Mitochondrial single-cell ATAC-seq for high-throughput multi-omic detection of mitochondrial genotypes and chromatin accessibility

Lareau, Caleb A.; Liu, Vincent; Praktiknjo, Samantha D.; Nitsch, Lena; Kautz, Pauline; Sandor, Katalin; Yin, Yijun; Gutierrez, Jacob C.; Pelka, Karin; Satpathy, Ansuman T.; Regev, Aviv; Sankaran, Vijay G.; Ludwig, Leif S.

doi:10.1038/s41596-022-00795-3

Cited by 26 publications

(11 citation statements)

References 54 publications

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“…However, the landscape of mtDNA mosaicism in normal cells remains unclear, mainly because of the technical challenges in detecting low heteroplasmic variants. Although single-cell ATAC sequencing has been applied to the mitochondrial genome 46,47 , sensitive detection of mtDNA alterations is difficult because of the insufficient mtDNA depth per cell 48 .…”

Section: Introductionmentioning

confidence: 99%

Mitochondrial DNA mosaicism in human normal somatic cells

Ju,

An,

Nam

et al. 2023

Preprint

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Genomic alterations accumulate in the somatic cells throughout an individual’s lifetime1-5. Recent sequencing studies have documented widespread mutations in the nuclear genome and the frequent clonal competition of normal cells carrying mutations6-11. However, the landscape of mitochondrial DNA (mtDNA) heteroplasmy in normal human tissues is poorly understood. In this study, we investigated the whole genome sequences of 2,096 clones established from single cells obtained from 31 donors. We identified 6,451 mtDNA variants with >0.3% heteroplasmy in the clones. Approximately 6% of these variants originated from fertilized eggs, suggesting pervasive mtDNA heteroplasmy in the first cell of our life, despite the purification bottleneck in the maternal germline12,13. Using the landscape of variants in the fertilized egg, sporadic mutations (88%) and hotspot variants (6%), we determined two fundamental components that shape mtDNA heteroplasmy in somatic cells: the absolute mutation rate in mtDNA (1.01x10-7 per bp) and the frequency of mtDNA turnovers (22-43 turnovers per year varying across cell types). We found that a dominant mutational signature exhibiting extreme replication strand bias was mainly responsible for sporadic mutations, and the expansion of truncating mutations was substantially repressed in the somatic lineages. Cross-comparison between DNA and RNA sequences further confirmed that mtDNA localized in the stems of tRNA and rRNA had an impact on the regulation of mtDNA transcripts. Despite extensive inter-clonal and inter-individual heterogeneity in the mtDNA copy number per cell, the cellular transcriptional profiles were surprisingly uniform. Taken together, our findings provide comprehensive insights into the origin and dynamics of heteroplasmy levels, and the functional consequences of mtDNA variants in human somatic cells.

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Section: Introductionmentioning

confidence: 99%

Mitochondrial DNA mosaicism in human normal somatic cells

Ju,

An,

Nam

et al. 2023

Preprint

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“…Indeed, the ATAC-Seq nuclei isolation and tagmentation protocol may not be optimal for capturing protein-DNA interactions in Mycoplasma. However, given the success of ATAC-Seq protocols in reliably capturing accessibility within mitochondrial DNA – indeed mitochondrial mapping reads are treated as an unavoidable experimental nuisance that have now been mined to provide useful accessibility data [ 32 , 33 ] - it is likely that the same applies to Mycoplasma . Furthermore, the extent of mycoplasma contamination across labs worldwide is a clear indicator that are conditions under which Mycoplasma thrive and are very successful, thus our observations are likely to underpin Mycoplasma gene regulation under more stringent conditions also.…”

Section: Resultsmentioning

confidence: 99%

The Mycoplasma hyorhinis genome displays differential chromatin accessibility

Taylor

Walsh

Ashton

et al. 2023

Heliyon

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“…Cofea first applies TF-IDF transformation to the input peak-by-cell matrix following Signac [ 22 ], a widely used toolkit for scCAS data analysis [ 48–51 ]. For an input scCAS dataset, considering the element \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} ${x}_{ij}$\end{document} , which represents the count value of the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} $i$\end{document} th peak of the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} $j$\end{document} th cell in the peak-by-cell matrix \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} $X$\end{document} , the TF-IDF transformation could be formulated as follows:…”

Section: Methodsmentioning

confidence: 99%

Cofea: correlation-based feature selection for single-cell chromatin accessibility data

Li,

Chen,

Song

et al. 2023

Briefings in Bioinformatics

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Single-cell chromatin accessibility sequencing (scCAS) technologies have enabled characterizing the epigenomic heterogeneity of individual cells. However, the identification of features of scCAS data that are relevant to underlying biological processes remains a significant gap. Here, we introduce a novel method Cofea, to fill this gap. Through comprehensive experiments on 5 simulated and 54 real datasets, Cofea demonstrates its superiority in capturing cellular heterogeneity and facilitating downstream analysis. Applying this method to identification of cell type-specific peaks and candidate enhancers, as well as pathway enrichment analysis and partitioned heritability analysis, we illustrate the potential of Cofea to uncover functional biological process.

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Mitochondrial single-cell ATAC-seq for high-throughput multi-omic detection of mitochondrial genotypes and chromatin accessibility

Cited by 26 publications

References 54 publications

Mitochondrial DNA mosaicism in human normal somatic cells

Mitochondrial DNA mosaicism in human normal somatic cells

The Mycoplasma hyorhinis genome displays differential chromatin accessibility

Cofea: correlation-based feature selection for single-cell chromatin accessibility data

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