Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 88,402 bioRxiv papers from 379,082 authors.
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in category evolutionary biology
5,324 results found. For more information, click each entry to expand.
2,395 downloads evolutionary biology
Bantu speech communities expanded over large parts of sub-Saharan Africa within the last 4000-5000 years, reaching different parts of southern Africa 1200-2000 years ago. The Bantu languages subdivide in several major branches, with languages belonging to the Eastern and Western Bantu branches spreading over large parts of Central, Eastern, and Southern Africa. There is still debate whether this linguistic divide is correlated with a genetic distinction between Eastern and Western Bantu speakers. During their expansion, Bantu speakers would have come into contact with diverse local populations, such as the Khoisan hunter-gatherers and pastoralists of southern Africa, with whom they may have intermarried. In this study, we analyze complete mtDNA genome sequences from over 900 Bantu-speaking individuals from Angola, Zambia, Namibia, and Botswana to investigate the demographic processes at play during the last stages of the Bantu expansion. Our results show that most of these Bantu-speaking populations are genetically very homogenous, with no genetic division between speakers of Eastern and Western Bantu languages. Most of the mtDNA diversity in our dataset is due to different degrees of admixture with autochthonous populations. Only the pastoralist Himba and Herero stand out due to high frequencies of particular L3f and L3d lineages; the latter are also found in the neighboring Damara, who speak a Khoisan language and were foragers and small-stock herders. In contrast, the close cultural and linguistic relatives of the Herero and Himba, the Kuvale, are genetically similar to other Bantu-speakers. Nevertheless, as demonstrated by resampling tests, the genetic divergence of Herero, Himba, and Kuvale is compatible with a common shared ancestry with high levels of drift and differential female admixture with local pre-Bantu populations.
2,385 downloads evolutionary biology
The parthenogenetic all-female marbled crayfish is a novel research model and potent invader of freshwater ecosystems. It is a triploid descendant of the sexually reproducing slough crayfish, Procambarus fallax, but its taxonomic status has remained unsettled. By cross-breeding experiments and parentage analysis we show here that marbled crayfish and P. fallax are reproductively separated. Both crayfish copulate readily, suggesting that the reproductive barrier is set at the cytogenetic rather than the behavioural level. Analysis of complete mitochondrial genomes of marbled crayfish from laboratory lineages and wild populations demonstrates genetic identity and indicates a single origin. Flow cytometric comparison of DNA contents of haemocytes and analysis of nuclear microsatellite loci confirm triploidy and suggest autopolyploidization as its cause. Global DNA methylation is significantly reduced in marbled crayfish implying the involvement of molecular epigenetic mechanisms in its origination. Morphologically, both crayfish are very similar but growth and fecundity are considerably larger in marbled crayfish, making it a different animal with superior fitness. These data and the high probability of a divergent future evolution of the marbled crayfish and P. fallax clusters suggest that marbled crayfish should be considered as an independent asexual species. Our findings also establish the P. fallax-marbled crayfish pair as a novel paradigm for rare chromosomal speciation by autopolyploidy and parthenogenesis in animals and for saltational evolution in general.
