Population Genetic Approaches Research Articles

Differentiated historical demography and ecological niche forming present distribution and genetic structure in coexisting two salamanders (Amphibia, Urodela, Hynobiidae) in a small island, Japan.

BackgroundThe climatic oscillations in the Quaternary period considerably shaped the distribution and population genetic structure of organisms. Studies on the historical dynamics of distribution and demography not only reflect the current geographic distribution but also allow us to understand the adaption and genetic differentiation of species. However, the process and factors affecting the present distribution and genetic structure of many taxa are still poorly understood, especially for endemic organisms to small islands.MethodsHere, we integrated population genetic and ecological niche modelling approaches to investigate the historical distribution and demographic dynamics of two co-existing salamanders on Tsushima Island, Japan: the true H. tsuensis (Group A), and Hynobius sp. (Group B). We also examined the hypothesis on the equivalency and similarity of niches of these groups by identity and background tests for ecological niche space.ResultsOur result showed that Group A is considered to have undergone a recent population expansion after the Last Glacial Maximum while it is unlikely to have occurred in Group B. The highest suitability was predicted for Group A in southern Tsushima Island, whereas the northern part of Tsushima Island was the potential distribution of Group B. The results also suggested a restricted range of both salamanders during the Last Interglacial and Last Glacial Maximum, and recent expansion in Mid-Holocene. The genetic landscape-shape interpolation analysis and historical suitable area of ecological niche modelling were consistent, and suggested refugia used during glacial ages in southern part for Group A, and in northern part of Tsushima Island for Group B. Additionally, we found evidence of nonequivalence for the ecological niche of the two groups of the salamanders, although our test could not show either niche divergence or conservatism based on the background tests. The environmental predictors affecting the potential distribution of each group also showed distinctiveness, leading to differences in selecting suitable areas. Finally, the combination of population genetics and ecological modeling has revealed the differential demographic/historical response between coexisting two salamanders on a small island.

A dynamic ancestral graph model and GPU-based simulation of a community based on metagenomic sampling.

In this paper, we present an ancestral graph model of the evolution of a guild in an ecological community. The model is based on a metagenomic sampling design in that a random sample is taken at the community, as opposed the taxon, level and species are discovered by genetic sequencing. The specific implementation of the model envisions an ecological guild that was founded by colonization at some point in the past that then potentially undergoes diversification by natural selection. Within the graph, species emerge and evolve through the diversification process and their densities in the graph are dynamic and governed by both ecological drift and random genetic drift, as well as differential viability. We employ the 3% sequence divergence rule at a marker locus to identify operational taxonomic units. We then explore approaches to see whether there are indirect signals of the diversification process, including population genetic and ecological approaches. In terms of population genetics, we study the joint site frequency spectrum of OTUs, as well its associated statistics. In terms of ecology, we study the species (or OTU) abundance distribution. For both, we observe deviations from neutrality, which indicates that there may be signals of diversifying selection in metagenomic studies under certain conditions. The model is available as a GPU-based computer program in C/C++ and using OpenCL, with the long-term goal of adding functionality iteratively to model large-scale eco-evolutionary processes for metagenomic data.

A new linear combination method of haplogroup distribution central vectors to model population admixtures

We introduce a novel population genetic approach suitable to model the origin and relationships of populations, using new computation methods analyzing Hg frequency distributions. Hgs were selected into groups which show correlated frequencies in subsets of populations, based on the assumption that correlations were established in ancient separation, migration and admixture processes. Populations are defined with this universal Hg database, then using unsupervised artificial intelligence, central vectors (CVs) are determined from local condensations of the Hg-distribution vectors in the multidimensional point system. Populations are clustered according to their proximity to CVs. We show that CVs can be regarded as approximations of ancient populations and real populations can be modeled as weighted linear combinations of the CVs using a new linear combination algorithm based on a gradient search for the weights. The efficacy of the method is demonstrated by comparing Copper Age populations of the Carpathian Basin to Middle Age ones and modern Hungarians. Our analysis reveals significant population continuity since the Middle Ages, and the presence of a substrate component since the Copper Age.

