Home > Articles > Published articles > Extreme differences between human germline and tumor mutation densities are driven by ancestral human-specific deviations |
Date: | 2020 |
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. |
Grants: | Ministerio de Economía y Competitividad BFU2017-86471-P Ministerio de Economía y Competitividad BFU2015-68649-P Ministerio de Ciencia e Innovación FJCI-2016-29558 Agencia Estatal de Investigación PGC2018-101927-BI00 Instituto de Salud Carlos III PT17-0009-0020 Ministerio de Ciencia e Innovación CEXS2028-000792-M Agència de Gestió d'Ajuts Universitaris i de Recerca 2017-SGR-880 |
Rights: | Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. |
Language: | Anglès |
Document: | Article ; recerca ; Versió publicada |
Subject: | Cancer ; Evolutionary genetics ; Mutation |
Published in: | Nature communications, Vol. 11 (May 2020) , art. 2512, ISSN 2041-1723 |
9 p, 2.2 MB |