Sponge gourd (Luffa cylindrica (L.) Roem.) or luffa is a diploid herbaceous plant with 26 chromosomes (2n = 26) and belongs to the family Cucurbitaceae. To address the limited knowledge of the genome of Luffa species, the chromosome‐level genome of L. cylindrica was assembled and analysed using PacBio long reads and Hi‐C data. We combined Hi‐C data with a draft genome assembly to generate chromosome‐length scaffolds. Thirteen scaffolds corresponding to the 13 chromosomes were assembled from 1,156 contigs to a final size of 669 Mb with a contig N50 size of 5 Mb and a scaffold N50 size of 53 Mb. After removing redundant sequences, 416.31 Mb (62.18% of the genome) of repeat sequences was detected. Subsequently, 31,661 protein‐coding genes with an average of 5.69 exons per gene were identified in the L. cylindrica genome using de novo methods, transcriptome data and homologue‐based approaches. In addition, 27,552 protein‐coding genes (87.02%) were annotated in five databases. According to the phylogenetic analysis, L. cylindrica is closely related to Cucurbita and Cucumis species and diverged from their common ancestor ~28.6–67.1 million years ago. Genome collinearity analysis was performed in Cucurbita moschata, Cucumis sativus and L. cylindrica, and it demonstrated a high degree of conserved gene order in these three species. The completeness of the genome will provide high‐quality genomic knowledge on breeding and reveal genetic variation in L. cylindrica.

The ability to detect the identity of a sample obtained from its environment is a cornerstone of molecular ecological research. Thanks to the falling price of shotgun sequencing, genome skimming, the acquisition of short reads spread across the genome at low coverage, is emerging as an alternative to traditional barcoding. By obtaining far more data across the whole genome, skimming has the promise to increase the precision of sample identification beyond traditional barcoding while keeping the costs manageable. While methods for assembly‐free sample identification based on genome skims are now available, little is known about how these methods react to the presence of DNA from organisms other than the target species. In this paper, we show that the accuracy of distances computed between a pair of genome skims based on k‐mer similarity can degrade dramatically if the skims include contaminant reads; i.e., any reads originating from other organisms. We establish a theoretical model of the impact of contamination. We then suggest and evaluate a solution to the contamination problem: Query reads in a genome skim against an extensive database of possible contaminants (e.g., all microbial organisms) and filter out any read that matches. We evaluate the effectiveness of this strategy when implemented using Kraken‐II, in detailed analyses. Our results show substantial improvements in accuracy as a result of filtering but also point to limitations, including a need for relatively close matches in the contaminant database.

The genomic era has led to an unprecedented increase in the availability of genome‐wide data for a broad range of taxa. Wildlife management strives to make use of these vast resources to enable refined genetic assessments that enhance biodiversity conservation. However, as new genomic platforms emerge, problems remain in adapting the usually complex approaches for genotyping of non‐invasively collected wildlife samples. Here, we provide practical guidelines for the standardized development of reduced single nucleotide polymorphism (SNP) panels applicable for microfluidic genotyping of degraded DNA samples, such as faeces or hairs. We demonstrate how microfluidic SNP panels can be optimized to efficiently monitor European wildcat (Felis silvestris S.) populations. We show how panels can be set up in a modular fashion to accommodate informative markers for relevant population genetics questions, such as individual identification, hybridization assessment and the detection of population structure. We discuss various aspects regarding the implementation of reduced SNP panels and provide a framework that will allow both molecular ecologists and practitioners to help bridge the gap between genomics and applied wildlife conservation.

The house sparrow is an important model species for studying physiological, ecological and evolutionary processes in wild populations. Here, we present a medium density, genome wide linkage map for house sparrow (Passer domesticus) that has aided the assembly of the house sparrow reference genome, and that will provide an important resource for ongoing mapping of genes controlling important traits in the ecology and evolution of this species. Using a custom house sparrow 10K iSelect Illumina SNP chip we have assigned 6,498 SNPs to 29 autosomal linkage groups, based on a mean of 430 informative meioses per SNP. The map was constructed by combining the information from linkage with that of the physical position of SNPs within scaffold sequences in an iterative process. Averaged between the sexes; the linkage map had a total length of 2004 cM, with a longer map for females (2,240 cM) than males (1801 cM). Additionally, recombination rates also varied along the chromosomes. Comparison of the linkage map to the reference genomes of zebra finch, collared flycatcher and chicken, showed a chromosome fusion of the two avian chromosomes 8 and 4A in house sparrow. Lastly, information from the linkage map was utilized to conduct analysis of linkage disequilibrium (LD) in eight populations with different effective population sizes (Ne) in order to quantify the background level LD. Together, these results aid the design of future association studies, facilitate the development of new genomic tools and support the body of research that describes the evolution of the avian genome.

