What can we learn about the distribution of fitness effects of new mutations from DNA sequence data?

Abstract

We investigate several questions concerning the inference of the distribution of fitness effects (DFE) of new mutations from the distribution of nucleotide frequencies in a population sample. If a fixed sequencing effort is available, we find that the optimum strategy is to sequence a modest number of alleles (approx. 10). If full genome information is available, the accuracy of parameter estimates increases as the number of alleles sequenced increases, but with diminishing returns. It is unlikely that the DFE for single genes can be reliably estimated in organisms such as humans and Drosophila, unless genes are very large and we sequence hundreds or perhaps thousands of alleles. We consider models involving several discrete classes of mutations in which the selection strength and density apportioned to each class can vary. Models with three classes fit almost as well as four class models unless many hundreds of alleles are sequenced. Large numbers of alleles need to be sequenced to accurately estimate the distribution's mean and variance. Estimating complex DFEs may therefore be difficult. Finally, we examine models involving slightly advantageous mutations. We show that the distribution of the absolute strength of selection is well estimated if mutations are assumed to be unconditionally deleterious.

Fitness effects of derived deleterious mutations in four closely related wild tomato species with spatial structure

“…The shape of the deleterious DFE distribution was fixed at b ¼ 0.1. This value is conservative for assessments of power, as for strongly leptokurtic shapes the estimates of the mean and variance of the g distribution are most inaccurate (Keightley and Eyre-Walker, 2010). Similar simulations were run with a more platikurtic g distribution (b ¼ 50).…”

“…The DFE can be summarized as four values representing the proportions of mutations falling into given ranges of ÀN e E(s), as used by Gossmann et al (2010) and Keightley and Eyre-Walker (2010). We show that this summary of the DFE can discriminate between the different purifying selection regimes (Figures 1a and b).…”

“…Methods to measure selection, thus, attempt to estimate the past demography of species, usually based on S sites, and simultaneously or subsequently compute the effects of selection (positive or negative) on NS and NC sites (Eyre-Walker and . Such methods have so far been applied mainly to model organisms for which genome-wide polymorphism data are available (humans, Drosophila, S. cerevisiae and Arabidopsis; Wright and Andolfatto, 2008;Eyre-Walker and Keightley, 2009;Keightley and Eyre-Walker, 2010; but see Gossmann et al, 2010 andSlotte et al, 2010 for recent studies on other plant species).…”

The population genetics of mutations: good, bad and indifferent

“…In their paper in this issue, Keightley & Eyre-Walker (2010) show that one of the most robust findings from research on DMEs is that the effects span many orders of magnitude. It is well known that some deleterious mutations are lethal while others appear to be effectively neutral in all population genetic tests, implying that heterozygous selection coefficient s of mutants ranges from 21 (lethal) to more neutral than 210 27 (effectively neutral for some Drosophila species).…”

“…Our knowledge of DMEs has come from laboratory experiments like that of Trindade et al (2010) and from population genetics approaches as used by Keightley & Eyre-Walker (2010), both of which are reported in this issue. Experimental approaches for inferring DMEs are based on mutation accumulation experiments pioneered by Mukai in Drosophila (Mukai et al 1972;Keightley & Eyre-Walker 1999;Lynch et al 1999), and one of the most extensive experiments of this type was completed by Charlesworth et al (2004).…”