IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v9y2018i1d10.1038_s41467-018-06500-x.html
   My bibliography  Save this article

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

Author

Listed:
  • Chaoyang Ye

    (Novartis Institutes for Biomedical Research
    Blueprint Medicines)

  • Daniel J. Ho

    (Novartis Institutes for Biomedical Research)

  • Marilisa Neri

    (Novartis Institutes for Biomedical Research)

  • Chian Yang

    (Novartis Institutes for Biomedical Research)

  • Tripti Kulkarni

    (Novartis Institutes for Biomedical Research)

  • Ranjit Randhawa

    (Novartis Institutes for Biomedical Research)

  • Martin Henault

    (Novartis Institutes for Biomedical Research)

  • Nadezda Mostacci

    (Novartis Institutes for Biomedical Research)

  • Pierre Farmer

    (Novartis Institutes for Biomedical Research)

  • Steffen Renner

    (Novartis Institutes for Biomedical Research)

  • Robert Ihry

    (Novartis Institutes for Biomedical Research)

  • Leandra Mansur

    (Novartis Institutes for Biomedical Research)

  • Caroline Gubser Keller

    (Novartis Institutes for Biomedical Research)

  • Gregory McAllister

    (Novartis Institutes for Biomedical Research)

  • Marc Hild

    (Novartis Institutes for Biomedical Research)

  • Jeremy Jenkins

    (Novartis Institutes for Biomedical Research)

  • Ajamete Kaykas

    (Novartis Institutes for Biomedical Research)

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.

Suggested Citation

  • Chaoyang Ye & Daniel J. Ho & Marilisa Neri & Chian Yang & Tripti Kulkarni & Ranjit Randhawa & Martin Henault & Nadezda Mostacci & Pierre Farmer & Steffen Renner & Robert Ihry & Leandra Mansur & Caroli, 2018. "DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-06500-x
    DOI: 10.1038/s41467-018-06500-x
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-018-06500-x
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-018-06500-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-06500-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.