Metabarcoding and Metagenomics

Environmental DNA metabarcoding is a powerful monitoring tool for assessing aquatic biodiversity, as well as the sustainability and impacts of fisheries and aquaculture. However, conventional laboratory workflows remain time-consuming and dependent on dedicated infrastructures. Here, we present a field trial of a fully portable, off-grid eDNA metabarcoding pipeline that enables end-to-end analysis within a few days using compact equipment, including a BentoLab workstation and an Oxford Nanopore Technologies (ONT) MinION sequencer. The workflow was implemented during two international training courses in Norway and Brazil, where students and early career researchers collected environmental samples, extracted and amplified DNA, prepared DNA libraries, and sequenced on-site before performing bioinformatics and statistical analyses. In the case study detailed here, seven eDNA samples collected and analysed on-site in the Oslofjord allowed detection of 16 fish and elasmobranch species. Although overall diversity was lower than in earlier studies using Illumina-based sequencing, our protocol reliably detected key species and demonstrates that portable eDNA metabarcoding is feasible for rapid ecological assessment, surveillance of high-risk regions and/or deployment in remote or resourcelZllimited settings.

Astyanax Baird & Girard, 1854 is a widely distributed and species-rich genus of Acestrorhamphidae, whose abundant populations in Neotropical basins play a crucial ecological role at the trophic level. Taxonomic uncertainties persist within the genus, as seen in Astyanax sp. (formerly designated as A. fasciatus) from the Magdalena basin in Colombia. Concerns about its genetic status are heightened due to ecological threats posed by hydroelectric dams, from habitat loss to river connectivity. We isolated and characterized 17 microsatellite loci to assess the population genetics of this species in a broad sample from the middle and lower sections of the Cauca River, now interrupted by the Ituango dam. Furthermore, a multidisciplinary approach integrating phylogenetic analyses of mitochondrial (COI) and nuclear (rag2) markers with geometric morphometric analyses was employed to evaluate potential cryptic diversity within Astyanax sp. Microsatellites revealed two genetic groups in the studied area, strongly supported as distinct lineages by phylogenetic analyses. Unexpectedly, one of these lineages of Astyanax sp. was recovered in an unresolved clade with samples of A. microlepis and allopatric samples of A. viejita from the Maracaibo Lake basin. Each genetic group showed high genetic diversity, but also evidence of recent bottleneck events and significant-high values of inbreeding. Morphometric analyses provided evidence of significant phenotypic differentiation among A. microlepis, Astyanax sp. 1 (Asp1), and Astyanax sp. 2 (Asp2). Morphological patterns ranged from the robust profile of A. microlepis to the streamlined shape of Astyanax sp. 2 (Asp2), with Astyanax sp. 1 (Asp1) displaying intermediate traits and localized differences in head length and fin placement. Statistical support from permutation tests and a high overall classification accuracy (95.65%) underscore the existence of distinct morphospecies, suggesting that phenotypic differentiation is well-established, despite the complex evolutionary history of the group. This study suggests the presence of cryptic diversity within Astyanax sp. and provides valuable genetic information for the conservation and management of their populations in the Magdalena basin.

Multiplexing samples in long-read sequencing with Oxford Nanopore Next Generation Sequencing Technology (ONT) by ligating specific native barcodes to individual DNA samples enables significant increases of high throughput sequencing combined with a significant reduction of sequencing costs. However, this advantage carries the risk of barcode misassignment / crosstalk. Employing ONT multiplex sequencing with samples, we observed misassigned barcodes so called barcode crosstalk, after ONT library preparation according to the standard protocol, particularly in samples with low input DNA concentrations. We assumed that these barcode misassignments are largely due to misligation of remaining native barcodes during subsequent the subsequent sequencing adapter ligation. To systematically investigate and quantify barcode crosstalk, genomic DNA (gDNA) from four bacterial type strains with different DNA input concentrations was prepared using three protocols for library preparation: the Nanopore standard protocol (protocol A: version valid until July 2, 2025) the new Nanopore protocol (protocol B: version from July 2, 2025), and an in house protocol with pooling of the barcoded samples only after the sequencing adapter ligation step (protocol C: in house). All samples were sequenced on a Nanopore PromethIon device. The results clearly showed that the use of protocol A resulted in a pronounced barcode crosstalk especially detectable in samples with low DNA input concentrations (up to 2.4% misassigned reads). The ONT adjustment in protocol B (altered washing buffer vs. protocol A) significantly alleviated the barcode crosstalk to below 0.01%, whereas protocol C eliminated barcode crosstalk virtually completely. These observations emphasize that sequencing results obtained with older ONT native barcoding protocol variants should be critically reviewed. The newer ONT barcoding protocol is preferable for sequencing, but it does not completely eliminate the barcode crosstalk effect. In conclusion, for low DNA input and high accuracy sequencing, protocol C is recommended.

