Molecular Ecology Resources最新文献

Describing living community compositions is essential to monitor ecosystems in a rapidly changing world, but it is challenging to produce fast and accurate depiction of ecosystems due to methodological limitations. Morphological methods provide absolute abundances with limited throughput, whereas metabarcoding provides relative abundances of genes that may not correctly represent living communities from environmental DNA assessed with morphological methods. However, it has the potential to deliver fast descriptions of living communities provided that it is interpreted with validated species-specific calibrations and reference databases. Here, we developed a quantitative approach to retrieve from metabarcoding data the assemblages of living large benthic foraminifera (LBF), photosymbiotic calcifying protists, from Indonesian coral reefs that are under increasing anthropogenic pressure. To depict the diversity, we calculated taxon-specific correction factors to reduce biological biases by comparing surface area, biovolume and calcite volume, and the number of mitochondrial gene copies in seven common LBF species. To validate the approach, we compared calibrated datasets of morphological communities from mock samples with bulk reef sediment; both sample types were metabarcoded. The calibration of the data significantly improved the estimations of genus relative abundance, with a difference of ±5% on average, allowing for comparison of past morphological datasets with future molecular ones. Our results also highlight the application of our quantitative approach to support reef monitoring operations by capturing fine-scale processes, such as seasonal and pollution-driven dynamics, that require high-throughput sampling treatment.

Bioindication, evaluating biological responses to environmental disturbances, is crucial for assessing the ecological status of an ecosystem. While historical bioindication relied on macroscopic organisms, the introduction of environmental DNA (eDNA) techniques allows the application of protists without the necessity of morphological identification. In this study, we propose a novel bioindication methodology utilizing Arcellinida, a group of top predators among protists, as bioindicators of freshwater ecosystems. For that purpose, we first characterized the Arcellinida diversity over 1 year at three different points of Lake Sanabria, an ancient glacier lake known to be subjected to anthropogenic disturbances. We compared this diversity with an undisturbed control site. Second, we characterized the Arcellinida diversity in other ecosystems to generate the ecological background to test the connectivity between them. Results indicate limited connectivity between the different ecosystems and an edge effect between terrestrial and aquatic ecosystems. Disturbed freshwater ecosystems exhibited reduced Arcellinida diversity at both specific and infraspecific levels, providing valuable insight into recent disturbances. Arcellinida-based bioindication provides a sensitive, accurate and easy-to-interpret protocol for monitoring disturbances in freshwater ecosystems. It represents a valuable tool for environmental assessments and conservation strategies.

The use of short-read metabarcoding for classifying microeukaryotes is challenged by the lack of comprehensive 18S rRNA reference databases. While recent advances in high-throughput long-read sequencing provide the potential to greatly increase the phylogenetic coverage of these databases, the performance of different sequencing technologies and subsequent bioinformatics processing remain to be evaluated, primarily because of the absence of well-defined eukaryotic mock communities. To address this challenge, we created a eukaryotic rRNA operon clone-library and turned it into a precisely defined synthetic eukaryotic mock community. This mock community was then used to evaluate the performance of three long-read sequencing strategies (PacBio circular consensus sequencing and two Nanopore approaches using unique molecular identifiers) and three tools for resolving amplicons sequence variants (ASVs) (USEARCH, VSEARCH, and DADA2). We investigated the sensitivity of the sequencing techniques based on the number of detected mock taxa, and the accuracy of the different ASV-calling tools with a specific focus on the presence of chimera among the final rRNA operon ASVs. Based on our findings, we provide recommendations and best practice protocols for how to cost-effectively obtain essentially error-free rRNA operons in high-throughput. An agricultural soil sample was used to demonstrate that the sequencing and bioinformatic results from the mock community also translates to highly diverse natural samples, which enables us to identify previously undescribed microeukaryotic lineages.

With increasingly large genomic datasets, even routine bioinformatic tasks can be arduous, computationally demanding, and time-consuming. Additionally, most bioinformatic programs do not have a graphical user interface (GUI) and thus, require users to be minimally competent in command-line. These impediments present significant economic and technological barriers for practitioners who do not have access to advanced computational resources and support. In this issue of Molecular Ecology Resources, Handika and Esselstyn (2024) developed an ultrafast and memory-efficient bioinformatic tool, SEGUL, that performs common manipulations and calculations of summary statistics on phylogenomic datasets. SEGUL has two main features that distinguish it from other bioinformatic programs: (1) it is based on the recently emergent, high-performance programming language Rust, and (2) it has a GUI written using Flutter, a cross-platform programming framework that also supports mobile operating systems (mobile iOS, iPadOS and Android). By leveraging and combining the power of Rust and Flutter, SEGUL achieves significantly faster computation times and lower memory usage across different platforms and CPU architectures compared to similar programs. The unique and innovative features of SEGUL pave the way for a new era of bioinformatics that can be more energy-efficient, inclusive, and available to a broader swathe of users.

