The landscape of analytical tools for population genomics continues to evolve. However, these tools are scattered across programming languages, making them largely inaccessible for many biologists. In this issue of Molecular Ecology Resources, Hemstrom and Jones, 2022 (Mol Ecol Resour; 962) introduce a new R package, snpR. This package combines a large number of existing analyses, to provide a one-stop shop for population genomics. F-statistics, admixture analyses, effective population size inferences, genome-wide association studies (GWAS), and parentage analyses are all implemented natively within the package. A variety of third-party software can also be run without leaving the R environment. The authors pay particular attention to data structure - avoiding redundancy - and allowing analyses to be run across multiple sample or single-nucleotide polymorphism (SNP) groupings. Because of its great accessibility and wide range of analyses, snpR has the potential to become a favourite within the Molecular Ecology community.

Next-generation sequencing of pooled samples (Pool-seq) is a popular method to assess genome-wide diversity patterns in natural and experimental populations. However, Pool-seq is associated with specific sources of noise, such as unequal individual contributions. Consequently, using Pool-seq for the reconstruction of evolutionary history has remained underexplored. Here we describe a novel Approximate Bayesian Computation (ABC) method to infer demographic history, explicitly modelling Pool-seq sources of error. By jointly modelling Pool-seq data, demographic history and the effects of selection due to barrier loci, we obtain estimates of demographic history parameters accounting for technical errors associated with Pool-seq. Our ABC approach is computationally efficient as it relies on simulating subsets of loci (rather than the whole-genome) and on using relative summary statistics and relative model parameters. Our simulation study results indicate Pool-seq data allows distinction between general scenarios of ecotype formation (single versus parallel origin) and to infer relevant demographic parameters (e.g. effective sizes and split times). We exemplify the application of our method to Pool-seq data from the rocky-shore gastropod Littorina saxatilis, sampled on a narrow geographical scale at two Swedish locations where two ecotypes (Wave and Crab) are found. Our model choice and parameter estimates show that ecotypes formed before colonization of the two locations (i.e. single origin) and are maintained despite gene flow. These results indicate that demographic modelling and inference can be successful based on pool-sequencing using ABC, contributing to the development of suitable null models that allow for a better understanding of the genetic basis of divergent adaptation.

Although plastid genome (plastome) structure is highly conserved across most seed plants, investigations during the past two decades have revealed several disparately related lineages that experienced substantial rearrangements. Most plastomes contain a large inverted repeat and two single-copy regions, and a few dispersed repeats; however, the plastomes of some taxa harbour long repeat sequences (>300 bp). These long repeats make it challenging to assemble complete plastomes using short-read data, leading to misassemblies and consensus sequences with spurious rearrangements. Single-molecule, long-read sequencing has the potential to overcome these challenges, yet there is no consensus on the most effective method for accurately assembling plastomes using long-read data. We generated a pipeline, plastid Genome Assembly Using Long-read data (ptGAUL), to address the problem of plastome assembly using long-read data from Oxford Nanopore Technologies (ONT) or Pacific Biosciences platforms. We demonstrated the efficacy of the ptGAUL pipeline using 16 published long-read data sets. We showed that ptGAUL quickly produces accurate and unbiased assemblies using only ~50× coverage of plastome data. Additionally, we deployed ptGAUL to assemble four new Juncus (Juncaceae) plastomes using ONT long reads. Our results revealed many long repeats and rearrangements in Juncus plastomes compared with basal lineages of Poales. The ptGAUL pipeline is available on GitHub: https://github.com/Bean061/ptgaul.

Epigenetic approaches for estimating the age of living organisms are revolutionizing studies of long-lived species. Molecular biomarkers that allow age estimates from small tissue biopsies promise to enhance studies of long-lived whales, addressing a fundamental and challenging parameter in wildlife management. DNA methylation (DNAm) can affect gene expression, and strong correlations between DNAm patterns and age have been documented in humans and nonhuman vertebrates and used to construct "epigenetic clocks". We present several epigenetic clocks for skin samples from two of the longest-lived cetaceans, killer whales and bowhead whales. Applying the mammalian methylation array to genomic DNA from skin samples we validate four different clocks with median errors of 2.3-3.7 years. These epigenetic clocks demonstrate the validity of using cytosine methylation data to estimate the age of long-lived cetaceans and have broad applications supporting the conservation and management of long-lived cetaceans using genomic DNA from remote tissue biopsies.

Target-capture approaches have facilitated a rapid growth in the field of phylogenomics but few probe sets exist for molluscs, an exceptionally rich phylum with unparalleled ecological and morphological diversity. We designed and tested the first universal probe set using Phyluce to capture ultraconserved elements (UCEs) and exon loci from the Subclass Caenogastropoda - one of six major lineages of gastropods. The probe set consists of 29,441 probes designed to target 1142 UCE loci and 1933 exon loci (3075 total). In silico analyses of our probe set yielded an average of 2110 loci from genomes and 1389 loci from transcriptomes of diverse caenogastropods, from which an average of 1669 and 849 loci were retained respectively after screening to remove those that matched multiple contigs. Phylogenetic analyses of the loci extracted from transcriptomes produced well-supported trees very similar to those published based on transcriptomic analyses. Phylogenetic relationships estimated from loci extracted from genomes recover similar phylogenetic relationships, and indicate that the loci targeted with this probe set are informative for resolving deep phylogenetic relationships. An in vitro analysis of the probe set with the Epitoniidae, a diverse caenogastropod family of uncertain affinity and with poorly resolved evolutionary relationships, recovered a total of 2850 loci. Although preliminary, the analysis of loci captured by our probe set for a small number of epitoniid taxa produced a well-resolved tree indicating that this probe set is also able to resolve relationships at shallower hierarchical scales. Together, the in silico and in vitro analyses indicate that target-capture enrichment with this probe set is a useful tool for reconstructing phylogenetic relationships across taxonomic levels and evolutionary time scales.

At the genome level, microorganisms are highly adaptable both in terms of allele and gene composition. Such heritable traits emerge in response to different environmental niches and can have a profound influence on microbial community dynamics. As a consequence, any individual genome or population will contain merely a fraction of the total genetic diversity of any operationally defined "species", whose ecological potential can thus be only fully understood by studying all of their genomes and the genes therein. This concept, known as the pangenome, is valuable for studying microbial ecology and evolution, as it partitions genomes into core (present in all the genomes from a species, and responsible for housekeeping and species-level niche adaptation among others) and accessory regions (present only in some, and responsible for intra-species differentiation). Here we present SuperPang, an algorithm producing pangenome assemblies from a set of input genomes of varying quality, including metagenome-assembled genomes (MAGs). SuperPang runs in linear time and its results are complete, non-redundant, preserve gene ordering and contain both coding and non-coding regions. Our approach provides a modular view of the pangenome, identifying operons and genomic islands, and allowing to track their prevalence in different populations. We illustrate this by analysing intra-species diversity in Polynucleobacter, a bacterial genus ubiquitous in freshwater ecosystems, characterized by their streamlined genomes and their ecological versatility. We show how SuperPang facilitates the simultaneous analysis of allelic and gene content variation under different environmental pressures, allowing us to study the drivers of microbial diversification at unprecedented resolution.

