The Impact of Environmental and Endogenous Damage on Somatic Mutation Load in Human Skin Fibroblasts

Abstract

Accumulation of somatic changes, due to environmental and endogenous lesions, in the human genome is associated with aging and cancer. Understanding the impacts of these processes on mutagenesis is fundamental to understanding the etiology, and improving the prognosis and prevention of cancers and other genetic diseases. Previous methods relying on either the generation of induced pluripotent stem cells, or sequencing of single-cell genomes were inherently error-prone and did not allow independent validation of the mutations. In the current study we eliminated these potential sources of error by high coverage genome sequencing of single-cell derived clonal fibroblast lineages, obtained after minimal propagation in culture, prepared from skin biopsies of two healthy adult humans. We report here accurate measurement of genome-wide magnitude and spectra of mutations accrued in skin fibroblasts of healthy adult humans. We found that every cell contains at least one chromosomal rearrangement and 600–13,000 base substitutions. The spectra and correlation of base substitutions with epigenomic features resemble many cancers. Moreover, because biopsies were taken from body parts differing by sun exposure, we can delineate the precise contributions of environmental and endogenous factors to the accrual of genetic changes within the same individual. We show here that UV-induced and endogenous DNA damage can have a comparable impact on the somatic mutation loads in skin fibroblasts. Trial Registration: ClinicalTrials.gov NCT01087307.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. Schematic for isolation and sequencing of single-cell fibroblast clonal lineages.

Example of Donor 1 is shown. Boxed insert illustrates the design of the clone IDs. Biopsy number is indicated if adjacent biopsies were taken from the same site.

Fig 2. Structural changes detected in skin fibroblast clones D1-L-F1 and D2-L-F.

(A) All genome changes detected in D1-L-F1 and D2-L-F clones. The tracks numbered from innermost are as follows: 1—structural changes. Green = deletions, black = duplications, blue = inversions and red = translocations. 2—deletions as detected by read-depth analyses. 3—amplifications as detected by read-depth analyses. 4—LOH events. 5—somatic SNVs, black dots are heterozygous SNVs and red dots are homozygous SNVs. (B) Schematic describing the chr19, chr20 translocation in D1-L-F1. Black rectangles depict region wherein translocation event was detected with a concomitant change in copy number.

Fig 3. Somatic mutation load and spectra in the fibroblast clones.

(A) The number of somatic mutations detected in each clone and the rate of accumulation of mutations per year are provided. (B) The spectra of base changes in the clones. For each base change the reverse complements are also included.

Fig 4. Analysis of mechanistic knowledge-based mutation signatures in the genomes of skin fibroblasts.

Similar analysis for the whole-genome sequenced melanoma (SKCM) cohort (dataset from [46]) is provided for comparison. (A) Fold enrichment of nCg →nTg and UV-signature mutations (yCn→yTn, nTt→nCt; y is either C or T, n is either A, T, G or C, in the trinucleotide context the mutated base is in capital). The black horizontal line denotes the level of no enrichment. (B) The minimum estimates of signature-specific mutation loads for each clone. For the melanoma cohort, the median of the minimum estimated mutation loads for each signature per genome in is shown. (C) Total CC→TT counts of tandem dinucleotide changes in each clone and the median of the total CC→TT counts per genome in the melanoma cohort.

Fig 5. Somatic mutation loads vary with replication timing and transcription status.

(A) SNVs from both, hips and forearms are enriched in late replicating genomic regions and heterochromatic regions of the genome. Values on the horizontal axis were obtained by averaging values of the genomic feature into 5 equal bins. (B) UV-attributable mutations demonstrate a strand bias for the non-transcribed strand. * denotes p-value after false discovery rate (FDR) correction for multiple hypothesis testing