Current methodologies of genome-wide single-nucleotide polymorphism (SNP) genotyping produce large amounts of missing data that may affect statistical inference and bias the outcome of experiments. Genotype imputation is routinely used in well-studied species to buffer the impact in downstream analysis, and several algorithms are available to fill in missing genotypes. The lack of reference haplotype panels precludes the use of these methods in genomic studies on non-model organisms. As an alternative, machine learning algorithms are employed to explore the genotype data and to estimate the missing genotypes. Here, we propose an imputation method based on self-organizing maps (SOM), a widely used neural networks formed by spatially distributed neurons that cluster similar inputs into close neurons. The method explores genotype datasets to select SNP loci to build binary vectors from the genotypes, and initializes and trains neural networks for each query missing SNP genotype. The SOM-derived clustering is then used to impute the best genotype. To automate the imputation process, we have implemented gtImputation, an open-source application programmed in Python3 and with a user-friendly GUI to facilitate the whole process. The method performance was validated by comparing its accuracy, precision and sensitivity on several benchmark genotype datasets with other available imputation algorithms. Our approach produced highly accurate and precise genotype imputations even for SNPs with alleles at low frequency and outperformed other algorithms, especially for datasets from mixed populations with unrelated individuals.

The utility of a universal DNA ‘barcode’ fragment (658 base pairs of the Cytochrome C Oxidase I [COI] gene) has been established as a useful tool for species identification, and widely criticized as one for understanding the evolutionary history of a group. Large amounts of COI sequence data have been produced that hold promise for rapid species identification, for example, for biosecurity. The fruit fly tribe Dacini holds about a thousand species, of which 80 are pests of economic concern. We generated a COI reference library for 265 species of Dacini containing 5601 sequences that span most of the COI gene using circular consensus sequencing. We compared distance metrics versus monophyly assessments for species identification and although we found a ‘soft’ barcode gap around 2% pairwise distance, the exceptions to this rule dictate that a monophyly assessment is the only reliable method for species identification. We found that all fragments regularly used for Dacini fruit fly identification >450 base pairs long provide similar resolution. 11.3% of the species in our dataset were non-monophyletic in a COI tree, which is mostly due to species complexes. We conclude with recommendations for the future generation and use of COI libraries. We revise the generic assignment of Dacus transversus stat. rev. Hardy 1982, and Dacus perpusillus stat. rev. Drew 1971 and we establish Dacus maculipterus White 1998 syn. nov. as a junior synonym of Dacus satanas Liang et al. 1993.

Research on supergenes, non-recombining genomic regions housing tightly linked genes that control complex phenotypes, has recently gained prominence in genomics. Heterostyly, a floral heteromorphism promoting outcrossing in several angiosperm families, is controlled by the S-locus supergene. The S-locus has been studied primarily in closely related Primula species and, more recently, in other groups that independently evolved heterostyly. However, it remains unknown whether genetic architecture and composition of the S-locus are maintained among species that share a common origin of heterostyly and subsequently diverged across larger time scales. To address this research gap, we present a chromosome-scale genome assembly of Primula edelbergii, a species that shares the same origin of heterostyly with Primula veris (whose S-locus has been characterized) but diverged from it 18 million years ago. Comparative genomic analyses between these two species allowed us to show, for the first time, that the S-locus can ‘jump’ (i.e. translocate) between chromosomes maintaining its function in controlling heterostyly. Additionally, we found that four S-locus genes were conserved but reshuffled within the supergene, seemingly without affecting their expression, thus we could not detect changes explaining the lack of self-incompatibility in P. edelbergii. Furthermore, we confirmed that the S-locus is not undergoing genetic degeneration. Finally, we investigated P. edelbergii evolutionary history within Ericales in terms of whole genome duplications and transposable element accumulation. In summary, our work provides a valuable resource for comparative analyses aimed at investigating the genetics of heterostyly and the pivotal role of supergenes in shaping the evolution of complex phenotypes.