2,345 downloads evolutionary biology
There is an overwhelming archeological and genetic evidence that modern speech apparatus was acquired by hominins by 600,000 years ago. On the other hand, artifacts signifying modern imagination, such as (1) composite figurative arts, (2) bone needles with an eye, (3) construction of dwellings, and (4) elaborate burials arose not earlier than 70,000 years ago. It remains unclear (1) why there was a long gap between acquisition of modern speech apparatus and modern imagination, (2) what triggered the acquisition of modern imagination 70,000 years ago, and (3) what role language might have played in this process. Our research into evolutionary origin of modern imagination has been driven by the observation of a temporal limit for the development of a particular component of imagination. Modern children not exposed to recursive language in early childhood never acquire the type of active constructive imagination called Prefrontal Synthesis (PFS). Unlike vocabulary and grammar acquisition, which can be learned throughout one’s lifetime, there is a strong critical period for the development of PFS and individuals not exposed to recursive language in early childhood can never acquire PFS as adults. Their language will always lack understanding of spatial prepositions and recursion that depend on the PFS ability. In a similar manner, early hominins would not have been able to learn recursive language as adults and, therefore, would not be able to teach recursive language to their children. Thus, the existence of a strong critical period for PFS acquisition creates an evolutionary barrier for behavioral modernity. An evolutionary mathematical model suggests that a synergistic confluence of three events (1) a genetic mutation that extended the critical period by slowing down the prefrontal cortex development simultaneously in two or more children, (2) invention of recursive elements of language, such as spatial prepositions, by these children and (3) their dialogic communications using these recursive elements, resulted in concurrent conversion of a non-recursive communication system of their parents to recursive language and acquisition of PFS around 70,000 years ago. : #ref-1 : #ref-2
2,321 downloads evolutionary biology
Ekaterina Khrameeva, Ilia Kurochkin, Dingding Han, Patricia Guijarro, Sabina Kanton, Malgorzata Santel, Zhengzong Qian, Shen Rong, Pavel Mazin, Matvei Bulat, Olga Efimova, Anna Tkachev, Song Guo, Chet C Sherwood, J. Gray Camp, Svante Paabo, Barbara Treutlein, Philipp Khaitovich
Identification of gene expression traits unique to the human brain sheds light on the mechanisms of human cognition. Here we searched for gene expression traits separating humans from other primates by analyzing 88,047 cell nuclei and 422 tissue samples representing 33 brain regions of humans, chimpanzees, bonobos, and macaques. We show that gene expression evolves rapidly within cell types, with more than two-thirds of cell type-specific differences not detected using conventional RNA sequencing of tissue samples. Neurons tend to evolve faster in all hominids, but non-neuronal cell types, such as astrocytes and oligodendrocyte progenitors, show more differences on the human lineage, including alterations of spatial distribution across neocortical layers.
2,306 downloads evolutionary biology
The eukaryotic cytoskeleton evolved from prokaryotic cytomotive filaments. Prokaryotic filament systems show bewildering structural and dynamic complexity, and in many aspects prefigure the self-organizing properties of the eukaryotic cytoskeleton. Here I compare the dynamic properties of the prokaryotic and eukaryotic cytoskeleton, and discuss how these relate to function and the evolution of organellar networks. The evolution of new aspects of filament dynamics in eukaryotes, including severing and branching, and the advent of molecular motors converted the eukaryotic cytoskeleton into a self-organizing active gel, the dynamics of which can only be described with computational models. Advances in modeling and comparative genomics hold promise of a better understanding of the evolution of the self-organizing cytoskeleton in early eukaryotes, and its role in the evolution of novel eukaryotic functions, such as amoeboid motility, mitosis, and ciliary swimming.
2,295 downloads evolutionary biology
Recombination is a process that unlinks neighbouring loci allowing for independent evolutionary trajectories within genomes of many organisms. If not properly accounted for, recombination can compromise many evolutionary analyses. In addition, when dealing with organisms that are not obligately sexually reproducing, recombination gives insight into the rate at which distinct genetic lineages come into contact. Since June, 2012, Middle East respiratory syndrome coronavirus (MERS-CoV) has caused 1106 laboratory-confirmed infections, with 421 MERS-CoV associated deaths as of April 16, 2015. Although bats are considered as the likely ultimate source of zoonotic betacoronaviruses, dromedary camels have been consistently implicated as the source of current human infections in the Middle East. In this paper we use phylogenetic methods and simulations to show that MERS-CoV genome has likely undergone numerous recombinations recently. Recombination in MERS-CoV implies frequent co-infection with distinct lineages of MERS-CoV, probably in camels given the current understanding of MERS-CoV epidemiology.
2,281 downloads evolutionary biology
The interplay of divergent selection and gene flow is key to understanding how populations adapt to local environments and how new species form. Here, we use DNA polymorphism data and genome-wide variation in recombination rate to jointly infer the strength and timing of selection, as well as the baseline level of gene flow under various demographic scenarios. We model how divergent selection leads to a genome-wide negative correlation between recombination rate and genetic differentiation among populations. Our theory shows that the selection density, i.e. the selection coefficient per base pair, is a key parameter underlying this relationship. We then develop a procedure for parameter estimation that accounts for the confounding effect of background selection. Applying this method to two datasets from Mimulus guttatus, we infer a strong signal of adaptive divergence in the face of gene flow between populations growing on and off phytotoxic serpentine soils. However, the genome-wide intensity of this selection is not exceptional compared to what M. guttatus populations may typically experience when adapting to local conditions. We also find that selection against genome-wide introgression from the selfing sister species M. nasutus has acted to maintain a barrier between these two species over at least the last 250 ky. Our study provides a theoretical framework for linking genome-wide patterns of divergence and recombination with the underlying evolutionary mechanisms that drive this differentiation.
