Evidence map›Paper›PMID 37291233›Full record

ArticleCommunications biology2023

acCRISPR: an activity-correction method for improving the accuracy of CRISPR screens.

Adithya Ramesh, Varun Trivedi, Sangcheon Lee, Aida Tafrishi, Cory Schwartz, Amirsadra Mohseni, Mengwan Li, Stefano Lonardi, Ian Wheeldon

Abstract read
In one paragraph

Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Analyzing CRISPR screens in non-conventional microbes.Journal of industrial microbiology & biotechnology · 2023
    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

9 authors.

Adithya Ramesh *Department of Chemical and Environmental Engineering, University of California, Riverside, CA, 92521, USA.
Varun Trivedi *Department of Chemical and Environmental Engineering, University of California, Riverside, CA, 92521, USA.ORCID 0000-0002-3525-6300
Sangcheon Lee *Department of Chemical and Environmental Engineering, University of California, Riverside, CA, 92521, USA.
Aida TafrishiDepartment of Chemical and Environmental Engineering, University of California, Riverside, CA, 92521, USA.
Cory SchwartzDepartment of Chemical and Environmental Engineering, University of California, Riverside, CA, 92521, USA.
Amirsadra MohseniDepartment of Computer Science and Engineering, University of California, Riverside, CA, 92521, USA.ORCID 0000-0003-0735-6846
Mengwan LiDepartment of Chemical and Environmental Engineering, University of California, Riverside, CA, 92521, USA.
Stefano LonardiDepartment of Computer Science and Engineering, University of California, Riverside, CA, 92521, USA.ORCID 0000-0002-2696-7274
Ian WheeldonDepartment of Chemical and Environmental Engineering, University of California, Riverside, CA, 92521, USA. wheeldon@ucr.edu.ORCID 0000-0002-3492-7539

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High throughput CRISPR screens are revolutionizing the way scientists unravel the genetic underpinnings of engineered and evolved phenotypes. One of the critical challenges in accurately assessing screening outcomes is accounting for the variability in sgRNA cutting efficiency. Poorly active guides targeting genes essential to screening conditions obscure the growth defects that are expected from disrupting them. Here, we develop acCRISPR, an end-to-end pipeline that identifies essential genes in pooled CRISPR screens using sgRNA read counts obtained from next-generation sequencing. acCRISPR uses experimentally determined cutting efficiencies for each guide in the library to provide an activity correction to the screening outcomes via calculation of an optimization metric, thus determining the fitness effect of disrupted genes. CRISPR-Cas9 and -Cas12a screens were carried out in the non-conventional oleaginous yeast Yarrowia lipolytica and acCRISPR was used to determine a high-confidence set of essential genes for growth under glucose, a common carbon source used for the industrial production of oleochemicals. acCRISPR was also used in screens quantifying relative cellular fitness under high salt conditions to identify genes that were related to salt tolerance. Collectively, this work presents an experimental-computational framework for CRISPR-based functional genomics studies that may be expanded to other non-conventional organisms of interest.

Indexed as

CRISPR-Cas SystemsYarrowiaGene LibraryGenes, EssentialGenomics

Identifiers

PMID37291233
PMCPMC10250353

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.