Molecular Ecology Resources最新文献

Documenting accelerating global biodiversity decline requires monitoring tools that can operate across large spatial scales and repeated timeframes. Analysis of airborne environmental DNA (eDNA) is an emerging method used to track species distributions, but it is unknown whether airborne eDNA retains coherent ecological signals across terrestrial landscapes, or whether atmospheric mixing and DNA transport make it too spatially diffuse to resolve meaningful macroecological patterns. To address this question, we conducted a biodiversity survey using car-mounted airborne eDNA sampling along a repeated 1155 km route across south-western Western Australia, spanning the Southwest Australian biodiversity hotspot and adjacent inland regions. This extensive and environmentally heterogeneous region faces ongoing pressures from habitat loss, invasive species and climate change, highlighting the need for scalable biodiversity monitoring approaches. Samples were collected at ~26 km intervals and analysed using metabarcoding assays targeting plants, vertebrates and arthropods, with generalised dissimilarity modelling used to assess environmental drivers of community turnover. We detected a broad range of plants and animals, including species of ecological and biosecurity importance. Different taxonomic groups showed distinct spatial scales of airborne eDNA community similarity and beta diversity was structured primarily by habitat and environmental gradients rather than geographic distance alone. This indicates that airborne eDNA did not simply reflect spatially homogenised biological material but retained ecological structure informative of macroecological patterns. Together, these findings demonstrate that car-mounted airborne eDNA can recover ecologically meaningful patterns of community turnover across heterogeneous terrestrial landscapes and support landscape-scale biodiversity assessment.

Environmental DNA (eDNA) exists in three states: membrane-bound, adsorbed and dissolved. These states differ in persistence and degradation, strongly influencing the interpretation of eDNA data. Despite this, they have rarely been separated and analyzed independently from environmental samples. We developed a state-sorting workflow to isolate and analyze them, applying it to samples from 221 sites from 58 streams across eight lake watersheds with COI and ITS metabarcoding, targeting metazoans and plants, respectively, to reveal differences in biodiversity content and transport dynamics. Our results show that all three states contain both shared and unique taxonomic diversity of metazoan eDNA. However, the plant eDNA was only detected in the membrane-bound state. For metazoans, membrane-bound eDNA contained 87.8% of observed ASVs, far exceeding the adsorbed (37.2%) and dissolved (20.5%) states. Only membrane-bound eDNA showed evidence of downstream transport, but its extent varied among watersheds due to local hydrology. While upstream eDNA was transported to stream–lake confluences, lake surface samples showed a turnover in community composition. Clarifying the fate of membrane-bound eDNA within lakes will enhance catchment-level detection from lake samples and understanding of lake hydrodynamics. Of the environmental parameters assessed, water temperature was most strongly aligned with changes in community composition between sites. Most previous studies have likely captured the majority of the eDNA diversity within their samples by inadvertently targeting the membrane-bound state. This study demonstrates the utility of eDNA state-sorting, but the methods require further refinement. Analyzing states independently improves the interpretation of eDNA data and elucidates the processes governing eDNA fate and transport.

Accurate knowledge of phylogenetic relationships and divergence time among plant species composing a regional flora is crucial for understanding the origin of the biodiversity patterns we observe today. Despite advances in phylogenomics, resources available for reconstructing regional phylogenies are still largely incomplete and poorly resolved at the species level. We developed a workflow to assemble a phylogenetic dataset for a regional flora using Angiosperms353 target-enrichment and high-throughput genome sequencing. We sampled tissues from freshly collected plants and herbarium specimens representing the angiosperm diversity of the Geneva canton in Switzerland (1098 species). We used ORTHOSKIM to recover targeted nuclear genes and plastid loci from off-target reads, estimated relationships and time divergence using IQTREE, weighted-ASTRAL and treePL, and compared the results obtained from nuclear and plastid genes. We recovered a mean of 289 nuclear and 54 plastid genes for 1316 taxa, representing 92% of the species native to the Geneva canton. We demonstrate that nuclear genes provide increased resolution and phylogenetic support, but similar divergence time estimates compared to plastomes. Our workflow based on Angiosperms353 data provides a phylogenetic framework for an entire regional flora that is consistent with current systematic knowledge and more resolved and complete at the infrageneric level than trees obtained from phylogenetic resources available for angiosperms. This type of genomic data opens perspectives for fine-scale biodiversity and conservation research that integrates evolutionary history.