Ciliates are a large group of ubiquitous and highly diverse single-celled eukaryotes that play an essential role in the functioning of microbial food webs. However, their genomic diversity is far from clear due to the need to develop cultivation methods for most species, so most research is based on wild organisms that almost invariably contain contaminants. Here we establish an integrated Genome Decontamination Pipeline (iGDP) that combines homology search, telomere reads-assisted and clustering approaches to filter contaminated ciliate genome assemblies from wild specimens. We benchmarked the performance of iGDP using genomic data from a contaminated ciliate culture and the results showed that iGDP could recall 91.9% of the target sequences with 96.9% precision. We also used a synthetic dataset to offer guidelines for the application of iGDP in the removal of various groups of contaminants. Compared with several popular metagenome binning tools, iGDP could show better performance. To further validate the effectiveness of iGDP on real-world data, we applied it to decontaminate genome assemblies of three wild ciliate specimens and obtained their genomes with high quality comparable to that of previously well-studied model ciliate genomes. It is anticipated that the newly generated genomes and the established iGDP method will be valuable community resources for detailed studies on ciliate biodiversity, phylogeny, ecology and evolution. The pipeline (https://github.com/GWang2022/iGDP) can be implemented automatically to reduce manual filtering and classification and may be further developed to apply to other microeukaryotes.

A large part of the soil protist diversity is missed in metabarcoding studies based on 0.25 g of soil environmental DNA (eDNA) and universal primers due to ca. 80% co-amplification of non-target plants, animals and fungi. To overcome this problem, enrichment of the substrate used for eDNA extraction is an easily implemented option but its effect has not yet been tested. In this study, we evaluated the effect of a 150 μm mesh size filtration and sedimentation method to improve the recovery of protist eDNA, while reducing the co-extraction of plant, animal and fungal eDNA, using a set of contrasted forest and alpine soils from La Réunion, Japan, Spain and Switzerland. Total eukaryotic diversity was estimated by V4 18S rRNA metabarcoding and classical amplicon sequence variant calling. A 2- to 3-fold enrichment in shelled protists (Euglyphida, Arcellinida and Chrysophyceae) was observed at the sample level with the proposed method, with, at the same time, a 2-fold depletion of Fungi and a 3-fold depletion of Embryophyceae. Protist alpha diversity was slightly lower in filtered samples due to reduced coverage in Variosea and Sarcomonadea, but significant differences were observed in only one region. Beta diversity varied mostly between regions and habitats, which explained the same proportion of variance in bulk soil and filtered samples. The increased resolution in soil protist diversity estimates provided by the filtration-sedimentation method is a strong argument in favour of including it in the standard protocol for soil protist eDNA metabarcoding studies.

Many recent studies have provided significant insights into polyploid breeding, but limited research has been carried out on trees. The genomic information needed to understand growth and response to abiotic stress in polyploidy trees is largely unknown, but has become critical due to the threats to forests imposed by climate change. Populus alba 'Berolinensis,' also known "Yinzhong poplar," is a triploid poplar from northeast China. This hybrid triploid poplar is widely used as a landscape ornamental and in urban forestry owing to its adaptation to adverse environments and faster growth than its parental diploid. It is an artificially synthesized male allotriploid hybrid, with three haploid genomes of P. alba 'Berolinensis' originating from different poplar species, so it is attractive for studying polyploidy genomic mechanisms in heterosis. In this study, we focused on the allelic genomic interactions in P. alba 'Berolinensis,' and generated a high-quality chromosome-level genome assembly consisting of 19 allelic chromosomes. Its three haploid chromosome sets are polymorphic with an average of 25.73 nucleotide polymorphism sites per kilobase. We found that some stress-related genes such as RD22 and LEA7 exhibited sequence differences between different haploid genomes. The genome assembly has been deposited in our polyploid genome online analysis website TreeGenomes (https://www.treegenomes.com). These polyploid genome-related resources will provide a critical foundation for the molecular breeding of P. alba 'Berolinensis' and help us uncover the allopolyploidization effects of heterosis and abiotic stress resistance and traits of polyploidy species in the future.

Soil protists are increasingly studied due to a release from previous methodological constraints and the acknowledgement of their immense diversity and functional importance in ecosystems. However, these studies often lack sufficient depth in knowledge, which is visible in the form of falsely used terms and false- or over-interpreted data with conclusions that cannot be drawn from the data obtained. As we welcome that also non-experts include protists in their still mostly bacterial and/or fungal-focused studies, our aim here is to help avoid some common errors. We provide suggestions for current terms to use when working on soil protists, like protist instead of protozoa, predator instead of grazer, microorganisms rather than microflora and other terms to be used to describe the prey spectrum of protists. We then highlight some dos and don'ts in soil protist ecology including challenges related to interpreting 18S rRNA gene amplicon sequencing data. We caution against the use of standard bioinformatic settings optimized for bacteria and the uncritical reliance on incomplete and partly erroneous reference databases. We also show why causal inferences cannot be drawn from sequence-based correlation analyses or any sampling/monitoring, study in the field without thorough experimental confirmation and sound understanding of the biology of taxa. Together, we envision this work to help non-experts to more easily include protists in their soil ecology analyses and obtain more reliable interpretations from their protist data and other biodiversity data that, in the end, will contribute to a better understanding of soil ecology.

The genome of recently admixed individuals or hybrids has characteristic genetic patterns that can be used to learn about their recent admixture history. One of these are patterns of interancestry heterozygosity, which can be inferred from SNP data from either called genotypes or genotype likelihoods, without the need for information on genomic location. This makes them applicable to a wide range of data that are often used in evolutionary and conservation genomic studies, such as low-depth sequencing mapped to scaffolds and reduced representation sequencing. Here we implement maximum likelihood estimation of interancestry heterozygosity patterns using two complementary models. We furthermore develop apoh (Admixture Pedigrees of Hybrids), a software that uses estimates of paired ancestry proportions to detect recently admixed individuals or hybrids, and to suggest possible admixture pedigrees. It furthermore calculates several hybrid indices that make it easier to identify and rank possible admixture pedigrees that could give rise to the estimated patterns. We implemented apoh both as a command line tool and as a Graphical User Interface that allows the user to automatically and interactively explore, rank and visualize compatible recent admixture pedigrees, and calculate the different summary indices. We validate the performance of the method using admixed family trios from the 1000 Genomes Project. In addition, we show its applicability on identifying recent hybrids from RAD-seq data of Grant's gazelle (Nanger granti and Nanger petersii) and whole genome low-depth data of waterbuck (Kobus ellipsiprymnus) which shows complex admixture of up to four populations.

