Dataset Information

Investigating Human Mitochondrial Genomes in Single Cells.

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.

SUBMITTER: Diroma MA

PROVIDER: S-EPMC7290567 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Investigating Human Mitochondrial Genomes in Single Cells.

Diroma Maria Angela MA Varvara Angelo Sante AS Attimonelli Marcella M Pesole Graziano G Picardi Ernesto E

Genes 20200511 5

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 mt ...[more]

PMID: 32403285

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Project description:BackgroundNext generation ultra-sequencing technologies are starting to produce extensive quantities of data from entire human genome or exome sequences, and therefore new software is needed to present and analyse this vast amount of information. The 1000 Genomes project has recently released raw data for 629 complete genomes representing several human populations through their Phase I interim analysis and, although there are certain public tools available that allow exploration of these genomes, to date there is no tool that permits comprehensive population analysis of the variation catalogued by such data.DescriptionWe have developed a genetic variant site explorer able to retrieve data for Single Nucleotide Variation (SNVs), population by population, from entire genomes without compromising future scalability and agility. ENGINES (ENtire Genome INterface for Exploring SNVs) uses data from the 1000 Genomes Phase I to demonstrate its capacity to handle large amounts of genetic variation (>7.3 billion genotypes and 28 million SNVs), as well as deriving summary statistics of interest for medical and population genetics applications. The whole dataset is pre-processed and summarized into a data mart accessible through a web interface. The query system allows the combination and comparison of each available population sample, while searching by rs-number list, chromosome region, or genes of interest. Frequency and FST filters are available to further refine queries, while results can be visually compared with other large-scale Single Nucleotide Polymorphism (SNP) repositories such as HapMap or Perlegen.ConclusionsENGINES is capable of accessing large-scale variation data repositories in a fast and comprehensive manner. It allows quick browsing of whole genome variation, while providing statistical information for each variant site such as allele frequency, heterozygosity or FST values for genetic differentiation. Access to the data mart generating scripts and to the web interface is granted from http://spsmart.cesga.es/engines.php.

Dataset Information

Investigating Human Mitochondrial Genomes in Single Cells.

Publications

Investigating Human Mitochondrial Genomes in Single Cells.

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