Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism
Life Sciences & Biomedicine - Other Topics
bottleneck
FOS: Computer and information sciences
Quantitative Biology - Subcellular Processes
MOUSE
Quantitative Biology - Quantitative Methods
DISEASE
Mice
computational biology
MONTE-CARLO
Models
Biology (General)
genes
Quantitative Methods (q-bio.QM)
0303 health sciences
mtDNA
Q
R
systems biology
Statistical
RANDOM GENETIC DRIFT
Mitochondrial
MITOCHONDRIAL-DNA HETEROPLASMY
Wills
statistics
Medicine
Life Sciences & Biomedicine
Computational and Systems Biology
570
chromosomes
statistic
QH301-705.5
Science
HUMAN OOCYTES
GENOMES
Biostatistics
Statistics - Applications
DNA, Mitochondrial
Models, Biological
developmental biology
03 medical and health sciences
RAPID SEGREGATION
Animals
Applications (stat.AP)
Biology
stat.AP
Subcellular Processes (q-bio.SC)
mouse
q-bio.SC
Science & Technology
Models, Statistical
q-bio.QM
500
DNA
Biological
COPY NUMBER
FOS: Biological sciences
REPLICATION
stochastic modelling
DOI:
10.7554/elife.07464
Publication Date:
2015-06-02T11:32:40Z
AUTHORS (8)
ABSTRACT
Dangerous damage to mitochondrial DNA (mtDNA) can be ameliorated during mammalian development through a highly debated mechanism called the mtDNA bottleneck. Uncertainty surrounding this process limits our ability to address inherited mtDNA diseases. We produce a new, physically motivated, generalisable theoretical model for mtDNA populations during development, allowing the first statistical comparison of proposed bottleneck mechanisms. Using approximate Bayesian computation and mouse data, we find most statistical support for a combination of binomial partitioning of mtDNAs at cell divisions and random mtDNA turnover, meaning that the debated exact magnitude of mtDNA copy number depletion is flexible. New experimental measurements from a wild-derived mtDNA pairing in mice confirm the theoretical predictions of this model. We analytically solve a mathematical description of this mechanism, computing probabilities of mtDNA disease onset, efficacy of clinical sampling strategies, and effects of potential dynamic interventions, thus developing a quantitative and experimentally-supported stochastic theory of the bottleneck.
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CITATIONS (82)
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