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The spread and adaptation of fungal plant pathogens in agroecosystems are facilitated by environmental homogeneity. Metagenomic sequencing of infected tissues allowed us to monitor eco-evolutionary dynamics and interactions between host, pathogen and plant microbiome. Exserohilum turcicum, the causal agent of northern corn leaf blight (NCLB) in maize, is distributed in multiple clonal lineages throughout Europe. To characterize regional pathogen diversity, we conducted metagenomic DNA sequencing on 241 infected leaf samples from the highly susceptible Swiss maize landrace Rheintaler Ribelmais, collected over 3 years (2016-2018) from an average of 14 agricultural farms within the Swiss Rhine Valley. All major European clonal lineages of E. turcicum were identified. Lineages differ by their mating types which indicates potential for sexual recombination and rapid evolution of new pathogen strains, although we found no evidence of recent recombination. The associated eukaryotic and prokaryotic leaf microbiome exhibited variation in taxonomic diversity between years and locations and is likely influenced by local weather conditions. A network analysis revealed distinct clusters of eukaryotic and prokaryotic taxa that correlates with the frequency of E. turcicum sequencing reads, suggesting causal interactions. Notably, the yeast genus Metschnikowia exhibited a strongly negative association with E. turcicum, supporting its known potential as biological control agent against fungal pathogens. Our findings show that metagenomic sequencing is a useful tool for analysing the role of environmental factors and potential pathogen-microbiome interactions in shaping pathogen dynamics and evolution, suggesting their potential for effective pathogen management strategies.

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Even seemingly homogeneous on the surface, the oceans display high environmental heterogeneity across space and time. Indeed, different soft barriers structure the marine environment, which offers an appealing opportunity to study various evolutionary processes such as population differentiation and speciation. Here, we focus on Amphiprion clarkii (Actinopterygii; Perciformes), the most widespread of clownfishes that exhibits the highest colour polymorphism. Clownfishes can only disperse during a short pelagic larval phase before their sedentary adult lifestyle, which might limit connectivity among populations, thus facilitating speciation events. Consequently, the taxonomic status of A. clarkii has been under debate. We used whole-genome resequencing data of 67 A. clarkii specimens spread across the Indian and Pacific Oceans to characterize the species' population structure, demographic history and colour polymorphism. We found that A. clarkii spread from the Indo-Pacific Ocean to the Pacific and Indian Oceans following a stepping-stone dispersal and that gene flow was pervasive throughout its demographic history. Interestingly, colour patterns differed noticeably among the Indonesian populations and the two populations at the extreme of the sampling distribution (i.e. Maldives and New Caledonia), which exhibited more comparable colour patterns despite their geographic and genetic distances. Our study emphasizes how whole-genome studies can uncover the intricate evolutionary past of wide-ranging species with diverse phenotypes, shedding light on the complex nature of the species concept paradigm.

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Plant collections held by botanic gardens and arboreta are key components of ex situ conservation. Maintaining genetic diversity in such collections allows them to be used as resources for supplementing wild populations. However, most recommended minimum sample sizes for sufficient ex situ genetic diversity are based on microsatellite markers, and it remains unknown whether these sample sizes remain valid in light of more recently developed next-generation sequencing (NGS) approaches. To address this knowledge gap, we examine how ex situ conservation status and sampling recommendations differ when derived from microsatellites and single nucleotide polymorphisms (SNPs) in garden and wild samples of two threatened oak species. For Quercus acerifolia, SNPs show lower ex situ representation of wild allelic diversity and slightly lower minimum sample size estimates than microsatellites, while results for each marker are largely similar for Q. boyntonii. The application of missing data filters tends to lead to higher ex situ representation, while the impact of different SNP calling approaches is dependent on the species being analyzed. Measures of population differentiation within species are broadly similar between markers, but larger numbers of SNP loci allow for greater resolution of population structure and clearer assignment of ex situ individuals to wild source populations. Our results offer guidance for future ex situ conservation assessments utilizing SNP data, such as the application of missing data filters and the usage of a reference genome, and illustrate that both microsatellites and SNPs remain viable options for botanic gardens and arboreta seeking to ensure the genetic diversity of their collections.

