SEARCH · bioRxiv Science

Results for “Evolutionary Biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 757 records · Page 42Linked to original sources

bioRxiv2015

An Option Space for Early Neural Evolution

The origin of nervous systems has traditionally been discussed within two conceptual frameworks. Input-output models stress the sensory-motor aspects of nervous systems, while internal coordination models emphasize the role of nervous systems in coordinating multicellular activity, especially muscle-based motility. Here we consider both frameworks and apply them to describe aspects of each of three main groups of phenomena that nervous systems control: behavior, physiology and development. We argue that both frameworks and all three aspects of nervous system function need to be considered for a comprehensive discussion of nervous system origins. This broad mapping of the option space enables an overview of the many influences and constraints that may have played a role in the evolution of the first nervous systems.

Evolutionary Biology↗

bioRxiv2015

Summer temperature can predict the distribution of wild yeast populations

The wine yeast, Saccharomyces cerevisiae, is the best understood microbial eukaryote at the molecular and cellular level, yet its natural geographic distribution is unknown. Here we report the results of a field survey for S. cerevisiae, S. paradoxus and other budding yeast on oak trees in Europe. We show that yeast species differ in their geographic distributions, and investigated which ecological variables can predict the isolation rate of S. paradoxus, the most abundant species. We find a positive association between trunk girth and S. paradoxus abundance suggesting that older trees harbour more yeast. S. paradoxus isolation frequency is also associated with summer temperature, showing highest isolation rates at intermediate temperatures. Using our statistical model, we estimated a range of summer temperatures at which we expect high S. paradoxus isolation rates, and show that the geographic distribution predicted by this optimum temperature range is consistent with the worldwide distribution of sites where S. paradoxus has been isolated. Using laboratory estimates of optimal growth temperatures for S. cerevisiae relative to S. paradoxus, we also estimated an optimum range of summer temperatures for S. cerevisiae. The geographical distribution of these optimum temperatures are consistent with the locations where wild S. cerevisiae have been reported, and can explain why only human-associated S. cerevisiae strains are isolated at northernmost latitudes. Our results provide a starting point for targeted isolation of S. cerevisiae from natural habitats, which could lead to a better understanding of climate associations and natural history in this important model microbe.

Evolutionary Biology↗

bioRxiv2015

Parental effects and the evolution of phenotypic memory

Despite growing evidence for nongenetic inheritance, the ecological conditions that favor the evolution of heritable parental or grandparental effects remain poorly understood. Here, we systematically explore the evolution of parental effects in a patch-structured population with locally changing environments. When selection favors the production of a mix of offspring types, this mix differs according to the parental phenotype, implying that parental effects are favored over selection for bet-hedging in which the mixture of offspring phenotypes produced does not depend on the parental phenotype. Positive parental effects (generating a positive correlation between parental and offspring phenotype) are favored in relatively stable habitats and when different types of local environment are roughly equally abundant, and can give rise to long-term parental inheritance of phenotypes. By contrast, unstable habitats can favor negative parental effects (generating a negative correlation between parental and offspring phenotype), and under these circumstances even slight asymmetries in the abundance of local environmental states select for marked asymmetries in transmission fidelity.

Evolutionary Biology↗

bioRxiv2015

Phototaxis and the origin of visual eyes

Vision allows animals to detect spatial differences in environmental light levels. High-resolution image-forming eyes evolved from low-resolution eyes via increases in photoreceptor cell number, improvements in optics and changes in the neural circuits that process spatially resolved photoreceptor input. However, the evolutionary origins of the first low-resolution visual systems have been unclear. We propose that the lowest-resolving (two-pixel) visual systems could initially have functioned in visual phototaxis. During visual phototaxis, such elementary visual systems compare light on either side of the body to regulate phototactic turns. Another, even simpler and non-visual strategy is characteristic of helical phototaxis, mediated by sensory-motor eyespots. The recent mapping of the complete neural circuitry (connectome) of an elementary visual system in the larva of the annelid Platynereis dumerilii sheds new light on the possible paths from non-visual to visual phototaxis and to image-forming vision. We outline an evolutionary scenario focusing on the neuronal circuitry to account for these transitions. We also present a comprehensive review of the structure of phototactic eyes in invertebrate larvae and assign them to the non-visual and visual categories. We propose that non-visual systems may have preceded visual phototactic systems in evolution that in turn may have repeatedly served as intermediates during the evolution of image-forming eyes.

