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Sequence alignment is an essential method in bioinformatics and the basis of many analyses, including phylogenetic inference, ancestral sequence reconstruction, and gene annotation. Sequence artifacts and errors made in alignment reconstruction can impact downstream analyses leading to erroneous conclusions in comparative and functional genomic studies. For example, abiological frameshifts and early stop codons are common artifacts found in protein coding sequences that have been annotated in reference genomes. While such errors are eventually fixed in the reference genomes of model organisms, many genomes used by researchers contain these artifacts, and researchers often discard large amounts of data in comparative genomic studies to prevent artifacts from impacting results. To address this need, we present COATi, a statistical, codon-aware pairwise aligner that supports complex insertion-deletion models and can handle artifacts present in genomic data. COATi allows users to reduce the amount of discarded data while generating more accurate sequence alignments.

Host switching allows parasites to expand their niches. However, successful switching may require suites of adaptations and may decrease performance on the old host. As a result, reductions in gene flow accompany many host switches, driving speciation. Because host switches tend to be rapid, it is difficult to study them in real time and their demographic parameters remain poorly understood. As a result, fundamental factors that control subsequent parasite evolution, such as the size of the switching population or the extent of immigration from the original host, remain largely unknown. To shed light on the host switching process, we explored how host switches occur in independent host shifts by two ectoparasitic honey bee mites (Varroa destructor and V. jacobsoni). Both switched to the western honey bee (Apis mellifera) after it was brought into contact with their ancestral host (Apis cerana), ~70 and ~12 years ago, respectively. Varroa destructor subsequently caused worldwide collapses of honey bee populations. Using whole-genome sequencing on 63 mites collected in their native ranges from both the ancestral and novel hosts, we were able to reconstruct the known temporal dynamics of the switch. We further found multiple previously undiscovered mitochondrial lineages on the novel host, along with genetic equivalent of tens of individuals that were involved in the initial host switch. Despite being greatly reduced, some gene flow remains between mites adapted to different hosts. Our findings suggest that while reproductive isolation may facilitate fixation of traits beneficial for exploitation of the new host, ongoing genetic exchange may allow genetic amelioration of inbreeding effects.

Insertions and deletions (indels) are common molecular evolutionary events. However, probabilistic models for indel evolution are under-developed due to their computational complexity. Here, we introduce several improvements to indel modeling: 1) While previous models for indel evolution assumed that the rates and length distributions of insertions and deletions are equal, here we propose a richer model that explicitly distinguishes between the two; 2) we introduce numerous summary statistics that allow approximate Bayesian computation-based parameter estimation; 3) we develop a method to correct for biases introduced by alignment programs, when inferring indel parameters from empirical data sets; and 4) using a model-selection scheme, we test whether the richer model better fits biological data compared with the simpler model. Our analyses suggest that both our inference scheme and the model-selection procedure achieve high accuracy on simulated data. We further demonstrate that our proposed richer model better fits a large number of empirical data sets and that, for the majority of these data sets, the deletion rate is higher than the insertion rate.

Background One of the most challenging topics for students in Evolution courses is that of non-adaptive evolution, particularly genetic drift. Novel teaching techniques and software have been implemented to facilitate student understanding of this and other evolution related topics; nonetheless, some of them still present certain disadvantages. Here we introduce Genie, a web-based application designed to demonstrate population genetics and evolutionary concepts. Results We used Genie as a tool to teach 203 students taking Arizona State University’s Evolution course. Students freely used Genie during recitation session after having learned about genetic drift and other mechanism of non-adaptive evolution during lectures. Student performance and comprehension of genetic drift, and other evolutionary concepts, was tested with the Genetic Drift Inventory before and after using Genie. We found that Genie was an efficient tool for teaching genetic drift, mutation, the effects of barrier formation, and gene flow, across a variety of student demographics. Specifically, we found that with our implementation of Genie, students had significantly improved understanding of concepts such as: changes in alleles frequencies due to genetic drift and the difference between adaptive and non-adaptive evolutionary mechanisms. Conclusions We believe that the easy usage, creativity, and real-time nature of Genie makes it an accessible tool for both teachers and students learning non-adaptive evolution, as well as a means for student development of creative and critical thinking. Genie is freely available ( https://cartwrig.ht/apps/genie/ ) and can be easily accessed across different operating systems.

