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bioRxiv2016

Using the Price equation to analyze multi-level selection on the reproductive policing mechanism of bacterial plasmids

The replication control system of non-conjugative bacterial plasmids constitutes a simple and elegant example of a reproductive policing mechanism that moderates competition in the intra-cellular replication pool and establishes a mutually beneficial partnership among plasmids within a bacterial host and between plasmids and their hosts. The emergence of these partnerships is a product of the conflict between the evolutionary interests of hosts, who seek to maximize their growth rates within the population, and plasmids, who seek to maximize their growth rates within hosts. We employ a multi-scale computational model describing the growth, division and death of hosts, as well as the independent replication of plasmids within hosts, in order to investigate the implications of this conflict for the evolution of the plasmid replication parameters. We apply the multi-level form of the Price equation in order to quantify and elucidate the various selective pressures that drive the evolution of plasmid replication control. Our analysis shows how the evolution of the constituent components of the plasmid replication control system are shaped by selection acting at the level of hosts and the level of plasmids. In addition, we calculate finer-grained selective pressures that are attributed to atomic plasmid-related events (such as intra-cellular replication and plasmid loss due to host death) and demonstrate their special role at the early stages of the evolution of policing. Our approach constitutes a novel application of the Price equation for discerning and discussing the synergies between the levels of selection given the availability of a mechanistic model for the generation of the systems dynamics. We show how the Price equation, particularly in its multi-level form, can provide significant insight by quantifying the relative importance of the various selective forces that shape the evolution of policing in bacterial plasmids.

Evolutionary Biology↗

bioRxiv2016

An efficient field and laboratory workflow for plant phylotranscriptomic projects

O_LIPremise of the study: We describe a field and lab workflow developed for plant phylotranscriptomic projects, involving field collected cryogenic tissues, RNA extraction and quality control, and library preparation. We also make recommendations for sample curation.\nC_LIO_LIMethods and Results: 216 frozen tissue samples of Caryophyllales and other angiosperm taxa were collected from the field or botanical gardens and were subjected to RNA extraction, stranded mRNA library preparation and sequencing on Illumina HiSeq platforms. These include difficult mucilaginous tissues such as those of Cactaceae and Droseraceae.\nC_LIO_LIConclusions: Our workflow is not only cost effective (~$270 per sample, as of August 2016, from tissue to reads) and time efficient (~5 hours a sample including all lab work and sample curation), but has proven robust for extraction of difficult samples such as tissues containing high levels of secondary compounds.\nC_LI

Evolutionary Biology↗

bioRxiv2016

Spatiotemporal patterns of desiccation tolerance in natural populations of Drosophila melanogaster

Water availability is a major environmental challenge to a variety of terrestrial organisms. In insects, desiccation tolerance varies predictably over various spatial and temporal scales and is an important physiological basis of fitness variation among natural populations. Here, we examine the dynamics of desiccation tolerance in North American populations of Drosophila melanogaster using: 1) natural populations sampled across latitudes and seasons in the eastern USA; 2) experimental evolution in the field in response to changing seasonal environments; 3) a sequenced panel of inbred lines (DGRP) to perform genome wide associations and examine whether SNPs/genes associated with variation in desiccation tolerance exhibit patterns of clinal and/or seasonal enrichment in pooled sequencing of populations. In natural populations we observed a shallow cline in desiccation tolerance, for which tolerance exhibited a positive association with latitude; the steepness of this cline increased with decreasing culture temperature, demonstrating a significant degree of thermal plasticity. No differences in desiccation tolerance were observed between spring and autumn collections from three mid-to-northern latitude populations, or as a function of experimental evolution to seasonality. Similarly, water loss rates did not vary significantly among latitudinal, seasonal or experimental evolution populations. However, changes in metabolic rates during prolonged exposure to dry conditions indicate increased tolerance in higher latitude populations. Genome wide association studies identified thirty-six SNPs in twenty-eight genes associated with sex-averaged drought tolerance. Among North American populations, genes associated with drought tolerance do not show increased signatures of spatially varying selection relative to the rest of the genome, whereas among Australian populations they do.

