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Results for “Evolutionary Biology”

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bioRxiv2016

Extensive genetic diversity among populations of the malaria mosquito Anopheles moucheti revealed by population genomics

Malaria vectors are exposed to intense selective pressures due to large-scale intervention programs that are underway in most African countries. One of the current priorities is therefore to clearly assess the adaptive potential of Anopheline populations, which is critical to understand and anticipate the response mosquitoes can elicit against such adaptive challenges. The development of genomic resources that will empower robust examinations of evolutionary changes in all vectors including currently understudied species is an inevitable step toward this goal. Here we constructed double-digest Restriction Associated DNA (ddRAD) libraries and generated 6461 Single Nucleotide Polymorphisms (SNPs) that we used to explore the population structure and demographic history of wild-caught Anopheles moucheti from Cameroon. The genome-wide distribution of allelic frequencies among samples best fitted that of an old population at equilibrium, characterized by a weak genetic structure and extensive genetic diversity, presumably due to a large long term effective population size. Estimates of FST and Linkage Disequilibrium (LD) across SNPs reveal a very low genetic differentiation throughout the genome and the absence of segregating LD blocks among populations, suggesting an overall lack of local adaptation. Our study provides the first investigation of the genetic structure and diversity in An. moucheti at the genomic scale. We conclude that, despite a weak genetic structure, this species has the potential to challenge current vector control measures and other rapid anthropogenic and environmental changes thanks to its great genetic diversity.

Evolutionary Biology↗

bioRxiv2016

Dynamics and fate of beneficial mutations under lineage contamination by linked deleterious mutations

Beneficial mutations drive adaptive evolution, yet their selective advantage does not ensure their fixation. Haldanes application of single-type branching process theory showed that genetic drift alone could cause the extinction of newly-arising beneficial mutations with high probability. With linkage, deleterious mutations will affect the dynamics of beneficial mutations and might further increase their extinction probability. Here, we model the lineage dynamics of a newly-arising beneficial mutation as a multitype branching process; this approach allows us to account for the combined effects of drift and the stochastic accumulation of linked deleterious mutations, which we call lineage contamination. We first study the lineage contamination phenomenon in isolation, deriving extinction times and probabilities of beneficial lineages. We then put the lineage contamination phenomenon into the context of an evolving population by incorporating the effects of background selection. We find that the survival probability of beneficial mutations is simply Haldanes classical formula multiplied by the correction factor [Formula], where U is deleterious mutation rate, [Formula] is mean selective advantage of beneficial mutations,{kappa} [isin] (1,{varepsilon} ], and{varepsilon} = 2 - e-1. We also find there exists a genomic deleterious mutation rate, [Formula], that maximizes the rate of production of surviving beneficial mutations, and that [Formula]. Both of these results, and others, are curiously independent of the fitness effects of deleterious mutations. We derive critical mutation rates above which: 1) lineage contamination alleviates competition among beneficial mutations, and 2) the adaptive substitution process all but shuts down.

Evolutionary Biology↗

bioRxiv2016

Population structure reduces the benefits from partner choice in mutualism

Mutualisms are key drivers of evolutionary and ecological processes. Understanding how different species can evolve to interact in mutually beneficial ways is an important goal of evolutionary theory, especially when the benefits require costly investments by the partners. For such costly investments to evolve, some sort of fitness feedback mechanism must exist that more than recoups the direct costs. Several such feedback mechanisms have been explored both theoretically and empirically, yet we know relatively little how they might act together, as they probably do in nature. In this paper, I model the joint action of three of the main mechanisms that can maintain symbiotic cooperation: partner choice by hosts, population structure amongst symbionts, and undirected rewards from hosts to symbionts. My results show that population structure reduces the benefit from partner choice to hosts. It may help or hinder beneficial symbionts and create positive or negative frequency dependence depending on the nature of host rewards to the symbiont. Strong population structure also makes it less likely that host choosiness and symbiont cooperation will be jointly maintained in a population. The intuition behind my results is that all else being equal, population structure reduces local variation available to the host to choose from. Thus, population structure is not always beneficial for the evolution of cooperation between species. My results also underscore the need to do full analyses of multiple mechanisms of social evolution to uncover their interactions to uncover the interactions between them.

