Diversifying selection drives parallel evolution of gill raker number and body size along the speciation continuum of European whitefish

Adaptive radiation is the evolution of ecological and phenotypical diversity. It arises via ecological opportunity that promotes the exploration of underutilized or novel niches mediating specialization and reproductive isolation. The assumed precondition for rapid local adaptation is diversifying natural selection, but random genetic drift could also be a major driver of this process. We used 27 populations of European whitefish (Coregonus lavaretus) from nine lakes distributed in three neighboring subarctic watercourses in northern Fennoscandia as a model to test the importance of random drift versus diversifying natural selection for parallel evolution of adaptive phenotypic traits. We contrasted variation for two key adaptive phenotypic traits correlated with resource utilization of polymorphic fish; the number of gill rakers and the total length of fish, with the posterior distribution of neutral genetic differentiation from 13 microsatellite loci, to test whether the observed phenotypic divergence could be achieved by random genetic drift alone. Our results show that both traits have been under diversifying selection and that the evolution of these morphs has been driven by isolation through habitat adaptations. We conclude that diversifying selection acting on gill raker number and body size has played a significant role in the ongoing adaptive radiation of European whitefish morphs in this region.     

TRANSLATING BETWEEN MICROEVOLUTIONARY PROCESS AND MACROEVOLUTIONARY PATTERNS: THE CORRELATION STRUCTURE OF INTERSPECIFIC DATA

As species evolve along a phylogenetic tree, we expect closely related species to retain some phenotypic similarities due to their shared evolutionary histories. The amount of expected similarity depends both on the hierarchical phylogenetic structure, and on the specific magnitude and types of evolutionary changes that accumulate during each generation. In this study, we show how models of microevolutionary change can be translated into the resulting macroevolutionary patterns. We illustrate how the structure of phenotypic covariances expected in interspecific measurements can be derived, and how this structure depends on the microevolutionary forces guiding phenotypic change at each generation. We then explore the covariance structure expected from several simple microevolutionary models of phenotypic evolution, including various combinations of random genetic drift, directional selection, stabilizing selection, and environmental change, as well as models of punctuated or burst-like evolution. We find that stabilizing selection leads to patterns of exponential decrease of between species covariance with phylogenetic distance. This is different from the usual linear patterns of decrease assumed in most comparative and systematic methods. Nevertheless, linear patterns of decrease can result from many processes in addition to random genetic drift, such as directional and fluctuating selection as well as modes of punctuated change. Our framework can be used to develop methods for (1) phylogenetic reconstruction; (2) inference of the evolutionary process from comparative data; and (3) conducting or evaluating statistical analyses of comparative data while taking phylogenetic history into account.     

Free fitness that always increases in evolution

I here introduce a free fitness function in population biology, which monotonically increases with time and takes its maximum at the evolutionary equilibrium. By suitably defining an "index" for each state, the free fitness is expressed as the average index plus an entropy term. In many cases, the index has a biologically clear meaning, such as the logarithmic population mean fitness. The technique is applicable to any Markov process model (either continuous or discrete) with a positive steady state. I discuss four examples from various branches of population biology: (1) one-locus-two-allele system of population genetics with mutation, selection, and random genetic drift; (2) evolutionary dynamics of quantitative characters; (3) a molecular evolution model; and (4) an ecological succession model. Introducing free fitness clarifies the balance between systematic forces (e.g. natural selection or successional trend toward the climax) and disturbing processes (e.g. random drift).     

Role of gene duplication in evolution

It is now known that many multigene and supergene families exist in eukaryote genomes: multigene families with uniform copy members like genes for ribosomal RNA, those with variable members like immunoglobulin genes, and supergene families such as those for various growth factor and hormone receptors. Many such examples indicate that gene duplication and subsequent differentiation are extremely important for organismal evolution. In particular, gene duplication could well have been the primary mechanism for the evolution of complexity in higher organisms. Population genetic models for the origin of gene families with diverse functions are presented, in which natural selection favors those genomes with more useful mutants in duplicated genes. Since any gene has a certain probability of degenerating by mutation, success versus failure in acquiring a new gene by duplication may be expressed as the ratio of probabilities of spreading of useful versus detrimental mutations in redundant gene copies. Also examined are the effects of gene duplication on evolution by compensatory advantageous mutations. Results of the analyses show that both natural selection and random drift are important for the origin of gene families. In addition, interaction between molecular mechanisms such as unequal crossing-over and gene conversion, and selection or drift is found to have a large effect on evolution by gene duplication.     

