MAINTENANCE OF POLYGENIC VARIATION IN SPATIALLY STRUCTURED POPULATIONS: ROLES FOR LOCAL MATING AND GENETIC REDUNDANCY

Independently evolved pollution resistance in four killifish populations is largely explained by few variants of large effect

The genetic architecture of phenotypic traits can affect the mode and tempo of trait evolution. Human-altered environments can impose strong natural selection, where successful evolutionary adaptation requires swift and large phenotypic shifts. In these scenarios, theory predicts that adaptation is due to a few adaptive variants of large effect, but empirical studies that have revealed the genetic architecture of rapidly evolved phenotypes are rare, especially for populations inhabiting polluted environments. Fundulus killifish have repeatedly evolved adaptive resistance to extreme pollution in urban estuaries. Prior studies, including genome scans for signatures of natural selection, have revealed some of the genes and pathways important for evolved pollution resistance, and provide context for the genotype-phenotype association studies reported here. We created multiple quantitative trait locus (QTL) mapping families using progenitors from four different resistant populations, and using RAD-seq genetically mapped variation in sensitivity (developmental perturbations) following embryonic exposure to a model toxicant PCB-126. We found that one to two large-effect QTL loci accounted for resistance to PCB-mediated developmental toxicity. QTLs harbored candidate genes that govern the regulation of aryl hydrocarbon receptor (AHR) signaling. One QTL locus was shared across all populations and another was shared across three populations. One QTL locus showed strong signatures of recent natural selection in the corresponding wild population but another QTL locus did not. Some candidate genes for PCB resistance inferred from genome scans in wild populations were identified as QTL, but some key candidate genes were not. We conclude that rapidly evolved resistance to the developmental defects normally caused by PCB-126 is governed by few genes of large effect. However, other aspects of resistance beyond developmental phenotypes may be governed by additional loci, such that comprehensive resistance to PCB-126, and to the mixtures of chemicals that distinguish urban estuaries more broadly, may be more genetically complex.

Polygenic routes lead to parallel altitudinal adaptation in Heliosperma pusillum (Caryophyllaceae)

Understanding how organisms adapt to the environment is a major goal of modern biology. Parallel evolution-the independent evolution of similar phenotypes in different populations-provides a powerful framework to investigate the evolutionary potential of populations, the constraints of evolution, its repeatability and therefore its predictability. Here, we quantified the degree of gene expression and functional parallelism across replicated ecotype formation in Heliosperma pusillum (Caryophyllaceae), and gained insights into the architecture of adaptive traits. Population structure analyses and demographic modelling support a previously formulated hypothesis of parallel polytopic divergence of montane and alpine ecotypes. We detect a large proportion of differentially expressed genes (DEGs) underlying divergence within each replicate ecotype pair, with a strikingly low number of shared DEGs across pairs. Functional enrichment of DEGs reveals that the traits affected by significant expression divergence are largely consistent across ecotype pairs, in strong contrast to the nonshared genetic basis. The remarkable redundancy of differential gene expression indicates a polygenic architecture for the diverged adaptive traits. We conclude that polygenic traits appear key to opening multiple routes for adaptation, widening the adaptive potential of organisms.

Genome-wide signatures of synergistic epistasis during parallel adaptation in a Baltic Sea copepod

The role of epistasis in driving adaptation has remained an unresolved problem dating back to the Evolutionary Synthesis. In particular, whether epistatic interactions among genes could promote parallel evolution remains unexplored. To address this problem, we employ an Evolve and Resequence (E&R) experiment, using the copepod Eurytemora affinis, to elucidate the evolutionary genomic response to rapid salinity decline. Rapid declines in coastal salinity at high latitudes are a predicted consequence of global climate change. Based on time-resolved pooled whole-genome sequencing, we uncover a remarkably parallel, polygenic response across ten replicate selection lines, with 79.4% of selected alleles shared between lines by the tenth generation of natural selection. Using extensive computer simulations of our experiment conditions, we find that this polygenic parallelism is consistent with positive synergistic epistasis among alleles, far more so than other mechanisms tested. Our study provides experimental and theoretical support for a novel mechanism promoting repeatable polygenic adaptation, a phenomenon that may be common for selection on complex physiological traits.