Gut microbiome disruptions may lead to adverse effects on wildlife fitness and viability, thus maintaining host microbiota biodiversity needs to become an integral part of wildlife conservation. The highly-endangered callitrichid golden lion tamarin (GLT-Leontopithecus rosalia) is a rare conservation success, but allochthonous callitrichid marmosets (Callithrix) serve as principle ecological GLT threats. However, incorporation of microbiome approaches to GLT conservation is impeded by limited gut microbiome studies of Brazilian primates. Here, we carried out analysis of metagenomic pools from a total of 80 individuals of wild and captive GLTs and marmosets. More specifically, we analyzed the bacterial component of ultra-filtered samples originally collected as part of a virome profiling study. The major findings of this study are consistent with previous studies in showing that Bifidobacterium, a bacterial species important to the metabolism of tree gums consumed by callitrichids, is an important component of the callitrichid gut microbiome - although GTLs and marmosets were enriched for different species of Bifidobacterium. Additionally, the composition of GLT and marmoset gut microbiota is sensitive to host environmental factors. Overall, our data expands baseline gut microbiome data for callitrichids to allow for the development of new tools to improve their management and conservation.

Background Callithrix marmosets are a relatively young primate radiation, whose phylogeny is not yet fully resolved. These primates are naturally para- and allopatric, but three species with highly invasive potential have been introduced into the southeastern Brazilian Atlantic Forest by the pet trade. There, these species hybridize with each other and endangered, native congeners. We aimed here to reconstruct a robust Callithrix phylogeny and divergence time estimates, and identify the biogeographic origins of autochthonous and allochthonous Callithrix mitogenome lineages. We sequenced 49 mitogenomes from four species (C. aurita, C. geoffroyi, C. jacchus, C. penicillata) and anthropogenic hybrids (C. aurita x Callithrix sp., C. penicillata x C. jacchus, Callithrix sp. x Callithrix sp., C. penicillata x C. geoffroyi) via Sanger and whole genome sequencing. We combined these data with previously published Callithrix mitogenomes to analyze five Callithrix species in total. Results We report the complete sequence and organization of the C. aurita mitogenome. Phylogenetic analyses showed that C. aurita was the first to diverge within Callithrix 3.54 million years ago (Ma), while C. jacchus and C. penicillata lineages diverged most recently 0.5 Ma as sister clades. MtDNA clades of C. aurita, C. geoffroyi, and C. penicillata show intraspecific geographic structure, but C. penicillata clades appear polyphyletic. Hybrids, which were identified by phenotype, possessed mainly C. penicillata or C. jacchus mtDNA haplotypes. The biogeographic origins of mtDNA haplotypes from hybrid and allochthonous Callithrix were broadly distributed across natural Callithrix ranges. Our phylogenetic results also evidence introgression of C. jacchus mtDNA into C. aurita. Conclusion Our robust Callithrix mitogenome phylogeny shows C. aurita lineages as basal and C. jacchus lineages among the most recent within Callithrix. We provide the first evidence that parental mtDNA lineages of anthropogenic hybrid and allochthonous marmosets are broadly distributed inside and outside of the Atlantic Forest. We also show evidence of cryptic hybridization between allochthonous Callithrix and autochthonous C. aurita. Our results encouragingly show that further development of genomic resources will allow to more clearly elucidate Callithrix evolutionary relationships and understand the dynamics of Callithrix anthropogenic introductions into the Brazilian Atlantic Forest.