Evolutionary Biology↗

bioRxiv2016

Fitness-valley crossing in subdivided asexual populations

Adaptations may require multiple mutations that are beneficial only in combination. To adapt, a lineage must acquire mutations that are individually neutral or deleterious before gaining the beneficial combination, thereby crossing a plateau or valley, respectively, in the mapping from genotype to fitness. Spatial population structure can facilitate plateau and valley crossing by allowing neutral and deleterious lineages to survive longer and produce more beneficial mutants. Here, we analyze adaptation across a two-mutation plateau or valley in an asexual population that is subdivided into discrete subpopulations, or demes, connected by migration. We describe how subdivision alters the dynamics of adaptation from those in an equally sized unstructured population and give a complete quantitative description of these dynamics for the island migration model. Subdivision can significantly decrease the waiting time for the adaptation if demes and migration rates are small enough that single-mutant lineages fix in one or more demes before producing the beneficial double mutant. But, the potential decrease is small in very large populations and may also be limited by the slow spread of the beneficial mutant in extremely subdivided populations. Subdivision has a smaller effect on the probability that the population adapts very quickly than on the mean time to adapt, which has important consequences in some applications, such as the development of cancer. Our results provide a general and intuitive framework for predicting the effects of spatial structure in other models and in natural populations.

Evolutionary Biology↗

bioRxiv2016

Reproductive Isolation through Experimental Manipulation of Sexually Antagonistic Coevolution in Drosophila Melanogaster

Promiscuity can drive the evolution of sexual conflict before and after mating occurs. Post-mating, the male ejaculate can selfishly manipulate female physiology leading to a chemical arms race between the sexes. Theory suggests that drift and sexually antagonistic coevolution can cause allopatric populations to evolve different chemical interactions between the sexes, thereby leading to postmating reproductive barriers and speciation. There is, however, little empirical evidence supporting this form of speciation. We tested this theory by creating an experimental evolutionary model of Drosophila melanogaster populations undergoing different levels of interlocus sexual conflict. We found that allopatric populations under elevated sexual conflict show assortative mating indicating premating reproductive isolation. Further, these allopatric populations also show reduced copulation duration and sperm defense ability when mating happens between individuals between individuals across populations compared to that within the same population, indicating postmating prezygotic isolation. Sexual conflict can cause reproductive isolation in allopatric populations through the coevolution of chemical (postmating prezygotic) as well as behavioural (premating) interaction between the sexes. Thus, to our knowledge, we provide the first comprehensive evidence of postmating (as well as premating) reproductive isolation due to sexual conflict.

Evolutionary Biology↗

bioRxiv2016

Optimal foraging models reveal barriers and stepping stones to the evolution of host-range generalism in bacteriophage

The nature and stability of coexistence of specialist species with more generalized competitors present theoretical questions that have been difficult to resolve. Recent surveys of bacteriophage host-ranges suggest that generalist phage often coexistent with specialists. However, previous theoretical work has explained this coexistence only in terms of strict genetic trade-offs, which are not consistently observed when phage are challenged to evolve to multiple hosts in laboratory environments. Here we use the framework of optimal foraging to identify conditions that might prevent generalists from outcompeting specialist relatives. Our analysis shows that heterogeneities in phage life-history properties make host-range specialist more viable, and that endogenous fluctuations in host density permit a narrow window of stable coexistence between specialists and generalists without the need for genetic trade-offs. These results are especially relevant for understanding the barriers to the evolution of broader host-ranges in bacteriophage and other pathogens with similar life-cycles.