Using time-series whole-genome sequencing data from a laboratory evolution experiment, along with extensive computer simulations, the authors show that synergistic epistasis could drive rapid parallel freshwater adaptation in a saline copepod.

Population differentiation of polygenic score predictions under stabilizing selection

Given the many small-effect loci uncovered by genome-wide association studies (GWAS), polygenic scores have become central to genomic medicine, and have found application in diverse settings including evolutionary studies of adaptation. Despite their promise, polygenic scores have been found to suffer from limited portability across human populations. This at first seems in conflict with the observation that most common genetic variation is shared among populations. We investigate one potential cause of this discrepancy: stabilizing selection on complex traits. Counterintuitively, while stabilizing selection constrains phenotypic evolution, it accelerates the loss and fixation of alleles underlying trait variation within populations (GWAS loci). Thus even when populations share an optimum phenotype, stabilizing selection erodes the variance contributed by their shared GWAS loci, such that predictions from GWAS in one population explain less of the phenotypic variation in another. We develop theory to quantify how stabilizing selection is expected to reduce the prediction accuracy of polygenic scores in populations not represented in GWAS samples. In addition, we find that polygenic scores can substantially overstate average genetic differences of phenotypes among populations. We emphasize stabilizing selection around a common optimum as a useful null model to connect patterns of allele frequency and polygenic score differentiation. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.

Evolution of polygenic traits under global vs local adaptation

Observations about the number, frequency, effect size, and genomic distribution of alleles associated with complex traits must be interpreted in light of evolutionary process. These characteristics, which constitute a trait’s genetic architecture, can dramatically affect evolutionary outcomes in applications from agriculture to medicine, and can provide a window into how evolution works. Here, I review theoretical predictions about the evolution of genetic architecture under spatially homogeneous, global adaptation as compared with spatially heterogeneous, local adaptation. Due to the tension between divergent selection and migration, local adaptation can favor “concentrated” genetic architectures that are enriched for alleles of larger effect, clustered in a smaller number of genomic regions, relative to expectations under global adaptation. However, the evolution of such architectures may be limited by many factors, including the genotypic redundancy of the trait, mutation rate, and temporal variability of environment. I review the circumstances in which predictions differ for global vs local adaptation and discuss where progress can be made in testing hypotheses using data from natural populations and lab experiments. As the field of comparative population genomics expands in scope, differences in architecture among traits and species will provide insights into how evolution works, and such differences must be interpreted in light of which kind of selection has been operating.

Polygenic Selection within a Single Generation Leads to Subtle Divergence among Ecological NichesINc

Selection on standing genetic variation may be effective enough to allow for adaptation to distinct niche environments within a single generation. Minor allele frequency changes at multiple, redundant loci of small effect can produce remarkable phenotypic shifts. Yet, demonstrating rapid adaptation via polygenic selection in the wild remains challenging. Here we harness natural replicate populations that experience similar selection pressures and harbor high within-, yet negligible among-population genetic variation. Such populations can be found among the teleost Fundulus heteroclitus that inhabits marine estuaries characterized by high environmental heterogeneity. We identify 10,861 single nucleotide polymorphisms in F. heteroclitus that belong to a single, panmictic population yet reside in environmentally distinct niches (one coastal basin and three replicate tidal ponds). By sampling at two time points within a single generation, we quantify both allele frequency change within as well as spatial divergence among niche subpopulations. We observe few individually significant allele frequency changes yet find that the “number” of moderate changes exceeds the neutral expectation by 10–100%. We find allele frequency changes to be significantly concordant in both direction and magnitude among all niche subpopulations, suggestive of parallel selection. In addition, within-generation allele frequency changes generate subtle but significant divergence among niches, indicative of local adaptation. Although we cannot distinguish between selection and genotype-dependent migration as drivers of within-generation allele frequency changes, the trait/s determining fitness and/or migration likelihood appear to be polygenic. In heterogeneous environments, polygenic selection and polygenic, genotype-dependent migration offer conceivable mechanisms for within-generation, local adaptation to distinct niches.

