Molecular Ecology Resources最新文献

In the last three decades, DNA sequencing of ancient animal osteological assemblages has become an important tool complementing standard archaeozoological approaches to reconstruct the history of animal domestication. However, osteological assemblages of key archaeological contexts are not always available or do not necessarily preserve enough ancient DNA for a cost-effective genetic analysis. Here, we develop an in-solution target-enrichment approach, based on 80-mer species-specific RNA probes (ranging from 306 to 1686 per species) to characterise (in single experiments) the mitochondrial genetic variation from eight domesticated animal species of major economic interest: cattle, chickens, dogs, donkeys, goats, horses, pigs and sheep. We also illustrate how our design can be adapted to enrich DNA library content and map the Y-chromosomal diversity within Equus caballus. By applying our target-enrichment assay to an extensive panel of ancient osteological remains, farm soil, and cave sediments spanning the last 43 kyrs, we demonstrate that minimal sequencing efforts are necessary to exhaust the DNA library complexity and to characterise mitogenomes to an average depth-of-coverage of 19.4 to 2003.7-fold. Our assay further retrieved horse mitogenome and Y-chromosome data from Late Pleistocene coprolites, as well as bona fide mitochondrial sequences from species that were not part of the probe design, such as bison and cave hyena. Our methodology will prove especially useful to minimise costs related to the genetic analyses of maternal and paternal lineages of a wide range of domesticated and wild animal species, and for mapping their diversity changes over space and time, including from environmental samples.

Escalating concern regarding the impacts of reduced genetic diversity on the conservation of endangered species has spurred efforts to obtain chromosome-level genomes through consortia such as the Vertebrate Genomes Project. However, assembling reference genomes for many threatened species remains challenging due to difficulties obtaining optimal input samples (e.g., fresh tissue, cell lines) that can characterise long-term conservation collections. Here, we present a pipeline that leverages genome synteny to construct high-quality genomes for species of conservation concern despite less-than-optimal samples and/or sequencing data, demonstrating its use on Hector's and Māui dolphins. These endemic New Zealand dolphins are threatened by human activities due to their coastal habitat and small population sizes. Hector's dolphins are classified as endangered by the IUCN, while the Māui dolphin is among the most critically endangered marine mammals. To assemble reference genomes for these dolphins, we created a pipeline combining de novo assembly tools with reference-guided techniques, utilising chromosome-level genomes of closely related species. The pipeline assembled highly contiguous chromosome-level genomes (scaffold N50: 110 MB, scaffold L50: 9, miniBUSCO completeness scores > 96.35%), despite non-optimal input tissue samples. We demonstrate that these genomes can provide insights relevant for conservation, including historical demography revealing long-term small population sizes, with subspecies divergence occurring ~20 kya, potentially linked to the Last Glacial Maximum. Māui dolphin heterozygosity was 40% lower than Hector's and comparable to other cetacean species noted for reduced genetic diversity. Through these exemplar genomes, we demonstrate that our pipeline can provide high-quality genomic resources to facilitate ongoing conservation genomics research.

DNA sequencing technology has undergone substantial improvements in recent years, to the extent that Third Generation Sequencing platforms are capable of massively generating long-reads. Amplicon sequencing has been among the most popular techniques due to its wide application in diverse fields of biological sciences. However, there is a lack of software specifically designed to analyse intra-individual genetic variation using amplicon long-read data. Here, we present CCS-consensuser, an end-to-end pipeline that generates consensus sequences from amplicon sequencing using high-fidelity reads produced by PacBio circular consensus sequencing (CCS). We evaluated the concordance of the results produced using CCS + CCS-consensuser and other sequencing platforms (Illumina and Sanger), as well as accuracy using a simulated dataset. This assessment showed that CCS amplicon data coupled with CCS-consensuser can produce high-quality sequences (PHRED > 30). The pipeline resulted in high proportions of identical sequence bins for real data, achieving up to 94.94% concordance with COI Sanger sequences and 92.61% with nuclear loci Illumina sequences (considering heterozygous loci), and 95.55% with a fully phased nuclear simulated dataset. Furthermore, our pipeline can be used to detect heteroplasmy in mtDNA, cross-contamination, resolve the phase of nuclear genes in diploid organisms, and conceivably for multi-copy gene systems such as rDNA. These results not only support its potential for application in studies using haploid data such as DNA barcoding, but also demonstrate its unique capacity to explore within individual haplotype variation. Therefore, our strategy shows promise for a broad range of applications in biology and medicine that have been challenging to assess using traditional techniques.

