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

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

Published: 2023-02-14 DOI: 10.1038/s41596-022-00795-3

chromatin accessibility

mitochondrial single-cell ATAC-seq

multi-omic detection

mtDNA genotyping

clonal relationships

AI 解读

Generation of mouse–human chimeric embryos

Genome-wide quantification of transcription factor binding at single-DNA-molecule resolution using methyl-transferase footprinting

Generation of CRISPR–Cas9-mediated genetic knockout human intestinal tissue–derived enteroid lines by lentivirus transduction and single-cell cloning

A puromycin-dependent activity-based sensing probe for histochemical staining of hydrogen peroxide in cells and animal tissues

Decoding personal biotic and abiotic airborne exposome

A clinically relevant model of focal embolic cerebral ischemia by thrombus and thrombolysis in rhesus monkeys

Bioengineering human intestinal mucosal grafts using patient-derived organoids, fibroblasts and scaffolds

Biomimetic tail-to-head terpene cyclizations using the resorcin[4]arene capsule catalyst

Neuroscience robotics for controlled induction and real-time assessment of hallucinations

Scanorama: integrating large and diverse single-cell transcriptomic datasets

Single-cell RNA sequencing (scRNA-seq)（单细胞RNA测序）

Data integration（数据集成）

Heterogeneity（异质性）

查看全部

Sections

Figures

References

Natural sequence variation within mitochondrial DNA (mtDNA) contributes to human phenotypes and may serve as natural genetic markers in human cells for clonal and lineage tracing. We recently developed a single-cell multi-omic approach, called ‘mi
Introduction
Materials
Procedure
Troubleshooting
Timing
Anticipated results
- References
- References
References
ACKNOWLEDGMENTS