DNA barcoding has greatly facilitated studies of taxonomy, biodiversity, biological conservation, and ecology. Here, we establish a reliable DNA barcoding library for Chinese snakes, unveiling hidden diversity with implications for taxonomy, and provide a standardized tool for conservation management. Our comprehensive study includes 1638 cytochrome c oxidase subunit I (COI) sequences from Chinese snakes that correspond to 17 families, 65 genera, 228 named species (80.6% of named species) and 36 candidate species. A barcode gap analysis reveals gaps, where all nearest neighbour distances exceed maximum intraspecific distances, in 217 named species and all candidate species. Three species-delimitation methods (ABGD, sGMYC, and sPTP) recover 320 operational taxonomic units (OTUs), of which 192 OTUs correspond to named and candidate species. Twenty-eight other named species share OTUs, such as Azemiops feae and A. kharini, Gloydius halys, G. shedaoensis, and G. intermedius, and Bungarus multicinctus and B. candidus, representing inconsistencies most probably caused by imperfect taxonomy, recent and rapid speciation, weak taxonomic signal, introgressive hybridization, and/or inadequate phylogenetic signal. In contrast, 43 species and candidate species assign to two or more OTUs due to having large intraspecific distances. If most OTUs detected in this study reflect valid species, including the 36 candidate species, then 30% more species would exist than are currently recognized. Several OTU divergences associate with known biogeographic barriers, such as the Taiwan Strait. In addition to facilitating future studies, this reliable and relatively comprehensive reference database will play an important role in the future monitoring, conservation, and management of Chinese snakes.

Age is an essential trait for understanding the ecology and management of wildlife. A conventional method of estimating age in wild animals is counting annuli formed in the cementum of teeth. This method has been used in bears despite some disadvantages, such as high invasiveness and the requirement for experienced observers. In this study, we established a novel age estimation method based on DNA methylation levels using blood collected from 49 brown bears of known ages living in both captivity and the wild. We performed bisulfite pyrosequencing and obtained methylation levels at 39 cytosine-phosphate-guanine (CpG) sites adjacent to 12 genes. The methylation levels of CpGs adjacent to four genes showed a significant correlation with age. The best model was based on DNA methylation levels at just four CpG sites adjacent to a single gene, SLC12A5, and it had high accuracy with a mean absolute error of 1.3 years and median absolute error of 1.0 year after leave-one-out cross-validation. This model represents the first epigenetic method of age estimation in brown bears, which provides benefits over tooth-based methods, including high accuracy, less invasiveness, and a simple procedure. Our model has the potential for application to other bear species, which will greatly improve ecological research, conservation, and management.

Genome sequencing enables answering fundamental questions about the genetic basis of adaptation, population structure and epigenetic mechanisms. Yet, we usually need a suitable reference genome for mapping population-level resequencing data. In some model systems, multiple reference genomes are available, giving the challenging task of determining which reference genome best suits the data. Here, we compared the use of two different reference genomes for the three-spined stickleback (Gasterosteus aculeatus), one novel genome derived from a European gynogenetic individual and the published reference genome of a North American individual. Specifically, we investigated the impact of using a local reference versus one generated from a distinct lineage on several common population genomics analyses. Through mapping genome resequencing data of 60 sticklebacks from across Europe and North America, we demonstrate that genetic distance among samples and the reference genomes impacts downstream analyses. Using a local reference genome increased mapping efficiency and genotyping accuracy, effectively retaining more and better data. Despite comparable distributions of the metrics generated across the genome using SNP data (i.e. π, Tajima's D and FST ), window-based statistics using different references resulted in different outlier genes and enriched gene functions. A marker-based analysis of DNA methylation distributions had a comparably high overlap in outlier genes and functions, yet with distinct differences depending on the reference genome. Overall, our results highlight how using a local reference genome decreases reference bias to increase confidence in downstream analyses of the data. Such results have significant implications in all reference-genome-based population genomic analyses.

Gaining meaningful insights into bacterial communities associated with animal hosts requires the provision of high-quality nucleic acids. Although many studies have compared DNA extraction methods for samples with low bacterial biomass (e.g. water) or specific PCR inhibitors (e.g. plants), DNA extraction bias in samples without inherent technical constraint (e.g. animal samples) has received little attention. Furthermore, there is an urgent need to identify a DNA extraction methods in a high-throughput format that decreases the cost and time for processing large numbers of samples. We here evaluated five DNA extraction protocols, using silica membrane-based spin columns and a 96-well microplate format and based on either mechanical or enzymatic lysis or a combination of both, using three bacterial mock communities and Illumina sequencing of the V4 region of the 16SrRNA gene. Our results showed that none of the DNA extraction methods fully eliminated bias associated with unequal lysis efficiencies. However, we identified a DNA extraction method with a lower bias for each mock community standard. Of these methods, those including an enzymatic lysis showed biases specific to some bacteria. Altogether, these results again demonstrate the importance of DNA extraction standardization to be able to compare the microbiome results of different samples. In this attempt, we advise for the use of the 96-well DNeasy Blood and Tissue kit (Qiagen) with a zirconia bead-beating procedure, which optimizes altogether the cost, handling time and bacteria-specific effects associated with enzymatic lysis.

In connectivity models, land cover types are assigned cost values characterizing their resistance to species movements. Landscape genetic methods infer these values from the relationship between genetic differentiation and cost distances. The spatial heterogeneity of population sizes, and consequently genetic drift, is rarely included in this inference although it influences genetic differentiation. Similarly, migration rates and population spatial distributions potentially influence this inference. Here, we assessed the reliability of cost value inference under several migration rates, population spatial patterns and degrees of population size heterogeneity. Additionally, we assessed whether considering intra-population variables, here using gravity models, improved the inference when drift is spatially heterogeneous. We simulated several gene flow intensities between populations with varying local sizes and spatial distributions. We then fit gravity models of genetic distances as a function of (i) the 'true' cost distances driving simulations or alternative cost distances, and (ii) intra-population variables (population sizes, patch areas). We determined the conditions making the identification of the 'true' costs possible and assessed the contribution of intra-population variables to this objective. Overall, the inference ranked cost scenarios reliably in terms of similarity with the 'true' scenario (cost distance Mantel correlations), but this 'true' scenario rarely provided the best model goodness of fit. Ranking inaccuracies and failures to identify the 'true' scenario were more pronounced when migration was very restricted (<4 dispersal events/generation), population sizes were most heterogeneous and some populations were spatially aggregated. In these situations, considering intra-population variables helps identify cost scenarios reliably, thereby improving cost value inference from genetic data.

Stygofauna are aquatic fauna that have evolved to live underground. The impacts of anthropogenic climate change, extraction and pollution on groundwater pose major threats to groundwater health, prompting the need for efficient and reliable means to detect and monitor stygofaunal communities. Conventional survey techniques for these species rely on morphological identification and can be biased, labour-intensive and often indeterminate to lower taxonomic levels. By contrast, environmental DNA (eDNA)-based methods have the potential to dramatically improve on existing stygofaunal survey methods in a large range of habitats and for all life stages, reducing the need for the destructive manual collection of often critically endangered species or for specialized taxonomic expertise. We compared eDNA and haul-net samples collected in 2020 and 2021 from 19 groundwater bores and a cave on Barrow Island, northwest Western Australia, and assessed how sampling factors influenced the quality of eDNA detection of stygofauna. The two detection methods were complementary; eDNA metabarcoding was able to detect soft-bodied taxa and fish often missed by nets, but only detected seven of the nine stygofaunal crustacean orders identified from haul-net specimens. Our results also indicated that eDNA metabarcoding could detect 54%-100% of stygofauna from shallow-water samples and 82%-90% from sediment samples. However, there was significant variation in stygofaunal diversity between sample years and sampling types. The findings of this study demonstrate that haul-net sampling has a tendency to underestimate stygofaunal diversity and that eDNA metabarcoding of groundwater can substantially improve the efficiency of stygofaunal surveys.

