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Results for “Evolutionary Biology”

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bioRxiv2015

Overlapping Genes and Size Constraints in Viruses - An Evolutionary Perspective

Viruses are the simplest replicating units, characterized by a limited number of coding genes and an exceptionally high rate of overlapping genes. We sought a unified explanation for the evolutionary constraints that govern genome sizes, gene overlapping and capsid properties. We performed an unbiased statistical analysis over the [~]100 known viral families, and came to refute widespread assumptions regarding viral evolution. We found that the volume utilization of viral capsids is often low, and greatly varies among families. Most notably, we show that the total amount of gene overlapping is tightly bounded. Although viruses expand three orders of magnitude in genome length, their absolute amount of gene overlapping almost never exceeds 1500 nucleotides, and mostly confined to <4 significant overlapping instances. Our results argue against the common theory by which gene overlapping is driven by a necessity of viruses to compress their genome. Instead, we support the notion that overlapping has a role in gene novelty and evolution exploration.

Evolutionary Biology↗

bioRxiv2015

Selection for mitochondrial quality drives the evolution of sexes with a dedicated germline

The origin of the germline-soma distinction is a fundamental unsolved question. Plants and basal metazoans do not have a germline but generate gametes from somatic tissues (somatic gametogenesis), whereas most bilaterians sequester a germline. We develop an evolutionary model which shows that selection for mitochondrial quality drives germline evolution. In organisms with low mitochondrial mutation rates, segregation of mutations over multiple cell divisions generates variation, allowing selection to optimize gamete quality through somatic gametogenesis. Higher mutation rates promote early germline sequestration. Oogamy reduces mitochondrial segregation in early development, improving adult fitness by restricting variation between tissues, but also limiting variation between early-sequestered oocytes, undermining gamete quality. Oocyte variation is restored through proliferation and random culling (atresia) of precursor cells. We predict a novel pathway from basal metazoans lacking a germline to active bilaterians with early sequestration of large oocytes subject to atresia, allowing the emergence of complex developmental processes.

Evolutionary Biology↗

bioRxiv2015

Natural selection and recombination rate variation shape nucleotide polymorphism across the genomes of three related Populus species.

A central aim of evolutionary genomics is to identify the relative roles that various evolutionary forces have played in generating and shaping genetic variation within and among species. Here we use whole-genome re-sequencing data to characterize and compare genome-wide patterns of nucleotide polymorphism, site frequency spectrum and population-scaled recombination rates in three species of Populus: P. tremula, P. tremuloides and P. trichocarpa. We find that P. tremuloides has the highest level of genome-wide variation, skewed allele frequencies and population-scaled recombination rates, whereas P. trichocarpa harbors the lowest. Our findings highlight multiple lines of evidence suggesting that natural selection, both due to purifying and positive selection, has widely shaped patterns of nucleotide polymorphism at linked neutral sites in all three species. Differences in effective population sizes and rates of recombination are largely explaining the disparate magnitudes and signatures of linked selection we observe among species. The present work provides the first phylogenetic comparative study at genome-wide scale in forest trees. This information will also improve our ability to understand how various evolutionary forces have interacted to influence genome evolution among related species.

Evolutionary Biology↗

bioRxiv2015

HacDivSel: Two new methods (haplotype-based and outlier-based) for the detection of divergent selection in pairs of populations

The detection of genomic regions involved in local adaptation is an important topic in current population genetics. There are several detection strategies available depending on the kind of genetic and demographic information at hand. A common drawback is the high risk of false positives. In this study, we introduce two complementary methods for the detection of divergent selection from populations connected by migration. Both methods have been developed with the aim of being robust to false positives. The first method combines haplotype information with inter-population differentiation (FST). Evidence of divergent selection is concluded only when both the haplotype pattern and the FST value support it. The second method is developed for independently segregating markers i.e. there is no haplotype information at hand. In this case, the power to detect selection is attained by developing a new outlier test based on detecting a bimodal distribution. The test computes the FST outliers and then assumes that those of interest would have a different mode which is detected by a clustering algorithm. The utility of the two methods is demonstrated through simulations and the analysis of real data. The simulation results show power ranging from 60-94% in several of the scenarios whilst the false positive rate is controlled below the nominal level in every scenario. The analysis of real samples consisted of phased data from the HapMap project and unphased data from intertidal marine snail ecotypes. The software HacDivSel implements the methods explained in this manuscript.