The percomorph fish clade Gobioidei is a suborder that comprises over 2200 species distributed in nearly all aquatic habitats. To understand the genetics underlying their species diversification, we sequenced and annotated the genome of the loach goby, Rhyacichthys aspro, an early-diverging group, and compared it with nine additional Gobioidei species. Within Gobioidei, the loach goby possesses the smallest genome at 594 Mb, and a rise in species diversity from early-diverging to more recently diverged lineages is mirrored by enlarged genomes and a higher presence of transposable elements (TEs), particularly DNA transposons. These DNA transposons are enriched in genic and regulatory regions and their copy number increase is strongly correlated with substitution rate, suggesting that DNA repair after transposon excision/insertion leads to nearby mutations. Consequently, the proliferation of DNA transposons might be the crucial driver of Gobioidei diversification and adaptability. The loach goby genome also points to mechanisms of ecological adaptation. It contains relatively few genes for lateral line development but an overrepresentation of synaptic function genes, with genes putatively under selection linked to synapse organisation and calcium signalling, implicating a sensory system distinct from other Gobioidei species. We also see an overabundance of genes involved in neurocranium development and renal function, adaptations likely connected to its flat morphology suited for strong currents and an amphidromous life cycle. Comparative analyses with hill-stream loaches and the European eel reveal convergent adaptations in body shape and saltwater balance. These findings shed new light on the loach goby's survival mechanisms and the broader evolutionary trends within Gobioidei.

Environmental DNA (eDNA) metagenomics sequences all DNA molecules present in environmental samples and has the potential of identifying virtually any organism from which they are derived. However, due to unacceptable levels of false positives and negatives, this approach is underexplored as a tool for biodiversity monitoring across the tree of life, particularly for non-microscopic eukaryotes. We present SeqIDist, a framework that combines multilocus BLAST matches against several reference databases followed by an analysis of sequence identity distribution patterns to disentangle false positives while revealing new biodiversity and increasing the accuracy of metagenomic approaches. We tested SeqIDist on an eDNA metagenomic dataset from a riverine site and compared the results to those obtained with an eDNA metabarcoding approach for benchmarking purposes. We start by characterising the biological community (~2000 taxa) across the tree of life at low taxonomic levels and show that eDNA metagenomics has a higher sensitivity than eDNA metabarcoding in discovering new diversity. We show that limited representation of whole genome sequences in reference databases can lead to false positives. For non-microscopic eukaryotes, eDNA metagenomic data often consist of a few sparse, anonymous sequences scattered across the genome, making metagenome assembly methods unfeasible. Finally, we infer eDNA source and residency time using read length distributions as a measure of decay status. The higher accuracy of SeqIDist opens the discussion of the potential of eDNA metagenomics for archived samples and its implementation in long-term biodiversity monitoring at a planetary scale.

Environmental DNA (eDNA) metabarcoding technologies promise significant advances in biodiversity monitoring, yet their application requires extensive optimisation and standardisation. Recent research demonstrated that increased sampling and analytical efforts are needed to improve biodiversity estimates, though fully optimising study designs is often hindered by resource constraints. Consequently, researchers must carefully navigate methodological trade-offs to design effective eDNA metabarcoding monitoring studies. We conducted a water eDNA survey of vertebrates in a Mediterranean watershed to identify key methodological factors influencing species richness and composition estimates. We examined the impacts of using high- versus low-capacity filtration capsules, varying levels of biological and technical replication, and the pooling of PCR replicates before indexing. The primary sources of variation identified were capsule filtration capacity and site replication across the watershed. While biological replication within sites and PCR replication also improved biodiversity estimates, their effects were comparatively smaller. Pooling PCR replicates before indexing performed more poorly than analysing them independently. Methodological impacts were stronger on terrestrial than on aquatic species. Based on these results, we recommend that priority should be given to high-capacity filtration and sampling across multiple sites. Site-level replication deserves lower priority, especially when filtering large water volumes. PCR replication is crucial for detecting rare species but should be balanced with increased site sampling and eventually site-level replication. Avoiding the pooling of PCR replicates is important to enhance sensitivity for rare species. Overall, we stress the importance of balancing methodological choices with resource constraints and monitoring goals, and we emphasise the need for research assessing methodological trade-offs in different study systems.