Baron, C. S. & van Oudenaarden, A. Unravelling cellular relationships during development and regeneration using genetic lineage tracing. Nat. Rev. Mol. Cell Biol. 20, 753–765 (2019).
VanHorn, S. & Morris, S. A. Next-generation lineage tracing and fate mapping to interrogate development. Dev. Cell 56, 7–21 (2021).
Wagner, D. E. & Klein, A. M. Lineage tracing meets single-cell omics: opportunities and challenges. Nat. Rev. Genet. 21, 410–427 (2020).
Woodworth, M. B., Girskis, K. M. & Walsh, C. A. Building a lineage from single cells: genetic techniques for cell lineage tracking. Nat. Rev. Genet. 18, 230–244 (2017).
Biasco, L. et al. In vivo tracking of human hematopoiesis reveals patterns of clonal dynamics during early and steady-state reconstitution phases. Cell Stem Cell 19, 107–119 (2016).
Ferrari, S. et al. Efficient gene editing of human long-term hematopoietic stem cells validated by clonal tracking. Nat. Biotechnol. 38, 1298–1308 (2020).
Park, S. et al. Clonal dynamics in early human embryogenesis inferred from somatic mutation. Nature 597, 393–397 (2021).
Coorens, T. H. H. et al. Extensive phylogenies of human development inferred from somatic mutations. Nature 597, 387–392 (2021).
Lodato, M. A. et al. Somatic mutation in single human neurons tracks developmental and transcriptional history. Science 350, 94–98 (2015).
Lee-Six, H. et al. Population dynamics of normal human blood inferred from somatic mutations. Nature 561, 473–478 (2018).
Brunner, S. F. et al. Somatic mutations and clonal dynamics in healthy and cirrhotic human liver. Nature 574, 538–542 (2019).
Macaulay, I. C. et al. G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nat. Methods 12, 519–522 (2015).
Ludwig, L. S. et al. Lineage tracing in humans enabled by mitochondrial mutations and single-cell genomics. Cell 176, 1325–1339.e22 (2019).
Xu, J. et al. Single-cell lineage tracing by endogenous mutations enriched in transposase accessible mitochondrial DNA. Elife 8, e45105 (2019).
Lareau, C. A. et al. Massively parallel single-cell mitochondrial DNA genotyping and chromatin profiling. Nat. Biotechnol. 39, 451–461 (2021).
Penter, L. et al. Longitudinal single-cell dynamics of chromatin accessibility and mitochondrial mutations in chronic lymphocytic leukemia mirror disease history. Cancer Discov. 11, 3048–3063 (2021).
Taylor, R. W. et al. Mitochondrial DNA mutations in human colonic crypt stem cells. J. Clin. Invest. 112, 1351–1360 (2003).
Teixeira, V. H. et al. Stochastic homeostasis in human airway epithelium is achieved by neutral competition of basal cell progenitors. Elife 2, e00966 (2013).
Stewart, J. B. & Chinnery, P. F. The dynamics of mitochondrial DNA heteroplasmy: implications for human health and disease. Nat. Rev. Genet. 16, 530–542 (2015).
Kang, E. et al. Age-related accumulation of somatic mitochondrial DNA mutations in adult-derived human iPSCs. Cell Stem Cell 18, 625–636 (2016).
Walker, M. A. et al. Purifying selection against pathogenic mitochondrial DNA in human T cells. N. Engl. J. Med. 383, 1556–1563 (2020).
Corces, M. R. et al. Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution. Nat. Genet. 48, 1193–1203 (2016).
Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017).
Montefiori, L. et al. Reducing mitochondrial reads in ATAC-seq using CRISPR/Cas9. Sci. Rep. 7, 1–9 (2017).
Fiskin, E. et al. Single-cell profiling of proteins and chromatin accessibility using PHAGE-ATAC. Nat. Biotechnol. 40, 374–381 (2022).
Mimitou, E. P. et al. Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells. Nat. Biotechnol. 39, 1246–1258 (2021).
Santibanez-Koref, M. et al. Assessing mitochondrial heteroplasmy using next generation sequencing: a note of caution. Mitochondrion 46, 302–306 (2019).
Laricchia, K. M. et al. Mitochondrial DNA variation across 56,434 individuals in gnomAD. Genome Res. 32, 569–582 (2022).
Maude, H. et al. NUMT confounding biases mitochondrial heteroplasmy calls in favor of the reference allele. Front. Cell Dev. Biol. 7, 201 (2019).
Satpathy, A. T. et al. Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion. Nat. Biotechnol. 37, 925–936 (2019).
Tang, Z. et al. A genetic bottleneck of mitochondrial DNA during human lymphocyte development. Mol. Biol. Evol. 39, msac090 (2022).
Lareau, C. A. et al. Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility. Nat. Biotechnol. 37, 916–924 (2019).
Domcke, S. et al. A human cell atlas of fetal chromatin accessibility. Science 370, eaba7612 (2020).
Buenrostro, J. D. et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523, 486–490 (2015).
Cusanovich, D. A. et al. Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing. Science 348, 910–914 (2015).
Basu, U., Bostwick, A. M., Das, K., Dittenhafer-Reed, K. E. & Patel, S. S. Structure, mechanism, and regulation of mitochondrial DNA transcription initiation. J. Biol. Chem. 295, 18406–18425 (2020).
Miller, T. E. et al. Mitochondrial variant enrichment from high-throughput single-cell RNA sequencing resolves clonal populations. Nat. Biotechnol. 40, 1030–1034 (2022).
Mulqueen, R. M. et al. High-content single-cell combinatorial indexing. Nat. Biotechnol. 39, 1574–1580 (2021).
Nam, A. S. et al. Somatic mutations and cell identity linked by Genotyping of Transcriptomes. Nature 571, 355–360 (2019).
Rodriguez-Meira, A. et al. Unravelling intratumoral heterogeneity through high-sensitivity single-cell mutational analysis and parallel RNA sequencing. Mol. Cell 73, 1292–1305.e8 (2019).
Stoeckius, M. et al. Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865–868 (2017).
Triska, P. et al. Landscape of germline and somatic mitochondrial DNA mutations in pediatric malignancies. Cancer Res. 79, 1318–1330 (2019).
Slyper, M. et al. A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors. Nat. Med. 26, 792–802 (2020).
Qian, J. et al. A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling. Cell Res. 30, 745–762 (2020).
Wakiro, I. et al. HTAPP_Dissociation of human ovarian cancer resection to a single-cell suspension for single-cell RNA-seq. Available at http://www.protocols.io/view/htapp-dissociation-of-human-ovarian-cancer-resecti-bhbhj2j6 (2020).
Swanson, E. et al. Simultaneous trimodal single-cell measurement of transcripts, epitopes, and chromatin accessibility using TEA-seq. Elife 10, e63632 (2021).
Chen, X. et al. ATAC-see reveals the accessible genome by transposase-mediated imaging and sequencing. Nat. Methods 13, 1013–1020 (2016).
Stoler, N. & Nekrutenko, A. Sequencing error profiles of Illumina sequencing instruments. NAR Genom. Bioinform. 3, lqab019 (2021).
Stuart, T., Srivastava, A., Madad, S., Lareau, C. A. & Satija, R. Single-cell chromatin state analysis with Signac. Nat. Methods 18, 1333–1341 (2021).
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26, 589–595 (2010).
Granja, J. M. et al. ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. Nat. Genet. 53, 403–411 (2021).
Van der Auwera, G. A. et al. From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr. Protoc. Bioinform. 43, 11.10.1–11.10.33 (2013).

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

推荐阅读