Callithrix marmosets are a relatively young primate radiation, whose phylogeny is not yet fully resolved. These primates are naturally para- and allopatric, but three species with highly invasive potential have been introduced into the southeastern Brazilian Atlantic Forest by the pet trade. There, these species hybridize with each other and endangered, native congeners. We aimed here to reconstruct a robust Callithrix phylogeny and divergence time estimates, and identify the biogeographic origins of autochthonous and allochthonous Callithrix mitogenome lineages. We sequenced 49 mitogenomes from four species (C. aurita, C. geoffroyi, C. jacchus, C. penicillata) and anthropogenic hybrids (C. aurita x Callithrix sp., C. penicillata x C. jacchus, Callithrix sp. x Callithrix sp., C. penicillata x C. geoffroyi) via Sanger and whole genome sequencing. We combined these data with previously published Callithrix mitogenomes to analyze five Callithrix species in total.ResultsWe report the complete sequence and organization of the C. aurita mitogenome. Phylogenetic analyses showed that C. aurita was the first to diverge within Callithrix 3.54 million years ago (Ma), while C. jacchus and C. penicillata lineages diverged most recently 0.5 Ma as sister clades. MtDNA clades of C. aurita, C. geoffroyi, and C. penicillata show intraspecific geographic structure, but C. penicillata clades appear polyphyletic. Hybrids, which were identified by phenotype, possessed mainly C. penicillata or C. jacchus mtDNA haplotypes. The biogeographic origins of mtDNA haplotypes from hybrid and allochthonous Callithrix were broadly distributed across natural Callithrix ranges. Our phylogenetic results also evidence introgression of C. jacchus mtDNA into C. aurita.ConclusionOur robust Callithrix mitogenome phylogeny shows C. aurita lineages as basal and C. jacchus lineages among the most recent within Callithrix. We provide the first evidence that parental mtDNA lineages of anthropogenic hybrid and allochthonous marmosets are broadly distributed inside and outside of the Atlantic Forest. We also show evidence of cryptic hybridization between allochthonous Callithrix and autochthonous C. aurita. Our results encouragingly show that further development of genomic resources will allow to more clearly elucidate Callithrix evolutionary relationships and understand the dynamics of Callithrix anthropogenic introductions into the Brazilian Atlantic Forest.

BackgroundHost switching allows parasites to expand their niches. However, successful switching may require suites of adaptations and also may decrease performance on the old host. As a result, reductions in gene flow accompany many host switches, driving speciation. Because host switches tend to be rapid, it is difficult to study them in real-time and their demographic parameters remain poorly understood. As a result, fundamental factors that control subsequent parasite evolution, such as the size of the switching population or the extent of immigration from the original host, remain largely unknown. To shed light on the host switching process, we explored how host switches occur in independent host shifts by two ectoparasitic honey bee mites (Varroa destructor and V. jacobsoni).ResultsBoth switched to the western honey bee (Apis mellifera) after it was brought into contact with their ancestral host (Apis cerana), ∼70 and ∼12 years ago, respectively. Varroa destructor subsequently caused worldwide collapses of honey bee populations. Using whole-genome sequencing on 63 mites collected in their native ranges from both the ancestral and novel hosts, we were able to reconstruct the known temporal dynamics of the switch. We further found multiple previously undiscovered mitochondrial lineages on the novel host, along with the genetic equivalent of tens of individuals that were involved in the initial host switch. Despite being greatly reduced, some gene flow remains between mites adapted to different hosts.ConclusionOur findings suggest that while reproductive isolation may facilitate the fixation of traits beneficial for exploitation of the new host, ongoing genetic exchange may allow genetic amelioration of inbreeding effects.

Microbial production of fuels and chemicals from lignocellulosic biomass provides promising biorenewable alternatives to the conventional petroleum-based products. However, heterogeneous sugar composition of lignocellulosic biomass hinders efficient microbial conversion due to carbon catabolite repression. The most abundant sugar monomers in lignocellulosic biomass materials are glucose and xylose. Although industrial Escherichia coli strains efficiently use glucose, their ability to use xylose is often repressed in the presence of glucose. Here we independently evolved three E. coli strains from the same ancestor to achieve high efficiency for xylose fermentation. Each evolved strain has a point mutation in a transcriptional activator for xylose catabolic operons, either CRP or XylR, and these mutations are demonstrated to enhance xylose fermentation by allelic replacements. Identified XylR variants (R121C and P363S) have a higher affinity to their DNA binding sites, leading to a xylose catabolic activation independent of catabolite repression control. Upon introducing these amino acid substitutions into the E. coli D-lactate producer TG114, 94% of a glucose-xylose mixture (50 g⋅L-1 each) was used in mineral salt media that led to a 50% increase in product titer after 96 h of fermentation. The two amino acid substitutions in XylR enhance xylose utilization and release glucose-induced repression in different E. coli hosts, including wild type, suggesting its potential wide application in industrial E. coli biocatalysts.

