De novomutation rates in sticklebacks

Abstract

Mutation rate is a fundamental parameter in population genetics. Apart from being an important scaling parameter for demographic and phylogenetic inference, it allows one to understand at what rate new genetic diversity is generated and what is the expected level of genetic diversity in a population at equilibrium. However, except for well-established model organisms, accurate estimates of de novo mutation rates are available for a very limited number of organisms from the wild. We estimated mutation rates (mu) in two marine populations of the nine-spined stickleback (Pungitius pungitius) with the aid of several 2- and 3-generational family pedigrees, deep (> 50x) whole genome re-sequencing and a high-quality reference genome. After stringent filtering, we discovered 295 germline mutations from 106 offspring translating to mu = 4.64 x 10 to the -9 and mu = 4.08 x 10 to the -9 per base, per generation, in the two populations, respectively. Twenty percent of the mutations were shared by full-sibs showing that the level of parental mosaicism was relatively high. Since the estimated mu was 3.2 times smaller than the commonly used substitution rate, recalibration with mu led to substantial increase in estimated divergence times between different stickleback species. Our estimates of de novo mutation rate should provide a useful resource for research focused on fish population genetics and that of sticklebacks in particular.

Estimating recent and historical effective population size of marine and freshwater sticklebacks

“…The input files were generated following Schiffels & Wang (2020), and along with mask files generated by bamCaller.py, the mappability masks (Kivikoski et al, 2021) were applied. Estimates were carried out with default settings, and the outputs were processed assuming mutation rate of 4.37⨉10 -9 per site per generation (Zhang et al, 2023) and a generation length of two years (DeFaveri et al, 2014). To conduct bootstrap estimations, the input data were chopped into 1 Mb blocks and an artificial 400 Mb long genome was generated by random sampling with replacement.…”