Evolutionary Biology↗

bioRxiv2016

Sexual selection drives floral scent diversification in carnivorous pitcher plants (NA Sarraceniaceae)

Plant volatiles play vital roles in signaling with their insect associates. Empirical studies show that both pollinators and herbivores exert strong selective pressures on plant phenotypes. While studies often evoke the assumption that volatiles from floral and vegetative tissues are distinct due to strong pollinator-mediated selection operating on the flowers or selection from herbivores acting on the leaves, explicit tests of these assumptions are often lacking. In this study, we examined the evolution of floral and vegetative volatiles in the North American (NA) pitcher plants (Sarraceniaceae). In these taxa, insects are attracted for both pollination and prey capture, providing an ideal opportunity to understand the evolution of scent compounds across different plant organs. We collected a comprehensive dataset of floral and vegetative volatiles from across the NA Sarraceniaceae. We used multivariate analysis methods to examine whether volatile profiles are distinct between plant tissues, and investigated rates of scent evolution in these unique taxa. Our major findings revealed that (i) flowers and pitchers produced highly distinct scent profiles, consistent with the hypothesis that volatiles alleviate trade-offs due to incidental pollinator consumption; (ii) across species, floral scent separated into distinct regions of scent space, while pitchers showed little evidence of clustering - this may be due to convergence on a generalist strategy for insect capture; and (iii) rates of scent evolution depended on tissue type, suggesting that pollinators and herbivores differentially influence the evolution of chemical traits. We emphasize the need for additional functional studies to further distinguish between volatile functions.

Evolutionary Biology↗

bioRxiv2016

2b or not 2b: Experimental evolution of functional exogenous sequences in a plant RNA virus

Horizontal gene transfer (HGT) is pervasive in viruses, and thought to be a key mechanism in their evolution. On the other hand, strong selective constraints against increasing genome size are an impediment for HGT, rapidly purging horizontally transferred sequences and thereby potentially hindering evolutionary innovation. Here we explore experimentally the evolutionary fate of viruses with simulated HGT events, using the plant RNA virus Tobacco etch virus (TEV), by separately introducing two functional, exogenous sequences to its genome. One of the events simulates the acquisition of a new function though HGT of a conserved AlkB domain, responsible for the repair of alkylation or methylation damage in many organisms. The other event simulates the acquisition of a sequence that duplicates an existing function, through HGT of the 2b RNA silencing suppressor from Cucumber mosaic virus (CMV). We then evolved these two viruses, tracked the maintenance of the horizontally transferred sequences over time, and for the final virus populations, sequenced their genome and measured viral fitness. We found that the AlkB domain was rapidly purged from the TEV genome, restoring fitness to wild-type levels. Conversely, the 2b gene was stably maintained and did not have a major impact on viral fitness. Moreover, we found that 2b is functional in TEV, as it provides a replicative advantage when the RNA silencing suppression domain of HC-Pro is mutated. These observations suggest a potentially interesting role for HGT of short functional sequences in ameliorating evolutionary constraints on viruses, through the duplication of functions.

Evolutionary Biology↗

bioRxiv2016

CLEAR: Composition of Likelihoods for Evolve And Resequence Experiments

Experimental evolution (EE) studies are powerful tools for observing molecular evolution \"in-action\" from populations sampled in controlled and natural environments. The advent of next generation sequencing technologies has made whole-genome and whole-population sampling possible, even for eukaryotic organisms with large genomes, and allowed us to locate the genes and variants responsible for genetic adaptation. While many computational tests have been developed for detecting regions under selection, they are mainly designed for static (single time) data, and work best when the favored allele is close to fixation.\n\nEE studies provide samples over multiple time points, underscoring the need for tools that can exploit the data. At the same time, EE studies are constrained by the limited time span since onset of selection, depending upon the generation time for the organism. This constraint impedes adaptation studies, as the population can only be evolve-and-resequenced for a small number of generations relative to the fixation time of the favored allele. Moreover, coverage in pool-sequenced experiments varies across replicates and time points, leading to heterogeneous ascertainment bias in measuring population allele frequency across different measurements.\n\nIn this article, we directly address these issues while developing tools for identifying selective sweep in pool-sequenced EE of sexual organisms and propose Composition of Likelihoods for Evolve-And-Resequence experiments (CO_SCPLOWLEARC_SCPLOW). Extensive simulations show that CO_SCPLOWLEARC_SCPLOW achieves higher power in detecting and localizing selection over a wide range of parameters. In contrast to existing methods, the CO_SCPLOWLEARC_SCPLOW statistics are robust to variation of coverage. CO_SCPLOWLEARC_SCPLOW also provides robust estimates of model parameters, including selection strength and overdominance, as byproduct of the statistical test, while being orders of magnitude faster than existing methods. Finally, we apply the CO_SCPLOWLEARC_SCPLOW statistic to data from a study of D. melanogaster adaptation to alternating temperatures and discover enrichment of genes related to \"response to heat\" and \"cold acclimation\".