Population genetics of polymorphism and divergence in rapidly evolving populations.

In rapidly evolving populations, numerous beneficial and deleterious mutations can arise and segregate within a population at the same time. In this regime, evolutionary dynamics cannot be analyzed using traditional population genetic approaches that assume that sites evolve independently. Instead, the dynamics of many loci must be analyzed simultaneously. Recent work has made progress by first analyzing the fitness variation within a population, and then studying how individual lineages interact with this traveling fitness wave. However, these "traveling wave" models have previously been restricted to extreme cases where selection on individual mutations is either much faster or much slower than the typical coalescent timescale Tc. In this work, we show how the traveling wave framework can be extended to intermediate regimes in which the scaled fitness effects of mutations (Tcs) are neither large nor small compared to one. This enables us to describe the dynamics of populations subject to a wide range of fitness effects, and in particular, in cases where it is not immediately clear which mutations are most important in shaping the dynamics and statistics of genetic diversity. We use this approach to derive new expressions for the fixation probabilities and site frequency spectra of mutations as a function of their scaled fitness effects, along with related results for the coalescent timescale Tc and the rate of adaptation or Muller's ratchet. We find that competition between linked mutations can have a dramatic impact on the proportions of neutral and selected polymorphisms, which is not simply summarized by the scaled selection coefficient Tcs. We conclude by discussing the implications of these results for population genetic inferences.

Role of Sexual Reproduction in the Evolution of the Wheat Stripe Rust Fungus Races in China.

Experimental and population genetic approaches have reshaped our view of how fungal pathogens reproduce, with consequences for our understanding of fungal invasions. Puccinia striiformis f. sp. tritici, the causal agent of stripe rust, poses a severe threat to wheat production worldwide. The sexual stage of P. striiformis f. sp. tritici was discovered >10 years ago, but how it affects the evolution of the pathogen, especially the emergence of the new virulent races, remains largely unknown. Here, using population genetic analyses, we demonstrate that sexual reproduction plays an important role in the evolution of P. striiformis f. sp. tritici races in China, specifically the newly emerged and devastating race virulent to resistance gene Yr26, which is widely used in China and exerts strong selective pressure on the pathogen population. Association analysis identified six genes encoding secreted proteins as candidates for virulence on wheat cultivars carrying the Yr26 resistance gene. Our results highlight the important role of sexual reproduction and selection exerted by hosts in the emergence of new virulent races in China.

Population differentiation and intraspecific genetic admixture in two Eucryptorrhynchus weevils (Coleoptera: Curculionidae) across northern China.

Increasing damage of pests in agriculture and forestry can arise both as a consequence of changes in local species and through the introduction of alien species. In this study, we used population genetics approaches to examine population processes of two pests of the tree‐of‐heaven trunk weevil (TTW), Eucryptorrhynchus brandti (Harold) and the tree‐of‐heaven root weevil (TRW), E. scrobiculatus (Motschulsky) on the tree‐of‐heaven across their native range of China. We analyzed the population genetics of the two weevils based on ten highly polymorphic microsatellite markers. Population genetic diversity analysis showed strong population differentiation among populations of each species, with F ST ranges from 0.0197 to 0.6650 and from −0.0724 to 0.6845, respectively. Populations from the same geographic areas can be divided into different genetic clusters, and the same genetic cluster contained populations from different geographic populations, pointing to dispersal of the weevils possibly being human‐mediated. Redundancy analysis showed that the independent effects of environment and geography could account for 93.94% and 29.70% of the explained genetic variance in TTW, and 41.90% and 55.73% of the explained genetic variance in TRW, respectively, indicating possible impacts of local climates on population genetic differentiation. Our study helps to uncover population genetic processes of these local pest species with relevance to control methods.

Information-based summary statistics for spatial genetic structure inference.

