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bioRxiv2016

Overcoming evolved resistance to population-suppressing homing-based gene drives

The use of homing-based gene drive systems to modify or suppress wild populations of a given species has been proposed as a solution to a number of significant ecological and public health related problems, including the control of mosquito-borne diseases. The recent development of a CRISPR-Cas9-based homing system for the suppression of Anopheles gambiae, the main African malaria vector, is encouraging for this approach; however, with current designs, the slow emergence of homing-resistant alleles is expected to result in suppressed populations rapidly rebounding, as homing-resistant alleles have a significant fitness advantage over functional, population-suppressing homing alleles. To explore this concern, we develop a mathematical model to estimate tolerable rates of homing-resistant allele generation to suppress a wild population of a given size. Our results suggest that, to achieve meaningful population suppression, tolerable rates of resistance allele generation are orders of magnitude smaller than those observed for current designs for CRISPR-Cas9-based homing systems. To remedy this, we propose a homing system architecture in which guide RNAs (gRNAs) are multiplexed, increasing the effective homing rate and decreasing the effective resistant allele generation rate. Modeling results suggest that the size of the population that can be suppressed increases exponentially with the number of multiplexed gRNAs and that, with six multiplexed gRNAs, a mosquito species could potentially be suppressed on a continental scale. We also demonstrate successful multiplexing in vivo in Drosophila melanogaster using a ribozyme-gRNA-ribozyme (RGR) approach - a strategy that could readily be adapted to engineer stable, homing-based suppression drives in relevant organisms.

evolutionary biology↗

bioRxiv2016

Ancient hybridization and strong adaptation to viruses across African vervet monkey populations

Vervet monkeys (genus Chlorocebus, also known as African green monkeys), are highly abundant in savannahs and riverine forests throughout sub-Saharan Africa. They are amongst the most widely distributed nonhuman primates, show considerable phenotypic diversity, and have long been an important biomedical model for a variety of human diseases1 and in vaccine research2-4. They are particularly interesting for HIV/AIDS research as they are the most abundant natural hosts of simian immunodeficiency virus (SIV), a close relative of HIV. Here we present the first genome-wide survey of polymorphism in vervets, using sequencing data from 163 individuals sampled from across Africa and the Caribbean islands where vervets were introduced during the colonial era. We find high diversity, within and between taxa, and clear evidence that taxonomic divergence was reticulate rather than following a simple branching pattern. A scan for diversifying selection across vervet taxa yields gene enrichments much stronger than in similar studies on humans5. In particular, we report strong and highly polygenic selection signals affecting viral processes -- in line with recent evidence that proposes a driving role for viruses in protein evolution in mammals6. Furthermore, selection scores are highly elevated in genes whose human orthologs interact with HIV, and in genes that show a response to experimental SIV infection in vervet monkeys but not in rhesus macaques, suggesting that part of the signal reflects taxon-specific adaptation to SIV. Intriguingly, rather than affecting genes with antiviral and inflammatory-related functions7, selection in vervets appears to have primarily targeted genes involved in the transcriptional regulation of viruses, and in particular those that are harmful only under immunodeficiency, suggesting adaptation to living with SIV rather than defense against infection.

evolutionary biology↗

bioRxiv2016

The natural selection of metabolism bends body mass evolution in time

The natural selection of metabolism and mass can explain inter-specific allometries from prokaryotes to mammals (Witting 2017a), with exponents that depend on the selected metabolism and the spatial dimensionality (2D/3D) of intra-specific behaviour. The predicted 2D-exponent for total metabolism increases from 3/4 to 7/4 when the fraction of the inter-specific body mass variation that follows from primary variation in metabolism increases from zero to one.\n\nA 7/4 exponent for mammals has not been reported from inter-specific comparisons, but I detect the full range of allometries for evolution in the fossil record. There are no fossil data for allometric correlations between metabolism and mass, but I estimate life history allometries from the allometry [Formula] for the rate of evolution [Formula] in mass (w) in physical time (t).\n\nThe [Formula] exponent describes the curvature of body mass evolution, with predicted values being: 3/2 (2D) for within niche evolution in small horses over 54 million years. 5/4 (2D) and 9/8 (3D) for across niche evolution of maximum mass in four mammalian clades. 3/4 (2D) for fast evolution in large horses, and maximum mass in trunked and terrestrial mammals. 1 for maximum mass across major life-forms during 3.5 billion years of evolution along a metabolic bound.

evolutionary biology↗

bioRxiv2016

The Impact of Lethal Recessive Alleles on Bottlenecks with Implications for Conservation Genetics