Evolutionary Biology↗

bioRxiv2016

The frequency spectrum of chromatin accessibility in Yorubans points toward a significant role of random genetic drift in shaping the chromatin landscape

The function of non-coding variation in the human genome is hotly debated. While much of the genome appears to be involved in some kind of molecular activity, a relatively small portion of the genome appears to be conserved across mammalian species. To try to understand part of this seeming paradox, we examined chromatin accessibility as a model molecular phenotype. We modeled chromatin state as either open or closed as looked at the frequency of open chromatin across 70 Yoruban cell lines. We saw that most regions of chromatin accessibility occurred in only a small number of individuals, although there are a number of regions that are accessible across the entire panel. To delve further into understanding the evolutionary mechanisms, we examined nucleotide diversity in and around accessible regions. We found that in the open chromatin access, low frequency regions had decreased nucleotide diversity, however, they were situated within regions of elevated nucleotide diversity. These results point toward a role of random mutation and genetic drift shaping the distribution of accessible regions in the human genome.

Evolutionary Biology↗

bioRxiv2016

Modeling the multiple facets of speciation-with-gene-flow towards improving divergence history inference of a recent fish adaptive radiation.

Parallel divergence patterns across replicated species pairs occurring in similar environmental contrasts may arise through distinct evolutionary scenarios. Deciphering whether such parallelism actually reflects repeated parallel divergence driven by divergent selection or a single divergence event with subsequent gene flow needs to be ascertained. Reconstructing historical gene flow is therefore of fundamental interest to understand how demography and selection jointly shaped genomic divergence during speciation. Here, we use an extended modeling framework to explore the multiple facets of speciation-with-gene-flow with demo-genetic divergence models that capture both temporal and genomic variation in effective population size and migration rate. We investigate the divergence history of five sympatric Lake Whitefish limnetic (dwarf) and benthic (normal) species pairs characterized by variable degrees of ecological divergence and reproductive isolation. Genome-wide SNPs were used to document the extent of genetic differentiation in each species pair, and 26 divergence models were fitted and compared to the unfolded joint allele frequency spectrum of each pair. We found evidence that a recent (circa 3000-4000 generations) asymmetrical secondary contact between expanding post-glacial populations has accompanied Whitefish diversification. Our results suggest that heterogeneous genomic differentiation patterns have emerged through the combined effects of linked selection generating variable rates of lineage sorting across the genome during geographical isolation, and heterogeneous introgression eroding divergence at different rates across the genome upon secondary contact. This study thus provides a new retrospective insight into the historical demographic and selective processes that shaped a continuum of divergence associated with ecological speciation.

Evolutionary Biology↗

bioRxiv2016

Phylogenomic Analysis of Ants, Bees and Stinging Wasps: Improved Taxon Sampling Enhances Understanding of Hymenopteran Evolution

The importance of taxon sampling in phylogenetic accuracy is a topic of active debate. We investigated the role of taxon sampling in causing incongruent results between two recent phylogenomic studies of stinging wasps (Hymenoptera: Aculeata), a diverse lineage that includes ants, bees and the majority of eusocial insects. Using target enrichment of ultraconserved element (UCE) loci, we assembled the largest aculeate phylogenomic data set to date, sampling 854 loci from 187 taxa, including 30 out of 31 aculeate families, and a diversity of parasitoid outgroups. We analyzed the complete matrix using multiple analytical approaches, and also performed a series of taxon inclusion/exclusion experiments, in which we analyzed taxon sets identical to and slightly modified from the previous phylogenomic studies. Our results provide a highly supported phylogeny for virtually all aculeate lineages sampled, supporting ants as sister to Apoidea (bees+apoid wasps), bees as sister to Philanthinae+Pemphredoninae (lineages within a paraphyletic Crabronidae), Melittidae as sister to remaining bees, and paraphyly of cuckoo wasps (Chrysidoidea). Our divergence dating analyses estimate ages for aculeate lineages in close concordance with the fossil record. Our analyses also demonstrate that outgroup choice and taxon evenness can fundamentally impact topology and clade support in phylogenomic inference.