The most common evolutionary events at the molecular level are single-base substitutions, as well as insertions and deletions (indels) of short DNA segments. A large body of research has been devoted to develop probabilistic substitution models and to infer their parameters using likelihood and Bayesian approaches. In contrast, relatively little has been done to model indel dynamics, probably due to the difficulty in writing explicit likelihood functions. Here, we contribute to the effort of modeling indel dynamics by presenting SpartaABC, an approximate Bayesian computation (ABC) approach to infer indel parameters from sequence data (either aligned or unaligned). SpartaABC circumvents the need to use an explicit likelihood function by extracting summary statistics from simulated sequences. First, summary statistics are extracted from the input sequence data. Second, SpartaABC samples indel parameters from a prior distribution and uses them to simulate sequences. Third, it computes summary statistics from the simulated sets of sequences. By computing a distance between the summary statistics extracted from the input and each simulation, SpartaABC can provide an approximation to the posterior distribution of indel parameters as well as point estimates. We study the performance of our methodology and show that it provides accurate estimates of indel parameters in simulations. We next demonstrate the utility of SpartaABC by studying the impact of alignment errors on the inference of positive selection. A C ++ program implementing SpartaABC is freely available in http://spartaabc.tau.ac.il.

Many analyses for the detection of biological phenomena rely on a multiple sequence alignment as input. The results of such analyses are often further studied through parametric bootstrap procedures, using sequence simulators. One of the problems with conducting such simulation studies is that users currently have no means to decide which insertion and deletion (indel) parameters to choose, so that the resulting sequences mimic biological data. Here, we present SpartaABC, a web server that aims to solve this issue. SpartaABC implements an approximate-Bayesian-computation rejection algorithm to infer indel parameters from sequence data. It does so by extracting summary statistics from the input. It then performs numerous sequence simulations under randomly sampled indel parameters. By computing a distance between the summary statistics extracted from the input and each simulation, SpartaABC retains only parameters behind simulations close to the real data. As output, SpartaABC provides point estimates and approximate posterior distributions of the indel parameters. In addition, SpartaABC allows simulating sequences with the inferred indel parameters. To this end, the sequence simulators, Dawg 2.0 and INDELible were integrated. Using SpartaABC we demonstrate the differences in indel dynamics among three protein-coding genes across mammalian orthologs. SpartaABC is freely available for use at http://spartaabc.tau.ac.il/webserver.

The explosion in population genomic data demands ever more complex modes of analysis, and increasingly these analyses depend on sophisticated simulations. Recent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to inconsistency and duplication of effort. This situation presents a major barrier to empirical researchers seeking to use simulations for power analyses of upcoming studies or sanity checks on existing genomic data. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here we describe a new resource,stdpopsim, that attempts to rectify this situation.Stdpopsimis a community-driven open source project, which provides easy access to a growing catalog of published simulation models from a range of organisms and supports multiple simulation engine backends. This resource is available as a well-documented python library with a simple command-line interface. We share some examples demonstrating howstdpopsimcan be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource.

Somatic mutations can have important effects on the life history, ecology, and evolution of plants, but the rate at which they accumulate is poorly understood and difficult to measure directly. Here, we develop a method to measure somatic mutations in individual plants and use it to estimate the somatic mutation rate in a large, long-lived, phenotypically mosaic Eucalyptus melliodora tree. Despite being 100 times larger than Arabidopsis, this tree has a per-generation mutation rate only ten times greater, which suggests that this species may have evolved mechanisms to reduce the mutation rate per unit of growth. This adds to a growing body of evidence that illuminates the correlated evolutionary shifts in mutation rate and life history in plants.

Efficient xylose utilization will facilitate microbial conversion of lignocellulosic sugar mixtures into valuable products. In Escherichia coli, xylose catabolism is controlled by carbon catabolite repression (CCR). However, in E. coli such as the succinate-producing strain KJ122 with disrupted CCR, xylose utilization is still inhibited under fermentative conditions. To probe the underlying genetic mechanisms inhibiting xylose utilization, we evolved KJ122 to enhance its xylose fermentation abilities in parallel and characterized the potential convergent genetic changes shared by multiple independently evolved strains. Whole-genome sequencing revealed that convergent mutations occurred in the galactose regulon during adaptive laboratory evolution potentially decreasing the transcriptional level or the activity of GalP, a galactose permease. We showed that deletion of galP increased xylose utilization in both KJ122 and wild-type E. coli, demonstrating a common repressive role of GalP for xylose fermentation. Concomitantly, induced expression of galP from a plasmid repressed xylose fermentation. Transcriptome analysis using RNA sequencing indicates that galP inactivation increases transcription levels of many catabolic genes for secondary sugars including xylose and arabinose. The repressive role of GalP for fermenting secondary sugars in E. coli suggests that utilization of GalP as a substitute glucose transporter is undesirable for conversion of lignocellulosic sugar mixtures.