Effective monitoring of the critically endangered European eel (Anguilla anguilla) is essential for conservation planning and regulatory decision-making, particularly in heavily fragmented rivers. Environmental DNA (eDNA) methods offer sensitive alternatives to traditional surveys, but there is uncertainty around whether targeted assays or community-wide approaches are better suited to achieve monitoring objectives. We compared eDNA metabarcoding and species-specific quantitative PCR (qPCR) for detecting A. anguilla across 145 pumped catchments in the Fens, East Anglia, England. All sites were sampled once initially, and sites negative for A. anguilla were re-sampled based on metabarcoding results. This allowed comparison of detection rates from a single water sample and site-level retrospective identification of sites where qPCR could have identified A. anguilla in earlier samples. The findings were also set in the context of the wider biodiversity information generated by metabarcoding. From the initial (single) water sample, qPCR detected A. anguilla at seven more sites than metabarcoding (17 versus 10). With repeated sampling, metabarcoding detected A. anguilla at 43 sites, including all but one of the sites where qPCR detected A. anguilla, and ten sites where qPCR did not detect A. anguilla within the same number of samples. Indeed, the additional sampling effort required to detect A. anguilla with metabarcoding at sites also positive with qPCR was small relative to the overall sampling effort. Furthermore, metabarcoding additionally detected 28 non-target fish species alongside fish, amphibian and mammal species of conservation concern. Our results highlight trade-offs between target-species sensitivity and the broader ecological information provided by each method, and support metabarcoding as an effective tool for a holistic conservation approach, with the additional community data outweighing the marginally increased sensitivity of qPCR.

The coleoid cephalopods (octopus, cuttlefish, and squid) are emerging model organisms for neuroscience, development, and evolutionary biology. Determining their sex early in life is critical for population management and controlled experiments. Here, we present a protocol to non-invasively determine the sex of multiple cephalopod species as young as 3 hours post-hatching using a skin swab and quantitative PCR (qPCR). We describe steps for designing qPCR primers, swabbing live animals, extracting DNA, running the qPCR, and analyzing the results. For complete details on the use and execution of this protocol, please refer to Rubino et al.1 HighlightsO_LISwab live cephalopods as early as 3 hours post-hatching C_LIO_LIExtract DNA from cephalopod skin swabs C_LIO_LIPerform qPCR-based sex determination C_LIO_LIDesign and validate qPCR primers for new species C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/715692v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@3aa68dorg.highwire.dtl.DTLVardef@8c7e61org.highwire.dtl.DTLVardef@1bd45d9org.highwire.dtl.DTLVardef@134cc4d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Pollen is a robust and widespread substance that captures a historical snapshot of a specific time and place, and it can be used to track movements through space by examining the pollen deposited on various objects. Palynology, the study of pollen, is used across fields such as conservation, natural history, and forensics, where it is particularly useful for tracing the origin and movement of objects. However, pollen has remained underutilized due to the difficulty of distinguishing many pollen taxa beyond the family level and limited pollen reference material to support location predictions. With recent developments in pollen DNA metabarcoding these issues have been rectified, but much of the available pollen data are primarily from wind-pollinated species, which are widespread and less informative of specific sample locations. Bee-collected pollen presents an untapped resource in training predictive models to geolocate sample origin. Here we compiled bee-collected pollen DNA sequence relative abundance data from three projects in the western U.S. and assessed the accuracy of supervised machine learning models to predict the location of sample origin based solely on pollen assemblage, without the need of incorporating additional data. Random Forest and k-Nearest Neighbors models yielded high accuracy across all projects. We also found that models trained on taxonomically clustered pollen assigned sequence variants (ASVs) performed slightly better than those trained on raw sequence data, but the difference was minor, indicating that models trained on raw sequence data can reliably predict location and avoid the time-consuming taxonomic assignment process. Our results demonstrate the utility of repurposing bee-collected pollen for geolocation and provide a framework for employing supervised machine learning in future geolocation efforts. HighlightsO_LIBee-collected pollen metabarcoding data was used to accurately predict sample origin C_LIO_LIRandom Forest and k-Nearest Neighbors algorithms were most accurate with lowest error C_LIO_LITaxonomically-classified and raw DNA sequence data training sets performed comparably C_LI