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Highly polymorphic markers, such as microsatellites, are invaluable for the study of natural populations. However, contemporary methods for genotyping highly polymorphic variants have serious drawbacks that impede their efficiency. We created Polly, an R package with C++ source code that uses Illumina short-read data to genotype microsatellites, detect highly polymorphic variants and identify clusters of highly polymorphic SNPs, indels and microsatellites. We tested Polly on short-read data from Xiphophorus birchmanni (Teleostei: Poeciliidae) and Arabidopsis thaliana, finding it to be efficient and accurate both for microsatellite genotyping and polymorphic marker detection. This program can be applied to any diploid population for which there exists short-read data and at least one scaffolded reference genome.

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Understanding the drivers of evolutionary innovation provides a crucial perspective of how evolutionary processes unfold across taxa and ecological systems. It has been hypothesised that the Southern Ocean provided ecological opportunities for novelty in the past. However, the drivers of innovation are challenging to pinpoint as the evolutionary genetics of Southern Ocean fauna are influenced by Quaternary glacial-interglacial cycles, oceanic currents and species ecology. Here we examined the genome-wide single nucleotide polymorphisms of the Southern Ocean brittle stars Ophionotus victoriae (five arms, broadcaster) and O. hexactis (six arms, brooder). We found that O. victoriae and O. hexactis are closely-related species with interspecific gene flow. During the late Pleistocene, O. victoriae likely persisted in a connected deep water refugium and in situ refugia on the Antarctic continental shelf and around Antarctic islands; O. hexactis persisted exclusively within in situ island refugia. Within O. victoriae, contemporary gene flow linking to the Antarctic Circumpolar Current, regional gyres and other local oceanographic regimes was observed. Gene flow connecting West and East Antarctic islands near the Polar Front was also detected in O. hexactis. A strong association was detected between outlier loci and salinity in O. hexactis. Both O. victoriae and O. hexactis are associated with genome-wide increase in alleles at intermediate-frequencies; the alleles associated with this peak appear to be species specific, and these intermediate-frequency variants are far more excessive in O. hexactis. We hypothesise that the peak in alleles at intermediate frequencies could be related to adaptation in the recent past, linked to evolutionary innovations of increase in arm number and a switch to brooding from broadcasting, in O. hexactis.

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While key elements of fitness in vertebrate animals are impacted by their microbiomes, the host genetic characteristics that factor into microbiome composition are not fully understood. Here, we correlate host genomic heterozygosity and gut microbiome phylogenetic diversity across a community of reptiles in southwestern New Mexico to test hypotheses about the behaviour of host genes that drive microbiome assembly. We find that microbiome communities are phylogenetically under-dispersed relative to random expectations, and that host heterozygosity is not correlated with microbiome diversity. Our analyses reinforce results from functional genomic work that identify conserved host immune and nonimmune genes as key players in microbiome assembly, rather than gene families that rely on heterozygosity for their function.

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Understanding spatial patterns of genetic differentiation and local adaptation is critical in a period of rapid environmental change. Climate change and anthropogenic development have led to population declines and shifting geographic distributions in numerous species. The streamside salamander, Ambystoma barbouri, is an endemic amphibian with a small geographic range that predominantly inhabits small, ephemeral streams. As A. barbouri is listed as near-threatened by the IUCN, we describe range-wide patterns of genetic differentiation and adaptation to assess the species' potential to respond to environmental change. We use outlier scans and genetic-environment association analyses to identify genomic variation putatively underlying local adaptation across the species' geographic range. We find evidence for adaptation with a polygenic architecture and a set of candidate SNPs that identify genes putatively contributing to local adaptation. Our results build on earlier work that suggests that some A. barbouri populations are locally adapted despite evidence for asymmetric gene flow between the range core and periphery. Taken together, the body of work describing the evolutionary genetics of range limits in A. barbouri suggests that the species may be unlikely to respond naturally to environmental challenges through a range shift or in situ adaptation. We suggest that management efforts such as assisted migration may be necessary in future.

