Mitochondria are a key organelle within human cells, with functions ranging from ATP synthesis to apoptosis. Changes in mitochondrial function are associated with many diseases, as well as ‘natural’ processes like ageing. Mitochondria have a unique evolutionary origin, as the result of an endosymbiotic relationship between a bacterium and an archaeal cell. Therefore, the phylogenetic history of the mitochondrial proteome is also unique within the total human proteome. A new description of the genes encoding the human mitochondrial proteome – IMPI (Integrated Mitochondrial Protein Index) 2017 – provided an opportunity for exploration of mitochondrial proteome history and the application of this knowledge to the understanding of gene function, disease and ageing. To facilitate the exploration of the mitochondrial proteome, I created a manually curated dataset of 190,097 predicted orthologues of the 1,550 IMPI 2017 human genes across 359 species, using reciprocal best hit analysis as the basis for orthologue prediction. I used this to explore gene history and the potential for phylogenetic profiling to predict the function of uncharacterised genes. This inspired the use of phylogenetic profiling within two phyla of animals, to link presence and absence of metabolic genes to the function of mitochondrial transporters. Potential transport substrates were predicted for two groups of uncharacterised mitochondrial carriers. I also used the dataset to identify features of genes associated with monogenetic disease, as well as differences between recessive and dominant disease genes. A similar orthologue identification method was used to explore the total sequenced viral proteome for potential orthologues of mitochondrial proteins. This showed that a range of mitochondrial proteins are shared with viruses, potentially facilitating the co-opting of mitochondrial function during viral infection of eukaryotic cells. I then used orthology to explore the conservation of residues linked to protein acetylation and identify a link with lifespan in warm-blooded vertebrates. In conclusion, I have used orthology to further the understanding of human mitochondrial proteome history and developed applications of this information. For example, phylogenetic features of disease genes are being used as part of a wider pipeline to predict mitochondrial disease genes. Furthermore, predicted substrates of the SLC25A14/30 mitochondrial carriers are being tested. My dataset provides further opportunities to explore the evolution and function of the mitochondrion.