DNA replication timing and higher-order nuclear organization determine single-nucleotide substitution patterns in cancer genomes

Abstract

Single-nucleotide substitutions are a defining characteristic of cancer genomes. Many single-nucleotide substitutions in cancer genomes arise because of errors in DNA replication, which is spatio-temporally stratified. Here we propose that DNA replication patterns help shape the mutational landscapes of normal and cancer genomes. Using data on five fully sequenced cancer types and two personal genomes, we determined that the frequency of intergenic single-nucleotide substitution is significantly higher in late DNA replication timing regions, even after controlling for a number of genomic features. Furthermore, some substitution signatures are more frequent in certain DNA replication timing zones. Finally, integrating data on higher-order nuclear organization, we found that genomic regions in close spatial proximity to late-replicating domains display similar mutation spectra as the late-replicating regions themselves. These data suggest that DNA replication timing together with higher-order genomic organization contribute to the patterns of single-nucleotide substitution in normal and cancer genomes.

Figure 1. Effects of DNA replication timing on mutation rates

The figure shows the Adjusted Intergenic Mutation Frequency (AIMF) for regions residing within constant early (purple) and constant late DNA replication timing zones (orange) for completely sequenced genomes of five cancer types and two personal genomes: (A) melanoma of study 1 (1 sample), (B) melanoma of study 2 (25 samples in total), (C) prostate cancer (7 samples in total), (D) small cell lung cancer (1 sample), (E) chronic lymphocytic leukemia (4 samples in total), (F) colorectal cancer (9 samples in total), (G) Watson and (H) HuRef genomes. The AIMF represents the number of single nucleotide substitutions observed per base pair in the Filtered Intergenic Regions (FIR), which overlap with constant early and constant late DNA replication timing zones, respectively. The horizontal axes display the results for chr1 – chr22 and chrX.

Figure 2. Relationship between DNA replication timing and substitution patterns

The figure shows the proportions of different types of single nucleotide substitutions in the constant early (purple) and constant late (orange) DNA replication timing zones for completely sequenced genomes of five cancer types and two personal genomes: (A) melanoma of study 1, (B) melanoma of study 2, (C) prostate cancer, (D) small cell lung cancer, (E) chronic lymphocytic leukemia, (F) colorectal cancer, (G) Watson and (H) HuRef genomes. The proportions were calculated based on the hg18 reference allele so that Prob(A→C: T→G) + Prob(A→G: T→C) + Prob(A→T: T→A) = 100%, and Prob(C→A: G→T) + Prob(C→T: G→A) + Prob(C→G: G→C) = 100% for each of the constant late and constant early categories. Note that A→T: T→A is a signature commonly higher in late replication timing in all cancer types. Using the Chi-squared test and correcting for multiple hypothesis testing by false discovery rate, (B), (C), (G) and (H) are significantly different with adjusted p-values less than 0.01.

Figure 3. Higher-order nuclear architecture is associated with mutation frequencies

The figure shows the Adjusted Intergenic Mutation Frequency (AIMF) in the ‘transition-to-late’ regions defined by different numbers of Hi-C interaction counts from the GM06990 cell line between regions inside and outside the constant late DNA replication timing zones for (A) the melanoma sample of study 1, (B) melanoma samples of study 2, (C) prostate cancer samples, (D) the small cell lung cancer sample, (E) chronic lymphocytic leukemia samples, and (F) colorectal cancer samples. Statistical significance was evaluated using simple linear regression, and p-values were obtained. All p-values were less than 0.01. The green bar shows the genome-wide AIMF, the orange bar the AIMF in constant late DNA replication timing FIR, and the purple bar the AIMF in constant early DNA replication timing FIR. The blue dashed line, i.e. the fitted linear model, shows the positive association between the AIMF and the Hi-C counts that was used to stratify the regions. Due to the small mutation number in the chronic lymphocytic leukemia genome, we only used 2–8 Hi-C counts in panel D. The x-axes display the groups of regions stratified by the number of Hi-C interactions with constant late replication timing regions.

Figure 4. Effects of transition regions on mutation frequencies

The figure shows the Adjusted Intergenic Mutation Frequency (AIMF) for (A) the melanoma sample of study 1, (B) melanoma samples of study 2, (C) prostate cancer samples, (D) the small cell lung cancer sample, (E) chronic lymphocytic leukemia samples, and (F) colorectal cancer samples, in four groups of adjusted intergenic regions: constant late replication timing regions linked with constant late replication timing regions by Hi-C interactions (purple); constant late replication timing regions linked with constant early replication timing regions by Hi-C interactions (green); constant early replication timing regions linked with constant late replication timing regions by Hi-C interactions (gold); and constant early replication timing regions linked with constant early replication timing regions by Hi-C interactions (red). The x-axes display the groups of paired regions stratified by the number of Hi-C reads (2 – 10). All pairwise comparisons were significantly different from each other (Mann-Whitney U-test, false discovery rate-adjusted p-values < 0.03 in all cases).