Mutations do not accumulate uniformly across the genome. Human germline and tumor mutation density correlate poorly, and each is associated with different genomic features. Here, we use non-human great ape (NHGA) germlines to determine human germline- and tumor-specific deviations from an ancestral-like great ape genome-wide mutational landscape. Strikingly, we find that the distribution of mutation densities in tumors presents a stronger correlation with NHGA than with human germlines. This effect is driven by human-specific differences in the distribution of mutations at non-CpG sites. We propose that ancestral human demographic events, together with the human-specific mutation slowdown, disrupted the human genome-wide distribution of mutation densities. Tumors partially recover this distribution by accumulating preneoplastic-like somatic mutations. Our results highlight the potential utility of using NHGA population data, rather than human controls, to establish the expected mutational background of healthy somatic cells.
%0 Journal Article
%1 herediagenestar2020extreme
%A Heredia-Genestar, José María
%A Marquès-Bonet, Tomàs
%A Juan, David
%A Navarro, Arcadi
%D 2020
%J Nature Communications
%K cancer mutation_motif mutation_spectrum
%N 1
%P 2512--
%R 10.1038/s41467-020-16296-4
%T Extreme differences between human germline and tumor mutation densities are driven by ancestral human-specific deviations
%U https://doi.org/10.1038/s41467-020-16296-4
%V 11
%X Mutations do not accumulate uniformly across the genome. Human germline and tumor mutation density correlate poorly, and each is associated with different genomic features. Here, we use non-human great ape (NHGA) germlines to determine human germline- and tumor-specific deviations from an ancestral-like great ape genome-wide mutational landscape. Strikingly, we find that the distribution of mutation densities in tumors presents a stronger correlation with NHGA than with human germlines. This effect is driven by human-specific differences in the distribution of mutations at non-CpG sites. We propose that ancestral human demographic events, together with the human-specific mutation slowdown, disrupted the human genome-wide distribution of mutation densities. Tumors partially recover this distribution by accumulating preneoplastic-like somatic mutations. Our results highlight the potential utility of using NHGA population data, rather than human controls, to establish the expected mutational background of healthy somatic cells.
@article{herediagenestar2020extreme,
abstract = {Mutations do not accumulate uniformly across the genome. Human germline and tumor mutation density correlate poorly, and each is associated with different genomic features. Here, we use non-human great ape (NHGA) germlines to determine human germline- and tumor-specific deviations from an ancestral-like great ape genome-wide mutational landscape. Strikingly, we find that the distribution of mutation densities in tumors presents a stronger correlation with NHGA than with human germlines. This effect is driven by human-specific differences in the distribution of mutations at non-CpG sites. We propose that ancestral human demographic events, together with the human-specific mutation slowdown, disrupted the human genome-wide distribution of mutation densities. Tumors partially recover this distribution by accumulating preneoplastic-like somatic mutations. Our results highlight the potential utility of using NHGA population data, rather than human controls, to establish the expected mutational background of healthy somatic cells.},
added-at = {2021-05-13T19:57:59.000+0200},
author = {Heredia-Genestar, José María and Marquès-Bonet, Tomàs and Juan, David and Navarro, Arcadi},
biburl = {https://www.bibsonomy.org/bibtex/263ff8d0eff7d784d6acf4630a5f1d45f/peter.ralph},
doi = {10.1038/s41467-020-16296-4},
interhash = {0125a3ed4274de51982be37c45f95787},
intrahash = {63ff8d0eff7d784d6acf4630a5f1d45f},
issn = {20411723},
journal = {Nature Communications},
keywords = {cancer mutation_motif mutation_spectrum},
number = 1,
pages = {2512--},
refid = {Heredia-Genestar2020},
timestamp = {2021-05-13T19:57:59.000+0200},
title = {Extreme differences between human germline and tumor mutation densities are driven by ancestral human-specific deviations},
url = {https://doi.org/10.1038/s41467-020-16296-4},
volume = 11,
year = 2020
}