Evolutionary Biology↗

bioRxiv2016

Exploring evolutionary relationships across the genome using topology weighting

We introduce the concept of topology weighting, a method for quantifying relationships between taxa that are not necessarily monophyletic, and visualising how these relationships change across the genome. A given set of taxa can be related in a limited number of ways, but if each taxon is represented by multiple sequences, the number of possible topologies becomes very large. Topology weighting reduces this complexity by quantifying the contribution of each 'taxon topology' to the full tree. We describe our method for topology weighting by iterative sampling of sub-trees (Twisst), and test it on both simulated and real genomic data. Overall, we show that this is an informative and versatile approach, suitable for exploring relationships in almost any genomic dataset.\n\nScripts to implement the method described are available at github.com/simonhmartin/twisst.

Evolutionary Biology↗

bioRxiv2016

Gene-culture co-inheritance of a behavioral trait.

Human behavioral traits are complex phenotypes that result from both genetic and cultural transmission. But different inheritance systems need not favor the same phenotypic outcome. What happens when there are conflicting selection forces in the two domains? To address this question, we derive a Price equation that incorporates both cultural and genetic inheritance of a phenotype where the effects of genes and culture are additive. We then use this equation to investigate whether a genetically maladaptive phenotype can evolve under dual transmission. We examine the special case of altruism using an illustrative model, and show that cultural selection can overcome genetic selection when the variance in culture is sufficiently high with respect to genes. Finally, we show how our basic result can be extended to non-additive effects models. We discuss the implications of our results for understanding the evolution of maladaptive behaviors.

Evolutionary Biology↗

bioRxiv2016

A functional analysis of the contribution of climatic niche divergence to adaptive radiation

Elucidating how ecological and evolutionary mechanisms interact to produce and maintain biodiversity is a fundamental problem in evolutionary ecology. We investigate this issue by focusing on how physiological evolution affects performance and species coexistence along the thermal niche axis in replicated radiations of Anolis lizards, groups best known for resource partitioning based on morphological divergence. We find repeated divergence in thermal physiology within these radiations, and that this divergence significantly affects performance within natural thermal environments. Morphologically similar species that co-occur invariably differ in their thermal physiology, providing evidence that physiological divergence facilitates species co-existence within anole communities. Despite repeated divergence in traits of demonstrable ecological importance, phylogenetic comparative analyses indicate that physiological traits have evolved more slowly than key morphological traits related to the structural niche. Phylogenetic analyses also reveal that physiological divergence is correlated with divergence in broad-scale habitat climatic features commonly used to estimate thermal niche evolution, but that the latter incompletely predicts variation in the former. We provide comprehensive evidence for repeated adaptive evolution of physiological divergence within Anolis adaptive radiations, including the complementary roles of physiological and morphological divergence in promoting community-level diversity. We recommend greater integration of performance-based traits into analyses of climatic niche evolution, as they facilitate a more complete understanding of the phenotypic and ecological consequences of climatic divergence.

Evolutionary Biology↗

bioRxiv2016

Genome-scale rates of evolutionary change in bacteria

Estimating the rates at which bacterial genomes evolve is critical to understanding major evolutionary and ecological processes such as disease emergence, long-term host-pathogen associations, and short-term transmission patterns. The surge in bacterial genomic data sets provides a new opportunity to estimate these rates and reveal the factors that shape bacterial evolutionary dynamics. For many organisms estimates of evolutionary rate display an inverse association with the time-scale over which the data are sampled. However, this relationship remains unexplored in bacteria due to the difficulty in estimating genome-wide evolutionary rates, which are impacted by the extent of temporal structure in the data and the prevalence of recombination. We collected 36 whole genome sequence data sets from 16 species of bacterial pathogens to systematically estimate and compare their evolutionary rates and assess the extent of temporal structure in the absence of recombination. The majority (28/36) of data sets possessed sufficient clock-like structure to robustly estimate evolutionary rates. However, in some species reliable estimates were not possible even with \"ancient DNA\" data sampled over many centuries, suggesting that they evolve very slowly or that they display extensive rate variation among lineages. The robustly estimated evolutionary rates spanned several orders of magnitude, from 10-6 to 10-8 nucleotide substitutions site-1 year-1. This variation was largely attributable to sampling time, which was strongly negatively associated with estimated evolutionary rates, with this relationship best described by an exponential decay curve. To avoid potential estimation biases such time-dependency should be considered when inferring evolutionary time-scales in bacteria.

