The Mediterranean cone snail, Lautoconus ventricosus, is currently considered a single species inhabiting the whole Mediterranean basin and the adjacent Atlantic coasts. Yet, no population genetic study has assessed its taxonomic status. Here, we collected 245 individuals from 75 localities throughout the Mediterranean Sea and used cox1 barcodes, complete mitochondrial genomes, and genome skims to test whether L. ventricosus represents a complex of cryptic species. The maximum likelihood phylogeny based on complete mitochondrial genomes recovered six main clades (hereby named blue, brown, green, orange, red, and violet) with sufficient sequence divergence to be considered putative species. On the other hand, phylogenomic analyses based on 437 nuclear genes only recovered four out of the six clades: blue and orange clades were thoroughly mixed and the brown one was not recovered. This mito-nuclear discordance revealed instances of incomplete lineage sorting and introgression, and may have caused important differences in the dating of main cladogenetic events. Species delimitation tests proposed the existence of at least three species: green, violet, and red + blue + orange (i.e., cyan). Green plus cyan (with sympatric distributions) and violet, had West and East Mediterranean distributions, respectively, mostly separated by the Siculo-Tunisian biogeographical barrier. Morphometric analyses of the shell using species hypotheses as factor and shell length as covariate showed that the discrimination power of the studied parameters was only 70.2%, reinforcing the cryptic nature of the uncovered species, and the importance of integrative taxonomic approaches considering morphology, ecology, biogeography, and mitochondrial and nuclear population genetic variation.

The harbour porpoise (Phocoena phocoena) is a highly mobile cetacean found across the Northern hemisphere. It occurs in coastal waters and inhabits basins that vary broadly in salinity, temperature and food availability. These diverse habitats could drive subtle differentiation among populations, but examination of this would be best conducted with a robust reference genome. Here, we report the first harbour porpoise genome, assembled de novo from an individual originating in the Kattegat Sea (Sweden). The genome is one of the most complete cetacean genomes currently available, with a total size of 2.39 Gb and 50% of the total length found in just 34 scaffolds. Using 122 of the longest scaffolds, we were able to show high levels of synteny with the genome of the domestic cattle (Bos taurus). Our draft annotation comprises 22,154 predicted genes, which we further annotated through matches to the NCBI nucleotide database, GO categorization and motif prediction. Within the predicted genes, we have confirmed the presence of >20 genes or gene families that have been associated with adaptive evolution in other cetaceans. Overall, this genome assembly and draft annotation represent a crucial addition to the genomic resources currently available for the study of porpoises and Phocoenidae evolution, phylogeny and conservation.

The mammalian evolutionary tree has lost several major clades through recent human-caused extinctions. This process of historical biodiversity loss has particularly affected tropical island regions such as the Caribbean, an area of great evolutionary diversification but poor molecular preservation. The most enigmatic of the recently extinct endemic Caribbean mammals are the Nesophontidae, a family of morphologically plesiomorphic lipotyphlan insectivores with no consensus on their evolutionary affinities, and which constitute the only major recent mammal clade to lack any molecular information on their phylogenetic placement. Here, we use a palaeogenomic approach to place Nesophontidae within the phylogeny of recent Lipotyphla. We recovered the near-complete mitochondrial genome and sequences for 17 nuclear genes from a similar to 750-year-old Hispaniolan Nesophontes specimen, and identify a divergence from their closest living relatives, the Solenodontidae, more than 40 million years ago. Nesophontidae is thus an older distinct lineage than many extant mammalian orders, highlighting not only the role of island systems as "museums" of diversity that preserve ancient lineages, but also the major human-caused loss of evolutionary history.

