Mutation In Finite Population Research Articles

Current hypotheses for the evolution of sex and recombination

The evolution of sex is one of the most important and controversial problems in evolutionary biology. Although sex is almost universal in higher animals and plants, its inherent costs have made its maintenance difficult to explain. The most famous of these is the twofold cost of males, which can greatly reduce the fecundity of a sexual population, compared to a population of asexual females. Over the past century, multiple hypotheses, along with experimental evidence to support these, have been put forward to explain widespread costly sex. In this review, we outline some of the most prominent theories, along with the experimental and observational evidence supporting these. Historically, there have been 4 classes of theories: the ability of sex to fix multiple novel advantageous mutants (Fisher-Muller hypothesis); sex as a mechanism to stop the build-up of deleterious mutations in finite populations (Muller's ratchet); recombination creating novel genotypes that can resist infection by parasites (Red Queen hypothesis); and the ability of sex to purge bad genomes if deleterious mutations act synergistically (mutational deterministic hypothesis). Current theoretical and experimental evidence seems to favor the hypothesis that sex breaks down selection interference between new mutants, or it acts as a mechanism to shuffle genotypes in order to repel parasitic invasion. However, there is still a need to collect more data from natural populations and experimental studies, which can be used to test different hypotheses.

A Density-Dependent Switch Drives Stochastic Clustering and Polarization of Signaling Molecules

Positive feedback plays a key role in the ability of signaling molecules to form highly localized clusters in the membrane or cytosol of cells. Such clustering can occur in the absence of localizing mechanisms such as pre-existing spatial cues, diffusional barriers, or molecular cross-linking. What prevents positive feedback from amplifying inevitable biological noise when an un-clustered “off” state is desired? And, what limits the spread of clusters when an “on” state is desired? Here, we show that a minimal positive feedback circuit provides the general principle for both suppressing and amplifying noise: below a critical density of signaling molecules, clustering switches off; above this threshold, highly localized clusters are recurrently generated. Clustering occurs only in the stochastic regime, suggesting that finite sizes of molecular populations cannot be ignored in signal transduction networks. The emergence of a dominant cluster for finite numbers of molecules is partly a phenomenon of random sampling, analogous to the fixation or loss of neutral mutations in finite populations. We refer to our model as the “neutral drift polarity model.” Regulating the density of signaling molecules provides a simple mechanism for a positive feedback circuit to robustly switch between clustered and un-clustered states. The intrinsic ability of positive feedback both to create and suppress clustering is a general mechanism that could operate within diverse biological networks to create dynamic spatial organization.

TOWARD A SELECTION THEORY OF MOLECULAR EVOLUTION

The Neutral Theory Models describing the dynamics of genetic variants with no effect on fitness—so-called neutral models—have been around almost as long as the field of population genetics (Fisher 1922; Wright 1931). Decades after the first models were introduced Motoo Kimura gave a complete description of the dynamics of neutral mutations in finite populations, using mathematical tools borrowed from particle physics (Kimura 1955). Although the elegance of this and other results from Kimura and colleagues were uncontested, their applicability to data seemed remote until experiments revealed enormous amounts of molecular genetic variation, both within and between species (Zuckerkandl and Pauling 1965; Harris 1966; Lewontin and Hubby 1966). The observed levels of variation appeared inconsistent with models that proposed selective effects for all or most mutations, and what has become known as the Neutral Theory of Molecular Evolution was born (Kimura 1968; King and Jukes 1969; Kimura and Ohta 1971). Despite contentious argument over the validity of the Neutral Theory (Kimura 1983; Gillespie 1991), it has become the predominant framework for research in population genetics and molecular evolution for almost 40 years. Increasingly complex models describing the expected patterns of variation within and between species allow researchers to ask about the evolutionary processes acting in nature, both at single loci and in increasingly large datasets encompassing all or most genes in a genome. The Neutral Theory provides a theoretical basis for understanding DNA variation with clear, testable hypotheses and an array of statistical tools that distinguish natural selection from random genetic drift (Kreitman 2000; Nielsen 2001; Hahn 2007). However, the recent paper by Begun and colleagues (Begun et al. 2007) should finally begin to change people’s view of this scientific paradigm. Although results inconsistent with the Neutral Theory have been mounting for some time (see below), the field has continued to use it as a foundation for understanding the molecular world. As the first true “population genomic” dataset, the results of Begun et al. force us to see that the central predictions of the Neutral Theory do not hold in natural populations. Far from just the half-caught glimpses of nonneutral evolution afforded by studies of limited numbers of loci, by sequencing the whole genomes of multiple lines of Drosophila simulans this work should cause a major shift in how we interpret DNA variation within populations and among species. As the conclusions of this article are appropriately cautious with respect to the implications of the work, I will use this essay to provide a wider view of the importance of these results and a synthesis with previous results. To do this I will address the two major tenets of the Neutral Theory, and how increasing amounts of data are showing that these claims and their attendant predictions do not hold for the vast majority of genes and species. I also argue that the implications of our continued use of neutral models are dire—at

