Mitochondria are the "powerhouses" in our cells, providing the energy we need to survive. Once an independent organism, the first mitochondrion was engulfed and harnessed billions of years ago by a cell that would become our ancestor. Our mitochondria today still contain some genes in their DNA (mitochondrial DNA or mtDNA), a relic of this evolutionary history. But why have they retained this genetic independence? MtDNA genes are at risk from the damaging environment of the mitochondrion, and mutations in mtDNA give rise to devastating inherited diseases. We know that genes can be transferred from the mitochondrion to the cell nucleus, which is a safer and advantageous place to store genes. Why store books in a leaky shed when you could keep them in a central library?
Dr Iain Johnston, a Birmingham Fellow in Biosciences, and Ben Williams, a researcher at the Whitehead Institute at MIT, used maths, statistics, and biological "big data" to answer this question. Building a mathematical model for evolution, they gathered mtDNA sequences from over 2000 species (from plants to protists) to explore the evolutionary history of mitochondria using an algorithm called "HyperTraPS". They also gathered data on physical and genetic many features of genes, seeking those features that made genes more or less likely to be kept in mitochondria.
They found that allowing mtDNA to retain some genes helps guarantee that important cellular machinery is delivered to the mitochondrion where it's needed. By keeping genes that play central roles in building this machinery within mitochondria, the cell also retains a way of efficiently controlling individual mitochondria, removing dysfunctional ones without altering others.
Johnston and Williams also found that those genes chosen to remain in mtDNA may have evolved specific features to better withstand the damaging chemical environment of the mitochondrion. They hope that this insight into the pressures that mitochondrial genes face will help understand both evolutionary and synthetic biology (where organisms are manipulated to perform useful tasks). The mathematical machinery that Johnston developed is also suitable for exploring many other important biological questions, from photosynthesis in crops to disease progression in individual patients.
Their article is in Cell Systems here with a commentary in Science here.