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bioRxiv2016

Approximate Likelihood Inference of Complex Population Histories and Recombination from Multiple Genomes

We introduce ABLE (Approximate Blockwise Likelihood Estimation), a novel composite likelihood framework based on a recently introduced summary of sequence variation: the blockwise site frequency spectrum (bSFS). This simulation-based framework uses the the frequencies of bSFS configurations to jointly model demographic history and recombination and is explicitly designed to make inference using multiple whole genomes or genome-wide multi-locus data (e.g. RADSeq) catering to the needs of researchers studying model or non-model organisms respectively. The flexible nature of our method further allows for arbitrarily complex population histories using unphased and unpolarized whole genome sequences. In silico experiments demonstrate accurate parameter estimates across a range of divergence models with increasing complexity, and as a proof of principle, we infer the demographic history of the two species of orangutan from multiple genome sequences (over 160 Mbp in length) from each species. Our results indicate that the two orangutan species split approximately 650-950 thousand years ago but experienced a pulse of secondary contact much more recently, most likely during a period of low sea-level South East Asia ([~]300,000 years ago). Unlike previous analyses we can reject a history of continuous gene flow and co-estimate genome-wide recombination. ABLE is available for download at https://github.com/champost/ABLE.

Evolutionary Biology↗

bioRxiv2016

A phylogenetic codon substitution model for antibody lineages

Phylogenetic methods have shown promise in understanding the development of broadly neutralizing antibody lineages (bNAbs). However, the mutational process that generates these lineages - somatic hypermutation (SHM) - is biased by hotspot motifs, which violates important assumptions in most phylogenetic substitution models. Here, we develop a modified GY94-type substitution model that partially accounts for this context-dependency while preserving independence of sites during calculation. This model shows a substantially better fit to three well-characterized bNAb lineages than the standard GY94 model. We show through simulations that accounting for hotspot motifs can lead to reduced bias of other substitution parameters, and more accurate ancestral state reconstructions. We also demonstrate how our model can be used to test hypotheses concerning the roles of different hotspot and coldspot motifs in the evolution of B-cell lineages. Further, we explore the consequences of the idea that the number of hotspot motifs - and perhaps the mutation rate in general - is expected to decay over time in individual bNAb lineages.

Evolutionary Biology↗

bioRxiv2016

Quantifying the evolutionary potential and constraints of a drug-targeted viral protein

RNA viruses are notorious for their ability to evolve rapidly under selection in novel environments. It is known that the high mutation rate of RNA viruses can generate huge genetic diversity to facilitate viral adaptation. However, less attention has been paid to the underlying fitness landscape that represents the selection forces on viral genomes. Here we systematically quantified the distribution of fitness effects (DFE) of about 1,600 single amino acid substitutions in the drug-targeted region of NS5A protein of Hepatitis C Virus (HCV). We found that the majority of non-synonymous substitutions incur large fitness costs, suggesting that NS5A protein is highly optimized in natural conditions. We characterized the adaptive potential of HCV by subjecting the mutant viruses to selection by the antiviral drug Daclatasvir. Both the selection coefficient and the number of beneficial mutations are found to increase with the level of environmental stress, which is modulated by the concentration of Daclatasvir. The changes in the spectrum of beneficial mutations in NS5A protein can be explained by a pharmacodynamics model describing viral fitness as a function of drug concentration. We test theoretical predictions regarding the distribution of beneficial fitness effects of mutations. We also interpret the data in the context of Fishers Geometric Model and find an increased distance to optimum as a function of environmental stress. Finally, we show that replication fitness of viruses is correlated with the pattern of sequence conservation in nature and viral evolution is constrained by the need to maintain protein stability.

Evolutionary Biology↗

bioRxiv2016

Accuracy of demographic inferences from Site Frequency Spectrum: The case of the Yoruba population

Some methods for demographic inference based on the observed genetic diversity of current populations rely on the use of summary statistics such as the Site Frequency Spectrum (SFS). Demographic models can be either model-constrained with numerous parameters such as growth rates, timing of demographic events and migration rates, or model-flexible, with an unbounded collection of piecewise constant sizes. It is still debated whether demographic histories can be accurately inferred based on the SFS. Here we illustrate this theoretical issue on an example of demographic inference for an African population. The SFS of the Yoruba population (data from the 1000 Genomes Project) is fit to a simple model of population growth described with a single parameter (e.g., founding time). We infer a time to the most recent common ancestor of 1.7 million years for this population. However, we show that the Yoruba SFS is not informative enough to discriminate between several different models of growth. We also show that for such simple demographies, the fit of one-parameter models outperforms the model-flexible method recently developed by Liu and Fu. The use of this method on simulated data suggests that it is biased by the noise intrinsically present in the data.

