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Engineering mtDNA Deletions by Reconstituting End-Joining in Human Mitochondria [DOGMAseq]

GSE276718 Homo sapiens Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing 9 samples Submitted 2025/03/10 Platform GPL34284
Summary
Recent breakthroughs in the genetic manipulation of mitochondrial DNA (mtDNA) have enabled the precise introduction of base substitutions and the effective removal of genomes carrying harmful mutations. However, the reconstitution of mtDNA deletions responsible for severe mitochondrial disorders and age-related diseases has not yet been achieved in human cells. Here, we developed a method to engineer specific mtDNA deletions in human cells by co-expressing end-joining (EJ) machinery and targeted endonucleases. As a proof-of-concept, we used mito-EJ and mito-ScaI to generate a panel of clonal cell lines harboring a ~3.5 kb mtDNA deletion with the full spectrum of heteroplasmy. Investigating these isogenic cells revealed a critical threshold of ~75% deleted genomes, beyond which cells exhibited depletion of OXPHOS proteins, severe metabolic disruption, and impaired growth in galactose-containing media. Single-cell multiomic analysis revealed two distinct patterns of nuclear gene deregulation in response to mtDNA deletion accumulation; one triggered at the deletion threshold and another progressively responding to increasing heteroplasmy. In summary, the co-expression of mito-EJ and programable nucleases provides a powerful tool to model disease-associated mtDNA deletions in different cell types. Establishing a panel of cell lines with a large-scale deletion at varying levels of heteroplasmy is a valuable resource for understanding the impact of mtDNA deletions on diseases and guiding the development of potential therapeutic strategies.
Published in
Engineering mtDNA deletions by reconstituting end joining in human mitochondria
Fu Y, Land M, Kavlashvili T et al. · Cell 2025 · PMID 40068680 · doi:10.1016/j.cell.2025.02.009
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Also filed as BioProject PRJNA1158748 and SRA study SRP531529. Searching any of these in the dataset finder brings you back here.

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