These aren't the loci you'e looking for: Principles of effective SNP filtering for molecular ecologists

Museomics help resolving the phylogeny of snowfinches (Aves, Passeridae, Montifringilla and allies)

Historical specimens from museum collections provide a valuable source of material also from remote areas or regions of conflict that are not easily accessible to scientists today. With this study, we are providing a taxon-complete phylogeny of snowfinches using historical DNA from whole skins of an endemic species from Afghanistan, the Afghan snowfinch, Pyrgilauda theresae. To resolve the strong conflict between previous phylogenetic hypotheses, we generated novel mitogenome sequences for selected taxa and genome-wide SNP data using ddRAD sequencing for all extant snowfinch species endemic to the Qinghai-Tibet Plateau (QTP) and for an extended intraspecific sampling of the sole Central and Western Palearctic snowfinch species (Montifringilla nivalis). Our phylogenetic reconstructions unanimously refuted the previously suggested paraphyly of genus Pyrgilauda. Misplacement of one species-level taxon (Onychostruthus tazcanowskii) in previous snowfinch phylogenies was undoubtedly inferred from chimeric mitogenomes that included heterospecific sequence information. Furthermore, comparison of novel and previously generated sequence data showed that the presumed sister-group relationship between M. nivalis and the QTP endemic M. henrici was suggested based on flawed taxonomy. Our phylogenetic reconstructions based on genome-wide SNP data and on mitogenomes were largely congruent and supported reciprocal monophyly of genera Montifringilla and Pyrgilauda with monotypic Onychostruthus being sister to the latter. The Afghan endemic P. theresae likely originated from a rather ancient Pliocene out-of-Tibet dispersal probably from a common ancestor with P. ruficollis. Our extended trans-Palearctic sampling for the white-winged snowfinch, M. nivalis, confirmed strong lineage divergence between an Asian and a European clade dated to 1.5 - 2.7 million years ago (mya). Genome-wide SNP data suggested subtle divergence among European samples from the Alps and from the Cantabrian mountains.

Association mapping and candidate gene identification for yield traits in European hazelnut (Corylus avellana L.)

European hazelnut (Corylus avellana L.) is an important nut crop due to its nutritional benefits, culinary uses, and economic value. Türkiye is the leading producer of hazelnut, followed by Italy and the United States. Quantitative trait locus studies offer promising opportunities for breeders and geneticists to identify genomic regions controlling desirable traits in hazelnut. A genome-wide association analysis was conducted with 5,567 single nucleotide polymorphisms on a Turkish core set of 86 hazelnut accessions, revealing 189 quantitative trait nucleotides (QTNs) associated with 22 of 31 traits (p < 2.9E-07). These QTNs were associated with plant and leaf, phenological, reproductive, nut, and kernel traits. Based on the close physical distance of QTNs associated with the same trait, we identified 23 quantitative trait loci. Furthermore, we identified 23 loci of multiple QTs comprising chromosome locations associated with more than one trait at the same position or in close proximity. A total of 159 candidate genes were identified for 189 QTNs, with 122 of them containing significant conserved protein domains. Some candidate matches to known proteins/domains were highly significant, suggesting that they have similar functions as their matches. This comprehensive study provides valuable insights for the development of breeding strategies and the improvement of hazelnut and enhances the understanding of the genetic architecture of complex traits by proposing candidate genes and potential functions.

Environmental and anthropogenic factors mediating the functional connectivity of the mesquite lizard along the eastern Trans-Mexican Volcanic Belt

Functional connectivity, the extent to which a landscape facilitates or impedes the dispersal of individuals across the landscape, is a key factor for the survival of species. Anthropogenic activities, such as urbanization, agriculture and roads, negatively impact functional connectivity of most species, particularly low-vagility species like lizards. Here, we examine how a landscape modified by anthropogenic activities affects the functional connectivity, at both broad and fine scales, of a widely distributed generalist lizard Sceloporus grammicus in the eastern Trans-Mexican Volcanic Belt, Mexico. We estimated for the first time the species' genetic structure, gene flow and functional connectivity in agricultural and forest zones using genomic data, a comprehensive landscape characterization and novel methods including gravity models. Our results showed not only marked genetic differentiation across the study region but also that functional connectivity is maintained for tens of kilometres despite S. grammicus low vagility. Specifically, we found that substrate and air temperature facilitated connectivity over broad and fine scales, respectively, while agricultural cover, relative humidity and slope were important for connectivity and gene flow. Contrastingly, forest cover and roads favoured (broad-scale) and limited (fine-scale) connectivity, likely associated with movement facilitated by small forest patches and with thermoregulation. Altogether, these results support that S. grammicus alternates its thermoregulatory behaviour depending on the distance travelled and the habitat environmental conditions, and that it can disperse through relatively modified landscapes, mainly using agricultural zones. The information obtained is crucial to understanding the response of lizards to current anthropogenic pressures and their potential to adapt.

Why we thrive beneath a northern sky - genomic signals of selection in apple for adaptation to northern Sweden

Good understanding of the genomic regions underlying adaptation of apple to boreal climates is needed to facilitate efficient breeding of locally adapted apple cultivars. Proper infrastructure for phenotyping and evaluation is essential for identification of traits responsible for adaptation, and dissection of their genetic composition. However, such infrastructure is costly and currently not available for the boreal zone of northern Sweden. Therefore, we used historical pomological data on climate adaptation of 59 apple cultivars and whole genome sequencing to identify genomic regions that have undergone historical selection among apple cultivars recommended for cultivation in northern Sweden. We found the apple collection to be composed of two ancestral groups that are largely concordant with the grouping into 'hardy' and 'not hardy' cultivars based on the pomological literature. Using a number of genome-wide scans for signals of selection, we obtained strong evidence of positive selection at a genomic region around 29 MbHFTH1 of chromosome 1 among apple cultivars in the 'hardy' group. Using phased genotypic data from the 20 K apple Infinium® SNP array, we identified haplotypes associated with the two cultivar groups and traced transmission of these haplotypes through the pedigrees of some apple cultivars. This demonstrates that historical data from pomological literature can be analyzed by population genomic approaches as a step towards revealing the genomic control of a key property for a horticultural niche market. Such knowledge is needed to facilitate efficient breeding strategies for development of locally adapted apple cultivars in the future. The current study illustrates the response to a very strong selective pressure imposed on tree crops by climatic factors, and the importance of genetic research on this topic and feasibility of breeding efforts in the light of the ongoing climate change.

Spatial variation in genomic signatures of local adaptation during the cane toad invasion of Australia

Adaptive evolution can facilitate species' range expansions across environmentally heterogeneous landscapes. However, serial founder effects can limit the efficacy of selection, and the evolution of increased dispersal during range expansions may result in gene flow swamping local adaptation. Here, we study how genetic drift, gene flow and selection interact during the cane toad's (Rhinella marina) invasion across the heterogeneous landscape of Australia. Following its introduction in 1935, the cane toad colonised eastern Australia and established several stable range edges. The ongoing, more rapid range expansion in north-central Australia has occurred concomitant with an evolved increase in dispersal capacity. Using reduced representation genomic data of Australian cane toads from the expansion front and from two areas of their established range, we test the hypothesis that high gene flow constrains local adaptation at the expansion front relative to established areas. Genetic analyses indicate the three study areas are genetically distinct but show similar levels of allelic richness, heterozygosity and inbreeding. Markedly higher gene flow or recency of colonisation at the expansion front have likely hindered local adaptation at the time of sampling, as indicated by reduced slopes of genetic-environment associations (GEAs) estimated using a novel application of geographically weighted regression that accounts for allele surfing; GEA slopes are significantly steeper in established parts of the range. Our work bolsters evidence supporting adaptation of invasive species post-introduction and adds novel evidence for differing strengths of evolutionary forces among geographic areas with different invasion histories.

Variant calling and genotyping accuracy of ddRAD-seq: Comparison with 20X WGS in layers

Whole Genome Sequencing (WGS) remains a costly or unsuitable method for routine genotyping of laying hens. Until now, breeding companies have been using or developing SNP chips. Nevertheless, alternatives methods based on sequencing have been developed. Among these, reduced representation sequencing approaches can offer sequencing quality and cost-effectiveness by reducing the genomic regions covered by sequencing. The aim of this study was to evaluate the ability of double digested Restriction site Associated DNA sequencing (ddRAD-seq) to identify and genotype SNPs in laying hens, by comparison with a presumed reliable WGS approach. Firstly, the sensitivity and precision of variant calling and the genotyping reliability of ddRADseq were determined. Next, the SNP Call Rate (CRSNP) and mean depth of sequencing per SNP (DPSNP) were compared between both methods. Finally, the effect of multiple combinations of thresholds for these parameters on genotyping reliability and amount of remaining SNPs in ddRAD-seq was studied. In raw form, the ddRAD-seq identified 349,497 SNPs evenly distributed on the genome with a CRSNP of 0.55, a DPSNP of 11X and a mean genotyping reliability rate per SNP of 80%. Considering genomic regions covered by expected enzymatic fragments (EFs), the sensitivity of the ddRAD-seq was estimated at 32.4% and its precision at 96.4%. The low CRSNP and DPSNP values were explained by the detection of SNPs outside the EFs theoretically generated by the ddRAD-seq protocol. Indeed, SNPs outside the EFs had significantly lower CRSNP (0.25) and DPSNP (1X) values than SNPs within the EFs (0.7 and 17X, resp.). The study demonstrated the relationship between CRSNP, DPSNP, genotyping reliability and the number of SNPs retained, to provide a decision-support tool for defining filtration thresholds. Severe quality control over ddRAD-seq data allowed to retain a minimum of 40% of the SNPs with a CcR of 98%. Then, ddRAD-seq was defined as a suitable method for variant calling and genotyping in layers.

Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools

Introduction

Genotyping large-scale gene bank collections requires an appropriate sampling strategy to represent the diversity within and between accessions.

Methods

A panel of 44 common bean (Phaseolus vulgaris L.) landraces from the Alliance Bioversity and The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) gene bank was genotyped with DArTseq using three sampling strategies: a single plant per accession, 25 individual plants per accession jointly analyzed after genotyping (in silico-pool), and by pooling tissue from 25 individual plants per accession (seq-pool). Sampling strategies were compared to assess the technical aspects of the samples, the marker information content, and the genetic composition of the panel.

Results

The seq-pool strategy resulted in more consistent DNA libraries for quality and call rate, although with fewer polymorphic markers (6,142 single-nucleotide polymorphisms) than the in silico-pool (14,074) or the single plant sets (6,555). Estimates of allele frequencies by seq-pool and in silico-pool genotyping were consistent, but the results suggest that the difference between pools depends on population heterogeneity. Principal coordinate analysis, hierarchical clustering, and the estimation of admixture coefficients derived from a single plant, in silico-pool, and seq-pool successfully identified the well-known structure of Andean and Mesoamerican gene pools of P. vulgaris across all datasets.

Conclusion

In conclusion, seq-pool proved to be a viable approach for characterizing common bean germplasm compared to genotyping individual plants separately by balancing genotyping effort and costs. This study provides insights and serves as a valuable guide for gene bank researchers embarking on genotyping initiatives to characterize their collections. It aids curators in effectively managing the collections and facilitates marker-trait association studies, enabling the identification of candidate markers for key traits.

Missing genotype imputation in non-model species using self-organizing maps

Current methodologies of genome-wide single-nucleotide polymorphism (SNP) genotyping produce large amounts of missing data that may affect statistical inference and bias the outcome of experiments. Genotype imputation is routinely used in well-studied species to buffer the impact in downstream analysis, and several algorithms are available to fill in missing genotypes. The lack of reference haplotype panels precludes the use of these methods in genomic studies on non-model organisms. As an alternative, machine learning algorithms are employed to explore the genotype data and to estimate the missing genotypes. Here, we propose an imputation method based on self-organizing maps (SOM), a widely used neural networks formed by spatially distributed neurons that cluster similar inputs into close neurons. The method explores genotype datasets to select SNP loci to build binary vectors from the genotypes, and initializes and trains neural networks for each query missing SNP genotype. The SOM-derived clustering is then used to impute the best genotype. To automate the imputation process, we have implemented gtImputation, an open-source application programmed in Python3 and with a user-friendly GUI to facilitate the whole process. The method performance was validated by comparing its accuracy, precision and sensitivity on several benchmark genotype datasets with other available imputation algorithms. Our approach produced highly accurate and precise genotype imputations even for SNPs with alleles at low frequency and outperformed other algorithms, especially for datasets from mixed populations with unrelated individuals.

Contrasting effect of hybridization on genetic differentiation in three rockfish species with similar life history

Hybridization can provide evolutionary benefits (e.g., population resilience to climate change) through the introduction of adaptive alleles and increase of genetic diversity. Nevertheless, management strategies may be designed based only on the parental species within a hybrid zone, without considering the hybrids. This can lead to ineffective spatial management of species, which can directly harm population diversity and negatively impact food webs. Three species of rockfish (Brown Rockfish (Sebastes caurinus), Copper Rockfish (S. auriculatus), and Quillback Rockfish (S. maliger)) are known to hybridize within Puget Sound, Washington, but genetic data from these species are used to infer population structure in the entire genus, including in species that do not hybridize. The goal of this project was to estimate the hybridization rates within the region and determine the effect of hybridization on geographic patterns of genetic structure. We sequenced 290 Brown, Copper, and Quillback rockfish using restriction-site associated DNA sequencing (RADseq) from four regions within and outside Puget Sound, Washington. We show that (i) hybridization within Puget Sound was asymmetrical, not recent, widespread among individuals, and relatively low level within the genome, (ii) hybridization affected population structure in Copper and Brown rockfish, but not in Quillback Rockfish and (iii) after taking hybridization into account we found limited directional dispersal in Brown and Copper rockfish, and evidence for two isolated populations in Quillback Rockfish. Our results suggest that rockfish population structure is species-specific, dependent on the extent of hybridization, and cannot be inferred from one species to another despite similar life history.

Variant calling in polyploids for population and quantitative genetics

Advancements in genome assembly and sequencing technology have made whole genome sequence (WGS) data and reference genomes accessible to study polyploid species. Compared to popular reduced-representation sequencing approaches, the genome-wide coverage and greater marker density provided by WGS data can greatly improve our understanding of polyploid species and polyploid biology. However, biological features that make polyploid species interesting also pose challenges in read mapping, variant identification, and genotype estimation. Accounting for characteristics in variant calling like allelic dosage uncertainty, homology between subgenomes, and variance in chromosome inheritance mode can reduce errors. Here, I discuss the challenges of variant calling in polyploid WGS data and discuss where potential solutions can be integrated into a standard variant calling pipeline.

Next-generation data filtering in the genomics era

Genomic data are ubiquitous across disciplines, from agriculture to biodiversity, ecology, evolution and human health. However, these datasets often contain noise or errors and are missing information that can affect the accuracy and reliability of subsequent computational analyses and conclusions. A key step in genomic data analysis is filtering - removing sequencing bases, reads, genetic variants and/or individuals from a dataset - to improve data quality for downstream analyses. Researchers are confronted with a multitude of choices when filtering genomic data; they must choose which filters to apply and select appropriate thresholds. To help usher in the next generation of genomic data filtering, we review and suggest best practices to improve the implementation, reproducibility and reporting standards for filter types and thresholds commonly applied to genomic datasets. We focus mainly on filters for minor allele frequency, missing data per individual or per locus, linkage disequilibrium and Hardy-Weinberg deviations. Using simulated and empirical datasets, we illustrate the large effects of different filtering thresholds on common population genetics statistics, such as Tajima's D value, population differentiation (FST), nucleotide diversity (π) and effective population size (Ne).

Complex patterns of genetic population structure in the mouthbrooding marine catfish, Bagre marinus, in the Gulf of Mexico and U.S. Atlantic

Patterns of genetic variation reflect interactions among microevolutionary forces that vary in strength with changing demography. Here, patterns of variation within and among samples of the mouthbrooding gafftopsail catfish (Bagre marinus, Family Ariidae) captured in the U.S. Atlantic and throughout the Gulf of Mexico were analyzed using genomics to generate neutral and non-neutral SNP data sets. Because genomic resources are lacking for ariids, linkage disequilibrium network analysis was used to examine patterns of putatively adaptive variation. Finally, historical demographic parameters were estimated from site frequency spectra. The results show four differentiated groups, corresponding to the (1) U.S. Atlantic, and the (2) northeastern, (3) northwestern, and (4) southern Gulf of Mexico. The non-neutral data presented two contrasting signals of structure, one due to increases in diversity moving west to east and north to south, and another to increased heterozygosity in the Atlantic. Demographic analysis suggested that recently reduced long-term effective population size in the Atlantic is likely an important driver of patterns of genetic variation and is consistent with a known reduction in population size potentially due to an epizootic. Overall, patterns of genetic variation resemble that of other fishes that use the same estuarine habitats as nurseries, regardless of the presence/absence of a larval phase, supporting the idea that adult/juvenile behavior and habitat are important predictors of contemporary patterns of genetic structure.

Reference Genome Choice and Filtering Thresholds Jointly Influence Phylogenomic Analyses

Molecular phylogenies are a cornerstone of modern comparative biology and are commonly employed to investigate a range of biological phenomena, such as diversification rates, patterns in trait evolution, biogeography, and community assembly. Recent work has demonstrated that significant biases may be introduced into downstream phylogenetic analyses from processing genomic data; however, it remains unclear whether there are interactions among bioinformatic parameters or biases introduced through the choice of reference genome for sequence alignment and variant calling. We address these knowledge gaps by employing a combination of simulated and empirical data sets to investigate the extent to which the choice of reference genome in upstream bioinformatic processing of genomic data influences phylogenetic inference, as well as the way that reference genome choice interacts with bioinformatic filtering choices and phylogenetic inference method. We demonstrate that more stringent minor allele filters bias inferred trees away from the true species tree topology, and that these biased trees tend to be more imbalanced and have a higher center of gravity than the true trees. We find the greatest topological accuracy when filtering sites for minor allele count (MAC) >3-4 in our 51-taxa data sets, while tree center of gravity was closest to the true value when filtering for sites with MAC >1-2. In contrast, filtering for missing data increased accuracy in the inferred topologies; however, this effect was small in comparison to the effect of minor allele filters and may be undesirable due to a subsequent mutation spectrum distortion. The bias introduced by these filters differs based on the reference genome used in short read alignment, providing further support that choosing a reference genome for alignment is an important bioinformatic decision with implications for downstream analyses. These results demonstrate that attributes of the study system and dataset (and their interaction) add important nuance for how best to assemble and filter short-read genomic data for phylogenetic inference.