Evolutionary Biology↗

bioRxiv2015

General methods for evolutionary quantitative genetic inference from generalised mixed models.

Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioural traits, have inherently non-normal distributions. The generalised linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for non-normal traits. However, whereas GLMMs provide inference on a statistically-convenient latent scale, it is sometimes desirable to express quantitative genetic parameters on the scale upon which traits are expressed. The parameters of a fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal for this effect by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulae for quantities such as heritability of traits with Binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation, and apply our approach to data from a wild pedigreed vertebrate population.

Evolutionary Biology↗

bioRxiv2015

Divergent MLS1 promoters lie on a fitness plateau for gene expression

Qualitative patterns of gene activation and repression are often conserved despite an abundance of quantitative variation in expression levels within and between species. A major challenge to interpreting patterns of expression divergence is knowing which changes in gene expression affect fitness. To characterize the fitness effects of gene expression divergence we placed orthologous promoters from eight yeast species upstream of malate synthase (MLS1) in Saccharomyces cerevisiae. As expected, we found these promoters varied in their expression level under activated and repressed conditions as well as in their dynamic response following loss of glucose repression. Despite these differences, only a single promoter driving near basal levels of expression caused a detectable loss of fitness. We conclude that the MLS1 promoter lies on a fitness plateau whereby even large changes in gene expression can be tolerated without a substantial loss of fitness.

Evolutionary Biology↗

bioRxiv2015

Selection on heritable heterozygosity but no response to selection. Why?

The realisation that heterozygosity can be heritable has recently generated some elegant research. However, none of this work has discussed the fact that when heterozygote advantage occurs, heterozygosity can be heritable, yet allele frequencies remain at equilibrium and do not evolve with time. From a quantitative genetic perspective this means the character is heritable, is under selection, yet no response to selection is observed. We explain why this is the case, and discuss potential implications for the study of evolution in the wild.

Evolutionary Biology↗

bioRxiv2015

EvolQG - An R package for evolutionary quantitative genetics

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable. Given this mathematical representation of available variation, the EvolQG package provides functions for calculation of relevant evolutionary statistics, estimation of sampling error, corrections for this error, matrix comparison via correlations and distances, and functions for testing evolutionary hypotheses on taxa diversification.

Evolutionary Biology↗

bioRxiv2015

Inference of complex population histories using whole-genome sequences from multiple populations

There has been much interest in analyzing genome-scale DNA sequence data to infer population histories, but inference methods developed hitherto are limited in model complexity and computational scalability. Here we present an efficient, flexible statistical method, diCal2, that can utilize whole-genome sequence data from multiple populations to infer complex demographic models involving population size changes, population splits, admixture, and migration. Applying our method to data from Australian, East Asian, European, and Papuan populations, we find that the population ancestral to Australians and Papuans started separating from East Asians and Europeans about 100,000 years ago, and that the separation of East Asians and Europeans started about 50,000 years ago, with pervasive gene flow between all pairs of populations.

Evolutionary Biology↗

bioRxiv2015

Mapping phylogenetic trees to reveal distinct patterns of evolution

Evolutionary relationships are described by phylogenetic trees, but a central barrier in many fields is the difficulty of interpreting data containing conflicting phylogenetic signals. Obtaining credible trees that capture the relationships present in complex data is one of the fundamental challenges in evolution today. We present a way to map trees which extracts distinct alternative evolutionary relationships embedded in data and resolves phylogenetic uncertainty. Our method reveals a remarkably distinct phylogenetic signature in the VP30 gene of Ebolavirus, indicating possible recombination with significant implications for vaccine development. Moving to higher organisms, we use our approach to detect alternative histories of the evolution of anole lizards. Our approach has the capacity to resolve key areas of uncertainty in the study of evolution, and to broaden the credibility and appeal of phylogenetic methods.

