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Worm Perturb-Seq: massively parallel whole-animal RNAi and RNA-seq

Author

Listed:
  • Hefei Zhang

    (University of Massachusetts Chan Medical School)

  • Xuhang Li

    (University of Massachusetts Chan Medical School)

  • Dongyuan Song

    (University of California
    University of Connecticut Health Center)

  • Onur Yukselen

    (Via Scientific Inc.)

  • Shivani Nanda

    (University of Massachusetts Chan Medical School
    Harvard Medical School)

  • Alper Kucukural

    (Via Scientific Inc.
    University of Massachusetts Chan Medical School)

  • Jingyi Jessica Li

    (University of California
    University of California)

  • Manuel Garber

    (University of Massachusetts Chan Medical School)

  • Albertha J. M. Walhout

    (University of Massachusetts Chan Medical School)

Abstract

Transcriptomes provide highly informative molecular phenotypes that, combined with gene perturbation, can connect genotype to phenotype. An ultimate goal is to perturb every gene and measure transcriptome changes, however, this is challenging, especially in whole animals. Here, we present ‘Worm Perturb-Seq (WPS)’, a method that provides high-resolution RNA-sequencing profiles for hundreds of replicate perturbations at a time in living animals. WPS introduces multiple experimental advances combining strengths of Caenhorhabditis elegans genetics and multiplexed RNA-sequencing with a novel analytical framework, EmpirDE. EmpirDE leverages the unique power of large transcriptomic datasets and improves statistical rigor by using gene-specific empirical null distributions to identify DEGs. We apply WPS to 103 nuclear hormone receptors (NHRs) and find a striking ‘pairwise modularity’ in which pairs of NHRs regulate shared target genes. We envision the advances of WPS to be useful not only for C. elegans, but broadly for other models, including human cells.

Suggested Citation

  • Hefei Zhang & Xuhang Li & Dongyuan Song & Onur Yukselen & Shivani Nanda & Alper Kucukural & Jingyi Jessica Li & Manuel Garber & Albertha J. M. Walhout, 2025. "Worm Perturb-Seq: massively parallel whole-animal RNAi and RNA-seq," Nature Communications, Nature, vol. 16(1), pages 1-21, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-60154-0
    DOI: 10.1038/s41467-025-60154-0
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    References listed on IDEAS

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    1. Xuhang Li & Hefei Zhang & Thomas Hodder & Wen Wang & Chad L. Myers & L. Safak Yilmaz & Albertha J. M. Walhout, 2025. "Systems-level design principles of metabolic rewiring in an animal," Nature, Nature, vol. 640(8057), pages 203-211, April.
    2. Efron, Bradley, 2004. "Large-Scale Simultaneous Hypothesis Testing: The Choice of a Null Hypothesis," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 96-104, January.
    3. Ravi S. Kamath & Andrew G. Fraser & Yan Dong & Gino Poulin & Richard Durbin & Monica Gotta & Alexander Kanapin & Nathalie Le Bot & Sergio Moreno & Marc Sohrmann & David P. Welchman & Peder Zipperlen &, 2003. "Systematic functional analysis of the Caenorhabditis elegans genome using RNAi," Nature, Nature, vol. 421(6920), pages 231-237, January.
    4. Antonio J. Santinha & Esther Klingler & Maria Kuhn & Rick Farouni & Sandra Lagler & Georgios Kalamakis & Ulrike Lischetti & Denis Jabaudon & Randall J. Platt, 2023. "Transcriptional linkage analysis with in vivo AAV-Perturb-seq," Nature, Nature, vol. 622(7982), pages 367-375, October.
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