Evolutionary Biology↗

bioRxiv2015

Estimating diversification rates from the fossil record

Diversification rates are estimated from phylogenies, typically without fossils, except in paleontological studies. By nature, rate estimations depend heavily on the time data provided in phylogenies, which are divergence times and (when used) fossil ages. Among these temporal data, fossil ages are by far the most precisely known (divergence times are inferences calibrated with fossils). We propose a method to compute the likelihood of a phylogenetic tree with fossils in which the only known time information is the fossil ages.\n\nTesting our approach on simulated data shows that the maximum likelihood rate estimates from the phylogenetic tree shape and the fossil dates are almost as accurate as the ones obtained by taking into account all the data, including the divergence times. Moreover they are substantially more accurate than the estimates obtained only from the exact divergence times (without taking into account the fossil record).

Evolutionary Biology↗

bioRxiv2015

Evolutionary assembly patterns of prokaryotic genomes

Evolutionary innovation must occur in the context of some genomic background, which limits available evolutionary paths. For example, protein evolution by sequence substitution is constrained by epistasis between residues. In prokaryotes, evolutionary innovation frequently happens by macrogenomic events such as horizontal gene transfer (HGT). Previous work has suggested that HGT can be influenced by ancestral genomic content, yet the extent of such gene-level constraints has not yet been systematically characterized. Here, we evaluated the evolutionary impact of such constraints in prokaryotes, using probabilistic ancestral reconstructions from 634 extant prokaryotic genomes and a novel framework for detecting evolutionary constraints on HGT events. We identified 8,228 directional dependencies between genes, and demonstrated that many such dependencies reflect known functional relationships, including, for example, evolutionary dependencies of the photosynthetic enzyme RuBisCO. Modeling all dependencies as a network, we adapted an approach from graph theory to establish chronological precedence in the acquisition of different genomic functions. Specifically, we demonstrated that specific functions tend to be gained sequentially, suggesting that evolution in prokaryotes is governed by functional assembly patterns. Finally, we showed that these dependencies are universal rather than clade-specific and are often sufficient for predicting whether or not a given ancestral genome will acquire specific genes. Combined, our results indicate that evolutionary innovation via HGT is profoundly constrained by epistasis and historical contingency, similar to the evolution of proteins and phenotypic characters, and suggest that the emergence of specific metabolic and pathological phenotypes in prokaryotes can be predictable from current genomes.

Evolutionary Biology↗

bioRxiv2015

On the causes of evolutionary transition:transversion bias

A pattern in which nucleotide transitions are favored several-fold over transversions is common in molecular evolution. When this pattern occurs among amino acid replacements, explanations often invoke an effect of selection, on the grounds that transitions are more conservative in their effects on proteins. However, the underlying hypothesis of conservative transitions has never been tested directly. Here we assess support for this hypothesis using direct evidence: the fitness effects of mutations in actual proteins, measured via individual or paired growth experiments. We assembled data from 8 published studies, ranging in size from 24 to 757 single-nucleotide mutations that change an amino acid. Every study has the statistical power to reveal significant effects of amino acid exchangeability, and most studies have the power to discern a binary conservative-vs-radical distinction. However, only one study suggests that transitions are significantly more conservative than transversions. In the combined set of 1239 replacements, the chance that a transition is more conservative than a transversion is 53 % (95 % confidence interval, 50 % to 56 %), compared to the null expectation of 50 %. We show that this effect is not large compared to that of most biochemical factors, and is not large enough to explain the several-fold bias observed in evolution. In short, available data have the power to verify the \"conservative transitions\" hypothesis if true, but suggest instead that selection on proteins plays at best a minor role in the observed bias.

Evolutionary Biology↗

bioRxiv2015

Genetic structure of island and mainland populations of a Neotropical bumble bee species

Biodiversity loss is a global problem and island species/populations are particularly vulnerable to such loss. Low genetic diversity is one of the factors that can lead a population to extinction. Loss of bee populations is of particular concern because of the knock-on consequences for the pollination guilds that the lost bees once serviced. Here we evaluate the genetic structure of the bumble bee Bombus morio populations on the mainland of South East Brazil and on nearby islands. We analyzed a total of 659 individuals from 24 populations by sequencing two mitochondrial genes (COI and Cytb) and using 14 microsatellite loci. Levels of diversity were high in most of populations and were similar on islands and the mainland. Furthermore, genetic diversity was not significantly correlated with island area, although it was lower in populations from distant islands. Our data suggest that long-term isolation on islands is not affecting the population viability of this species. This may be attributed to the high dispersal ability of B. morio, its capacity to suvive in urban environments, and the characteristics of the studied islands.