Understanding the molecular basis of repeated evolved phenotypes can yield key insights into the evolutionary process. Quantifying the amount of gene flow between populations is especially important in interpreting mechanisms of repeated phenotypic evolution, and genomic analyses have revealed that admixture is more common between diverging lineages than previously thought. In this study, we resequenced and analyzed nearly 50 whole genomes of the Mexican tetra from three blind cave populations, two surface populations, and outgroup samples. We confirmed that cave populations are polyphyletic and twoAstyanax mexicanuslineages are present in our dataset. The two lineages likely diverged ∼257k generations ago, which, assuming 1 generation per year, is substantially younger than previous mitochondrial estimates of 5-7mya. Divergence of cave populations from their phylogenetically closest surface population likely occurred between ∼161k - 191k generations ago. The favored demographic model for most population pairs accounts for divergence with secondary contact and heterogeneous gene flow across the genome, and we rigorously identified abundant gene flow between cave and surface fish, between caves, and between separate lineages of cave and surface fish. Therefore, the evolution of cave-related traits occurred more rapidly than previously thought, and trogolomorphic traits are maintained despite substantial gene flow with surface populations. After incorporating these new demographic estimates, our models support that selection may drive the evolution of cave-derived traits, as opposed to the classic hypothesis of disuse and drift. Finally, we show that a key QTL is enriched for genomic regions with very low divergence between caves, suggesting that regions important for cave phenotypes may be transferred between caves via gene flow. In sum, our study shows that shared evolutionary history via gene flow must be considered in studies of independent, repeated trait evolution.

Inbreeding in hermaphroditic plants can occur through two different mechanisms: biparental inbreeding, when a plant mates with a related individual, or self-fertilization, when a plant mates with itself. To avoid inbreeding, many hermaphroditic plants have evolved self-incompatibility (SI) systems which prevent or limit self-fertilization. One particular SI system—homomorphic SI—can also reduce biparental inbreeding. Homomorphic SI is found in many angiosperm species, and it is often assumed that the additional benefit of reduced biparental inbreeding may be a factor in the success of this SI system. To test this assumption, we developed a spatially-explicit, individual-based simulation of plant populations that displayed three different types of homomorphic SI. We measured the total level of inbreeding avoidance by comparing each population to a self-compatible population (NSI), and we measured biparental inbreeding avoidance by comparing to a population of self-incompatible plants that were free to mate with any other individual (PSI). Because biparental inbreeding is more common when offspring dispersal is limited, we examined the levels of biparental inbreeding over a range of dispersal distances. We also tested whether the introduction of inbreeding depression affected the level of biparental inbreeding avoidance. We found that there was a statistically significant decrease in autozygosity in each of the homomorphic SI populations compared to the PSI population and, as expected, this was more pronounced when seed and pollen dispersal was limited. However, levels of homozygosity and inbreeding depression were not reduced. At low dispersal, homomorphic SI populations also suffered reduced female fecundity and had smaller census population sizes. Overall, our simulations showed that the homomorphic SI systems had little impact on the amount of biparental inbreeding in the population especially when compared to the overall reduction in inbreeding compared to the NSI population. With further study, this observation may have important consequences for research into the origin and evolution of homomorphic self-incompatibility systems.

MotivationMutation accumulation (MA) is the most widely used method for directly studying the effects of mutation. Modern sequencing technologies have led to an increased interest in MA experiments. By sequencing whole genomes from MA lines, researchers can directly study the rate and molecular spectra of spontaneous mutations and use these results to understand how mutation contributes to biological processes. At present there is no software designed specifically for identifying mutations from MA lines. Studies that combine MA with whole genome sequencing use custom bioinformatic pipelines that implement heuristic rules to identify putative mutations.ResultsHere we describeaccuMUlate, a program that is designed to detect mutations from MA experiments.accuMUlateimplements a probabilistic model that reflects the design of a typical MA experiments while being flexible enough to accommodate properties unique to any particular experiment. For each putative mutation identified from this modelaccuMUlatecalculates a set of summary statistics that can be used to filter sites that may be false positives. A companion tool,denominate, can be used to apply filtering rules based on these statistics to simulated mutations and thus identify the number of callable sites per sample.AvailabilitySource code and releases available fromhttps://github.com/dwinter/accuMUlate.

