Evidence map›Paper›PMID 36135925›Full record

ArticleeLife2022

Fitness effects of CRISPR endonucleases in

Anna M Langmüller, Jackson Champer, Sandra Lapinska, Lin Xie, Matthew Metzloff, Samuel E Champer, Jingxian Liu, Yineng Xu, Jie Du, Andrew G Clark and 1 more

Abstract read
In one paragraph

Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Predicting the invasiveness of threshold-dependent gene drives.bioRxiv : the preprint server for biology · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. eLife · 2022
    Article
  11. Article
  12. Article
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Anna M Langmüller *Department of Computational Biology, Cornell University, Ithaca, United States.ORCID 0000-0002-6102-8862
Jackson Champer *Department of Computational Biology, Cornell University, Ithaca, United States.ORCID 0000-0002-3814-3774
Sandra LapinskaDepartment of Computational Biology, Cornell University, Ithaca, United States.
Lin XieDepartment of Computational Biology, Cornell University, Ithaca, United States.
Matthew MetzloffDepartment of Computational Biology, Cornell University, Ithaca, United States.ORCID 0000-0002-6108-5031
Samuel E ChamperDepartment of Computational Biology, Cornell University, Ithaca, United States.ORCID 0000-0002-4559-7627
Jingxian LiuDepartment of Computational Biology, Cornell University, Ithaca, United States.ORCID 0000-0002-2172-3297
Yineng XuDepartment of Computational Biology, Cornell University, Ithaca, United States.ORCID 0000-0002-4473-4052
Jie DuCenter for Bioinformatics, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
Andrew G ClarkDepartment of Computational Biology, Cornell University, Ithaca, United States.
Philipp W MesserDepartment of Computational Biology, Cornell University, Ithaca, United States.ORCID 0000-0001-8453-9377

Funding

Evolutionary dynamics of CRISPR gene drives in natural populationsR01GM127418 · NIGMS · CORNELL UNIVERSITY · PI MESSER, PHILIPP W · 2018 to 2022
$1.6M
Improving the efficiency and control of CRISPR/Cas9 gene drive systemsR21AI130635 · NIAID · CORNELL UNIVERSITY · PI CLARK, ANDREW G, MESSER, PHILIPP W · 2017 to 2018
$431k
Dynamics of Gene Drives in Natural PopulationsF32AI138476 · NIAID · CORNELL UNIVERSITY · PI CHAMPER, JACKSON · 2018 to 2020
$192k
NIAID NIH HHS F32 AI138476NIGMS NIH HHS R01 GM127418
6 · The paper itself

Abstract

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 provides a highly efficient and flexible genome editing technology with numerous potential applications ranging from gene therapy to population control. Some proposed applications involve the integration of CRISPR/Cas9 endonucleases into an organism's genome, which raises questions about potentially harmful effects to the transgenic individuals. One example for which this is particularly relevant are CRISPR-based gene drives conceived for the genetic alteration of entire populations. The performance of such drives can strongly depend on fitness costs experienced by drive carriers, yet relatively little is known about the magnitude and causes of these costs. Here, we assess the fitness effects of genomic CRISPR/Cas9 expression in

Indexed as

EndonucleasesGene Drive TechnologyAnimalsAnimals, Genetically ModifiedCRISPR-Associated Protein 9CRISPR-Cas SystemsDrosophila melanogasterGene EditingRNA, Guide, CRISPR-Cas SystemsCRISPR-Associated Protein 9EndonucleasesRNA, Guide, CRISPR-Cas SystemsCRISPRD. melanogasterevolutionary biologyfitnessgene drivegeneticsgenomicsoff-target effects

Identifiers

PMID36135925
PMCPMC9545523

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.