Cetaceans (dolphins, whales, and porpoises) have large and anatomically sophisticated brains. To expand our understanding of the cellular makeup of cetacean brains and the similarities and divergence between the brains of cetaceans and terrestrial mammals, we report a short-finned pilot whale (Globicephala macrorhynchus) single-nucleus transcriptome atlas. To achieve this goal, we assembled a chromosome-scale reference genome spanning 2.25 Gb on 22 chromosomes and profiled the gene expression of five major anatomical cortical regions of the short-finned pilot whale by single-nucleus RNA-sequencing (snRNA-seq). We identified six major cell lineages in the cerebral cortex (excitatory neurons, inhibitory neurons, oligodendrocytes, oligodendrocyte precursor cells, astrocytes, and endothelial cells), eight molecularly distinct subclusters of excitatory neurons, and four subclusters of inhibitory neurons. Finally, a comparison of snRNA-seq data from the short-finned pilot whale, human, and rhesus macaque revealed a broadly conserved cellular makeup of brain cell types. Our study provides genomic resources and molecular insights into cetacean brain evolution.

Library preparation protocols for most sequencing technologies involve PCR amplification of the template DNA, which open the possibility that a given template DNA molecule is sequenced multiple times. Reads arising from this phenomenon, known as PCR duplicates, inflate the cost of sequencing and can jeopardize the reliability of affected experiments. Despite the pervasiveness of this artefact, our understanding of its causes and of its impact on downstream statistical analyses remains essentially empirical. Here, we develop a general quantitative model of amplification distortions in sequencing data sets, which we leverage to investigate the factors controlling the occurrence of PCR duplicates. We show that the PCR duplicate rate is determined primarily by the ratio between library complexity and sequencing depth, and that amplification noise (including in its dependence on the number of PCR cycles) only plays a secondary role for this artefact. We confirm our predictions using new and published RAD-seq libraries and provide a method to estimate library complexity and amplification noise in any data set containing PCR duplicates. We discuss how amplification-related artefacts impact downstream analyses, and in particular genotyping accuracy. The proposed framework unites the numerous observations made on PCR duplicates and will be useful to experimenters of all sequencing technologies where DNA availability is a concern.

The availability of a large number of high-density markers (SNPs) allows the estimation of historical effective population size (Ne ) from linkage disequilibrium between loci. A recent refinement of methods to estimate historical Ne from the recent past has been shown to be rather accurate with simulation data. The method has also been applied to real data for numerous species. However, the simulation data cannot encompass all the complexities of real genomes, and the performance of any estimation method with real data is always uncertain, as the true demography of the populations is not known. Here, we carried out an experimental design with Drosophila melanogaster to test the method with real data following a known demographic history. We used a population maintained in the laboratory with a constant census size of about 2800 individuals and subjected the population to a drastic decline to a size of 100 individuals. After a few generations, the population was expanded back to the previous size and after a few further generations again expanded to twice the initial size. Estimates of historical Ne were obtained with the software GONE both for autosomal and X chromosomes from samples of 17 individuals sequenced for the whole genome. Estimates of the historical effective size were able to infer the patterns of changes that occurred in the populations showing generally good performance of the method. We discuss the limitations of the method and the application of the software carried out so far.

Some of the most vexing problems of deep level relationship that remain in angiosperms involve the superrosids. The superrosid clade contains a quarter of all angiosperm species, with 18 orders in three subclades (Vitales, Saxifragales and core rosids) exhibiting remarkable morphological and ecological diversity. To help resolve deep-level relationships, we constructed a high-quality chromosome-level genome assembly for Tiarella polyphylla (Saxifragaceae) thus providing broader genomic representation of Saxifragales. Whole genome microsynteny analysis of superrosids showed that Saxifragales shared more synteny clusters with core rosids than Vitales, further supporting Saxifragales as more closely related with core rosids. To resolve the ordinal phylogeny of superrosids, we screened 122 single copy nuclear genes from genomes of 36 species, representing all 18 superrosid orders. Vitales were recovered as sister to all other superrosids (Saxifragales + core rosids). Our data suggest dramatic differences in relationships compared to earlier studies within core rosids. Fabids should be restricted to the nitrogen-fixing clade, while Picramniales, the Celastrales-Malpighiales (CM) clade, Huerteales, Oxalidales, Sapindales, Malvales and Brassicales formed an "expanded" malvid clade. The Celastrales-Oxalidales-Malpighiales (COM) clade (sensu APG IV) was not monophyletic. Crossosomatales, Geraniales, Myrtales and Zygophyllales did not belong to either of our well-supported malvids or fabids. There is strong discordance between nuclear and plastid phylogenetic hypotheses for superrosid relationships; we show that this is best explained by a combination of incomplete lineage sorting and ancient reticulation.

Understanding the genetic variations of the horse (Equus caballus) genome will improve breeding conservation and welfare. However, genetic variations in long segments, such as structural variants (SVs), remain understudied. We de novo assembled 10 chromosome-level three-dimensional horse genomes, each representing a distinct breed, and analysed horse SVs using a multi-assembly approach. Our findings suggest that SVs with the accumulation of mammalian-wide interspersed repeats related to long interspersed nuclear elements might be a horse-specific mechanism to modulate genome-wide gene regulatory networks. We found that olfactory receptors were commonly loss and accumulated deleterious mutations, but no purge of deleterious mutations occurred during horse domestication. We examined the potential effects of SVs on the spatial structure of chromatin via topologically associating domains (TADs). Breed-specific TADs were significantly enriched by breed-specific SVs. We identified 4199 unique breakpoint-resolved novel insertions across all chromosomes that account for 2.84 Mb sequences missing from the reference genome. Several novel insertions might have potential functional consequences, as 519 appeared to reside within 449 gene bodies. These genes are primarily involved in pathogen recognition, innate immune responses and drug metabolism. Moreover, 37 diverse horses were resequenced. Combining this with public data, we analysed 97 horses through a comparative population genomics approach to identify the genetic basis underlying breed characteristics using Thoroughbreds as a case study. We provide new scientific evidence for horse domestication, an understanding of the genetic mechanism underlying the phenotypic evolution of horses, and a comprehensive genetic variation resource for further genetic studies of horses.