Low-coverage sequencing and Wahlund effect severely bias estimates of inbreeding, heterozygosity and effective population size in North American wolves

vonHoldt et al. ((2024), Molecular Ecology, 33, e17231) (vH24) used low-coverage (average ~ 7X read depth) restriction site-associated DNA sequence data to estimate individual inbreeding and heterozygosity, and recent effective population size (Ne), in Great Lakes (GL) and Northern Rocky Mountain (RM) wolves. They concluded that RM heterozygosity rapidly declined between 1991 and 2020, and that Ne declined substantially in GL and RM over the last 50 generations. Here, we evaluate the effects of low sequence coverage and sampling strategy on vH24's findings and provide general recommendations for using sequence data to evaluate inbreeding, heterozygosity and Ne. Low-coverage sequencing resulted in downwardly biased estimates of individual inbreeding and heterozygosity, and an erroneous large temporal decline in RM heterozygosity due to declining read depth through time. Additionally, vH24's sampling strategy-which combined individuals from several genetically differentiated populations and across at least eight wolf generations-is expected to have resulted in severe downward bias in estimates of recent Ne for RM. We recommend using high-coverage sequence data (≥ $$ \ge $$ 15-20X) to estimate inbreeding and heterozygosity. Carefully filtering individuals, loci and genotypes, and using genotype imputation or likelihoods can help to minimise bias when low-coverage sequence data must be used. For estimation of contemporary Ne, the marginal benefits of using more than 103-104 loci are small, so aggressive filtering of loci with low average read depth potentially can retain most individuals without sacrificing much precision. Individuals are relatively more valuable than loci because analyses of contemporary Ne should focus on roughly single-generation samples from local breeding populations.

The role of historical biogeography in shaping colour morph diversity in the common wall lizard

The maintenance of polymorphisms often depends on multiple selective forces, but less is known on the role of stochastic or historical processes in maintaining variation. The common wall lizard (Podarcis muralis) is a colour polymorphic species in which local colour morph frequencies are thought to be modulated by natural and sexual selection. Here, we used genome-wide single-nucleotide polymorphism data to investigate the relationships between morph composition and population biogeography at a regional scale, by comparing morph composition with patterns of genetic variation of 54 populations sampled across the Pyrenees. We found that genetic divergence was explained by geographic distance but not by environmental features. Differences in morph composition were associated with genetic and environmental differentiation, as well as differences in sex ratio. Thus, variation in colour morph frequencies could have arisen via historical events and/or differences in the permeability to gene flow, possibly shaped by the complex topography and environment. In agreement with this hypothesis, colour morph diversity was positively correlated with genetic diversity and rates of gene flow and inversely correlated with the likelihood of the occurrence of bottlenecks. Concurrently, we did not find conclusive evidence for selection in the two colour loci. As an illustration of these effects, we observed that populations with higher proportions of the rarer yellow and yellow-orange morphs had higher genetic diversity. Our results suggest that processes involving a decay in overall genetic diversity, such as reduced gene flow and/or bottleneck events have an important role in shaping population-specific morph composition via non-selective processes.

Estimates of heterozygosity from single nucleotide polymorphism markers are context-dependent and often wrong

Genetic diversity is frequently described using heterozygosity, particularly in a conservation context. Often, it is estimated using single nucleotide polymorphisms (SNPs); however, it has been shown that heterozygosity values calculated from SNPs can be biased by both study design and filtering parameters. Though solutions have been proposed to address these issues, our own work has found them to be inadequate in some circumstances. Here, we aimed to improve the reliability and comparability of heterozygosity estimates, specifically by investigating how sample size and missing data thresholds influenced the calculation of autosomal heterozygosity (heterozygosity calculated from across the genome, i.e. fixed and variable sites). We also explored how the standard practice of tri- and tetra-allelic site exclusion could bias heterozygosity estimates and influence eventual conclusions relating to genetic diversity. Across three distinct taxa (a frog, Litoria rubella; a tree, Eucalyptus microcarpa; and a grasshopper, Keyacris scurra), we found heterozygosity estimates to be meaningfully affected by sample size and missing data thresholds, partly due to the exclusion of tri- and tetra-allelic sites. These biases were inconsistent both between species and populations, with more diverse populations tending to have their estimates more severely affected, thus having potential to dramatically alter interpretations of genetic diversity. We propose a modified framework for calculating heterozygosity that reduces bias and improves the utility of heterozygosity as a measure of genetic diversity, whilst also highlighting the need for existing population genetic pipelines to be adjusted such that tri- and tetra-allelic sites be included in calculations.

Clonal genomic population structure of Beauveria brongniartii and Beauveria pseudobassiana: Pathogens of the common European cockchafer (Melolontha melolontha L.)

Beauveria brongniartii is a fungal pathogen that infects the beetle Melolontha melolontha, a significant agricultural pest in Europe. While research has primarily focused on the use of B. brongniartii for controlling M. melolontha, the genomic structure of the B. brongniartii population remains unknown. This includes whether its structure is influenced by its interaction with M. melolontha, the timing of beetle-swarming flights, geographical factors, or reproductive mode. To address this, we analysed genome-wide SNPs to infer the population genomics of Beauveria spp., which were isolated from infected M. melolontha adults in an Alpine region. Surprisingly, only one-third of the isolates were identified as B. brongniartii, while two-thirds were distributed among cryptic taxa within B. pseudobassiana, a fungal species not previously recognized as a pathogen of M. melolontha. Given the prevalence of B. pseudobassiana, we conducted analyses on both species. We found no spatial or temporal genomic patterns within either species and no correlation with the population structure of M. melolontha, suggesting that the dispersal of the fungi is independent of the beetle. Both species exhibited clonal population structures, with B. brongniartii fixed for one mating type and B. pseudobassiana displaying both mating types. This implies that factors other than mating compatibility limit sexual reproduction. We conclude that the population genomic structure of Beauveria spp. is primarily influenced by predominant asexual reproduction and dispersal.

Population genomics of the white-beaked dolphin (Lagenorhynchus albirostris): Implications for conservation amid climate-driven range shifts

Climate change is rapidly affecting species distributions across the globe, particularly in the North Atlantic. For highly mobile and elusive cetaceans, the genetic data needed to understand population dynamics are often scarce. Cold-water obligate species such as the white-beaked dolphin (Lagenorhynchus albirostris) face pressures from habitat shifts due to rising sea surface temperatures in addition to other direct anthropogenic threats. Unravelling the genetic connectivity between white-beaked dolphins across their range is needed to understand the extent to which climate change and anthropogenic pressures may impact species-wide genetic diversity and identify ways to protect remaining habitat. We address this by performing a population genomic assessment of white-beaked dolphins using samples from much of their contemporary range. We show that the species displays significant population structure across the North Atlantic at multiple scales. Analysis of contemporary migration rates suggests a remarkably high connectivity between populations in the western North Atlantic, Iceland and the Barents Sea, while two regional populations in the North Sea and adjacent UK and Irish waters are highly differentiated from all other clades. Our results have important implications for the conservation of white-beaked dolphins by providing guidance for the delineation of more appropriate management units and highlighting the risk that local extirpation may have on species-wide genetic diversity. In a broader context, this study highlights the importance of understanding genetic structure of all species threatened with climate change-driven range shifts to assess the risk of loss of species-wide genetic diversity.

Influence of molecular marker type on estimating effective population size and other genetic parameters in a critically endangered parrot

Genetics is a fast-moving field, and for conservation practitioners or ecologists, it can be bewildering. The choice of marker used in studies is fundamental; in the literature, preference has recently shifted from microsatellites to single nucleotide polymorphism (SNP) loci. Understanding how marker type affects estimates of population genetic parameters is important in the context of conservation, especially because the accuracy of estimates has a bearing on the actions taken to protect threatened species. We compare parameter estimates between seven microsatellites, 3761 SNP loci, and a random subset of 100 SNPs for the exact same 324 individual swift parrots, Lathamus discolor, and also use 457 additional samples from subsequent years to compare SNP estimates. Both marker types estimated a lower H O than H E. We show that microsatellites and SNPs mainly indicate a lack of spatial genetic structure, except when a priori collection locations were used on the SNP data in a discriminant analysis of principal components (DAPC). The 100-SNP subset gave comparable results to when the full dataset was used. Estimates of effective population size (N e) were comparable between markers when the same individuals were considered, but SNPs had narrower confidence intervals. This is reassuring because conservation assessments that rely on population genetic estimates based on a few microsatellites are unlikely to be nullified by the general shift toward SNPs in the literature. However, estimates between markers and datasets varied considerably when only adult samples were considered; hence, including samples of all age groups is recommended to be used when available. The estimated N e was higher for the full SNP dataset (2010-2019) than the smaller comparison data (2010-2015), which might be a better reflection of the species status. The lower precision of microsatellites may not necessarily be a barrier for most conservation applications; however, SNPs will improve confidence limits, which may be useful for practitioners.

