International Journal of Molecular SciencesGenomicsPeer-reviewed journal article
Immortalization of different breast epithelial cell types results in distinct mitochondrial mutagenesis
Abstract
Different phenotypes of normal cells might influence genetic profiles, epigenetic profiles, and tumorigenicities of their transformed derivatives. In this study, we investigated whether the whole mitochondrial genome of immortalized cells can be attributed to different phenotypes (stem vs non-stem) of their normal epithelial cell originators. To accurately determine mutations, we employed Duplex Sequencing, which exhibits the lowest error rates among currently available DNA sequencing methods. Our results indicate that the vast majority of observed mutations of the whole mitochondrial DNA occur at low-frequency (rare mutations). The most prevalent rare mutation types are C[->]T/G[->]A and A[->]G/T[->]C transitions. Frequencies and spectra of homoplasmic point mutations are virtually identical between stem cell-derived immortalized (SV1) cells and non-stem cell-derived immortalized (SV22) cells, verifying that both cell types were derived from the same woman. However, frequencies of rare point mutations are significantly lower in SV1 cells (5.79x10-5) than in SV22 cells (1.16x10-4). Additionally, the predicted pathogenicity for rare mutations in the mitochondrial tRNA genes is significantly lower (by 2.5-fold) in SV1 cells than in SV22 cells. Our findings suggest that the immortalization of normal cells with stem cell features leads to decreased mitochondrial mutagenesis, particularly in noncoding RNA regions. The mutation spectra and mutations specific to stem cell-derived immortalized cells (vs non-stem cell derived) have implications in characterizing heterogeneity of tumors and understanding the role of mitochondrial mutations in immortalization and transformation of human cells.
- organism: human
- assay: DNA methylation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: variant calling
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 4
- FWCI
- 0.08
- Field percentile
- 38th percentile
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