Evolving mtDNA populations within cells
Iain G Johnston, Joerg P Burgstaller
Biochemical Society Transactions 47 1367 (2019)
Iain G Johnston
Frontiers in Cell and Developmental Biology 7 294 (2019)
We've recently written two review papers looking at the dynamics of mitochondrial DNA (mtDNA) in cells. As we've written about before, cells contain populations of hundreds or thousands of mtDNA molecules. These molecules replicate and degrade, so that over time, cellular populations of mtDNA change and evolve. The amount of disease-causing mutations, and the number and structure of mtDNA molecules, may all change as organisms develop and age, with different consequences.
The first article, in Biochemical Society Transactions, takes a broad look at how cellular mtDNA populations change over time, considering a range of organisms from humans and other animals to plants and fungi. We look at the different processes that change mtDNA populations, which include replication and degradation but may also include recombination (particularly in plants) and cell-to-cell exchange of mitochondria. The review particularly highlights the importance of understanding cell-to-cell variability in mtDNA populations -- as it only takes a few cells with lots of mutant mtDNA to cause disease, it's important to understand the statistics of mtDNA populations across cells. We review experiments and theory aiming to do so, including our recent work showing that cell-to-cell variability of mtDNA mutant load increases over time in a wide variety of circumstances.
The second article, in Frontiers in Cell and Developmental Biology, focuses on the so-called "mtDNA bottleneck", a process that shapes mtDNA populations in early mammalian development, and helps prevent the inheritance of mutant mtDNA. Specifically, mtDNA undergoes a "genetic bottleneck" between generations, meaning that mothers' egg cells, and offspring, often have dramatically different mtDNA populations. The review emphasises that this "genetic bottleneck" is an effective quantity, not a directly measurable observation, that arises from several physical processes, including but not limited to a "physical bottleneck" or mtDNA depletion during development. Different ways of modelling, analysing, and explaining the "genetic bottleneck" are reviewed, from human populations to mouse egg cells and Adélie penguins. We invest some time in trying to explain the different assumptions, symbols, and methods that researchers have used to quantify the bottleneck over the years. Again, the importance of understanding cell-to-cell variance in mtDNA populations is a core theme.
Like all reviews, these articles don't have new results, but attempt to summarise existing knowledge and thinking on these topics. We hope that both papers provide some interesting insights, references, and (in the case of the bottleneck paper) visualisations that may help understand these often confusing topics.
Iain G Johnston, Joerg P Burgstaller
Biochemical Society Transactions 47 1367 (2019)
and
Varied mechanisms and models for the varying mitochondrial bottleneckIain G Johnston
Frontiers in Cell and Developmental Biology 7 294 (2019)
We've recently written two review papers looking at the dynamics of mitochondrial DNA (mtDNA) in cells. As we've written about before, cells contain populations of hundreds or thousands of mtDNA molecules. These molecules replicate and degrade, so that over time, cellular populations of mtDNA change and evolve. The amount of disease-causing mutations, and the number and structure of mtDNA molecules, may all change as organisms develop and age, with different consequences.
The first article, in Biochemical Society Transactions, takes a broad look at how cellular mtDNA populations change over time, considering a range of organisms from humans and other animals to plants and fungi. We look at the different processes that change mtDNA populations, which include replication and degradation but may also include recombination (particularly in plants) and cell-to-cell exchange of mitochondria. The review particularly highlights the importance of understanding cell-to-cell variability in mtDNA populations -- as it only takes a few cells with lots of mutant mtDNA to cause disease, it's important to understand the statistics of mtDNA populations across cells. We review experiments and theory aiming to do so, including our recent work showing that cell-to-cell variability of mtDNA mutant load increases over time in a wide variety of circumstances.
The second article, in Frontiers in Cell and Developmental Biology, focuses on the so-called "mtDNA bottleneck", a process that shapes mtDNA populations in early mammalian development, and helps prevent the inheritance of mutant mtDNA. Specifically, mtDNA undergoes a "genetic bottleneck" between generations, meaning that mothers' egg cells, and offspring, often have dramatically different mtDNA populations. The review emphasises that this "genetic bottleneck" is an effective quantity, not a directly measurable observation, that arises from several physical processes, including but not limited to a "physical bottleneck" or mtDNA depletion during development. Different ways of modelling, analysing, and explaining the "genetic bottleneck" are reviewed, from human populations to mouse egg cells and Adélie penguins. We invest some time in trying to explain the different assumptions, symbols, and methods that researchers have used to quantify the bottleneck over the years. Again, the importance of understanding cell-to-cell variance in mtDNA populations is a core theme.
A. Different processes shaping mixed mtDNA populations inside cells. B. The "genetic bottleneck", increasing mtDNA variance between egg cells and offspring.
Like all reviews, these articles don't have new results, but attempt to summarise existing knowledge and thinking on these topics. We hope that both papers provide some interesting insights, references, and (in the case of the bottleneck paper) visualisations that may help understand these often confusing topics.
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