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MitoRS, a method for high throughput, sensitive, and accurate detection of mitochondrial DNA heteroplasmy

Overview of attention for article published in BMC Genomics, April 2017
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Title
MitoRS, a method for high throughput, sensitive, and accurate detection of mitochondrial DNA heteroplasmy
Published in
BMC Genomics, April 2017
DOI 10.1186/s12864-017-3695-5
Pubmed ID
Authors

Julien Marquis, Gregory Lefebvre, Yiannis A. I. Kourmpetis, Mohamed Kassam, Frédéric Ronga, Umberto De Marchi, Andreas Wiederkehr, Patrick Descombes

Abstract

Mitochondrial dysfunction is linked to numerous pathological states, in particular related to metabolism, brain health and ageing. Nuclear encoded gene polymorphisms implicated in mitochondrial functions can be analyzed in the context of classical genome wide association studies. By contrast, mitochondrial DNA (mtDNA) variants are more challenging to identify and analyze for several reasons. First, contrary to the diploid nuclear genome, each cell carries several hundred copies of the circular mitochondrial genome. Mutations can therefore be present in only a subset of the mtDNA molecules, resulting in a heterogeneous pool of mtDNA, a situation referred to as heteroplasmy. Consequently, detection and quantification of variants requires extremely accurate tools, especially when this proportion is small. Additionally, the mitochondrial genome has pseudogenized into numerous copies within the nuclear genome over the course of evolution. These nuclear pseudogenes, named NUMTs, must be distinguished from genuine mtDNA sequences and excluded from the analysis. Here we describe a novel method, named MitoRS, in which the entire mitochondrial genome is amplified in a single reaction using rolling circle amplification. This approach is easier to setup and of higher throughput when compared to classical PCR amplification. Sequencing libraries are generated at high throughput exploiting a tagmentation-based method. Fine-tuned parameters are finally applied in the analysis to allow detection of variants even of low frequency heteroplasmy. The method was thoroughly benchmarked in a set of experiments designed to demonstrate its robustness, accuracy and sensitivity. The MitoRS method requires 5 ng total DNA as starting material. More than 96 samples can be processed in less than a day of laboratory work and sequenced in a single lane of an Illumina HiSeq flow cell. The lower limit for accurate quantification of single nucleotide variants has been measured at 1% frequency. The MitoRS method enables the robust, accurate, and sensitive analysis of a large number of samples. Because it is cost effective and simple to setup, we anticipate this method will promote the analysis of mtDNA variants in large cohorts, and may help assessing the impact of mtDNA heteroplasmy on metabolic health, brain function, cancer progression, or ageing.

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Mendeley readers

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The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 <1%
Unknown 132 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 26%
Student > Ph. D. Student 24 18%
Student > Master 16 12%
Student > Bachelor 10 8%
Student > Doctoral Student 9 7%
Other 21 16%
Unknown 18 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 48 36%
Agricultural and Biological Sciences 30 23%
Medicine and Dentistry 12 9%
Neuroscience 7 5%
Computer Science 3 2%
Other 7 5%
Unknown 26 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 April 2017.
All research outputs
#18,542,806
of 22,965,074 outputs
Outputs from BMC Genomics
#8,217
of 10,686 outputs
Outputs of similar age
#235,315
of 309,828 outputs
Outputs of similar age from BMC Genomics
#177
of 226 outputs
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