Roadmap and Considerations for Genome Editing in a Non-Model Organism: Genetic Variations and Off-Target Profiling

The CRISPR/Cas genome editing approach in non-model organisms poses challenges that remain to be resolved. Here, we demonstrated a generalized roadmap for a de novo genome annotation approach applied to the non-model organism <i>Macrobrachium rosenbergii</i>. We also addressed the typical genome editing challenges arising from genetic variations, such as a high frequency of single nucleotide polymorphisms, differences in sex chromosomes, and repetitive sequences that can lead to off-target events. For the genome editing of <i>M. rosenbergii</i>, our laboratory recently adapted the CRISPR/Cas genome editing approach to embryos and the embryonic primary cell culture. In this continuation study, an annotation pipeline was trained to predict the gene models by leveraging the available genomic, transcriptomic, and proteomic data, and enabling accurate gene prediction and guide design for knock-outs. A next-generation sequencing analysis demonstrated a high frequency of genetic variations in genes on both autosomal and sex chromosomes, which have been shown to affect the accuracy of editing analyses. To enable future applications based on the CRISPR/Cas tool in non-model organisms, we also verified the reliability of editing efficiency and tracked off-target frequencies. Despite the lack of comprehensive information on non-model organisms, this study provides an example of the feasibility of selecting and editing specific genes with a high degree of certainty.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2024-11-22
DOI
https://doi.org/10.3390/ijms252312530
Citations
2
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
0.47

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article

Roadmap and Considerations for Genome Editing in a Non-Model Organism: Genetic Variations and Off-Target Profiling

Vered Chalifa‐Caspi, Hanin Wattad, Jonathan Molcho, Eliahu D. Aflalo et al.
2 citations
International Journal of Molecular Sciences
CRISPR and Genetic Engineering
0.47
article

Roadmap and Considerations for Genome Editing in a Non-Model Organism: Genetic Variations and Off-Target Profiling

Vered Chalifa‐Caspi, Hanin Wattad, Jonathan Molcho, Eliahu D. Aflalo, Rivka Manor, Amir Sagi, Simy Weil
article en
2 citations

Abstract

The CRISPR/Cas genome editing approach in non-model organisms poses challenges that remain to be resolved. Here, we demonstrated a generalized roadmap for a de novo genome annotation approach applied to the non-model organism <i>Macrobrachium rosenbergii</i>. We also addressed the typical genome editing challenges arising from genetic variations, such as a high frequency of single nucleotide polymorphisms, differences in sex chromosomes, and repetitive sequences that can lead to off-target events. For the genome editing of <i>M. rosenbergii</i>, our laboratory recently adapted the CRISPR/Cas genome editing approach to embryos and the embryonic primary cell culture. In this continuation study, an annotation pipeline was trained to predict the gene models by leveraging the available genomic, transcriptomic, and proteomic data, and enabling accurate gene prediction and guide design for knock-outs. A next-generation sequencing analysis demonstrated a high frequency of genetic variations in genes on both autosomal and sex chromosomes, which have been shown to affect the accuracy of editing analyses. To enable future applications based on the CRISPR/Cas tool in non-model organisms, we also verified the reliability of editing efficiency and tracked off-target frequencies. Despite the lack of comprehensive information on non-model organisms, this study provides an example of the feasibility of selecting and editing specific genes with a high degree of certainty.

International Journal of Molecular SciencesVol. 25(23)
Ben-Gurion University of the Negev (IL), Achva Academic College (IL)
U.S. Department of Agriculture, National Institute of Food and Agriculture
Openalex Percentile: Top 34%
CRISPR and Genetic Engineering
0.47
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