Testing the applicability of environmental DNA metabarcoding to landscape genetics.

Landscape genetics is a field dealing with local genetic differences and contributes to strategic conservation planning. Recently, environmental DNA (eDNA) metabarcoding has proven useful not only for detecting species but also for assessing genetic diversity and genetic structure on a large scale such as in phylogeography. However, it remains unclear whether eDNA analysis also has sufficient power to perform the landscape genetics, which focuses on a local scale. To reveal the applicability of eDNA to landscape genetics, we conducted an eDNA metabarcoding analysis of the mitochondrial DNA D-loop region of the fluvial sculpin Cottus nozawae in the upper Sorachi River in Japan and compared the results with inferences based on traditional tissue-based approaches by the same D-loop region and genome-wide SNP data. As a result, the spatial distribution of haplotypes was generally consistent between the eDNA- and tissue-based approaches. In addition, the genetic differentiation statistics calculated using eDNA and tissue samples were highly correlated when comparing both in the D-loop region. The removal of low-frequency reads or the conversion to semi-quantitative rankings of eDNA data did not alter the correlation of genetic diversity and differentiation statistics with tissue-based approaches much. Finally, we confirmed that analyses using eDNA data can reveal patterns such as isolation-by-distance shown in previous studies on this species, indicating the applicability of eDNA to basic landscape genetics. Even though some limitations remain, eDNA may have great potential for conducting basic landscape genetics.

Deep Learning and Likelihood Approaches for Viral Phylogeography Converge on the Same Answers Whether the Inference Model Is Right or Wrong.

Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences about the phylodynamics and history of viral transmission. However, these methods are often computationally expensive, which limits the complexity and realism of phylodynamic models and makes them ill-suited for informing policy decisions in real-time during rapidly developing outbreaks. Likelihood-free methods using deep learning are pushing the boundaries of inference beyond these constraints. In this paper, we extend, compare, and contrast a recently developed deep learning method for likelihood-free inference from trees. We trained multiple deep neural networks using phylogenies from simulated outbreaks that spread among 5 locations and found they achieve close to the same levels of accuracy as Bayesian inference under the true simulation model. We compared robustness to model misspecification of a trained neural network to that of a Bayesian method. We found that both models had comparable performance, converging on similar biases. We also implemented a method of uncertainty quantification called conformalized quantile regression that we demonstrate has similar patterns of sensitivity to model misspecification as Bayesian highest posterior density (HPD) and greatly overlap with HPDs, but have lower precision (more conservative). Finally, we trained and tested a neural network against phylogeographic data from a recent study of the SARS-Cov-2 pandemic in Europe and obtained similar estimates of region-specific epidemiological parameters and the location of the common ancestor in Europe. Along with being as accurate and robust as likelihood-based methods, our trained neural networks are on average over 3 orders of magnitude faster after training. Our results support the notion that neural networks can be trained with simulated data to accurately mimic the good and bad statistical properties of the likelihood functions of generative phylogenetic models.

Detection of Ghost Introgression Requires Exploiting Topological and Branch Length Information.

In recent years, the study of hybridization and introgression has made significant progress, with ghost introgression-the transfer of genetic material from extinct or unsampled lineages to extant species-emerging as a key area for research. Accurately identifying ghost introgression, however, presents a challenge. To address this issue, we focused on simple cases involving 3 species with a known phylogenetic tree. Using mathematical analyses and simulations, we evaluated the performance of popular phylogenetic methods, including HyDe and PhyloNet/MPL, and the full-likelihood method, Bayesian Phylogenetics and Phylogeography (BPP), in detecting ghost introgression. Our findings suggest that heuristic approaches relying on site-pattern counts or gene-tree topologies struggle to differentiate ghost introgression from introgression between sampled non-sister species, frequently leading to incorrect identification of donor and recipient species. The full-likelihood method BPP uses multilocus sequence alignments directly-hence taking into account both gene-tree topologies and branch lengths, by contrast, is capable of detecting ghost introgression in phylogenomic datasets. We analyzed a real-world phylogenomic dataset of 14 species of Jaltomata (Solanaceae) to showcase the potential of full-likelihood methods for accurate inference of introgression.

