Population sequencing data reveal a compendium of mutational processes in the human germ line

It has become increasing clear that mutation affects phenotypic variation and disease risk across humans. However, there are many different types of mutation. Seplyarskiy et al. applied a matrix factorization method to large human genomic datasets to identify germline mutational processes in an unsupervised manner. From this survey, nine robust mutational components were identified and specific mechanisms generating seven of these processes were proposed from correlations with genomic features. These results confirm and improve upon our understanding of mutational processes and reveal likely mechanisms of mutation in the human genome. Science , aba7408, this issue p. [1030][1] Biological mechanisms underlying human germline mutations remain largely unknown. We statistically decompose variation in the rate and spectra of mutations along the genome using volume-regularized nonnegative matrix factorization. The analysis of a sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. We provide a biological interpretation for seven of these processes. We associate one process with bulky DNA lesions that are resolved asymmetrically with respect to transcription and replication. Two processes track direction of replication fork and replication timing, respectively. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions and a mutagenic effect of long interspersed nuclear elements. We localize a mutagenic process specific to oocytes from population sequencing data. This process appears transcriptionally asymmetric. [1]: /lookup/doi/10.1126/science.aba7408