The measurement of biodiversity at all levels of organization is an essential first step to understand the ecological and evolutionary processes that drive spatial patterns of biodiversity. Ecologists have explored the use of a large range of different summary statistics and have come to the view that information-based summary statistics, and in particular so-called Hill numbers, are a useful tool to measure biodiversity. Population geneticists, on the other hand, have focused largely on summary statistics based on heterozygosity and measures of allelic richness. However, recent studies proposed the adoption of information-based summary statistics in population genetics studies. Here, we performed a comprehensive assessment of the power of this family of summary statistics to inform regarding spatial patterns of genetic diversity and we compared it with that of traditional population genetics approaches, namely measures based on allelic richness and heterozygosity. To give an unbiased evaluation, we used three machine learning methods to test the performance of different sets of summary statistics to discriminate between spatial scenarios. We defined three distinct sets, (i) one based on allelic richness measures which included the Jaccard index, (ii) a set based on heterozygosity that included FST and (iii) a set based on Hill numbers derived from Shannon entropy, which included the recently proposed Shannon differentiation, ΔD. The results showed that the last of these performed as well or, under some specific spatial scenarios, even better than the traditional population genetics measures. Interestingly, we found that a rarely or never used genetic differentiation measure based on allelic richness, Jaccard dissimilarity (J), showed the highest discriminatory power to discriminate among spatial scenarios, followed by Shannon differentiation ΔD. We concluded, therefore, that information-based measures as well as Jaccard dissimilarity represent excellent additions to the population genetics toolkit.

The impact of frequently neglected model violations on bacterial recombination rate estimation: a case study in Mycobacterium canettii and Mycobacterium tuberculosis.

Mycobacterium canettii is a causative agent of tuberculosis in humans, along with the members of the Mycobacterium tuberculosis complex. Frequently used as an outgroup to the M. tuberculosis complex in phylogenetic analyses, M. canettii is thought to offer the best proxy for the progenitor species that gave rise to the complex. Here, we leverage whole-genome sequencing data and biologically relevant population genomic models to compare the evolutionary dynamics driving variation in the recombining M. canettii with that in the nonrecombining M. tuberculosis complex, and discuss differences in observed genomic diversity in the light of expected levels of Hill–Robertson interference. In doing so, we highlight the methodological challenges of estimating recombination rates through traditional population genetic approaches using sequences called from populations of microorganisms and evaluate the likely mis-inference that arises owing to a neglect of common model violations including purifying selection, background selection, progeny skew, and population size change. In addition, we compare performance when full within-host polymorphism data are utilized, versus the more common approach of basing analyses on within-host consensus sequences.

Global flyway evolution in red knots Calidris canutus and genetic evidence for a Nearctic refugium

Present‐day ecology and population structure are the legacies of past climate and habitat perturbations, and this is particularly true for species that are widely distributed at high latitudes. The red knot, Calidris canutus, is an arctic‐breeding, long‐distance migratory shorebird with six recognized subspecies defined by differences in morphology, migration behavior, and annual cycle phenology, in a global distribution thought to have arisen just since the last glacial maximum (LGM). We used nextRAD sequencing of 10,881 single‐nucleotide polymorphisms (SNPs) to assess the neutral genetic structure and phylogeographic history of 172 red knots representing all known global breeding populations. Using population genetics approaches, including model‐based scenario‐testing in an approximate Bayesian computation (ABC) framework, we infer that red knots derive from two main lineages that diverged ca. 34,000 years ago, and thus most probably persisted at the LGM in both Palearctic and Nearctic refugia, followed by at least two instances of secondary contact and admixture. Within two Beringian subspecies (C. c. roselaari and rogersi), we detected previously unknown genetic structure among sub‐populations sharing a migratory flyway, reflecting additional complexity in the phylogeographic history of the region. Conversely, we found very weak genetic differentiation between two Nearctic populations (rufa and islandica) with clearly divergent migratory phenotypes and little or no apparent contact throughout the annual cycle. Together, these results suggest that relative gene flow among migratory populations reflects a complex interplay of historical, geographical, and ecological factors.

