Molecular Ecology Resources最新文献

One key challenge in characterizing plant communities is determining the relative abundance of distinct species in root biomass. Metabarcoding is increasingly used to estimate a species' proportion in root mass based on its proportion in sample reads, but results have been mixed in accurately converting sequencing output to species mass in mixture. We created calibration mixtures from four focal plant species to determine how the association between a species' proportion in mass and its proportion in sequencing reads of the rbcL chloroplast gene varied across sample years, soil depth, and non-target proportion of reads. We also determined whether including these explanatory variables in prediction models could improve accuracy. We found the association between a species' proportion in reads and its proportion in mass varied across years and non-target proportion of reads, and to a lesser extent, rooting depth, and incorporating these explanatory factors into prediction models improved prediction accuracy. A secondary objective was to determine the number of calibration levels and sequencing depth required to accurately predict a species' proportion in mass. Through simulations, we estimated that 42 calibration samples (seven proportional levels * three years * two depths) and 700 reads per sample consistently obtained accurate predictions for simple mixtures. The association between a species' proportion in mass and proportion in reads can vary considerably, and our study suggests that measuring and explaining this variation can lead to more accurate predictions of the relative abundance of plants within root biomass using metabarcoding.

Sampling environmental nucleic acids (eDNA and eRNA, collectively eNA) in aquatic systems facilitates the efficient exploration of the distribution of aquatic species. Since eRNA is inherently less stable than eDNA, eRNA may yield more spatiotemporally precise information about organisms, but this volatility also poses unique methodological challenges, making it unclear whether eDNA protocols are suitable for eRNA samples. To address this gap, we conducted experiments using naturally occurring eRNA and eDNA from the mitochondrial cytochrome b (CytB) gene from largemouth bass (Micropterus salmoides) along with DNA and RNA extracted from bluegill tissue (Lepomis megalotis). We first conducted a degradation experiment to test the efficacy of refrigeration for eRNA preservation (specifically mitochondrial messenger eRNA, emRNA), given its widespread use for eDNA samples. We then compared a suite of approaches for the long-term preservation and co-extraction of emRNA and eDNA in the laboratory. Despite the potential that the instability of eRNA might render eDNA approaches unsuitable, we found that methods developed for eDNA samples can be readily repurposed for emRNA. Contrary to our hypothesis that refrigeration of water samples might not efficiently preserve emRNA in the short term, samples in a cooler on ice showed no decrease in concentration or detectability over 25 h for largemouth bass (Tukey's, all p > 0.3). Filtration time (i.e., time spent at room temperature) also slightly reduced eRNA yields, with concentration decreasing as filtration time increased for largemouth bass emRNA (LM, p = 0.05), highlighting the importance of cold conditions throughout processing. Additionally, as we hypothesized, a low-cost chloroform extraction protocol yielded equivalent emRNA quantities to more expensive commercial kits for both largemouth bass and bluegill (Tukey's, p between methods > 0.8), in some cases even yielding higher concentrations than these methods. Overall, these results demonstrate the possible practical feasibility of eRNA sampling and provide guidance for future work on eRNA in natural systems.

Gene flow shapes evolutionary trajectories by introducing novel alleles, facilitating or retarding adaptation or eroding divergence among populations. Studies commonly infer gene flow through estimates of genetic admixture from methods that cluster individuals by allele-frequency similarity. However, the ability of these methods to reliably detect historical admixture remains poorly understood, particularly under spatially restricted dispersal and across a range of migration rates. Here, we evaluate how signals of admixture arise and decay during and after gene flow across a range of within- and between-population dispersal rates, using three common inference methods: ADMIXTURE, sNMF and PopCluster. Using forward-time simulations in a two-dimensional landscape, we modelled two metapopulations that diverged in isolation, experienced a pulse of secondary contact and subsequently returned to isolation. All three methods systematically underestimated admixture, with the bias increasing once gene flow ceased: inferred admixture averaged 56% of the true value at the end of gene flow, declined to 23% after 1000 generations and fell below 5% by 2000 generations, even where true admixture exceeded 20%. This underestimation was accompanied by corresponding overestimation of barrier strength, assessed using a metric analogous to cline width. Both patterns reflect the erosion of allele-frequency differences upon which these methods depend, which coincides with the rapid re-establishment of Hardy–Weinberg and linkage equilibrium following secondary contact. Our simulations show that, at least in some scenarios, the clustering-based admixture methods evaluated here cannot recover the signal of historical gene flow from present-day samples.

