Molecular Ecology Resources最新文献

Single nucleotide polymorphism (SNP) panels are powerful tools for assessing the genetic population structure and dispersal of fishes and can enhance management practices for commercial, recreational and subsistence mixed-stock fisheries. Arctic Char (Salvelinus alpinus), Brook Trout (Salvelinus fontinalis) and Lake Whitefish (Coregonus clupeaformis) are among the most harvested and consumed fish species in Northern Indigenous communities in Canada, contributing significantly to food security, culture, tradition and economy. However, genetic resources supporting Indigenous fisheries have not been widely accessible to northern communities (e.g. Inuit, Cree, Dene). Here, we developed Genotyping-in-Thousands by sequencing (GT-seq) panels for population assignment and mixed-stock analyses of three salmonids, to support fisheries stewardship or co-management in Northern Canada. Using low-coverage Whole Genome Sequencing data from 418 individuals across source populations in Cambridge Bay (Nunavut), Great Slave Lake (Northwest Territories), James Bay (Québec) and Mistassini Lake (Québec), we developed a bioinformatic SNP filtering workflow to select informative SNP markers from genotype likelihoods. These markers were then used to design GT-seq panels, thus enabling high-throughput genotyping for these species. The three GT-seq panels yielded an average of 413 autosomal loci and were validated using 525 individuals with an average assignment accuracy of 83%. Thus, these GT-seq panels are powerful tools for assessing population structure and quantifying the relative contributions of populations/stocks in mixed-stock fisheries across multiple regions. Interweaving genomic data derived from these tools with Traditional Ecological Knowledge will ensure the sustainable harvest of three culturally important salmonids in Indigenous communities, contributing to food security programmes and the economy in Northern Canada.

The ammonia monooxygenase subunit A (amoA) gene has been used to investigate the phylogenetic diversity, spatial distribution and activity of ammonia-oxidising archaeal (AOA) and bacterial (AOB), which contribute significantly to the nitrogen cycle in various ecosystems. Amplicon sequencing of amoA is a widely used method; however, it produces inaccurate results owing to the lack of a 'universal' primer set. Moreover, currently available primer sets suffer from amplification biases, which can lead to severe misinterpretation. Although shotgun metagenomic and metatranscriptomic analyses are alternative approaches without amplification bias, the low abundance of target genes in heterogeneous environmental DNA restricts a comprehensive analysis to a realisable sequencing depth. In this study, we developed a probe set and bioinformatics workflow for amoA enrichment sequencing using a hybridisation capture technique. Using metagenomic mock community samples, our approach effectively enriched amoA genes with low compositional changes, outperforming amplification and meta-omics sequencing analyses. Following the analysis of metatranscriptomic marine samples, we predicted 80 operational taxonomic units (OTUs) assigned to either AOA or AOB, of which 30 OTUs were unidentified using simple metatranscriptomic or amoA gene amplicon sequencing. Mapped read ratios to all the detected OTUs were significantly higher for the capture samples (50.4 ± 27.2%) than for non-capture samples (0.05 ± 0.02%), demonstrating the high enrichment efficiency of the method. The analysis also revealed the spatial diversity of AOA ecotypes with high sensitivity and phylogenetic resolution, which are difficult to examine using conventional approaches.

Symbiotic microbiota strongly impact host physiology. Amphibians and reptiles occupy a pivotal role in the evolutionary history of Animalia, and they are of significant ecological, economic, and scientific value. Many prior studies have found that symbiotic microbiota in herpetofaunal species are closely associated with host phylogeny, physiological traits, and environmental factors; however, insufficient integrated databases hinder researchers from querying, accessing, and reanalyzing these resources. To rectify this, we built the first herpetofaunal microbiota database (HMicroDB; https://herpdb.com/) that integrates 11,697 microbiological samples from 337 host species (covering 23 body sites and associated with 23 host phenotypic or environmental factors), and we identified 11,084 microbial taxa by consistent annotation. The standardised analysis process, cross-dataset integration, user-friendly interface, and interactive visualisation make the HMicroDB a powerful resource for researchers to search, browse, and explore the relationships between symbiotic microbiota, hosts, and environment. This facilitates research in host-microbiota coevolution, biological conservation, and resource utilisation.

