Evidence map›Paper›PMID 32952937›Full record

ReviewComputational and structural biotechnology journal2020

Designing custom CRISPR libraries for hypothesis-driven drug target discovery.

Vaishnavi Srinivasan Iyer, Long Jiang, Yunbing Shen, Sanjaykumar V Boddul, Sudeepta Kumar Panda, Zsolt Kasza, Bernhard Schmierer, Fredrik Wermeling

Open access · goldAbstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
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

11 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Exploring liver cancer biology through functional genetic screens.Nature reviews. Gastroenterology & hepatology · 2021
    Review
  11. A rapid CRISPR competitive assay forComputational and structural biotechnology journal · 2021
    Article
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

8 authors at 2 institutions in 2 countries.

Vaishnavi Srinivasan IyerCenter for Molecular Medicine, Division of Rheumatology, Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
Long JiangCenter for Molecular Medicine, Division of Rheumatology, Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
Yunbing ShenCenter for Molecular Medicine, Division of Rheumatology, Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
Sanjaykumar V BoddulCenter for Molecular Medicine, Division of Rheumatology, Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
Sudeepta Kumar PandaCenter for Molecular Medicine, Division of Rheumatology, Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
Zsolt KaszaCenter for Molecular Medicine, Division of Rheumatology, Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
Bernhard SchmiererHigh Throughput Genome Engineering, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
Fredrik WermelingCenter for Molecular Medicine, Division of Rheumatology, Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
Karolinska University Hospital · SEScience for Life Laboratory · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last decade Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) has been developed into a potent molecular biology tool used to rapidly modify genes or their expression in a multitude of ways. In parallel, CRISPR-based screening approaches have been developed as powerful discovery platforms for dissecting the genetic basis of cellular behavior, as well as for drug target discovery. CRISPR screens can be designed in numerous ways. Here, we give a brief background to CRISPR screens and discuss the pros and cons of different design approaches, including unbiased genome-wide screens that target all known genes, as well as hypothesis-driven custom screens in which selected subsets of genes are targeted (Fig. 1). We provide several suggestions for how a custom screen can be designed, which could broadly serve as inspiration for any experiment that includes candidate gene selection. Finally, we discuss how results from CRISPR screens could be translated into drug development, as well as future trends we foresee in the rapidly evolving CRISPR screen field.

Identifiers

PMID32952937
PMCPMC7479249
OpenAlexW3079739538

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.