Evidence map›Paper›PMID 42638110›Full record

ArticleGenome biology2026

Determinants of mutation susceptibility along the genome are largely invariant across human tissues.

Corinna Lewis Schmalohr, Yashna Paul, Nina Bundschuh, Andreas Beyer

Abstract read
In one paragraph

Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Corinna Lewis SchmalohrCologne Excellence Cluster for Aging and Aging-Associated Diseases (CECAD), University of Cologne, 50931, Cologne, Germany.
Yashna PaulCologne Excellence Cluster for Aging and Aging-Associated Diseases (CECAD), University of Cologne, 50931, Cologne, Germany.
Nina BundschuhCologne Excellence Cluster for Aging and Aging-Associated Diseases (CECAD), University of Cologne, 50931, Cologne, Germany.
Andreas BeyerCologne Excellence Cluster for Aging and Aging-Associated Diseases (CECAD), University of Cologne, 50931, Cologne, Germany. andreas.beyer@uni-koeln.de.ORCID https://orcid.org/0000-0002-3891-2123

Funding

Deutsche Forschungsgemeinschaft CRC 1678, grant agreement no. 520471345Deutsche Forschungsgemeinschaft, Germany CECAD EXC 2030 - 390661388Deutsche Forschungsgemeinschaft, Germany CRC 1310, grant agreement no. 325931972
6 · The paper itself

Abstract

backgroundThe 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.

resultsHere, 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.

conclusionsOur 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.

Indexed as

Genome, HumanMutationMutation RateChromatinHumansModels, GeneticNeoplasmsOrgan SpecificityPoint MutationChromatinChromatin contextMachine learningMutation susceptibilitySequence contextSNVsSomatic mutations

Identifiers

PMID42638110
PMCPMC13501610

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.