Following the advent of industrial-scale antibiotic production in the 1940s,1 antimicrobial resistance (AMR) has been on the rise and now poses a major global health threat in terms of mortality, morbidity, and economic burden.2,3 Because AMR can be exchanged between humans, livestock, and wildlife, wild animals can be used as indicators of human-associated AMR contamination of the environment.4 However, AMR is a normal function of natural environments and is present in host-associated microbiomes, which makes it challenging to distinguish between anthropogenic and natural sources.4,5 One way to overcome this difficulty is to use historical samples that span the period from before the mass production of antibiotics to today. We used shotgun metagenomic sequencing of dental calculus, the calcified form of the oral microbial biofilm, to determine the abundance and repertoire of AMR genes in the oral microbiome of Swedish brown bears collected over the last 180 years. Our temporal metagenomics approach allowed us to establish a baseline of natural AMR in the pre-antibiotics era and to quantify a significant increase in total AMR load and diversity of AMR genes that is consistent with patterns of national human antibiotic use. We also demonstrated a significant decrease in total AMR load in bears in the last two decades, which coincides with Swedish strategies to mitigate AMR. Our study suggests that public health policies can be effective in limiting human-associated AMR contamination of the environment and wildlife.

We sequenced Early Neolithic genomes from the Zagros region of Iran (eastern Fertile Crescent), where some of the earliest evidence for farming is found, and identify a previously uncharacterized population that is neither ancestral to the first European farmers nor has contributed substantially to the ancestry of modern Europeans. These people are estimated to have separated from Early Neolithic farmers in Anatolia some 46,000 to 77,000 years ago and show affinities to modern-day Pakistani and Afghan populations, but particularly to Iranian Zoroastrians. We conclude that multiple, genetically differentiated hunter-gatherer populations adopted farming in southwestern Asia, that components of pre-Neolithic population structure were preserved as farming spread into neighboring regions, and that the Zagros region was the cradle of eastward expansion.

We produced a high-quality de novo genome assembly of the red-legged partridge A. rufa, the first reference genome of its genus, by utilising novel 10× Chromium technology. The estimated genome size was 1.19 Gb with an overall genome heterozygosity of 0.0022; no runs of homozygosity were observed. In total, 21,589 protein coding genes were identified and assigned to 16,772 orthologs. Of these, 201 emerged as unique to Alectoris and were enriched for positive regulation of epithelial cell migration, viral genome integration and maturation. Using PSMC analysis, we inferred a major demographic decline commencing ~140,000 years ago, consistent with forest expansion and reduction of open habitats during the Eemian interglacial. Present-day populations exhibit the historically lowest genetic diversity. Besides implications for management and conservation, this genome also promises key insights into the physiology of these birds with a view to improving poultry husbandry practices.

The black rhinoceros is again on the verge of extinction due to unsustainable poaching in its nativerange. Despite a wide historic distribution, the black rhinoceros was traditionally thought of asdepauperate in genetic variation, and with very little known about its evolutionary history. Thisknowledge gap has hampered conservation efforts because hunting has dramatically reduced thespecies' once continuous distribution, leaving five surviving gene pools of unknown genetic affinity.Here we examined the range-wide genetic structure of historic and modern populations using thelargest and most geographically representative sample of black rhinoceroses ever assembled. Usingboth mitochondrial and nuclear datasets, we described a staggering loss of 69% of the species'mitochondrial genetic variation, including the most ancestral lineages that are now absent frommodern populations. Genetically unique populations in countries such as Nigeria, Cameroon, Chad,Eritrea, Ethiopia, Somalia, Mozambique, Malawi and Angola no longer exist. We found that the historicrange of the West African subspecies (D. b. longipes), declared extinct in 2011, extends into southernKenya, where a handful of individuals survive in the Masai Mara. We also identify conservation unitsthat will help maintain evolutionary potential. Our results suggest a complete re-evaluation of currentconservation management paradigms for the black rhinoceros.

The population structure of the highly mobile marine mammal, the harbor porpoise (Phocoena phocoena), in the Atlantic shelf waters follows a pattern of significant isolation-bydistance. The population structure of harbor porpoises from the Baltic Sea, which is connected with the North Sea through a series of basins separated by shallow underwater ridges, however, is more complex. Here, we investigated the population differentiation of harbor porpoises in European Seas with a special focus on the Baltic Sea and adjacent waters, using a population genomics approach. We used 2872 single nucleotide polymorphisms (SNPs), derived from double digest restriction-site associated DNA sequencing (ddRAD-seq), as well as 13 microsatellite loci and mitochondrial haplotypes for the same set of individuals. Spatial principal components analysis (sPCA), and Bayesian clustering on a subset of SNPs suggest three main groupings at the level of all studied regions: the Black Sea, the North Atlantic, and the Baltic Sea. Furthermore, we observed a distinct separation of the North Sea harbor porpoises from the Baltic Sea populations, and identified splits between porpoise populations within the Baltic Sea. We observed a notable distinction between the Belt Sea and the Inner Baltic Sea sub-regions. Improved delineation of harbor porpoise population assignments for the Baltic based on genomic evidence is important for conservation management of this endangered cetacean in threatened habitats, particularly in the Baltic Sea proper. In addition, we show that SNPs outperform microsatellite markers and demonstrate the utility of RAD-tags from a relatively small, opportunistically sampled cetacean sample set for population diversity and divergence analysis.