Evolutionary Biology↗

bioRxiv2016

A unifying comparative phylogenetic framework including traits coevolving across interacting lineages

Models of phenotypic evolution fit to phylogenetic comparative data are widely used to make inferences regarding the tempo and mode of trait evolution. A wide range of models is already available for this type of analysis, and the field is still under active development. One of the most needed developments concerns models that better account for the effect of within- and between-clade interspecific interactions on trait evolution, that can result from processes as diverse as competition, predation, parasitism, or mutualism. Here, we begin by developing a very general comparative phylogenetic framework for (multi)-trait evolution that can be applied to both ultrametric and non-ultrametric trees. This framework not only encapsulates all previous classical models of univariate and multivariate phenotypic evolution, but also paves the way for the consideration of a much broader series of models in which lineages co-evolve, meaning that trait changes in one lineage are influenced by the value of traits in other, interacting lineages. Next, we provide a standard way for deriving the probabilistic distribution of traits at tip branches under our framework. We show that a multivariate normal distribution remains the expected distribution for a broad class of models accounting for interspecific interactions. Our derivations allow us to fit various models efficiently, and in particular greatly reduce the computation time needed to fit the recently proposed phenotype matching model. Finally, we illustrate the utility of our framework by developing a toy model for mutualistic coevolution. Our framework should foster a new era in the study of coevolution from comparative data.

Evolutionary Biology↗

bioRxiv2016

XRN1 is a Species-Specific Virus Restriction Factor in Yeasts

In eukaryotes, the degradation of cellular mRNAs is accomplished by Xrn1p and the cytoplasmic exosome. Because viral RNAs often lack canonical caps or poly-A tails, they can also be vulnerable to degradation by these host exonucleases. Yeast lack sophisticated mechanisms of innate and adaptive immunity, but do use RNA degradation as an antiviral defense mechanism. One model is that the RNA of yeast viruses is subject to degradation simply as a side effect of the intrinsic exonuclease activity of proteins involved in RNA metabolism. Contrary to this model, we find a highly refined, species-specific relationship between Xrn1p and the \"L-A\" totiviruses of different Saccharomyces yeast species. We show that the gene XRN1 has evolved rapidly under positive natural selection in Saccharomyces yeast, resulting in high levels of Xrn1p protein sequence divergence from one yeast species to the next. We also show that these sequence differences translate to differential interactions with the L-A virus, where Xrn1p from S. cerevisiae is most efficient at controlling the L-A virus that chronically infects S. cerevisiae, and Xrn1p from S. kudriavzevii is most efficient at controlling the L-A-like virus that we have discovered within S. kudriavzevii. All Xrn1p orthologs are equivalent in their interaction with another virus-like parasite, the Ty1 retrotransposon. Thus, the activity of Xrn1p against totiviruses is not simply an incidental consequence of the enzymatic activity of Xrn1p, but rather Xrn1p co-evolves with totiviruses to maintain its potent antiviral activity and limit viral propagation in Saccharomyces yeasts. Consistent with this, we demonstrated that Xrn1p physically interacts with the Gag protein encoded by the L-A virus, suggesting a host-virus interaction that is more complicated than just Xrn1p-mediated nucleolytic digestion of viral RNAs.