2,267 downloads evolutionary biology
Sex specific pheromones are known to play an important role in butterfly courtship, and may influence both individual reproductive success and reproductive isolation between species. Extensive ecological, behavioural and genetic studies of Heliconius butterflies have made a substantial contribution to our understanding of speciation. However, although long suspected to play an important role, chemical signals have received relatively little attention in this genus. Here, we combine morphological, chemical and behavioural analyses of a male pheromone in the neotropical butterfly Heliconius melpomene. First we identify specialized brush-like scales that are putative androconia, and lie within the shiny grey region found on the hindwing of males. We then describe six putative male sex pheromone compounds, which are largely confined to the androconial region of the hindwing of mature males, but not immature males or females. Finally, behavioural assays reveal subtle, but detectable, differences in female response to models scented with hindwing androconial extracts of mature conspecific males as compared to unscented controls. Collectively, the results describe structures involved in release of the pheromone and a list of potential male sex pheromone compounds triggering a behavioural response in females.
2,250 downloads evolutionary biology
Growing demands for aquatic sources of animal proteins have attracted significant investments in aquaculture research in recent years. The crustacean aquaculture industry has undergone substantial growth to accommodate a rising global demand, however such large-scale production is susceptible to pathogen-mediated destruction. It is clear that a thorough understanding of the crustacean innate immune system is imperative for future research into combating current and future pathogens of the main food crop species. Through a comparative genomics approach utilising extant data from 55 species, we describe the innate immune system of crustaceans from the Malacostraca class. We identify 7407 malacostracan genes from 39 gene families implicated in different aspects of host defence and demonstrate dynamic evolution of innate immunity components within this group. Malacostracans have achieved flexibility in recognising infectious agents through divergent evolution and expansion of pathogen recognition receptors genes. Antiviral RNAi, Toll and JAK-STAT signal transduction pathways have remained conserved within Malacostraca, although the Imd pathway appears to lack several key components. Immune effectors such as the antimicrobial peptides (AMPs) have unique evolutionary profiles, with many malacostracan AMPs not found in other arthropod groups. Lastly, we describe four putative novel immune gene families, characterised by distinct protein domains, potentially representing important evolutionary novelties of the malacostracan immune system.
2,248 downloads evolutionary biology
The idea of driving genetically modified alleles to fixation in a population has fascinated scientists for over 40 years. Potential applications are broad and ambitious, including the eradication of disease vectors, the control of pest species, and the preservation of endangered species from extinction. Until recently, these possibilities have remained largely abstract due to the lack of an effective drive mechanism. CRISPR/Cas9 gene drive (CGD) now promise a highly adaptable approach for driving even deleterious alleles to high population frequency, and this approach was recently shown to be effective in small laboratory populations of insects. However, it remains unclear whether CGD will also work in large natural populations in the face of potential resistance mechanisms. Here we show that resistance against CGD will inevitably evolve unless populations are small and repair of CGD-induced cleavage via nonhomologous end joining (NHEJ) can be effectively suppressed, or resistance costs are on par with those of the driver. We specifically calculate the probability that resistance evolves from variants at the target site that are not recognized by the driver's guide RNA, either because they are already present when the driver allele is introduced, arise by de novo mutation, or are created by the driver itself when NHEJ introduces mutations at the target site. Our results shed light on strategies that could facilitate the engineering of a successful drive by lowering resistance potential, as well as strategies that could promote resistance as a possible mechanism for controlling a drive. This study highlights the need for careful modeling of CGD prior to the actual release of a driver construct into the wild.