Abyssal (3501–6500 m) and hadal (>6500 m) fauna evolve under harsh abiotic stresses, characterized by high hydrostatic pressure, darkness and food shortage, providing unique opportunities to investigate mechanisms underlying environmental adaptation. Genomes of several hadal species have recently been reported. However, the genetic adaptation of deep sea species across a broad spectrum of ocean depths has yet to be thoroughly investigated, due to the challenges imposed by collecting the deep sea species. To elucidate the correlation between genetic innovation and vertical distribution, we generated a chromosome-level genome assembly of the macrourids Coryphaenoides yaquinae, which is widely distributed in the abyssal/hadal zone ranging from 3655 to 7259 m in depth. Genomic comparisons among shallow, abyssal and hadal-living species identified idiosyncratic and convergent genetic alterations underlying the extraordinary adaptations of deep-sea species including light perception, circadian regulation, hydrostatic pressure and hunger tolerance. The deep-sea fishes (Coryphaenoides Sp. and Pseudoliparis swirei) venturing into various ocean depths independently have undergone convergent amino acid substitutions in multiple proteins such as rhodopsin 1, pancreatic and duodenal homeobox 1 and melanocortin 4 receptor which are known or verified in zebrafish to be related with vision adaptation and energy expenditure. Convergent evolution events were also identified in heat shock protein 90 beta family member 1 and valosin-containing protein genes known to be related to hydrostatic pressure adaptation specifically in fishes found around the hadal range. The uncovering of the molecular convergence among the deep-sea species shed new light on the common genetic innovations required for deep-sea adaptation by the fishes.

Landscape genetics is a field dealing with local genetic differences and contributes to strategic conservation planning. Recently, environmental DNA (eDNA) metabarcoding has proven useful not only for detecting species but also for assessing genetic diversity and genetic structure on a large scale such as in phylogeography. However, it remains unclear whether eDNA analysis also has sufficient power to perform the landscape genetics, which focuses on a local scale. To reveal the applicability of eDNA to landscape genetics, we conducted an eDNA metabarcoding analysis of the mitochondrial DNA D-loop region of the fluvial sculpin Cottus nozawae in the upper Sorachi River in Japan and compared the results with inferences based on traditional tissue-based approaches by the same D-loop region and genome-wide SNP data. As a result, the spatial distribution of haplotypes was generally consistent between the eDNA- and tissue-based approaches. In addition, the genetic differentiation statistics calculated using eDNA and tissue samples were highly correlated when comparing both in the D-loop region. The removal of low-frequency reads or the conversion to semi-quantitative rankings of eDNA data did not alter the correlation of genetic diversity and differentiation statistics with tissue-based approaches much. Finally, we confirmed that analyses using eDNA data can reveal patterns such as isolation-by-distance shown in previous studies on this species, indicating the applicability of eDNA to basic landscape genetics. Even though some limitations remain, eDNA may have great potential for conducting basic landscape genetics.

Terrestrial orchids are a group of genetically understudied, yet culturally and economically important plants. The Orchidinae tribe contains many species that produce edible tubers that are used for the production of traditional delicacies collectively called ‘salep’. Overexploitation of wild orchids in the Eastern Mediterranean and Western Asia threatens to drive many of these species to extinction, but cost-effective tools for monitoring their trade are currently lacking. Here we present a custom bait kit for target enrichment and sequencing of 205 novel genetic markers that are tailored to phylogenomic applications in Orchidinae s.l. A subset of 31 markers capture genes putatively involved in the production of glucomannan, a water-soluble polysaccharide that gives salep its distinctive properties. We tested the kit on 73 taxa native to the area, demonstrating universally high locus recovery irrespective of species identity, that exceeds the total sequence length obtained with alternative kits currently available. Phylogenetic inference with concatenation and coalescent approaches was robust and showed high levels of support for most clades, including some which were previously unresolved. Resolution for hybridizing and recently radiated lineages remains difficult, but could be further improved by analysing multiple haplotypes and the non-exonic sequences captured by our kit, with the promise to shed new light on the evolution of enigmatic taxa with a complex speciation history. Offering a step-up from traditional barcoding and universal markers, the genome-wide custom loci targeted by Orchidinae-205 are a valuable new resource to study the evolution, systematics and trade of terrestrial orchids.