Large-scale genetic analysis reveals mammalian mtDNA heteroplasmy dynamics and variance increase through lifetimes and generations
Research output: Contribution to journal › Article › peer-review
Colleges, School and Institutes
- Imperial College London
- University of Natural Resources and Life Sciences, Konrad Lorenz Strasse 20, 3430, Tulln, Austria.
- Department for Biomedical Sciences, Reproduction Centre Wieselburg, University of Veterinary Medicine, Vienna, Austria.
- Department for Agrobiotechnology, Biotechnology in Animal Production, IFA Tulln, 3430, Tulln, Austria.
- University of Oxford
- Research Facility Studenec, Institute of Vertebrate Biology of the Czech Academy of Sciences, Květná 8, 603 65, Brno, Czech Republic.
- Genomics Core Facility, VetCore, University of Veterinary Medicine Vienna, Veterinärplatz 1, 1210, Vienna, Austria.
- Institute of Laboratory Animal Science, University of Veterinary Medicine Vienna, Veterinärplatz 1, 1210, Vienna, Austria.
- Institute of Animal Breeding and Genetics, University of Veterinary Medicine Vienna, Veterinärplatz 1, 1210, Vienna, Austria.
- School of Biosciences, University of Birmingham
Vital mitochondrial DNA (mtDNA) populations exist in cells and may consist of heteroplasmic mixtures of mtDNA types. The evolution of these heteroplasmic populations through development, ageing, and generations is central to genetic diseases, but is poorly understood in mammals. Here we dissect these population dynamics using a dataset of unprecedented size and temporal span, comprising 1947 single-cell oocyte and 899 somatic measurements of heteroplasmy change throughout lifetimes and generations in two genetically distinct mouse models. We provide a novel and detailed quantitative characterisation of the linear increase in heteroplasmy variance throughout mammalian life courses in oocytes and pups. We find that differences in mean heteroplasmy are induced between generations, and the heteroplasmy of germline and somatic precursors diverge early in development, with a haplotype-specific direction of segregation. We develop stochastic theory predicting the implications of these dynamics for ageing and disease manifestation and discuss its application to human mtDNA dynamics.
|Publication status||Published - 27 Jun 2018|
- Applied mathematics, Mitochondria, Mitochondrial genome, Stochastic modelling