Project Summary Mutations drive evolution, account for genetic variants in the population, and are the primary cause of cancer and other genetic disorders. Yet our molecular understanding of the biochemical processes that cause mutations remains rudimentary. For most mutational processes, we do not understand why the mutational probabilities vary by many orders of magnitude depending on the type of base substitution and sequence context. Most mutational patterns cannot be explained by the 1D sequence or 3D structural characteristics of the DNA motif in which they are found. While mutational processes due to exogenous sources (e.g. UV, smoking) have been described extensively, studies increasingly point to DNA replicative errors as an important and potentially dominant source of disease-causing mutations. However, the molecular mechanisms that underlie DNA replicative errors and their contributions to oncogenesis are not fully understood. In addition, over half of the mutational processes identified in human cancers have unknown biochemical origins. The main hypothesis in this proposal is that DNA dynamics that alter the mode of base pairing is a major driver of mutational processes. The project will experimentally characterize sequence and mismatch-dependent DNA base pair dynamics with unprecedented breadth and depth, and generate conformational propensities describing the sequence-specific probabilities of forming alternative mutagenic conformations. This knowledge will be used to develop a predictive understanding of replication errors generated by human polymerase ?, one of two polymerases tasked with eukaryotic nuclear DNA replication. The critical and necessary technological innovation is the development of breakthrough techniques for measuring DNA structural dynamics in high throughput, enabling studies of over hundreds and in some cases thousands of sequence variants. Aim 1 will determine the propensities for various mismatches to form Watson-Crick like conformations, measure the signatures of replicative error for proofreading deficient human polymerase ?, and advance a predictive model for sequence- and mismatch- dependent nucleotide misincorporation. Aim 2 will determine the propensities to sample unpaired conformations, measure the signatures of replicative error for proofreading proficient human polymerase ?, and advance a predictive model for sequence- and mismatch-dependent replicative errors. Aim 3 will determine propensities to form Hoogsteen base pairs, and uncover mutational processes driven by Hoogsteen-mediated damage. By developing a deep and predictive understanding of DNA replication infidelity and damage, this work will help illuminate fundamental processes that drive evolution and oncogenesis while also providing a conceptual framework and experimental tools that can help catalyze the discovery and characterization of other mutagenic and biochemical processes driven by DNA dynamics.