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Anopheles hinesorum is a mosquito species with variable host preference. Throughout New Guinea and northern Australia, An. hinesorum feeds on humans (it is opportunistically anthropophagic) while in the south-west Pacific's Solomon Archipelago, the species is abundant but has rarely been found biting humans (it is exclusively zoophagic in most populations). There are at least two divergent zoophagic (nonhuman biting) mitochondrial lineages of An. hinesorum in the Solomon Archipelago representing two independent dispersals. Since zoophagy is a derived (nonancestral) trait in this species, this leads to the question: has zoophagy evolved independently in these two populations? Or conversely: has nuclear gene flow or connectivity resulted in the transfer of zoophagy? Although we cannot conclusively answer this, we find close nuclear relationships between Solomon Archipelago populations indicating that recent nuclear gene flow has occurred between zoophagic populations from the divergent mitochondrial lineages. Recent work on isolated islands of the Western Province (Solomon Archipelago) has also revealed an anomalous, anthropophagic island population of An. hinesorum. We find a common shared mitochondrial haplotype between this Solomon Island population and another anthropophagic population from New Guinea. This finding suggests that there has been recent migration from New Guinea into the only known anthropophagic population from the Solomon Islands. Although currently localized to a few islands in the Western Province of the Solomon Archipelago, if anthropophagy presents a selective advantage, we may see An. hinesorum emerge as a new malaria vector in a region that is now working on malaria elimination.

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Balancing selection is an important adaptive mechanism underpinning a wide range of phenotypes. Despite its relevance, the detection of recent balancing selection from genomic data is challenging as its signatures are qualitatively similar to those left by ongoing positive selection. In this study, we developed and implemented two deep neural networks and tested their performance to predict loci under recent selection, either due to balancing selection or incomplete sweep, from population genomic data. Specifically, we generated forward-in-time simulations to train and test an artificial neural network (ANN) and a convolutional neural network (CNN). ANN received as input multiple summary statistics calculated on the locus of interest, while CNN was applied directly on the matrix of haplotypes. We found that both architectures have high accuracy to identify loci under recent selection. CNN generally outperformed ANN to distinguish between signals of balancing selection and incomplete sweep and was less affected by incorrect training data. We deployed both trained networks on neutral genomic regions in European populations and demonstrated a lower false-positive rate for CNN than ANN. We finally deployed CNN within the MEFV gene region and identified several common variants predicted to be under incomplete sweep in a European population. Notably, two of these variants are functional changes and could modulate susceptibility to familial Mediterranean fever, possibly as a consequence of past adaptation to pathogens. In conclusion, deep neural networks were able to characterize signals of selection on intermediate frequency variants, an analysis currently inaccessible by commonly used strategies.

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The ability to generate genomic data from wild animal populations has the potential to give unprecedented insight into the population history and dynamics of species in their natural habitats. However, for many species, it is impossible legally, ethically or logistically to obtain tissue samples of quality sufficient for genomic analyses. In this study we evaluate the success of multiple sources of genetic material (faeces, urine, dentin and dental calculus) and several capture methods (shotgun, whole-genome, exome) in generating genome-scale data in wild eastern chimpanzees (Pan troglodytes schweinfurthii) from Gombe National Park, Tanzania. We found that urine harbours significantly more host DNA than other sources, leading to broader and deeper coverage across the genome. Urine also exhibited a lower rate of allelic dropout. We found exome sequencing to be far more successful than both shotgun sequencing and whole-genome capture at generating usable data from low-quality samples such as faeces and dental calculus. These results highlight urine as a promising and untapped source of DNA that can be noninvasively collected from wild populations of many species.