2,248 downloads evolutionary biology
Olivier Tenaillon, Jeffrey E. Barrick, Noah Ribeck, Daniel E. Deatherage, Jeffrey L. Blanchard, Aurko Dasgupta, Gabriel C. Wu, Sébastien Wielgoss, Stéphane Cruveiller, Claudine Médigue, Dominique Schneider, Richard E. Lenski
Adaptation depends on the rates, effects, and interactions of many mutations. We analyzed 264 genomes from 12 Escherichia coli populations to characterize their dynamics over 50,000 generations. The trajectories for genome evolution in populations that retained the ancestral mutation rate fit a model where most fixed mutations are beneficial, the fraction of beneficial mutations declines as fitness rises, and neutral mutations accumulate at a constant rate. We also compared these populations to lines evolved under a mutation-accumulation regime that minimizes selection. Nonsynonymous mutations, intergenic mutations, insertions, and deletions are overrepresented in the long-term populations, supporting the inference that most fixed mutations are favored by selection. These results illuminate the shifting balance of forces that govern genome evolution in populations adapting to a new environment.
2,242 downloads evolutionary biology
Nicola J. Barson, Tutku Aykanat, Kjetil Hindar, Matthew Baranski, Geir H Bolstad, Peder Fiske, Céleste Jacq, Arne J. Jensen, Susan E. Johnston, Sten Karlsoon, Matthew Kent, Eero Niemelä, Torfinn Nome, Tor F. Næsje, Panu Orell, Atso Romakkaniemi, Harald Sægrov, Kurt Urdal, Jaakko Erkinaro, Sigbjørn Lien, Craig R. Primmer
Males and females share many traits that have a common genetic basis, however selection on these traits often differs between the sexes leading to sexual conflict. Under such sexual antagonism, theory predicts the evolution of genetic architectures that resolve this sexual conflict. Yet, despite intense theoretical and empirical interest, the specific genetic loci behind sexually antagonistic phenotypes have rarely been identified, limiting our understanding of how sexual conflict impacts genome evolution and the maintenance of genetic diversity. Here, we identify a large effect locus controlling age at maturity in 57 salmon populations, an important fitness trait in which selection favours earlier maturation in males than females, and show it is a clear example of sex dependent dominance reducing intralocus sexual conflict and maintaining adaptive variation in wild populations. Using high density SNP data and whole genome re-sequencing, we found that vestigial-like family member 3 (VGLL3) exhibits sex-dependent dominance in salmon, promoting earlier and later maturation in males and females, respectively. VGLL3, an adiposity regulator associated with size and age at maturity in humans, explained 39.4% of phenotypic variation, an unexpectedly high effect size for what is usually considered a highly polygenic trait. Such large effects are predicted under balancing selection from either sexually antagonistic or spatially varying selection. Our results provide the first empirical example of dominance reversal permitting greater optimisation of phenotypes within each sex, contributing to the resolution of sexual conflict in a major and widespread evolutionary trade-off between age and size at maturity. They also provide key empirical evidence for how variation in reproductive strategies can be maintained over large geographical scales. We further anticipate these findings will have a substantial impact on population management in a range of harvested species where trends towards earlier maturation have been observed
2,228 downloads evolutionary biology
PhyloNet was released in 2008 as a software package for representing and analyzing phylogenetic networks. At the time of its release, the main functionalities in PhyloNet consisted of measures for comparing network topologies and a single heuristic for reconciling gene trees with a species tree. Since then, PhyloNet has grown significantly. The software package now includes a wide array of methods for inferring phylogenetic networks from data sets of unlinked loci while accounting for both reticulation (e.g., hybridization) and incomplete lineage sorting. In particular, PhyloNet now allows for maximum parsimony, maximum likelihood, and Bayesian inference of phylogenetic networks from gene tree estimates. Furthermore, Bayesian inference directly from sequence data (sequence alignments or bi-allelic markers) is implemented. Maximum parsimony is based on an extension of the "minimizing deep coalescences" criterion to phylogenetic networks, whereas maximum likelihood and Bayesian inference are based on the multispecies network coalescent. All methods allow for multiple individuals per species. As computing the likelihood of a phylogenetic network is computationally hard, PhyloNet allows for evaluation and inference of networks using a pseudo-likelihood measure. PhyloNet summarizes the results of the various analyses, and generates phylogenetic networks in the extended Newick format that is readily viewable by existing visualization software.