Dispersal direction of Malaysian Fasciola gigantica from neighboring southeast Asian countries inferred using mitochondrial DNA analysis.

Fasciola gigantica and hybrid Fasciola flukes, responsible for the disease fasciolosis, are found in Southeast Asian countries. In the present study, we performed molecular species identification of Fasciola flukes distributed in Terengganu, Malaysia using multiplex PCR for phosphoenolpyruvate carboxykinase (pepck) and PCR-restriction fragment length polymorphism (RFLP) for DNA polymerase delta (pold). Simultaneously, phylogenetic analysis based on mitochondrial NADH dehydrogenase subunit 1 (nad1) was performed for the first time on Malaysian Fasciola flukes to infer the dispersal direction among neighboring countries. A total of 40 flukes used in this study were identified as F. gigantica. Eight nad1 haplotypes were identified in the F. gigantica population of Terengganu. Median-joining network analysis revealed that the Malaysian population was related to those obtained from bordering countries such as Thailand and Indonesia. However, genetic differentiation was detected using population genetics analyses. Nevertheless, the nucleotide diversity (π) value suggested that F. gigantica with the predominant haplotypes was introduced into Malaysia from Thailand and Indonesia. The dispersal direction suggested by population genetics in the present study may not be fully reliable since Fasciola flukes were collected from a single location in one state of Malaysia. Further studies analyzing more samples from many locations are required to validate the dispersal direction proposed herein.

Accounting for spatial sampling patterns in Bayesian phylogeography.

Statistical phylogeography provides useful tools to characterize and quantify the spread of organisms during the course of evolution. Analyzing georeferenced genetic data often relies on the assumption that samples are preferentially collected in densely populated areas of the habitat. Deviation from this assumption negatively impacts the inference of the spatial and demographic dynamics. This issue is pervasive in phylogeography. It affects analyses that approximate the habitat as a set of discrete demes as well as those that treat it as a continuum. The present study introduces a Bayesian modeling approach that explicitly accommodates for spatial sampling strategies. An original inference technique, based on recent advances in statistical computing, is then described that is most suited to modeling data where sequences are preferentially collected at certain locations, independently of the outcome of the evolutionary process. The analysis of georeferenced genetic sequences from the West Nile virus in North America along with simulated data shows how assumptions about spatial sampling may impact our understanding of the forces shaping biodiversity across time and space.

Phylogeography and phylogeny of Rhinoviruses collected from Severe Acute Respiratory Infection (SARI) cases over successive epidemic periods in Tunisia.

Rhinoviruses (RV) are a major cause of Severe Acute Respiratory Infection (SARI) in children, with high genotypic diversity in different regions. However, RV type diversity remains unknown in several regions of the world. In this study, the genetic variability of the frequently circulating RV types in Northern Tunisia was investigated, using phylogenetic and phylogeographic analyses with a specific focus on the most frequent RV types: RV-A101 and RV-C45. This study concerned 13 RV types frequently circulating in Northern Tunisia. They were obtained from respiratory samples collected in 271 pediatric SARI cases, between September 2015 and November 2017. A total of 37 RV VP4-VP2 sequences, selected among a total of 49 generated sequences, was compared to 359 sequences from different regions of the world. Evolutionary analysis of RV-A101 and RV-C45 showed high genetic relationship between different Tunisian strains and Malaysian strains. RV-A101 and C45 progenitor viruses' dates were estimated in 1981 and 1995, respectively. Since the early 2000s, the two types had a wide spread throughout the world. Phylogenetic analyses of other frequently circulating strains showed significant homology of Tunisian strains from the same epidemic period, in contrast with earlier strains. The genetic relatedness of RV-A101 and RV-C45 might result from an introduction of viruses from different clades followed by local dissemination rather than a local persistence of an endemic clades along seasons. International traffic may play a key role in the spread of RV-A101, RV-C45, and other RVs.

Population genetic structure of European wildcats inhabiting the area between the Dinaric Alps and the Scardo-Pindic mountains.

