Molecular Ecology Resources最新文献

With the growing accessibility of low cost genome skimming, large-scale recovery of target genes in non-model species has become feasible, providing strong data for phylogenomic and evolutionary studies. However, existing tools for data assembly including Read2Tree, HybPiper, and GeneMiner still suffer from computational difficulty and assembly errors when processing genome skimming data, especially for low-level taxa that lack closely related genome references. Here, we present GeneMiner2, an updated version of GeneMiner, as an efficient and automated gene assembly and phylogenetic tool to overcome these limitations. Compared with the previous version, GeneMiner2 introduces three key optimizations by deploying a two-level hash table that speeds up k-mer filtering, applying fine-grained read selection with strand-orientation and structural-anomaly detection to handle complex heterozygous regions, and incorporating adaptive k-mer selection in the de Bruijn assembler. Together enabling accurate assembly of target genes without the need for closely related references. Using simulated datasets with low coverage and divergent references, we validated the robustness and improved accuracy of GeneMiner2 in the assembly of single-copy genes. Moreover, using genome skimming data from the subfamily Apioideae (Apiaceae), GeneMiner2 outperformed Read2Tree and HybPiper in accuracy, completeness, and speed. Equipped with a user-friendly graphical interface, GeneMiner2 integrates functions including assembly quality control, paralog detection, tree reconstruction, and divergence time calibration, offering a robust and efficient solution for phylogenetic inference using genomic level data. GeneMiner2 supports cross-platform operation. GeneMiner2 provides a user-friendly graphical interface for desktop users, and its high-performance command-line interface is specifically optimised for high-throughput analyses on Linux servers and computing clusters. Installation instructions, detailed documentation, and source code are available on GitHub (https://github.com/sculab/GeneMiner2).

Molecular techniques such as DNA metabarcoding are increasingly used to characterise parasite communities. However, relatively few studies have examined how sample processing methods influence detection rates. We used faecal samples collected from free-roaming horses to evaluate how parasite density and pre-processing methods influenced quantification of parasite richness, community composition, and detection of different taxa. Methods that concentrated parasites substantially increased parasite detection, especially at the low infection levels often seen in wildlife. Specifically, we found that DNA extracts from larval coproculture and a newly developed egg concentration approach detected approximately twice as many species and genera as extracts made directly from faecal matter. Although parasite richness was consistently lower in these faecal subsamples, overall parasite communities were still similar between pre-processing methods. Ultimately, the optimal method depends on research constraints and goals. Working with parasite larvae is more time intensive, but lower cost as larval parasites can be extracted using a lysis buffer approach which performs similarly to commercial extraction kits. DNA extraction from faecal subsamples misses rare and common taxa but minimises field processing. Our novel egg concentration method offers a compromise between relatively rapid processing and high sensitivity.

Permanent grasslands are predominantly composed of allogamous plant species that exhibit high levels of plant genetic diversity (PGD) within their populations. Grasslands with high PGD are more resilient to environmental stress and constitute valuable reservoirs of genetic resources for plant breeding. Therefore, monitoring PGD is the basis for detecting changes in PGD and for intervening accordingly. However, PGD monitoring is often neglected in biodiversity reports due to difficulties in taking representative samples and in using standardised and affordable indicators of PGD. Here we successfully applied two common approaches, multispecies amplicon sequencing (MSAS) and genotyping-by-sequencing (GBS), to assess PGD of agronomically relevant grassland species. Using MSAS, we were able to taxonomically distinguish five species (Dactylis glomerata L., Festuca pratensis Huds., Lolium perenne L., Trifolium pratense L. and T. repens L.) from multispecies samples and differentiate accessions within species, with fixation index (F_ST) values ranging from 0.014 for T. repens to 0.089 for L. perenne. Based on an extended L. perenne sample set containing mixtures of two cultivars at different ratios, mixtures containing both cultivars at 50% separated from the corresponding cultivars according to this ratio using MSAS and GBS. Furthermore, GBS enabled separation of samples containing two cultivars at a 75:25 ratio from the corresponding cultivars and the 50:50-ratio samples. These results indicate complementing applications of the two approaches in PGD monitoring. While we anticipate that MSAS with its cost-effectiveness could be applied to large-scale PGD monitoring, GBS with its lower detection limit could be applied to studies where cultivar composition shifts are of interest.

DNA extraction with an alkaline buffer system called ‘HotSHOT’ is widely used for barcoding because it is rapid, inexpensive, and voucher preserving, but it remains unclear whether sufficient genomic DNA (gDNA) remains in small vouchers for downstream use in genomics. We here evaluate gDNA quality and quantity before and after HotSHOT treatment of 11 insect families representing six orders. Some specimens were flash frozen immediately after collection, while others were kept for 1 week at tropical temperatures in ethanol to mimic Malaise trap conditions. Encouragingly, we show that gDNA of sufficiently high quality and quantity for genomic sequencing remained in specimens treated with HotSHOT. We also show that DNA integrity was strongly influenced by field storage, with specimens exposed to Malaise trap conditions showing such pronounced degradation that the standard HotSHOT treatment no longer significantly altered DNA quality. For control material, HotSHOT treatments involving longer exposure to high temperature led to smaller fragment lengths, with the effect apparently being influenced by the degree of specimen sclerotization. Our results thus suggest that optimised HotSHOT treatments, together with carefully controlled pre-extraction storage, preserve voucher gDNA of sufficient quality for downstream genomic analyses with both short-read and possibly even some long-read sequencing technologies. We provide protocol selection guidelines that improve voucher gDNA preservation in HotSHOT-treated samples. This is particularly important for many species which are only known from one or few specimens discovered during barcoding projects.