When a bottleneck occurs, lethal recessive alleles from the ancestral population provide a genetic load. The purging of lethal recessive mutations may prolong the bottleneck, or even cause the population to become extinct. But the purging is of short duration, it will be over before near neutral deleterious alleles accumulate. Lethal recessive alleles from the parental population and near neutral deleterious mutations which occur during a bottleneck are temporally separated threats to the survival of a population. Breeding individuals from a large population into a small endangered population will provide the benefit of viable alleles to replace near neutral deleterious alleles but also the cost of lethal recessive mutations from the large population.

evolutionary biology↗

bioRxiv2016

Adaptive mutations in RNA polymerase and the transcriptional terminator Rho have similar effects on Escherichia coli gene expression

Modifications to transcriptional regulators play a major role in adaptation. Here we compared the effects of multiple beneficial mutations within and between Escherichia coli rpoB, the gene encoding the RNA polymerase {beta} subunit, and rho, which encodes a transcriptional terminator. These two genes have harbored adaptive mutations in numerous E. coli evolution experiments but particularly in our previous large-scale thermal stress experiment, where the two genes characterized two alternative adaptive pathways. To compare the effects of beneficial mutations, we engineered four advantageous mutations into each of the two genes and measured their effects on fitness, growth, gene expression and transcriptional termination at 42.2{degrees}C. Among the eight mutations, two rho mutations had no detectable effect on relative fitness, suggesting they were beneficial only in the context of epistatic interactions. The remaining six mutations had an average relative fitness benefit of [~]20%. The rpoB mutations altered the expression of [~]1700 genes; rho mutations altered the expression of fewer genes, most of which were a subset of the genes altered by rpoB. Across our eight mutants, relative fitness correlated with the degree to which a mutation restored gene expression back to the unstressed, 37.0{degrees}C state. The rho mutations do not enhance transcriptional termination in known rho-terminated regions, but the genome-wide effects of mutations in both genes was to enhance termination. Although beneficial mutations in the two genes did not have identical effects on fitness, growth or gene expression, they acted predominantly through parallel phenotypic effects on gene expression and transcriptional termination.

evolutionary biology↗

bioRxiv2016

Inference of evolutionary jumps in large phylogenies using Levy processes

While it is now widely accepted that the rate of phenotypic evolution may not necessarily be constant across large phylogenies, the frequency and phylogenetic position of periods of rapid evolution remain unclear. In his highly influential view of evolution, G. G. Simpson supposed that such evolutionary jumps occur when organisms transition into so called new adaptive zones, for instance after dispersal into a new geographic area, after rapid climatic changes, or following the appearance of an evolutionary novelty. Only recently, large, accurate and well calibrated phylogenies have become available that allow testing this hypothesis directly, yet inferring evolutionary jumps remains computationally very challenging. Here, we develop a computationally highly efficient algorithm to accurately infer the rate and strength of evolutionary jumps as well as their phylogenetic location. Following previous work we model evolutionary jumps as a compound process, but introduce a novel approach to sample jump configurations that does not require matrix inversions and thus naturally scales to large trees. We then make use of this development to infer evolutionary jumps in Anolis lizards and Loriini parrots where we find strong signal for such jumps at the basis of clades that transitioned into new adaptive zones, just as postulated by Simpson's hypothesis.

evolutionary biology↗

bioRxiv2016

Biased evolutionary inferences from bulk tumor samples

It is generally agreed that tumors are composed of multiple cell clones defined by different somatic mutations. Characterizing the evolutionary mechanisms driving this intratumor genetic heterogeneity (ITH) is crucial to improve both cancer diagnosis and therapeutic strategies. For that purpose, recent ITH studies have focused on qualitative comparisons of mutational profiles derived from bulk sequencing of multiple tumor samples extracted from the same patient. Here, we show some examples where the naive use of bulk data in multiregional studies may lead to erroneous inferences of the evolutionary trajectories that underlie tumor progression, including biased timing of somatic mutations, spurious parallel mutation events, and/or incorrect chronological ordering of metastatic events. In addition, we analyze three real datasets to highlight how the use of bulk mutational profiles instead of inferred clones can lead to different conclusions about mutational recurrence and population structure.

