ArticleComputational and structural biotechnology journal2022
In silico performance analysis of web tools for CRISPRa sgRNA design in human genes.
Article in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
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- A Cas12a Toolbox for Rapid and Flexible Group B Streptococcus Genomic Editing and CRISPRi.Molecular microbiology · 2025Article
- A CRISPRi library screen in group BInfection and immunity · 2025Article
- Mapping variant effects on anti-tumor hallmarks of primary human T cells with base-editing screens.Nature biotechnology · 2025Article
- A CRISPRi Library Screen in Group BbioRxiv : the preprint server for biology · 2024Article
- Resf1 is a compound G4 quadruplex-associated tumor suppressor for triple negative breast cancer.PLoS genetics · 2024Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Angiogenic gene overexpression has been the main strategy in numerous vascular regenerative gene therapy projects. However, most have failed in clinical trials. CRISPRa technology enhances gene overexpression levels based on the identification of sgRNAs with maximum efficiency and safety. CRISPick and CHOP CHOP are the most widely used web tools for the prediction of sgRNAs. The objective of our study was to analyze the performance of both platforms for the sgRNA design to angiogenic genes (VEGFA, KDR, EPO, HIF-1A, HGF, FGF, PGF, FGF1) involving different human reference genomes (GRCH 37 and GRCH 38). The top 20 ranked sgRNAs proposed by the two tools were analyzed in different aspects. No significant differences were found on the DNA curvature associated with the sgRNA binding sites but the sgRNA predicted on-target efficiency was significantly greater when CRISPick was used. Moreover, the mean ranking variation was greater for the same platform in EPO, EGF, HIF-1A, PGF and HGF, whereas it did not reach statistical significance in KDR, FGF-1 and VEGFA. The rearrangement analysis of the ranking positions was also different between platforms. CRISPick proved to be more accurate in establishing the best sgRNAs in relation to a more complete genome, whereas CHOP CHOP showed a narrower classification reordering.
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