Yellow perch, Perca flavescens, is an ecologically and economically important species native to a large portion of the northern United States and southern Canada and is also a promising candidate species for aquaculture. No yellow perch reference genome, however, has been available to facilitate improvements in both fisheries and aquaculture management practices. By combining Oxford Nanopore Technologies long‐reads, 10X genomics Illumina short linked reads and a chromosome contact map produced with Hi‐C, we generated a high‐continuity chromosome scale yellow perch genome assembly of 877.4 Mb. It contains, in agreement with the known diploid chromosome yellow perch count, 24 chromosome‐size scaffolds covering 98.8% of the complete assembly (N50 = 37.4 Mb, L50 = 11). We also provide a first characterization of the yellow perch sex determination locus that contains a male‐specific duplicate of the anti‐Mullerian hormone type II receptor gene (amhr2by) inserted at the proximal end of the Y chromosome (chromosome 9). Using this sex‐specific information, we developed a simple PCR genotyping assay which accurately differentiates XY genetic males (amhr2by+) from XX genetic females (amhr2by‐). Our high‐quality genome assembly is an important genomic resource for future studies on yellow perch ecology, toxicology, fisheries, and aquaculture research. In addition, the characterization of the amhr2by gene as a candidate sex determining gene in yellow perch provides a new example of the recurrent implication of the transforming growth factor beta pathway in fish sex determination, and highlights gene duplication as an important genomic mechanism for the emergence of new master sex determination genes.

Microbial communities, which drive major ecosystem functions, consist of a wide range of interacting species. Understanding how microbial communities are structured and the processes underlying this is crucial to interpreting ecosystem responses to global change but is challenging as microbial interactions cannot usually be directly observed. Multiple efforts are currently focused to combine next‐generation sequencing (NGS) techniques with refined statistical analysis (e.g., network analysis, multivariate analysis) to characterize the structures of microbial communities. However, most of these approaches consider a single table of sequencing data measured for several samples. Technological advances now make it possible to collect NGS data on different taxonomic groups simultaneously for the same samples, allowing us to analyse a pair of tables. Here, an analytical framework based on co‐correspondence analysis (CoCA) is proposed to study the distributions, assemblages and interactions between two microbial communities. We show the ability of this approach to highlight the relationships between two microbial communities, using two data sets exhibiting various types of interactions. CoCA identified strong association patterns between autotrophic and heterotrophic microbial eukaryote assemblages, on the one hand, and between microalgae and viruses, on the other. We demonstrate also how CoCA can be used, complementary to network analysis, to reorder co‐occurrence networks and thus investigate the presence of patterns in ecological networks.

The superb fairy‐wren, Malurus cyaneus, is one of the most iconic Australian passerine species. This species belongs to an endemic Australasian clade, Meliphagides, which diversified early in the evolution of the oscine passerines. Today, the oscine passerines comprise almost half of all avian species diversity. Despite the rapid increase of available bird genome assemblies, this part of the avian tree has not yet been represented by a high‐quality reference. To rectify that, we present the first high‐quality genome assembly of a Meliphagides representative: the superb fairy‐wren. We combined Illumina shotgun and mate‐pair sequences, PacBio long‐reads, and a genetic linkage map from an intensively sampled pedigree of a wild population to generate this genome assembly. Of the final assembled 1.07‐Gb genome, 975 Mb (90.4%) was anchored onto 25 pseudochromosomes resulting in a final superscaffold N50 of 68.11 Mb. This high‐quality bird genome assembly is one of only a handful which is also accompanied by a genetic map and recombination landscape. In comparison to other pedigree‐based bird genetic maps, we find that the fairy‐wren genetic map more closely resembles those of Taeniopygia guttata and Parus major maps, unlike the Ficedula albicollis map which more closely resembles that of Gallus gallus. Lastly, we also provide a predictive gene and repeat annotation of the genome assembly. This new high‐quality, annotated genome assembly will be an invaluable resource not only regarding the superb fairy‐wren species and relatives but also broadly across the avian tree by providing a novel reference point for comparative genomic analyses.