DNA-barcoding utilises a fragment of the mitochondrial cytochrome oxidase subunit 1 (COI) gene to identify most animal species. Using next generation sequencing (NGS), this method can be further developed into metabarcoding processes that allow the simultaneous identification of several species from a mixed sample. We created a database of COI sequences of 27 mosquito species collected in Sweden, and combined our data with 27 additional sequences from GenBank to cover the taxa recently documented in Sweden and to include possible invasive taxa. Comparisons show that COI metabarcoding reliably identifies 41 of 54 species and the remainder to species group. Using three independent primer pairs along the COI gene, we further developed this barcoding approach to simultaneously identify Swedish mosquitoes in communities using NGS and quantify relative abundance of each mosquito species in the sample, using bioinformatics methods. We tested the accuracy of the metabarcoding method using communities assembled from morphologically identified mosquitoes, revealing 80% positive identification rate and the estimates of population structure which reflects the input sample. We conclude that metabarcoding is useful as a high throughput identification technique and for the quantification of species.

Background. Multiple studies have demonstrated that partitioning of molecular datasets is important in model-based phylogenetic analyses. Commonly, partitioning is done a priori based on some known properties of sequence evolution, e.g. differences in rate of evolution among codon positions of a protein-coding gene. Here we propose a new method for data partitioning based on relative evolutionary rates of the sites in the alignment of the dataset being analysed. The rates are inferred using the previously published Tree Independent Generation of Evolutionary Rates (TIGER), and the partitioning is conducted using our novel python script RatePartitions. We conducted simulations to assess the performance of our new method, and we applied it to eight published multi-locus phylogenetic datasets, representing different taxonomic ranks within the insect order Lepidoptera (butterflies and moths) and one phylogenomic dataset, which included ultra-conserved elements as well as introns.

Methods. We used TIGER-rates to generate relative evolutionary rates for all sites in the alignments. Then, using RatePartitions, we partitioned the data into partitions based on their relative evolutionary rate. RatePartitions applies a simple formula that ensures a distribution of sites into partitions following the distribution of rates of the characters from the full dataset. This ensures that the invariable sites are placed in a partition with slowly evolving sites, avoiding the pitfalls of previously used methods, such as kmeans. Different partitioning strategies were evaluated using BIC scores as calculated by PartitionFinder.

Results. Simulations did not highlight any misbehaviour of our partitioning approach, even under difficult parameter conditions or missing data. In all eight phylogenetic datasets, partitioning using TIGER-rates and RatePartitions was significantly better as measured by the BIC scores than other partitioning strategies, such as the commonly used partitioning by gene and codon position. We compared the resulting topologies and node support for these eight datasets as well as for the phylogenomic dataset.

Discussion. We developed a new method of partitioning phylogenetic datasets without using any prior knowledge (e.g. DNA sequence evolution). This method is entirely based on the properties of the data being analysed and can be applied to DNA sequences (protein-coding, introns, ultra-conserved elements), protein sequences, as well as morphological characters. A likely explanation for why our method performs better than other tested partitioning strategies is that it accounts for the heterogeneity in the data to a much greater extent than when data are simply subdivided based on prior knowledge.