2,222 downloads evolutionary biology
Evolution of a novel function can greatly alter the effects of an organism on its environment. These environmental changes can, in turn, affect the further evolution of that organism and any coexisting organisms. We examine these effects and feedbacks following evolution of a novel function in the long-term evolution experiment (LTEE) with Escherichia coli. A characteristic feature of E. coli is its inability to consume citrate aerobically. However, that ability evolved in one of the LTEE populations. In this population, citrate-utilizing bacteria (Cit+) coexisted stably with another clade of bacteria that lacked the capacity to utilize citrate (Cit−). This coexistence was shaped by the evolution of a cross-feeding relationship in which Cit+ cells released the dicarboxylic acids succinate, fumarate, and malate into the medium, and Cit− cells evolved improved growth on these carbon sources, as did the Cit+ cells. Thus, the evolution of citrate consumption led to a flask-based ecosystem that went from a single limiting resource, glucose, to one with five resources either shared or partitioned between two coexisting clades. Our findings show how evolutionary novelties can change environmental conditions, thereby facilitating diversity and altering both the structure of an ecosystem and the evolutionary trajectories of coexisting organisms.
2,217 downloads evolutionary biology
A classic problem in population genetics is the characterization of discrete population structure in the presence of continuous patterns of genetic differentiation. Especially when sampling is discontinuous, the use of clustering or assignment methods may incorrectly ascribe differentiation due to continuous processes (e.g., geographic isolation by distance) to discrete processes, such as geographic, ecological, or reproductive barriers between populations. This reflects a shortcoming of current methods for inferring and visualizing population structure when applied to genetic data deriving from geographically distributed populations. Here, we present a statistical framework for the simultaneous inference of continuous and discrete patterns of population structure. The method estimates ancestry proportions for each sample from a set of two-dimensional population layers, and, within each layer, estimates a rate at which relatedness decays with distance. This thereby explicitly addresses the “clines versus cluster” problem in modeling population genetic variation. The method produces useful descriptions of structure in genetic relatedness in situations where separated, geographically distributed populations interact, as after a range expansion or secondary contact. We demonstrate the utility of this approach using simulations and by applying it to empirical datasets of poplars and black bears in North America.
2,208 downloads evolutionary biology
The Eurasian sympatry of Neandertals and anatomically modern humans - beginning at least 45,000 years ago and lasting for more than 5,000 years - has long sparked anthropological interest into the factors that potentially contributed to Neandertal extinction. Among many different hypotheses, the "differential pathogen resistance" extinction model posits that Neandertals were disproportionately affected by exposure to novel infectious diseases that were transmitted during the period of spatiotemporal sympatry with modern humans. Comparisons of new archaic hominin paleogenome sequences with modern human genomes have confirmed a history of genetic admixture - and thus direct contact - between humans and Neandertals. Analyses of these data have also shown that Neandertal nuclear genome genetic diversity was likely considerably lower than that of the Eurasian anatomically modern humans with whom they came into contact, perhaps leaving Neandertal innate immune systems relatively more susceptible to novel pathogens. In this study, we compared levels of genetic diversity in genes for which genetic variation is hypothesized to benefit pathogen defense among Neandertals and African, European, and Asian modern humans, using available exome sequencing data (six chromosomes per population). We observed that Neandertals had only 31-39% as many nonsynonymous (amino acid changing) polymorphisms across 73 innate immune system genes compared to modern human populations. We also found that Neandertal genetic diversity was relatively low in an unbiased set of balancing selection candidate genes for primates - genes with the highest 1% genetic diversity genome-wide in non-human apes. In contrast, Neandertals had similar to higher levels of genetic diversity than humans in 13 major histocompatibility complex (MHC) genes. Thus, while Neandertals may have been relatively more susceptible to some novel pathogens and differential pathogen resistance could be considered as one potential contributing factor in their extinction, this model does have limitations.