Evolutionary Biology↗

bioRxiv2015

Detecting and quantifying changing selection intensities from time-sampled polymorphism data

During his well-known debate with Fisher regarding the phenotypic dataset of Panaxia dominula, Wright (1948) suggested fluctuating selection as a potential explanation for the observed change in frequency. This model has since been invoked in a number of analyses, with the focus of discussion centering mainly on random or oscillatory fluctuations of selection intensities. Here, we present a novel method to consider non-random changes in selection intensities using Wright-Fisher approximate Bayesian (ABC)-based approaches, in order to detect and evaluate a change in selection strength from time-sampled data. This novel method jointly estimates the position of a change point as well as the strength of both corresponding selection coefficients (and dominance for diploid cases) from the allele trajectory. The simulation studies of CP-WFABC reveal the combinations of parameter ranges and input values that optimize performance, thus indicating optimal experimental design strategies. We apply this approach to both the historical dataset of Panaxia dominula in order to shed light on this historical debate, as well as to whole-genome time-serial data from influenza virus in order to identify sites with changing selection intensities in response to drug treatment

Evolutionary Biology↗

bioRxiv2015

Modelling the role of immunity in reversion of viral antigenic sites

Antigenic sites in viral pathogens exhibit distinctive evolutionary dynamics due to their role in evading recognition by host immunity. Antigenic selection is known to drive higher rates of non-synonymous substitution; less well understood is why differences are observed between viruses in their propensity to mutate to a novel or previously encountered amino acid. Here, we present a model to explain patterns of antigenic reversion and forward substitution in terms of the epidemiological and molecular processes of the viral population. We develop an analytical three-strain model and extend the analysis to a multi-site model to predict characteristics of observed sequence samples. Our model provides insight into how the balance between selection to escape immunity and to maintain viability is affected by the rate of mutational input. We also show that while low probabilities of reversion may be due to either a low cost of immune escape or slowly decaying host immunity, these two scenarios can be differentiated by the frequency patterns at antigenic sites. Comparison between frequency patterns of human influenza A (H3N2) and human RSV-A suggests that the increased rates of antigenic reversion in RSV-A is due to faster decaying immunity and not higher costs of escape.

Evolutionary Biology↗

bioRxiv2015

Deep learning for population genetic inference

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce here a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. In contrast to Approximate Bayesian Computation, another likelihood-free approach widely used in population genetics and other fields, deep learning does not require a distance function on summary statistics or a rejection step, and it is robust to the addition of uninformative statistics. To demonstrate that deep learning can be effectively employed to estimate population genetic parameters and learn informative features of data, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme, likely due in part to the unaccounted impact of selection.

Evolutionary Biology↗

bioRxiv2015

Mitochondrial introgression suggests extensive ancestral hybridization events among Saccharomyces species

1.Horizontal Gene Transfer (HGT) in eukaryotic plastids and mitochondrial genomes is common, and plays an important role in organism evolution. In yeasts, recent mitochondrial HGT has been suggested between S. cerevisiae and S. paradoxus. However, few strains have been explored due to the lack of accurate mitochondrial genome annotations. Mitochondrial genome sequences are important to understand how frequent these introgressions occur and their role in cytonuclear incompatibilities and fitness. In fact, most of the Bateson-Dobzhansky-Muller genetic incompatibilities described in yeasts are driven by cytonuclear incompatibilities. In this study, we have explored the mitochondrial inheritance of several worldwide distributed Saccharomyces species isolated from different sources and geographic origins. We demonstrated the existence of several recombination points in the mitochondrial region COX2-ORF1, likely mediated by the transfer of two different types of ORF1 (F-SceIII), encoding a freestanding homing endonuclease, or mostly facilitated by A+T tandem repeats and regions of integration of GC clusters. These introgressions were shown to occur at intra- as well as at interspecific levels. This suggest a complex model of Saccharomyces evolution which involve several ancestral hybridization events in wild environments.

