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Selection-dependent and Independent Generation of CRISPR/Cas9-mediated Gene Knockouts in Mammalian Cells
Published on: June 16, 2017
Allele-specific suppression of pathogenic bestrophin-1 transcripts by CRISPR/Cas9-mediated genome editing
Andrea Milenkovic1, Bernhard H F Weber2,3
1Institute of Human Genetics, University of Regensburg, Universitätsstrasse 31, Regensburg, D-93053, Germany.
Background:
Treating autosomal dominant gene mutations remains challenging, particularly when mutations convey a gain-of-function or a dominant-negative effect, as standard gene supplementation strategies often fail to counteract the pathogenic allele.
Methods:
In this study, we employed human induced pluripotent stem cell-derived retinal pigment epithelium (hiPSC-RPE) to investigate allele-specific CRISPR/Cas9 genome editing as a potential treatment for Best disease (BD), an autosomal dominant macular dystrophy caused by over 250 distinct mutations in the bestrophin-1 (BEST1) gene. We designed and evaluated single guide RNAs (sgRNA) targeting three known BEST1 mutations (p.(R218C), p.(A243V), and p.(I295del)), assessing their impact on BD-associated hiPSC-RPE phenotypes and BEST1 channel function. Computationally predicted sgRNAs were rigorously tested for on-target efficiency, allele specificity and genome-wide off-target activities.
Results:
We found that shortening sgRNA length improved specificity in some cases, while introducing an additional mismatch generally compromised editing efficiency. Notably, only one of the three mutations yielded an sgRNA with both high cleavage efficiency and undetectable off-target effects in hiPSC-RPE cells. We then explored the consequences of allele-specific editing on BEST1 expression and function in clonal BD hiPSC-RPE lines. Eliminating the mutant BEST1 transcript led to enhanced BEST1 localization, improved protein stability and restoration of anion transport function.
Conclusions:
Taken together, our findings support allele-specific gene editing as a viable therapeutic strategy for selected BEST1 mutations, while underscoring the necessity for rigorous testing of computationally designed sgRNAs, given their mutation- and context-dependent variability.
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