Our peer-reviewed findings so far have included exciting answers to the three above long-standing questions: why different genes are differentially retained in organelles across species, why different species retain different profiles of organelle genes, and how oDNA maintenance takes places across eukaryotic kingdoms. This final point has opened up an exciting new avenue of research: why mitochondria behave so differently in different organisms, and why they move with such complex collective dynamics in plants. We have created a “social network” picture of genetic exchange to explain these phenomena and have published a collection of peer-reviewed articles in this new paradigm. We have published a wide variety of experimental data, mathematical models and simulation code, and bioinformatics pipelines via public repositories to allow further research.
Specifically, we have found that:
- Strategies for avoiding organelle "mutational meltdown" depend on an organism's ability to set aside protected cells for inheritance between generations. Several animals can do this, allowing the relatively well-known mtDNA bottleneck. Plants, fungi, and single cells cannot, and we have shown a role for a process called gene conversion that can compensate for this inability. This theory has been experimentally verified in plants in collaboration with colleagues. In so doing we have created the most general explanation of which we are aware for how organelles spread mutational damage.
- Plant mitochondria move to resolve a tension between staying spread through the cell and meeting to exchange contents. We used video microscopy, computational analysis, and network science to define the "social networks" of mitochondria -- the meetings of mitochondria in the cell. These social networks are surprisingly good at supporting beneficial exchange of contents between mitochondria, and we have shown with experiments on mutant lines and followup theory that this "trade network" is controlled in such a way as to optimise exchange.
- The retention of genes in organelles is shaped by a combination of factors, including hydrophobicity, protein product centrality, and nucleic acid biochemistry. This relationship is so universal that statistical models trained on retention patterns in chloroplasts can predict those in mitochondria, and vice versa. The same features also describe gene retention in independent endosymbionts.
- The extent of oDNA gene loss is connected in part to features of an organism’s environment. Theoretical models and bioinformatic surveys agree that strongly varying environmental demands on metabolism (like those found in intertidal zones, and through pronounced diurnal variation) favour the retention of more genes in oDNA, aligned with the theory of colocation for redox regulation (CoRR). The extent of gene retention in mitochondria and plastids is coupled, supporting this picture.
During this progress, we have also developed and published several highly generalisable tools for bioinformatic, evolutionary, and cell biological modelling, including powerful machinery for “accumulation modelling” (the parallel acquisition or loss of traits across lineages), phylogenetic comparative methods for non-standard data structures, and simulation models for agents in cell biology.
Progress beyond the state of the art and expected results until the end of the project