Organelle genomes serve as crucial datasets for investigating the genetics and evolution of plants and animals, genome diversity, and species identification. To enhance the collection, analysis, and visualisation of such data, we have developed a novel open-source software tool named Organelle Genome Utilities (OGU). The software encompasses three modules designed to streamline the handling of organelle genome data. The data collection module is dedicated to retrieving, validating and organising sequence information. The evaluation module assesses sequence variance using a range of methods, including novel metrics termed stem and terminal phylogenetic diversity. The primer module designs universal primers for downstream applications. Finally, a visualisation pipeline has been developed to present comprehensive insights into organelle genomes across different lineages rather than focusing solely on individual species. The performance, compatibility and stability of OGU have been rigorously evaluated through benchmarking with four datasets, including one million mixed GenBank records, plastid genomic data from the Lamiaceae family, mitochondrial data from rodents, and 308 plastid genomes sourced from various angiosperm families. Based on software capabilities, we identified 30 plastid intergenic spacers. These spacers exhibit a moderate evolutionary rate and offer practical utility comparable to coding regions, highlighting the potential applications of intergenic spacers in organelle genomes. We anticipate that OGU will substantially enhance the efficient utilisation of organelle genomic data and broaden the prospects for related research endeavours.

Phylogenetic studies now routinely require manipulating and summarizing thousands of data files. For most of these tasks, currently available software requires considerable computing resources and substantial knowledge of command-line applications. We develop an ultrafast and memory-efficient software, SEGUL, that performs common phylogenomic dataset manipulations and calculates statistics summarizing essential data features. Our software is available as standalone command-line interface (CLI) and graphical user interface (GUI) applications, and as a library for Rust, R and Python, with possible support of other languages. The CLI and library versions run native on Windows, Linux and macOS, including Apple ARM Macs. The GUI version extends support to include mobile iOS, iPadOS and Android operating systems. SEGUL leverages the high performance of the Rust programming language to offer fast execution times and low memory footprints regardless of dataset size and platform choice. The inclusion of a GUI minimizes bioinformatics barriers to phylogenomics while SEGUL's efficiency reduces economic barriers by allowing analysis on inexpensive hardware. Our support for mobile operating systems further enables teaching phylogenomics where access to computing power is limited.

Lignin, as an abundant organic carbon, plays a vital role in the global carbon cycle. However, our understanding of the global lignin-degrading microbiome remains elusive. The greatest barrier has been absence of a comprehensive and accurate functional gene database. Here, we first developed a curated functional gene database (LCdb) for metagenomic profiling of lignin degrading microbial consortia. Via the LCdb, we draw a clear picture describing the global biogeography of communities with lignin-degrading potential. They exhibit clear niche differentiation at the levels of taxonomy and functional traits. The terrestrial microbiomes showed the highest diversity, yet the lowest correlations. In particular, there were few correlations between genes involved in aerobic and anaerobic degradation pathways, showing a clear functional redundancy property. In contrast, enhanced correlations, especially closer inter-connections between anaerobic and aerobic groups, were observed in aquatic consortia in response to the lower diversity. Specifically, dypB and dypA, are widespread on Earth, indicating their essential roles in lignin depolymerization. Estuarine and marine consortia featured the laccase and mnsod genes, respectively. Notably, the roles of archaea in lignin degradation were revealed in marine ecosystems. Environmental factors strongly influenced functional traits, but weakly shaped taxonomic groups. Null mode analysis further verified that composition of functional traits was deterministic, while taxonomic composition was highly stochastic, demonstrating that the environment selects functional genes rather than taxonomic groups. Our study not only develops a useful tool to study lignin degrading microbial communities via metagenome sequencing but also advances our understanding of ecological traits of these global microbiomes.