Evolutionary Biology↗

bioRxiv2015

How sex-biased dispersal affects conflict over parental investment

Abstract Existing models of parental investment have mainly focused on interactions at the level of the family, and have paid much less attention to the impact of population-level processes. Here we extend classical models of parental care to assess the impact of population structure and limited dispersal. We find that sex-differences in dispersal substantially affect the amount of care provided by each parent, with the more philopatric sex providing the majority of the care to young. This effect is most pronounced in highly viscous populations: in such cases, when classical models would predict stable biparental care, inclusion of a modest sex difference in dispersal leads to uniparental care by the philopatric sex. In addition, mating skew also affects sex-differences in parental investment, with the more numerous sex providing most of the care. However, the effect of mating skew only holds when parents care for their own offspring. When individuals breed communally, we recover the previous finding that the more philopatric sex provides most of the care, even when it is the rare sex. Finally, we show that sex-differences in dispersal can mask the existence of sex-specific costs of care, because the philopatric sex may provide most of the care even in the face of far higher mortality costs relative to the dispersing sex. We conclude that sex-biased dispersal is likely to be an important, yet currently overlooked driver of sex-differences in parental care.

Evolutionary Biology↗

bioRxiv2015

Genetic structure of the stingless bee Tetragonisca angustula

The stingless bee Tetragonisca angustula Latreille 1811 is distributed from Mexico to Argentina and is one of the most widespread bee species in the Neotropics. However, this wide distribution contrasts with the short distance traveled by females to build new nests. Here we evaluate the genetic structure of several populations of T. angustula using mitochondrial DNA and microsatellites. These markers can help us to detect differences in the migratory behavior of males and females. Our results show that the populations are highly differentiated suggesting that both females and males have low dispersal distance. Therefore, its continental distribution probably consists of several cryptic species.

Evolutionary Biology↗

bioRxiv2015

Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with multiple exponential functions

Admixture-introduced linkage disequilibrium (LD) has recently been introduced into the inference of the histories of complex admixtures. However, the influence of ancestral source populations on the LD pattern in admixed populations is not properly taken into consideration by currently available methods, which affects the estimation of several gene flow parameters from empirical data. We first illustrated the dynamic changes of LD in admixed populations and mathematically formulated the LD under a generalized admixture model with finite population size. We next developed a new method, MALDmef, by fitting LD with multiple exponential functions for inferring and dating multiple-wave admixtures. MALDmef takes into account the effects of source populations which substantially affect modeling LD in admixed population, which renders it capable of efficiently detecting and dating multiple-wave admixture events. The performance of MALDmef was evaluated by simulation and it was shown to be more accurate than MALDER, a state-of-the-art method that was recently developed for similar purposes, under various admixture models. We further applied MALDmef to analyzing genome-wide data from the Human Genome Diversity Project (HGDP) and the HapMap Project. Interestingly, we were able to identify more than one admixture events in several populations, which have yet to be reported. For example, two major admixture events were identified in the Xinjiang Uyghur, occurring around 27-30 generations ago and 182-195 generations ago, respectively. In an African population (MKK), three recent major admixtures occurring 13-16, 50-67, and 107-139 generations ago were detected. Our method is a considerable improvement over other current methods and further facilitates the inference of the histories of complex population admixtures.

Evolutionary Biology↗

bioRxiv2015

Non-null Effects of the Null Range in Biogeographic Models: Exploring Parameter Estimation in the DEC Model

Historical biogeography seeks to understand the distribution of biodiversity in space and time. The dispersal-extinction-cladogenesis (DEC) model, a likelihood-based model of geographic range evolution, is widely used in assessing the biogeography of clades. Robust inference of dispersal and local extinction parameters is crucial for biogeographic inference, and yet a major caveat to its use is that the DEC model severely underestimates local extinction. We suggest that this is mainly due to the way in which the model is constructed to allow observed species to transition into being present in no areas (i.e., null range). By prohibiting transitions into the null range in the transition rate matrix, we were able to better infer local extinction and support this with simulations. This modified model, DEC*, has higher model fit and model adequacy than DEC, suggesting this modification should be considered for DEC and other models of geographic range evolution.

Evolutionary Biology↗

bioRxiv2015

Rolling the Dice Twice: Evolving Reconstructed Ancient Proteins in Extant Organisms

