During the course of a lifetime, somatic cells acquire mutations. Different mutational processes may contribute to the mutations accumulated in a cell, with each imprinting a mutational signature on the cell's genome. Some processes generate mutations throughout life at a constant rate in all individuals, and the number of mutations in a cell attributable to these processes will be proportional to the chronological age of the person. Using mutations from 10,250 cancer genomes across 36 cancer types, we investigated clock-like mutational processes that have been operating in normal human cells. Two mutational signatures show clock-like properties. Both exhibit different mutation rates in different tissues. However, their mutation rates are not correlated, indicating that the underlying processes are subject to different biological influences. For one signature, the rate of cell division may influence its mutation rate. This study provides the first survey of clock-like mutational processes operating in human somatic cells.
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We would like to thank M.E. Hurles and R. Durbin for early discussions about the analyses performed. We would like to thank The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC) and the authors of all previous studies cited in Supplementary Data Set 1 for providing free access to their somatic mutational data. This work was supported by the Wellcome Trust (grant 098051). S.N.-Z. is a Wellcome-Beit Prize Fellow and is supported through a Wellcome Trust Intermediate Fellowship (grant WT100183MA). P.J.C. is personally funded through a Wellcome Trust Senior Clinical Research Fellowship (grant WT088340MA). J.E.S. is supported by an MRC grant to the Laboratory of Molecular Biology (MC_U105178808). L.B.A. is supported through a J. Robert Oppenheimer Fellowship at Los Alamos National Laboratory. P.H.J. is supported by the Wellcome Trust, an MRC Grant-in-Aid and Cancer Research UK (programme grant C609/A17257). This research used resources provided by the Los Alamos National Laboratory Institutional Computing Program, which is supported by the US Department of Energy National Nuclear Security Administration under contract DE-AC52-06NA25396. Research performed at Los Alamos National Laboratory was carried out under the auspices of the National Nuclear Security Administration of the US Department of Energy.
MATLAB code for calculating the P values across individual cancer types.