<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Heredia-Genestar, José María</style></author><author><style face="normal" font="default" size="100%">Marques-Bonet, Tomas</style></author><author><style face="normal" font="default" size="100%">Juan, David</style></author><author><style face="normal" font="default" size="100%">Navarro, Arcadi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Extreme differences between human germline and tumor mutation densities are driven by ancestral human-specific deviations</style></title><secondary-title><style face="normal" font="default" size="100%">Nature Communications</style></secondary-title><short-title><style face="normal" font="default" size="100%">Nature Communications</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020/05/19</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.nature.com/articles/s41467-020-16296-4#citeas</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">2512</style></pages><isbn><style face="normal" font="default" size="100%">2041-1723</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;
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