Agriculture has modified the soil structure due to the influence of external factors and processes that affect microbial biodiversity. Metagenomics is a fundamental tool for the study of soil microbial diversity because it provides information about the ecosystem diversity, including both the microorganisms that cannot be isolated in culture media and those that are no longer viable in the analyzed sample. In this work, six soil samples obtained from agroecosystems of central and northern Argentina were subjected to a preliminary 16S metagenomic analysis. Copiotrophic bacteria (Proteobacteria and Actinobacteria) were dominant and one of the samples had a dominance of an oligotrophic Phylum (Acidobacteria). Our findings support previous evidence from traditionally managed agroecosystems and provide new insights into the diversity of soil microbiomes in Argentine regions outside the Pampas. Finally, we analyzed the most common genera with relevant species to agronomy, both beneficial and pathogenic, and their abundance and diversity in the sequenced samples.

Hybridization between invasive and native species poses a hidden but critical threat to biodiversity. While environmental DNA (eDNA) has revolutionized species monitoring, it has lacked the resolution to detect hybrid individuals. Here, we present the first experimental demonstration of hybrid identification using eDNA. Our method isolates a single cell in the environment (hereafter, eCell) and enables cellular-level analysis using multiplex digital PCR targeting nuclear markers from both parental species. Validation with controlled tank experiments using Oncorhynchus masou masou x Salvelinus leucomaenis leucomaenis hybrid individuals confirmed the methods ability to separately detect hybrid individuals from co-habiting purebred parent individuals. This eCell analysis overcomes the limitations of traditional eDNA methods and offers a scalable, non-invasive tool for detecting cryptic hybridization. By enabling early and accurate detection of hybrid individuals, it supports timely conservation decisions, including management prioritization and the protection of purebred populations. This novel technique bridges a critical gap in conservation genetics and enhances eDNAs utility for biodiversity management in the face of global change.

Invasive round goby Neogobius melanostomus have advanced eastward through the state of New York and provinces of Ontario and Quebec over the past two decades and are approaching Lake Champlain, one of the largest lakes in North America. This manuscript describes international efforts to monitor round goby populations during 2021-2025 on (a) the southern approach to Lake Champlain via the Hudson River and Champlain Canal, and (b) the northern approach to Lake Champlain via the Saint Lawrence River and Richelieu River. Monitoring utilized environmental DNA (eDNA), backpack electrofishing, beach seining, benthic trawling, and viral hemorrhagic septicemia virus (VHSV) testing. In the Champlain Canal, round goby were captured as far north as the downstream side of the C1 dam (97 kilometers [km] from Lake Champlain) while eDNA detections occurred as far north as the upstream side of the C2 dam (90 km from Lake Champlain). In the Richelieu River, round goby were captured as far south as Saint-Marc-sur-Richelieu (82 km from Lake Champlain) while the southern-most eDNA detections occurred near the Canadian side of the international border (4 km from Lake Champlain). Water temperature influenced habitat usage of round goby in the Champlain Canal, with catch rates in near-shore areas declining at < 10 {degrees}C. All VHSV test results were non-detections at the mouth of the Richelieu River, while one positive and two inconclusive results occurred along the Champlain Canal. Together, these data have informed multiple mitigation measures and have implications for management of aquatic invasive species across North America.

