds engaging the same target, demonstrating the value of using DRUG-seq for understanding on and off-target activities. We demonstrate DRUG-seq captures common mechanisms, as well as differences between compound treatment and CRISPR on the same target. DRUG-seq provides a powerful tool for comprehensive transcriptome readout in a high-throughput screening environment.<br />RNA-seq is a powerful tool to investigate how drugs affect the transcriptome but library construction can be costly. Here the authors introduce DRUG-seq, an automated platform for high-throughput transcriptome profiling.

Details

ISSN :
20411723
Volume :
9
Database :
OpenAIRE
Journal :
Nature Communications
Accession number :
edsair.doi.dedup.....d9089b74819c1f0e0dfaf422f38c70de
Full Text :
https://doi.org/10.1038/s41467-018-06500-x