Molecular regulatory mechanisms underlying the adaptability of polyploid plants

Polyploidization influences the genetic composition and gene expression of an organism. This multi-level genetic change allows the formation of new regulatory pathways leading to increased adaptability. Although both forms of polyploidization provide advantages, autopolyploids were long thought to have little impact on plant divergence compared to allopolyploids due to their formation through genome duplication only, rather than in combination with hybridization. Recent advances have begun to clarify the molecular regulatory mechanisms such as microRNAs, alternative splicing, RNA-binding proteins, histone modifications, chromatin remodelling, DNA methylation, and N⁶ -methyladenosine (m6A) RNA methylation underlying the evolutionary success of polyploids. Such research is expanding our understanding of the evolutionary adaptability of polyploids and the regulatory pathways that allow adaptive plasticity in a variety of plant species. Herein we review the roles of individual molecular regulatory mechanisms and their potential synergistic pathways underlying plant evolution and adaptation. Notably, increasing interest in m6A methylation has provided a new component in potential mechanistic coordination that is still predominantly unexplored. Future research should attempt to identify and functionally characterize the evolutionary impact of both individual and synergistic pathways in polyploid plant species.

Distinct Patterns of Selective Sweep and Polygenic Adaptation in Evolve and Resequence Studies

In molecular population genetics, adaptation is typically thought to occur via selective sweeps, where targets of selection have independent effects on the phenotype and rise to fixation, whereas in quantitative genetics, many loci contribute to the phenotype and subtle frequency changes occur at many loci during polygenic adaptation. The sweep model makes specific predictions about frequency changes of beneficial alleles and many test statistics have been developed to detect such selection signatures. Despite polygenic adaptation is probably the prevalent mode of adaptation, because of the traditional focus on the phenotype, we are lacking a solid understanding of the similarities and differences of selection signatures under the two models. Recent theoretical and empirical studies have shown that both selective sweep and polygenic adaptation models could result in a sweep-like genomic signature; therefore, additional criteria are needed to distinguish the two models. With replicated populations and time series data, experimental evolution studies have the potential to identify the underlying model of adaptation. Using the framework of experimental evolution, we performed computer simulations to study the pattern of selected alleles for two models: 1) adaptation of a trait via independent beneficial mutations that are conditioned for fixation, that is, selective sweep model and 2) trait optimum model (polygenic adaptation), that is adaptation of a quantitative trait under stabilizing selection after a sudden shift in trait optimum. We identify several distinct patterns of selective sweep and trait optimum models in populations of different sizes. These features could provide the foundation for development of quantitative approaches to differentiate the two models.

Evolutionary potential varies across populations and traits in the neotropical oak Quercus oleoides

Heritable variation in polygenic (quantitative) traits is critical for adaptive evolution and is especially important in this era of rapid climate change. In this study, we examined the levels of quantitative genetic variation of populations of the tropical tree Quercus oleoides Cham. and Schlect. for a suite of traits related to resource use and drought resistance. We tested whether quantitative genetic variation differed across traits, populations and watering treatments. We also tested potential evolutionary factors that might have shaped such a pattern: selection by climate and genetic drift. We measured 15 functional traits on 1322 1-year-old seedlings of 84 maternal half-sib families originating from five populations growing under two watering treatments in a greenhouse. We estimated the additive genetic variance, coefficient of additive genetic variation and narrow-sense heritability for each combination of traits, populations and treatments. In addition, we genotyped a total of 119 individuals (with at least 20 individuals per population) using nuclear microsatellites to estimate genetic diversity and population genetic structure. Our results showed that gas exchange traits and growth exhibited strikingly high quantitative genetic variation compared with traits related to leaf morphology, anatomy and photochemistry. Quantitative genetic variation differed between populations even at geographical scales as small as a few kilometers. Climate was associated with quantitative genetic variation, but only weakly. Genetic structure and diversity in neutral markers did not relate to coefficient of additive genetic variation. Our study demonstrates that quantitative genetic variation is not homogeneous across traits and populations of Q. oleoides. More importantly, our findings suggest that predictions about potential responses of species to climate change need to consider population-specific evolutionary characteristics.

