Back

Mitochondrial dynamics can resolve stoichiometric challenges in plant mtDNA repair

Johnston, I.; Sloan, D. B.; Moller, I. M.

2026-10-09 plant biology
10.64898/2026.10.08.757513 bioRxiv
Show abstract

Although mitochondrial DNA (mtDNA) is subject to damage and high mutation rates in many eukaryotes, plants have a variety of mtDNA repair pathways that somehow result in exceptionally low mutation rates. However, the stoichiometry of biomolecules in plant mitochondria raises challenges for the DNA repair process. The protein complexes responsible for repair pathways contain subunits present at low copy numbers per mitochondrion. Mitochondria on average contain less than a full genome, limiting the capacity for templated repair, and raising the risk that repair machinery is localised to a DNA-empty mitochondrion where it cannot be used. Here we build on recent experimental characterisation of the copy numbers and physical processes involved to model the capacity for DNA repair in plant mitochondria. We find that targeted import of protein machinery, biased fusion of mitochondria bearing DNA, and exchange of biomolecules upon fusion can improve repair capacity through different mechanisms. Specifically, our model indicates that base excision repair can keep ~95% of mtDNA intact even without targetting or exchange rules and that targetting protein import to DNA-bearing mitochondria or exchanging protein content drives this to effectively 100%. In contrast, template repair cannot keep a majority of mtDNA intact unless mtDNA is shared across mitochondria through fusion, in which case its efficacy increases. Exchanging of metabolons (repair protein complexes) increases repair efficiency across all circumstances. We discuss the implications of our model for plant development and organelle inheritance.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.