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Genetic structure in host species is often used to predict disease spread. However, host and pathogen genetic variation may be incongruent. Understanding landscape factors that have either concordant or divergent influence on host and pathogen genetic structure is crucial for wildlife disease management. Devil facial tumour disease (DFTD) was first observed in 1996 and has spread throughout almost the entire Tasmanian devil geographic range, causing dramatic population declines. Whereas DFTD is predominantly spread via biting among adults, devils typically disperse as juveniles, which experience low DFTD prevalence. Thus, we predicted little association between devil and tumour population structure and that environmental factors influencing gene flow differ between devils and tumours. We employed a comparative landscape genetics framework to test the influence of environmental factors on patterns of isolation by resistance (IBR) and isolation by environment (IBE) in devils and DFTD. Although we found evidence for broad-scale costructuring between devils and tumours, we found no relationship between host and tumour individual genetic distances. Further, the factors driving the spatial distribution of genetic variation differed for each. Devils exhibited a strong IBR pattern driven by major roads, with no evidence of IBE. By contrast, tumours showed little evidence for IBR and a weak IBE pattern with respect to elevation in one of two tumour clusters we identify herein. Our results warrant caution when inferring pathogen spread using host population genetic structure and suggest that reliance on environmental barriers to host connectivity may be ineffective for managing the spread of wildlife diseases. Our findings demonstrate the utility of comparative landscape genetics for identifying differential factors driving host dispersal and pathogen transmission.

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Monarch butterflies are known for their spectacular annual migration in eastern North America, with millions of monarchs flying up to 4,500 km to overwintering sites in central Mexico. Monarchs also live west of the Rocky Mountains, where they travel shorter distances to overwinter along the Pacific Coast. It is often assumed that eastern and western monarchs form distinct evolutionary units, but genomic studies to support this notion are lacking. We used a tethered flight mill to show that migratory eastern monarchs have greater flight performance than western monarchs, consistent with their greater migratory distances. However, analysing more than 20 million SNPs in 43 monarch genomes, we found no evidence for genomic differentiation between eastern and western monarchs. Genomic analysis also showed identical and low levels of genetic diversity, and demographic analyses indicated similar effective population sizes and ongoing gene flow between eastern and western monarchs. Gene expression analysis of a subset of candidate genes during active flight revealed differential gene expression related to nonmuscular motor activity. Our results demonstrate that eastern and western monarchs maintain migratory differences despite ongoing gene flow, and suggest that migratory differences between eastern and western monarchs are not driven by select major-effects alleles. Instead, variation in migratory distance and destination may be driven by environmentally induced differential gene expression or by many alleles of small effect.

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Genome scans can potentially identify genetic loci involved in evolutionary processes such as local adaptation and gene flow. Here, we show that recombination rate variation across a neutrally evolving genome gives rise to mixed sampling distributions of mean FST ( FST^ ), a common population genetic summary statistic. In particular, we show that in regions of low recombination the distribution of FST^ estimates has more variance and a longer tail than in more highly recombining regions. Determining outliers from the genome-wide distribution without taking local recombination rate into consideration may therefore increase the frequency of false positives in low recombination regions and be overly conservative in more highly recombining ones. We perform genome scans on simulated and empirical Drosophila melanogaster data sets and, in both cases, find patterns consistent with this neutral model. Similar patterns are observed for other summary statistics used to capture variation in the coalescent process. Linked selection, particularly background selection, is often invoked to explain heterogeneity in FST^ across the genome, but here we point out that even under neutrality, statistical artefacts can arise due to variation in recombination rate. Our results highlight a flaw in the design of genome-scan studies and suggest that without estimates of local recombination rate, interpreting the genomic landscape of any summary statistic that captures variation in the coalescent process will be very difficult.