The delivery of consistent and accurate fine-resolution data on biodiversity using metabarcoding promises to improve environmental assessment and research. Whilst this approach is a substantial improvement upon traditional techniques, critics note that metabarcoding data are suitable for establishing taxon occurrence, but not abundance. We propose a novel hierarchical approach to recovering abundance information from metabarcoding, and demonstrate this technique using benthic macroinvertebrates. To sample a range of abundance structures without introducing additional changes in composition, we combined seasonal surveys with fish-exclusion experiments at Catamaran Brook in northern New Brunswick, Canada. Five monthly surveys collected 31 benthic samples for DNA metabarcoding divided between caged and control treatments. A further six samples per survey were processed using traditional morphological identification for comparison. By estimating the probability of detecting a single individual, multispecies abundance models infer changes in abundance based on changes in detection frequency. Using replicate detections of 184 genera (and 318 species) from metabarcoding samples, our analysis identified changes in abundance arising from both seasonal dynamics and the exclusion of fish predators. Counts obtained from morphological samples were highly variable, a feature that limited the opportunity for more robust comparison, and emphasizing the difficulty standard methods also face to detect changes in abundance. Our approach is the first to demonstrate how quantitative estimates of abundance can be made using metabarcoding, both among species within sites as well as within species among sites. Many samples are required to capture true abundance patterns, particularly in streams where counts are highly variable, but few studies can afford to process entire samples. Our approach allows study of responses across whole communities, and at fine taxonomic resolution. We discuss how ecological studies can use additional sampling to capture changes in abundance at fine resolution, and how this can complement broad-scale biomonitoring using DNA metabarcoding.

As whole-genome sequencing has become pervasive, some have suggested that reduced genomic representation approaches, for example, sequence capture, are becoming obsolete. In the present study, we argue that these techniques still provide excellent tools in terms of price and quality of data as well as in their ability to provide markers with specific features, as required, for example, in phylogenomics. A potential drawback of the wide-scale application of reduced representation approaches could be their drop in efficiency with increasing phylogenetic distance from the reference species. While some studies have focused on the degree and performance of reduced representation techniques in such situations, to our knowledge, none of them evaluated their applicability to inter-specific hybrids and polyploids. This highlights a significant gap in current knowledge since there is increasing evidence for the frequent occurrence of natural hybrids and polyploids, as well as for the major importance of both phenomena in evolution. The main aim of the present study was to carry out a thorough validation of SEQcap applicability to (1) a set of non-model taxa with a wide range of phylogenetic relatedness and (2) inter-specific hybrids of various ploidies and genomic compositions. Considering the latter point, we especially focused on mechanisms causing allelic bias and consequent allelic dropout, as these could have confounding effects with respect to the evolutionary genomic dynamics of hybrids, especially in asexuals, which virtually reproduce as a frozen F1 generation.

The full potential for using DNA barcodes for profiling functional trait diversity has yet to be determined in plants and animals; thus, we outline a general framework for quantifying functional trait diversity of insect community DNA and propose and assess the accuracy of three methods for achieving this. We built a novel dataset of traits and DNA barcodes for wild bees in China. An informatics framework was developed for phylogeny-based integration of these data and prediction of traits for any subject barcodes, which was compared with two distance-based methods. For Phylogenetic Assignment, we additionally conducted a species-level analysis of publically available bee trait data. Under the specimen-level dataset, the rate of trait assignment was negatively correlated with distance between the query and the nearest trait-known reference, for all methods. Phylogenetic Assignment was found to perform best under several criteria; particularly, it had the lowest false-positive rate (rarely returning a state prediction where success was unlikely; where the distance from query to the nearest reference was high). For a wider range of compiled traits, conservative life-history traits showed the highest rates of assignment; for example, sociality was predicted with confidence at 53%, parasitism at 44% and nest location at 33%. As outlined herein, automated trait assignment might be applied at scale to either barcodes or metabarcodes. With further compilation and databasing of DNA barcode and trait data, the rate and accuracy of trait assignment is expected to increase to the point of being a widely viable and informative approach.

As most eukaryotic genomes are yet to be sequenced, the mechanisms underlying their contribution to different ecosystem processes remain untapped. Although approaches to recovering Prokaryotic genomes have become common in genome biology, few studies have tackled the recovery of eukaryotic genomes from metagenomes. This study assessed the reconstruction of microbial eukaryotic genomes using 6000 metagenomes from terrestrial and some transition environments using the EukRep pipeline. Only 215 metagenomic libraries yielded eukaryotic bins. From a total of 447 eukaryotic bins recovered 197 were classified at the phylum level. Streptophytes and fungi were the most represented clades with 83 and 73 bins, respectively. More than 78% of the obtained eukaryotic bins were recovered from samples whose biomes were classified as host-associated, aquatic, and anthropogenic terrestrial. However, only 93 bins were taxonomically assigned at the genus level and 17 bins at the species level. Completeness and contamination estimates were obtained for a total of 193 bins and consisted of 44.64% (σ = 27.41%) and 3.97% (σ = 6.53%), respectively. Micromonas commoda was the most frequent taxon found while Saccharomyces cerevisiae presented the highest completeness, probably because more reference genomes are available. Current measures of completeness are based on the presence of single-copy genes. However, mapping of the contigs from the recovered eukaryotic bins to the chromosomes of the reference genomes showed many gaps, suggesting that completeness measures should also include chromosome coverage. Recovering eukaryotic genomes will benefit significantly from long-read sequencing, development of tools for dealing with repeat-rich genomes, and improved reference genomes databases.

DNA barcoding is a well-established tool for rapid species identification and biodiversity monitoring. A reliable and traceable DNA barcode reference library with extensive coverage is necessary but unavailable for many geographical regions. The arid region in northwestern China, a vast area of about 2.5 million km2 , is ecologically fragile and often overlooked in biodiversity studies. In particular, DNA barcode data from the arid region in China are lacking. We develop and evaluate the efficacy of an extensive DNA barcode library for native flowering plants in the arid region of northwestern China. Plant specimens were collected, identified and vouchered for this purpose. The database utilized four DNA barcode markers, namely rbcL, matK, ITS and ITS2, for 1816 accessions (representing 890 species from 385 genera and 72 families), and consisted of 5196 barcode sequences. Individual barcodes varied in resolution rates: species- and genus-level rates for rbcL, matK, ITS and ITS2 were 79.9%-51.1%/76.1%, 79.9%-67.2%/88.9%, 85.0%-72.0%/88.2% and 81.0%-67.4%/84.9%, respectively. The three-barcode combination of rbcL + matK + ITS (RMI) revealed a higher species- and genus-level resolution (75.5%/92.1%, respectively). A total of 110 plastomes were newly generated as super-barcodes to increase species resolution for seven species-rich genera, namely Astragalus, Caragana, Lactuca, Lappula, Lepidium, Silene and Zygophyllum. Plastomes revealed higher species resolution compared to standard DNA barcodes and their combination. We suggest future databases include super-barcodes, especially for species-rich and complex genera. The plant DNA barcode library in the current study provides a valuable resource for future biological investigations in the arid regions of China.