Evolutionary Biology↗

bioRxiv2016

A non-zero variance of Tajima’s estimator for two sequences even for infinitely many unlinked loci

The population-scaled mutation rate,{theta} , is informative on the effective population size and is thus widely used in population genetics. We show that for two sequences and n unlinked loci, Tajimas estimator ([Formula]), which is the average number of pairwise differences, is not consistent and therefore its variance does not vanish even as n [->] {infty}. The non-zero variance of [Formula] results from a (weak) correlation between coalescence times even at unlinked loci, which, in turn, is due to the underlying fixed pedigree shared by all genealogies. We derive the correlation coefficient under a diploid, discrete-time, Wright-Fisher model, and we also derive a simple, closed-form lower bound. We also obtain empirical estimates of the correlation of coalescence times under demographic models inspired by large-scale human genealogies. While the effect we de scribe is small [Formula], it is important to recognize this feature of statistical population genetics, which runs counter to commonly held notions about unlinked loci.

Evolutionary Biology↗

bioRxiv2016

High GC Content Causes De Novo Created Proteins to be Intrinsically Disordered

De novo creation of protein coding genes involves formation of short ORFs from noncoding regions; some of these ORFs might then become fixed in the population. De novo created proteins need to, at the bare minimum, not cause serious harm to the organism, meaning that they should for instance not cause aggregation. Therefore, although the creation of the short ORFs could be truly random, but the fixation should be of subject to some selective pressure. The selective forces acting on de novo created proteins have been elusive and contradictory results have been reported. In Drosophila they are more disordered, i.e. are enriched in polar residues, than ancient proteins, while the opposite trend is present in yeast. To the best of our knowledge no valid explanation for this difference has been proposed.\n\nTo solve this riddle we studied structural properties and age of all proteins in 187 eukaryotic species. We find that, on average, there are small differences between proteins of different ages, with the exception that younger proteins are shorter. However, when we take the GC content into account we find that this can explain the opposite trends observed in yeast (low GC) and drosophila (high GC). GC content is correlated with codons coding for disorder-promoting amino acids, and inversely correlated with transmembrane, helix and sheet promoting residues. We find that for the youngest proteins, i.e. the ones that are most likely to be de novo created, there exists a strong correlation with GC and structural properties. In contrast, this strong relationship is not seen for ancient proteins. This leads us to propose that structural features are not a strong determining factor for fixation of de novo created genes. Instead these proteins resemble random proteins given a particular GC level. The dependency on GC content is then gradually weakened during evolution.\n\nAuthor SummaryWe show that the GC content of a genomic area is of great importance for the properties of a protein-coding de novo created gene. The GC content affects the frequency of the codons and this affects the probability for each amino acid to be included in a de novo created protein. The codons encoding for Ala, Pro and Glu contain 80% GC, while codons for Lys, Phe, Asn, Tyr and Ile contain 20% or less. Pro and Gly are disorder-promoting, while Phe, Tyr and Ile are order-promoting. Therefore random protein sequences at a high GC will be more disordered than the ones created at a low GC. The structural properties of the youngest (orphan) proteins match to a large degree the properties of random proteins when the GC content is taken into account. In contrast structural properties of ancient proteins only show a weak correlation with GC content. This suggests that even after fixation of de novo created proteins largely resemble random proteins given a certain GC content. Thereafter, during evolution the correlation between structural properties and GC weakens.

Evolutionary Biology↗

bioRxiv2016

Pherotype polymorphism in Streptococcus pneumoniae and its effects on population structure and recombination

Natural transformation in the Gram-positive pathogen Streptococcus pneumoniae occurs when cells become \"competent\", a state that is induced in response to high extracellular concentrations of a secreted peptide signal called CSP (Competence Stimulating Peptide) encoded by the comC locus. Two main CSP signal types (pherotypes) are known to dominate the pherotype diversity across strains. Using thousands of fully sequenced pneumococcal genomes, we confirm that pneumococcal populations are highly genetically structured and that there is significant variation among diverged populations in pherotype frequencies; most carry only a single pherotype. Moreover, we find that the relative frequencies of the two dominant pherotypes significantly vary within a small range across geographical sites. It has been variously proposed that pherotypes either promote genetic exchange among cells expressing the same pherotype, or conversely that they promote recombination between strains bearing different pherotypes. We distinguish these hypotheses using a bioinformatics approach by estimating recombination frequencies within and between pherotypes across 4,089 full genomes. Despite underlying population structure, we observe extensive recombination between populations; additionally, we found significantly higher rates of genetic exchange between strains expressing different pherotypes than among isolates carrying the same pherotype. Our results indicate that pherotypes do not restrict, and marginally facilitate, recombination between strains. Furthermore, our results suggest that the CSP balanced polymorphism does not causally underlie population differentiation. Therefore, when strains carrying different pherotypes encounter one another during co-colonization, genetic exchange can freely occur.

