Molecular Ecology Resources最新文献

Comparative genomic studies of closely related taxa are important for our understanding of the causes of divergence on a changing Earth. This being said, the genomic resources available for marine intertidal molluscs are limited and currently, there are few publicly available high-quality annotated genomes for intertidal species and for molluscs in general. Here we report transcriptome assemblies for six species of Patellogastropoda and genome assemblies and annotations for three of these species (Scurria scurra, Scurria viridula and Scurria zebrina). Comparative analysis using these genomic resources suggest that and recently diverging lineages (10-20 Mya) have experienced similar amounts of contractions and expansions but across different gene families. Furthermore, differences among recently diverged species are reflected in variation in the amount of coding and noncoding material in genomes, such as amount of repetitive elements and lengths of transcripts and introns and exons. Additionally, functional ontologies of species-specific and duplicated genes together with demographic inference support the finding that recent divergence among members of the genus Scurria aligns with their unique ecological characteristics. Overall, the resources presented here will be valuable for future studies of adaptation in molluscs and in intertidal habitats as a whole.

In recent years, numerous single nucleotide polymorphism (SNP) panel methods to genotype non-invasive faecal samples have been developed. However, none of these existing methods fit all of the criteria necessary to make a SNP panel broadly usable for conservation projects in any country-cost effective, streamlined lab protocol and user-friendly open-source bioinformatics protocols for panel design and analysis. Here, we present such a method and display its utility by developing a multiplex PCR SNP panel for conducting individual ID of snow leopards, Panthera uncia, from faecal samples. The SNP panel we present consists of 144 SNPs and utilises next-generation sequencing technology. We validate our SNP panel with paired tissue and faecal samples from zoo individuals, showing a minimum of 96.7% accuracy in allele calls per run. We then generate SNP data from 235 field-collected faecal samples from across Pakistan to show that the panel can reliably identify individuals from low-quality faecal samples of unknown age and is robust to contamination. We also show that our SNP panel has the capability to identify first-order relatives among sampled zoo individuals and provides insights into the geographic origin of samples. This SNP panel will empower the snow leopard research community in their efforts to assess local and global snow leopard population sizes. More broadly, we present a SNP panel development method that can be used for any species of interest for which adequate genomic reference data is available.

Molecular methods such as DNA/eDNA metabarcoding have emerged as useful tools to document the biodiversity of complex communities over large spatio-temporal scales. We established an international Marine Biodiversity Observation Network (ARMS-MBON) combining standardised sampling using autonomous reef monitoring structures (ARMS) with metabarcoding for genetic monitoring of marine hard-bottom benthic communities. Here, we present the data of our first sampling campaign comprising 56 ARMS units deployed in 2018-2019 and retrieved in 2018-2020 across 15 observatories along the coasts of Europe and adjacent regions. We describe the open-access data set (image, genetic and metadata) and explore the genetic data to show its potential for marine biodiversity monitoring and ecological research. Our analysis shows that ARMS recovered more than 60 eukaryotic phyla capturing diversity of up to ~5500 amplicon sequence variants and ~1800 operational taxonomic units, and up to ~250 and ~50 species per observatory using the cytochrome c oxidase subunit I (COI) and 18S rRNA marker genes, respectively. Further, ARMS detected threatened, vulnerable and non-indigenous species often targeted in biological monitoring. We show that while deployment duration does not drive diversity estimates, sampling effort and sequencing depth across observatories do. We recommend that ARMS should be deployed for at least 3-6 months during the main growth season to use resources as efficiently as possible and that post-sequencing curation is applied to enable statistical comparison of spatio-temporal entities. We suggest that ARMS should be used in biological monitoring programs and long-term ecological research and encourage the adoption of our ARMS-MBON protocols.

