Estimating the distribution of fitness effects for deleterious mutations and implications for detecting adaptive introgression

Thu, Sep 13, 2018, 12:00 pm

Many mutations that occur in genomes are deleterious, resulting in a decrease in reproductive fitness. In this talk, I will present our recent work on estimating fitness effects of deleterious mutations using genetic variation data from natural populations. First, I will discuss our new computational approach, FitDadi, to estimate fitness effects and how this approach leads to improved estimates of the proportion of deleterious mutations in the human genome. Second, I will show that the distribution of fitness effects for amino acid changing mutations differs across species, and that Fisher’s geometric model can explain these patterns. Third, I will describe how we estimate both fitness effects and dominance effects of new mutations by combining genetic variation data from outcrossing and selfing species of Arabidopsis. We find that most deleterious mutations tend to be partially recessive, with strongly deleterious mutations being more recessive. Based on these results, we propose a new model for the evolution of dominance. Lastly, I will show how deleterious mutations can mimic signatures of adaptive introgression in genomes

Guyot 10
Ecology and Evolutionary Biology
Open to public

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