Evolutionary Biology↗

bioRxiv2015

Evolving synergetic interactions

The outcome of a major evolutionary transition is the aggregation of independent entities into a new synergetic level of organisation. Classical models involve either pairwise interactions between individuals or a linear superposition of these interactions. However, major evolutionary transitions display synergetic effects: their outcome is not just the sum of its parts. Multiplayer games can display such synergies, as their payoff can be different from the sum of any collection of two-player interactions. Assuming that all interactions start from pairs, how can synergetic multiplayer games emerge from simpler pairwise interaction? Here, we present a mathematical model that captures the transition from pairwise interactions to synergetic multiplayer ones. We assume that different social groups have different breaking rates. We show that non-uniform breaking rates do foster the emergence of synergy, even though individuals always interact in pairs. Our work sheds new light on the mechanisms underlying a major evolutionary transition.

Evolutionary Biology↗

bioRxiv2015

Evaluating the performance of selection scans to detect selective sweeps in domestic dogs

Selective breeding of dogs has resulted in repeated artificial selection on breed-specific morphological phenotypes. A number of quantitative trait loci associated with these phenotypes have been identified in genetic mapping studies. We analyzed the population genomic signatures observed around the causal mutations for 12 of these loci in 25 dog breeds, for which we genotyped 25 individuals in each breed. By measuring the population frequencies of the causal mutations in each breed, we identified those breeds in which specific mutations most likely experienced positive selection. These instances were then used as positive controls for assessing the performance of popular statistics to detect selection from population genomic data. We found that artificial selection during dog domestication has left characteristic signatures in the haplotype and nucleotide polymorphism patterns around selected loci that can be detected in the genotype data from a single population sample. However, the sensitivity and accuracy at which such signatures were detected varied widely between loci, the particular statistic used, and the choice of analysis parameters. We observed examples of both hard and soft selective sweeps and detected strong selective events that removed genetic diversity almost entirely over regions >10 Mbp. Our study demonstrates the power and limitations of selection scans in populations with high levels of linkage disequilibrium due to severe founder effects and recent population bottlenecks.

Evolutionary Biology↗

bioRxiv2015

A segregating inversion generates fitness variation in a yellow monkeyflower (Mimulus guttatus) population

Polymorphic chromosomal rearrangements, which can bind together hundreds of genes into single genetic loci with diverse effects, are increasingly associated with local adaptation and speciation. They may also be an important component of genetic variation within populations. We genetically and phenotypically characterized a novel segregating inversion (inv6) in the Iron Mountain (IM) population of Mimulus guttatus (yellow monkeyflower). We first identified a region of recombination suppression in three F2 mapping populations resulting from crosses among IM plants; in each case, the F1 hybrid parent was heterozygous for a homogenous derived haplotype (inv6) across markers spanning over 4.2 Mb of Linkage Group 6. Genotype-phenotype associations in the three F2 populations demonstrated negative inv6 effects on male and female fitness components. In addition, inv6 carriers suffered a ~30% loss of pollen viability in the field. Despite these costs, inv6 exists at moderate and apparently stable frequency (~7%) in the natural population, suggesting counter-balancing fitness benefits that maintain the polymorphism. Across four years of monitoring in the field, inv6 had an overall significant positive effect on the seed production (lifetime female fitness) of carriers. This benefit was particularly strong in harsh years and may be mediated (in part) by strong positive inv6 effects on flower production. These data suggest that opposing fitness effects maintain an intermediate frequency, and as a consequence, inv6 generates inbreeding depression and high genetic variance. We discuss these findings in the context of theory about the genetic basis of inbreeding depression and the role for chromosomal rearrangements in population divergence with gene flow.