2,203 downloads evolutionary biology
Although estimated to have emerged in humans in Central Africa in the early 1900s, HIV-1, the main causative agent of AIDS, was only discovered in 1983. With very little direct biological data of HIV-1 from before the 1980s, far-reaching evolutionary and epidemiological inferences regarding the long pre-discovery phase of this pandemic are based on extrapolations by phylodynamic models of HIV-1 genomic sequences gathered mostly over recent decades. Here, using a very sensitive multiplex RT-PCR assay, we screened 1,652 formalin-fixed paraffin-embedded tissue specimens collected for pathology diagnostics in Kinshasa, Democratic Republic of Congo (DRC), between 1959 and 1967. We report the near-complete genome of one positive from 1966 ('DRC66') - a non-recombinant sister lineage to subtype C that constitutes the oldest HIV-1 near-full-length genome recovered to date. Root-to-tip plots showed the DRC66 sequence is not an outlier as would be expected if dating estimates from more recent genomes were systematically biased; and inclusion of DRC66 sequence in tip-dated BEAST analyses did not significantly alter root and internal node age estimates based on post-1978 HIV-1 sequences. There was larger variation in divergence time estimates among datasets that were subsamples of the available HIV-1 genomes from 1978-2015, showing the inherent phylogenetic stochasticity across subsets of the real HIV-1 diversity. In conclusion, this unique archival HIV-1 sequence provides direct genomic insight into HIV-1 in 1960s DRC, and, as an ancient-DNA calibrator, it validates our understanding of HIV-1 evolutionary history.
2,202 downloads evolutionary biology
Epistasis can make adaptation highly unpredictable, rendering evolutionary trajectories contingent on the chance effects of initial mutations. We used experimental evolution in Saccharomyces cerevisiae to quantify this effect, finding dramatic differences in adaptability between 64 closely related genotypes. Despite these differences, sequencing of 105 evolved clones showed no significant effect of initial genotype on future sequence-level evolution. Instead, reconstruction experiments revealed a consistent pattern of diminishing returns epistasis. Our results suggest that many beneficial mutations affecting a variety of biological processes are globally coupled: they interact strongly, but only through their combined effect on fitness. Sequence-level adaptation is thus highly stochastic. Nevertheless, fitness evolution is strikingly predictable because differences in adaptability are determined only by global fitness-mediated epistasis, not by the identity of individual mutations.
2,201 downloads evolutionary biology
Experiments show that evolutionary fitness landscapes can have a rich combinatorial structure due to epistasis. For some landscapes, this structure can produce a computational constraint that prevents evolution from finding local fitness optima -- thus overturning the traditional assumption that local fitness peaks can always be reached quickly if no other evolutionary forces challenge natural selection. Here, I introduce a distinction between easy landscapes of traditional theory where local fitness peaks can be found in a moderate number of steps and hard landscapes where finding local optima requires an infeasible amount of time. Hard examples exist even among landscapes with no reciprocal sign epistasis; on these semi-smooth fitness landscapes, strong selection weak mutation dynamics cannot find the unique peak in polynomial time. More generally, on hard rugged fitness landscapes that include reciprocal sign epistasis, no evolutionary dynamics -- even ones that do not follow adaptive paths -- can find a local fitness optimum quickly. Moreover, on hard landscapes, the fitness advantage of nearby mutants cannot drop off exponentially fast but has to follow a power-law that long term evolution experiments have associated with unbounded growth in fitness. Thus, the constraint of computational complexity enables open-ended evolution on finite landscapes. Knowing this constraint allows us to use the tools of theoretical computer science and combinatorial optimization to characterize the fitness landscapes that we expect to see in nature. I present candidates for hard landscapes at scales from single genes, to microbes, to complex organisms with costly learning (Baldwin effect) or maintained cooperation (Hankshaw effect). Just how ubiquitous hard landscapes (and the corresponding ultimate constraint on evolution) are in nature becomes an open empirical question.
2,200 downloads evolutionary biology
Inference for population genetics models is hindered by computationally intractable likelihoods. While this issue is tackled by likelihood-free methods, these approaches typically rely on hand-crafted summary statistics of the data. In complex settings, designing and selecting suitable summary statistics is problematic and results are very sensitive to such choices. In this paper, we learn the first exchangeable feature representation for population genetic data to work directly with genotype data. This is achieved by means of a novel Bayesian likelihood-free inference framework, where a permutation-invariant convolutional neural network learns the inverse functional relationship from the data to the posterior. We leverage access to scientific simulators to learn such likelihood-free function mappings, and establish a general framework for inference in a variety of simulation-based tasks. We demonstrate the power of our method on the recombination hotspot testing problem, outperforming the state-of-the-art.
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