Genomic analyses elucidate S-locus evolution in response to intra-specific losses of distyly in Primula vulgaris

Distyly, a floral dimorphism that promotes outcrossing, is controlled by a hemizygous genomic region known as the S-locus. Disruptions of genes within the S-locus are responsible for the loss of distyly and the emergence of homostyly, a floral monomorphism that favors selfing. Using whole-genome resequencing data of distylous and homostylous individuals from populations of Primula vulgaris and leveraging high-quality reference genomes of Primula we tested, for the first time, predictions about the evolutionary consequences of transitions to selfing on S-genes. Our results reveal a previously undetected structural rearrangement in CYPᵀ associated with the shift to homostyly and confirm previously reported, homostyle-specific, loss-of-function mutations in the exons of the S-gene CYPᵀ. We also discovered that the promoter and intronic regions of CYPᵀ in distylous and homostylous individuals are conserved, suggesting that down-regulation of CYPᵀ via mutations in its promoter and intronic regions is not a cause of the shift to homostyly. Furthermore, we found that hemizygosity is associated with reduced genetic diversity in S-genes compared with their paralogs outside the S-locus. Additionally, the shift to homostyly lowers genetic diversity in both the S-genes and their paralogs, as expected in primarily selfing plants. Finally, we tested, for the first time, long-standing theoretical models of changes in S-locus genotypes during early stages of the transition to homostyly, supporting the assumption that two copies of the S-locus might reduce homostyle fitness.

How Can Genomics Help or Hinder Wildlife Conservation?

Genomic data are becoming increasingly affordable and easy to collect, and new tools for their analysis are appearing rapidly. Conservation biologists are interested in using this information to assist in management and planning but are typically limited financially and by the lack of genomic resources available for non-model taxa. It is therefore important to be aware of the pitfalls as well as the benefits of applying genomic approaches. Here, we highlight recent methods aimed at standardizing population assessments of genetic variation, inbreeding, and forms of genetic load and methods that help identify past and ongoing patterns of genetic interchange between populations, including those subjected to recent disturbance. We emphasize challenges in applying some of these methods and the need for adequate bioinformatic support. We also consider the promises and challenges of applying genomic approaches to understand adaptive changes in natural populations to predict their future adaptive capacity.

Hidden in the sand: Phylogenomics unravel an unexpected evolutionary history for the desert-adapted vipers of the genus Cerastes

The desert vipers of the genus Cerastes are a small clade of medically important venomous snakes within the family Viperidae. According to published morphological and molecular studies, the group is comprised by four species: two morphologically similar and phylogenetically sister taxa, the African horned viper (Cerastes cerastes) and the Arabian horned viper (Cerastes gasperettii); a more distantly related species, the Saharan sand viper (Cerastes vipera), and the enigmatic Böhme's sand viper (Cerastes boehmei), only known from a single specimen in captivity allegedly captured in Central Tunisia. In this study, we sequenced one mitochondrial marker (COI) as well as genome-wide data (ddRAD sequencing) from 28 and 41 samples, respectively, covering the entire distribution range of the genus to explore the population genomics, phylogenomic relationships and introgression patterns within the genus Cerastes. Additionally, and to provide insights into the mode of diversification of the group, we carried out niche overlap analyses considering climatic and habitat variables. Both nuclear phylogenomic reconstructions and population structure analyses have unveiled an unexpected evolutionary history for the genus Cerastes, which sharply contradicts the morphological similarities and previously published mitochondrial approaches. Cerastes cerastes and C. vipera are recovered as sister taxa whilst C. gasperettii is a sister taxon to the clade formed by these two species. We found a relatively high niche overlap (OI > 0.7) in both climatic and habitat variables between C. cerastes and C. vipera, contradicting a potential scenario of sympatric speciation. These results are in line with the introgression found between the northwestern African populations of C. cerastes and C. vipera. Finally, our genomic data confirms the existence of a lineage of C. cerastes in Arabia. All these results highlight the importance of genome-wide data over few genetic markers to study the evolutionary history of species.

Genomics and conservation: Guidance from training to analyses and applications

Environmental change is intensifying the biodiversity crisis and threatening species across the tree of life. Conservation genomics can help inform conservation actions and slow biodiversity loss. However, more training, appropriate use of novel genomic methods and communication with managers are needed. Here, we review practical guidance to improve applied conservation genomics. We share insights aimed at ensuring effectiveness of conservation actions around three themes: (1) improving pedagogy and training in conservation genomics including for online global audiences, (2) conducting rigorous population genomic analyses properly considering theory, marker types and data interpretation and (3) facilitating communication and collaboration between managers and researchers. We aim to update students and professionals and expand their conservation toolkit with genomic principles and recent approaches for conserving and managing biodiversity. The biodiversity crisis is a global problem and, as such, requires international involvement, training, collaboration and frequent reviews of the literature and workshops as we do here.

Disease-driven top predator decline affects mesopredator population genomic structure

Top predator declines are pervasive and often have dramatic effects on ecological communities via changes in food web dynamics, but their evolutionary consequences are virtually unknown. Tasmania's top terrestrial predator, the Tasmanian devil, is declining due to a lethal transmissible cancer. Spotted-tailed quolls benefit via mesopredator release, and they alter their behaviour and resource use concomitant with devil declines and increased disease duration. Here, using a landscape community genomics framework to identify environmental drivers of population genomic structure and signatures of selection, we show that these biotic factors are consistently among the top variables explaining genomic structure of the quoll. Landscape resistance negatively correlates with devil density, suggesting that devil declines will increase quoll genetic subdivision over time, despite no change in quoll densities detected by camera trap studies. Devil density also contributes to signatures of selection in the quoll genome, including genes associated with muscle development and locomotion. Our results provide some of the first evidence of the evolutionary impacts of competition between a top predator and a mesopredator species in the context of a trophic cascade. As top predator declines are increasing globally, our framework can serve as a model for future studies of evolutionary impacts of altered ecological interactions.

Genomic insights into the Montseny brook newt (Calotriton arnoldi), a Critically Endangered glacial relict

The Montseny brook newt (Calotriton arnoldi), considered the most endangered amphibian in Europe, is a relict salamandrid species endemic to a small massif located in northeastern Spain. Although conservation efforts should always be guided by genomic studies, those are yet scarce among urodeles, hampered by the extreme sizes of their genomes. Here, we present the third available genome assembly for the order Caudata, and the first genomic study of the species and its sister taxon, the Pyrenean brook newt (Calotriton asper), combining whole-genome and ddRADseq data. Our results reveal significant demographic oscillations which accurately mirrored Europe's climatic history. Although severe bottlenecks have led to depauperate genomic diversity and long runs of homozygosity along a gigantic genome, inbreeding might have been avoided by assortative mating strategies. Other life history traits, however, seem to have been less advantageous, and the lack of land dispersal has driven to exceptional levels of population fragmentation.

Widespread Deviant Patterns of Heterozygosity in Whole-Genome Sequencing Due to Autopolyploidy, Repeated Elements, and Duplication

Most population genomic tools rely on accurate single nucleotide polymorphism (SNP) calling and filtering to meet their underlying assumptions. However, genomic complexity, resulting from structural variants, paralogous sequences, and repetitive elements, presents significant challenges in assembling contiguous reference genomes. Consequently, short-read resequencing studies can encounter mismapping issues, leading to SNPs that deviate from Mendelian expected patterns of heterozygosity and allelic ratio. In this study, we employed the ngsParalog software to identify such deviant SNPs in whole-genome sequencing (WGS) data with low (1.5×) to intermediate (4.8×) coverage for four species: Arctic Char (Salvelinus alpinus), Lake Whitefish (Coregonus clupeaformis), Atlantic Salmon (Salmo salar), and the American Eel (Anguilla rostrata). The analyses revealed that deviant SNPs accounted for 22% to 62% of all SNPs in salmonid datasets and approximately 11% in the American Eel dataset. These deviant SNPs were particularly concentrated within repetitive elements and genomic regions that had recently undergone rediploidization in salmonids. Additionally, narrow peaks of elevated coverage were ubiquitous along all four reference genomes, encompassed most deviant SNPs, and could be partially associated with transposons and tandem repeats. Including these deviant SNPs in genomic analyses led to highly distorted site frequency spectra, underestimated pairwise FST values, and overestimated nucleotide diversity. Considering the widespread occurrence of deviant SNPs arising from a variety of sources, their important impact in estimating population parameters, and the availability of effective tools to identify them, we propose that excluding deviant SNPs from WGS datasets is required to improve genomic inferences for a wide range of taxa and sequencing depths.

