• T Rensch, D Villar, J Horvath, DT Odom, P Flicek. Mitochondrial heteroplasmy in vertebrates using ChIP-sequencing data. Genome Biol 2016;17(1):139. doi:10.1186/s13059-016-0996-y
  [BibTeX] [Abstract]
  

  \textbf{BACKGROUND:} Mitochondrial 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.
  \textbf{RESULTS:} We 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.
  \textbf{CONCLUSION:} In 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

  @Article{27349964,
  author = {Rensch T and Villar D and Horvath J and Odom DT and Flicek P},
  title = {Mitochondrial heteroplasmy in vertebrates using ChIP-sequencing data},
  journal = {Genome Biol},
  volume = {17},
  number = {1},
  pages = {139},
  year = {2016},
  doi = {10.1186/s13059-016-0996-y},
  abstract = {\textbf{BACKGROUND:} Mitochondrial 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.
  \textbf{RESULTS:} We 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.
  \textbf{CONCLUSION:} In 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},}

Description

Mitochondrial heteroplasmy, the presence of more than one 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 mitochondrial heteroplasmy from the concomitant mitochondrial DNA fraction sequenced in these experiments.
We first demonstrate that the sequencing coverage of mtDNA in ChIP-sequencing 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.
In addition to documenting the prevalence of mtDNA in ChIP-sequencing 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.

Raw Data

Newly created raw ChIP-seq data for CEBPA, H3K4me1, H3K27ac, and Histone3 can be found in ArrayExpress with the accession number  E-MTAB-3933.
We also used the following previously published ChIP-seq datasets for this study:
HNF4A and CEBPA data from  Schmidt, Wilson, Ballester, et al.  with accession number  E-TABM-722 .
CTCF, SA1, NRSF/REST and H2AK5ac data from  Schmidt, Schwalie, et al.  with accession number  E-MTAB-437 .
CTCF and YY1 ChIP-seq data  Schwalie, Ward, et al.  with accession number  E-MTAB-1511 .
CEBPA, FOXA1, ONECUT1, and HNF4A ChIP-seq data from Ballester, et al. with accession number  E-MTAB-1509 .
H3K4me3 and H3K27ac ChIP-seq from  Villar, Berthelot, et al.  with accession number  E-MTAB-2633 .

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