In the face of global biodiversity declines, surveys of beneficial and antagonistic arthropod diversity as well as the ecological services that they provide are increasingly important in both natural and agro-ecosystems. Conventional survey methods used to monitor these communities often require extensive taxonomic expertise and are time-intensive, potentially limiting their application in industries such as agriculture, where arthropods often play a critical role in productivity (e.g. pollinators, pests and predators). Environmental DNA (eDNA) metabarcoding of a novel substrate, crop flowers, may offer an accurate and high throughput alternative to aid in the detection of these managed and unmanaged taxa. Here, we compared the arthropod communities detected with eDNA metabarcoding of flowers, from an agricultural species (Persea americana-'Hass' avocado), with two conventional survey techniques: digital video recording (DVR) devices and pan traps. In total, 80 eDNA flower samples, 96 h of DVRs and 48 pan trap samples were collected. Across the three methods, 49 arthropod families were identified, of which 12 were unique to the eDNA dataset. Environmental DNA metabarcoding from flowers revealed potential arthropod pollinators, as well as plant pests and parasites. Alpha diversity levels did not differ across the three survey methods although taxonomic composition varied significantly, with only 12% of arthropod families found to be common across all three methods. eDNA metabarcoding of flowers has the potential to revolutionize the way arthropod communities are monitored in natural and agro-ecosystems, potentially detecting the response of pollinators and pests to climate change, diseases, habitat loss and other disturbances.

We analysed the robustness of species identification based on proteomic composition to data processing and intraspecific variability, specificity and sensitivity of species-markers as well as discriminatory power of proteomic fingerprinting and its sensitivity to phylogenetic distance. Our analysis is based on MALDI-TOF MS (matrix-assisted laser desorption ionization time of flight mass spectrometry) data from 32 marine copepod species coming from 13 regions (North and Central Atlantic and adjacent seas). A random forest (RF) model correctly classified all specimens to the species level with only small sensitivity to data processing, demonstrating the strong robustness of the method. Compounds with high specificity showed low sensitivity, that is identification was based on complex pattern-differences rather than on presence of single markers. Proteomic distance was not consistently related to phylogenetic distance. A species-gap in proteome composition appeared at 0.7 Euclidean distance when using only specimens from the same sample. When other regions or seasons were included, intraspecific variability increased, resulting in overlaps of intra and inter-specific distance. Highest intraspecific distances (>0.7) were observed between specimens from brackish and marine habitats (i.e., salinity probably affects proteomic patterns). When testing library sensitivity of the RF model to regionality, strong misidentification was only detected between two congener pairs. Still, the choice of reference library may have an impact on identification of closely related species and should be tested before routine application. We envisage high relevance of this time- and cost-efficient method for future zooplankton monitoring as it provides not only in-depth taxonomic resolution for counted specimens but also add-on information, such as on developmental stage or environmental conditions.

Phylogeography is an integrative field of science linking micro- and macro-evolutionary processes, contributing to the inference of vicariance, dispersal, speciation, and other population-level processes. Phylogeographic surveys usually require considerable effort and time to obtain numerous samples from many geographical sites covering the distribution range of target species; this associated high cost limits their application. Recently, environmental DNA (eDNA) analysis has been useful not only for detecting species but also for assessing genetic diversity; hence, there has been growing interest in its application to phylogeography. As the first step of eDNA-based phylogeography, we examined (1) data screening procedures suitable for phylogeography and (2) whether the results obtained from eDNA analysis accurately reflect known phylogeographic patterns. For these purposes, we performed quantitative eDNA metabarcoding using group-specific primer sets in five freshwater fish species belonging to two taxonomic groups from a total of 94 water samples collected from western Japan. As a result, three-step data screening based on the DNA copy number of each haplotype detected successfully eliminated suspected false positive haplotypes. Furthermore, eDNA analysis could almost perfectly reconstruct the phylogenetic and phylogeographic patterns obtained for all target species with the conventional method. Despite existing limitations and future challenges, eDNA-based phylogeography can significantly reduce survey time and effort and is applicable for simultaneous analysis of multiple species in single water samples. eDNA-based phylogeography has the potential to revolutionize phylogeography.

The ability to gather genetic information using DNA metabarcoding of bulk samples obtained directly from the environment is crucial to determine biodiversity baselines and understand population dynamics in the marine realm. While DNA metabarcoding is effective in evaluating biodiversity at community level, genetic patterns within species are often concealed in metabarcoding studies and overlooked for marine invertebrates. In the present study, we implement recently developed bioinformatics tools to investigate intraspecific genetic variability for invertebrate taxa in the Mediterranean Sea. Using metabarcoding samples from Autonomous Reef Monitoring Structures (ARMS) deployed in three locations, we present haplotypes and diversity estimates for 145 unique species. While overall genetic diversity was low, we identified several species with high diversity records and potential cryptic lineages. Further, we emphasize the spatial scale of genetic variability, which was observed from locations to individual sampling units (ARMS). We carried out a population genetic analysis of several important yet understudied species, which highlights the current knowledge gap concerning intraspecific genetic patterns for the target taxa in the Mediterranean basin. Our approach considerably enhances biodiversity monitoring of charismatic and understudied Mediterranean species, which can be incorporated into ARMS surveys.

The proliferation of genomic sequencing approaches has significantly impacted the field of phylogenetics. Target capture approaches provide a cost-effective, fast and easily applied strategy for phylogenetic inference of non-model organisms. However, several existing target capture processing pipelines are incapable of incorporating whole genome sequencing (WGS). Here, we develop a new pipeline for capture and de novo assembly of the targeted regions using whole genome re-sequencing reads. This new pipeline captured targeted loci accurately, and given its unbiased nature, can be used with any target capture probe set. Moreover, due to its low computational demand, this new pipeline may be ideal for users with limited resources and when high-coverage sequencing outputs are required. We demonstrate the utility of our approach by incorporating WGS data into the first comprehensive phylogenomic reconstruction of the freshwater mussel family Margaritiferidae. We also provide a catalogue of well-curated functional annotations of these previously uncharacterized freshwater mussel-specific target regions, representing a complementary tool for scrutinizing phylogenetic inferences while expanding future applications of the probe set.

Epigenetic processes have taken center stage for the investigation of many biological processes, and epigenetic modifications have shown to influence phenotype, morphology and behavioural traits such as stress resistance by affecting gene regulation and expression without altering the underlying genomic sequence. The multiple molecular layers of epigenetics synergistically construct the cell type-specific gene regulatory networks, characterized by a high degree of plasticity and redundancy to create cell-type-specific morphology and function. DNA methylation occurring on the 5' carbon of cytosines in different genomic sequence contexts is the most studied epigenetic modification. DNA methylation has been shown to provide a molecular record of the exposure to a large variety of environmental factors, which might be persistent through the entire lifetime of an organism and even be passed onto the offspring. Animals might display altered phenotypes mediated by epigenetic modifications depending on the developmental stage or the environmental conditions as well as during evolution. Therefore, the analysis of DNA methylation patterns might allow deciphering previous exposures, explaining ecologically relevant phenotypic diversity and predicting evolutionary trajectories enabling accelerated adaption to changing environmental conditions. Despite the explanatory potential of DNA methylation integrating genetic and environmental factors to shape phenotypic variation and contribute significantly to evolutionary dynamics, studies of DNA methylation are still scarce in the field of ecology. This might be at least partly due to the complexity of DNA methylation analysis and the interpretation of the acquired data. In the current issue of Molecular Ecology Resources, Laine and colleagues (Molecular Ecology Resources, 2022) provide a detailed summary of guidelines and valuable recommendations for researchers in the field of ecology to avoid common pitfalls and perform interpretable genome-wide DNA methylation analyses.