PoolParty2: An integrated pipeline for analysing pooled or indexed low-coverage whole-genome sequencing data to discover the genetic basis of diversity

Whole-genome sequencing data allow survey of variation from across the genome, reducing the constraint of balancing genome sub-sampling with estimating recombination rates and linkage between sampled markers and target loci. As sequencing costs decrease, low-coverage whole-genome sequencing of pooled or indexed-individual samples is commonly utilized to identify loci associated with phenotypes or environmental axes in non-model organisms. There are, however, relatively few publicly available bioinformatic pipelines designed explicitly to analyse these types of data, and fewer still that process the raw sequencing data, provide useful metrics of quality control and then execute analyses. Here, we present an updated version of a bioinformatics pipeline called PoolParty2 that can effectively handle either pooled or indexed DNA samples and includes new features to improve computational efficiency. Using simulated data, we demonstrate the ability of our pipeline to recover segregating variants, estimate their allele frequencies accurately, and identify genomic regions harbouring loci under selection. Based on the simulated data set, we benchmark the efficacy of our pipeline with another bioinformatic suite, angsd, and illustrate the compatibility and complementarity of these suites using angsd to generate genotype likelihoods as input for identifying linkage outlier regions using alignment files and variants provided by PoolParty2. Finally, we apply our updated pipeline to an empirical dataset of low-coverage whole genomic data from population samples of Columbia River steelhead trout (Oncorhynchus mykiss), results from which demonstrate the genomic impacts of decades of artificial selection in a prominent hatchery stock. Thus, we not only demonstrate the utility of PoolParty2 for genomic studies that combine sequencing data from multiple individuals, but also illustrate how it compliments other bioinformatics resources such as angsd.

Genomic evidence of sex chromosome aneuploidy and infection-associated genotypes in the tsetse fly Glossina fuscipes, the major vector of African trypanosomiasis in Uganda

The primary vector of the trypanosome parasite causing human and animal African trypanosomiasis in Uganda is the riverine tsetse fly Glossina fuscipes fuscipes (Gff). Our study improved the Gff genome assembly with whole genome 10× Chromium sequencing of a lab reared pupae, identified autosomal versus sex-chromosomal regions of the genome with ddRAD-seq data from 627 field caught Gff, and identified SNPs associated with trypanosome infection with genome-wide association (GWA) analysis in a subset of 351 flies. Results from 10× Chromium sequencing greatly improved Gff genome assembly metrics and assigned a full third of the genome to the sex chromosome. Results from ddRAD-seq suggested possible sex-chromosome aneuploidy in Gff and identified a single autosomal SNP to be highly associated with trypanosome infection. The top associated SNP was ∼1100 bp upstream of the gene lecithin cholesterol acyltransferase (LCAT), an important component of the molecular pathway that initiates trypanosome lysis and protection in mammals. Results suggest that there may be naturally occurring genetic variation in Gff in genomic regions in linkage disequilibrium with LCAT that can protect against trypanosome infection, thereby paving the way for targeted research into novel vector control strategies that can promote parasite resistance in natural populations.

Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

BACKGROUND

Producing animal protein while reducing the animal's impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible.

RESULTS

Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets.

CONCLUSIONS

Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual's future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.

Genetic diversity and signature of divergence in the genome of grapevine clones of Southern Italy varieties

Sexual reproduction has contributed to a significant degree of variability in cultivated grapevine populations. However, the additional influence of spontaneous somatic mutations has played a pivotal role in shaping the diverse landscape of grapevine agrobiodiversity. These naturally occurring selections, termed 'clones,' represent a vast reservoir of potentially valuable traits and alleles that hold promise for enhancing grape quality and bolstering plant resilience against environmental and biotic challenges. Despite their potential, many of these clones remain largely untapped.In light of this context, this study aims to delve into the population structure, genetic diversity, and distinctive genetic loci within a collection of 138 clones derived from six Campanian and Apulian grapevine varieties, known for their desirable attributes in viticulture and winemaking. Employing two reduced representation sequencing methods, we extracted Single-Nucleotide Polymorphism (SNP) markers. Population structure analysis and fixation index (FST) calculations were conducted both between populations and at individual loci. Notably, varieties originating from the same geographical region exhibited pronounced genetic similarity.The resulting SNP dataset facilitated the identification of approximately two hundred loci featuring divergent markers (FST ≥ 0.80) within annotated exons. Several of these loci exhibited associations with essential traits like phenotypic adaptability and environmental responsiveness, offering compelling opportunities for grapevine breeding initiatives. By shedding light on the genetic variability inherent in these treasured traditional grapevines, our study contributes to the broader understanding of their potential. Importantly, it underscores the urgency of preserving and characterizing these valuable genetic resources to safeguard their intra-varietal diversity and foster future advancements in grapevine cultivation.

Genetic structure and relatedness of brown trout (Salmo trutta) populations in the drainage basin of the Ölfusá river, South-Western Iceland

Background

Lake Þingvallavatn in Iceland, a part of the river Ölfusá drainage basin, was presumably populated by brown trout soon after it formed at the end of the last Ice Age. The genetic relatedness of the brown trout in Þingvallavatn to other populations in the Ölfusá drainage basin is unknown. After the building of a dam at the outlet of the lake in 1959 brown trout catches declined, though numbers have now increased. The aim of this study was to assess effects of geographic isolation and potential downstream gene flow on the genetic structure and diversity in brown trout sampled in several locations in the western side of the watershed of River Ölfusá. We hypothesized that brown trout in Lake Þingvallavatn constituted several local spawning populations connected by occasional gene flow before the damming of the lake. We also estimated the effective population size (NE) of some of these populations and tested for signs of a recent population bottleneck in Lake Þingvallavatn.

Methods

We sampled brown trout inhabiting four lakes and 12 rivers within and near the watershed of River Ölfusá by means of electro- and net- fishing. After stringent data filtering, 2,597 polymorphic loci obtained from ddRADseq data from 317 individuals were ascertained as putative neutral markers.

Results

Overall, the genetic relatedness of brown trout in the Ölfusá watershed reflected the connectivity and topography of the waterways. Ancestry proportion analyses and a phylogenetic tree revealed seven distinct clusters, some of which corresponded to small populations with reduced genetic diversity. There was no evidence of downstream gene flow from Lake Þingvallavatn, although gene flow was observed from much smaller mountain populations. Most locations showed low NE values (i.e., ~14.6 on average) while the putative anadromous trout from River Sog and the spawning population from River Öxará, that flows into Lake Þingvallavatn, showed notably higher NE values (i.e., 71.2 and 56.5, respectively). No signals of recent population bottlenecks were detected in the brown trout of Lake Þingvallavatn.

Discussion

This is the first time that the genetic structure and diversity of brown trout in the watershed of River Ölfusá have been assessed. Our results point towards the presence of a metapopulation in the watershed of Lake Þingvallavatn, which has been influenced by restoration efforts and is now dominated by a genetic component originated in River Öxará. Many of the locations studied represent different populations. Those that are isolated in headwater streams and lakes are genetically distinct presenting low genetic diversity, yet they can be important in increasing the genetic variation in downstream populations. These populations should be considered for conservation and direct management.

Philopatry influences the genetic population structure of the blacktip shark (Carcharhinus limbatus) at multiple spatial scales

Understanding how interactions among microevolutionary forces generate genetic population structure of exploited species is vital to the implementation of management policies that facilitate persistence. Philopatry displayed by many coastal shark species can impact gene flow and facilitate selection, and has direct implications for the spatial scales of management. Here, genetic structure of the blacktip shark (Carcharhinus limbatus) was examined using a mixed-marker approach employing mitochondrial control region sequences and 4339 SNP-containing loci generated using ddRAD-Seq. Genetic variation was assessed among young-of-the-year sampled in 11 sites in waters of the United States in the western North Atlantic Ocean, including the Gulf of Mexico. Spatial and environmental analyses detected 68 nuclear loci putatively under selection, enabling separate assessments of neutral and adaptive genetic structure. Both mitochondrial and neutral SNP data indicated three genetically distinct units-the Atlantic, eastern Gulf, and western Gulf-that align with regional stocks and suggest regional philopatry by males and females. Heterogeneity at loci putatively under selection, associated with temperature and salinity, was observed among sites within Gulf units, suggesting local adaptation. Furthermore, five pairs of siblings were identified in the same site across timescales corresponding with female reproductive cycles. This indicates that females re-used a site for parturition, which has the potential to facilitate the sorting of adaptive variation among neighbouring sites. The results demonstrate differential impacts of microevolutionary forces at varying spatial scales and highlight the importance of conserving essential habitats to maintain sources of adaptive variation that may buffer species against environmental change.

