Abstract
BackgroundStructural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood. Many SVs are thought to emerge from errors in the repair processes following DNA double strand breaks (DSBs).ResultsWe used experimentally quantified DSB frequencies in cell lines with matched chromatin and sequence features to derive the first quantitative genome-wide models of DSB susceptibility. These models are accurate and provide novel insights into the mutational mechanisms generating DSBs. Models trained in one cell type can be successfully applied to others, but a substantial proportion of DSBs appear to reflect cell type-specific processes. Using model predictions as a proxy for susceptibility to DSBs in tumors, many SV-enriched regions appear to be poorly explained by selectively neutral mutational bias alone. A substantial number of these regions show unexpectedly high SV breakpoint frequencies given their predicted susceptibility to mutation and are therefore credible targets of positive selection in tumors. These putatively positively selected SV hotspots are enriched for genes previously shown to be oncogenic. In contrast, several hundred regions across the genome show unexpectedly low levels of SVs, given their relatively high susceptibility to mutation. These novel coldspot regions appear to be subject to purifying selection in tumors and are enriched for active promoters and enhancers.ConclusionsWe conclude that models of DSB susceptibility offer a rigorous approach to the inference of SVs putatively subject to selection in tumors.
Highlights
Structural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood
These datasets include two novel double strand breaks (DSBs) mapping datasets derived from the K562 erythroleukemia and MCF7 breast cancer cell lines using the recently developed BLISS method [25] and two previously published DSB mapping datasets derived from the NHEK keratinocyte cell line using BLESS and DSBCapture [22] protocols
DSB frequency is defined in each dataset as the number of unique reads mapping to a given 50 kb region, since each read in a DSBCapture, BLESS, or BLISS experiment represents an exposed DNA DSB end
Summary
Structural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood. In analyses of tumor SNVs, variants are routinely prioritized based on algorithms including corrections for estimates of SNV mutation rate variation [11], but analogous methods are not yet applied to SVs. Variable rates of SVs observed across the genome are likely to be affected by differences in the efficiency of repair of DNA double strand breaks (DSBs). A third repair process, alternative NHEJ (alt-NHEJ) uses microhomology to mediate repairs when the c-NHEJ pathway is unavailable, and repair by alt-NHEJ appears to increase the rate of deletions, insertions, and translocations further [14] The efficiency of these repair processes is often dependent upon the chromatin features and nuclear organization present where the damage occurs. The associations between DSB repair and the underlying chromatin landscape may, explain the observed correlations between tumor SV rates and chromatin structure [9]
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