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Vernal pools are unique in their isolation and the strong selection acting on their resident species. Vernal pool clam shrimp (Eulimnadia texana) are a promising model due to ease of culturing, short generation time, small genomes, and obligate desiccated diapaused eggs. Clam shrimp are also androdioecious (sexes include males and hermaphrodites), and here we use population-scaled recombination rates to support the hypothesis that the heterogametic sex is recombination free in these shrimp. We collected short-read sequence data from pooled samples from different vernal pools to gain insights into local adaptation. We identify genomic regions in which some populations have allele frequencies that differ significantly from the metapopulation. BayPass (Gautier M. 2015. Genome-wide scan for adaptive divergence and association with population-specific covariates. Genetics 201(4):1555-1579.) detected 19 such genomic regions showing an excess of population subdivision. These regions on average are 550 bp in size and had 2.5 genes within 5 kb of them. Genes located near these regions are involved in Malpighian tubule function and osmoregulation, an essential function in vernal pools. It is likely that salinity profiles vary between pools and over time, and variants at these genes are adapted to local salinity conditions.

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The world's forests face unprecedented threats from invasive insects and pathogens that can cause large irreversible damage to the ecosystems. This threatens the world's capacity to provide long-term fiber supply and ecosystem services that range from carbon storage, nutrient cycling, and water and air purification, to soil preservation and maintenance of wildlife habitat. Reducing the threat of forest invasive alien species requires vigilant biosurveillance, the process of gathering, integrating, interpreting, and communicating essential information about pest and pathogen threats to achieve early detection and warning and to enable better decision-making. This process is challenging due to the diversity of invasive pests and pathogens that need to be identified, the diverse pathways of introduction, and the difficulty in assessing the risk of establishment. Genomics can provide powerful new solutions to biosurveillance. The process of invasion is a story written in four chapters: transport, introduction, establishment, and spread. The series of processes that lead to a successful invasion can leave behind a DNA signature that tells the story of an invasion. This signature can help us understand the dynamic, multistep process of invasion and inform management of current and future introductions. This review describes current and future application of genomic tools and pipelines that will provide accurate identification of pests and pathogens, assign outbreak or survey samples to putative sources to identify pathways of spread, and assess risk based on traits that impact the outbreak outcome.

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Understanding the biological processes involved in genetic differentiation and divergence between populations within species is a pivotal aim in evolutionary biology. One particular phenomenon that requires clarification is the maintenance of genetic barriers despite the high potential for gene flow in the marine environment. Such patterns have been attributed to limited dispersal or local adaptation, and to a lesser extent to the demographic history of the species. The corkwing wrasse (Symphodus melops) is an example of a marine fish species where regions of particular strong divergence are observed. One such genetic break occurred at a surprisingly small spatial scale (FST ~0.1), over a short coastline (<60 km) in the North Sea-Skagerrak transition area in southwestern Norway. Here, we investigate the observed divergence and purported reproductive isolation using genome resequencing. Our results suggest that historical events during the post-glacial recolonization route can explain the present population structure of the corkwing wrasse in the northeast Atlantic. While the divergence across the break is strong, we detected ongoing gene flow between populations over the break suggesting recent contact or negative selection against hybrids. Moreover, we found few outlier loci and no clear genomic regions potentially being under selection. We concluded that neutral processes and random genetic drift e.g., due to founder events during colonization have shaped the population structure in this species in Northern Europe. Our findings underline the need to take into account the demographic process in studies of divergence processes.

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Aedes aegypti is among the best-studied mosquitoes due to its critical role as a vector of human pathogens and ease of laboratory rearing. Until now, this species was thought to have originated in continental Africa, and subsequently colonized much of the world following the establishment of global trade routes. However, populations of this mosquito on the islands in the southwestern Indian Ocean (SWIO), where the species occurs with its nearest relatives referred to as the Aegypti Group, have received little study. We re-evaluated the evolutionary history of Ae. aegypti and these relatives, using three data sets: nucleotide sequence data, 18,489 SNPs and 12 microsatellites. We found that: (a) the Aegypti Group diverged 16 MYA (95% HPD: 7-28 MYA) from its nearest African/Asian ancestor; (b) SWIO populations of Ae. aegypti are basal to continental African populations; (c) after diverging 7 MYA (95% HPD: 4-15 MYA) from its nearest formally described relative (Ae. mascarensis), Ae. aegypti moved to continental Africa less than 85,000 years ago, where it recently (<1,000 years ago) split into two recognized subspecies Ae. aegypti formosus and a human commensal, Ae. aegypti aegypti; (d) the Madagascar samples form a clade more distant from all other Ae. aegypti than the named species Ae. mascarensis, implying that Madagascar may harbour a new cryptic species; and (e) there is evidence of introgression between Ae. mascarensis and Ae. aegypti on Réunion, and between the two subspecies elsewhere in the SWIO, a likely consequence of recent introductions of domestic Ae. aegypti aegypti from Asia.