Hermaphroditic plants experience inbreeding through both self-fertilization and bi-parental inbreeding. Therefore, many plant species have evolved either heteromorphic (morphology-based) or homomorphic (molecular-based) self-incompatibility (SI) systems. These SI systems limit extreme inbreeding through self-fertilization and, in the case of homomorphic SI systems, have the potential to limit bi-parental inbreeding, which is common when dispersal is restricted to a local region. Homomorphic SI species are prevalent across the angiosperms, and it is often assumed that the potential to reduce bi-parental inbreeding may be a factor in their success. To test this assumption, we developed a spatially-explicit, individual-based simulation of plant populations with either heteromorphic SI or one of three different types of homomorphic SI. In our simulations, we varied dispersal distance and the presence of inbreeding depression. We found that autozygosity in the homomorphic SI populations was significantly lower than in the heteromorphic SI populations and that this reduction was due to bi-parental inbreeding avoidance. As expected, the differences between the homomorphic and heteromorphic SI populations were more pronounced when seed and pollen dispersal was limited. However, levels of homozygosity and inbreeding depression between these plant populations were not different. At low dispersal, homomorphic SI populations also suffered reduced female fecundity and had smaller census population sizes. Our results suggest that bi-parental inbreeding avoidance was unlikely to be a major driver in the evolution of homomorphic SI systems.

Microbial production of fuels and chemicals from lignocellulosic biomass provides promising bio-renewable alternatives to the conventional petroleum-based products. However, heterogeneous sugar composition of lignocellulosic biomass hinders efficient microbial conversion due to carbon catabolite repression. The most abundant sugar monomers in lignocel-lulosic biomass materials are glucose and xylose. While industrialEscherichia colistrains efficiently utilize glucose, their ability to utilize xylose is often repressed in the presence of glucose. Here we independently evolved threeE. colistrains from the same ancestor to achieve high efficiency for xylose fermentation. Each evolved strain has a point mutation in a transcriptional activator for xylose catabolic operons, either CRP or XylR, and these mutations are demonstrated to enhance xylose fermentation by allelic replacements. Identified XylR variants (R121C and P363S) have a higher affinity to their DNA binding sites, leading to a xylose catabolic activation independent of catabolite repression control. Upon introducing these amino acid substitutions into theE. coliD-lactate producer TG114, 94 % of a glucose-xylose mixture (50 g L-1each) was utilized in mineral salt media that led to a 50 % increase in product titer after 96 h of fermentation. The two amino acid substitutions in XylR enhance xylose utilization and release glucose-induced repression in differentE. colihosts, including wild-type, suggesting its potential wide application in industrialE. colibiocatalysts.

Domestication and plant breeding are ongoing 10,000-year-old evolutionary experiments that have radically altered wild species to meet human needs. Maize has undergone a particularly striking transformation. Researchers have sought for decades to identify the genes underlying maize evolution, but these efforts have been limited in scope. Here, we report a comprehensive assessment of the evolution of modern maize based on the genome-wide resequencing of 75 wild, landrace and improved maize lines. We find evidence of recovery of diversity after domestication, likely introgression from wild relatives, and evidence for stronger selection during domestication than improvement. We identify a number of genes with stronger signals of selection than those previously shown to underlie major morphological changes. Finally, through transcriptome-wide analysis of gene expression, we find evidence both consistent with removal of cis-acting variation during maize domestication and improvement and suggestive of modern breeding having increased dominance in expression while targeting highly expressed genes.

Blindness has evolved repeatedly in cave-dwelling organisms, and investigating the loss of sight in cave dwellers presents an opportunity to understand the operation of fundamental evolutionary processes, including drift, selection, mutation, and migration. The observation of blind organisms has prompted many hypotheses for their blindness, including both accumulation of neutral, loss-of-function mutations and adaptation to darkness. Here we model the evolution of blindness in caves. This model captures the interaction of three forces: (1) selection favoring alleles causing blindness, (2) immigration of sightedness alleles from a surface population, and (3) loss-of-function mutations creating blindness alleles. We investigated the dynamics of this model and determined selection-strength thresholds that result in blindness evolving in caves despite immigration of sightedness alleles from the surface. Our results indicate that strong selection is required for the evolution of blindness in cave-dwelling organisms, which is consistent with recent work suggesting a high metabolic cost of eye development.