How microbiomes can help inform conservation: landscape characterisation of gut microbiota helps shed light on additional population structure in a specialist folivore

BackgroundThe koala (Phascolarctos cinereus), an iconic yet endangered specialised folivore experiencing widespread decline across Australia, is the focus of many conservation programs. Whilst animal translocation and progressive conservation strategies such as faecal inoculations may be required to bring this species back from the brink of extinction, insight into the variation of host-associated gut microbiota and the factors that shape this variation are fundamental for their success. Despite this, very little is known about the landscape variability and factors affecting koala gut microbial community dynamics. We used large scale field surveys to evaluate the variation and diversity of koala gut microbiotas and compared these diversity patterns to those detected using a population genetics approach. Scat samples were collected from five locations across South East Queensland with microbiota analysed using 16S rRNA gene amplicon sequencing.ResultsAcross the landscape koala gut microbial profiles showed large variability, with location having a large effect on bacterial community composition and bacterial diversity. Certain bacteria were found to be significantly differentially abundant amongst locations; koalas from Noosa showed a depletion in two bacterial orders (Gastranaerophilales and Bacteroidales) which have been shown to provide beneficial properties to their host. Koala gut microbial patterns were also not found to mirror population genetic patterns, a molecular tool often used to design conservation initiatives.ConclusionsOur data shows that koala gut microbiotas are extremely variable across the landscape, displaying complex micro- and macro- spatial variation. By detecting locations which lack certain bacteria we identified koala populations that may be under threat from future microbial imbalance or dysbiosis. Additionally, the mismatching of gut microbiota and host population genetic patterns exposed important population structure that has previously gone undetected across South East Queensland. Overall, this baseline data highlights the importance of integrating microbiota research into conservation biology in order to guide successful conservation programs such as species translocation and the implementation of faecal inoculations.

Host, Microbiome, and Complex Space: Applying Population and Landscape Genetic Approaches to Gut Microbiome Research in Wild Populations.

In recent years, emerging sequencing technologies and computational tools have driven a tidal wave of research on host-associated microbiomes, particularly the gut microbiome. These studies demonstrate numerous connections between the gut microbiome and vital host functions, primarily in humans, model organisms, and domestic animals. As the adaptive importance of the gut microbiome becomes clearer, interest in studying the gut microbiomes of wild populations has increased, in part due to the potential for discovering conservation applications. The study of wildlife gut microbiomes holds many new challenges and opportunities due to the complex genetic, spatial, and environmental structure of wild host populations, and the potential for these factors to interact with the microbiome. The emerging picture of adaptive coevolution in host-microbiome relationships highlights the importance of understanding microbiome variation in the context of host population genetics and landscape heterogeneity across a wide range of host populations. We propose a conceptual framework for understanding wildlife gut microbiomes in relation to landscape variables and host population genetics, including the potential of approaches derived from landscape genetics. We use this framework to review current research, synthesize important trends, highlight implications for conservation, and recommend future directions for research. Specifically, we focus on how spatial structure and environmental variation interact with host population genetics and microbiome variation in natural populations, and what we can learn from how these patterns of covariation differ depending on host ecological and evolutionary traits.

A point mutation and large deletion at the candidate avirulence locus AvrMlp7 in the poplar rust fungus correlate with poplar RMlp7 resistance breakdown.

The deployment of plant varieties carrying resistance genes (R) exerts strong selection pressure on pathogen populations. Rapidly evolving avirulence genes (Avr) allow pathogens to escape R-mediated plant immunity through a variety of mechanisms, leading to virulence. The poplar rust fungus Melampsora larici-populina is a damaging pathogen of poplars in Europe. It underwent a major adaptive event in 1994, with the breakdown of the poplar RMlp7 resistance gene. Population genomics studies identified a locus in the genome of M. larici-populina that probably corresponds to the candidate avirulence gene AvrMlp7. Here, to further characterize this effector, we used a population genetics approach on a comprehensive set of 281 individuals recovered throughout a 28-year period encompassing the resistance breakdown event. Using two dedicated molecular tools, genotyping at the candidate locus highlighted two different alterations of a predominant allele found mainly before the resistance breakdown: a nonsynonymous mutation and a complete deletion of this locus. This results in six diploid genotypes: three genotypes related to the avirulent phenotype and three related to the virulent phenotype. The temporal survey of the candidate locus revealed that both alterations were found in association during the resistance breakdown event. They pre-existed before the breakdown in a heterozygous state with the predominant allele cited above. Altogether, these results suggest that the association of both alterations at the candidate locus AvrMlp7 drove the poplar rust adaptation to RMlp7-mediated immunity. This study demonstrates for the first time a case of adaptation from standing genetic variation in rust fungi during a qualitative resistance breakdown.

