The mutational landscape of human somatic and germline cells
During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.
- 85 samples
- DAC: EGAC00001000000
- Technology: Illumina HiSeq 4000
- PUB DUO:0000019 (version: 2021-02-23)publication requiredThis data use modifier indicates that requestor agrees to make results of studies using the data available to the larger scientific community.
- US DUO:0000026 (version: 2021-02-23)user specific restrictionThis data use modifier indicates that use is limited to use by approved users.
- IS DUO:0000028 (version: 2021-02-23)institution specific restrictionThis data use modifier indicates that use is limited to use within an approved institution.
- GRU DUO:0000042 (version: 2021-02-23)general research useThis data use permission indicates that use is allowed for general research use for any research purpose.
Wellcome Trust Sanger Institute Cancer Genome Group Data Sharing Policy
Studies are experimental investigations of a particular phenomenon, e.g., case-control studies on a particular trait or cancer research projects reporting matching cancer normal genomes from patients.
| Study ID | Study Title | Study Type |
|---|---|---|
| EGAS00001003952 | Cancer Genomics |
This table displays only public information pertaining to the files in the dataset. If you wish to access this dataset, please submit a request. If you already have access to these data files, please consult the download documentation.