Environmental DNA (eDNA) provides powerful insights into species presence and community composition but remains limited in its capacity to infer species abundance or population structure. Here, we show that the deviation between within-sample haplotype frequencies and the overall population-level haplotype frequencies can be used to estimate the number of individual contributors to a given sample. We first establish the theoretical framework for approximating population haplotype frequencies directly from eDNA data, enabling application even in the absence of tissue-derived references. Building on this foundation, we introduce a maximum likelihood estimator to infer the number of contributors and assess its performance through simulations spanning a range of haplotype frequency distributions and noise scenarios. These approaches assume that all samples are drawn from a single, panmictic population. We find that accurate estimates are attainable when haplotypes are sufficiently variable, population frequencies are well-characterised, and samples are large enough to capture frequency deviations. By bridging population genetic theory and eDNA, our method complements existing molecular approaches and offers a novel path towards quantifying abundance from eDNA metabarcoding data.

Asserting which allele is ancestral or derived, known as polarisation, is a prerequisite of many population and quantitative genetic methods. One important application is the inference of the unfolded site-frequency spectrum (uSFS). The most widely used approaches are based on outgroup data. However, for studies on species with only distantly related outgroups, large divergence between the ingroup and outgroup can result in alignment difficulties and substantial missing data, causing many sites of interest to be lost. Here, we present PolarBEAR (Polarisation By Estimation of the Ancestral Recombination graph), a method that uses the local genealogies from the ancestral recombination graph (ARG) to infer ancestral states. We show that PolarBEAR reaches high accuracy in polarisation and uSFS estimation using simulations under several scenarios. This accuracy, however, heavily depends on the ARG reconstruction method employed. We also applied our method to human population data and compared it with the outgroup-based method est-sfs. Although PolarBEAR could not infer the ancestral state with high confidence at certain positions, it obtained results for positions that est-sfs could not polarise due to missing outgroup data. The polarisation results of the two methods were highly consistent at positions inferred by both methods. The two methods inferred similar uSFS, with PolarBEAR estimating slightly fewer high-frequency derived alleles. Furthermore, we demonstrate that PolarBEAR is robust across different mutation models in our simulations, while est-sfs exhibits a bias in the presence of heterogeneous base composition. PolarBEAR can complement outgroup-based methods, or replace them when no appropriate outgroup sequence is available.

Environmental DNA (eDNA) constitutes a valuable tool for monitoring terrestrial animal diversity, but outcomes are affected by multiple factors. Among these factors, the choice of sampling substrate and method is especially important and must be aligned with research objectives. We reviewed 245 published studies that utilise eDNA for terrestrial animal monitoring and compiled an overview of the most frequently used environmental substrates. Based on the reviewed literature, we provide a key description of each substrate, as well as its particular properties and limitations related to the detection of animal species across different spatial and temporal scales. We categorise these substrates into three groups: abiotic substrates (soil, water, air, sediment), biotic substrates (invertebrate samples, plant tissues, spiderwebs) and direct-evidence substrates (scat, footprints, shelters, feeding sites). In addition, we identify several key challenges with the interpretation of eDNA-based biodiversity monitoring, including false negatives and false positives, as well as the dynamics of spatial and temporal deviations. The latter concepts, which we propose and define in this review, describe the temporal and spatial discrepancies between the DNA source and its detection in a given sample. We reflect on how these temporal and spatial deviations are expected to affect eDNA data extracted from the different types of substrates and how knowledge of these dynamics can inform effective and accurate biomonitoring. In summary, this review provides a decision basis for designing terrestrial eDNA monitoring studies by summarising the properties and limitations of different substrates and contextualising the interpretation of results in light of substrate-specific challenges.

High-quality reference genome assemblies have become essential for deepening our understanding of biodiversity, yet obtaining them for many species remains surprisingly challenging. Drawing on experiences from the European Reference Genome Atlas (ERGA) community, we focus on permit and sample-handling procedures leading up to nucleic acid sequencing, covering tasks such as ensuring ethical and legal compliance, verifying accurate species identification, maintaining sample integrity during transport, and isolating high-quality DNA or nuclei. While many of the challenges and solutions we discuss are broadly relevant, our regulatory and logistical examples are primarily from Europe. By synthesising practical guidance, we highlight the crucial importance of taxonomic expertise, proper vouchering and biobanking, rigorous cold-chain management or alternative preservation methods, and emphasise adherence to packaging and shipping requirements for biological materials. We showcase examples spanning diverse regions, taxa and source materials, which underscore the importance of context-specific strategies and internationally harmonised protocols, particularly for metadata reporting. Our recommendations aim to support both small-scale projects and large initiatives, directing collective efforts to facilitate efficient sampling, vouchering and sample processing for future genomic studies.