Estimation of the rate and effects of deleterious genomic mutations in finite populations with linkage disequilibrium

Under several assumptions such as infinite population size with unlinked loci at linkage equilibrium (LD) under mutation-selection (M-S) balance, the rate (U), and the average effects (dominance and selection coefficients h and s) of deleterious genomic mutations (DGM) can be estimated by the Deng-Lynch method in some natural populations. However, all natural populations are finite in size and many of them are not large enough to be considered as approximately infinite. In the absence of an analytical estimation approach to characterize DGM in finite populations, we test the robustness and applicability of the Deng-Lynch method in finite populations with computer simulations. The results indicate that the estimation obtained by the Deng-Lynch method in finite populations with LD is generally robust when population size is greater than 400. With constant mutation effects, in outcrossing populations, the estimates U and ĥ are unbiased or only slightly upwardly biased, and ŝ is unbiased for most cases. In highly selfing populations, U and ĥ are upwardly biased, U is no more than 1.5U and ĥ is less than 1.1 h, and ŝ is either unbiased or slightly downwardly biased. With variable mutation effects, U ranges from 0.56 to 0.72U, and s ranges from 1.4 to 1.8s. Generally speaking, with the same finite population size, the estimation in outcrossing populations is better than in highly selfing populations. Given that even the order of the magnitude of the parameters of DMG (U in particular) is controversial, our investigation here may provide a basis for using the Deng-Lynch method to characterize DGM in finite populations of size greater than 400 in the presence of LD.

A computer simulation evaluation of the role of mutations in finite populations on the response to directional selection: The generations required to attain maximum genetic variance

The role of mutations in finite populations on response to artificial selection was investigated by a computer simulation model designed to mimic the biological model of pupal weight of Tribolium. Given the model, the results showed that with selection about 25-55 generations were needed for genetic variances to reach a maximum value depending on population size, selection intensity, and gene number. When effective population size was larger than 40 or the intensity of selection was high (less than 50% selected), selection had a dramatic effect in reducing the time to approach the maximum point of genetic variance. Furthermore, the genetic variance after that point often declined as a function of selection instead of remaining at a steady state in the subsequent generations.

Variances and covariances of squared linkage disequilibria in finite populations

Analysis of linkage disequilibrium D among restriction sites or bases in DNA sequences, arising from mutations in finite populations, depends on a knowledge of the variance-covariance structure of measures such as D 2 between different pairs of sites. This requires evaluation of the eighth moments of gene frequencies among two, three, and four loci, and the necessary methodology is derived here and results are computed. While primary emphasis is placed on disequilibrium arising from mutation or gene conversion, the methodology also allows for the joint effects of only drift and recombination. Numerical results confirm that squared linkage disequilibria can have high variances and covariances.

Effects of linkage on response to directional selection from new mutations.

SUMMARYThe influence of linkage on the rates of response to continued directional selection of quantitative traits deriving from variation contributed by new mutations in finite populations is investigated. Mutant genes are assumed to have additive effects which are randomly sampled from a symmetric distribution, and to be randomly located on the chromosome. Results were obtained by Monte Carlo simulation.The expected steady rate of response, when variability from new mutations is balanced by that lost by drift and selection, is reduced the tighter the linkage, but the reduction is small unless there are few, short chromosomes. For a given rate of new mutational variance per haploid chromosome set per generation, greater effects of linkage are obtained in large than in small populations, because more mutants segregate. The response and influence of linkage are essentially the same whether the new variance is due to many genes of small effect or few of large effect.The variability of response between replicates and generations was investigated, and the contribution to this of new mutants or recombination of existing mutants compared. Usually most genetic variability was due to the occurrence of a new favourable mutant of large effect.

Linkage disequilibrium, genetic distance and evolutionary distance under a general model of linked genes or a part of the genome

SummaryA general model of linked genes or a part of a genome is proposed which enables us to study various problems in molecular population genetics in a unified way. Several formulae with special reference to the linkage disequilibrium and genetic distance are derived for neutral mutations in finite populations, based on the method of diffusion equations. It is argued that the model and formulae are useful particularly when observations are made in terms of DNA sequence.

Linkage disequilibrium among multiple neutral alleles produced by mutation in finite population

An analysis is undertaken for a finite random mating population of the linkage disequilibrium between two loci, at both of which all alleles are neutral, all mutant alleles differ from existing ones and several may be segregating at any time. Formulae are derived for the expected total squared disequilibrium, measured as the sum of squares of disequilibria between all pairs of alleles. The ratio of this quantity to the expected value of the product of the heterozygosities at the two loci is similar to that obtained previously by Ohta and Kimura for two nucleotide sites at each of which not more than two mutant types can segregate at any time.

Protein polymorphism as a phase of molecular evolution.

It is proposed that random genetic drift of neutral mutations in finite populations can account for observed protein polymorphisms.