Genetic redundancy fuels polygenic adaptation in Drosophila

The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic-i.e., result from selection on a large number of genetic loci-but most molecularly characterized traits have a simple genetic basis. This discrepancy is best explained by the difficulty in detecting small allele frequency changes (AFCs) across many contributing loci. To resolve this, we use laboratory natural selection to detect signatures for selective sweeps and polygenic adaptation. We exposed 10 replicates of a Drosophila simulans population to a new temperature regime and uncovered a polygenic architecture of an adaptive trait with high genetic redundancy among beneficial alleles. We observed convergent responses for several phenotypes-e.g., fitness, metabolic rate, and fat content-and a strong polygenic response (99 selected alleles; mean s = 0.059). However, each of these selected alleles increased in frequency only in a subset of the evolving replicates. We discerned different evolutionary paradigms based on the heterogeneous genomic patterns among replicates. Redundancy and quantitative trait (QT) paradigms fitted the experimental data better than simulations assuming independent selective sweeps. Our results show that natural D. simulans populations harbor a vast reservoir of adaptive variation facilitating rapid evolutionary responses using multiple alternative genetic pathways converging at a new phenotypic optimum. This key property of beneficial alleles requires the modification of testing strategies in natural populations beyond the search for convergence on the molecular level.

Quantifying how constraints limit the diversity of viable routes to adaptation

Convergent adaptation occurs at the genome scale when independently evolving lineages use the same genes to respond to similar selection pressures. These patterns of genetic repeatability provide insights into the factors that facilitate or constrain the diversity of genetic responses that contribute to adaptive evolution. A first step in studying such factors is to quantify the observed amount of repeatability relative to expectations under a null hypothesis. Here, we formulate a novel index to quantify the constraints driving the observed amount of repeated adaptation in pairwise contrasts based on the hypergeometric distribution, and then generalize this for simultaneous analysis of multiple lineages. This index is explicitly based on the probability of observing a given amount of repeatability by chance under a given null hypothesis and is readily compared among different species and types of trait. We also formulate an index to quantify the effective proportion of genes in the genome that have the potential to contribute to adaptation. As an example of how these indices can be used to draw inferences, we assess the amount of repeatability observed in existing datasets on adaptation to stress in yeast and climate in conifers. This approach provides a method to test a wide range of hypotheses about how different kinds of factors can facilitate or constrain the diversity of genetic responses observed during adaptive evolution.

How many ways can evolution solve the same adaptive problem? While convergent adaptation is evident in many organisms at the phenotypic level, we are only beginning to understand how commonly this convergence extends to the genome scale. Quantifying the repeatability of adaptation at the genome scale is therefore critical for assessing how constraints affect the diversity of viable genetic responses. Here, we develop probability-based indices to quantify the deviation between observed repeatability and expectations under a range of null hypotheses, and an estimator of the proportion of loci in the genome that can contribute to adaptation. We demonstrate the usage of these indices with individual-based simulations and example datasets from yeast and conifers and discuss how they differ from previously developed approaches to studying repeatability. Because these indices are unitless, they provide a general approach to quantifying and comparing how constraints drive convergence at the genome scale across a wide range of traits and taxa.