A comprehensive understanding of life history is vital to successful species conservation and management. When different life history stages are accompanied by considerable morphological or cryptic variation, such as the egg and larval phases exhibited by most fishes, genomic tools are essential for identifying species so that early-life ecology questions can be studied. Genotyping-in-thousands by sequencing (GT-seq) has recently emerged as a targeted and efficient approach for species identification. We leveraged existing genomic and transcriptomic data to develop a GT-seq panel capable of differentiating the members of the Coregonus artedi complex, a radiation of salmonids in the Laurentian Great Lakes whose members are indistinguishable with mitochondrial DNA barcoding loci and are the focus of bi-national conservation initiatives. Our panel of 494 loci was able to assign fishes in the C. artedi complex to species and lake. We examined cross-amplification in other coregonines with overlapping distributions and found that congeneric Lake Whitefish (C. clupeaformis) cross-amplified at 94% of loci and confamilial Round and Pygmy Whitefish (Prosopium spp.) cross-amplified at 42% and 38% of loci, respectively. We adapted bioinformatic probes to account for Prosopium-specific variants including 22 new SNPs and developed a whitelist of 428 SNPs capable of distinguishing these whitefishes. Finally, we demonstrated performance by identifying 3066 coregonine larvae and juveniles collected in spring 2019–2021 from Lake Superior. These results hold promise for future insights into the species-specific ecology of early life coregonines and demonstrate the flexibility of GT-seq panels, which may cross-amplify hundreds of informative genome-wide loci in related taxa.

Environmental DNA (eDNA) analyses have been applied to terrestrial environments for over a decade, yet knowledge of the dynamics of eDNA deposition, movement and degradation remains limited. To address this, we conducted a controlled experiment over 1 year to assess the persistence of eDNA from an arboreal mammal across four substrates (water, sediment, sheltered nest-box surfaces, and exposed nest-box surfaces). Environmental DNA deposited by captive individuals was sampled repeatedly following removal of animals and analysed using both species-specific qPCR and metabarcoding. We modelled degradation using quantitative decay, detection probability, and conditional decay frameworks, and applied a random breakage model to estimate theoretical fragment persistence. Decay followed first-order exponential kinetics in water and on nest box surfaces but not in sediment, which exhibited high stochasticity. We observed a large difference in degradation rates between substrates, with exponential decay models revealing half-lives ranging from 7.3 days in water to 276 days on sheltered internal surfaces. Rapid decay in water restricted detections to approximately 77 days, while persistence models predicted that sheltered surfaces could retain detectable DNA for more than 4 years (> 1700 days), indicating the potential for prolonged accumulation of legacy DNA in protected environments. While species-specific qPCR offered higher sensitivity than metabarcoding, both methods had parallel decay patterns. Our findings indicate that substrate selection is a critical decision when designing an eDNA survey, as there is a trade-off between maximising detection probability and maintaining temporal resolution.

DNA library construction methods can affect the recovery of ancient DNA, thus influencing downstream analyses. While single-stranded library preparation (ssLib) has been shown to outperform double-stranded (dsLib) for highly degraded vertebrate host DNA, especially for samples older than 40,000 years, few studies have examined how library protocols shape ancient microbial community reconstruction. Here, we compare the sequencing output of paired ssLib and dsLib dental calculus libraries generated from 12 Neanderthals and two Chalcolithic humans, prepared using implementations of the Gansauge et al. and Meyer and Kircher protocols, respectively, and sequenced with identical Illumina chemistry. We compared read length and GC%, read duplication and taxonomic profiles across normalization strategies to assess protocol-specific biases. Double-stranded libraries retained a significantly higher proportion of sequenced reads throughout data processing (dsLib 72.1%, ssLib 37.9%), a higher proportion of oral reads (dsLib 9.78%, ssLib 6.75%), significantly longer median oral DNA read lengths (dsLib 57.5 bp, ssLib 50.5 bp) and more GC-rich fragments (dsLib 60.5% GC, ssLib 52.5% GC). In contrast, ssLibs exhibited slightly higher Shannon diversity and a greater proportion of unique reads. Despite these differences, species richness and overall community composition was not significantly different between protocols, with individual and preservation status explaining the most variance. Stratifying reads by length (< 50 bp vs. ≥ 50 bp) resulted in different classification rates but only had minor effects on diversity estimates. Together, these results demonstrate that dsLib and ssLib protocols impose distinct trade-offs and library choice should be guided by study-specific goals.