Evolutionary Biology↗

bioRxiv2015

Biogeographic dating of speciation times using paleogeographically informed processes

Standard models of molecular evolution cannot estimate absolute speciation times alone, and require external calibrations to do so. Because fossil calibration methods rely on the unreliable fossil record, most nodes in the tree of life are dated with poor accuracy. However, many major paleogeographical events are dated, and since biogeographic processes depend on paleogeographical conditions, biogeographic dating may be used as an alternative or complementary method to fossil dating. I demonstrate how a time-stratified biogeographic stochastic process may be used to estimate absolute divergence times by conditioning on dated paleogeographical events. Informed by the current paleogeographical literature, I construct an empirical dispersal graph using 25 areas and 26 epochs for the past 540 Ma of Earths history. Simulations indicate biogeographic dating performs well so long as paleogeography imposes constraint on biogeographic character evolution. To gauge whether biogeographic dating may have any practical use, I analyze the well-studied turtle clade (Testudines) then assess how well biogeographic dating fares compared to heavily fossil-calibrated dating results as reported in the literature. Fossil-free biogeographic dating estimated the age of the most recent common ancestor of extant turtles to be approximately 201 Ma, which is consistent with fossil-based estimates. Accuracy improves further when including a root node fossil calibration. The described model, paleogeographical dispersal graph, and analysis scripts are available for use with RevBayes.

Evolutionary Biology↗

bioRxiv2015

Trees, Population Structure, F-statistics!

Many questions about human genetic history can be addressed by examining the patterns of shared genetic variation between sets of populations. A useful methodological framework for this purpose are F-statistics, that measure shared genetic drift between sets of two, three and four populations, and can be used to test simple and complex hypotheses about admixture between populations. Here, we put these statistics in context of phylogenetic and population genetic theory. We show how measures of genetic drift can be interpreted as branch lengths, paths through an admixture graph or in terms of the internal branches in coalescent trees. We show that the admixture tests can be interpreted as testing general properties of phylogenies, allowing us to generalize applications for arbitrary phylogenetic trees. Furthermore, we derive novel expressions for the F-statistics, which enables us to explore the behavior of F-statistic under population structure models. In particular, we show that population substructure may complicate inference.\n\nAuthor SummaryFor the analysis of genetic data from hundreds of populations, a commonly used technique are a set of simple statistics on data from two, three and four populations. These statistics are used to test hypotheses involving the history of populations, in particular whether data is consistent with the history of a set of populations forming a tree.\n\nHere, we provide context to these statistics by deriving novel expressions and by relating them to approaches in comparative phylogenetics. These results are useful because they provide a straightforward interpretation of these statistics under many demographic processes and lead to simplified expressions. However, the result also reveals the limitations of F-statistics, in that population substructure may complicate inference.

Evolutionary Biology↗

bioRxiv2015

Dietary Breadth is Positively Correlated with Venom Complexity in Cone Snails

Although diet is believed to be a major factor underlying the evolution of venom, few comparative studies examine both venom composition and diet across a radiation of venomous species. Cone snails within the family, Conidae, comprise more than 700 species of carnivorous marine snails that capture their prey by using a cocktail of venomous neurotoxins (conotoxins or conopeptides). Venom composition across species has been previously hypothesized to be shaped by (a) prey taxonomic class (i.e., worms, molluscs, or fish) and (b) dietary breadth. We tested these hypotheses under a comparative phylogenetic framework using ecological data in conjunction with venom duct transcriptomes sequenced from 12 phylogenetically disparate cone snail species, including 10 vermivores (worm-eating), one molluscivore, and one generalist. We discovered 2223 unique conotoxin precursor peptides that encoded 1864 unique mature toxins across all species, >90% of which are new to this study. In addition, we identified two novel gene superfamilies and 16 novel cysteine frameworks. Each species exhibited unique venom profiles, with venom composition and expression patterns among species dominated by a restricted set of gene superfamilies and mature toxins. In contrast with the dominant paradigm for interpreting Conidae venom evolution, prey taxonomic class did not predict venom composition patterns among species. Our results suggests that cone snails have either evolved species-specific expression patterns likely as a consequence of the rapid evolution of conotoxin genes, or that traditional means of categorizing prey type (i.e., worms, mollusc, or fish) and conotoxins (i.e., by gene superfamily) do not accurately encapsulate evolutionary dynamics between diet and venom composition. We also found a significant positive relationship between dietary breadth and measures of conotoxin complexity. These results indicate that species with more generalized diets tend to have more complex venoms and utilize a greater number of venom genes for prey capture. Whether this increased gene diversity confers an increased capacity for evolutionary change remains to be tested. Overall, our results corroborate the key role of diet in influencing patterns of venom evolution in cone snails and other venomous radiations.

Evolutionary Biology↗