Evidence map›Paper›PMID 35341983›Full record

ReviewGenomics, proteomics & bioinformatics2023

Computational Tools and Resources for CRISPR/Cas Genome Editing.

Chao Li, Wen Chu, Rafaqat Ali Gill, Shifei Sang, Yuqin Shi, Xuezhi Hu, Yuting Yang, Qamar U Zaman, Baohong Zhang

Open access · goldAbstract readReview
In one paragraph

Review in Genomics, proteomics & bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
10.1field-weighted citation impact, top 1% 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

41 citing papers in PubMed, 123 citations in OpenAlex.

  1. Establishment of CRISPR/Cas9 Genome Editing inJournal of fungi (Basel, Switzerland) · 2026
    Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Bioinformatic Identification of CRISPR-Cas Systems inPathogens (Basel, Switzerland) · 2025
    Article
  8. Rapid detection ofActa biochimica et biophysica Sinica · 2025
    Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. CRISPR-Activation: Boosting Expression of Plant MIRs.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  17. Article
  18. Review
  19. Article
  20. 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 at 2 institutions in 2 countries.

Chao LiOil Crops Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory for Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China. Electronic address: lichao01@caas.cn.
Wen ChuOil Crops Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory for Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; Graduate School of Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Rafaqat Ali GillOil Crops Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory for Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China.
Shifei SangOil Crops Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory for Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; Graduate School of Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Yuqin ShiOil Crops Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory for Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; Graduate School of Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Xuezhi HuOil Crops Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory for Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China.
Yuting YangOil Crops Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory for Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; Graduate School of Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Qamar U ZamanOil Crops Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory for Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; Graduate School of Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Baohong ZhangDepartment of Biology, East Carolina University, Greenville, NC 27858, USA. Electronic address: zhangb@ecu.edu.
Chinese Academy of Agricultural Sciences · CNEast Carolina University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The past decade has witnessed a rapid evolution in identifying more versatile clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) nucleases and their functional variants, as well as in developing precise CRISPR/Cas-derived genome editors. The programmable and robust features of the genome editors provide an effective RNA-guided platform for fundamental life science research and subsequent applications in diverse scenarios, including biomedical innovation and targeted crop improvement. One of the most essential principles is to guide alterations in genomic sequences or genes in the intended manner without undesired off-target impacts, which strongly depends on the efficiency and specificity of single guide RNA (sgRNA)-directed recognition of targeted DNA sequences. Recent advances in empirical scoring algorithms and machine learning models have facilitated sgRNA design and off-target prediction. In this review, we first briefly introduce the different features of CRISPR/Cas tools that should be taken into consideration to achieve specific purposes. Secondly, we focus on the computer-assisted tools and resources that are widely used in designing sgRNAs and analyzing CRISPR/Cas-induced on- and off-target mutations. Thirdly, we provide insights into the limitations of available computational tools that would help researchers of this field for further optimization. Lastly, we suggest a simple but effective workflow for choosing and applying web-based resources and tools for CRISPR/Cas genome editing.

Indexed as

CRISPR-Cas SystemsGene EditingGenomeGenomicsRNA, Guide, CRISPR-Cas SystemsRNA, Guide, CRISPR-Cas SystemsAlgorithmComputational toolCRISPR/Cas9Efficiency and specificityGenome editingsgRNA

Identifiers

PMID35341983
PMCPMC10372911
OpenAlexW4221055802

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.