Natural history and agricultural collections contain hundreds of millions of specimens classified in terms of time, space and taxonomy. Since the first success of ancient DNA (aDNA) isolation in the 1980s, these repositories, including herbaria for plants, have been intensively used to support studies in taxonomy, macroevolution and genetic responses to anthropogenic activities. For herbarium specimens, aDNA is usually extracted from leaf samples and is highly fragmented (typically length of 50–100 bp). To optimise the amount of data retrieved and minimise destructive sampling, we isolated DNA from an unconventional plant tissue type—seed embryos. We carried out whole-genome sequencing and compared sequenced DNA quality between embryo and leaf tissue from the same specimen. We evaluated endogenous DNA proportion, median fragment length, damage fraction per site (λ), decay rates (k), nucleotide misincorporations and library complexity for three species: cultivated rice Oryza sativa, wild rice O. rufipogon and wild barley Hordeum spontaneum. In O. sativa, embryos exhibited significantly higher endogenous content and median fragment length than leaves. The superior DNA preservation was likely due to the protective role of the seed husk, which might play an important role in DNA preservation in plants collected in the tropics. By contrast, in temperate H. spontaneum, tissue type had minimal impact on DNA quality. Despite the minuscule size of the embryos, all derived genomic libraries were highly complex, sufficient for deep whole genome sequencing. These results highlight seed embryos as a promising alternative aDNA source for herbarium specimens, economic botany and anthropological museum collections.

Nuclear mitochondrial DNA segments (NUMTs) are genomic DNA fragments that originate from historical insertions of mitochondrial DNA sequences into the nuclear genome. During mitochondrial genome (mtgenome) assembly from short-read genome sequencing data, NUMT fragments may be misidentified and incorporated into mtgenome assemblies, leading to NUMT contamination. Although some assembly programs include steps to filter NUMTs, these approaches are not always effective. Here, we present MitoNumt, a multifunctional workflow. Using this pipeline, we recovered mtgenomes, complete NUMT (coexistence with the mtgenomes), and incomplete NUMT fragments from PacBio HiFi long-read sequencing data for five species of the genus Panthera and Puma concolor. We then used these sequences to check mtgenomes available in the NCBI database. NUMT contamination was detected in mtgenomes from all Panthera species examined, with 23 contaminated mtgenomes identified and contamination lengths ranging from 3 to 416 bp. In addition, phylogenetic trees reconstructed from NUMT fragments of at least 5000 bp consistently recovered a topology congruent with the currently accepted Panthera phylogeny. Overall, this workflow enables the identification of HiFi-supported mtgenomes and complete NUMTs, and the detection of NUMT contamination in assembled mtgenomes, thereby improving the reliability of mtgenome-based evolutionary and genetic studies.

DNA metabarcoding of freshwater macroinvertebrate samples can provide rapid and accurate identification of species diversity. Processing samples where macroinvertebrates are not separated from net contents can substantially reduce time and cost. We devised and tested a standardised method for processing combined kick/sweep samples using DNA metabarcoding to provide accurate estimates of macroinvertebrate species diversity. Kick and sweep samples were collected from 10 sites across Greater Melbourne known to vary in catchment land use, macroinvertebrate abundance and diversity as well as the type and volume of sampling debris. A sieving, blending and DNA extraction protocol was developed to reduce large debris, rocks and sand in samples, and to concentrate macroinvertebrates for metabarcoding. Variable percentages of the dry weight of samples from each site were used as a source of DNA for metabarcoding. We found that the macroinvertebrate species diversity recovered was mostly consistent when processing different percentages (20%–40%) of dry weight, but a minimum dry weight would be recommended for samples with low total dry weight. We present a method with a laboratory and bioinformatic workflow that enables the cost-effective and reliable processing of large volume samples, like those encountered in freshwater bioassessment. This metabarcoding approach has potential to be applied to any invertebrate biodiversity analysis where invertebrates are not separated from sampling debris, regardless of volume and composition, and used on samples varying in species abundance, diversity and density.

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.