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Mitochondrial heteroplasmy in vertebrates using ChIP-sequencing data.

Thomas Rensch1, Diego Villar2, Julie Horvath3,4

  • 1European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.

Genome Biology
|June 29, 2016
PubMed
Summary

Mitochondrial heteroplasmy is common across mammals, with a new method detecting it in 45 individuals from 16 species. Most heteroplasmies were found in intergenic regions, offering evolutionary insights.

Keywords:
Chromatin immunoprecipitation sequencing (ChIP-seq)HeteroplasmyMitochondrionVertebratesmitochondrial DNA (mtDNA)

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Area of Science:

  • Evolutionary Biology
  • Genetics
  • Molecular Biology

Background:

  • Mitochondrial heteroplasmy, the coexistence of multiple mitochondrial DNA (mtDNA) variants, is more prevalent than previously assumed.
  • High mtDNA mutation rates and limited repair mechanisms contribute to heteroplasmy.
  • Research has primarily focused on human mitochondrial diseases, necessitating broader evolutionary and cross-species studies.

Purpose of the Study:

  • To conduct an integrated, cross-species evaluation of mitochondrial heteroplasmy in mammals.
  • To explore general principles and evolutionary dynamics of heteroplasmy.
  • To develop a novel method for detecting heteroplasmy from existing next-generation sequencing (NGS) data, specifically ChIP-seq.

Main Methods:

  • Utilized previously reported NGS data from ChIP-seq experiments.
  • Developed and applied a novel computational method for accurate heteroplasmy detection, accounting for NGS error rates.
  • Analyzed data from 79 individuals across 16 mammalian species.

Main Results:

  • Demonstrated sufficient sequencing coverage of mtDNA in ChIP-seq data for heteroplasmy detection.
  • Identified 107 heteroplasmic positions in 45 individuals across 16 species.
  • Found that the majority of detected heteroplasmies occur in intergenic regions.

Conclusions:

  • Mitochondrial heteroplasmy is prevalent in mammals and shares characteristics with human heteroplasmies.
  • The developed method effectively detects heteroplasmy from ChIP-seq data.
  • Cross-species analysis provides valuable insights into the evolutionary dynamics of mitochondrial heteroplasmy.