A targeted next generation sequencing approach to develop robust, genotype-specific mutation profiles and uncover novel variants inSaccharomyces cerevisiae

Abstract

ABSTRACTDistinct mutation signatures arise from environmental exposures and/or from defects in metabolic pathways that promote genome stability. The presence of a particular mutation signature in a cell or a tumor can therefore predict the underlying mechanism of mutagenesis, which, in practice, may be clinically important. These insults to the genome often alter dNTP pools, which itself impacts replication fidelity. Therefore, the impact of altered dNTP pools should be considered when making mechanistic predictions based on mutation signatures. We developed a targeted deep-sequencing approach on theCAN1gene inSaccharomyces cerevisiaeto define information-rich mutational profiles associated with distinctrnr1backgrounds that alter replication fidelity by elevating dNTP levels.. The mutation spectra ofrnr1Y285Fandrnr1Y285Aalleles were characterized previously; our analysis was consistent with this prior work but the sequencing depth achieved in our study allowed a significantly more robust and nuanced computational analysis of the variants observed, generating profiles that integrated information about mutation spectra, position effects, and sequence context. This approach revealed novel, genotype-specific mutation profiles in the presence of even modest changes in dNTP pools. Furthermore, we identified broader sequence contexts and specific nucleotide motifs that influenced variant profiles in differentrnr1backgrounds, which allowed us to make specific mechanistic predictions about the impact of altered dNTP pools on replication fidelity.