EnTAP (Eukaryotic Non‐Model Transcriptome Annotation Pipeline) was designed to improve the accuracy, speed, and flexibility of functional gene annotation for de novo assembled transcriptomes in non‐model eukaryotes. This software package addresses the fragmentation and related assembly issues that result in inflated transcript estimates and poor annotation rates of protein‐coding transcripts. Following filters applied through assessment of true expression and frame selection, open‐source tools are leveraged to functionally annotate the reduced set of translated proteins. Downstream features include fast similarity search across five repositories, protein domain assignment, orthologous gene family assessment, and Gene Ontology (GO) term assignment. The final annotation integrates across multiple databases and selects an optimal assignment from a combination of weighted metrics describing similarity search score, taxonomic relationship, and informativeness. Researchers have the option to include additional filters to identify and remove contaminants, identify associated pathways, and prepare the transcripts for enrichment analysis. This fully featured pipeline is easy to install, configure, and runs significantly faster than comparable annotation packages. EnTAP is optimized to generate extensive functional information for the gene space of organisms with limited or poorly characterized genomic resources.

Although environmental DNA shed from an organism is now widely used for species detection in a wide variety of contexts, mobilizing environmental DNA for management requires estimation of population size and trends in addition to assessing presence or absence. However, the efficacy of environmental‐DNA‐based indices of abundance for long‐term population monitoring have not yet been assessed. Here we report on the relationship between six years of mark‐recapture population estimates for eulachon (Thaleichthys pacificus) and “eDNA rates” which are calculated from the product of stream flow and DNA concentration. Eulachon are a culturally and biologically important anadromous fish that have significantly declined in the southern part of their range but were historically rendered into oil and traded. Both the peak eDNA rate and the area under the curve of the daily eDNA rate were highly predictive of the mark‐recapture population estimate, explaining 84.96% and 92.53% of the deviance, respectively. Even in the absence of flow correction, the peak of the daily eDNA concentration explained an astonishing 89.53% while the area under the curve explained 90.74% of the deviance. These results support the use of eDNA to monitor eulachon population trends and represent a >80% cost savings over mark‐recapture, which could be further increased with automated water sampling, reduced replication, and focused temporal sampling. Due to its logistical ease and affordability, eDNA sampling can facilitate monitoring a larger number of rivers and in remote locations where mark‐recapture is infeasible.

The Tetraodontidae family are known to have relatively small and compact genomes compared to other vertebrates. The obscure puffer fish Takifugu obscurus is an anadromous species that migrates to freshwater from the sea for spawning. Thus the euryhaline characteristics of T. obscurus have been investigated to gain understanding of their survival ability, osmoregulation, and other homeostatic mechanisms in both freshwater and seawater. In this study, a high‐quality chromosome‐level reference genome for T. obscurus was constructed using long‐read Pacific Biosciences (PacBio) Sequel sequencing and a Hi‐C‐based chromatin contact map platform. The final genome assembly of T. obscurus is 381 Mb, with a contig N50 length of 3,296 kb and longest length of 10.7 Mb, from a total of 62 Gb of raw reads generated using single‐molecule real‐time sequencing technology from a PacBio Sequel platform. The PacBio data were further clustered into chromosome‐scale scaffolds using a Hi‐C approach, resulting in a 373 Mb genome assembly with a contig N50 length of 15.2 Mb and and longest length of 28 Mb. When we directly compared the 22 longest scaffolds of T. obscurus to the 22 chromosomes of the tiger puffer Takifugu rubripes, a clear one‐to‐one orthologous relationship was observed between the two species, supporting the chromosome‐level assembly of T. obscurus. This genome assembly can serve as a valuable genetic resource for exploring fugu‐specific compact genome characteristics, and will provide essential genomic information for understanding molecular adaptations to salinity fluctuations and the evolution of osmoregulatory mechanisms.