Habitat fragmentation and loss have contributed significantly to the demographic decline of European wildcat populations and hybridization with domestic cats poses a threat to the loss of genetic purity of the species. In this study we used microsatellite markers to analyse genetic variation and structure of the wildcat populations from the area between the Dinaric Alps and the Scardo-Pindic mountains in Slovenia, Croatia, Serbia and North Macedonia. We also investigated hybridisation between populations of wildcats and domestic cats in the area. One hundred and thirteen samples from free-leaving European wildcats and thirty-two samples from domestic cats were analysed. Allelic richness across populations ranged from 3.61 to 3.98. The observed Ho values ranged between 0.57 and 0.71. The global FST value for the four populations was 0.080 (95% CI 0.056-0.109) and differed significantly from zero (P < 0.001). The highest FST value was observed between the populations North Macedonia and Slovenia and the lowest between Slovenia and Croatia. We also found a signal for the existence of isolation by distance between populations. Our results showed that wildcats are divided in two genetic clusters largely consistent with a geographic division into a genetically diverse northern group (Slovenia, Croatia) and genetically eroded south-eastern group (Serbia, N. Macedonia). Hybridisation rate between wildcats and domestic cats varied between 13% and 52% across the regions.

An Epidemiological Analysis of SARS-CoV-2 Genomic Sequences from Different Regions of India.

The number of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) cases is increasing in India. This study looks upon the geographic distribution of the virus clades and variants circulating in different parts of India between January and August 2020. The NPS/OPS from representative positive cases from different states and union territories in India were collected every month through the VRDLs in the country and analyzed using next-generation sequencing. Epidemiological analysis of the 689 SARS-CoV-2 clinical samples revealed GH and GR to be the predominant clades circulating in different states in India. The northern part of India largely reported the 'GH' clade, whereas the southern part reported the 'GR', with a few exceptions. These sequences also revealed the presence of single independent mutations-E484Q and N440K-from Maharashtra (first observed in March 2020) and Southern Indian States (first observed in May 2020), respectively. Furthermore, this study indicates that the SARS-CoV-2 variant (VOC, VUI, variant of high consequence and double mutant) was not observed during the early phase of virus transmission (January-August). This increased number of variations observed within a short timeframe across the globe suggests virus evolution, which can be a step towards enhanced host adaptation.

Population structure and gene flow of the syntopic turtles Emys and Mauremys from coastal and inland regions of Anatolia (Turkey): results from mitochondrial and microsatellite data.

Revealing the genetic basis of the existence of different species living together in different geographic regions provides clarification of this phylogeographic differentiation. In this study, we investigated the population genetics and evaluated the level of genetic variation of inland and coastal populations of Mauremys and Emys in Turkey. Tissue samples of 196 terrapins were studied which were collected from syntopic coastal (Gölbent-Söke/Aydin; M. rivulata and E. orbicularis) and inland populations (Bahçesaray/Aksaray; M. caspica and E. orbicularis). DNA was isolated using the InnuPREP DNA Mini Kit. Mitochondrial DNA sequences and allelic variation at 13 microsatellite loci for Mauremys and 12 microsatellite loci for Emys were examined.  Three haplotypes were found for Emys orbicularis (Im, Ip and Iw) collected from the coastal region and two haplotypes for Emys orbicularis (Ig and Im) collected from inland. Two haplotypes were identified for M. caspica (Cmt8 and Cmt9) and three haplotypes were identified for M. rivulata (Rmt3, Rmt24 and Rmt26). Using microsatellites and the software STRUCTURE the most probable value for K was revealed as two 2 for both species. The FST value between M. rivulata and M. caspica was 0.39, and between the coastal and inland populations of E. orbicularis 0.09. It can be concluded that Emys populations tend to evolve by somehow preserving the allelic richness they have and Mauremys populations continue to differentiate so that new species emerge in the evolutionary process to reach the ideal allelic structure.

The origin of island populations of the African malaria mosquito, Anopheles coluzzii.

Anopheles coluzzii is a major malaria vector throughout its distribution in west-central Africa. Here we present a whole-genome study of 142 specimens from nine countries in continental Africa and three islands in the Gulf of Guinea. This sample set covers a large part of this species' geographic range. Our population genomic analyses included a description of the structure of mainland populations, island populations, and connectivity between them. Three genetic clusters are identified among mainland populations and genetic distances (FST) fits an isolation-by-distance model. Genomic analyses are applied to estimate the demographic history and ancestry for each island. Taken together with the unique biogeography and history of human occupation for each island, they present a coherent explanation underlying levels of genetic isolation between mainland and island populations. We discuss the relationship of our findings to the suitability of São Tomé and Príncipe islands as candidate sites for potential field trials of genetic-based malaria control strategies.