Robustness, evolvability, and neutrality

Biological systems, from macromolecules to whole organisms, are robust if they continue to function, survive, or reproduce when faced with mutations, environmental change, and internal noise. I focus here on biological systems that are robust to mutations and ask whether such systems are more or less evolvable, in the sense that they can acquire novel properties. The more robust a system is, the more mutations in it are neutral, that is, without phenotypic effect. I argue here that such neutral change--and thus robustness--can be a key to future evolutionary innovation, if one accepts that neutrality is not an essential feature of a mutation. That is, a once neutral mutation may cause phenotypic effects in a changed environment or genetic background. I argue that most, if not all, neutral mutations are of this sort, and that the essentialist notion of neutrality should be abandoned. This perspective reconciles two opposing views on the forces dominating organismal evolution, natural selection and random drift: neutral mutations occur and are especially abundant in robust systems, but they do not remain neutral indefinitely, and eventually become visible to natural selection, where some of them lead to evolutionary innovations.     

Detecting the Genomic Signature of Divergent Selection in Presence of Gene Flow

The study of local adaptation is a main focus of evolutionary biology since it may contribute to explain the current species diversity. The genomic scan procedures permit for the first time to study the connection between specific DNA patterns and processes as natural selection, genetic drift, recombination, mutation and gene flow. Accordingly, the information on genomes from non-model organisms increases and the interest on detecting the signal of natural selection in the DNA sequences of different populations also raises. The main goal of the present work is to explore a sequence-based method for detecting natural selection in divergent populations connected by migration. In doing so, we rely on a recently published statistic based upon th e definition of haplotype allelic classes (HAC). The original measure was modified to be more sensitive to intermediate frequencies in non-model species. A linkage-disequilibrium-based method was also assayed and individual-based simulations were performed to test the methods. The results suggest that the HAC-based methods and, specifically, the new proposed method are quite powerful for detecting the footprint of moderate divergent selection. They are also robust to reasonable model misspecification. One obvious advantage of the new algorithm is that it does not require knowledge of the allelic state.     

Selectionism and neutralism in molecular evolution

Charles Darwin proposed that evolution occurs primarily by natural selection, but this view has been controversial from the beginning. Two of the major opposing views have been mutationism and neutralism. Early molecular studies suggested that most amino acid substitutions in proteins are neutral or nearly neutral and the functional change of proteins occurs by a few key amino acid substitutions. This suggestion generated an intense controversy over selectionism and neutralism. This controversy is partially caused by Kimura's definition of neutrality, which was too strict (|2Ns|< or =1). If we define neutral mutations as the mutations that do not change the function of gene products appreciably, many controversies disappear because slightly deleterious and slightly advantageous mutations are engulfed by neutral mutations. The ratio of the rate of nonsynonymous nucleotide substitution to that of synonymous substitution is a useful quantity to study positive Darwinian selection operating at highly variable genetic loci, but it does not necessarily detect adaptively important codons. Previously, multigene families were thought to evolve following the model of concerted evolution, but new evidence indicates that most of them evolve by a birth-and-death process of duplicate genes. It is now clear that most phenotypic characters or genetic systems such as the adaptive immune system in vertebrates are controlled by the interaction of a number of multigene families, which are often evolutionarily related and are subject to birth-and-death evolution. Therefore, it is important to study the mechanisms of gene family interaction for understanding phenotypic evolution. Because gene duplication occurs more or less at random, phenotypic evolution contains some fortuitous elements, though the environmental factors also play an important role. The randomness of phenotypic evolution is qualitatively different from allele frequency changes by random genetic drift. However, there is some similarity between phenotypic and molecular evolution with respect to functional or environmental constraints and evolutionary rate. It appears that mutation (including gene duplication and other DNA changes) is the driving force of evolution at both the genic and the phenotypic levels.     

The use of genetic markers to measure genomic response to selection in livestock

A method to measure genomic response to natural and artificial selection by means of genetic markers in livestock is proposed. Genomic response through several levels of selection was measured using sequential testing for distorted segregation of alleles among selected and nonselected sons, single-sperm typing, and a test with records for growth performance. Statistical power at a significance level of 0.05 was >0.5 for a marker linked to a QTL with recombination fractions 0, 0.10, and 0.20 for detecting genomic responses for gene effects of 0.6, 0.7, and 1.0 phenotypic standard deviations, respectively. Genomic response to artificial selection in six commercial bull sire families comprising 285 half-sib sons selected for growth performance was measured using 282 genetic markers evenly distributed over the cattle genome. A genome-wide test using selected sons was significant (P < 0.001), indicating that selection induces changes in the genetic makeup of commercial cattle populations. Markers located in chromosomes 6, 10, and 16 identified regions in those chromosomes that are changing due to artificial selection as revealed by the association of records of performance with alleles at specific markers. Either natural selection or genetic drift may cause the observed genomic response for markers in chromosomes 1, 7, and 17.     