Understanding the dietary patterns of introduced predators is essential for assessing their impacts on freshwater ecosystems. Here, we investigated the feeding ecology of the invasive Korean perch (Coreoperca herzi) introduced to the Oyodo River system, Japan, by integrating gut content DNA metabarcoding and environmental DNA (eDNA) metabarcoding. Fifty specimens were collected, and prey taxa were identified using metabarcoding targeting fish, aquatic insects, and crustaceans. In parallel, eDNA metabarcoding of habitat water samples was used to assess prey availability and selectivity. The results revealed that the Korean perch prey extensively on aquatic insects and fish. Aquatic insect prey were dominated by epilithic clinger taxa inhabiting stone surfaces, particularly mayflies, suggesting visual-mediated prey selection. Fish predation was frequently detected even in small individuals (<100 mm SL), in contrast to previous studies based on conventional methods, indicating that piscivory begins early and ontogenetic dietary shifts are not pronounced. Furthermore, quantitative fish eDNA analysis showed a positive relationship between eDNA concentrations of prey species and predation frequency, indicating opportunistic feeding on abundant, size-accessible prey. By applying two metabarcoding approaches, this study provides an integrated assessment of prey utilisation and environmental context, highlighting ecological risks posed by the Korean perch to freshwater communities in Japan.

Artificial pond construction is widely used in wetland restoration, yet biodiversity outcomes depend strongly on design and subsequent management. We tested how different regimes (grazing, mowing, and no management) influence habitat structure, water conditions, and aquatic macroinvertebrate diversity in newly excavated experimental ponds within an eutrophic wetland in South Moravia (Czechia). Across four focal groups (Mollusca, Odonata, Coleoptera, Heteroptera), we observed rapid colonisation of the newly built ponds. Species richness and densities rose during early development, dropped after drying events, and then partially recovered, indicating repeated "resetting" of communities under fluctuating hydrology. Periodic drying also prevented fish stock establishment. Management significantly affected species composition and both grazed and mowed ponds displayed higher densities (abundances) than controls, but differed only slightly in terms of species richness. The grazed ponds were characterised by high sunlight exposure, reduced reed dominance, and trampling-generated high littoral heterogeneity. These ponds showed highest numbers of taxa adapted to shallow and warm waterbodies, muddy substrate, semiaquatic microhabitats, or newly emerged and disturbed habitats. The mowed ponds promoted dense submergent vegetation, supporting Odonata representation and other taxa requiring aquatic vegetation. The control ponds remained highly shaded by high-grown reed, organic-matter rich, hosting a set of taxa tolerant of low-light, low-oxygen conditions. At the wetland scale, multiple small ponds increased overall diversity through high between-pond heterogeneity. Our results highlight that pond construction alone is insufficient for wetland restoration: follow-up long-term management regimes, especially extensive grazing, can rapidly generate structural heterogeneity and sustain diverse aquatic invertebrate assemblages in eutrophic wetlands.

SummaryThe combination of target capture metagenomics and long-read sequencing represents a powerful approach for the characterisation of rare microbial taxa and their functional genes. However, standard Nanopore library preparations are incompatible with established capture protocols. A possible workaround is the preparation of Illumina libraries prior to ONT sequencing. Currently, this hybrid approach is hindered by a lack of specialised demultiplexing software capable of handling residual adapter fragments; Nanopores higher error rates and positional variability. Here, we present deluxpore: a Nextflow pipeline that demultiplexes Nanopore reads from Illumina dual-indexed libraries (NEBNext and Nextera) using BLAST alignment and Levenshtein distance matching. Extensive benchmarking across 18 replicates validates the viability and precision of this hybrid indexing approach. Benchmarking demonstrates that accurate demultiplexing requires minimum Q20 data quality and strategic index selection. Unique index-to-sample designs achieved 91.7% sample recovery at Q20 versus 46.1% for combinatorial approaches. We also identified high-crosstalk index pairs within NEBNext Primer Set A and provide an optimized 8-sample configuration achieving ~95% accuracy at Q20. deluxpore enables reliable, automated demultiplexing for hybrid capture-long-read sequencing workflows. Availability and implementationdeluxpore is implemented in Nextflow, Python, and Bash under the GNU GPL v3.0. Source code, documentation, and benchmarking workflows are available at https://github.com/compgenomicslab/deluxpore and https://github.com/compgenomicslab/deluxpore-benchmarking.