What Darwin could not see: island formation and historical sea levels shape genetic divergence and island biogeography in a coastal marine species

Oceanic islands play a central role in the study of evolution and island biogeography. The Galapagos Islands are one of the most studied oceanic archipelagos but research has almost exclusively focused on terrestrial organisms compared to marine species. Here we used the Galapagos bullhead shark (Heterodontus quoyi) and single nucleotide polymorphisms (SNPs) to examine evolutionary processes and their consequences for genetic divergence and island biogeography in a shallow-water marine species without larval dispersal. The sequential separation of individual islands from a central island cluster gradually established different ocean depths between islands that pose barriers to dispersal in H. quoyi. Isolation by resistance analysis suggested that ocean bathymetry and historical sea level fluctuations modified genetic connectivity. These processes resulted in at least three genetic clusters that exhibit low genetic diversity and effective population sizes that scale with island size and the level of geographic isolation. Our results exemplify that island formation and climatic cycles shape genetic divergence and biogeography of coastal marine organisms with limited dispersal comparable to terrestrial taxa. Because similar scenarios exist in oceanic islands around the globe our research provides a new perspective on marine evolution and biogeography with implications for the conservation of island biodiversity.

Scaling-up RADseq methods for large datasets of non-invasive samples: Lessons for library construction and data preprocessing

Genetic non-invasive sampling (gNIS) is a critical tool for population genetics studies, supporting conservation efforts while imposing minimal impacts on wildlife. However, gNIS often presents variable levels of DNA degradation and non-endogenous contamination, which can incur considerable processing costs. Furthermore, the use of restriction-site-associated DNA sequencing methods (RADseq) for assessing thousands of genetic markers introduces the challenge of obtaining large sets of shared loci with similar coverage across multiple individuals. Here, we present an approach to handling large-scale gNIS-based datasets using data from the spotted hyena population inhabiting the Ngorongoro Crater in Tanzania. We generated 3RADseq data for more than a thousand individuals, mostly from faecal mucus samples collected non-invasively and varying in DNA degradation and contamination level. Using small-scale sequencing, we screened samples for endogenous DNA content, removed highly contaminated samples, confirmed overlap fragment length between libraries, and balanced individual representation in a sequencing pool. We evaluated the impact of (1) DNA degradation and contamination of non-invasive samples, (2) PCR duplicates and (3) different SNP filters on genotype accuracy based on Mendelian error estimated for parent-offspring trio datasets. Our results showed that when balanced for sequencing depth, contaminated samples presented similar genotype error rates to those of non-contaminated samples. We also showed that PCR duplicates and different SNP filters impact genotype accuracy. In summary, we showed the potential of using gNIS for large-scale genetic monitoring based on SNPs and demonstrated how to improve control over library preparation by using a weighted re-pooling strategy that considers the endogenous DNA content.

Recent evolution of flowering time across multiple European plant species correlates with changes in aridity

Ongoing global warming and increasing drought frequencies impact plant populations and potentially drive rapid evolutionary adaptations. Historical comparisons, where plants grown from seeds collected in the past are compared to plants grown from freshly collected seeds from populations of the same sites, are a powerful method to investigate recent evolutionary changes across many taxa. We used 21-38 years old seeds of 13 European plant species, stored in seed banks and originating from Mediterranean and temperate regions, together with recently collected seeds from the same sites for a greenhouse experiment to investigate shifts in flowering phenology as a potential result of adaptive evolution to changes in drought intensities over the last decades. We further used single nucleotide polymorphism (SNP) markers to quantify relatedness and levels of genetic variation. We found that, across species, current populations grew faster and advanced their flowering. These shifts were correlated with changes in aridity at the population origins, suggesting that increased drought induced evolution of earlier flowering, whereas decreased drought lead to weak or inverse shifts in flowering phenology. In five out of the 13 species, however, the SNP markers detected strong differences in genetic variation and relatedness between the past and current populations collected, indicating that other evolutionary processes may have contributed to changes in phenotypes. Our results suggest that changes in aridity may have influenced the evolutionary trajectories of many plant species in different regions of Europe, and that flowering phenology may be one of the key traits that is rapidly evolving.

Genomic evidence indicates small island-resident populations and sex-biased behaviors of Hawaiian reef Manta Rays

BACKGROUND

Reef manta rays (Mobula alfredi) are globally distributed in tropical and subtropical seas. Their life history traits (slow growth, late maturity, low reproductive output) make them vulnerable to perturbations and therefore require informed management strategies. Previous studies have reported wide-spread genetic connectivity along continental shelves suggesting high gene flow along continuous habitats spanning hundreds of kilometers. However, in the Hawaiian Islands, tagging and photo-identification evidence suggest island populations are isolated despite proximity, a hypothesis that has not yet been evaluated with genetic data.

RESULTS

This island-resident hypothesis was tested by analyzing whole mitogenome haplotypes and 2048 nuclear single nucleotide polymorphisms (SNPs) between M. alfredi (n = 38) on Hawai'i Island and Maui Nui (the 4-island complex of Maui, Moloka'i, Lāna'i and Kaho'olawe). Strong divergence in the mitogenome (ΦST = 0.488) relative to nuclear genome-wide SNPs (neutral FST = 0.003; outlier FST = 0.186), and clustering of mitochondrial haplotypes among islands provides robust evidence that female reef manta rays are strongly philopatric and do not migrate between these two island groups. Combined with restricted male-mediated migration, equivalent to a single male moving between islands every 2.2 generations (~ 64 years), we provide evidence these populations are significantly demographically isolated. Estimates of contemporary effective population size (Ne) are 104 (95% CI: 99-110) in Hawai'i Island and 129 (95% CI: 122-136) in Maui Nui.

CONCLUSIONS

Concordant with evidence from photo identification and tagging studies, these genetic results indicate reef manta rays in Hawai'i have small, genetically-isolated resident island populations. We hypothesize that due to the Island Mass Effect, large islands provide sufficient resources to support resident populations, thereby making crossing deep channels separating island groups unnecessary. Small effective population size, low genetic diversity, and k-selected life history traits make these isolated populations vulnerable to region-specific anthropogenic threats, which include entanglement, boat strikes, and habitat degradation. The long-term persistence of reef manta rays in the Hawaiian Islands will require island-specific management strategies.

Responses of population structure and genomic diversity to climate change and fishing pressure in a pelagic fish

The responses of marine species to environmental changes and anthropogenic pressures (e.g., fishing) interact with ecological and evolutionary processes that are not well understood. Knowledge of changes in the distribution range and genetic diversity of species and their populations into the future is essential for the conservation and sustainable management of resources. Almaco jack (Seriola rivoliana) is a pelagic fish with high importance to fisheries and aquaculture in the Pacific Ocean. In this study, we assessed contemporary genomic diversity and structure in loci that are putatively under selection (outlier loci) and determined their potential functions. Using a combination of genotype-environment association, spatial distribution models, and demogenetic simulations, we modeled the effects of climate change (under three different RCP scenarios) and fishing pressure on the species' geographic distribution and genomic diversity and structure to 2050 and 2100. Our results show that most of the outlier loci identified were related to biological and metabolic processes that may be associated with temperature and salinity. The contemporary genomic structure showed three populations-two in the Eastern Pacific (Cabo San Lucas and Eastern Pacific) and one in the Central Pacific (Hawaii). Future projections suggest a loss of suitable habitat and potential range contractions for most scenarios, while fishing pressure decreased population connectivity. Our results suggest that future climate change scenarios and fishing pressure will affect the genomic structure and genotypic composition of S. rivoliana and lead to loss of genomic diversity in populations distributed in the eastern-central Pacific Ocean, which could have profound effects on fisheries that depend on this resource.

Diversification processes in Gerp's mouse lemur demonstrate the importance of rivers and altitude as biogeographic barriers in Madagascar's humid rainforests

Madagascar exhibits exceptionally high levels of biodiversity and endemism. Models to explain the diversification and distribution of species in Madagascar stress the importance of historical variability in climate conditions which may have led to the formation of geographic barriers by changing water and habitat availability. The relative importance of these models for the diversification of the various forest-adapted taxa of Madagascar has yet to be understood. Here, we reconstructed the phylogeographic history of Gerp's mouse lemur (Microcebus gerpi) to identify relevant mechanisms and drivers of diversification in Madagascar's humid rainforests. We used restriction site associated DNA (RAD) markers and applied population genomic and coalescent-based techniques to estimate genetic diversity, population structure, gene flow and divergence times among M. gerpi populations and its two sister species M. jollyae and M. marohita. Genomic results were complemented with ecological niche models to better understand the relative barrier function of rivers and altitude. We show that M. gerpi diversified during the late Pleistocene. The inferred ecological niche, patterns of gene flow and genetic differentiation in M. gerpi suggest that the potential for rivers to act as biogeographic barriers depended on both size and elevation of headwaters. Populations on opposite sides of the largest river in the area with headwaters that extend far into the highlands show particularly high genetic differentiation, whereas rivers with lower elevation headwaters have weaker barrier functions, indicated by higher migration rates and admixture. We conclude that M. gerpi likely diversified through repeated cycles of dispersal punctuated by isolation to refugia as a result of paleoclimatic fluctuations during the Pleistocene. We argue that this diversification scenario serves as a model of diversification for other rainforest taxa that are similarly limited by geographic factors. In addition, we highlight conservation implications for this critically endangered species, which faces extreme habitat loss and fragmentation.