Collagen is the most ubiquitous protein in the animal kingdom and one of the most abundant proteins on Earth. Despite having a relatively repetitive amino acid sequence motif that enables its triple helical structure, in type 1 collagen, that dominates skin and bone, there is enough variation for its increasing use for the biomolecular species identification of animal tissues processed or degraded beyond the amenability of DNA-based analyses. In recent years, this has been most commonly achieved through the technique of collagen peptide mass fingerprinting (PMF) known as ZooMS (Zooarchaeology by Mass Spectrometry), applied to the analysis of tens of thousands of samples across over one hundred studies in the past decade alone. However, a robust means to quantify variation between these fingerprints remains elusive, despite being increasingly required due to the shift towards a wider range of wild fauna and those that are more distantly related from currently known sequences. This is particularly problematic in fish due to their greater sequence variation. Here we evaluate the quantification of the relative closeness of collagen fingerprints between families using ANOSIM and a modified SIMPER analysis, incorporating relative peak intensity. Our results show a clear correlation between sequence differentiation and statistical distance of PMFs, indicating that the additional complexity of type 1 collagen in fish could directly affect the efficacy of biomolecular techniques such as ZooMS. Furthermore, this multivariate statistical analysis demonstrates that PMFs in fish are substantively more distinct than those of mammalian or amphibian taxa.

The boll weevil, Anthonomus grandis grandis Boheman, and thurberia weevil, Anthonomus grandis thurberiae Pierce, together comprise a species complex that ranges throughout Mexico, the southwestern regions of the United States and parts of South America. The boll weevil is a historically damaging and contemporaneously threatening pest to commercial upland cotton, Gossypium hirsutum L. (Malvales: Malvaceae), whereas the thurberia weevil is regarded as an innocuous non-pest subspecies that is mostly found on non-cultivated Thurber's or Arizona cotton, Gossypium thurberi L., throughout its native range in western Mexico and the southwestern United States. Recent independent analyses, using mitochondrial and whole-genome markers, have suggested the independent evolution of these lineages is more attributable to geographic isolation than biotic factors. We suggest a combination of drivers after employing comparative genomic, population genetic and pangenome methodologies to identify large and small polymorphisms. By leveraging genetic differences, we determined 39,310 diagnostic loci between the subspecies, find genes under selection, and model the subspecies' shared and unique evolutionary history. Interestingly, structural variations capture a large proportion of genes at the population level and demographic reconstruction suggests a split between approximately 3,320-16,300 before present (YBP), which coincides with cotton cultivation in Mesoamerica, approximately 3,000-5,000 YBP. Observed polymorphisms are enriched for reproductive, regulatory, and metabolic genes, which may be attributed to the subspecies split and coevolution with cultivated cotton. Our results demonstrate the utility of a holistic, comparative framework utilising small and large polymorphisms to reconstruct demography and identify genetic novelty via pangenomics.

Known for its remarkable diversity and ecological importance, the fungal kingdom remains largely unexplored. In fact, the number of unknown and undescribed fungi is predicted to exceed the number of known fungal species by far. Despite efforts to uncover these dark fungal taxa, we still face inherent sampling biases and methodological limitations. Here, we present a framework that combines taxonomic knowledge, molecular biology and data processing to explore the fungal biodiversity of enigmatic aquatic fungal lineages. Our work is based on serial screening of environmental fungal cells to approach unknown fungal taxa. Microscopic documentation is followed by DNA analysis of laser micro-dissected cells, coupled with a ribosomal operon barcoding step realised by long-read sequencing, followed by an optional whole genome sequencing step. We tested this approach on a range of aquatic fungal cells mostly belonging to the ecological group of aquatic hyphomycetes derived from environmental samples. From this initial screening, we were able to identify 60 potentially new fungal taxa in the target dataset. By extending this methodology to other fungal lineages associated with different habitats, we expect to increasingly characterise the molecular barcodes of dark fungal taxa in diverse environmental samples. This work offers a promising solution to the challenges posed by unknown and unculturable fungi and holds the potential to be applied to the diverse lineages of undescribed microeukaryotes.

