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Ye, Chaoyang; Ho, Daniel J.; Neri, Marilisa; Yang, Chian; Kulkarni, Tripti; Randhawa, Ranjit; Henault, Martin; Mostacci, Nadezda; Farmer, Pierre; Renner, Steffen; Ihry, Robert; Mansur, Leandra; Keller, Caroline Gubser; McAllister, Gregory; Hild, Marc; Jenkins, Jeremy; Kaykas, Ajamete

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

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  • Medientyp: E-Artikel
  • Titel: DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery
  • Beteiligte: Ye, Chaoyang; Ho, Daniel J.; Neri, Marilisa; Yang, Chian; Kulkarni, Tripti; Randhawa, Ranjit; Henault, Martin; Mostacci, Nadezda; Farmer, Pierre; Renner, Steffen; Ihry, Robert; Mansur, Leandra; Keller, Caroline Gubser; McAllister, Gregory; Hild, Marc; Jenkins, Jeremy; Kaykas, Ajamete
  • Erschienen: Springer Science and Business Media LLC, 2018
  • Erschienen in: Nature Communications
  • Sprache: Englisch
  • DOI: 10.1038/s41467-018-06500-x
  • ISSN: 2041-1723
  • Schlagwörter: General Physics and Astronomy ; General Biochemistry, Genetics and Molecular Biology ; General Chemistry ; Multidisciplinary
  • Entstehung:
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  • Beschreibung: <jats:title>Abstract</jats:title><jats:p>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 1/100<jats:sup>th</jats:sup> 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.</jats:p>
  • Zugangsstatus: Freier Zugang