Coral restoration is recognised as a critical tool to mitigate pantropical degradation of reef ecosystems. Robust monitoring of restoration progress is crucial for projects to evaluate their success, improve practice, and share knowledge. However, traditional visual surveys often fail to capture the full impact of coral restoration on reef function. Therefore, we employed Passive Acoustic Monitoring (PAM) to assess whether the soundscape of a coral restoration site in the Seychelles differs from adjacent healthy and degraded reference reefs. We applied two methods of soundscape analysis: manual detection of unidentified fish sounds; and machine learning-based Uniform Manifold Approximation and Projection analysis. Results were approach-specific: the manual approach highlighted similarities in fish calls between the restoration site and the healthy reference reef, while the machine learning approach extracted broader soundscape patterns, clustering the restoration site alongside the degraded reference reef. Although this is a single-site study, these findings suggest that a) coral restoration alters reef soundscapes, though recovery time may be taxon-specific, and b) multiple metrics are needed to bridge single-taxon and broad soundscape scales. This study contributes to the evolving field of soundscape ecology in coral reef ecosystems, highlighting the utility of PAM in monitoring changes to reef function through coral restoration.

Since 1995, European fisheries of Pecten maximus have faced the presence of Pseudo-nitzschia species, which are able to produce the neurotoxin domoic acid responsible for Amnesic Shellfish Poisoning (ASP). As filter-feeders, scallops can accumulate and retain domoic acid much longer than most other bivalves, from months to years. When concentrations exceed the regulatory threshold, fisheries are closed leading to economic concern. Inter-individual variability increases the difficulty to predict the depuration dynamics. Quantifying the correlations between domoic acid depuration in P. maximus and individual physiological traits, particularly body size, could improve the understanding of contamination and depuration. We analysed toxin dynamics in organs and assessed the effects of body size and growth. This analysis was based on two datasets from an experimental and an in situ depuration monitoring of P. maximus exposed to a natural bloom of toxic P. australis. Results showed that the distribution of domoic acid shifted among organs between contamination and two months of depuration. Toxin concentrations correlated negatively with body size during contamination and after two months of depuration, but shifted to a positive correlation after 7 months of depuration. This suggested that smaller scallops both accumulate more domoic acid and depurate it more rapidly. Dilution by growth appeared to explain the inversion of the correlation between domoic acid and body size throughout depuration. These results yield useful information for modelling these mechanisms, thus providing valuable tools for scallop fishery management facing ASP. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=60 SRC="FIGDIR/small/708139v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@1fd317org.highwire.dtl.DTLVardef@15b9032org.highwire.dtl.DTLVardef@57dae8org.highwire.dtl.DTLVardef@1e4c7fc_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIExperimental and in situ datasets allowed to quantify DA proportion dynamics in organs in P. maximus C_LIO_LIDA concentration and body size are negatively correlated during contamination phase, but positively after a 7-month depuration C_LIO_LIConsidering dilution by growth is important for young scallops to assess DA depuration dynamics C_LIO_LIBoth depuration rate and dilution by growth need to be considered to model DA depuration over the whole scallop size range C_LI

The geographical and familial origins of Christopher Columbus have remained a subject of intense historiographical debate for over five centuries. Despite numerous hypotheses, empirical genetic evidence capable of resolving his ancestral history or place of birth has been absent from the literature until now. This study presents the third stage of the first forensic genetic analysis performed on skeletal remains belonging to several direct descendants of Columbus, spanning the 16th to 18th centuries. By applying Massively Parallel Sequencing (MPS) to analyse autosomal, X- and Y- chromosome DNA markers, and integrating the results with multidisciplinary evidence from historical, genealogical, archaeological, and anthropological research implicated in this project, the identification of several individuals founded in the Crypt of Santa Maria de Gracia located in Gelves (Sevilla, Spain) has been achieved. The analysis of their biological relatedness enabled the reconstruction of kinship networks among the individuals interred in the crypt, which, when interpreted in the context of documented genealogical lineages, provides indirect but consistent evidence pointing toward the debated origin of the discoverer.