Phymatotrichopsis omnivora is a member of Pezizomycetes and causes root rot disease on a broad range of dicotyledonous plants. Using recently generated draft genome sequence data from four P. omnivora isolates, we developed simple sequence repeat (SSR) markers and identified both mating type genes (MAT1-1-1 and MAT1-2-1) in this fungus. To understand the genetic diversity of P. omnivora isolates (n = 43) and spore mats (n = 29) collected from four locations (Oklahoma, Texas, Arizona, and Mexico) and four host crops (cotton, alfalfa, peach, and soybean), we applied 24 SSR markers and showed that of the 72 P. omnivora isolates and spore mats tested, 41 were distinct genotypes. Furthermore, the developed SSR markers did not show cross-transferability to other close relatives of P. omnivora in the class Pezizomycetes. A multiplex PCR detecting both mating type idiomorphs and a reference gene (TUB2) was developed to screen P. omnivora isolates. Based on the dataset we tested, P. omnivora is a heterothallic fungus with both mating types present in the United States in a ratio close to 1:1. We tested P. omnivora spore mats obtained from spatially distinct disease rings that developed in a center-pivot alfalfa field and showed that both mating types can be present not only in the same field but also within a single spore mat. This study shows that P. omnivora has the genetic toolkit for generating sexually diverse progeny, providing impetus for future studies that focus on identifying sexual morphs in nature.

Background

The international Dog10K project aims to sequence and analyze several thousand canine genomes. Incorporating 20 × data from 1987 individuals, including 1611 dogs (321 breeds), 309 village dogs, 63 wolves, and four coyotes, we identify genomic variation across the canid family, setting the stage for detailed studies of domestication, behavior, morphology, disease susceptibility, and genome architecture and function.

Results

We report the analysis of > 48 M single-nucleotide, indel, and structural variants spanning the autosomes, X chromosome, and mitochondria. We discover more than 75% of variation for 239 sampled breeds. Allele sharing analysis indicates that 94.9% of breeds form monophyletic clusters and 25 major clades. German Shepherd Dogs and related breeds show the highest allele sharing with independent breeds from multiple clades. On average, each breed dog differs from the UU_Cfam_GSD_1.0 reference at 26,960 deletions and 14,034 insertions greater than 50 bp, with wolves having 14% more variants. Discovered variants include retrogene insertions from 926 parent genes. To aid functional prioritization, single-nucleotide variants were annotated with SnpEff and Zoonomia phyloP constraint scores. Constrained positions were negatively correlated with allele frequency. Finally, the utility of the Dog10K data as an imputation reference panel is assessed, generating high-confidence calls across varied genotyping platform densities including for breeds not included in the Dog10K collection.

Conclusions

We have developed a dense dataset of 1987 sequenced canids that reveals patterns of allele sharing, identifies likely functional variants, informs breed structure, and enables accurate imputation. Dog10K data are publicly available.

Genome assemblies are currently being produced at an impressive rate by consortia and individual laboratories. The low costs and increasing efficiency of sequencing technologies now enable assembling genomes at unprecedented quality and contiguity. However, the difficulty in assembling repeat-rich and GC-rich regions (genomic “dark matter”) limits insights into the evolution of genome structure and regulatory networks. Here, we compare the efficiency of currently available sequencing technologies (short/linked/long reads and proximity ligation maps) and combinations thereof in assembling genomic dark matter. By adopting different de novo assembly strategies, we compare individual draft assemblies to a curated multiplatform reference assembly and identify the genomic features that cause gaps within each assembly. We show that a multiplatform assembly implementing long-read, linked-read and proximity sequencing technologies performs best at recovering transposable elements, multicopy MHC genes, GC-rich microchromosomes and the repeat-rich W chromosome. Telomere-to-telomere assemblies are not a reality yet for most organisms, but by leveraging technology choice it is now possible to minimize genome assembly gaps for downstream analysis. We provide a roadmap to tailor sequencing projects for optimized completeness of both the coding and noncoding parts of nonmodel genomes.

It is a broadly observed pattern that the non-recombining regions of sex-limited chromosomes (Y and W) accumulate more repeats than the rest of the genome, even in species like birds with a low genome-wide repeat content. Here, we show that in birds with highly heteromorphic sex chromosomes, the W chromosome has a transposable element (TE) density of greater than 55% compared to the genome-wide density of less than 10%, and contains over half of all full-length (thus potentially active) endogenous retroviruses (ERVs) of the entire genome. Using RNA-seq and protein mass spectrometry data, we were able to detect signatures of female-specific ERV expression. We hypothesize that the avian W chromosome acts as a refugium for active ERVs, probably leading to female-biased mutational load that may influence female physiology similar to the ‘toxic-Y’ effect in Drosophila males. Furthermore, Haldane's rule predicts that the heterogametic sex has reduced fertility in hybrids. We propose that the excess of W-linked active ERVs over the rest of the genome may be an additional explanatory variable for Haldane's rule, with consequences for genetic incompatibilities between species through TE/repressor mismatches in hybrids. Together, our results suggest that the sequence content of female-specific W chromosomes can have effects far beyond sex determination and gene dosage.