Empirical landscape genetic comparison of single nucleotide polymorphisms and microsatellites in three arid-zone mammals with high dispersal capacity

Landscape genetics is increasingly transitioning away from microsatellites, with single nucleotide polymorphisms (SNPs) providing increased resolution for detecting patterns of spatial-genetic structure. This is particularly pertinent for research in arid-zone mammals due to challenges associated with unique life history traits, such as boom-bust population dynamics and long-distance dispersal capacities. Here, we provide a case study comparing SNPs versus microsatellites for testing three explicit landscape genetic hypotheses (isolation-by-distance, isolation-by-barrier, and isolation-by-resistance) in a suite of small, arid-zone mammals in the Pilbara region of Western Australia. Using clustering algorithms, Mantel tests, and linear mixed effects models, we compare functional connectivity between genetic marker types and across species, including one marsupial, Ningaui timealeyi, and two native rodents, Pseudomys chapmani and P. hermannsburgensis. SNPs resolved subtle genetic structuring not detected by microsatellites, particularly for N. timealeyi where two genetic clusters were identified. Furthermore, stronger signatures of isolation-by-distance and isolation-by-resistance were detected when using SNPs, and model selection based on SNPs tended to identify more complex resistance surfaces (i.e., composite surfaces of multiple environmental layers) in the best-performing models. While we found limited evidence for physical barriers to dispersal across the Pilbara for all species, we found that topography, substrate, and soil moisture were the main environmental drivers shaping functional connectivity. Our study demonstrates that new analytical and genetic tools can provide novel ecological insights into arid landscapes, with potential application to conservation management through identifying dispersal corridors to mediate the impacts of ongoing habitat fragmentation in the region.

When One's Not Enough: Colony Pool-Seq Outperforms Individual-Based Methods for Assessing Introgression in Apis mellifera mellifera

The human management of honey bees (Apis mellifera) has resulted in the widespread introduction of subspecies outside of their native ranges. One well known example of this is Apis mellifera mellifera, native to Northern Europe, which has now been significantly introgressed by the introduction of C lineage honey bees. Introgression has consequences for species in terms of future adaptive potential and long-term viability. However, estimating introgression in colony-living haplodiploid species is challenging. Previous studies have estimated introgression using individual workers, individual drones, multiple drones, and pooled workers. Here, we compare introgression estimates via three genetic approaches: SNP array, individual RAD-seq, and pooled colony RAD-seq. We also compare two statistical approaches: a maximum likelihood cluster program (ADMIXTURE) and an incomplete lineage sorting model (ABBA BABA). Overall, individual approaches resulted in lower introgression estimates than pooled colonies when using ADMIXTURE. However, the pooled colony ABBA BABA approach resulted in generally lower introgression estimates than all three ADMIXTURE estimates. These results highlight that sometimes one individual is not enough to assess colony-level introgression, and future studies that do use colony pools should not be solely dependent on clustering programs for introgression estimates.

Mitochondrial Heteroplasmy and PCR Amplification Bias Lead to Wrong Species Delimitation with High Confidence in the South American and Antarctic Marine Bivalve Aequiyoldia eightsii Species Complex

The species delimitation of the marine bivalve species complex Aequiyoldia eightsii in South America and Antarctica is complicated by mitochondrial heteroplasmy and amplification bias in molecular barcoding. In this study, we compare different data sources (mitochondrial cytochrome c oxidase subunit I (COI) sequences; nuclear and mitochondrial SNPs). Whilst all the data suggest that populations on either side of the Drake Passage belong to different species, the picture is less clear within Antarctic populations, which harbor three distinct mitochondrial lineages (p-dist ≈ 6%) that coexist in populations and in a subset of individuals with heteroplasmy. Standard barcoding procedures lead to amplification bias favoring either haplotype unpredictably and thus overestimate the species richness with high confidence. However, nuclear SNPs show no differentiation akin to the trans-Drake comparison, suggesting that the Antarctic populations represent a single species. Their distinct haplotypes likely evolved during periods of temporary allopatry, whereas recombination eroded similar differentiation patterns in the nuclear genome after secondary contact. Our study highlights the importance of using multiple data sources and careful quality control measures to avoid bias and increase the accuracy of molecular species delimitation. We recommend an active search for mitochondrial heteroplasmy and haplotype-specific primers for amplification in DNA-barcoding studies.

Environmental selection, rather than neutral processes, best explain regional patterns of diversity in a tropical rainforest fish

To conserve the high functional and genetic variation in hotspots such as tropical rainforests, it is essential to understand the forces driving and maintaining biodiversity. We asked to what extent environmental gradients and terrain structure affect morphological and genomic variation across the wet tropical distribution of an Australian rainbowfish, Melanotaenia splendida splendida. We used an integrative riverscape genomics and morphometrics framework to assess the influence of these factors on both putative adaptive and non-adaptive spatial divergence. We found that neutral genetic population structure was largely explainable by restricted gene flow among drainages. However, environmental associations revealed that ecological variables had a similar power to explain overall genetic variation, and greater power to explain body shape variation, than the included neutral covariables. Hydrological and thermal variables were the strongest environmental predictors and were correlated with traits previously linked to heritable habitat-associated dimorphism in rainbowfishes. In addition, climate-associated genetic variation was significantly associated with morphology, supporting heritability of shape variation. These results support the inference of evolved functional differences among localities, and the importance of hydroclimate in early stages of diversification. We expect that substantial evolutionary responses will be required in tropical rainforest endemics to mitigate local fitness losses due to changing climates.

2b or not 2b? 2bRAD is an effective alternative to ddRAD for phylogenomics

Restriction-site-associated DNA sequencing (RADseq) has become an accessible way to obtain genome-wide data in the form of single-nucleotide polymorphisms (SNPs) for phylogenetic inference. Nonetheless, how differences in RADseq methods influence phylogenetic estimation is poorly understood because most comparisons have largely relied on conceptual predictions rather than empirical tests. We examine how differences in ddRAD and 2bRAD data influence phylogenetic estimation in two non-model frog groups. We compare the impact of method choice on phylogenetic information, missing data, and allelic dropout, considering different sequencing depths. Given that researchers must balance input (funding, time) with output (amount and quality of data), we also provide comparisons of laboratory effort, computational time, monetary costs, and the repeatability of library preparation and sequencing. Both 2bRAD and ddRAD methods estimated well-supported trees, even at low sequencing depths, and had comparable amounts of missing data, patterns of allelic dropout, and phylogenetic signal. Compared to ddRAD, 2bRAD produced more repeatable datasets, had simpler laboratory protocols, and had an overall faster bioinformatics assembly. However, many fewer parsimony-informative sites per SNP were obtained from 2bRAD data when using native pipelines, highlighting a need for further investigation into the effects of each pipeline on resulting datasets. Our study underscores the importance of comparing RADseq methods, such as expected results and theoretical performance using empirical datasets, before undertaking costly experiments.

GRAS-Di SNP-based molecular characterization and fingerprinting of a Turkish Corylus avellana core set provide insights into the cultivation and breeding of hazelnut in Turkey

Hazelnut (Corylus avellana L.) is an economically and socially important product for Turkey, the country that leads global production of this crop. The preservation of Turkish hazelnut genetic diversity and informed breeding of new cultivars are crucial for maintaining quality and crop yield stability. In this study, genotyping by random amplicon sequencing (GRAS-Di) was used to identify single-nucleotide polymorphisms (SNPs) in a panel of 96 individuals representing the Turkish national hazelnut collection. The resulting 7609 high-quality SNPs were physically mapped to the Tombul cultivar reference genome and used for population structure and diversity analyses. These analyses revealed that cultivars are not less diverse than wild accessions and that 44% of the panel had admixed ancestry. The results also indicated that recently released Turkish cultivars are highly similar to each other, suggesting that diversity analysis is an important tool that should be employed to prevent future genetic bottlenecks in this crop. A minimal marker algorithm was used to select a set of seven SNP markers that were capable of differentiating the panel accessions. These fingerprinting markers should be useful for the propagation of true-to-type elite cultivars that can be used to renew Turkey's aging hazelnut orchards.

Inferring population connectivity in eastern massasauga rattlesnakes (Sistrurus catenatus) using landscape genetics

Assessing the environmental factors that influence the ability of a threatened species to move through a landscape can be used to identify conservation actions that connect isolated populations. However, direct observations of species' movement are often limited, making the development of alternate approaches necessary. Here we use landscape genetic analyses to assess the impact of landscape features on the movement of individuals between local populations of a threatened snake, the eastern massasauga rattlesnake (Sistrurus catenatus). We linked connectivity data with habitat information from two landscapes of similar size: a large region of unfragmented habitat and a previously studied fragmented landscape consisting of isolated patches of habitat. We used this analysis to identify features of the landscape where modification or acquisition would enhance population connectivity in the fragmented region. We found evidence that current connectivity was impacted by both contemporary land-cover features, especially roads, and inherent landscape features such as elevation. Next, we derived estimates of expected movement ability using a recently developed pedigree-based approach and least-cost paths through the unfragmented landscape. We then used our pedigree and resistance map to estimate resistance polygons of the potential extent for S. catenatus movement in the fragmented landscape. These polygons identify possible sites for future corridors connecting currently isolated populations in this landscape by linking the impact of future habitat modification or land acquisition to dispersal ability in this species. Overall, our study shows how modeling landscape resistance across differently fragmented landscapes can identify habitat features that affect contemporary movement in threatened species in fragmented landscapes and how this information can be used to guide mitigation actions whose goal is to connect isolated populations.

