Abstract
Mitochondria host multiple copies of their own small circular genome that has been extensively studied to trace the evolution of the modern eukaryotic cell and discover important mutations linked to inherited diseases. Whole genome and exome sequencing have enabled the study of mtDNA in a large number of samples and experimental conditions at single nucleotide resolution, allowing the deciphering of the relationship between inherited mutations and phenotypes and the identification of acquired mtDNA mutations in classical mitochondrial diseases as well as in chronic disorders, ageing and cancer. By applying an ad hoc computational pipeline based on our MToolBox software, we reconstructed mtDNA genomes in single cells using whole genome and exome sequencing data obtained by different amplification methodologies (eWGA, DOP-PCR, MALBAC, MDA) as well as data from single cell Assay for Transposase Accessible Chromatin with high-throughput sequencing (scATAC-seq) in which mtDNA sequences are expected as a byproduct of the technology. We show that assembled mtDNAs, with the exception of those reconstructed by MALBAC and DOP-PCR methods, are quite uniform and suitable for genomic investigations, enabling the study of various biological processes related to cellular heterogeneity such as tumor evolution, neural somatic mosaicism and embryonic development.
Highlights
Mitochondria are subcellular organelles involved in energetic metabolism through three main sets of biochemical reactions: the tricarboxylic acid cycle (TCA cycle or Krebs cycle), the respiratory chain (RC) and the ATP synthesis machinery [1]
To capture genuine mitochondrial DNA (mtDNA) reads and take into account potential technical biases in scWGS data, we adapted our computational pipeline to single cells WGS data, initially designed for reconstructing mtDNA genomes in WGS and WES experiments from bulk tissues [13,15] (Figure 1)
We investigated the effect of the genome amplification strategy on the reconstruction of mtDNA genomes
Summary
Mitochondria are subcellular organelles involved in energetic metabolism through three main sets of biochemical reactions: the tricarboxylic acid cycle (TCA cycle or Krebs cycle), the respiratory chain (RC) and the ATP synthesis machinery [1]. With few exceptions a typical eukaryotic cell has hundreds or thousands of these organelles and these numbers vary among species and tissue types depending on specific energetic needs [2]. Mutations occurring at mitochondrial DNA (mtDNA) can compromise the production of ATP and lead, in humans, to a variety of multisystemic disorders mainly involving high energy demanding tissues, such as skeletal muscle, the central nervous system and heart muscle [3]. MtDNA has a very high mutation rate and, compared to nuclear DNA [4], its variants can be either heteroplasmic (where both mutated and wild type mtDNA molecules co-exist within the cell). A few years ago, we released MToolBox, a software package implementing a fully automated pipeline for heteroplasmy quantification, annotation, and prioritization of human mtDNA variants in whole genome (WGS), whole exome (WES) and Sanger sequencing data [15]
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