The genetics of adaptation: the roles of pleiotropy, stabilizing selection and drift in shaping the distribution of bidirectional fixed mutational effects

Pleiotropy allows for the deterministic fixation of bidirectional mutations: mutations with effects both in the direction of selection and opposite to selection for the same character. Mutations with deleterious effects on some characters can fix because of beneficial effects on other characters. This study analytically quantifies the expected frequency of mutations that fix with negative and positive effects on a character and the average size of a fixed effect on a character when a mutation pleiotropically affects from very few to many characters. The analysis allows for mutational distributions that vary in shape and provides a framework that would allow for varying the frequency at which mutations arise with deleterious and positive effects on characters. The results show that a large fraction of fixed mutations will have deleterious pleiotropic effects even when mutation affects as little as two characters and only directional selection is occurring, and, not surprisingly, as the degree of pleiotropy increases the frequency of fixed deleterious effects increases. As a point of comparison, we show how stabilizing selection and random genetic drift affect the bidirectional distribution of fixed mutational effects. The results are then applied to QTL studies that seek to find loci that contribute to phenotypic differences between populations or species. It is shown that QTL studies are biased against detecting chromosome regions that have deleterious pleiotropic effects on characters.     

Coming to Grips with Evolvability

To explain the evolution of complex organisms by random mutation, drift, and selection is not a trivial task. This becomes obvious if we imagine an organism in which most genes affect most traits and all mutations are immediately expressed in the phenotype. Most of the mutations will be deleterious. Computer programmers experienced a similar problem when trying to evolve computer programs by introducing random changes to a conventional computer code, realizing that almost all random changes are “lethal.” Everyone who has done any programming knows that conventional computer languages are very brittle! Real organisms are not organized in this way but rather involve mediation between the genes and the phenotypic traits, namely development, also sometimes called the genotype–phenotype map. This map of genetic effects is structured in a way that enables evolvability, that is, enhances the probability that mutations will improve the performance of the organism. Here we outline two properties of organismal development, namely modularity and robustness. Modularity refers to the situation in which genes affect a restricted number of functionally related phenotypic characters. Robustness describes a situation in which cryptic mutations can accumulate without effect on fitness but can become visible to selection in a new environment or genetic background. We discuss recent empirical evidence in support of both phenomena and their effect on evolvability and also briefly address their evolution.     

Gene, phenotype and function: GLABROUS1 and resistance to herbivory in natural populations of Arabidopsis lyrata

The molecular genetic basis of adaptive variation is of fundamental importance for evolutionary dynamics, but is still poorly known. Only in very few cases has the relationship between genetic variation at the molecular level, phenotype and function been established in natural populations. We examined the functional significance and genetic basis of a polymorphism in production of leaf hairs, trichomes, in the perennial herb Arabidopsis lyrata. Earlier studies suggested that trichome production is subject to divergent selection. Here we show that the production of trichomes is correlated with reduced damage from insect herbivores in natural populations, and using statistical methods developed for medical genetics we document an association between loss of trichome production and mutations in the regulatory gene GLABROUS1. Sequence data suggest that independent mutations in this regulatory gene have provided the basis for parallel evolution of reduced resistance to insect herbivores in different populations of A. lyrata and in the closely related Arabidopsis thaliana. The results show that candidate genes identified in model organisms provide a valuable starting point for analysis of the genetic basis of phenotypic variation in natural populations.     

DNA水平上检测正选择方法的研究进展

达尔文的自然选择学说指出, 自然选择作用是物种进化的主要因素。而1968年Kimura提出的中性进化学说认为中性突变和随机漂变才是进化的主要动力。在接下来的30多年时间中, 人们尝试从各种角度来检测自然选择是否存在。随着DNA测序技术的发展, 大量的DNA序列信息为检验自然选择提供了丰富的数据。因为自然选择会影响DNA变异模式, 所以可以通过分析现有的DNA样本来推断过去是否发生了自然选择。另一方面, 种群历史等因素也会影响到DNA变异模式, 因此会对自然选择的检测产生干扰。文章主要介绍了中性检验基本的概念, 全面回顾了一些经典的检验方法, 并着重介绍了近几年新发展出的研究方向。     