Evolutionary Biology↗

bioRxiv2016

Viral outbreaks involve destabilised viruses: evidence from Ebola, Influenza and Zika

Recent history has provided us with one pandemic (Influenza A/H1N1) and two severe viral outbreaks (Ebola and Zika). In all three cases, post-hoc analyses have given us deep insights into what triggered these outbreaks, their timing, evolutionary dynamics, and phylogeography, but the genomic characteristics of outbreak viruses are still unclear. To address this outstanding question, we searched for a common denominator between these recent outbreaks, positing that the genome of outbreak viruses is in an unstable evolutionary state, while that of non-outbreak viruses is stabilized by a network of correlated substitutions. Here, we show that during regular epidemics, viral genomes are indeed stabilized by a dense network of weakly correlated sites, and that these networks disappear during pandemics and outbreaks when rates of evolution increase transiently. Post-pandemic, these evolutionary networks are progressively re-established. We finally show that destabilization is not caused by substitutions targeting epitopes, but more likely by changes in the environment sensu lato. Our results prompt for a new interpretation of pandemics as being associated with evolutionary destabilized viruses.

Evolutionary Biology↗

bioRxiv2016

Natural and laboratory mutations in kuzbanian are associated with heavy metal stress phenotypes in Drosophila melanogaster

Organisms must cope with altered environmental conditions such as high concentrations of heavy metals. Stress response to heavy metals is mediated by the metal-responsive transcription factor 1 (MTF-1), which is conserved from Drosophila to humans. MTF-1 binds to metal response elements (MREs) and changes the expression of target genes. kuzbanian (kuz), a metalloendopeptidase that activates the evolutionary conserved Notch signaling pathway, has been identified as an MTF-1 target gene. We have previously identified a putatively adaptive transposable element in the Drosophila melanogaster genome, named FBti0019170, inserted in a kuz intron. In this work, we investigated whether laboratory-induced mutations in kuz are associated with zinc stress phenotypes. We found that both embryos and adult flies overexpressing kuz are more tolerant to zinc compared with wild-type flies. On the other hand, we found that the effect of FBti0019170 on zinc stress tolerance depends on developmental stage and genetic background. Moreover, in the majority of the genetic backgrounds analyzed, FBti0019170 has a deleterious effect in unpolluted environments in pre-adult stages. These results highlight the complexity of natural mutations and suggest that besides laboratory-induced mutations natural mutations need to be studied in order to accurately characterize gene function and evolution.

Evolutionary Biology↗

bioRxiv2016

Escherichia coli populations adapt to complex, unpredictable fluctuations by minimizing trade-offs across environments

In nature, organisms are simultaneously exposed to multiple stresses (i.e. complex environments) that often fluctuate unpredictably. While both these factors have been studied in isolation, the interaction of the two remains poorly explored. To address this issue, we selected laboratory populations of Escherichia coli under complex (i.e. stressful combinations of pH, H2O2 and NaCl) unpredictably fluctuating environments for ~900 generations. We compared the growth rates and the corresponding trade-off patterns of these populations to those that were selected under constant values of the component stresses (i.e. pH, H2O2 and NaCl) for the same duration. The fluctuation-selected populations had greater mean growth rate and lower variation for growth rate over all the selection environments experienced. However, while the populations selected under constant stresses experienced trade-offs in the environments other than those in which they were selected, the fluctuation-selected populations could by-pass the across-environment trade-offs almost entirely. Interestingly, trade-offs were found between growth rates and carrying capacities. The results suggest that complexity and fluctuations can strongly affect the underlying trade-off structure in evolving populations.

Evolutionary Biology↗