DANGER analysis: risk-averse on/off-target assessment for CRISPR editing without a reference genome

Kazuki Nakamae; Hidemasa Bono

doi:10.1093/bioadv/vbad114

DANGER analysis: risk-averse on/off-target assessment for CRISPR editing without a reference genome

Bioinform Adv. 2023 Aug 23;3(1):vbad114. doi: 10.1093/bioadv/vbad114. eCollection 2023.

Authors

Kazuki Nakamae^{1

2}, Hidemasa Bono^{1

3}

Affiliations

¹ Laboratory of Bio-DX, Genome Editing Innovation Center, Hiroshima University, 3-10-23 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-0046, Japan.
² Research and Development Department, PtBio Inc., 3-10-23 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-0046, Japan.
³ Laboratory of Genome Informatics, Graduate School of Integrated Sciences for Life, Hiroshima University, 3-10-23 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-0046, Japan.

Abstract

Motivation: The CRISPR-Cas9 system has successfully achieved site-specific gene editing in organisms ranging from humans to bacteria. The technology efficiently generates mutants, allowing for phenotypic analysis of the on-target gene. However, some conventional studies did not investigate whether deleterious off-target effects partially affect the phenotype.

Results: Herein, we present a novel phenotypic assessment of CRISPR-mediated gene editing: Deleterious and ANticipatable Guides Evaluated by RNA-sequencing (DANGER) analysis. Using RNA-seq data, this bioinformatics pipeline can elucidate genomic on/off-target sites on mRNA-transcribed regions related to expression changes and then quantify phenotypic risk at the gene ontology term level. We demonstrated the risk-averse on/off-target assessment in RNA-seq data from gene-edited samples of human cells and zebrafish brains. Our DANGER analysis successfully detected off-target sites, and it quantitatively evaluated the potential contribution of deleterious off-targets to the transcriptome phenotypes of the edited mutants. Notably, DANGER analysis harnessed de novo transcriptome assembly to perform risk-averse on/off-target assessments without a reference genome. Thus, our resources would help assess genome editing in non-model organisms, individual human genomes, and atypical genomes from diseases and viruses. In conclusion, DANGER analysis facilitates the safer design of genome editing in all organisms with a transcriptome.

Availability and implementation: The Script for the DANGER analysis pipeline is available at https://github.com/KazukiNakamae/DANGER_analysis. In addition, the software provides a tutorial on reproducing the results presented in this article on the Readme page. The Docker image of DANGER_analysis is also available at https://hub.docker.com/repository/docker/kazukinakamae/dangeranalysis/general.