The origin of flight and laryngeal echolocation in bats is likely to have been accompanied by evolutionary changes in other aspects of their sensory biology. Of all sensory modalities in bats, olfaction is perhaps the least well understood. Olfactory receptors (ORs) function in recognizing odour molecules, with crucial roles in evaluating food, as well as in processing social information. Here we compare OR repertoire sizes across taxa and apply a new pipeline that integrates comparative genome data with protein structure modelling and then we employ molecular docking techniques with small molecules to analyse OR functionality based on binding energies. Our results suggest a sharp contraction in odorant recognition of the functional OR repertoire during the origin of bats, consistent with a reduced dependence on olfaction. We also compared bat lineages with contrasting different ecological characteristics and found evidence of differences in OR gene expansion and contraction, and in the composition of ORs with different tuning breadths. The strongest binding energies of ORs in non-echolocating fruit-eating bats were seen to correspond to ester odorants, although we did not detect a quantitative advantage of functional OR repertoires in these bats compared with echolocating insectivorous species. Overall, our findings based on molecular modelling and computational docking suggest that bats have undergone olfactory evolution linked to dietary adaptation. Our results from extant and ancestral bats help to lay the groundwork for targeted experimental functional tests in the future.

Mayflies (Ephemeroptera) are among the crucial water and habitat quality bioindicators. However, despite their intensive long-term use in various studies, more reliable mayfly DNA barcode data have been produced in a negligible number of countries, and only ~40% of European species had been barcoded with less than 50% of families covered. Despite being carried out in a small area, our study presents the second-most species-rich DNA reference library of mayflies from Europe and the first comprehensive view from an important biodiversity hotspot such as the Western Carpathians. Within 1153 sequences, 76 morphologically determined species were recorded and added to the Barcode of Life Data System (BOLD) database. All obtained sequences were assigned to 97 BINs, 11 of which were unique and three represented species never barcoded before. Sequences of 16 species with high intraspecific variability were divided into 40 BINs, confirming the presence of cryptic lineages. Due to the low interspecific divergence and the non-existing barcoding gap, sequences of six species were assigned to three shared BINs. Delimitation analyses resulted in 79 and 107 putative species respectively. Bayesian and maximum-likelihood phylogenies confirmed the monophyly of almost all species and complexes of cryptic taxa and proved that DNA barcoding distinguishes almost all studied mayfly species. We have shown that it is still sufficient to thoroughly investigate the fauna of a small but geographically important area to enrich global databases greatly. In particular, the insights gained here transcend the local context and may have broader implications for advancing barcoding efforts.

Diapause, a form of dormancy to delay or halt the reproductive development during unfavourable seasons, has evolved in many insect species. One example is aestivation, an adult-stage diapause enhancing malaria vectors' survival during the dry season (DS) and their re-establishment in the next rainy season (RS). This work develops a novel genetic approach to estimate the number or proportion of individuals undergoing diapause, as well as the breeding sizes of the two seasons, using signals from temporal allele frequency dynamics. Our modelling shows the magnitude of drift is dampened at early RS when previously aestivating individuals reappear. Aestivation severely biases the temporal effective population size ($��N_e�$), leading to overestimation of the DS breeding size by $��1�/�{\left(�1�-�\alpha �\right)}^2�$ across 1 year, where $��\alpha �$ is the aestivating proportion. We find sampling breeding individuals in three consecutive seasons starting from an RS is sufficient for parameter estimation, and perform extensive simulations to verify our derivations. This method does not require sampling individuals in the dormant state, the biggest challenge in most studies. We illustrate the method by applying it to a published data set for Anopheles coluzzii mosquitoes from Thierola, Mali. Our method and the expected evolutionary implications are applicable to any species in which a fraction of the population diapauses for more than one generation, and are difficult or impossible to sample during that stage.

The analyses of environmental DNA (eDNA) and environmental RNA (eRNA) released by organisms into their surrounding environment (water, soil and air) have emerged as powerful tools for monitoring biodiversity. While eDNA has been widely adopted for the non-invasive detection of species and characterization of community composition, the utilization of eRNA is still in its infancy. Due to its functional nature, eRNA holds intriguing potential for biodiversity monitoring offering new avenues of research beyond species detection. For example, conspecifics that are almost genetically identical can exhibit distinct transcriptomic differences depending on their life stage. In this issue of Molecular Ecology Resources, Parsley and Goldberg (2024) demonstrate, through a lab-validated field study, that eRNA can be used to detect distinct life stages of amphibians. This study elegantly demonstrates that eRNA can be used not only to detect invasive or endangered species but also to reveal population demographic information important for guiding effective conservation strategies.