转录组
计算生物学
药物发现
RNA序列
仿形(计算机编程)
药品
基因表达谱
生物
药物靶点
计算机科学
生物信息学
基因
遗传学
基因表达
药理学
操作系统
作者
Chaoyang Ye,Daniel Ho,Marilisa Neri,Chian Yang,Tripti Kulkarni,Ranjit Randhawa,Martin Hénault,Nadezda Kryuchkova-Mostacci,Pierre Farmer,Steffen Renner,Robert J. Ihry,Leandra Mansur,Caroline Gubser Keller,Gregory McAllister,Marc Hild,Jeremy L. Jenkins,Ajamete Kaykas
标识
DOI:10.1038/s41467-018-06500-x
摘要
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.
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