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Population divergence can occur due to mechanisms associated with geographic isolation and/or due to selection associated with different ecological niches. Much of the evidence for selection-driven speciation has come from studies of specialist insect herbivores that use different host plant species; however, the influence of host plant use on population divergence of generalist herbivores remains poorly understood. We tested how diet breadth, host plant species and geographic distance influence population divergence of the fall webworm (Hyphantria cunea; FW). FW is a broadly distributed, extreme generalist herbivore consisting of two morphotypes that have been argued to represent two different species: black-headed and red-headed. We characterized the differentiation of FW populations at two geographic scales. We first analysed the influence of host plant and geographic distance on genetic divergence across a broad continental scale for both colour types. We further analysed the influence of host plant, diet breadth and geographic distance on divergence at a finer geographic scale focusing on red-headed FW in Colorado. We found clear genetic and morphological distinction between red- and black-headed FW, and Colorado FW formed a genetic cluster distinct from other locations. Although both geographic distance and host plant use were correlated with genetic distance, geographic distance accounted for up to 3× more variation in genetic distance than did host plant use. As a rare study investigating the genetic structure of a widespread generalist herbivore over a broad geographic range (up to 3,000 km), our study supports a strong role for geographic isolation in divergence in this system.

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Population geneticists often use multiple independent hypothesis tests of Hardy-Weinberg Equilibrium (HWE), Linkage Disequilibrium (LD), and population differentiation, to make broad inferences about their systems of choice. However, correcting for Family-Wise Error Rates (FWER) that are inflated due to multiple comparisons, is sparingly reported in our current literature. In this issue of Molecular Ecology Resources, perform a meta-analysis of 215 population genetics studies published between 2011 and 2013 to show (i) scarce use of FWER corrections across all three classes of tests, and (ii) when used, inconsistent application of correction methods with a clear bias towards less-conservative corrections for tests of population differentiation, than for tests of HWE, and LD. Here we replicate this meta-analysis using 205 population genetics studies published between 2013 and 2018, to show the same continued disuse, and inconsistencies. We hope that both studies serve as a wake-up call to population geneticists, reviewers, and editors to be rigorous about consistently correcting for FWER inflation.

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Approximately 200 weed species are responsible for more than 90% of crop losses and these comprise less than one percent of all named plant species, suggesting that there are only a few evolutionary routes that lead to weediness. Agricultural weeds can evolve along three main paths: they can be escaped crops, wild species, or crop-wild hybrids. We tested these three hypotheses in weedy radish, a weed of small grains and an emerging model for investigating the evolution of agricultural weeds, using 21 CAPS and SSR markers scored on 338 individuals from 34 populations representing all major species and sub-species in the radish genus Raphanus. To test for adaptation of the weeds to the agricultural environment, we estimated genetic differentiation in flowering time in a series of common garden experiments with over 2,400 individuals from 43 populations (all but one of the genotyped populations plus 10 additional populations). Our findings suggest that the agricultural weed radish R. r. raphanistrum is most genetically similar to native populations of R. r. raphanistrum and is likely not a feral crop or crop hybrid. We also show that weedy radish flowers more rapidly than any other Raphanus population or cultivar, which is consistent with rapid adaptation to the frequent and severe disturbance that characterizes agricultural fields.