Potential mammalian species for investigating the past connections between Amazonia and the Atlantic Forest.

Much evidence suggests that Amazonia and the Atlantic Forest were connected through at least three dispersion routes in the past: the Eastern route, the central route, and the Western route. However, few studies have assessed the use of these routes based on multiple species. Here we present a compilation of mammal species that potentially have dispersed between the two forest regions and which may serve to investigate these connections. We evaluate the present-day geographic distributions of mammals occurring in both Amazonia and the Atlantic Forest and the likely connective routes between these forests. We classified the species per habitat occupancy (strict forest specialists, species that prefer forest habitat, or generalists) and compiled the genetic data available for each species. We found 127 mammalian species presently occurring in both Amazonia and the Atlantic Forest for which, substantial genetic data was available. Hence, highlighting their potential for phylogeographic studies investigating the past connections between the two forests. Differently from what was previously proposed, the present-day geographic distribution of mammal species found in both Amazonia and the Atlantic Forest points to more species in the eastern portion of the dry diagonal (and adjoining forested habitats). The Central route was associated with the second most species. Although it remains to be seen how this present-day geography reflects the paleo dispersal routes, our results show the potential of using mammal species to investigate and bring new insights about the past connections between Amazonia and the Atlantic Forest.

Bayesian Phylogeographic Analysis Incorporating Predictors and Individual Travel Histories in BEAST.

Advances in sequencing technologies have tremendously reduced the time and costs associated with sequence generation, making genomic data an important asset for routine public health practices. Within this context, phylogenetic and phylogeographic inference has become a popular method to study disease transmission. In a Bayesian context, these approaches have the benefit of accommodating phylogenetic uncertainty, and popular implementations provide the possibility to parameterize the transition rates between locations as a function of epidemiological and ecological data to reconstruct spatial spread while simultaneously identifying the main factors impacting the spatial spread dynamics. Recent developments enable researchers to make use of travel history data of infected individuals in the reconstruction of pathogen spread, offering increased inference accuracy and mitigating sampling bias. Here, we describe a detailed workflow to reconstruct the spatial spread of a pathogen through Bayesian phylogeographic analysis in discrete space using these novel approaches, implemented in BEAST. The individual protocols focus on how to incorporate molecular data, covariates of spread, and individual travel history data into the analysis. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Creating a SARS-CoV-2 MSA using sequences from GISAID Basic Protocol 2: Setting up a discrete trait phylogeographic reconstruction in BEAUti Basic Protocol 3: Phylogeographic reconstruction incorporating travel history information Basic Protocol 4: Visualizing ancestral spatial trajectories for specific taxa.

Phylogeography and morphological evolution of Pseudechiniscus (Heterotardigrada: Echiniscidae).

Tardigrades constitute a micrometazoan phylum usually considered as taxonomically challenging and therefore difficult for biogeographic analyses. The genus Pseudechiniscus, the second most speciose member of the family Echiniscidae, is commonly regarded as a particularly difficult taxon for studying due to its rarity and homogenous sculpturing of the dorsal plates. Recently, wide geographic ranges for some representatives of this genus and a new hypothesis on the subgeneric classification have been suggested. In order to test these hypotheses, we sequenced 65 Pseudechiniscus populations extracted from samples collected in 19 countries distributed on 5 continents, representing the Neotropical, Afrotropical, Holarctic, and Oriental realms. The deep subdivision of the genus into the cosmopolitan suillus-facettalis clade and the mostly tropical-Gondwanan novaezeelandiae clade is demonstrated. Meridioniscus subgen. nov. is erected to accommodate the species belonging to the novaezeelandiae lineage characterised by dactyloid cephalic papillae that are typical for the great majority of echiniscids (in contrast to pseudohemispherical papillae in the suillus-facettalis clade, corresponding to the subgenus Pseudechiniscus). Moreover, the evolution of morphological traits (striae between dorsal pillars, projections on the pseudosegmental plate IV', ventral sculpturing pattern) crucial in the Pseudechiniscus taxonomy is reconstructed. Furthermore, broad distributions are emphasised as characteristic of some taxa. Finally, the Malay Archipelago and Indochina are argued to be the place of origin and extensive radiation of Pseudechiniscus.