Genomic Targets of Positive Selection in Giant Mice from Gough Island

A key challenge in understanding how organisms adapt to their environments is to identify the mutations and genes that make it possible. By comparing patterns of sequence variation to neutral predictions across genomes, the targets of positive selection can be located. We applied this logic to house mice that invaded Gough Island (GI), an unusual population that shows phenotypic and ecological hallmarks of selection. We used massively parallel short-read sequencing to survey the genomes of 14 GI mice. We computed a set of summary statistics to capture diverse aspects of variation across these genome sequences, used approximate Bayesian computation to reconstruct a null demographic model, and then applied machine learning to estimate the posterior probability of positive selection in each region of the genome. Using a conservative threshold, 1,463 5-kb windows show strong evidence for positive selection in GI mice but not in a mainland reference population of German mice. Disproportionate shares of these selection windows contain genes that harbor derived nonsynonymous mutations with large frequency differences. Over-represented gene ontologies in selection windows emphasize neurological themes. Inspection of genomic regions harboring many selection windows with high posterior probabilities pointed to genes with known effects on exploratory behavior and body size as potential targets. Some genes in these regions contain candidate adaptive variants, including missense mutations and/or putative regulatory mutations. Our results provide a genomic portrait of adaptation to island conditions and position GI mice as a powerful system for understanding the genetic component of natural selection.     

FURTHER SIMULATION STUDIES ON EVOLUTION BY GENE DUPLICATION

In order to understand the origin of multigene families, Monte Carlo simulations were performed to see how a genetic system evolves under unequal crossing-over, mutation, random genetic drift and natural selection, starting from a single gene copy. Both haploid and diploid models were examined. Beneficial, neutral, and detrimental mutations were incorporated, and “positive” selection favors those chromosomes (haploid) or individuals (diploid) with more beneficial mutations than others. The same model for haploids was previously investigated with special reference to the evolution of gene organization, and the ratio of the numbers of beneficial genes to pseudogenes was found to be a rough indicator of the relative strengths of positive and negative (against deleterious alleles) natural selection (Ohta, 1987b). In the present paper, the evolution of gene organization and of sequence divergence among genes in the multigene family is examined. It is shown that positive selection accelerates the accumulation of arrays containing different beneficial mutations, but that total divergence including both neutral and beneficial mutations is not very sensitive to positive selection, under this model. The proportion of beneficial mutations in the total mutations accumulated is a better indicator of positive selection than is the total divergence. It is pointed out that various observed examples in which amino-acid substitutions are accelerated, as compared with synonymous substitutions in duplicated genes (Li, 1985), may reflect the effect of selection similar to the present scheme. The diploid model is shown to be more efficient for accumulating beneficial mutations in duplicated genes than the haploid one, and the relevance of this finding to the advantage of sexual reproduction is discussed.     

Self‐incompatibilty in gamete recognition: Single self‐recognizing determinants and multiple,non‐self‐recognizing ones function in the same individual

The frameworks (key mechanisms) of the self/non‐self‐discrimination systems that are found in various organisms have not been actively selected for, but have evolved by genetic drift such that the genetic frequency of random, advantageous mutations has increased within the genomes of these species by natural selection. The passive nature of this process leads to an important conclusion: in the self/non‐self‐discrimination system, the number of self‐recognizing determinants becomes one compared to multiple non‐self‐recognizing determinants. Thus, the number of determinants is defined not by the character of the determinant, but by the system framework. Mol. Reprod. Dev. 80: 2–7, 2013. © 2012 Wiley Periodicals, Inc.     

The stationary distribution of a continuously varying strategy in a class-structured population under mutation-selection-drift balance

Many traits and/or strategies expressed by organisms are quantitative phenotypes. Because populations are of finite size and genomes are subject to mutations, these continuously varying phenotypes are under the joint pressure of mutation, natural selection and random genetic drift. This article derives the stationary distribution for such a phenotype under a mutation-selection-drift balance in a class-structured population allowing for demographically varying class sizes and/or changing environmental conditions. The salient feature of the stationary distribution is that it can be entirely characterized in terms of the average size of the gene pool and Hamilton's inclusive fitness effect. The exploration of the phenotypic space varies exponentially with the cumulative inclusive fitness effect over state space, which determines an adaptive landscape. The peaks of the landscapes are those phenotypes that are candidate evolutionary stable strategies and can be determined by standard phenotypic selection gradient methods (e.g. evolutionary game theory, kin selection theory, adaptive dynamics). The curvature of the stationary distribution provides a measure of the stability by convergence of candidate evolutionary stable strategies, and it is evaluated explicitly for two biological scenarios: first, a coordination game, which illustrates that, for a multipeaked adaptive landscape, stochastically stable strategies can be singled out by letting the size of the gene pool grow large; second, a sex-allocation game for diploids and haplo-diploids, which suggests that the equilibrium sex ratio follows a Beta distribution with parameters depending on the features of the genetic system.     