Effect of migration and environmental heterogeneity on the maintenance of quantitative genetic variation: a simulation study

The paradox of high genetic variation observed in traits under stabilizing selection is a long-standing problem in evolutionary theory, as mutation rates appear too low to explain observed levels of standing genetic variation under classic models of mutation-selection balance. Spatially or temporally heterogeneous environments can maintain more standing genetic variation within populations than homogeneous environments, but it is unclear whether such conditions can resolve the above discrepancy between theory and observation. Here, we use individual-based simulations to explore the effect of various types of environmental heterogeneity on the maintenance of genetic variation (V_A ) for a quantitative trait under stabilizing selection. We find that V_A is maximized at intermediate migration rates in spatially heterogeneous environments and that the observed patterns are robust to changes in population size. Spatial environmental heterogeneity increased variation by as much as 10-fold over mutation-selection balance alone, whereas pure temporal environmental heterogeneity increased variance by only 45% at max. Our results show that some combinations of spatial heterogeneity and migration can maintain considerably more variation than mutation-selection balance, potentially reconciling the discrepancy between theoretical predictions and empirical observations. However, given the narrow regions of parameter space required for this effect, this is unlikely to provide a general explanation for the maintenance of variation. Nonetheless, our results suggest that habitat fragmentation may affect the maintenance of V_A and thereby reduce the adaptive capacity of populations.

Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions

Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species' demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.

On the importance of balancing selection in plants

Balancing selection refers to a variety of selective regimes that maintain advantageous genetic diversity within populations. We review the history of the ideas regarding the types of selection that maintain such polymorphism in flowering plants, notably heterozygote advantage, negative frequency-dependent selection, and spatial heterogeneity. One shared feature of these mechanisms is that whether an allele is beneficial or detrimental is conditional on its frequency in the population. We highlight examples of balancing selection on a variety of discrete traits. These include the well-referenced case of self-incompatibility and recent evidence from species with nuclear-cytoplasmic gynodioecy, both of which exhibit trans-specific polymorphism, a hallmark of balancing selection. We also discuss and give examples of how spatial heterogeneity in particular, which is often thought unlikely to allow protected polymorphism, can maintain genetic variation in plants (which are rooted in place) as a result of microhabitat selection. Lastly, we discuss limitations of the protected polymorphism concept for quantitative traits, where selection can inflate the genetic variance without maintaining specific alleles indefinitely. We conclude that while discrete-morph variation provides the most unambiguous cases of protected polymorphism, they represent only a fraction of the balancing selection at work in plants.

Potential for evolutionary responses to climate change - evidence from tree populations

Evolutionary responses are required for tree populations to be able to track climate change. Results of 250 years of common garden experiments show that most forest trees have evolved local adaptation, as evidenced by the adaptive differentiation of populations in quantitative traits, reflecting environmental conditions of population origins. On the basis of the patterns of quantitative variation for 19 adaptation-related traits studied in 59 tree species (mostly temperate and boreal species from the Northern hemisphere), we found that genetic differentiation between populations and clinal variation along environmental gradients were very common (respectively, 90% and 78% of cases). Thus, responding to climate change will likely require that the quantitative traits of populations again match their environments. We examine what kind of information is needed for evaluating the potential to respond, and what information is already available. We review the genetic models related to selection responses, and what is known currently about the genetic basis of the traits. We address special problems to be found at the range margins, and highlight the need for more modeling to understand specific issues at southern and northern margins. We need new common garden experiments for less known species. For extensively studied species, new experiments are needed outside the current ranges. Improving genomic information will allow better prediction of responses. Competitive and other interactions within species and interactions between species deserve more consideration. Despite the long generation times, the strong background in quantitative genetics and growing genomic resources make forest trees useful species for climate change research. The greatest adaptive response is expected when populations are large, have high genetic variability, selection is strong, and there is ecological opportunity for establishment of better adapted genotypes.

Parallel adaptation: one or many waves of advance of an advantageous allele?

