Bifidobacteria define gut microbiome profiles of golden lion tamarin (Leontopithecus rosalia) and marmoset (Callithrix sp.) metagenomic shotgun pools.

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 gut metagenomic pools from 114 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 for 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 expand baseline gut microbiome data for callitrichids to allow for the development of new tools to improve their management and conservation.

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations.

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Federated learning and Indigenous genomic data sovereignty.

Indigenous peoples are under-represented in genomic datasets, which can lead to limited accuracy and utility of machine learning models in precision health. While open data sharing undermines rights of Indigenous communities to govern data decisions, federated learning may facilitate secure and community-consented data sharing.

Genie: an interactive real-time simulation for teaching genetic drift.

Neutral evolution is a fundamental concept in evolutionary biology but teaching this and other non-adaptive concepts is especially challenging. Here we present Genie, a browser-based educational tool that demonstrates population-genetic concepts such as genetic drift, population isolation, gene flow, and genetic mutation. Because it does not need to be downloaded and installed, Genie can scale to large groups of students and is useful for both in-person and online instruction. Genie was used to teach genetic drift to Evolution students at Arizona State University during Spring 2016 and Spring 2017. The effectiveness of Genie to teach key genetic drift concepts and misconceptions was assessed with the Genetic Drift Inventory developed by Price et al. (CBE Life Sci Educ 13(1):65-75, 2014). Overall, Genie performed comparably to that of traditional static methods across all evaluated classes. We have empirically demonstrated that Genie can be successfully integrated with traditional instruction to reduce misconceptions about genetic drift.

The gut microbiome of exudivorous marmosets in the wild and captivity.

Mammalian captive dietary specialists like folivores are prone to gastrointestinal distress and primate dietary specialists suffer the greatest gut microbiome diversity losses in captivity compared to the wild. Marmosets represent another group of dietary specialists, exudivores that eat plant exudates, but whose microbiome remains relatively less studied. The common occurrence of gastrointestinal distress in captive marmosets prompted us to study the Callithrix gut microbiome composition and predictive function through bacterial 16S ribosomal RNA V4 region sequencing. We sampled 59 wild and captive Callithrix across four species and their hybrids. Host environment had a stronger effect on the gut microbiome than host taxon. Wild Callithrix gut microbiomes were enriched for Bifidobacterium, which process host-indigestible carbohydrates. Captive marmoset guts were enriched for Enterobacteriaceae, a family containing pathogenic bacteria. While gut microbiome function was similar across marmosets, Enterobacteriaceae seem to carry out most functional activities in captive host guts. More diverse bacterial taxa seem to perform gut functions in wild marmosets, with Bifidobacterium being important for carbohydrate metabolism. Captive marmosets showed gut microbiome composition aspects seen in human gastrointestinal diseases. Thus, captivity may perturb the exudivore gut microbiome, which raises implications for captive exudivore welfare and calls for husbandry modifications.

The first steps toward a global pandemic: Reconstructing the demographic history of parasite host switches in its native range.

Host 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). Both switched to the western honey bee (Apis mellifera) after being 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. Our findings suggest that while reproductive isolation may facilitate the fixation of traits beneficial for exploiting the new host, ongoing genetic exchange may allow genetic amelioration of inbreeding effects.

A Probabilistic Model for Indel Evolution: Differentiating Insertions from Deletions.

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.

Genomic skimming and nanopore sequencing uncover cryptic hybridization in one of world's most threatened primates.

The Brazilian buffy-tufted-ear marmoset (Callithrix aurita), one of the world's most endangered primates, is threatened by anthropogenic hybridization with exotic, invasive marmoset species. As there are few genetic data available for C. aurita, we developed a PCR-free protocol with minimal technical requirements to rapidly generate genomic data with genomic skimming and portable nanopore sequencing. With this direct DNA sequencing approach, we successfully determined the complete mitogenome of a marmoset that we initially identified as C. aurita. The obtained nanopore-assembled sequence was highly concordant with a Sanger sequenced version of the same mitogenome. Phylogenetic analyses unexpectedly revealed that our specimen was a cryptic hybrid, with a C. aurita phenotype and C. penicillata mitogenome lineage. We also used publicly available mitogenome data to determine diversity estimates for C. aurita and three other marmoset species. Mitogenomics holds great potential to address deficiencies in genomic data for endangered, non-model species such as C. aurita. However, we discuss why mitogenomic approaches should be used in conjunction with other data for marmoset species identification. Finally, we discuss the utility and implications of our results and genomic skimming/nanopore approach for conservation and evolutionary studies of C. aurita and other marmosets.