Evolutionary Biology↗

bioRxiv2016

Combining phenotypic and genomic approaches reveals no evidence for adaptation to the local mutualist in Medicago lupulina

Local adaptation is a common but not ubiquitous feature of species interactions, and understanding the circumstances under which it evolves illuminates the factors that influence adaptive population divergence. Antagonistic species interactions dominate the local adaptation literature relative to mutualistic ones, preventing an overall assessment of adaptation within interspecific interactions. Here, we tested whether the legume Medicago lupulina is adapted to the locally abundant species of mutualistic nitrogen-fixing bacteria (\"rhizobia\"), which vary in frequency across its eastern North American range. We reciprocally inoculated northern and southern M. lupulina genotypes with the northern (Ensifer medicae) or southern bacterium (E. meliloti) in a greenhouse experiment. Neither northern nor southern plants produced more seed flowered earlier, or were more likely to flower when inoculated with their local rhizobium species, although plants produced more root nodules (the structures that house the bacteria) wit their local rhizobia. We used a pre-existing dataset to perform a genome scan for loci that showed elevated differentiation between field-collected plants that hosted different bacteria. None of the loci we identified belonged to the well-characterized suite of legume-rhizobia symbiosis genes, suggesting that the rhizobia do not drive genetic divergence between M. lupulina populations. Our results demonstrate that symbiont local adaptation is weak in this mutualism despite large-scale geographic variation in the identity of the interacting species.

Evolutionary Biology↗

bioRxiv2016

Determining the role of inflammation in the selection of JAK2 mutant cells in myeloproliferative neoplasms

Myeloproliferative neoplasm (MPN) is a hematologic malignancy characterized by the clonal outgrowth of hematopoietic cells with a somatically acquired mutation most commonly in JAK2 (JAK2V 617F). This mutation endows upon myeloid progenitors cytokine independent growth and consequently leads to excessive production of myeloid lineage cells. It has been previously suggested that inflammation may play a role in the clonal evolution of JAK2V 617F mutants. In particular, it is possible that one or more cellular kinetic parameters of hematopoietic stem cells (HSCs) are affected by inflammation, such as division or death rates of cells, and the probability of HSC differentiation. This suggests a mechanism that can steer the outcome of the cellular competition in favor of the mutants, initiating the disease. In this paper we create a number of mathematical evolutionary models, from very abstract to more concrete, that describe cellular competition in the context of inflammation. It is possible to build a model axiomatically, where only very general assumptions are imposed on the modeling components and no arbitrary (and generally unknown) functional forms are used, and still generate a set of testable predictions. In particular, we show that, if HSC death is negligible, the evolutionary advantage of mutant cells can only be conferred by an increase in differentiation probability of HSCs in the presence of inflammation, and if death plays a significant role in the dynamics, an additional mechanism may be an increase of HSCs division-to-death ratio in the presence of inflammation. Further, we show that in the presence of inflammation, the wild type cell population is predicted to shrink under inflammation (even in the absence of mutants). Finally, it turns out that if only the differentiation probability is affected by the inflammation, then the resulting steady state population of wild type cells will contain a relatively smaller percentage of HSCs under inflammation. If the division-to-death rate is also affected, then the percentage of HSCs under inflammation can either decrease or increase, depending on other parameters.

Evolutionary Biology↗

bioRxiv2016

The non-stationary dynamics of fitness distributions: asexual model with epistasis and standing variation.

Various models describe asexual evolution by mutation, selection and drift. Some focus directly on fitness, typically modelling drift but ignoring or simplifying both epistasis and the distribution of mutation effects (travelling wave models). Others follow the dynamics of quantitative traits determining fitness (Fishers geometrical model), imposing a complex but fixed form of mutation effects and epistasis, and often ignoring drift. In all cases, predictions are typically obtained in high or low mutation rate limits and for long-term stationary regimes, thus loosing information on transient behaviors and the effect of initial conditions. Here, we connect fitness-based and trait-based models into a single framework, and seek explicit solutions even away from stationarity. The expected fitness distribution is followed over time via its cumulant generating function, using a deterministic approximation that neglects drift. In several cases, explicit trajectories for the full fitness distribution are obtained, for arbitrary mutation rates and standing variance. For non-epistatic mutation, especially with beneficial mutations, this approximation fails over the long term but captures the early dynamics, thus complementing stationary stochastic predictions. The approximation also handles several diminishing return epistasis models (e.g. with an optimal genotype): it can then apply at and away from equilibrium. General results arise at equilibrium, where fitness distributions display a phase transition with mutation rate. Beyond this phase transition, in Fishers geometrical model, the full trajectory of fitness and trait distributions takes simple form, robust to details of the mutant phenotype distribution. Analytical arguments are explored for why and when the deterministic approximation applies.\n\nSignificance statementHow fast do asexuals evolve in new environments? Asexual fitness dynamics are well documented empirically. Various corresponding theories exist, to which they may be compared, but most typically describe stationary regimes, thus losing information on the shorter timescale of experiments, and on the impact of the initial conditions set by the experimenter. Here, a general deterministic approximation is proposed that encompasses many previous models as subcases, and shows surprising accuracy when compared to stochastic simulations. It can yield predictions over both short and long timescales, hopefully fostering the quantitative test of alternative models, using data from experimental evolution in asexuals.

Evolutionary Biology↗

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↗