Evidence map›Paper›PMID 27349964›Full record

ArticleGenome biology2016

Mitochondrial heteroplasmy in vertebrates using ChIP-sequencing data.

Thomas Rensch, Diego Villar, Julie Horvath, Duncan T Odom, Paul Flicek

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 30 citations in OpenAlex.

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  10. Evolving mtDNA populations within cells.Biochemical Society transactions · 2019
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 2 countries.

Thomas RenschEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
Diego VillarCancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK.
Julie HorvathBiological and Biomedical Sciences, North Carolina Central University, Durham, NC, 27707, USA.
Duncan T OdomCancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK.
Paul FlicekEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. flicek@ebi.ac.uk.
Cancer Research UK · GBEuropean Bioinformatics Institute · GBNorth Carolina Central University · USWellcome Sanger Institute · GB

Funding

Cancer Research UK 20412Wellcome Trust WT095908Wellcome Trust WT098051
6 · The paper itself

Abstract

backgroundMitochondrial heteroplasmy, the presence of more than one mitochondrial DNA (mtDNA) variant in a cell or individual, is not as uncommon as previously thought. It is mostly due to the high mutation rate of the mtDNA and limited repair mechanisms present in the mitochondrion. Motivated by mitochondrial diseases, much focus has been placed into studying this phenomenon in human samples and in medical contexts. To place these results in an evolutionary context and to explore general principles of heteroplasmy, we describe an integrated cross-species evaluation of heteroplasmy in mammals that exploits previously reported NGS data. Focusing on ChIP-seq experiments, we developed a novel approach to detect heteroplasmy from the concomitant mitochondrial DNA fraction sequenced in these experiments.

resultsWe first demonstrate that the sequencing coverage of mtDNA in ChIP-seq experiments is sufficient for heteroplasmy detection. We then describe a novel detection method for accurate detection of heteroplasmies, which also accounts for the error rate of NGS technology. Applying this method to 79 individuals from 16 species resulted in 107 heteroplasmic positions present in a total of 45 individuals. Further analysis revealed that the majority of detected heteroplasmies occur in intergenic regions.

conclusionIn addition to documenting the prevalence of mtDNA in ChIP-seq data, the results of our mitochondrial heteroplasmy detection method suggest that mitochondrial heteroplasmies identified across vertebrates share similar characteristics as found for human heteroplasmies. Although largely consistent with previous studies in individual vertebrates, our integrated cross-species analysis provides valuable insights into the evolutionary dynamics of mitochondrial heteroplasmy.

Indexed as

Evolution, MolecularAnimalsChromatin ImmunoprecipitationDNA, MitochondrialHigh-Throughput Nucleotide SequencingHumansMitochondriaMitochondrial DiseasesSequence Analysis, DNAVertebratesDNA, MitochondrialChromatin immunoprecipitation sequencing (ChIP-seq)Heteroplasmymitochondrial DNA (mtDNA)MitochondrionVertebrates

Identifiers

PMID27349964
PMCPMC4922064
OpenAlexW2462516771

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.