evolutionary biology↗

bioRxiv2016

Time-dependent-asymmetric-linear-parsimonious ancestral state reconstruction

The time-dependent-asymmetric-linear parsimony is an ancestral state reconstruction method which extends the standard linear parsimony (a.k.a. Wagner parsimony) approach by taking into account both branch lengths and asymmetric evolutionary costs for reconstructing quantitative characters (asymmetric costs amount to assuming an evolutionary trend toward the direction with the lowest cost).\n\nA formal study of the influence of the asymmetry parameter shows that the time-dependent-asymmetric-linear parsimony infers states which are all taken among the known states, except for some degenerate cases corresponding to special values of the asymmetry parameter. This remarkable property holds in particular for the Wagner parsimony.\n\nThis study leads to a polynomial algorithm which determines, and provides a compact representation of, the parametric reconstruction of a phylogenetic tree, that is for all the unknown nodes, the set of all the possible reconstructed states associated to the asymmetry parameters leading to them. The time-dependent-asymmetric-linear parsimony is finally illustrated with the parametric reconstruction of the body size of cetaceans.

evolutionary biology↗

bioRxiv2016

Temporal Genetic Dynamics of an Experimental, Biparental Field Population of Phytophthora capsici

Defining the contributions of dispersal, reproductive mode, and mating system to the population structure of a pathogenic organism is essential to estimating its evolutionary potential. After introduction of the devastating plant pathogen, Phytophthora capsici, into a growers field, a lack of aerial spore dispersal restricts migration. Once established, coexistence of both mating types results in formation of overwintering recombinant oospores, engendering persistent pathogen populations. To mimic these conditions, in 2008, we inoculated a field with two P. capsici isolates of opposite mating type. We analyzed pathogenic isolates collected in 2009-13 from this experimental population, using genome-wide single-nucleotide polymorphism markers. By tracking heterozygosity across years, we show that the population underwent a generational shift; transitioning from exclusively F1 in 2009-10; mixed generational in 2011; and ultimately all inbred in 2012-13. Survival of F1 oospores, characterized by heterozygosity excess, coupled with a low rate of selfing, delayed declines in heterozygosity due to inbreeding and attainment of equilibrium genotypic frequencies. Large allele and haplotype frequency changes in specific genomic regions accompanied the generational shift, representing putative signatures of selection. Finally, we identified an approximately 1.6 Mb region associated with mating type determination, constituting the first detailed genomic analysis of a mating type region (MTR) in Phytophthora. Segregation patterns in the MTR exhibited tropes of sex-linkage, where maintenance of allele frequency differences between isolates of opposite mating type was associated with elevated heterozygosity despite inbreeding. Characterizing the trajectory of this experimental system provides key insights into the processes driving persistent, sexual pathogen populations.

evolutionary biology↗

bioRxiv2016

Testing the neutral hypothesis of phenotypic evolution

It is generally accepted that a large fraction of genomic sequence variations within and between species are neutral or nearly so1. Whether the same is true for phenotypic variations is a central question in biology2-7. On the one hand, numerous phenotypic adaptations have been documented2,8,9 and even Kimura, the champion of the neutral theory of molecular evolution, believed in widespread adaptive phenotypic evolution1. On the other hand, phenotypic studies are strongly biased toward traits that are likely to be adaptive9, contrasting genomic studies that are typically unbiased. It is thus desirable to test the neutral hypothesis of phenotypic evolution using traits irrespective of their potential involvement in adaptation. Here we present such a test for 210 morphological traits measured in multiple strains of the yeast Saccharomyces cerevisiae and two related species. Our test is based on the premise that, under neutrality, the rate of phenotypic evolution declines as the trait becomes more important to fitness, analogous to the neutral paradigm that functional genes evolve more slowly than functionless pseudogenes10. Neutrality is rejected in favor of adaptation if important traits evolve faster than less important ones, parallel to the demonstration of molecular adaptation when a functional gene evolves faster than pseudogenes. After controlling for the mutational size, we find faster evolution of more important morphological traits within and between species. By contrast, an analysis of 3466 yeast gene expression traits fails to reject neutrality. Thus, yeast morphological evolution is largely adaptive, but the same may not apply to other classes of phenotypes.

evolutionary biology↗

bioRxiv2016

Intra- and inter-specific variations of gene expression levels in yeast are largely neutral

It is commonly, although not universally, accepted that most intra- and inter-specific genome sequence variations are more or less neutral, whereas a large fraction of organism-level phenotypic variations are adaptive. Gene expression levels are molecular phenotypes that bridge the gap between genotypes and corresponding organism-level phenotypes. Yet, it is unknown whether natural variations in gene expression levels are mostly neutral or adaptive. Here we address this fundamental question by genome-wide profiling and comparison of gene expression levels in nine yeast strains belonging to three closely related Saccharomyces species and originating from five different ecological environments. We find that the transcriptome-based clustering of the nine strains approximates the genome sequence-based phylogeny irrespective of their ecological environments. Remarkably, only [~]0.5% of genes exhibit similar expression levels among strains from a common ecological environment, no greater than that among strains with comparable phylogenetic relationships but different environments. These and other observations strongly suggest that most intra- and inter-specific variations in yeast gene expression levels result from the accumulation of random mutations rather than environmental adaptations. This finding has profound implications for understanding the driving force of gene expression evolution, genetic basis of phenotypic adaptation, and general role of stochasticity in evolution.

