2026-04-17T03:56:50Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/2118802025-12-04T19:31:32Zcom_2072_1057col_2072_478908col_2072_478917

00925njm 22002777a 4500 dc Arnedo Pac, Claudia author Muiños Ballester, Ferran author González Pérez, Abel David author López Bigas, Núria author 2024-05-24T16:16:50Z 2024-05-24T16:16:50Z 2024-01-01 2024-05-23T11:13:14Z The sparsity of mutations observed across tumours hinders our ability to study mutation rate variability at nucleotide resolution. To circumvent this, here we investigated the propensity of mutational processes to form mutational hotspots as a readout of their mutation rate variability at single base resolution. Mutational signatures 1 and 17 have the highest hotspot propensity (5-78 times higher than other processes). After accounting for trinucleotide mutational probabilities, sequence composition and mutational heterogeneity at 10 Kbp, most (94-95%) signature 17 hotspots remain unexplained, suggesting a significant role of local genomic features. For signature 1, the inclusion of genome-wide distribution of methylated CpG sites into models can explain most (80-100%) of the hotspot propensity. There is an increased hotspot propensity of signature 1 in normal tissues and de novo germline mutations. We demonstrate that hotspot propensity is a useful readout to assess the accuracy of mutation rate models at nucleotide resolution. This new approach and the findings derived from it open up new avenues for a range of somatic and germline studies investigating and modelling mutagenesis.© 2023. The Author(s). Mutació (Biologia) Nucleòtids Mutation (Biology) Nucleotides Hotspot propensity across mutational processes