Single-cell mtDNA dynamics in tumors is driven by coregulation of nuclear and mitochondrial genomes.


Journal

Nature genetics
ISSN: 1546-1718
Titre abrégé: Nat Genet
Pays: United States
ID NLM: 9216904

Informations de publication

Date de publication:
13 May 2024
Historique:
received: 21 06 2022
accepted: 20 03 2024
medline: 14 5 2024
pubmed: 14 5 2024
entrez: 13 5 2024
Statut: aheadofprint

Résumé

The extent of cell-to-cell variation in tumor mitochondrial DNA (mtDNA) copy number and genotype, and the phenotypic and evolutionary consequences of such variation, are poorly characterized. Here we use amplification-free single-cell whole-genome sequencing (Direct Library Prep (DLP+)) to simultaneously assay mtDNA copy number and nuclear DNA (nuDNA) in 72,275 single cells derived from immortalized cell lines, patient-derived xenografts and primary human tumors. Cells typically contained thousands of mtDNA copies, but variation in mtDNA copy number was extensive and strongly associated with cell size. Pervasive whole-genome doubling events in nuDNA associated with stoichiometrically balanced adaptations in mtDNA copy number, implying that mtDNA-to-nuDNA ratio, rather than mtDNA copy number itself, mediated downstream phenotypes. Finally, multimodal analysis of DLP+ and single-cell RNA sequencing identified both somatic loss-of-function and germline noncoding variants in mtDNA linked to heteroplasmy-dependent changes in mtDNA copy number and mitochondrial transcription, revealing phenotypic adaptations to disrupted nuclear/mitochondrial balance.

Identifiants

pubmed: 38741018
doi: 10.1038/s41588-024-01724-8
pii: 10.1038/s41588-024-01724-8
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Susan G. Komen (Susan G. Komen Breast Cancer Foundation)
ID : SAC220206
Organisme : U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
ID : P30-CA008748
Organisme : U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
ID : R37-CA276200
Organisme : U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
ID : R37-CA276200
Organisme : U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI)
ID : RM1-HG011014
Organisme : U.S. Department of Defense (United States Department of Defense)
ID : W81XWH-18-1-0318

Informations de copyright

© 2024. The Author(s).

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Auteurs

Minsoo Kim (M)

Tri-Institutional PhD Program in Computational Biology & Medicine, Weill Cornell Medicine, New York City, NY, USA.
Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Alexander N Gorelick (AN)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.
Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Ignacio Vàzquez-García (I)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Marc J Williams (MJ)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Sohrab Salehi (S)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Hongyu Shi (H)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Adam C Weiner (AC)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Nick Ceglia (N)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Tyler Funnell (T)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Tricia Park (T)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Sonia Boscenco (S)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Ciara H O'Flanagan (CH)

Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.

Hui Jiang (H)

Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Diljot Grewal (D)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Cerise Tang (C)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Nicole Rusk (N)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Payam A Gammage (PA)

Institute of Cancer Sciences, University of Glasgow, Glasgow, UK.
CRUK Beatson Institute, Glasgow, UK.

Andrew McPherson (A)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Sam Aparicio (S)

Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.

Sohrab P Shah (SP)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA. shahs3@mskcc.org.

Ed Reznik (E)

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA. reznike@mskcc.org.

Classifications MeSH