Evolutionary Biology↗

bioRxiv2016

Contrasting patterns of genome-level diversity across distinct co-occurring bacterial populations

To understand the forces driving differentiation and diversification in wild bacterial populations, we must be able to delineate and track ecologically relevant units through space and time. Mapping metagenomic sequences to reference genomes derived from the same environment can reveal genetic heterogeneity within populations, and in some cases, be used to identify boundaries between genetically similar, but ecologically distinct, populations. Here we examine population-level heterogeneity within abundant and ubiquitous freshwater bacterial groups such as the acI Actinobacteria and LD12 Alphaproteobacteria (the freshwater sister clade to the marine SAR11) using 33 single cell genomes and a 5-year metagenomic time series. The single cell genomes grouped into 15 monophyletic clusters (termed \"tribes\") that share at least 97.9% 16S rRNA identity. Distinct populations were identified within most tribes based on the patterns of metagenomic read recruitments to single-cell genomes representing these tribes. Genetically distinct populations within tribes of the acI actinobacterial lineage living in the same lake had different seasonal abundance patterns, suggesting these populations were also ecologically distinct. In contrast, sympatric LD12 populations were less genetically differentiated. This suggests that within one lake, some freshwater lineages harbor genetically discrete (but still closely related) and ecologically distinct populations, while other lineages are composed of less differentiated populations with overlapping niches. Our results point at an interplay of evolutionary and ecological forces acting on these communities that can be observed in real time.

Evolutionary Biology↗

bioRxiv2016

Fast Inference of Individual Admixture Coefficients Using Geographic Data

Accurately evaluating the distribution of genetic ancestry across geographic space is one of the main questions addressed by evolutionary biologists. This question has been commonly addressed through the application of Bayesian estimation programs allowing their users to estimate individual admixture proportions and allele frequencies among putative ancestral populations. Following the explosion of high-throughput sequencing technologies, several algorithms have been proposed to cope with computational burden generated by the massive data in those studies. In this context, incorporating geographic proximity in ancestry estimation algorithms is an open statistical and computational challenge. In this study, we introduce new algorithms that use geographic information to estimate ancestry proportions and ancestral genotype frequencies from population genetic data. Our algorithms combine matrix factorization methods and spatial statistics to provide estimates of ancestry matrices based on least-squares approximation. We demonstrate the benefit of using spatial algorithms through extensive computer simulations, and we provide an example of application of our new algorithms to a set of spatially referenced samples for the plant species Arabidopsis thaliana. Without loss of statistical accuracy, the new algorithms exhibit runtimes that are much shorter than those observed for previously developed spatial methods. Our algorithms are implemented in the R package, tess3r.