Genetic evidence for the association between COVID-19 epidemic severity and timing of non-pharmaceutical interventions.

Unprecedented public health interventions including travel restrictions and national lockdowns have been implemented to stem the COVID-19 epidemic, but the effectiveness of non-pharmaceutical interventions is still debated. We carried out a phylogenetic analysis of more than 29,000 publicly available whole genome SARS-CoV-2 sequences from 57 locations to estimate the time that the epidemic originated in different places. These estimates were examined in relation to the dates of the most stringent interventions in each location as well as to the number of cumulative COVID-19 deaths and phylodynamic estimates of epidemic size. Here we report that the time elapsed between epidemic origin and maximum intervention is associated with different measures of epidemic severity and explains 11% of the variance in reported deaths one month after the most stringent intervention. Locations where strong non-pharmaceutical interventions were implemented earlier experienced much less severe COVID-19 morbidity and mortality during the period of study.

Reconstructing unseen transmission events to infer dengue dynamics from viral sequences.

For most pathogens, transmission is driven by interactions between the behaviours of infectious individuals, the behaviours of the wider population, the local environment, and immunity. Phylogeographic approaches are currently unable to disentangle the relative effects of these competing factors. We develop a spatiotemporally structured phylogenetic framework that addresses these limitations by considering individual transmission events, reconstructed across spatial scales. We apply it to geocoded dengue virus sequences from Thailand (N = 726 over 18 years). We find infected individuals spend 96% of their time in their home community compared to 76% for the susceptible population (mainly children) and 42% for adults. Dynamic pockets of local immunity make transmission more likely in places with high heterotypic immunity and less likely where high homotypic immunity exists. Age-dependent mixing of individuals and vector distributions are not important in determining spread. This approach provides previously unknown insights into one of the most complex disease systems known and will be applicable to other pathogens.

Phylogeographic analysis of Pseudogymnoascus destructans partitivirus-pa explains the spread dynamics of white-nose syndrome in North America.

Understanding the dynamics of white-nose syndrome spread in time and space is an important component for the disease epidemiology and control. We reported earlier that a novel partitivirus, Pseudogymnoascus destructans partitivirus-pa, had infected the North American isolates of Pseudogymnoascus destructans, the fungal pathogen that causes white-nose syndrome in bats. We showed that the diversity of the viral coat protein sequences is correlated to their geographical origin. Here we hypothesize that the geographical adaptation of the virus could be used as a proxy to characterize the spread of white-nose syndrome. We used over 100 virus isolates from diverse locations in North America and applied the phylogeographic analysis tool BEAST to characterize the spread of the disease. The strict clock phylogeographic analysis under the coalescent model in BEAST showed a patchy spread pattern of white-nose syndrome driven from a few source locations including Connecticut, New York, West Virginia, and Kentucky. The source states had significant support in the maximum clade credibility tree and Bayesian stochastic search variable selection analysis. Although the geographic origin of the virus is not definite, it is likely the virus infected the fungus prior to the spread of white-nose syndrome in North America. We also inferred from the BEAST analysis that the recent long-distance spread of the fungus to Washington had its root in Kentucky, likely from the Mammoth cave area and most probably mediated by a human. The time to the most recent common ancestor of the virus is estimated somewhere between the late 1990s to early 2000s. We found the mean substitution rate of 2 X 10-3 substitutions per site per year for the virus which is higher than expected given the persistent lifestyle of the virus, and the stamping-machine mode of replication. Our approach of using the virus as a proxy to understand the spread of white-nose syndrome could be an important tool for the study and management of other infectious diseases.

Relax, Keep Walking - A Practical Guide to Continuous Phylogeographic Inference with BEAST.

Spatially explicit phylogeographic analyses can be performed with an inference framework that employs relaxed random walks to reconstruct phylogenetic dispersal histories in continuous space. This core model was first implemented 10 years ago and has opened up new opportunities in the field of phylodynamics, allowing researchers to map and analyze the spatial dissemination of rapidly evolving pathogens. We here provide a detailed and step-by-step guide on how to set up, run, and interpret continuous phylogeographic analyses using the programs BEAUti, BEAST, Tracer, and TreeAnnotator.

