Mitochondrial DNA (mtDNA) and plastid DNA (ptDNA) encode vital bioenergetic apparatus, and mutations in these organelle DNA (oDNA) molecules can be devastating. In the germline of several animals, a genetic “bottleneck” increases cell-to-cell variance in mtDNA heteroplasmy, allowing purifying selection to act to maintain low proportions of mutant mtDNA. However, most eukaryotes do not sequester a germline early in development, and even the animal bottleneck remains poorly understood. How then do eukaryotic organelles avoid Muller’s ratchet—the gradual buildup of deleterious oDNA mutations? Here, we construct a comprehensive and predictive genetic model, quantitatively describing how different mechanisms segregate and decrease oDNA damage across eukaryotes. We apply this comprehensive theory to characterise the animal bottleneck with recent single-cell observations in diverse mouse models. Further, we show that gene conversion is a particularly powerful mechanism to increase beneficial cell-to-cell variance without depleting oDNA copy number, explaining the benefit of observed oDNA recombination in diverse organisms which do not sequester animal-like germlines (for example, sponges, corals, fungi, and plants). Genomic, transcriptomic, and structural datasets across eukaryotes support this mechanism for generating beneficial variance without a germline bottleneck. This framework explains puzzling oDNA differences across taxa, suggesting how Muller’s ratchet is avoided in different eukaryotes.

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Network analysis of Arabidopsis mitochondrial dynamics reveals a resolved tradeoff between physical distribution and social connectivity Graphical abstract Highlights d Dynamic social networks of plant mitochondria reflect physical organellar encounters d Network analysis and modeling show priorities and tradeoffs for mitochondrial motion d Mitochondria in plant cells trade off physical spacing against social connectivity d Plant cells favor efficient networks with high potential for information exchange

Mitochondria form highly dynamic populations in the cells of plants (and all eukaryotes). The characteristics and benefits of this collective behaviour, and how it is influenced by nuclear features, remain to be fully elucidated. Here, we use a recently developed quantitative approach to reveal and analyse the physical and collective "social" dynamics of mitochondria in an Arabidopsis msh1 mutant where organelle DNA maintenance machinery is compromised. We use a newly created line combining the msh1 mutant with mitochondrially-targeted GFP, and characterise mitochondrial dynamics with a combination of single-cell timelapse microscopy, computational tracking and network analysis. The collective physical behaviour of msh1 mitochondria is altered from wildtype in several ways: mitochondria become less evenly spread, and networks of inter-mitochondrial encounters become more connected with greater potential efficiency for inter-organelle exchange -- reflecting a potential compensatory mechanism for the genetic challenge to the mtDNA population, supporting more inter-organelle exchange. We find that these changes are similar to those observed in friendly, where mitochondrial dynamics are altered by a physical perturbation, suggesting that this shift to higher connectivity may reflect a general response to mitochondrial challenges, where physical dynamics of mitochondria may be altered to control the genetic structure of the mtDNA population.

Mitochondria and plastids power complex life, and retain their own organelle DNA (oDNA) genomes, with highly reduced gene contents compared to their endosymbiont ancestors. Why some protein-coding genes are retained in oDNA and some lost remains a debated question. Here we harness over 15k oDNA sequences and over 300 whole genome sequences with tools from structural biology, bioinformatics, machine learning, and Bayesian model selection to reveal the properties of genes, and associated underlying mechanisms, that shape oDNA evolution. Striking symmetry exists between the two organelle types: gene retention patterns in both are predicted by the hydrophobicity of a protein product and its energetic centrality within its protein complex, with additional influences of nucleic acid and amino acid biochemistry. Remarkably, retention principles from one organelle type successfully and quantitatively predict retention in the other, supporting this universality; these principles also distinguish gene profiles in independent endosymbiotic relationships. The identification of these features shaping organelle gene retention both provides quantitative support for several existing evolutionary hypotheses, and suggests new biochemical and biophysical mechanisms influencing organelle genome evolution.