The effect of multiple paternity on genetic diversity during and after colonisation

The effect of multiple paternity on genetic diversity during and after colonisation

M. Rafajlovic, A. Eriksson, A. Rimark, S. H. Saltin, G. Charrier, M. Panova, C. André, K. Johannesson, B. Mehlig
(Submitted on 5 Nov 2012)

In metapopulations, genetic variation of local populations is influenced by the genetic content of the founders, and of migrants following establishment. We analyse the effect of multiple paternity on genetic diversity using a model in which the highly promiscuous marine snail Littorina saxatilis expands from a mainland to colonise initially empty islands of an archipelago. Migrant females carry a large number of eggs fertilised by 1 – 10 mates. We quantify the genetic diversity of the population in terms of its heterozygosity: initially during the transient colonisation process, and at long times when the population has reached an equilibrium state with migration. During colonisation, multiple paternity increases the heterozygosity by 10 – 300 % in comparison with the case of single paternity. The equilibrium state, by contrast, is less strongly affected: multiple paternity gives rise to 10 – 50 % higher heterozygosity compared with single paternity. Further we find that far from the mainland, new mutations spreading from the mainland cause bursts of high genetic diversity separated by long periods of low diversity. This effect is boosted by multiple paternity. We conclude that multiple paternity facilitates colonisation and maintenance of small populations, whether or not this is the main cause for the evolution of extreme promiscuity in Littorina saxatilis.

Genomic mutation rates that neutralize adaptive evolution and natural selection

Genomic mutation rates that neutralize adaptive evolution and natural selection

Philip Gerrish, Alexandre Colato, Paul Sniegowski
(Submitted on 5 Nov 2012)

When mutation rates are low, natural selection remains effective, and increasing the mutation rate can give rise to an increase in adaptation rate. When mutation rates are high to begin with, however, increasing the mutation rate may have a detrimental effect because of the overwhelming presence of deleterious mutations. Indeed, if mutation rates are high enough: 1) adaptation rate can become negative despite the continued availability of adaptive and/or compensatory mutations, or 2) natural selection may be disabled because adaptive and/or compensatory mutations — whether established or newly-arising — are eroded by excessive mutation and decline in frequency. We apply these two criteria to a standard model of asexual adaptive evolution and derive mathematical expressions — some new, some old in new guise — delineating the mutation rates under which either adaptive evolution or natural selection is neutralized. The expressions are simple and require no \emph{a priori} knowledge of organism- and/or environment-specific parameters. Our discussion connects these results to each other and to previous theory, showing convergence or equivalence of the different results in most cases.

Response to Horizontal gene transfer may explain variation in θs

Response to Horizontal gene transfer may explain variation in \theta_s

Inigo Martincorena, Nicholas M. Luscombe
(Submitted on 5 Nov 2012)

In a short article submitted to ArXiv [1], Maddamsetti et al. argue that the variation in the neutral mutation rate among genes in Escherichia coli that we recently reported [2] might be explained by horizontal gene transfer (HGT). To support their argument they present a reanalysis of synonymous diversity in 10 E.coli strains together with an analysis of a collection of 1,069 synonymous mutations found in repair-deficient strains in a long-term in vitro evolution experiment. Here we respond to this communication. Briefly, we explain that HGT was carefully accounted for in our study by multiple independent phylogenetic and population genetic approaches, and we show that there is no new evidence of HGT affecting our results. We also argue that caution must be exercised when comparing mutations from repair deficient strains to data from wild-type strains, as these conditions are dominated by different mutational processes. Finally, we reanalyse Maddamsetti’s collection of mutations from a long-term in vitro experiment and we report preliminary evidence of non-random variation of the mutation rate in these repair deficient strains.

Our paper: The McDonald-Kreitman Test and its Extensions under Frequent Adaptation: Problems and Solutions

For our next guest post Philipp Messer and Dmitri Petrov write about their paper
The McDonald-Kreitman Test and its Extensions under Frequent Adaptation: Problems and Solutions, arXived here

The McDonald-Kreitman (MK) test is the basis of most modern approaches to measure the rate of adaptation from population genomic data. This test was used to argue that in some organisms, such as Drosophila, the rate of adaptation is surprisingly high. However, the MK test, and in fact most of the current machinery of population genetics, relies on the assumption that adaptation is rare so that the effects of selective sweeps on linked variation can be neglected. We test this assumption using a powerful forward simulation and show that the MK test is severely biased even when the rate of adaptation is only moderate. The biases arise from the complex linkage effects between slightly deleterious and strongly advantageous mutations. In order to deal with these biases, we suggest a new robust approach based on a simple asymptotic extension of the MK test.