Metaproteomics enables the functional characterization of microbiomes and host-microbe interactions by detecting and quantifying thousands of proteins. In data-dependent acquisition metaproteomics, protein quantification is commonly performed using either MS1-based area under the curve (AUC) or MS2-based peptide spectral counts (SpC). In AUC quantification, match between runs (MBR) is frequently employed to minimize data sparsity, yet its impact on metaproteomic data remains unclear. Understanding MBRs impact on metaproteomics data is especially important due to the high peak density in the MS1 mass spectra and the potential presence of not only proteins, but even entire organisms, in one sample and their absence in the other, which would complicate accurate feature mapping and transfer. While accurate quantification is essential for deriving meaningful biological inferences from metaproteomic analyses, systematic evaluations of AUC and SpC quantification in metaproteomics remain scarce. In this study, we used defined complex metaproteomic samples to perform a ground truth-based evaluation of AUC and SpC quantification and to determine the impact of MBR on AUC quantification. We found that MBR led to a substantial number of falsely identified proteins in complex samples. Protein identifications from an organism not present in the sample were wrongly transferred from other samples when MBR was used. We found that MBR-free AUC data had a wider dynamic range, higher quantitative accuracy, and more sensitive detection of abundance differences. Significance of the StudyAlthough metaproteomics is increasingly used to advance microbiome research, quantification strategies in metaproteomics are mostly selected based on convention rather than evidence, due to a lack of ground truth-based evaluation of quantification strategies in metaproteomics. Accurate protein quantification is key to deriving meaningful biological inferences from metaproteomic samples, yet it remains challenging due to their high complexity and uneven protein abundances. Here, we used defined metaproteomic samples to evaluate widely used quantification strategies in metaproteomics and to determine the effects of match between runs (MBR) on quantitative accuracy. Based on our findings, MBR adds falsely identified proteins to metaproteomic data. While MBR-free AUC offers a broader dynamic range and higher quantitative accuracy, SpC offers better proteome coverage. With this study, we provide an evidence-based framework for the informed selection of quantification strategies in metaproteomics, and highlight the strengths and limitations of these approaches with respect to proteome coverage, dynamic range, quantitative accuracy, and error propagation. Our findings also have important implications for the biological interpretation of data derived from these strategies and lay the groundwork for future studies validating quantitative approaches in data-independent acquisition workflows.

Passive acoustic monitoring (PAM) enables non-invasive sampling of wildlife across broad spatial, temporal and taxonomic scales. Its ongoing and widespread use has generated unprecedented volumes of acoustic data, shifting the primary bottleneck from data collection to the storage, processing, integration, and interpretation of PAM outputs. Although many software tools exist to address these challenges, differences in their design, scope, and usability often create fragmented and complex analytical workflows. To identify the key barriers and opportunities shaping the implementation of PAM surveys, we conducted a structured expert solicitation involving 30 international practitioners working across terrestrial and aquatic ecosystems. Experts identified and ranked their most critical pain points in current PAM workflows, spanning data storage, processing, and interpretation. The top challenge identified related to accurate species identification using deep learning and artificial intelligence (AI) models, especially in noisy soundscapes or for underrepresented taxa. Eight additional priority challenges included workflow fragmentation, limited availability of user-friendly analytical and visualisation tools, uneven access to software, manual validation bottlenecks, computational constraints, and difficulties in data handling, standardisation, and sharing. Participants also proposed practical mitigation strategies for these priority challenges, supported by step-by-step guidance to help overcome key barriers. Together, these insights provide a roadmap toward more scalable, open-access, and collaborative software systems, which are increasingly essential to realise the full potential of PAM in global biodiversity monitoring.

Here we evaluated the performance of a previously published tiling PCR primer scheme by Ringlander et al. (2022) for whole-genome amplification of Hepatitis B virus (HBV) in combination with Oxford Nanopore sequencing. The primer set originally developed for Ion Torrent sequencing was adapted by removing platform-specific adapters and tested using clinical serum or plasma samples submitted for routine HBV genotyping and resistance testing. Two multiplexing strategies were compared: a single PCR pool containing all primers and a two-pool strategy with non-overlapping amplicons. Sequencing reads were processed using a Nanopore analysis pipeline, and genome coverage and amplicon performance were compared across samples spanning a wide Ct range and representing HBV genotypes A-E. Across all samples, the median genome coverage was approximately 50%, although recovery varied widely, ranging from complete failure to nearly full genomes. Combining all primers into a single PCR reaction, or separating overlapping amplicons into different reactions, had little overall impact on genome recovery, and no consistent differences between the two pooling strategies were observed. In contrast, amplification efficiency differed markedly between individual amplicons. Amplicons 1-5 generally produced higher sequencing depth, whereas amplicons 6-10 frequently showed low coverage and contributed to incomplete genome recovery. Genome coverage was strongly associated with Ct values, with higher coverage observed in samples with lower Ct values, while coverage was broadly similar across genotypes. These results demonstrate that the Ringlander et al. primer scheme can be adapted for multiplex PCR and Nanopore sequencing of HBV, but uneven amplicon performance limits consistent full-genome recovery and highlights the need for further optimization of HBV tiling PCR designs.