Environmental DNA-based diversity studies have increased in popularity with the development of high throughput sequencing technologies. This permits the potential simultaneous retrieval of vast amounts of molecular data from many different organisms and species, thus contributing to a wide range of biological disciplines. Environmental DNA protocols designed for protists often focused on the highly conserved small subunit of the ribosome gene, that does not permit species-level assignments. On the other hand, eDNA protocols aiming at species-level assignments allow a fine level ecological resolution and reproducible results. These protocols are currently applied to organisms living in marine and shallow lotic freshwater ecosystems, often in a bioindication purpose. Therefore, in this study, we present a species-level eDNA protocol designed to explore diversity of Arcellinida (Amoebozoa: Tubulinea) testate amoebae taxa that is based on mitochondrial cytochrome oxidase subunit I (COI). These organisms are widespread in lentic water bodies and soil ecosystems. We applied this protocol to 42 samples from peatlands, estuaries and soil environments, recovering all the infraorders in Glutinoconcha (with COI data), except for Hyalospheniformes. Our results revealed an unsuspected diversity in morphologically homogeneous groups such as Cylindrothecina, Excentrostoma or Sphaerothecina. With this protocol we expect to revolutionize the design of modern distributional Arcellinida surveys. Our approach involves a rapid and cost-effective analysis of testate amoeba diversity living in contrasted ecosystems. Therefore, the order Arcellinida has the potential to be established as a model group for a wide range of theoretical and applied studies.

Although being famous for sequestering milkweed cardenolides, the mechanism of sequestration and where cardenolides are localized in caterpillars of the monarch butterfly (Danaus plexippus, Lepidoptera: Danaini) is still unknown. While monarchs tolerate cardenolides by a resistant Na+ /K+ -ATPase, it is unclear how closely related species such as the nonsequestering common crow butterfly (Euploea core, Lepidoptera: Danaini) cope with these toxins. Using novel atmospheric-pressure scanning microprobe matrix-assisted laser/desorption ionization mass spectrometry imaging, we compared the distribution of cardenolides in caterpillars of D. plexippus and E. core. Specifically, we tested at which physiological scale quantitative differences between both species are mediated and how cardenolides distribute across body tissues. Whereas D. plexippus sequestered most cardenolides from milkweed (Asclepias curassavica), no cardenolides were found in the tissues of E. core. Remarkably, quantitative differences already manifest in the gut lumen: while monarchs retain and accumulate cardenolides above plant concentrations, the toxins are degraded in the gut lumen of crows. We visualized cardenolide transport over the monarch midgut epithelium and identified integument cells as the final site of storage where defences might be perceived by predators. Our study provides molecular insight into cardenolide sequestration and highlights the great potential of mass spectrometry imaging for understanding the kinetics of multiple compounds including endogenous metabolites, plant toxins, or insecticides in insects.

The coastline of Sub-Saharan Africa hosts highly diverse fish communities of great conservation value, which are also key resources for local livelihoods. However, many costal ecosystems are threatened by overexploitation and their conservation state is frequently unknown due to their vast spatial extent and limited monitoring budgets. Here, we evaluated the potential of citizen science-based eDNA surveys to alleviate such chronic data deficiencies and assessed fish communities in Mozambique using two 12S metabarcoding primer sets. Samples were either collected by scientific personnel or trained community members and results from the two metabarcoding primers were combined using a new data merging approach. Irrespective of the background of sampling personnel, a high average fish species richness was recorded (38 ± 20 OTUs per sample). Individual sections of the coastline largely differed in the occurrence of threatened and commercially important species, highlighting the need for regionally differentiated management strategies. A detailed comparison of the two applied primer sets revealed an important trade-off in primer choice with MiFish primers amplifying a higher number of species but Riaz primers performing better in the detection of threatened fish species. This trade-off could be partly resolved by applying our new data-merging approach, which was especially designed to increase the robustness of multiprimer assessments in regions with poor reference libraries. Overall, our study provides encouraging results but also highlights that eDNA-based monitoring will require further improvements of, for example, reference databases and local analytical infrastructure to facilitate routine applications in Sub-Saharan Africa.

Innovations in ancient DNA (aDNA) preparation and sequencing technologies have exponentially increased the quality and quantity of aDNA data extracted from ancient biological materials. The additional temporal component from the incoming aDNA data can provide improved power to address fundamental evolutionary questions like characterizing selection processes that shape the phenotypes and genotypes of contemporary populations or species. However, utilizing aDNA to study past selection processes still involves considerable hurdles like how to eliminate the confounding factor of genetic interactions in the inference of selection. To address this issue, we extend the approach of He et al., 2023 to infer temporally variable selection from the aDNA data in the form of genotype likelihoods with the flexibility of modelling linkage and epistasis in this work. Our posterior computation is carried out by a robust adaptive version of the particle marginal Metropolis-Hastings algorithm with a coerced acceptance rate. Our extension inherits the desirable features of He et al., 2023 such as modelling sample uncertainty resulting from the damage and fragmentation of aDNA molecules and reconstructing underlying gamete frequency trajectories of the population. We evaluate its performance through extensive simulations and show its utility with an application to the aDNA data from pigmentation loci in horses.

Mythimna separata and Mythimna loreyi are global pests of gramineous cereals, heavily controlled with synthetic insecticides. Here, we generated two high-quality chromosome-level genome assemblies for M. separata (688 Mb) and M. loreyi (683 Mb). Our analysis identified Z and W chromosomes, with few genes and abundant transposable elements (TEs) found on the W chromosome. We also observed a recent explosion of long interspersed nuclear elements (LINEs), which contributed to the larger genomes of Mythimna. The two armyworms diverged ~10.5 MYA, with only three chromosomes have intrachromosomal rearrangements. Additionally, we observed a tandem repeat expansion of α-amylase genes in Mythimna, which may promote the digestion of carbohydrates and exacerbate their damage to crops. Furthermore, we inferred the sex pheromone biosynthesis pathway for M. separata, M. loreyi and Spodoptera frugiperda. We discovered that M. loreyi and S. frugiperda synthesized the same major constituents of sex pheromones through different pathways. Specifically, the double bonds in the dominant sex pheromone components of S. frugiperda were generated by Δ9- and Δ11-desaturase, while they were generated by Δ11-desaturase and chain-shortening reactions in M. loreyi. We also identified pheromone receptor (PR) genes and inferred their corresponding components. These findings provide a better understanding of sex pheromone communication and promote the development of a new pest control strategy involving pheromone traps, which are more effective and environmentally friendly than current strategies.

