Literature DB >> 31021199

Impact of Genetic Variation on CRISPR-Cas Targeting.

Matthew C Canver1,2, J Keith Joung1,2, Luca Pinello1,2.   

Abstract

The CRISPR-CRISPR-associated (Cas) nuclease system offers the ability to perform unprecedented functional genetic experiments and the promise of therapy for a variety of genetic disorders. The understanding of factors contributing to CRISPR targeting efficacy and specificity continues to evolve. As CRISPR systems rely on Watson-Crick base pairing to ultimately mediate genomic cleavage, it logically follows that genetic variation would affect CRISPR targeting by increasing or decreasing sequence homology at on-target and off-target sites or by altering protospacer adjacent motifs. Numerous efforts have been made to document the extent of human genetic variation, which can serve as resources to understand and mitigate the effect of genetic variation on CRISPR targeting. Here, we review efforts to elucidate the effect of human genetic variation on CRISPR targeting at on-target and off-target sites with considerations for laboratory experiments and clinical translation of CRISPR-based therapies.

Entities:  

Year:  2018        PMID: 31021199      PMCID: PMC6319324          DOI: 10.1089/crispr.2017.0016

Source DB:  PubMed          Journal:  CRISPR J        ISSN: 2573-1599


  5 in total

1.  CRISPRitz: rapid, high-throughput and variant-aware in silico off-target site identification for CRISPR genome editing.

Authors:  Samuele Cancellieri; Matthew C Canver; Nicola Bombieri; Rosalba Giugno; Luca Pinello
Journal:  Bioinformatics       Date:  2020-04-01       Impact factor: 6.937

Review 2.  Technologies and Computational Analysis Strategies for CRISPR Applications.

Authors:  Kendell Clement; Jonathan Y Hsu; Matthew C Canver; J Keith Joung; Luca Pinello
Journal:  Mol Cell       Date:  2020-07-02       Impact factor: 17.970

Review 3.  Challenges and Strategies in Ascribing Functions to Long Noncoding RNAs.

Authors:  Yang Zhao; Hongqi Teng; Fan Yao; Shannon Yap; Yutong Sun; Li Ma
Journal:  Cancers (Basel)       Date:  2020-06-03       Impact factor: 6.639

4.  VARSCOT: variant-aware detection and scoring enables sensitive and personalized off-target detection for CRISPR-Cas9.

Authors:  Laurence O W Wilson; Sara Hetzel; Christopher Pockrandt; Knut Reinert; Denis C Bauer
Journal:  BMC Biotechnol       Date:  2019-06-27       Impact factor: 2.563

Review 5.  Computational Tools and Resources Supporting CRISPR-Cas Experiments.

Authors:  Pawel Sledzinski; Mateusz Nowaczyk; Marta Olejniczak
Journal:  Cells       Date:  2020-05-22       Impact factor: 6.600

  5 in total

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