Rapid introgression of non-native alleles following hybridization between a native Anolis lizard species and a cryptic invader across an urban landscape

Invasive species can impact native populations through competition, predation, habitat alteration, and disease transmission, but also genetically through hybridization. Potential outcomes of hybridization span the continuum from extinction to hybrid speciation and can be further complicated by anthropogenic habitat disturbance. Hybridization between the native green anole lizard (Anolis carolinensis) and a morphologically similar invader (A. porcatus) in south Florida provides an ideal opportunity to study interspecific admixture across a heterogeneous landscape. We used reduced-representation sequencing to describe introgression in this hybrid system and to test for a relationship between urbanization and non-native ancestry. Our findings indicate that hybridization between green anole lineages was probably a limited, historic event, producing a hybrid population characterized by a diverse continuum of ancestry proportions. Genomic cline analyses revealed rapid introgression and disproportionate representation of non-native alleles at many loci and no evidence for reproductive isolation between parental species. Three loci were associated with urban habitat characteristics; urbanization and non-native ancestry were positively correlated, although this relationship did not remain significant when accounting for spatial nonindependence. Ultimately, our study demonstrates the persistence of non-native genetic material even in the absence of ongoing immigration, indicating that selection favouring non-native alleles can override the demographic limitation of low propagule pressure. We also note that not all outcomes of admixture between native and non-native species should be considered intrinsically negative. Hybridization with ecologically robust invaders can lead to adaptive introgression, which may facilitate the long-term survival of native populations otherwise unable to adapt to anthropogenically mediated global change.

Large effective population size masks population genetic structure in Hirondellea amphipods within the deepest marine ecosystem, the Mariana Trench

The examination of genetic structure in the deep-ocean hadal zone has focused on divergence between tectonic trenches to understand how environment and geography may drive species divergence and promote endemism. There has been little attempt to examine localized genetic structure within trenches, partly because of logistical challenges associated with sampling at an appropriate scale, and the large effective population sizes of species that can be sampled adequately may mask underlying genetic structure. Here we examine genetic structure in the superabundant amphipod Hirondellea gigas in the Mariana Trench at depths of 8126-10,545 m. RAD sequencing was used to identify 3182 loci containing 43,408 single nucleotide polymorphisms (SNPs) across individuals after stringent pruning of loci to prevent paralogous multicopy genomic regions being erroneously merged. Principal components analysis of SNP genotypes resolved no genetic structure between sampling locations, consistent with a signature of panmixia. However, discriminant analysis of principal components identified divergence between all sites driven by 301 outlier SNPs in 169 loci and significantly associated with latitude and depth. Functional annotation of loci identified differences between singleton loci used in analysis and paralogous loci pruned from the data set and also between outlier and nonoutlier loci, all consistent with hypotheses explaining the role of transposable elements driving genome dynamics. This study challenges the traditional perspective that highly abundant amphipods within a trench form a single panmictic population. We discuss the findings in relation to eco-evolutionary and ontogenetic processes operating in the deep sea, and highlight key challenges associated with population genetic analysis in nonmodel systems with inherent large effective population sizes and genomes.

Evolution of pathogenicity-associated genes in Rhizoctonia solani AG1-IA by genome duplication and transposon-mediated gene function alterations

BACKGROUND

Rhizoctonia solani is a polyphagous fungal pathogen that causes diseases in crops. The fungal strains are classified into anastomosis groups (AGs); however, genomic complexity, diversification into the AGs and the evolution of pathogenicity-associated genes remain poorly understood.

RESULTS

We report a recent whole-genome duplication and sequential segmental duplications in AG1-IA strains of R. solani. Transposable element (TE) clusters have caused loss of synteny in the duplicated blocks and introduced differential structural alterations in the functional domains of several pathogenicity-associated paralogous gene pairs. We demonstrate that the TE-mediated structural variations in a glycosyl hydrolase domain and a GMC oxidoreductase domain in two paralogous pairs affect the pathogenicity of R. solani. Furthermore, to investigate the association of TEs with the natural selection and evolution of pathogenicity, we sequenced the genomes of forty-two rice field isolates of R. solani AG1-IA. The genomic regions with high population mutation rates and with the lowest nucleotide diversity are enriched with TEs. Genetic diversity analysis predicted the genes that are most likely under diversifying and purifying selections. We present evidence that a smaller variant of a glucosamine phosphate N-acetyltransferase (GNAT) protein, predicted to be under purifying selection, and an LPMP_AA9 domain-containing protein, predicted to be under diversifying selection, are important for the successful pathogenesis of R. solani in rice as well as tomato.

CONCLUSIONS

Our study has unravelled whole-genome duplication, TE-mediated neofunctionalization of genes and evolution of pathogenicity traits in R. solani AG1-IA. The pathogenicity-associated genes identified during the study can serve as novel targets for disease control.

Inferring inter-colony movement within metapopulations of yellow-footed rock-wallabies using estimates of kinship

Understanding the exchange of individuals between wildlife populations, particularly those with naturally fragmented habitats, is important for the effective management of these species. This is of particular consequence when the species is of conservation concern, and isolated populations may be lost due to pressures from predation or competition, or catastrophic events such as wildfire. Here we demonstrate the use kinship and population structure analysis to show potential recent movement between colonies in metapopulations of yellow-footed rock-wallaby (Petrogale xanthopus Gray 1854) at two sites in the Grey Range of Queensland, and at four sites in the Gawler Ranges of South Australia. These colonies are also compared to a single colony from the Flinders Ranges, a connected landscape of rock-wallaby habitat. Using reduced representation next-generation sequencing, we acquired and filtered a set of ~ 17,000 single-nucleotide polymorphisms to examine population genetic variation, structure and relationships within populations, and also identify putative migrants. Initial STRUCTURE analysis re-confirmed each population should be considered separately. Tests of population genetic variation identify several colonies appearing to be experiencing genetic erosion, also with low calculated effective population sizes (Ne = 4.5–36.6). Pairwise comparisons of individual relatedness (relatedness coeffiecients; r) implied several contemporary movement events between colonies within both the Gawler and Grey Ranges (r > 0.125), which was then affirmed with tests for putative first generation migrants. These results are of particular note in South Australia, where threat abatement (management of key predators and competitors) may facilitate dispersion. Additionally, in Queensland, colonies are separated by anthropogenic barriers: predator exclusion fencing designed to exclude dingoes (Canis familiaris) from grazing land, which may hinder dispersal. This work highlights the usefulness of population genetics to inform management outcomes in wildlife, in this case, highlighting the need for threatened species management at the landscape level.

Range‐wide population genomics of the spongy moth, Lymantria dispar (Erebidae): Implications for biosurveillance, subspecies classification and phylogeography of a destructive moth

The spongy moth, Lymantria dispar, is an irruptive forest pest native to Eurasia where its range extends from coast to coast and overspills into northern Africa. Accidentally introduced from Europe in Massachusetts in 1868-1869, it is now established in North America where it is considered a highly destructive invasive pest. A fine-scale characterization of its population genetic structure would facilitate identification of source populations for specimens intercepted during ship inspections in North America and would enable mapping of introduction pathways to help prevent future incursions into novel environments. In addition, detailed knowledge of L. dispar's global population structure would provide new insight into the adequacy of its current subspecies classification system and its phylogeographic history. To address these issues, we generated >2000 genotyping-by-sequencing-derived SNPs from 1445 contemporary specimens sampled at 65 locations in 25 countries/3 continents. Using multiple analytical approaches, we identified eight subpopulations that could be further partitioned into 28 groups, achieving unprecedented resolution for this species' population structure. Although reconciliation between these groupings and the three currently recognized subspecies proved to be challenging, our genetic data confirmed circumscription of the japonica subspecies to Japan. However, the genetic cline observed across continental Eurasia, from L. dispar asiatica in East Asia to L. d. dispar in Western Europe, points to the absence of a sharp geographical boundary (e.g., the Ural Mountains) between these two subspecies, as suggested earlier. Importantly, moths from North America and the Caucasus/Middle East displayed high enough genetic distances from other populations to warrant their consideration as separate subspecies of L. dispar. Finally, in contrast with earlier mtDNA-based investigations that identified the Caucasus as L. dispar's place of origin, our analyses suggest continental East Asia as its evolutionary cradle, from where it spread to Central Asia and Europe, and to Japan through Korea.