Historical biogeography and comparative phylogeography of the Mexican genusBakerantha(Bromeliaceae): insights into evolution and diversification

AbstractWe studied the rupicolous and dioecious species of Bakerantha (Bromeliaceae) that grow as narrow endemics in central-eastern Mexico. We aimed to describe the spatio-temporal framework in which Bakerantha and its species originated using a phylogeographic and population genetics approach. We carried out population genetics analyses on 29 populations of the five Bakerantha spp., using plastid and nuclear DNA sequences. The data were used to analyse their diversity, genetic structure and demography, to carry out molecular dating and to reconstruction their ancestral area. Our analyses revealed that speciation in Bakerantha began in the Late Pliocene, associated with vicariance resulting from the rise of the Trans-Mexican Volcanic Belt, a barrier that isolated the Bakerantha spp. to its north and south, and subsequent dispersal events in the Sierra Madre Oriental. Genetic data suggest that the species have achieved a high degree of genetic differentiation and variation, but most of them lack intraspecific structure, even though species have remained stable over the time due their life history traits.

Phylogeography and Genetic Structure in the California Giant Salamander (Dicamptodon ensatus): Impacts of current and historic landscape features.

The California Floristic Province contains numerous ecological regions and a complex geological and geographical history that make it one of the worlds biodiversity hotspots. A number of wide-ranging taxa span across these regions and show complex patterns of dispersal, vicariance and lineage diversification, making localized small ranged species with lower levels of vagility essential to understanding the overall region. Here, we investigate the biogeography and population structure of the California Giant Salamander (Dicamptodon ensatus) (Eschscholtz 1833), an endemic species localized to a narrow coastal region between two areas of biological significance in the California Floristic Province, the North Coast Divide and Monterey Bay. We sequenced one mtDNA fragment (control region) for 133 individuals and a subset of 38 individuals for the anonymous nuclear locus E16C7. We analyzed these sequences with phylogenetic, coalescent, Bayesian clustering, and population genetic approaches in order to infer population structure, phylogenetic structure, and biogeographic history. Additionally, we examined occurrence data with species distribution modeling to generate a habitat suitability map to aid our interpretation of geographic structure. Our analyses recovered 4 major mtDNA lineages, two of which are combined into 3 major lineages when nuDNA is examined. These 3 major lineages are bounded by 4 major current or past geological features; the North Coast Divide, the former Wilson Grove Embayment/current Petaluma Gap, San Francisco Bay, and Monterey Bay. Other low-vagility species linked to moist microclimates and forest habitat do share similarities with the genetic patterns of D. ensatus hinting at a larger role for the past Wilson Grove embayment and modern Petaluma Gap in California biogeography.

Circulation and Evolution of SARS-CoV-2 in India: Let the Data Speak.

The COVID-19 pandemic is a global challenge that impacted 200+ countries. India ranks in the second and third positions in terms of number of reported cases and deaths. Being a populous country with densely packed cities, SARS-CoV-2 spread exponentially. India sequenced ≈0.14% isolates from confirmed cases for pandemic surveillance and contributed ≈1.58% of complete genomes sequenced globally. This study was designed to map the circulating lineage diversity and to understand the evolution of SARS-CoV-2 in India using comparative genomics and population genetics approaches. Despite varied sequencing coverage across Indian States and Union Territories, isolates belonging to variants of concern (VoC) and variants of interest (VoI) circulated, persisted, and diversified during the first seventeen months of the pandemic. Delta and Kappa lineages emerged in India and spread globally. The phylogenetic tree shows lineage-wise monophyletic clusters of VoCs/VoIs and diversified tree topologies for non-VoC/VoI lineages designated as ‘Others’ in this study. Evolutionary dynamics analyses substantiate a lack of spatio-temporal clustering, which is indicative of multiple global and local introductions. Sites under positive selection and significant variations in spike protein corroborate with the constellation of mutations to be monitored for VoC/VoI as well as substitutions that are characteristic of functions with implications in virus–host interactions, differential glycosylation, immune evasion, and escape from neutralization.

