bioRxivCancer BiologyPreprint
Germline and somatic variation influence nuclear-mitochondrial crosstalk in tumourigenesis
Maëlle DaunesseiD, Vasavi SundaramiD, Elissavet KentepozidouiD, John C. ConnellyiD, Craig J. AndersoniD, Núria López-BigasiD, Colin A M SempleiD, Duncan T. OdomiD, Martin S. TayloriD, Maša RolleriD, Sarah J. AitkeniD, Paul FlicekiD
Abstract
Hepatocellular carcinoma is the most prevalent primary liver cancer and arises from hepatocytes, which are very metabolically active and contain abundant mitochondria. Despite extensive characterisation of nuclear driver genes and pathways, the role of crosstalk between the mitochondrial and nuclear genomes in mitochondrial mutagenesis remains poorly understood. To address this, we leveraged a chemical carcinogenesis model of liver cancer in four mouse strains. We analysed hundreds of tumours with paired whole-genome sequencing and total RNA sequencing to comprehensively characterise mitochondrial mutations and expression. Following de novo assembly of strain-specific mitochondrial genomes, we devised an accurate and efficient heteroplasmy detection approach and analysed mitochondrial DNA (mtDNA) content and transcription. Across strains, there was high concordance of the number of heteroplasmies, mutation signatures, and variant allele frequencies. In contrast, the heteroplasmy rate and genic locations differed between strains, suggesting strain-specificity in DNA repair mechanisms in early tumour development. Independent of age or environmental factors, tumours had lower mtDNA content than adjacent normal liver, suggesting mitochondrial loss during tumourigenesis. Additionally, within individual strains, mtDNA content differences were associated with nuclear driver gene choice. Our comprehensive characterisation of mitochondrial genomes and expression patterns demonstrates that both germline and somatic genetic variation influence tumour mtDNA content, mutation patterns, and gene expression.
- organism: mouse
- assay: whole-genome sequencing
- assay: whole-exome sequencing
- research focus: variant calling
- research focus: differential expression
- approach: statistical model
- Citations
- 1
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