Distinct late Pleistocene subtropical-tropical divergence revealed by fifteen low-copy nuclear genes in a dominant species in South-East China.

In East Asia, genetic divergence is usually considered to be correlated to different floristic regions, however, subtropical-tropical divergence is largely ignored, compared to widely explored temperate-subtropical divergence. Lindera aggregata (Lauraceae), a dominant species in South-East China was selected to address this issue. Fifteen low-copy nuclear genes (LCGs) and four chloroplast DNA (cpDNA) fragments were used to detect its evolutionary history. In LCGs, STRUCTURE and dated Bayesian phylogeny analyses detect distinct subtropical-tropical divergence since late Pleistocene. Approximate Bayesian calculation (ABC) further supports the distinct subtropical-tropical divergence, and close related Taiwan and South China populations are diverged at the last interglacial. Isolation by distance, isolation by environment and isolation by resistance analyses suggest the current climatic difference rather than geographical distance contributes to the genetic differentiation. Principle component analysis shows populations of tropical cluster occur in warmer area with higher precipitation. Ancestral area reconstruction based on Bayesian phylogeny indicates that ancestral L. aggregata populations are distributed in tropical region. In cpDNA, although unique haplotypes are found in tropical region, distinct subtropical-tropical divergence is absent. In conclusion, distinct late Pleistocene subtropical-tropical divergence of L. aggregata is triggered by climate. It is likely that L. aggregata is originated in Southwest-South China and experienced hierarchical dispersal from south to north. The South China Sea land bridge has dual role in connecting or isolating Taiwan and mainland populations since the last glaciation.

Sampling bias and model choice in continuous phylogeography: Getting lost on a random walk.

Phylogeographic inference allows reconstruction of past geographical spread of pathogens or living organisms by integrating genetic and geographic data. A popular model in continuous phylogeography-with location data provided in the form of latitude and longitude coordinates-describes spread as a Brownian motion (Brownian Motion Phylogeography, BMP) in continuous space and time, akin to similar models of continuous trait evolution. Here, we show that reconstructions using this model can be strongly affected by sampling biases, such as the lack of sampling from certain areas. As an attempt to reduce the effects of sampling bias on BMP, we consider the addition of sequence-free samples from under-sampled areas. While this approach alleviates the effects of sampling bias, in most scenarios this will not be a viable option due to the need for prior knowledge of an outbreak's spatial distribution. We therefore consider an alternative model, the spatial Λ-Fleming-Viot process (ΛFV), which has recently gained popularity in population genetics. Despite the ΛFV's robustness to sampling biases, we find that the different assumptions of the ΛFV and BMP models result in different applicabilities, with the ΛFV being more appropriate for scenarios of endemic spread, and BMP being more appropriate for recent outbreaks or colonizations.

A Southeast Asian origin for present-day non-African human Y chromosomes.

The genomes of present-day humans outside Africa originated almost entirely from a single out-migration ~ 50,000-70,000 years ago, followed by mixture with Neanderthals contributing ~ 2% to all non-Africans. However, the details of this initial migration remain poorly understood because no ancient DNA analyses are available from this key time period, and interpretation of present-day autosomal data is complicated due to subsequent population movements/reshaping. One locus, however, does retain male-specific information from this early period: the Y chromosome, where a detailed calibrated phylogeny has been constructed. Three present-day Y lineages were carried by the initial migration: the rare haplogroup D, the moderately rare C, and the very common FT lineage which now dominates most non-African populations. Here, we show that phylogenetic analyses of haplogroup C, D and FT sequences, including very rare deep-rooting lineages, together with phylogeographic analyses of ancient and present-day non-African Y chromosomes, all point to East/Southeast Asia as the origin 50,000-55,000 years ago of all known surviving non-African male lineages (apart from recent migrants). This observation contrasts with the expectation of a West Eurasian origin predicted by a simple model of expansion from a source near Africa, and can be interpreted as resulting from extensive genetic drift in the initial population or replacement of early western Y lineages from the east, thus informing and constraining models of the initial expansion.