We further show that already under very moderate amounts of adaptation, linkage effects from recurrent selective sweeps can profoundly affect key population genetic parameters, such as the fixation probabilities of deleterious mutations and the frequency distributions of polymorphisms. In synonymous polymorphism data, these linkage effects leave signatures that can easily be mistaken for the signatures of recent, severe population expansion.

The bigger claim of our paper is that the effects of linked selection cannot be simply swept under the rug by introducing effective parameters, such as effective population size or effective strength of selection, and then using these effective parameters in formulae derived from the diffusion approximation under the assumption of free recombination. Given that most of our estimates of the key evolutionary parameters are still obtained from methods based on this paradigm, we argue that it is crucial to verify whether they are robust to linkage effects.

Philipp Messer and Dmitri Petrov

Inference of Admixture Parameters in Human Populations Using Weighted Linkage Disequilibrium

Inference of Admixture Parameters in Human Populations Using Weighted Linkage Disequilibrium

Po-Ru Loh, Mark Lipson, Nick Patterson, Priya Moorjani, Joseph K Pickrell, David Reich, Bonnie Berger
(Submitted on 1 Nov 2012)

Long-range migrations and the resulting admixture between populations have been an important force shaping human genetic diversity. Most existing methods for detecting and reconstructing historical admixture events are based on allele frequency divergences or patterns of ancestry segments in chromosomes of admixed individuals. An emerging new approach harnesses the exponential decay of admixture-induced linkage disequilibrium (LD) as a function of genetic distance. Here, we comprehensively develop LD-based inference into a versatile tool for investigating admixture. We present a new weighted LD statistic that can be used to infer mixture proportions as well as dates with fewer constraints on reference populations than previous methods. We define an LD-based three-population test for admixture and identify scenarios in which it can detect admixture that previous formal tests cannot. We further show that we can discover phylogenetic relationships between populations by comparing weighted LD curves obtained using a suite of references. Finally, we describe several improvements to the computation and fitting of weighted LD curves that greatly increase the robustness and speed of the computation. We implement all of these advances in a software package, ALDER, which we validate in simulations and apply to test for admixture among all populations from the Human Genome Diversity Project (HGDP), highlighting insights into the admixture history of Central African Pygmies, Sardinians, and Japanese.

The McDonald-Kreitman Test and its Extensions under Frequent Adaptation: Problems and Solutions

The McDonald-Kreitman Test and its Extensions under Frequent Adaptation: Problems and Solutions

Philipp W. Messer, Dmitri A. Petrov
(Submitted on 1 Nov 2012)

Population genomic studies have shown that genetic draft and background selection can profoundly affect the genome-wide patterns of molecular variation. We performed forward simulations under realistic gene-structure and selection scenarios to investigate whether such linkage effects impinge on the ability of the McDonald-Kreitman (MK) test to infer the rate of positive selection (\alpha) from polymorphism and divergence data. We find that in the presence of slightly deleterious mutations, MK estimates of \alpha\ severely underestimate the true rate of adaptation even if all polymorphisms with population frequencies under 50% are excluded. Furthermore, already under intermediate rates of adaptation, genetic draft substantially distorts the site frequency spectra at neutral and functional sites from the expectations under mutation-selection-drift balance. MK-type approaches that first infer demography from synonymous sites and then use the inferred demography to correct the estimation of \alpha\ obtain almost the correct \alpha\ in our simulations. However, these approaches typically infer a severe past population expansion although there was no such expansion in the simulations, casting doubt on the accuracy of methods that infer demography from synonymous polymorphism data. We suggest a simple asymptotic extension of the MK test that should yield accurate estimates of \alpha\ even in the presence of linkage effects.

The evolution of genetic architectures underlying quantitative traits

The evolution of genetic architectures underlying quantitative traits
Etienne Rajon, Joshua B. Plotkin
(Submitted on 31 Oct 2012)

In the classic view introduced by R.A. Fisher, a quantitative trait is encoded by many loci with small, additive effects. Recent advances in QTL mapping have begun to elucidate the genetic architectures underlying vast numbers of phenotypes across diverse taxa, producing observations that sometimes contrast with Fisher’s blueprint. Despite these considerable empirical efforts to map the genetic determinants of traits, it remains poorly understood how the genetic architecture of a trait should evolve, or how it depends on the selection pressures on the trait. Here we develop a simple, population-genetic model for the evolution of genetic architectures. Our model predicts that traits under moderate selection should be encoded by many loci with highly variable effects, whereas traits under either weak or strong selection should be encoded by relatively few loci. We compare these theoretical predictions to qualitative trends in the genetics of human traits, and to systematic data on the genetics of gene expression levels in yeast. Our analysis provides an evolutionary explanation for broad empirical patterns in the genetic basis of traits, and it introduces a single framework that unifies the diversity of observed genetic architectures, ranging from Mendelian to Fisherian.