Mitogenomic phylogeny of Callithrix with special focus on human transferred taxa.

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.

A community-maintained standard library of population genetic models.

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. Stdpopsim is 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 how stdpopsim can be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource.

A phylogenomic approach reveals a low somatic mutation rate in a long-lived plant.

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.

The role of gene flow in rapid and repeated evolution of cave-related traits in Mexican tetra, Astyanax mexicanus.

Understanding the molecular basis of repeatedly evolved phenotypes can yield key insights into the evolutionary process. Quantifying gene flow between populations is especially important in interpreting mechanisms of repeated phenotypic evolution, and genomic analyses have revealed that admixture occurs more frequently between diverging lineages than previously thought. In this study, we resequenced 47 whole genomes of the Mexican tetra from three cave populations, two surface populations and outgroup samples. We confirmed that cave populations are polyphyletic and two Astyanax mexicanus lineages are present in our data set. The two lineages likely diverged much more recently than previous mitochondrial estimates of 5-7 mya. Divergence of cave populations from their phylogenetically closest surface population likely occurred between ~161 and 191 k generations ago. The favoured demographic model for most population pairs accounts for divergence with secondary contact and heterogeneous gene flow across the genome, and we rigorously identified gene flow among all lineages sampled. Therefore, the evolution of cave-related traits occurred more rapidly than previously thought, and trogolomorphic traits are maintained despite gene flow with surface populations. The recency of these estimated divergence events suggests that selection may drive the evolution of cave-derived traits, as opposed to disuse and drift. Finally, we show that a key trogolomorphic phenotype QTL is enriched for genomic regions with low divergence between caves, suggesting that regions important for cave phenotypes may be transferred between caves via gene flow. Our study shows that gene flow must be considered in studies of independent, repeated trait evolution.

accuMUlate: a mutation caller designed for mutation accumulation experiments.

Summary: Mutation accumulation (MA) is the most widely used method for directly studying the effects of mutation. 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. Here we describe accuMUlate, a probabilistic mutation caller that reflects the design of a typical MA experiment while being flexible enough to accommodate properties unique to any particular experiment. Availability and implementation accuMUlate is available from https://github.com/dwinter/accuMUlate. Supplementary information: Supplementary data are available at Bioinformatics online.

The impact of self-incompatibility systems on the prevention of biparental inbreeding.

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.

Experimental evolution reveals an effective avenue to release catabolite repression via mutations in XylR.

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.

SpartaABC: a web server to simulate sequences with indel parameters inferred using an approximate Bayesian computation algorithm.

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.

Inferring Rates and Length-Distributions of Indels Using Approximate Bayesian Computation.

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.

Estimating error models for whole genome sequencing using mixtures of Dirichlet-multinomial distributions.

MOTIVATION: Accurate identification of genotypes is an essential part of the analysis of genomic data, including in identification of sequence polymorphisms, linking mutations with disease and determining mutation rates. 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 regions, which can produce erroneous genotype calls. By removing sites that do not fit the major component, we can improve the accuracy of genotype calls. AVAILABILITY AND IMPLEMENTATION: Methods and data files are available at https://github.com/CartwrightLab/WuEtAl2017/ (doi:10.5281/zenodo.256858). CONTACT: cartwright@asu.edu. SUPPLEMENTARY INFORMATION: Supplementary data is available at Bioinformatics online.

The importance of selection in the evolution of blindness in cavefish.

BACKGROUND: Blindness has evolved repeatedly in cave-dwelling organisms, and many hypotheses have been proposed to explain this observation, including both accumulation of neutral loss-of-function mutations and adaptation to darkness. 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. RESULTS: 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) 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. We estimate that the selection coefficient for blindness would need to be at least 0.005 (and maybe as high as 0.5) for blindness to evolve in the model cave-organism, Astyanax mexicanus. CONCLUSIONS: 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.

Low Base-Substitution Mutation Rate in the Germline Genome of the Ciliate Tetrahymena thermophil.

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.