According to the nearly-neutral theory of evolution, the relative strengths of selection and drift shift in favour of drift at small population sizes. Numerous studies have analysed the effect of bottlenecks and small population sizes on genetic diversity in the MHC, which plays a central role in pathogen recognition and immune defense and is thus considered a model example for the study of adaptive evolution. However, to understand changes in genetic diversity at loci under selection, it is necessary to compare the genetic diversity of a population before and after the bottleneck. In this study, we analyse three fragments of the MHC DQA gene in woolly mammoth samples radiocarbon dated to before and after a well-documented bottleneck that took place about ten thousand years ago. Our results indicate a decrease in observed heterozygosity and number of alleles, suggesting that genetic drift had an impact on the variation on MHC. Based on coalescent simulations, we found no evidence of balancing selection maintaining MHC diversity during the Holocene. However, strong trans-species polymorphism among mammoths and elephants points to historical effects of balancing selection on the woolly mammoth lineage.

Inference of population demographic history has vastly improved in recent years due to a number of technological and theoretical advances including the use of ancient DNA. Approximate Bayesian computation (ABC) stands among the most promising methods due to its simple theoretical fundament and exceptional flexibility. However, limited availability of user-friendly programs that perform ABC analysis renders it difficult to implement, and hence programming skills are frequently required. In addition, there is limited availability of programs able to deal with heterochronous data. Here we present the software BaySICS: Bayesian Statistical Inference of Coalescent Simulations. BaySICS provides an integrated and user-friendly platform that performs ABC analyses by means of coalescent simulations from DNA sequence data. It estimates historical demographic population parameters and performs hypothesis testing by means of Bayes factors obtained from model comparisons. Although providing specific features that improve inference from datasets with heterochronous data, BaySICS also has several capabilities making it a suitable tool for analysing contemporary genetic datasets. Those capabilities include joint analysis of independent tables, a graphical interface and the implementation of Markov-chain Monte Carlo without likelihoods.

The black rhinoceros (Diceros bicornis L.) is a critically endangered species historically distributed across sub-Saharan Africa. Hunting and habitat disturbance have diminished both its numbers and distribution since the 19th century, but a poaching crisis in the late 20th century drove them to the brink of extinction. Genetic and genomic assessments can greatly increase our knowledge of the species and inform management strategies. However, when a species has been severely reduced, with the extirpation and artificial admixture of several populations, it is extremely challenging to obtain an accurate understanding of historic population structure and evolutionary history from extant samples. Therefore, we generated and analyzed whole genomes from 63 black rhinoceros museum specimens collected between 1775 and 1981. Results showed that the black rhinoceros could be genetically structured into six major historic populations (Central Africa, East Africa, Northwestern Africa, Northeastern Africa, Ruvuma, and Southern Africa) within which were nested four further subpopulations (Maasailand, southwestern, eastern rift, and northern rift), largely mirroring geography, with a punctuated north–south cline. However, we detected varying degrees of admixture among groups and found that several geographical barriers, most prominently the Zambezi River, drove population discontinuities. Genomic diversity was high in the middle of the range and decayed toward the periphery. This comprehensive historic portrait also allowed us to ascertain the ancestry of 20 resequenced genomes from extant populations. Lastly, using insights gained from this unique temporal data set, we suggest management strategies, some of which require urgent implementation, for the conservation of the remaining black rhinoceros diversity.

