{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T04:23:27Z","timestamp":1787372607088,"version":"3.56.0"},"reference-count":0,"publisher":"Springer Science and Business Media LLC","license":[{"start":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T00:00:00Z","timestamp":1787356800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T00:00:00Z","timestamp":1787356800000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Deutsche Forschungsgemeinschaft, Germany","award":["CRC 1310, grant agreement no. 325931972"],"award-info":[{"award-number":["CRC 1310, grant agreement no. 325931972"]}]},{"name":"Deutsche Forschungsgemeinschaft, Germany","award":["CECAD EXC 2030 - 390661388"],"award-info":[{"award-number":["CECAD EXC 2030 - 390661388"]}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["CRC 1678, grant agreement no. 520471345"],"award-info":[{"award-number":["CRC 1678, grant agreement no. 520471345"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008001","name":"Universit\u00e4t zu K\u00f6ln","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100008001","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Genome Biol"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The propensity for accumulating somatic mutations varies along the genome, which critically influences somatic mosaicism, tumor evolution and the potential role of somatic mutations in the context of age-associated diseases. Genomic factors contributing to the variability of mutation rates have been established, including, for example, distance from the replication origin, chromatin structure and sequence context. However, their relative importance for explaining variable mutation rates along the genome as well as variable mutation rates between tissues remains elusive.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here, we present a modelling strategy that integrates 146 genomic features at different scales to predict susceptibilities for point mutations in 25 human tissues along the genome. These models faithfully predict mutation rates in coding and non-coding parts of the human genome in cancer and healthy tissues, including even unseen tissue types that were not used during the model training. Our work revealed that the dependency of mutation rates on chromatin structure and other genomic features is remarkably invariant across tissues, pointing to fundamental, conserved processes underlying mutagenic processes. Local variability in mutation rates on the scale of a few base pairs is almost exclusively driven by the sequence context, whereas large-scale variability is dominated by chromatin features, gene expression and GC content.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Our modelling strategy quantifies the relative contribution of genomic factors to mutation susceptibility, predicting mutational biases at any genomic resolution across human tissues, and provides a basis for better understanding tumor evolution and age-related diseases.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13059-026-04245-1","type":"journal-article","created":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T03:32:20Z","timestamp":1787369540000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Determinants of mutation susceptibility along the genome are largely invariant across human tissues"],"prefix":"10.1186","author":[{"given":"Corinna Lewis","family":"Schmalohr","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yashna","family":"Paul","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nina","family":"Bundschuh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3891-2123","authenticated-orcid":false,"given":"Andreas","family":"Beyer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,22]]},"container-title":["Genome Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13059-026-04245-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T03:32:22Z","timestamp":1787369542000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s13059-026-04245-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,22]]},"references-count":0,"alternative-id":["4245"],"URL":"https:\/\/doi.org\/10.1186\/s13059-026-04245-1","relation":{},"ISSN":["1474-760X"],"issn-type":[{"value":"1474-760X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,22]]},"assertion":[{"value":"26 November 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 August 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 August 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"All data used in this study were obtained from publicly available databases, including The Cancer Genome Atlas (TCGA), Pan-cancer analysis of whole genomes (PCAWG), UCSC Genome Browser, Genotype-Tissue Expression (GTEx) project, cBioPortal, and ENCODE. These databases contain de-identified data for which the original studies obtained appropriate ethical approval and informed consent from participants. No additional ethical approval was required for this secondary analysis of publicly available, de-identified data.","order":1,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}]}}