Motivation: Accurate identification of genotypes is critical in identifying de novo mutations, linking mutations with disease, and determining mutation rates. Because de novo mutations are rare, even low levels of genotyping error can cause a large fraction of false positive de novo mutations. Biological and technical processes that adversely affect genotyping include copy-number-variation, paralogous sequences, library preparation, sequencing error, and reference-mapping biases, among others. Results: We modeled the read depth for all data as a mixture of Dirichlet-multinomial distributions, resulting in significant improvements over previously used models. In most cases the best model was comprised of two distributions. The major-component distribution is similar to a binomial distribution with low error and low reference bias. The minor-component distribution is overdispersed with higher error and reference bias. We also found that sites fitting the minor component are enriched for copy number variants and low complexity region. We expect that this approach to modeling the distribution of NGS data, will lead to improved genotyping. For example, this approach provides an expected distribution of reads that can be incorporated into a model to estimate de novo mutations using reads across a pedigree.

Leishmania, a genus of parasites transmitted to human hosts and mammalian/reptilian reservoirs by an insect vector, is the causative agent of the human disease complex leishmaniasis. The evolutionary relationships within the genus Leishmania and its origins are the source of ongoing debate, reflected in conflicting phylogenetic and biogeographic reconstructions. This study employs a recently described bioinformatics method, SISRS, to identify over 200,000 informative sites across the genome from newly sequenced and publicly available Leishmania data. This dataset is used to reconstruct the evolutionary relationships of this genus. Additionally, we constructed a large multi-gene dataset; we used this dataset to reconstruct the phylogeny and estimate divergence dates for species. We conclude that the genus Leishmania evolved at least 90-100 million years ago. Our results support the hypothesis that Leishmania clades separated prior to, and during, the breakup of Gondwana. Additionally, we confirm that reptile-infecting Leishmania are derived from mammalian forms, and that the species that infect porcupines and sloths form a clade long separated from other species. We also firmly place the guinea-pig infecting species, L. enrietti, the globally dispersed L. siamensis, and the newly identified Australia species from kangaroos as sibling species whose distribution arises from the ancient connection between Australia, Antarctica, and South America.

Leishmania, a genus of parasites transmitted to human hosts and mammalian/reptilian reservoirs by an insect vector, is the causative agent of the human disease complex leishmaniasis. The evolutionary relationships within the genus Leishmania and its origins are the source of ongoing debate, reflected in conflicting phylogenetic and biogeographic reconstructions. This study employs a recently described bioinformatics method, SISRS, to identify over 200,000 informative sites across the genome from newly sequenced and publicly available Leishmania data. This dataset is used to reconstruct the evolutionary relationships of this genus. Additionally, we constructed a large multi-gene dataset, using it to reconstruct the phylogeny and estimate divergence dates for species. We conclude that the genus Leishmania evolved at least 90-100 million years ago, supporting a modified version of the Multiple Origins hypothesis that we call the Supercontinent hypothesis. According to this scenario, separate Leishmania clades emerged prior to, and during, the breakup of Gondwana. Additionally, we confirm that reptile-infecting Leishmania are derived from mammalian forms and that the species that infect porcupines and sloths form a clade long separated from other species. Finally, we firmly place the guinea-pig infecting species, Leishmaniaenriettii, the globally dispersed Leishmaniasiamensis, and the newly identified Australian species from a kangaroo, as sibling species whose distribution arises from the ancient connection between Australia, Antarctica, and South America.