Models for detecting the effect of adaptation on population genomic diversity are often predicated on a single newly arisen mutation sweeping rapidly to fixation. However, a population can also adapt to a new environment by multiple mutations of similar phenotypic effect that arise in parallel, at the same locus or different loci. These mutations can each quickly reach intermediate frequency, preventing any single one from rapidly sweeping to fixation globally, leading to a "soft" sweep in the population. Here we study various models of parallel mutation in a continuous, geographically spread population adapting to a global selection pressure. The slow geographic spread of a selected allele due to limited dispersal can allow other selected alleles to arise and start to spread elsewhere in the species range. When these different selected alleles meet, their spread can slow dramatically and so initially form a geographic patchwork, a random tessellation, which could be mistaken for a signal of local adaptation. This spatial tessellation will dissipate over time due to mixing by migration, leaving a set of partial sweeps within the global population. We show that the spatial tessellation initially formed by mutational types is closely connected to Poisson process models of crystallization, which we extend. We find that the probability of parallel mutation and the spatial scale on which parallel mutation occurs are captured by a single compound parameter, a characteristic length, which reflects the expected distance a spreading allele travels before it encounters a different spreading allele. This characteristic length depends on the mutation rate, the dispersal parameter, the effective local density of individuals, and to a much lesser extent the strength of selection. While our knowledge of these parameters is poor, we argue that even in widely dispersing species, such parallel geographic sweeps may be surprisingly common. Thus, we predict that as more data become available, many more examples of intraspecies parallel adaptation will be uncovered.

Geographical variation in resistance to acetyl-coenzyme A carboxylase-inhibiting herbicides across the range of the arable weed Alopecurus myosuroides (black-grass)

*The geographical structure of resistance to herbicides inhibiting acetyl-coenzyme A carboxylase (ACCase) was investigated in the weed Alopecurus myosuroides (black-grass) across its geographical range to gain insight into the process of plant adaptation in response to anthropogenic selective pressures occurring in agricultural ecosystems. *We analysed 297 populations distributed across six countries in A. myosuroides' main area of occupancy. The frequencies of plants resistant to two broadly used ACCase inhibitors and of seven mutant, resistant ACCase alleles were assessed using bioassays and genotyping, respectively. *Most of the resistance was not endowed by mutant ACCase alleles. Resistance and ACCase allele distribution patterns were characterized by mosaicism. The prevalence of resistance and of ACCase alleles differed among countries. *Resistance clearly evolved by redundant evolution of a set of resistance alleles or genes, most of which remain unidentified. Resistance in A. myosuroides was shaped by variation in the herbicide selective pressure at both the individual field level and the national level.

Spatial patterns of variation due to natural selection in humans

Empowered by technology and sampling efforts designed to facilitate genome-wide association mapping, human geneticists are now studying the geography of genetic variation in unprecedented detail. With high genomic coverage and geographic resolution, these studies are identifying loci with spatial signatures of selection, such as extreme levels of differentiation and correlations with environmental variables. Collectively, patterns at these loci are beginning to provide new insights into the process of human adaptation. Here, we review the challenges of these studies and emerging results, including how human population structure has influenced the response to novel selective pressures.

The joint effects of selection and dominance on the QST - FST contrast

Q(ST) measures the differentiation of quantitative traits between populations. It is often compared to F(ST), which measures population differentiation at neutral marker loci due to drift, migration, and mutation. When Q(ST) is different from F(ST), it is usually taken as evidence that selection has either restrained or accelerated the differentiation of the quantitative trait relative to neutral markers. However, a number of other factors such as inbreeding, dominance, and epistasis may also affect the Q(ST) - F(ST) contrast. In this study, we examine the effects of dominance, selection, and inbreeding on Q(ST) - F(ST). We compare Q(ST) with F(ST) at selected and neutral loci for populations at equilibrium between selection, drift, mutation, and migration using both analytic and simulation approaches. Interestingly, when divergent selection is acting on a locus, inbreeding and dominance generally inflate Q(ST) relative to F(ST) when they are both measured at the quantitative locus at equilibrium. As a consequence, dominance is unlikely to hide the signature of divergent selection on the Q(ST) - F(ST) contrast. However, although in theory dominance and inbreeding affect the expectation for Q(ST) - F(ST), of most concern is the very large variance in both Q(ST) and F(ST), suggesting that we should be cautious in attributing small differences between Q(ST) and F(ST) to selection.