Pardosa spiders, belonging to the wolf spider family Lycosidae, play a vital role in maintaining the health of forest and agricultural ecosystems due to their function in pest control. This study presents chromosome-level genome assemblies for two allied Pardosa species, P. laura and P. agraria. Both species' genomes show a notable expansion of helitron transposable elements, which contributes to their large genome sizes. Methylome analysis indicates that P. laura has higher overall DNA methylation levels compared to P. agraria. DNA methylation may not only aids in transposable element-driven genome expansion but also positively affects the three-dimensional organisation of P. laura after transposon amplification, thereby potentially enhancing genome stability. Genes associated with hyper-differentially methylated regions in P. laura (compared to P. agraria) are enriched in functions related to mRNA processing and energy production. Furthermore, combined transcriptome and methylome profiling has uncovered a complex regulatory interplay between DNA methylation and gene expression, emphasising the important role of gene body methylation in the regulation of gene expression. Comparative genomic analysis shows a significant expansion of cuticle protein and detoxification-related gene families in P. laura, which may improve its adaptability to various habitats. This study provides essential genomic and methylomic insights, offering a deeper understanding of the relationship between transposable elements and genome stability, and illuminating the adaptive evolution and species differentiation among allied spiders.

While a best practice for evaluating the behaviour of genetic clustering algorithms on empirical data is to conduct parallel analyses on simulated data, these types of simulation techniques often involve sampling genetic data with replacement. In this paper we demonstrate that sampling with replacement, especially with large marker sets, inflates the perceived statistical power to correctly assign individuals (or the alleles that they carry) back to source populations-a phenomenon we refer to as resampling-induced, spurious power inflation (RISPI). To address this issue, we present gscramble, a simulation approach in R for creating biologically informed individual genotypes from empirical data that: (1) samples alleles from populations without replacement and (2) segregates alleles based on species-specific recombination rates. This framework makes it possible to simulate admixed individuals in a way that respects the physical linkage between markers on the same chromosome and which does not suffer from RISPI. This is achieved in gscramble by allowing users to specify pedigrees of varying complexity in order to simulate admixed genotypes, segregating and tracking haplotype blocks from different source populations through those pedigrees, and then sampling-using a variety of permutation schemes-alleles from empirical data into those haplotype blocks. We demonstrate the functionality of gscramble with both simulated and empirical data sets and highlight additional uses of the package that users may find valuable.

Illegal wildlife trade is a growing problem internationally. Poaching of animals not only leads to the extinction of populations and species but also has serious consequences for ecosystems and economies. This study introduces a molecular marker system that authorities can use to detect and substantiate wildlife trafficking. SNPSTR markers combine short tandem repeats with single nucleotide polymorphisms within an amplicon to increase discriminatory power. Within the FOGS (Forensic Genetics for Species Protection) project, we have established SNPSTR marker sets for 74 vertebrate species. On average, each set consists of 19 SNPSTR markers with 82 SNPs per set. More than 1300 SNPSTR markers and over 300 STR markers were identified. Also, through its biobanking pipeline, the FOGS project enabled the cryopreservation of somatic cells from 91 vertebrate species as well as viable tissues for later cell initiation from a further 109 species, providing future strategies for ex situ conservation. In addition, many more fixed tissues and DNA samples of endangered species were biobanked. Therefore, FOGS was an interdisciplinary study, combining molecular wildlife forensics and conservation tools. The SNPSTR sets and cell culture information are accessible through the FOGS database (https://fogs-portal.de/data) that is open to scientists, researchers, breeders and authorities worldwide to protect wildlife from illegal trade.

The exon capture approach allows for sequencing a large number of loci to reconstruct phylogenetic relationships at varying taxonomic levels. In order to efficiently recover the targeted loci, the probes designed to capture the exons need to be genetically sufficiently similar to bind to the DNA, with a proposed limit of 10% of divergence. However, this threshold has never been tested with a specific protocol. We have designed a set of probes to capture 1125 exons in the Neogastropoda (Mollusca, Gastropoda), processed with the same protocol from the field to the DNA sequencing to control for potential bias in DNA quantity and quality. We sequenced 30 different species, including 14 species of Neogastropoda and 16 species of Caenogastropoda non-Neogastropoda. Each species includes five specimens, for a total of 150 specimens, and for four specimens among the 150, DNA extracts were aliquoted in four samples, sequenced separately, to estimate the intraspecific and intraspecimen variability in capture success. Our results confirm the impact of genetic distance on the success of exon capture with a negative linear correlation between the genetic distance and the number of exons captured for each sample. Consequently, designing new capture probes would allow for capturing exons in genetically more distant groups without the need to redesign a new set of exons.