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Stochastic Drift in Mitochondrial DNA Point Mutations: A Novel Perspective Ex Silico

Overview of attention for article published in PLoS Computational Biology, November 2009
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Title
Stochastic Drift in Mitochondrial DNA Point Mutations: A Novel Perspective Ex Silico
Published in
PLoS Computational Biology, November 2009
DOI 10.1371/journal.pcbi.1000572
Pubmed ID
Authors

Suresh Kumar Poovathingal, Jan Gruber, Barry Halliwell, Rudiyanto Gunawan

Abstract

The mitochondrial free radical theory of aging (mFRTA) implicates Reactive Oxygen Species (ROS)-induced mutations of mitochondrial DNA (mtDNA) as a major cause of aging. However, fifty years after its inception, several of its premises are intensely debated. Much of this uncertainty is due to the large range of values in the reported experimental data, for example on oxidative damage and mutational burden in mtDNA. This is in part due to limitations with available measurement technologies. Here we show that sample preparations in some assays necessitating high dilution of DNA (single molecule level) may introduce significant statistical variability. Adding to this complexity is the intrinsically stochastic nature of cellular processes, which manifests in cells from the same tissue harboring varying mutation load. In conjunction, these random elements make the determination of the underlying mutation dynamics extremely challenging. Our in silico stochastic study reveals the effect of coupling the experimental variability and the intrinsic stochasticity of aging process in some of the reported experimental data. We also show that the stochastic nature of a de novo point mutation generated during embryonic development is a major contributor of different mutation burdens in the individuals of mouse population. Analysis of simulation results leads to several new insights on the relevance of mutation stochasticity in the context of dividing tissues and the plausibility of ROS "vicious cycle" hypothesis.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Germany 1 2%
Brazil 1 2%
Switzerland 1 2%
China 1 2%
United Kingdom 1 2%
Unknown 38 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 33%
Student > Ph. D. Student 12 27%
Professor 5 11%
Student > Bachelor 4 9%
Student > Master 4 9%
Other 1 2%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 53%
Biochemistry, Genetics and Molecular Biology 8 18%
Chemical Engineering 2 4%
Engineering 2 4%
Mathematics 1 2%
Other 4 9%
Unknown 4 9%