Determining the origin of individuals in mixed population samples is key in many ecological, conservation and management contexts. Genetic data can be analyzed using Genetic Stock Identification (GSI), where the origin of single individuals is determined using Individual Assignment (IA) and population proportions are estimated with Mixed Stock Analysis (MSA). In such analyses, allele frequencies in a reference baseline are required. Unknown individuals or mixture proportions are assigned to source populations based on the likelihood that their multilocus genotypes occur in a particular baseline sample. Representative sampling of populations included in a baseline is important when designing and performing GSI. Here we investigate the effects of family sampling on GSI, using both simulated and empirical genotypes for Atlantic salmon (Salmo salar). We show that non‐representative sampling leading to inclusion of close relatives in a reference baseline may introduce bias in estimated proportions of contributing populations in a mixed sample, and increases the amount of incorrectly assigned individual fish. Simulated data further show that the induced bias increases with increasing family structure, but that it can be partly mitigated by increased baseline population sample sizes. Results from standard accuracy tests of GSI (using only a reference baseline and/or self‐assignment) gave a false and elevated indication of the baseline power and accuracy to identify stock proportions and individuals. These findings suggest that family structure in baseline population samples should be quantified and its consequences evaluated, before carrying out GSI.

Molecular ecology regularly requires the analysis of count data that reflect the relative abundance of features of a composition (e.g., taxa in a community, gene transcripts in a tissue). The sampling process that generates these data can be modeled using the multinomial distribution. Replicate multinomial samples inform the relative abundances of features in an underlying Dirichlet distribution. These distributions together form a hierarchical model for relative abundances among replicates and sampling groups. This type of Dirichletmultinomial modelling (DMM) has been described previously, but its benefits and limitations are largely untested. With simulated data, we quantified the ability of DMM to detect differences in proportions between treatment and control groups, and compared the efficacy of three computational methods to implement DMM—Hamiltonian Monte Carlo (HMC), variational inference (VI), and Gibbs Markov chain Monte Carlo. We report that DMM was better able to detect shifts in relative abundances than analogous analytical tools, while identifying an acceptably low number of false positives. Among methods for implementing DMM, HMC provided the most accurate estimates of relative abundances, and VI was the most computationally efficient. The sensitivity of DMM was exemplified through analysis of previously published data describing lung microbiomes. We report that DMM identified several potentially pathogenic, bacterial taxa as more abundant in the lungs of children who aspirated foreign material during swallowing; these differences went undetected with different statistical approaches. Our results suggest that DMM has strong potential as a statistical method to guide inference in molecular ecology.

Museum collections are essential for reconstructing and understanding past biodiversity. Many museum specimens are, however, challenging to identify. Museum samples may be incomplete, have an unusual morphology, or represent juvenile individuals, all of which complicate accurate identification. In some cases, inaccurate identification can lead to false biogeographic reconstructions with cascading impacts on paleontological and paleoecological research. Here we analyze an unusual Equid mandible found in the Far North of the Taymyr peninsula that was identified morphologically as Equus hemionus, an ancestor of present‐day Asiatic wild asses. If correct, this identification represents the only finding of a putative Late Pleistocene hemione in the Arctic region, and is therefore critical to understanding wild ass evolution and paleoecology. To confirm the accuracy of this specimen's taxonomic assignment, we used ancient DNA and mitochondrial hybridization capture to identify and place this specimen in the larger equid phylogeny. We find that the specimen is actually a member of E. caballus, the ancestor of domestic horses. Our study demonstrates the utility of ancient DNA to validate morphological identification, in particular of incomplete, otherwise problematic, or taxonomically unusual museum specimens.

Genomic technologies continue to shed light on important ecological and evolutionary questions. Nonetheless, these new tools are applied disproportionately in a small fraction of global biodiversity, partly because of technical challenges to studying highly diverse taxa that occur in low abundances in an environment (e.g., marine and microbial communities). As a result, our understanding of ecological and evolutionary processes lags in many taxa. In a From the Cover manuscript in this issue of Molecular Ecology Resources, Galen, Borner, Williamson, Witt, and Perkins (2020) present a novel approach for characterizing diversity that combines metatranscriptomics with rigorous bioinformatic processing to dramatically improve detection and identification of diverse, low‐abundance avian blood parasites. Their approach is an exciting application of available tools that increases our potential for a deeper understanding of diversity in other communities of low‐abundance, highly diverse taxa.