evolutionary biology↗

bioRxiv2016

Soft sweeps are the dominant mode of adaptation in the human genome

The degree to which adaptation in recent human evolution shapes genetic variation remains controversial. This is in part due to the limited evidence in humans for classic \"hard selective sweeps,\" wherein a novel beneficial mutation rapidly sweeps through a population to fixation. However, positive selection may often proceed via \"soft sweeps\" acting on mutations already present within a population. Here we examine recent positive selection across six human populations using a powerful machine learning approach that is sensitive to both hard and soft sweeps. We found evidence that soft sweeps are widespread and account for the vast majority of recent human adaptation. Surprisingly, our results also suggest that linked positive selection affects patterns of variation across much of the genome, and may increase the frequencies of deleterious mutations. Our results also reveal insights into the role of sexual selection, cancer risk, and central nervous system development in recent human evolution.

evolutionary biology↗

bioRxiv2016

The evolutionary history of bears is shaped by gene flow across species

Bears are iconic mammals with a complex evolutionary history. Natural bear hybrids and studies of few nuclear genes indicate that gene flow among bears may be more common than expected and not limited to the closely related polar and brown bears. Here we present a genome analysis of the bear family with representatives of all living species. Phylogenomic analyses of 869 mega base pairs divided into 18,621 genome fragments yielded a well-resolved coalescent species tree despite signals for extensive gene flow across species. However, genome analyses using three different statistical methods show that gene flow is not limited to closely related species pairs. Strong ancestral gene flow between the Asiatic black bear and the ancestor to polar, brown and American black bear explains numerous uncertainties in reconstructing the bear phylogeny. Gene flow across the bear clade may be mediated by intermediate species such as the geographically wide-spread brown bears leading to massive amounts of phylogenetic conflict. Genome-scale analyses lead to a more complete understanding of complex evolutionary processes. The increasing evidence for extensive inter-specific gene flow, found also in other animal species, necessitates shifting the attention from speciation processes achieving genome-wide reproductive isolation to the selective processes that maintain species divergence in the face of gene flow.

evolutionary biology↗

bioRxiv2016

The natural selection of metabolism explains curvature in allometric scaling

I simulate the evolution of metabolism and mass to explain the curvature in the metabolic allometry for placental and marsupial mammals. I assume that the release of inter-specific competition by the extinction of dinosaurs 65 million years ago made it possible for each clade to diversity into a multitude of species across a wide range of niches. The natural selection of metabolism and mass was then fitted to explain the maximum observed body masses over time, as well as the current inter-specific allometry for metabolism. The estimated selection of mass specific metabolism was found to bend the metabolic allometry over time, with the strongest curvature in the placental clade. The rate of exponential increase in mass specific metabolism for placentals was estimated to 9.3 x 10-9 (95% CI:7.3 x 10-9 - 1.1 x 10-8) on the per generation time-scale. This is an order of magnitude larger than the estimate for marsupials, in agreement with an average metabolism that is 30% larger in placentals relative to marsupials of similar size.

evolutionary biology↗

bioRxiv2016

Tuning the course of evolution on the biophysical fitness landscape of an RNA virus

Predicting viral evolution remains a major challenge with profound implications for public health. Viral evolutionary pathways are determined by the fitness landscape, which maps viral genotype to fitness. However, a quantitative description of the landscape and the evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based on capsid folding stability and antibody binding affinity to predict the evolutionary pathway of norovirus escaping a neutralizing antibody. The model is validated by experimental evolution in bulk culture and in a drop-based microfluidics device, the \"Evolution Chip\", which propagates millions of independent viral sub-populations. We demonstrate that along the axis of binding affinity, selection for escape variants and drift due to random mutations have the same direction. However, along folding stability, selection and drift are opposing forces whose balance is tuned by viral population size. Our results demonstrate that predictable epistatic tradeoffs shape viral evolution.

evolutionary biology↗

bioRxiv2016

The effect of known mutator alleles in a cluster of clinical Saccharomyces cerevisiae strains