Evolutionary Biology↗

bioRxiv2016

The coevolution of social learning and sensitivity to changing environments

AO_SCPLOWBSTRACTC_SCPLOWThere is widespread agreement that social and individual learning are adaptations to varying environments. However, existing theory assumes that organisms cannot detect changes in the environment and instead adapt to averages. This paper develops the first analytical model that allows for the simultaneous coevolution of socially learned traditions, reliance on social learning, and signal detection for environmental change. There are numerous conditions under which detection can be stable once common but cannot invade the population when rare. When signal detection is maintained by selection, it always leads to pure separating equilibria at which organisms always learn individually when they believe the environment has recently changed and otherwise always learn socially. Detection can increase mean fitness at equilibrium, but it may also reduce it.

evolutionary biology↗

bioRxiv2016

Bayesian Analysis of Evolutionary Divergence with Genomic Data Under Diverse Demographic Models

We present a new Bayesian method for estimating demographic and phylogenetic history using population genomic data. Several key innovations are introduced that allow the study of diverse models within an Isolation with Migration framework. For the Markov chain Monte Carlo (MCMC) phase of the analysis, we use a reduced state space, consisting of simple coalescent trees without migration paths, and a simple importance sampling distribution without demography. Migration paths are analytically integrated using a Markov chain as a representation of genealogy. The new method is scalable to a large number of loci with excellent MCMC mixing properties. Once obtained, a single sample of trees is used to calculate the joint posterior density for model parameters under multiple diverse demographic models, without having to repeat MCMC runs. As implemented in the computer program MIST, we demonstrate the accuracy, scalability and other advantages of the new method using simulated data and DNA sequences of two common chimpanzee subspecies: Pan troglodytes troglodytes (P. t.) and P. t. verus.

Evolutionary Biology↗

bioRxiv2016

Effect of error and missing data on population structure inference using microsatellite data

Missing data and genotyping errors are common in microsatellite data sets. We used simulated data to quantify the effect of these data aberrations on the accuracy of population structure inference. Data sets with complex, randomly-generated, population histories were simulated under the coalescent. Models describing the characteristic patterns of missing data and genotyping error in real microsatellite data sets were used to modify the simulated data sets. Accuracy of ordination, tree-based, and model-based methods of inference was evaluated before and after data set modifications. The ability to recover correct population clusters decreased as missing data increased. The rate of decrease was similar among analytical procedures, thus no single analytical approach was preferable. For every 1% of a data matrix that contained missing genotypes, 2-4% fewer correct clusters were found. For every 1% of a matrix that contained erroneous genotypes, 1-2% fewer correct clusters were found using ordination and tree-based methods. Model-based procedures that minimize the deviation from Hardy-Weinberg equilibrium in order to assign individuals to clusters performed better as genotyping error increased. We attribute this surprising result to the inbreeding-like nature of microsatellite genotyping error, wherein heterozygous genotypes are mischaracterized as homozygous. We show that genotyping error elevates estimates of the level of genetic admixture. Overall, missing data negatively impact population structure inference more than typical genotyping errors.

evolutionary biology↗

bioRxiv2016

Topological features of gene regulatory networks predict patterns of natural diversity in environmental response

Molecular interactions affect the evolution of complex traits. For instance, adaptation may be constrained by pleiotropic or epistatic effects, both of which will be reflected in the structure of molecular interaction networks. To date, empirical studies investigating the role of molecular interactions in phenotypic evolution have been idiosyncratic, offering no clear patterns. Here, we investigated the network topology of genes putatively involved in local adaptation to two abiotic stressors--drought and cold--in Arabidopsis thaliana. Our findings suggest that the gene-interaction topologies for both cold and drought stress response are non-random, with genes that show genetic variation in drought response (GxE) being significantly more peripheral and cold response genes being significantly more central than genes not involved in either response. We suggest that the observed topologies reflect different constraints on the genetic pathways involved in the assayed phenotypes. The approach presented here may inform predictive models linking genetic variation in molecular signaling networks with phenotypic variation, specifically traits involved in environmental response.\n\nSignificance StatementOur study focuses on genes whose transcriptional activity exhibits genetic variation in response to the environment, or \"GxE.\" GxE is a widely observed phenomenon of critical importance to understanding the genotype-to-phenotype map, the evolution of natural populations, medical genetics, population response to climate change, and agricultural improvement. We investigated expression GxE in plant responses to two abiotic cues: cold and drought. We found that genes showing genetically variable response to cold stress are centrally located in regulatory networks whereas genes showing genetically variable response to drought stress are peripherally located in regulatory networks. This result suggests that selection is presented with vastly different mutational landscapes for shaping evolutionary or breeding response to these two important climatic factors

evolutionary biology↗

bioRxiv2016

Grow with the flow: a latitudinal cline in physiology is associated with more variable precipitation in Mimulus cardinalis