Genomic incompatibilities and differential ecological adaptation are thought to be fundamental mechanisms of speciation. In this study, we generated a chromosome-scale reference genome and annotation for Gopherus morafkai , the Sonoran Desert tortoise, and conducted a detailed analysis of genes under positive selection with its sister species, the Mojave Desert tortoise. They occupy desert habitats with differing seasonal rainfall patterns and have considerable behavioural and reproductive differences, yet maintain a narrow hybrid zone. We find high conservation of synteny with other chelonian species. Results show extensive positive selection (422 candidate genes) relating to eye development and function that may reflect differences in UV exposure, as well as core reproductive isolation mechanisms of sperm-egg recognition, spindle assembly checkpoint and sister chromatid pairing. Together, our results offer strong genomic support and speciation genomic resources for processes shaping reproductive isolation in chelonians.

Species abundance is a fundamental metric in ecology and conservation. Assessing how populations change across space time enables the identification of population trends and informs management and conservation decisions. However, measuring species abundance can be a challenging task, with logistical constraints, sampling biases, and detection limits inhibiting meaningful abundance estimates. Environmental DNA (eDNA) approaches have improved our ability to monitor species presence and biodiversity and may also serve as a tool for measuring species abundance. However, abundance estimates from eDNA typically rely on the correlation between species abundance and the concentration of target species' DNA in a sample, which may be hindered by complex interactions including variable amounts of DNA being shed by different individuals and environmental factors affecting DNA persistence. In this issue, Ai et al. (2025) present a new framework for estimating species abundance from eDNA that uses the amount of genetic diversity detected in a sample, specifically the number of segregating sites, to predict species abundance. The approach was developed and validated using in silico, in vitro, and in situ experiments, demonstrating improved correlations with species abundance compared to estimates based on eDNA concentration. With further improvements in detecting rare genetic variants, this approach has the potential to enhance our ability to quantify species abundance using eDNA.

Population genetic analyses use information from the site frequency spectrum to infer evolutionary processes. Two summary statistics, Watterson's estimator ( ${\theta }_w$ ) of genetic diversity, and Tajima's $D$ , used for detecting non-neutral evolution, are among the most frequently computed statistics utilising this information. However, missing information in genomic data, particularly as encoded in the Variant Call Format (VCF), can bias these estimates, leading to incorrect evolutionary inferences. We assessed the impact of missing data on the estimation of these statistics using various population genetic software packages (VCFtools, PopGenome, pegas and scikit-allel). By simulating neutral genomic data with varying levels of missing genotypes and sites, we found consistent underestimation of ${\theta }_w$ across programs. We found a consequent bias in estimates of Tajima's $D$ , though the direction varied by software. We developed and implemented correction methods as functions in an update of the popular pixy software, significantly reducing these biases. Our findings highlight the need for accurate data handling in population genomics to avoid misinterpretations of evolutionary phenomena.

Stomach content DNA (scDNA) analyses have become the standard practice for measuring trophic interactions. scDNA metabarcoding has provided broadscale diet composition data but can potentially underestimate certain prey species, as many of the recovered sequence reads come from predator-derived DNA, potentially resulting in incomplete diet information. Targeted detection (quantitative real-time PCR-qPCR) strategies allow for single-species detection from complex multispecies scDNA mixtures. A recent advancement in qPCR technology, high-throughput qPCR (HT-qPCR), allows simultaneous multispecies targeted detection and quantification of candidate species. Here, we describe the development and validation of a panel of single-species qPCR assays targeting the CO1 region of 28 prey fishes from the Great Lakes. We performed a three-step validation procedure for all assays using high-throughput OpenArray nanofluidic technology, measuring assay sensitivity, specificity and interference. Specifically, all assays were measured against dilution series of both target and non-target species DNA with detection limits ranging from 0.00503 pg to 0.0221 ng template DNA per reaction. Assays were tested for interference (e.g., PCR inhibitor) effects by creating artificial scDNA samples spiked with serially diluted target species DNA, resulting in a range of reduction in sensitivity (range = 0.0-125x fold). We validated the OpenArray qPCR assays using individual full-reaction TaqMan qPCR for nine of the assays, finding similar sensitivity despite expectations for the loss of sensitivity in the nanoscale reactions. HT-qPCR targeted detection has the potential to revolutionise scDNA (and eDNA) monitoring by significantly reducing laboratory effort to provide sensitive, targeted and quantitative detection data for multiple species simultaneously.