Genetic Diversity in Chimpanzee Transcriptomics Does Not Represent Wild Populations.

Chimpanzees (Pan troglodytes) are a genetically diverse species, consisting of four highly distinct subspecies. As humans’ closest living relative, they have been a key model organism in the study of human evolution, and comparisons of human and chimpanzee transcriptomes have been widely used to characterize differences in gene expression levels that could underlie the phenotypic differences between the two species. However, the subspecies from which these transcriptomic data sets have been derived is not recorded in metadata available in the public NCBI Sequence Read Archive (SRA). Furthermore, labeling of RNA sequencing (RNA-seq) samples is for the most part inconsistent across studies, and the true number of individuals from whom transcriptomic data are available is difficult to ascertain. Thus, we have evaluated genetic diversity at the subspecies and individual level in 486 public RNA-seq samples available in the SRA, spanning the vast majority of public chimpanzee transcriptomic data. Using multiple population genetics approaches, we find that nearly all samples (96.6%) have some degree of Western chimpanzee ancestry. At the individual donor level, we identify multiple samples that have been repeatedly analyzed across different studies and identify a total of 135 genetically distinct individuals within our data, a number that falls to 89 when we exclude likely first- and second-degree relatives. Altogether, our results show that current transcriptomic data from chimpanzees are capturing low levels of genetic diversity relative to what exists in wild chimpanzee populations. These findings provide important context to current comparative transcriptomics research involving chimpanzees.

Genome-wide population structure inferences of human coxsackievirus-A; insights the genotypes diversity and evolution.

Coxsackievirus-A (CV-A) is a causative agent of Hand Foot Mouth Disease (HFMD) worldwide. It belongs to the Human Enterovirus genus of the family Picornaviridae. The genomics data availability of CV-A samples, isolated from human host across different continental regions, provide an excellent opportunity to study its genetic composition, diversity, and evolutionary events. The complete genome sequences of 424 CV-A isolates were analyzed through a model-based population genetic approach implemented in the STRUCTURE program. Twelve genetically distinct sub-populations were identified for CV-A isolates with a marked Fst distinction of 0.76991 (P-value=0.00000). Besides, genetically admixed strains were characterized in the G-Id, G-IIIb clusters constituted by the CV-A12 and CV-A6 enterovirus serotypes. The serotypes depicted inter/intra-genotype recombination and episodic positive selection signatures in the structural and non-structural protein-coding regions. The observed genetic composition of CV-A samples was also deduced by the phylogenetic tree analyses, where a uniform genetic structure was inferred for most of the CV-A genotypes. However, the CV-A6 serotype samples genetically stratified into three sub-populations that may lead to the emergence of new lineages in future. These informations may implicate in planning the effective strategies to combat the coxsackievirus-A-mediated infection.

Understanding how an amphicarpic species with a mixed mating system responds to fire: a population genetic approach.

