Researchers have recently developed a software tool called DANGER (Deleterious and ANticipatable Guides Evaluated by RNA-sequencing) analysis, which provides a safer approach to designing genome editing in organisms with a transcriptome. For the past decade, the CRISPR technology has been widely used for genome editing. However, there are certain challenges associated with its use. The DANGER analysis overcomes these challenges and enables researchers to perform on- and off-target assessments more safely, even without a reference genome. This breakthrough has significant implications for the fields of medicine, agriculture, and biological research.
The findings of this research have been published in the journal Bioinformatics Advances on August 23, 2023.
Genome editing, or gene editing, involves technologies that allow researchers to modify the genomic DNA of an organism. With these technologies, it becomes possible to add, remove, or alter genetic material within the genome.
Among the various gene editing technologies available, CRISPR-Cas9 is particularly well-known. It is renowned for its accuracy, speed, and cost-effectiveness compared to other similar technologies. However, gene editing using CRISPR technology comes with its own set of challenges. One such challenge is the lack of quantitative monitoring of the phenotypic effects caused by unexpected CRISPR dynamics.
Another challenge lies in the fact that CRISPR technology heavily relies on basic genomic data, including the reference genome, which serves as a template for general information about the genome. However, unexpected sequence editing with mismatches can occur, generating off-target sites that are often unpredicted. Therefore, researchers need a way to observe actual genomic sequences and minimize potential off-target effects.
In order to address the challenges of phenotypic effects and the reliance on a reference genome, the research team developed the DANGER analysis software. This software allows for a more accurate assessment of on- and off-target effects. The team conducted risk-averse on- and off-target assessments using RNA-sequencing data obtained from gene-edited samples of human cells and zebrafish brains.
The DANGER analysis pipeline offers several key advantages. It detects potential DNA on- and off-target sites within the mRNA-transcribed region of the genome using RNA-sequencing data. It evaluates phenotypic effects by analyzing deleterious off-target sites through changes in gene expression. Furthermore, it quantifies the phenotypic risk at the level of gene ontology terms, all without the need for a reference genome. The success of this approach demonstrates the potential of DANGER analysis for use in various organisms, personalized human genomes, as well as genomes altered by diseases and viruses.
The DANGER analysis pipeline identifies genomic on- and off-target sites through de novo transcriptome assembly using RNA-sequencing data. Transcriptome assembly involves the compilation of all active gene readouts in a cell without relying on a reference genome. The DANGER analysis then identifies deleterious off-targets, which are off-targets within the mRNA-transcribed regions that lead to a downregulation of gene expression in edited samples compared to wild-type samples. Finally, the software quantifies the phenotypic risk based on the gene ontology of these deleterious off-targets.
According to Hidemasa Bono, a professor at the Genome Editing Innovation Center at Hiroshima University, “Our DANGER analysis is a novel software that enables quantifying phenotypic effects caused by estimated off-target. Furthermore, our tool uses de novo transcriptome assembly whose sequences can be built from RNA-sequencing data of treated samples without a reference genome.”
Moving forward, the research team intends to expand their research using the DANGER analysis. They plan to apply the software to a variety of genome editing samples, including those from patients and crops, in order to gain a better understanding of the phenotypic effects and establish safer strategies for genome editing.
The DANGER analysis is an open-source tool that is freely adaptable. As such, the algorithm used in this pipeline can be repurposed for the analysis of other genome editing systems beyond the CRISPR-Cas9 system. Additionally, it is possible to enhance the specificity of DANGER analysis for CRISPR-Cas9 by incorporating CRISPR-Cas9-specific off-target scoring algorithms. The research team believes that the DANGER analysis pipeline has the potential to significantly expand the scope of genomic studies and industrial applications involving genome editing.
The research team consists of Kazuki Nakamae from Hiroshima University and PtBio Inc., as well as Hidemasa Bono from Hiroshima University.
Funding for this research was provided by the Center of Innovation for Bio-Digital Transformation, the open innovation platform for industry-academia co-creation (COI-NEXT) under the Japan Science and Technology Agency COI-NEXT (JPMJPF2010), and the Japan Society for the Promotion of Science KAKENHI (21K17855).
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1. Source: Coherent Market Insights, Public sources, Desk research
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