Scientists have access to artifacts of evolutionary history (namely, the fossil record and genomic sequences of living organisms) but they have limited means with which to infer the exact evolutionary events that occurred to produce todays living world. An intriguing question to arise from this historical limitation is whether the evolutionary paths of organisms are dominated by internal or external controlled processes (i.e., Life as a factory) or whether they are inherently random and subject to completely different outcomes if repeated under identical conditions (i.e., Life as a casino parlor). Two experimental approaches, ancestral sequence reconstruction and experimental evolution with microorganisms, can be used to recapitulate ancient adaptive pathways and provide valuable insights into the mutational steps that constitute an organisms genetic heritage. Ancestral sequence reconstruction follows a backwards-from-present-day strategy in which various ancestral forms of a modern gene or protein are reconstructed and then studied mechanistically. Experimental evolution, by contrast, follows a forward-from-present day strategy in which microbial populations are evolved in the laboratory under defined conditions in which their evolutionary paths may be closely monitored. Here I describe a novel hybrid of these two methods, in which synthetic components constructed from inferred ancestral gene or protein sequences are placed into the genomes of modern organisms that are then experimentally evolved. Through this system, we aim to establish the comparative study of ancient phenotypes as a novel, statistically rigorous methodology with which to explore the respective impacts of biophysics and chance in evolution within the scope of the Extended Synthesis.

Evolutionary Biology↗

bioRxiv2015

Diverse phenotypic and genetic responses to short-term selection in evolving Escherichia coli populations

Beneficial mutations fuel adaptation by altering phenotypes that enhance the fit of organisms to their environment. However, the phenotypic effects of mutations often depend on ecological context, making the distribution of effects across multiple environments essential to understanding the true nature of beneficial mutations. Studies that address both the genetic basis and ecological consequences of adaptive mutations remain rare. Here, we characterize the direct and pleiotropic fitness effects of a collection of 21 first-step beneficial mutants derived from naive and adapted genotypes used in a long-term experimental evolution of Escherichia coli. Whole-genome sequencing was used to identify most beneficial mutations. In contrast to previous studies, we find diverse fitness effects of mutations selected in a simple environment and few cases of genetic parallelism. The pleiotropic effects of these mutations were predominantly positive but some mutants were highly antagonistic in alternative environments. Further, the fitness effects of mutations derived from the adapted genotypes were dramatically reduced in nearly all environments. These findings suggest that many beneficial variants are accessible from a single point on the fitness landscape, and the fixation of alternative beneficial mutations may have dramatic consequences for niche breadth reduction via metabolic erosion.

Evolutionary Biology↗

bioRxiv2015

Sustained fitness gains and variability in fitness trajectories in the long-term evolution experiment with Escherichia coli

Many populations live in environments subject to frequent biotic and abiotic changes. Nonetheless, it is interesting to ask whether an evolving populations mean fitness can increase indefinitely, and potentially without any limit, even in a constant environment. A recent study showed that fitness trajectories of Escherichia coli populations over 50,000 generations were better described by a power-law model than by a hyperbolic model. According to the power-law model, the rate of fitness gain declines over time but fitness has no upper limit, whereas the hyperbolic model implies a hard limit. Here, we examine whether the previously estimated power-law model predicts the fitness trajectory for an additional 10,000 generations. To that end, we conducted more than 1100 new competitive fitness assays. Consistent with the previous study, the power-law model fits the new data better than the hyperbolic model. We also analysed the variability in fitness among populations, finding subtle, but significant, heterogeneity in mean fitness. Some, but not all, of this variation reflects differences in mutation rate that evolved over time. Taken together, our results imply that both adaptation and divergence can continue indefinitely-- or at least for a long time--even in a constant environment.

Evolutionary Biology↗

bioRxiv2015

Social selection parapatry in an Afrotropical sunbird

The extent of range overlap of incipient and recent species depends on the type and magnitude of phenotypic divergence that separates them. Trait divergence by social selection likely initiates many speciation events, but may yield niche-conserved lineages predisposed to limit each others ranges via ecological competition. Here we examine this neglected aspect of social selection speciation theory in relation to the discovery of a non-ecotonal species border between sunbirds. We find that Nectarinia moreaui and N. fuelleborni meet in a ~6 km wide contact zone, as estimated by molecular cline analysis. These species exploit similar bioclimatic niches, but sing highly divergent learned songs, consistent with divergence by social selection. Cline analyses suggest that within-species stabilizing social selection on song-learning predispositions maintains species differences in song despite both hybridization and cultural transmission in the contact zone. We conclude that ecological competition between moreaui and fuelleborni contributes to the stabilization of the species border, but that ecological competition acts in conjunction with reproductive interference. The evolutionary maintenance of learned song differences in a hybrid zone recommend this study system for future studies on the mechanisms of learned song divergence and its role in speciation.

Evolutionary Biology↗