RT Journal Article SR Electronic T1 Deep sequencing of natural and experimental populations of Drosophila melanogaster reveals biases in the spectrum of new mutations JF bioRxiv FD Cold Spring Harbor Laboratory SP 095182 DO 10.1101/095182 A1 Zoe June Assaf A1 Susanne Tilk A1 Jane Park A1 Mark L. Siegal A1 Dmitri A. Petrov YR 2016 UL http://biorxiv.org/content/early/2016/12/18/095182.abstract AB Mutations provide the raw material of evolution, and thus our ability to study evolution depends fundamentally on whether we have precise measurements of mutational rates and patterns. Here we explore the rates and patterns of mutations using i) de novo mutations from Drosophila melanogaster mutation accumulation lines and ii) polymorphisms segregating at extremely low frequencies. The first, mutation accumulation (MA) lines, are the product of maintaining flies in tiny populations for many generations, therefore rendering natural selection ineffective and allowing new mutations to accrue in the genome. In addition to generating a novel dataset of sequenced MA lines, we perform a meta-analysis of all published MA studies in D. melanogaster, which allows more precise estimates of mutational patterns across the genome. In the second half of this work, we identify polymorphisms segregating at extremely low frequencies using several publicly available population genomic data sets from natural populations of D. melanogaster. Extremely rare polymorphisms are difficult to detect with high confidence due to the problem of distinguishing them from sequencing error, however a dataset of true rare polymorphisms would allow the quantification of mutational patterns. This is due to the fact that rare polymorphisms, much like de novo mutations, are on average younger and also relatively unaffected by the filter of natural selection. We identify a high quality set of ~70,000 rare polymorphisms, fully validated with resequencing, and use this dataset to measure mutational patterns in the genome. This includes identifying a high rate of multi-nucleotide mutation events at both short (~5bp) and long (~1kb) genomic distances, showing that mutation drives GC content lower in already GC-poor regions, and finding that the context-dependency of the mutation spectrum predicts long-term evolutionary patterns at four-fold synonymous sites. We also show that de novo mutations from independent mutation accumulation experiments display similar patterns of single nucleotide mutation, and match well the patterns of mutation found in natural populations.Author Summary Mutations provide the raw material of evolution, and thus our ability to study evolution depends fundamentally on whether we have precise measurements of mutational rates and patterns. Yet, because a large proportion of new mutations are detrimental, our ability to detect new mutations is severely limited. In this paper, we use both experimental and population genomic approaches to generate a large dataset of ~70,000 genetic variants in the fruit fly Drosophila melanogaster, and subsequently use these data to quantify rates and patterns of new mutations. We identify many interesting features of the mutation spectrum, including a high rate of multi-nucleotide mutation events and context-dependent mutational patterns.