Rapid divergence of genetic variance-covariance matrix within a natural population

The matrix of genetic variances and covariances (G matrix) represents the genetic architecture of multiple traits sharing developmental and genetic processes and is central for predicting phenotypic evolution. These predictions require that the G matrix be stable. Yet the timescale and conditions promoting G matrix stability in natural populations remain unclear. We studied stability of the G matrix in a 20-year evolution field experiment, where a population of the cosmopolitan parthenogenetic soil nematode Acrobeloides nanus was subjected to drift and divergent selection (benign and stress environments). Selection regime did not influence the level of absolute genetic constraints: under both regimes, two genetic dimensions for three life-history traits were identified. A substantial response to selection in principal components structure and in general matrix pattern was indicated by three statistical methods. G structure was also influenced by drift, with higher divergence under benign conditions. These results show that the G matrix might evolve rapidly in natural populations. The observed high dynamics of G structure probably represents the general feature of asexual species and limits the predictive power of G in phenotypic evolution analyses.     

Within- and between-species DNA sequence variation and the 'footprint' of natural selection

Extensive DNA data emerging from genome-sequencing projects have revitalized interest in the mechanisms of molecular evolution. Although the contribution of natural selection at the molecular level has been debated for over 30 years, the relevant data and appropriate statistical methods to address this issue have only begun to emerge. This paper will first present the predominant models of neutral, nearly neutral, and adaptive molecular evolution. Then, a method to identify the role of natural selection in molecular evolution by comparing within- and between-species DNA sequence variation will be presented. Computer simulations show that such methods are powerful for detecting even very weak selection. Examination of DNA variation data within and between Drosophila species suggests that 'silent' sites evolve under a balance between weak selection and genetic drift. Simulated data also show that sequence comparisons are a powerful method to detect adaptive protein evolution, even when selection is weak or affects a small fraction of nucleotide sites. In the Drosophila data examined, positive selection appears to be a predominant force in protein evolution.     

Expressed sequence tag-linked microsatellites as a source of gene-associated polymorphisms for detecting signatures of divergent selection in atlantic salmon (Salmo salar L.)

The prediction that selection affects the genome in a locus-specific way also affecting flanking neutral variation, known as genetic hitchhiking, enables the use of polymorphic markers in noncoding regions to detect the footprints of selection. However, as the strength of the selective footprint on a locus depends on the distance from the selected site and will decay with time due to recombination, the utilization of polymorphic markers closely linked to coding regions of the genome should increase the probability of detecting the footprints of selection as more gene-containing regions are covered. The occurrence of highly polymorphic microsatellites in the untranslated regions of expressed sequence tags (ESTs) is a potentially useful source of gene-associated polymorphisms which has thus far not been utilized for genome screens in natural populations. In this study, we searched for the genetic signatures of divergent selection by screening 95 genomic and EST-derived mini- and microsatellites in eight natural Atlantic salmon, Salmo salar L., populations from different spatial scales inhabiting contrasting natural environments (salt-, brackish, and freshwater habitat). Altogether, we identified nine EST-associated microsatellites, which exhibited highly significant deviations from the neutral expectations using different statistical methods at various spatial scales and showed similar trends in separate population samples from different environments (salt-, brackish, and freshwater habitats) and sea areas (Barents vs. White Sea). We consider these ESTs as the best candidate loci affected by divergent selection, and hence, they serve as promising genes associated with adaptive divergence in Atlantic salmon. Our results demonstrate that EST-linked microsatellite genome scans provide an efficient strategy for discovering functional polymorphisms, especially in nonmodel organisms.     

SnIPRE: Selection Inference Using a Poisson Random Effects Model

We present an approach for identifying genes under natural selection using polymorphism and divergence data from synonymous and non-synonymous sites within genes. A generalized linear mixed model is used to model the genome-wide variability among categories of mutations and estimate its functional consequence. We demonstrate how the model''s estimated fixed and random effects can be used to identify genes under selection. The parameter estimates from our generalized linear model can be transformed to yield population genetic parameter estimates for quantities including the average selection coefficient for new mutations at a locus, the synonymous and non-synynomous mutation rates, and species divergence times. Furthermore, our approach incorporates stochastic variation due to the evolutionary process and can be fit using standard statistical software. The model is fit in both the empirical Bayes and Bayesian settings using the lme4 package in R, and Markov chain Monte Carlo methods in WinBUGS. Using simulated data we compare our method to existing approaches for detecting genes under selection: the McDonald-Kreitman test, and two versions of the Poisson random field based method MKprf. Overall, we find our method universally outperforms existing methods for detecting genes subject to selection using polymorphism and divergence data.