Natural selection has the potential to act on all phenotypes, including genomic mutation rate. Classic evolutionary theory predicts that in asexual populations, mutator alleles, which cause high mutation rates, can fix due to linkage with beneficial mutations. This phenomenon has been demonstrated experimentally and may explain the frequency of mutators found in bacterial pathogens. In contrast, in sexual populations, recombination decouples mutator alleles from beneficial mutations, preventing mutator fixation. In the facultatively sexual yeast Saccharomyces cerevisiae, segregating alleles of MLH1 and PMS1 have been shown to be incompatible, causing a high mutation rate when combined. These alleles had never been found together naturally, but were recently discovered in a cluster of clinical isolates. Here we report that the incompatible mutator allele combination only marginally elevates mutation rate in these clinical strains. Genomic and phylogenetic analyses provide no evidence of a historically elevated mutation rate. We conclude that the effect of the mutator alleles is dampened by background genetic modifiers. Thus, the relationship between mutation rate and microbial pathogenicity may be more complex than once thought. Our findings provide rare observational evidence that supports evolutionary theory suggesting that sexual organisms are unlikely to harbor alleles that increase their genomic mutation rate.

evolutionary biology↗

bioRxiv2016

The emergence, evolution, and diversification of the miR390-TAS3-ARF pathway in land plants

In plants, miR390 directs the production of tasiRNAs from TRANS-ACTING SIRNA 3 (TAS3) transcripts to regulate AUXIN RESPONSIVE FACTOR (ARF) genes, transcription factors critical for auxin signaling; these tasiRNAs are known as tasiARFs. This pathway is highly conserved, with the TAS3 as the only one noncoding gene present almost ubiquitously in land plants. To understand the evolution of this miR390-TAS3-ARF pathway, we characterized homologs of these three genes from thousands of plant species, from bryophytes to angiosperms. Both miR390 and TAS3 are present and functional in liverworts, confirming their ancestral role to regulate ARFs in land plants. We found the lower-stem region of MIR390 genes, critical for accurate DCL1 (DICER-LIKE 1) processing, is conserved in sequence in seed plants. We propose a model for the transition of functional tasiRNA sequences in TAS3 genes occurred at the emergence of vascular plants, in which the two miR390 target sites of TAS3 genes showed distinct pairing patterns in different plant lineages. Based on the cleavability of miR390 target sites and the distance between target site and tasiARF we inferred a potential bidirectional processing mechanism exists for some TAS3 genes. We also demonstrated a tight mutual selection between tasiARF and its target genes, and characterized unusual aspects and diversity of regulatory components of this pathway. Taken together, these data illuminate the evolutionary path of the miR390-TAS3-ARF pathway in land plants, and demonstrate the significant variation that occurs in the production of phasiRNAs in plants, even in the functionally important and archetypal miR390-TAS3-ARF regulatory circuit.

evolutionary biology↗

bioRxiv2016

The Bacterial Sequential Markov Coalescent

Bacteria can exchange and acquire new genetic material from other organisms directly and via the environment. This process, known as bacterial recombination, has a strong impact on the evolution of bacteria, for example leading to the spread of antibiotic resistance across clades and species, and to the avoidance of clonal interference. Recombination hinders phylogenetic and transmission inference because it creates patterns of substitutions that are not consistent with the hypothesis of a single evolutionary tree (homoplasies). Bacterial recombination is typically modelled as statistically akin to the gene conversion process of eukaryotes, i.e., using the coalescent with gene conversion (CGC). However, this model can be very computationally demanding as it requires to account for the correlations of evolutionary histories of even distant loci. So, with the increasing popularity of whole genome sequencing, the need has emerged for a new and faster approach to model and simulate bacterial evolution at genomic scales. We present a new model that approximates the coalescent with gene conversion: the bacterial sequential Markov coalescent (BSMC). Our approach is based on a similar idea to the the sequential Markov coalescent (SMC), an approximation of the coalescent with recombination. However, bacterial recombination poses hurdles to a sequential Markov approximation, as it leads to strong correlations and linkage disequilibrium across very distant sites in the genome. Our BSMC overcomes these difficulties and shows both a considerable reduction in computational demand compared the exact CGC, and very similar patterns in the simulated data. We use the BSMC within an Approximate Bayesian Computation (ABC) inference scheme and show that we can correctly recover parameters simulated under the exact CGC, which further showcases the accuracy of our approximation. We also use this ABC approach to infer recombination rate, mutation rate, and recombination tract length from a whole genome alignment of Bacillus cereus. Lastly, we implemented our BSMC model within a new simulation software FastSimBac. In addition to the decreased computational demand compared to previous bacterial genome evolution simulators, FastSimBac also provides a much more general set of options for evolutionary scenarios, allowing population structure with migration, speciations, population size changes, and recombination hotspots. FastSimBac is available from https://bitbucket.org/nicofmay/fastsimbac and is distributed as open source under the terms of the GNU General Public Licence.

evolutionary biology↗