Evidence map›Paper›PMID 39975282›Full record

ArticlebioRxiv : the preprint server for biology2025

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

Hefei Zhang, Xuhang Li, Dongyuan Song, Onur Yukselen, Shivani Nanda, Alper Kucukural, Jingyi Jessica Li, Manuel Garber, Albertha J M Walhout

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Hefei ZhangDepartment of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
Xuhang LiDepartment of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
Dongyuan SongBioinformatics Interdepartmental Ph.D. Program, University of California, Los Angeles, CA, USA.
Onur YukselenVia Scientific Inc. Cambridge, MA, USA.
Shivani NandaDepartment of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
Alper KucukuralVia Scientific Inc. Cambridge, MA, USA.ORCID 0000-0001-9983-394X
Jingyi Jessica LiBioinformatics Interdepartmental Ph.D. Program, University of California, Los Angeles, CA, USA.
Manuel GarberDepartment of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA.ORCID 0000-0001-8732-1293
Albertha J M WalhoutDepartment of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA.ORCID 0000-0001-5587-3608

Funding

Transcription networks in C elegans organogenesisR01DK068429 · NIDDK · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI A. J. Marian Walhout · 2005 to 2026
$10.9M
Gene regulatory and metabolic network structure, function and evolutionR35GM122502 · NIGMS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI A. J. Marian Walhout · 2017 to 2026
$8.3M
Predictive Modeling of the Functional and Phenotypic Impacts of Genetic VariantsU01HG012064 · NHGRI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI Manuel Garber, XIHONG LIN · 2021 to 2026
$4.0M
Statistical Methods for Elucidating Regulatory Mechanisms and Functional Impacts of Transcriptome Variation at Population and Single-Cell ScalesR35GM140888 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LI, JINGYI JESSICA · 2021 to 2025
$2.0M
Gene Regulatory Networks in Development and PhysiologyR56DK068429 · NIDDK · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI WALHOUT, A. J. MARIAN · 2018 to 2018
$671k
NHGRI NIH HHS U01 HG012064NIDDK NIH HHS R01 DK068429NIDDK NIH HHS R56 DK068429NIGMS NIH HHS R35 GM122502NIGMS NIH HHS R35 GM140888
6 · The paper itself

Abstract

The transcriptome provides a highly informative molecular phenotype to connect genotype to phenotype and is most frequently measured by RNA-sequencing (RNA-seq). Therefore, an ultimate goal is to perturb every gene and measure changes in the transcriptome. However, this remains challenging, especially in intact organisms due to different experimental and computational challenges. Here, we present 'Worm Perturb-Seq (WPS)', which provides high-resolution RNA-seq profiles for hundreds of replicate perturbations at a time in a living animal. WPS introduces multiple experimental advances that combine strengths of bulk and single cell RNA-seq, and that further provides an analytical framework, EmpirDE, that leverages the unique power of the large WPS datasets. EmpirDE identifies differentially expressed genes (DEGs) by using gene-specific empirical null distributions, rather than control conditions alone, thereby systematically removing technical biases and improving statistical rigor. We applied WPS to 103

Identifiers

PMID39975282
PMCPMC11838469

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.