Mutation is the ultimate source of all genetic variation and is, therefore, central to evolutionary change. Previous work on Paramecium tetraurelia found an unusually low germline base-substitution mutation rate in this ciliate. Here, we tested the generality of this result among ciliates using Tetrahymena thermophila. We sequenced the genomes of 10 lines of T. thermophila that had each undergone approximately 1,000 generations of mutation accumulation (MA). We applied an existing mutation-calling pipeline and developed a new probabilistic mutation detection approach that directly models the design of an MA experiment and accommodates the noise introduced by mismapped reads. Our probabilistic mutation-calling method provides a straightforward way of estimating the number of sites at which a mutation could have been called if one was present, providing the denominator for our mutation rate calculations. From these methods, we find thatT. thermophilahas a germline base-substitution mutation rate of 7.61 × 10−12per site, per cell division, which is consistent with the low base-substitution mutation rate in P. tetraurelia. Over the course of the evolution experiment, genomic exclusion lines derived from the MA lines experienced a fitness decline that cannot be accounted for by germline base-substitution mutations alone, suggesting that other genetic or epigenetic factors must be involved. Because selection can only operate to reduce mutation rates based upon the “visible” mutational load, asexual reproduction with a transcriptionally silent germline may allow ciliates to evolve extremely low germline mutation rates.

We present the DeNovoGear software for analyzing de novo mutations from familial and somatic tissue sequencing data. DeNovoGear uses likelihood-based error modeling to reduce the false positive rate of mutation discovery in exome analysis, and fragment information to identify the parental origin of germline mutations. We used our program to create a whole-genome de novo indel callset with a 95% validation rate, producing a direct estimate of the human germline indel mutation rate.

Selection in which fitnesses vary with the changing genetic composition of the population may facilitate the maintenance of genetic diversity in a wide range of organisms. Here, a detailed theoretical investigation is made of a frequency-dependent selection model, in which fitnesses are based on pairwise interactions between the two phenotypes at a diploid, diallelic, autosomal locus with complete dominance. The allele frequency dynamics are fully delimited analytically, along with all possible shapes of the mean fitness function in terms of where it increases or decreases as a function of the current allele frequency in the population. These results in turn allow possibly the first complete characterization of the dynamical behavior by the mean fitness through time under frequency-dependent selection. Here the mean fitness (i) monotonically increases, (ii) monotonically decreases, (iii) initially increases and then decreases, or (iv) initially decreases and then increases as equilibrium is approached. We analytically derive the exact initial and fitness conditions that produce each dynamic and how often each arises. Computer simulations with random initial conditions and fitnesses reveal that the potential decline in mean fitness is not negligible; on average a net decrease occurs 20% of the time and reduces the mean fitness by >17%.

We have developed a novel method to rapidly obtain homologous genomic data for phylogenetics directly from next-generation sequencing reads without the use of a reference genome. This software, called SISRS, avoids the time consuming steps of de novo whole genome assembly, genome-genome alignment, and annotation. For simulations SISRS is able to identify large numbers of loci containing variable sites with phylogenetic signal. For genomic data from apes, SISRS identified thousands of variable sites, from which we produced an accurate phylogeny. Finally, we used SISRS to identify phylogenetic markers that we used to estimate the phylogeny of placental mammals. We recovered phylogenies from multiple datasets that were consistent with previous conflicting estimates of the relationships among mammals. SISRS is open source and freely available at https://github.com/rachelss/SISRS., 12 pages plus36 figures, 1 supplementary table, 3 supplementary figures

Mutation is the ultimate source of all genetic variation and is, therefore, central to evolutionary change. Previous work on Paramecium tetraurelia found an unusually low germline base-substitution mutation rate in this ciliate. Here, we tested the generality of this result among ciliates using Tetrahymena thermophila. We sequenced the genomes of 10 lines of T. thermophila that had each undergone approximately 1,000 generations of mutation accumulation (MA). We applied an existing mutation-calling pipeline and developed a new probabilistic mutation detection approach that directly models the design of an MA experiment and accommodates the noise introduced by mismapped reads. Our probabilistic mutation-calling method provides a straightforward way of estimating the number of sites at which a mutation could have been called if one was present, providing the denominator for our mutation rate calculations. From these methods, we find that T. thermophila has a germline base-substitution mutation rate of 7.61 × 10 − 12 per-site, per cell division, which is consistent with the low base-substitution mutation rate in P. tetraurelia. Over the course of the evolution experiment, genomic exclusion lines derived from the MA lines experienced a fitness decline that cannot be accounted for by germline base-substitution mutations alone, suggesting that other genetic or epigenetic factors must be involved. Because selection can only operate to reduce mutation rates based upon the "visible" mutational load, asexual reproduction with a transcriptionally silent germline may allow ciliates to evolve extremely low germline mutation rates.