We implemented multilocus selection in a spatially‐explicit, individual‐based framework that enables multivariate environmental gradients to drive selection in many loci as a new module for the landscape genetics programs, CDPOP and CDMetaPOP. Our module simulates multilocus selection using a linear additive model, providing a flexible platform to evaluate a wide range of genotype‐environment associations. Importantly, the module allows simulation of selection in any number of loci under the influence of any number of environmental variables. We validated the module with individual‐based selection simulations under Wright‐Fisher assumptions. We then evaluated results for simulations under a simple landscape selection model. Next, we simulated individual‐based multilocus selection across a complex selection landscape with three loci linked to three different environmental variables. Finally, we demonstrated how the program can be used to simulate multilocus selection under varying selection strengths across different levels of gene flow in a landscape genetics framework. This new module provides a valuable addition to the study of landscape genetics, allowing for explicit evaluation of the contributions and interactions between gene flow and selection‐driven processes across complex, multivariate environmental and landscape conditions.

Multiple male mating (MMM) causes sperm competition, which may play an important role in the evolution of reproductive traits. The frequency of multiple paternity (MP), where multiple males sire offspring within a single litter, has been used as an index of MMM frequency. However, MP frequency is necessarily lower than MMM frequency. The magnitude of the difference between MMM and MP frequency depends on litter size (LS) and fertilization probability skew (FPS), and this difference may be meaningfully large in animals with small LSs. In this study, we propose a method to estimate MMM frequency using an individual‐based model with three variables (MP frequency, LS and FPS). We incorporated observed paternity skew data to infer a possible range of FPS that cannot be measured in free‐living populations and tested the validity of our method using a data set from a grey‐sided vole (Myodes rufocanus) population and from hypothetical populations. MP was found in 50 out of 215 litters (23.3%) in the grey‐sided vole population, while MMM frequency was estimated in 67 of 215 litters (31.2%), with a certainty range of 59–88 (27.4%–40.9%). The point estimation of MMM frequency was realized, and the certainty range was limited within the practical range. The use of observed paternity skew was very effective at narrowing the certainty range of the estimate. Our method could contribute to a deeper understanding of the ecology of MMM in free‐living populations.

Management of biological invasions and conservation activity in the fight against habitat fragmentation both require information on how ongoing dispersal of organisms is affected by the environment. However, there are few landscape genetic programs that map resistance to dispersal at small spatiotemporal scales. To facilitate such analyses, we present an R package named ResDisMapper for the mapping of resistance to dispersal at small spatiotemporal scales, without the need for prior knowledge on environmental features or intensive computation. Based on the concept of isolation by distance (IBD), ResDisMapper calculates resistance using deviations of each pair of samples from the general IBD trend (IBD residuals). The IBD residuals are projected onto the studied area, which allows construction and visualization of a fine‐scale map of resistance based on spatial accumulation of positive or negative IBD residuals. In this study, we tested ResDisMapper with both simulated and empirical datasets and compared its performance with two other popular landscape genetic programs. Overall, we found that ResDisMapper can map resistance with relatively high accuracy. The latest version of the package and associated documentation are available on GitHub (https://github.com/takfung/ResDisMapper).

Metatranscriptomics is a powerful method for studying the composition and function of complex microbial communities. The application of metatranscriptomics to multispecies parasite infections is of particular interest, as research on parasite evolution and diversification has been hampered by technical challenges to genome‐scale DNA sequencing. In particular, blood parasites of vertebrates are abundant and diverse although they often occur at low infection intensities and exist as multispecies infections, rendering the isolation of genomic sequence data challenging. Here, we use birds and their diverse haemosporidian parasites to illustrate the potential for metatranscriptome sequencing to generate large quantities of genome‐wide sequence data from multiple blood parasite species simultaneously. We used RNA‐sequencing of 24 blood samples from songbirds in North America to show that metatranscriptomes can yield large proportions of haemosporidian protein‐coding gene repertoires even when infections are of low intensity (<0.1% red blood cells infected) and consist of multiple parasite taxa. By bioinformatically separating host and parasite transcripts and assigning them to the haemosporidian genus of origin, we found that transcriptomes detected ~23% more total parasite infections across all samples than were identified using microscopy and DNA barcoding. For single‐species infections, we obtained data for >1,300 loci from samples with as low as 0.03% parasitaemia, with the number of loci increasing with infection intensity. In total, we provide data for 1,502 single‐copy orthologous loci from a phylogenetically diverse set of 33 haemosporidian mitochondrial lineages. The metatranscriptomic approach described here has the potential to accelerate ecological and evolutionary research on haemosporidians and other diverse parasites.