Regional heterogeneity and gene flow maintain variance in a quantitative trait within populations of lodgepole pine

Genetic variation is of fundamental importance to biological evolution, yet we still know very little about how it is maintained in nature. Because many species inhabit heterogeneous environments and have pronounced local adaptations, gene flow between differently adapted populations may be a persistent source of genetic variation within populations. If this migration-selection balance is biologically important then there should be strong correlations between genetic variance within populations and the amount of heterogeneity in the environment surrounding them. Here, we use data from a long-term study of 142 populations of lodgepole pine (Pinus contorta) to compare levels of genetic variation in growth response with measures of climatic heterogeneity in the surrounding region. We find that regional heterogeneity explains at least 20% of the variation in genetic variance, suggesting that gene flow and heterogeneous selection may play an important role in maintaining the high levels of genetic variation found within natural populations.

Cardiovascular system in larval zebrafish responds to developmental hypoxia in a family specific manner

Background

Genetic and environmental variation are both known to influence development. Evolution of a developmental response that is optimized to the environment (adaptive plasticity) requires the existence of genetic variation for that developmental response. In complex traits composed of integrated sets of subsidiary traits, the adaptive process may be slowed by the existence of multiple possible integrated responses. This study tests for family (sibship) specific differences in plastic response to hypoxia in an integrated set of cardiovascular traits in zebrafish.

Results

Cardiac output, which is the integrated product of several subsidiary traits, varied highly significantly between families, and families differed significantly in the degree and direction of response to developmental oxygen level. The cardiac output response to oxygen environment was entirely family specific with no significant overall trend due to oxygen level. Constituent physiological variables that contribute to cardiac output all showed significant family specific response to hypoxia. Traits that were not directly related to cardiac output, such as arterial and venous diameter, and red blood cell velocities did not respond to hypoxia in a family specific manner.

Conclusion

Zebrafish families vary in their plastic response to hypoxia. Genetic variation in plastic response to hypoxia may therefore provide the basic ingredient for adaptation to a variable environment. Considerable variation in the degree of familial response to hypoxia exists between different cardiovascular traits that may contribute to cardiac output. It is possible that the integration of several subsidiary traits into cardiac output allows the maintenance of genetic variance in cardiac response.

Geographical variation in selection, from phenotypes to molecules

Molecular technologies now allow researchers to isolate quantitative trait loci (QTLs) and measure patterns of gene sequence variation within chromosomal regions containing important polymorphisms. I develop a simulation model to investigate gene sequence evolution within genomic regions that harbor QTLs. The QTLs influence a trait experiencing geographical variation in selection, which is common in nature and produces obvious differentiation at the phenotypic level. Counter to expectations, the simulations suggest that selection can substantially affect quantitative genetic variation without altering the amount and pattern of molecular variation at sites closely linked to the QTLs. Even with large samples of gene sequences, the likelihood of rejecting neutrality is often low. The exception is situations where strong selection is combined with low migration among demes, conditions that may be common in many plant species. The results have implications for gene sequence surveys and, perhaps more generally, for interpreting the apparently weak connection between levels of molecular and quantitative trait variation within species.