Large vertebrates are extremely sensitive to anthropogenic pressure, and their populations are declining fast. The white rhinoceros (Ceratotherium simum) is a paradigmatic case: this African megaherbivore has suffered a remarkable decline in the last 150 years due to human activities. Its subspecies, the northern (NWR) and the southern white rhinoceros (SWR), however, underwent opposite fates: the NWR vanished quickly, while the SWR recovered after the severe decline. Such demographic events are predicted to have an erosive effect at the genomic level, linked to the extirpation of diversity, and increased genetic drift and inbreeding. However, there is little empirical data available to directly reconstruct the subtleties of such processes in light of distinct demographic histories. Therefore, we generated a whole-genome, temporal data set consisting of 52 resequenced white rhinoceros genomes, representing both subspecies at two time windows: before and during/after the bottleneck. Our data reveal previously unknown population structure within both subspecies, as well as quantifiable genomic erosion. Genome-wide heterozygosity decreased significantly by 10% in the NWR and 36% in the SWR, and inbreeding coefficients rose significantly by 11% and 39%, respectively. Despite the remarkable loss of genomic diversity and recent inbreeding it suffered, the only surviving subspecies, the SWR, does not show a significant accumulation of genetic load compared to its historical counterpart. Our data provide empirical support for predictions about the genomic consequences of shrinking populations, and our findings have the potential to inform the conservation efforts of the remaining white rhinoceroses.

The growing grey seal (Halichoerus grypus) population in the Baltic Sea has created conflicts with local fisheries, comparable to similar emerging problems worldwide. Adequate information on the foraging habits is a requirement for responsible management of the seal population. We investigated the applicability of available dietary assessment methods by comparing morphological analysis and DNA metabarcoding of gut contents (short-term diet; n = 129/125 seals, respectively), and tissue chemical markers i.e. fatty acid (FA) profiles of blubber and stable isotopes (SIs) of liver and muscle (mid- or long-term diet; n = 108 seals for the FA and SI markers). The methods provided complementary information. Short-term methods indicated prey species and revealed dietary differences between age groups and areas but for limited time period. In the central Baltic, herring was the main prey, while in the Gulf of Finland percid and cyprinid species together comprised the largest part of the diet. Perch was also an important prey in the western Baltic Proper. The DNA analysis provided firm identification of many prey species, which were neglected or identified only at species group level by morphological analysis. Liver SIs distinguished spatial foraging patterns and identified potentially migrated individuals, whereas blubber FAs distinguished individuals frequently utilizing certain types of prey. Tissue chemical markers of adult males suggested specialized feeding to certain areas and prey, which suggest that these individuals are especially prone to cause economic losses for fisheries. We recommend combined analyses of gut contents and tissue chemical markers as dietary monitoring methodology of aquatic top predators to support an optimal ecosystem-based management.

The moose (Alces alces) is the most intensely managed game species in Fennoscandia; approximately one-third of the population, ca. 160,000 animals, is harvested annually. Despite the species' biological and socioeconomic importance, there are knowledge gaps with respect to its intraspecific diversity and genetic structure. Recent studies of moose in neighboring countries report 2 genetic groups in Finland, 3 in Norway with one of them suggested to be of ancient origin, and no indications of bottlenecks. To delineate the spatial genetic landscape of the Swedish moose, we used allozyme variability from over 20,000 georeferenced moose collected all over Sweden in combination with 12 microsatellites (n = 1,200) and mitochondrial DNA (mtDNA) sequences (n = 44). We combined individual-based and traditional statistical approaches with coalescence-based simulations. The results indicate a complex history with bottlenecks and recent expansions that is consistent with historical records. Swedish moose are separated into 2 major genetic groups, a northern and a southern one, where the southern group is further divided into 3 subgroups. The 2 main subpopulations are moderately differentiated (F-ST = 0.1; R-ST = 0.07) and separated by sharp genetic discontinuities occurring over a relatively narrow transition zone in central Sweden that coincides with a similar, previously reported transition zone in Norway. This differentiation is not reflected in mtDNA variation, where no significant divergence was observed. Together with the F-ST andR(ST) similarities, this suggests that the 2 major subpopulations in Sweden reflect divergence shaped after the postglacial recolonization of Scandinavia. Neighborhood size assessments indicate that gene flow is relatively restricted with an estimated average dispersal distance of 3.5-11.1 km, and spatial autocorrelograms suggest that genetic similarity decreases almost linearly over space resulting in continuous genetic clines within major subgroups. Management areas largely coincide with genetic clusters, simplifying the integration of genetic information into management.