Amphicarpic plants produce both above-ground and below-ground seeds. Because below-ground seeds are protected in the soil and may maintain viability when above-ground conditions are stressful, they were proposed as an adaptation to recolonize a site after disturbance. However, whether below-ground seeds are the main colonizers after a disturbance remains unknown. Our goal was to understand whether recolonization by an amphicarpic species after fire was accomplished primarily through germination of seeds produced above-ground or below-ground. We investigated Polygala lewtonii, an amphicarpic, perennial species endemic to fire-prone Florida sandhill and scrub, where fire kills plants but subsequently increases recruitment and population sizes. Polygala lewtonii produces three flower types: above-ground chasmogamous flowers and above-ground and below-ground cleistogamous flowers, with previous research demonstrating chasmogamous flowers produce a much greater proportion of seeds than cleistogamous flowers. We quantified outcrossing in seeds produced by chasmogamous flowers to determine whether it differed from the 100 % self-fertilized below-ground seeds. Approximately 25 % of seeds from chasmogamous flowers showed evidence of cross-pollination. Assuming that chasmogamous flowers produce the majority of the above-ground seeds, as was shown previously, this indicates it is possible to differentiate between germination by above-ground versus below-ground seeds in post-fire colonization. We next compared genetic diversity, admixture, inbreeding and population genetic structure pre- and post-fire. If fire promoted germination of chasmogamous seeds, heterozygosity and admixture would increase, and genetic structure and inbreeding would decrease. Instead, inbreeding and genetic structure increased and admixture decreased, suggesting that the below-ground selfed seeds (with limited dispersal ability) increased their contribution to the population after fire, possibly because fire reduced above-ground seed viability. Additionally, new alleles not found previously in range-wide analyses emerged from the seed bank post-fire. These results suggest that amphicarpy is a powerful adaptation to preserve genetic variation, maintain adaptive potential and promote rapid post-fire colonization.

Machine learning to predict the source of campylobacteriosis using whole genome data.

Campylobacteriosis is among the world’s most common foodborne illnesses, caused predominantly by the bacterium Campylobacter jejuni. Effective interventions require determination of the infection source which is challenging as transmission occurs via multiple sources such as contaminated meat, poultry, and drinking water. Strain variation has allowed source tracking based upon allelic variation in multi-locus sequence typing (MLST) genes allowing isolates from infected individuals to be attributed to specific animal or environmental reservoirs. However, the accuracy of probabilistic attribution models has been limited by the ability to differentiate isolates based upon just 7 MLST genes. Here, we broaden the input data spectrum to include core genome MLST (cgMLST) and whole genome sequences (WGS), and implement multiple machine learning algorithms, allowing more accurate source attribution. We increase attribution accuracy from 64% using the standard iSource population genetic approach to 71% for MLST, 85% for cgMLST and 78% for kmerized WGS data using the classifier we named aiSource. To gain insight beyond the source model prediction, we use Bayesian inference to analyse the relative affinity of C. jejuni strains to infect humans and identified potential differences, in source-human transmission ability among clonally related isolates in the most common disease causing lineage (ST-21 clonal complex). Providing generalizable computationally efficient methods, based upon machine learning and population genetics, we provide a scalable approach to global disease surveillance that can continuously incorporate novel samples for source attribution and identify fine-scale variation in transmission potential.

Population genetics unveils large-scale migration dynamics and population turnover of Spodoptera exigua.

Migration is a widespread phenomenon among many insect species, including herbivorous crop pests. At present, scant information exists on the long-range migration of the polyphagous armyworm, Spodoptera exigua and its underlying climatic determinants (i.e. East Asian or South Asian monsoon circulation). In this study, we employed a population genetics approach to delineate S.exigua migration patterns across multiple Asian countries. Using mitochondrial cytochrome I (COI) and microsatellite markers, low-to-moderate levels of genetic diversity were detected among 101 S.exigua populations collected across China, Pakistan and Vietnam. Haplotype diversity and nucleotide diversity did not differ between years. Two spatially explicit genetic clusters were detected, an eastern and a western clade, with the former comprising populations in the East Asia monsoon area. No genetic differentiation was recorded among armyworm populations in the year-round breeding area, nor among those of the overwintering and nonoverwintering areas. Five of the most widespread mitochondrial haplotypes reflected the extensive gene flow across at a large spatial scale. Low-to-moderate levels of genetic diversity were observed, and evidence was found for genetic clustering in certain geographical areas. Accordingly, our unique insights into S.exigua population genetics and spatiotemporal migration dynamics help to guide applied ecological studies, ecological intensification schemes or (area-wide) pest management campaigns in China and abroad. © 2021 Society of Chemical Industry.