The early evolutionary history of modern domestic horses (Equus caballus/E. ferus caballus), known as the DOM2 lineage, is well documented due to numerous archaeological and ancient DNA (aDNA) studies. Although many uncertainties remain in the domestication timeline, current evidence suggests that the domestication of modern horses began in the Pontic-Caspian steppe at least [~]2700 BCE (before common era), or even earlier. However, it is not known how long remnant wild horse populations survived or when domestic horses were introduced into Northern Europe. In this study, we review the current knowledge of horse domestication, focusing on Northern Europe. We analysed prehistoric horses from western Russia to assess the body sizes of wild horses from the Ivanovskaya site (5900-3800 BCE) in the Pontic-Caspian steppe, and the body weight of one Lithuanian wild horse (4000-3800 BCE). Additionally, we analysed body sizes of Late Bronze Age-Early Roman Age horses (1100 BCE-300 CE; common era) and re-analysed body sizes and estimated rider weights of historic domestic horses from Lithuania (100-1400 CE). We searched for pathological changes and signs of bit wear indicative of bridling. Furthermore, we investigated maternal genetic diversity by sequencing ancient mitochondrial DNA. We found that wild horses from Ivanovskaya were intermediate in body size between earlier and more recent horses of the Eurasian Steppe, and that the Lithuanian wild horse weighed only [~]270 kg and Late Bronze Age-Early Roman Age horses 200-300 kg. Lithuanian domestic horses were pony-sized (< 130 cm on average). Bit wear was confirmed on one tooth, the oldest domestic horse in Lithuania (799-570 cal BCE). Another tooth showed signs of the Equine Odontoclastic Tooth Resorption and Hypercementosis (EOTRH) condition. Mitochondrial DNA was successfully amplified from one Ivanovskaya wild horse along with 25 other ancient samples, including Lithuanias oldest domestic horse. mtDNA diversity was high, revealing several maternal lineages.

Vessel-whale collisions are a growing global concern and remain challenging to quantify. Therefore, the use of proxies, such as Close Encounters (CEs) that comprise Surprise Encounters (SEs) and Near-Miss Events (NMEs), has been proposed and widely employed to assess collision risk. To better understand this risk in the Eastern North Atlantic, where maritime traffic is intensive, this study aimed to redefine and quantify CEs, and to assess detectability-related variables that may affect CE identification. CEs were assessed using a cetacean occurrence dataset collected between 2012 and 2024 on board cargo ships and oceanographic vessels. CEs thresholds were redefined based on Time to Potential Collision (TPC), rather than distance alone (as described in literature), to allow a more dynamic, risk-based, and speed-sensitive approach. In total, 1226 sightings of whales (baleen, sperm, and beaked whales) were recorded, of which 37.4% were classified as SEs and 2.0% as NMEs. The sperm whale, Physeter macrocephalus, was the species most frequently involved in CEs (13.9% of all CEs), followed by the Cuviers beaked whale, Ziphius cavirostris (11.8%). A Generalized Additive Model was used to assess the influence of detectability-related variables (i.e., meteorological conditions, whale taxa, vessel characteristics, and Marine Mammals Observers (MMOs) experience) on TPC. Significantly lower TPC values were observed with beaked whales, cargo ships, poor visibility conditions, and less experienced MMOs. The results of this study provide an CEs assessment in this region and contribute to the ongoing efforts to standardize CE quantification, by using TPC as a metric. This work also highlights the importance of decreased speeds and the presence of experienced MMOs on board to increase detection probability and TPC, thereby potentially minimizing collision risk.