197: Somatic Mutation and Selection at Population Scale

️ Episode 197: Somatic Mutation and Selection at Population Scale In this episode of PaperCast Base by Base, we explore how ultra-accurate NanoSeq duplex sequencing reveals the hidden landscape of somatic mutations and clonal selection across blood and oral epithelium in over a thousand adults. Study Highlights:This study introduces improved whole-genome and targeted versions of NanoSeq, a duplex sequencing method with error rates below five mutations per billion base pairs, enabling reliable detection of single-molecule variants in highly polyclonal tissues. By applying targeted NanoSeq to 1,042 buccal swabs and 371 blood samples from a twins cohort, the authors map age-related somatic mutation rates and identify 46 genes under positive selection in oral epithelium, yielding more than 62,000 cancer-driver mutations. They also uncover negative selection against truncating variants in essential genes, generating in vivo saturation mutagenesis maps that distinguish activating hotspots from deleterious loss-of-function sites. Mutational signature analyses reveal a ubiquitous clock-like process and an alcohol-associated signature whose burdens vary widely between individuals and correlate with lifestyle factors such as tobacco use, alcohol consumption, and poor oral health. Twin-based and germline analyses further suggest that inherited variants, including a locus near ALDH2, can modulate somatic mutation signatures and driver landscapes. Conclusion:Accurate single-molecule sequencing at population scale shows that normal tissues are mosaics of tiny driver-mutant clones shaped by age, environment, and germline background, opening a path toward mechanistic cancer epidemiology and new biomarkers for early carcinogenesis. Music:Enjoy the music based on this article at the end of the episode. Reference:Lawson ARJ, Abascal F, Nicola PA, et al. Somatic mutation and selection at population scale. Nature. 2025;647:411–419. https://doi.org/10.1038/s41586-025-09584-w License:This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support:If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.com/  

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