Conifers make up about one third of global forests but are threatened by seed parasitoid wasp species. Many of these wasps belong to the genus Megastigmus, yet little is known about their genomic background. In this study, we provide chromosome-level genome assemblies for two oligophagous conifer parasitoid species of Megastigmus, which represent the first two chromosome-level genomes of the genus. The assembled genomes of Megastigmus duclouxiana and M. sabinae are 878.48 Mb (scaffold N50 of 215.60 Mb) and 812.98 Mb (scaffold N50 of 139.16 Mb), respectively, which are larger than the genome size of most hymenopterans due to the expansion of transposable elements. Expanded gene families highlight the difference in sensory-related genes between the two species, reflecting the difference in their hosts. We further found that these two species have fewer family members but more single-gene duplications than polyphagous congeners in the gene families of ATP-binding cassette transporter (ABC), cytochrome P450 (P450) and olfactory receptors (OR). These findings shed light on the pattern of adaptation to a narrow spectrum of hosts in oligophagous parasitoids. Our findings suggest potential drivers underlying genome evolution and parasitism adaptation, and provide valuable resources for understanding the ecology, genetics and evolution of Megastigmus, as well as for the research and biological control of global conifer forest pests.

The distribution of fitness effects (DFE) of new mutations has been of interest to evolutionary biologists since the concept of mutations arose. Modern population genomic data enable us to quantify the DFE empirically, but few studies have examined how data processing, sample size and cryptic population structure might affect the accuracy of DFE inference. We used simulated and empirical data (from Arabidopsis lyrata) to show the effects of missing data filtering, sample size, number of single nucleotide polymorphisms (SNPs) and population structure on the accuracy and variance of DFE estimates. Our analyses focus on three filtering methods-downsampling, imputation and subsampling-with sample sizes of 4-100 individuals. We show that (1) the choice of missing-data treatment directly affects the estimated DFE, with downsampling performing better than imputation and subsampling; (2) the estimated DFE is less reliable in small samples (<8 individuals), and becomes unpredictable with too few SNPs (<5000, the sum of 0- and 4-fold SNPs); and (3) population structure may skew the inferred DFE towards more strongly deleterious mutations. We suggest that future studies should consider downsampling for small data sets, and use samples larger than 4 (ideally larger than 8) individuals, with more than 5000 SNPs in order to improve the robustness of DFE inference and enable comparative analyses.

Adaptive capacity can present challenges for modelling as it encompasses multiple ecological and evolutionary processes such as natural selection, genetic drift, gene flow and phenotypic plasticity. Spatially explicit, individual-based models provide an outlet for simulating these complex interacting eco-evolutionary processes. We expanded the existing Cost-Distance Meta-POPulation (CDMetaPOP) framework with inducible plasticity modelled as a habitat selection behaviour, using temperature or habitat quality variables, with a genetically based selection threshold conditioned on past individual experience. To demonstrate expected results in the new module, we simulated hypothetical populations and then evaluated model performance in populations of redband trout (Oncorhynchus mykiss gairdneri) across three watersheds where temperatures induce physiological stress in parts of the stream network. We ran simulations using projected warming stream temperature data under four scenarios for alleles that: (1) confer thermal tolerance, (2) bestow plastic habitat selection, (3) give both thermal tolerance and habitat selection preference and (4) do not provide either thermal tolerance or habitat selection. Inclusion of an adaptive allele decreased declines in population sizes, but this impact was greatly reduced in the relatively cool stream networks. As anticipated with the new module, high-temperature patches remained unoccupied by individuals with the allele operating plastically after exposure to warm temperatures. Using complete habitat avoidance above the stressful temperature threshold, habitat selection reduced the overall population size due to the opportunity cost of avoiding areas with increased, but not guaranteed, mortality. Inclusion of plasticity within CDMetaPOP will provide the potential for genetic or plastic traits and 'rescue' to affect eco-evolutionary dynamics for research questions and conservation applications.

Measurement of allele frequency shifts between temporally spaced samples has long been used for assessment of effective population size (Ne ), and this 'temporal method' provides estimates of Ne referred to as variance effective size (NeV ). We show that NeV of a local population that belongs to a sub-structured population (a metapopulation) is determined not only by genetic drift and migration rate (m), but also by the census size (Nc ). The realized NeV of a local population can either increase or decrease with increasing m, depending on the relationship between Ne and Nc in isolation. This is shown by explicit mathematical expressions for the factors affecting NeV derived for an island model of migration. We verify analytical results using high-resolution computer simulations, and show that the phenomenon is not restricted to the island model migration pattern. The effect of Nc on the realized NeV of a local subpopulation is most pronounced at high migration rates. We show that Nc only affects local NeV , whereas NeV for the metapopulation as a whole, inbreeding (NeI ), and linkage disequilibrium (NeLD ) effective size are all independent of Nc . Our results provide a possible explanation to the large variation of Ne /Nc ratios reported in the literature, where Ne is frequently estimated by NeV . They are also important for the interpretation of empirical Ne estimates in genetic management where local NeV is often used as a substitute for inbreeding effective size, and we suggest an increased focus on metapopulation NeV as a proxy for NeI .

Detection of invasive species is critical for management but is often limited by challenges associated with capture, processing and identification of early life stages. DNA metabarcoding facilitates large-scale monitoring projects to detect establishment early. Here, we test the use of DNA metabarcoding to monitor invasive species by sequencing over 5000 fishes in bulk ichthyoplankton samples (larvae and eggs) from four rivers of ecological and cultural importance in southern Canada. We were successful in detecting species known from each river and three invasive species in two of the four rivers. This includes the first detection of early life-stage rudd in the Credit River. We evaluated whether sampling gear affected the detection of invasive species and estimates of species richness, and found that light traps outperform bongo nets in both cases. We also found that the primers used for the amplification of target sequences and the number of sequencing reads generated per sample affect the consistency of species detections. However, these factors have less impact on detections and species richness estimates than the number of samples collected and analysed. Our analyses also show that incomplete reference databases can result in incorrectly attributing DNA sequences to invasive species. Overall, we conclude that DNA metabarcoding is an efficient tool for monitoring the early establishment of invasive species by detecting evidence of reproduction but requires careful consideration of sampling design and the primers used to amplify, sequence and classify the diversity of native and potentially invasive species.

Morphological identification of cnidarian species can be difficult throughout all life stages due to the lack of distinct morphological characters. Moreover, in some cnidarian taxa genetic markers are not fully informative, and in these cases combinations of different markers or additional morphological verifications may be required. Proteomic fingerprinting based on MALDI-TOF mass spectra was previously shown to provide reliable species identification in different metazoans including some cnidarian taxa. For the first time, we tested the method across four cnidarian classes (Staurozoa, Scyphozoa, Anthozoa, Hydrozoa) and included different scyphozoan life-history stages (polyp, ephyra, medusa) in our dataset. Our results revealed reliable species identification based on MALDI-TOF mass spectra across all taxa with species-specific clusters for all 23 analysed species. In addition, proteomic fingerprinting was successful for distinguishing developmental stages, still by retaining a species specific signal. Furthermore, we identified the impact of different salinities in different regions (North Sea and Baltic Sea) on proteomic fingerprints to be negligible. In conclusion, the effects of environmental factors and developmental stages on proteomic fingerprints seem to be low in cnidarians. This would allow using reference libraries built up entirely of adult or cultured cnidarian specimens for the identification of their juvenile stages or specimens from different geographic regions in future biodiversity assessment studies.