Local adaptation is commonly observed in nature: organisms perform well in their natal environment, but poorly outside it. Correlations between traits and latitude, or latitudinal clines, are among the most common pieces of evidence for local adaptation, but identifying the traits under selection and the selective agents is challenging. Here, we investigated a latitudinal cline in growth and photosynthesis across 16 populations of the perennial herb Erythranthe cardinalis (Phrymaceae). Using machine learning methods, we identify interannual variation in precipitation as a likely selective agent: Southern populations from more variable environments had higher photosynthetic rates and grew faster. We hypothesize that selection may favor a more annualized life history - grow now rather than save for next year - in environments where severe droughts occur more often. Thus our study provides insight into how species may adapt if Mediterranean climates become more variable due to climate change.

evolutionary biology↗

bioRxiv2016

Evolutionary rescue in randomly mating, selfing, and clonal populations

Severe environmental change can drive a population extinct unless the population adapts in time to the new conditions (\"evolutionary rescue\"). How does bi-parental sexual reproduction influence the chances of population persistence compared to clonal reproduction or selfing? In this paper, we set up a one-locus two-allele model for adaptation in diploid species, where rescue is contingent on the establishment of the mutant homozygote. Reproduction can occur by random mating, selfing, or clonally. Random mating generates and destroys the rescue mutant; selfing is efficient at generating it but at the same time depletes the heterozygote, which can lead to a low mutant frequency in the standing genetic variation and also affects the establishment probability of the mutation. Due to these antagonistic effects, we find a non-trivial dependence of population survival on the rate of sex/selfing, which is strongly affected by the dominance coefficient of the mutation before and after the environmental change. Importantly, since mating with the wildtype breaks the mutant homozygote up, a slow decay of the wildtype population size can impede rescue in randomly mating populations.

evolutionary biology↗

bioRxiv2016

Pervasive adaptation in Plasmodium-interacting proteins in mammals

The protozoan genus Plasmodium causes malaria in dozens of mammal species, including humans, non-human primates, rodents, and bats. In humans, Plasmodium infections have caused hundreds of millions of documented deaths, imposing strong selection on certain populations and driving the emergence of several resistance alleles. Over the deep timescale of mammalian evolution, however, little is known about host adaptation to Plasmodium. In this work, we expand the collection of known Plasmodium-interacting-proteins (PIPs) in mammalian hosts from ~10 to 410, by manually curating thousands of scientific abstracts. We use comparative tests of adaptation to show that PIPs have experienced >3 times more positive selection than similar mammalian proteins, consistent with Plasmodium as a major and long-standing selective pressure. PIP adaptation is strongly linked to gene expression in the blood, liver, and lung, all of which are clinically relevant tissues in Plasmodium infection. Interestingly, we find that PIPs with immune functions are especially enriched for additional interactions with viruses or bacteria, which together drive a 3.7-fold excess of adaptation. These pleiotropic interactions with unrelated pathogens, along with pressure from other Plasmodium-like Apicomplexan parasites, may help explain the PIP adaptation we observe in all clades of the mammalian tree. As a case study, we also show that alpha-spectrin, the major membrane component of mammalian red blood cells, has experienced accelerated adaptation in domains known to interact specifically with Plasmodium proteins. Similar interactions with Plasmodium-like parasites appear to have driven substantial adaptation in hundreds of host proteins throughout mammalian evolution.

evolutionary biology↗