A central challenge in evaluating biodiversity using environmental DNA (eDNA) metabarcoding is that each primer set has biases resulting in selective amplification of taxonomic diversity. Here we test 11 primer pairs to assess Central Pacific coral reef diversity in the five kingdoms of marine eukaryotes: Chromista, Fungi, Metazoa, Plantae and Protozoa. Zero-width OTUs (ZOTUs) were compared to public sequence databases and resolved to the finest taxonomic rank possible. Across all primers, we recovered 421 distinct taxa from five kingdoms in 35 phyla, comprising 62 classes. The number of taxa and taxonomic groups recovered varied widely. Nearly all primers recovered a large fraction of metazoan taxa, and several also recovered a large portion of taxa belonging to Chromista. Based on our results, most primers we tested here can be clustered into four groups: (1) the ‘fish’ primers, specialized for fishes, (2) the ‘diverse’ primers, which recover the highest number of identifications at lower taxonomic levels, (3) the ‘general’ primers, which perform moderately well across the tree of life, and (4) the algae primers. Taxonomic assignments tended to decrease with taxonomic rank, from 86%–100% at the phylum level to 35%–77% at the species level. Primers specialized for specific groups (i.e., fishes) tended to recover fewer taxa at higher taxonomic resolution, while more general primers tended to recover more taxa, though at lower taxonomic resolution. While each primer set proved uniquely informative for some taxa, the taxon recovery profiles provided here should aid researchers in matching the taxonomic specificity of environmental metabarcoding primers with research questions of interest.

Monitoring marine biodiversity requires approaches capable of capturing its spatial and temporal complexity. DNA metabarcoding coupled with Autonomous Reef Monitoring Structures (ARMS) is increasingly used for this purpose, yet most applications still pool all sessile fractions and rarely benchmark molecular outputs against photographic observations. Here, we combined photographic analysis with cytochrome c oxidase I (COI) metabarcoding across 10 north-western Mediterranean sites to compare and refine ARMS-based monitoring protocols. We first optimized laboratory procedures (DNA extraction and polymerase choice) and applied the control-driven, replicate-aware VTAM pipeline to minimize false positives and ensure traceability. We then conducted the first face-by-face comparison of α- and β-diversity between imaging and eDNA, metabarcoding each ARMS face separately rather than pooling samples. Metabarcoding detected ~15× higher site-level richness and revealed stronger correlations with geographic distance and environmental gradients—which stemmed from its finer taxonomic resolution—whereas photography provided complementary information on macro-taxa and surface cover. For metabarcoding, processing each face separately yielded much higher richness and stronger β-diversity–distance correlations than with the NOAA pooling protocol, demonstrating that pooling inflates sampling variance, weakening ecological signal. Grouping the 17 faces into five structural categories offered a more operational alternative while further increasing α-diversity and strengthening β-diversity correlations. Overall, our results show that retaining ARMS microhabitat structure is critical for maximizing metabarcoding performance. Using five structural sessile fractions per ARMS combined with a control-driven bioinformatic workflow provides a reproducible, scalable framework for long-term eDNA monitoring and early detection of biodiversity change.

With the massive increase in genomic resources, it is becoming increasingly popular to analyse thousands of loci across many species. However, many of the available genomes are not annotated, which hinders an efficient search for orthologous protein-coding genes. Here, we aim to develop a semi-automated pipeline and compare four genomic annotation methods (BRAKER2, BUSCO, Miniprot and Scipio). Our results highlight the importance of integrating multiple annotation tools to optimise ortholog detection and improve genomic studies. Each annotation method showed different strengths. BRAKER2 annotated a substantial number of genes. BUSCO, despite limitations inherent to its reference database, identified a higher number of orthologs. Miniprot exhibited notable flexibility in accommodating diverse protein datasets, whereas Scipio successfully recovered a considerable set of genes that were not detected by the other tools. The combination of these tools allowed for more comprehensive ortholog detection. Taking advantage of this pipeline, we developed a comprehensive dataset of orthologous genes for swallowtail butterflies (Lepidoptera: Papilionidae), called Papilionidae_odb, which will facilitate future studies, especially for a non-model group with abundant genomic data and few transcriptomic resources. We tested Papilionidae_odb by inferring a robust phylogenetic framework for Leptocircini using 142 complete genomes, which improved branch support for some phylogenetic relationships, although challenges remained in resolving relationships within certain species groups, likely due to rapid radiations. Our results highlight the complementary nature of the annotation methods and suggest that combining these tools can yield more accurate results in genomic research. This approach was implemented in a Snakemake workflow called CASIO (Combining Annotation Software to Identify Orthologous genes) and can easily be applied to other non-model groups to improve genomic datasets in diverse taxa where transcriptomic resources are still limited.