Nonequivalent Loci and the distribution of mutant effects

It has been observed repeatedly that the distribution of new mutations of a quantitative trait has a kurtosis (a statistical measure of the distribution's shape) that is systematically larger than that of a normal distribution. Here we suggest that rather than being a property of individual loci that control the trait, the enhanced kurtosis is highly likely to be an emergent property that arises directly from the loci being mutationally nonequivalent. We present a method of incorporating nonequivalent loci into quantitative genetic modeling and give an approximate relation between the kurtosis of the mutant distribution and the degree of mutational nonequivalence of loci. We go on to ask whether incorporating the experimentally observed kurtosis through nonequivalent loci, rather than at locus level, affects any biologically important conclusions of quantitative genetic modeling. Concentrating on the maintenance of quantitative genetic variation by mutation-selection balance, we conclude that typically nonequivalent loci yield a genetic variance that is of order 10% smaller than that obtained from the previous approaches. For large populations, when the kurtosis is large, the genetic variance may be <50% of the result of equivalent loci, with Gaussian distributions of mutant effects.

Evolution of genetic redundancy

Genetic redundancy means that two or more genes are performing the same function and that inactivation of one of these genes has little or no effect on the biological phenotype. Redundancy seems to be widespread in genomes of higher organisms. Examples of apparently redundant genes come from numerous studies of developmental biology, immunology, neurobiology and the cell cycle. Yet there is a problem: genes encoding functional proteins must be under selection pressure. If a gene was truly redundant then it would not be protected against the accumulation of deleterious mutations. A widespread view is therefore that such redundancy cannot be evolutionarily stable. Here we develop a simple genetic model to analyse selection pressures acting on redundant genes. We present four cases that can explain why genetic redundancy is common. In three cases, redundancy is even evolutionarily stable. Our theory provides a framework for exploring the evolution of genetic organization.

Population structure, fitness surfaces, and linkage in the shifting balance process

Wright first introduced the idea that random genetic drift and classical mass-action selection might combine in such a way as to allow populations to find the highest peak in complicated adaptive surfaces. His theory assumes large but structured populations, in which mating is spatially local. If gene flow is sufficiently low, and the subpopulations (demes) are small enough, they will be subject to genetic drift. Distant demes drift independently, allowing many independent searches of the adaptive surface to take place. A deme that has shifted to a higher peak can, by emigration, cause the rest of the demes to shift to the higher peak. The probability of this shift depends on the migration rate. Previous studies have concluded that very little migration is necessary to effect the shift in adaptive peaks that characterizes the last phase of Wright's Shifting Balance Process (SBP). Here we present the results of a computer study that investigates the roles of dispersal distance, the degree of epistasis in the fitness surface, and recombination on the shifting balance process. In particular, we measure their effect on the population's mean fitness. We show that over a range of dispersal distances the advantage of the SBP is a monotonically increasing function of the amount of epistasis. Our results show that the extent of dispersal that results in the greatest effect of the SBP in increasing mean fitness depends on the extent of epistasis. Finally, for low levels of epistasis, higher recombination performs better, while for intermediate levels, lower recombination results in a greater advantage of the SBP.

Laboratory and natural heritabilities of male courtship song characters in Drosophila montana and D. littoralis

We estimated heritabilities for several male courtship song characters in two Drosophila species using father-son regression under conditions where both fathers and sons had been raised in the laboratory. In D. montana the heritabilities of song characters were rather high (-0.23 to 0.80) and in most cases significant. In D. littoralis the heritabilities of song characters were generally lower (-0.33 to 0.18), and none of them was significantly larger than zero. We also estimated heritabilities regressing characters of wild-caught fathers with those of their laboratory reared sons, and used the method employed by Riska et al. to estimate the lower bound of heritabilities in nature. In D. montana most and in D. littoralis all of the across-environment heritabilities were non-significant (-0.15 to 0.43 and -0.04 to 0.15, respectively), and in some cases the across-environment heritabilities were significantly lower than the heritabilities measured under laboratory conditions. The low across-environment heritabilities appeared to be due to larger phenotypic variability of song characters in the field and in some cases also due to genotype-environment interactions.