Molecular Ecology Resources publishes broad resources to enhance studies in evolution, ecology, and conservation. The journal consistently ranks high among journals in Ecology and Evolutionary Biology, with an h5‐index of 64 and Impact Factor of 7.06 for the current year. The journal aims to publish high quality resources for broad use in the community including computer programs, statistical and methodological advances, and extensive molecular tools. Standards for manuscripts reflect advances across multiple fields and we encourage authors to review guidelines prior to submitting manuscripts to Molecular Ecology Resources since previous content may not reflect current standards.

Museum genomics has transformed the field of collections‐based research, opening up a range of new research directions for paleontological specimens as well as natural history specimens collected over the past few centuries. Recent work demonstrates that it is possible to characterize epigenetic markers such as DNA methylation in well preserved ancient tissues. This approach has not yet been tested in traditionally prepared natural history specimens such as dried bones and skins, the most common specimen types in vertebrate collections. In this study, we developed and tested methods to characterize cytosine methylation in dried skulls up to 76 years old. Using a combination of ddRAD and bisulphite treatment, we characterized patterns of cytosine methylation in two species of deer mouse (Peromyscus spp.) collected in the same region in Michigan in 1940, 2003, and 2013–2016. We successfully estimated methylation in specimens of all age groups, although older specimens yielded less data and showed greater interindividual variation in data yield than newer specimens. Global methylation estimates were reduced in the oldest specimens (76 years old) relative to the newest specimens (1–3 years old), which may reflect post‐mortem hydrolytic deamination. Methylation was reduced in promoter regions relative to gene bodies and showed greater bimodality in autosomes relative to female X chromosomes, consistent with expectations for methylation in mammalian somatic cells. Our work demonstrates the utility of historic specimens for methylation analyses, as with genomic analyses; however, studies will need to accommodate the large variance in the quantity of data produced by older specimens.

High‐throughput sequencing of amplicons from environmental DNA samples permits rapid, standardized and comprehensive biodiversity assessments. However, retrieving and interpreting the structure of such data sets requires efficient methods for dimensionality reduction. Latent Dirichlet Allocation (LDA) can be used to decompose environmental DNA samples into overlapping assemblages of co‐occurring taxa. It is a flexible model‐based method adapted to uneven sample sizes and to large and sparse data sets. Here, we compare LDA performance on abundance and occurrence data, and we quantify the robustness of the LDA decomposition by measuring its stability with respect to the algorithm's initialization. We then apply LDA to a survey of 1,131 soil DNA samples that were collected in a 12‐ha plot of primary tropical forest and amplified using standard primers for bacteria, protists, fungi and metazoans. The analysis reveals that bacteria, protists and fungi exhibit a strong spatial structure, which matches the topographical features of the plot, while metazoans do not, confirming that microbial diversity is primarily controlled by environmental variation at the studied scale. We conclude that LDA is a sensitive, robust and computationally efficient method to detect and interpret the structure of large DNA‐based biodiversity data sets. We finally discuss the possible future applications of this approach for the study of biodiversity.

The data used for profiling microbial communities is usually sparse with some microbes having high abundance in a few samples and being nearly absent in others. However, current bioinformatics tools able to deal with this sparsity are lacking. pime (Prevalence Interval for Microbiome Evaluation) was designed to remove those taxa that may be high in relative abundance in just a few samples but have a low prevalence overall. The reliability and robustness of pime were compared against existing methods and tested using 16S rRNA independent data sets. pime filters microbial taxa not shared in a per treatment prevalence interval started at 5% prevalence with increasing increments of 5% at each filtering step. For each prevalence interval, hundreds of decision trees were calculated to predict the likelihood of detecting differences in treatments. The best prevalence‐filtered data set was user‐selected by choosing the prevalence interval that kept a large portion of the 16S rRNA sequences in the data set while also showing the lowest error rate. To obtain the likelihood of introducing type I error while building prevalence‐filtered data sets, an error detection step based was also included. A pime reanalysis of published data sets uncovered other expected microbial associations than previously reported, which may be masked when only relative abundance was considered.

Plastic marine debris (PMD) affects spatial scales of life from microbes to whales. However, understanding interactions between plastic and microbes in the “Plastisphere”—the thin layer of life on the surface of PMD—has been technology‐limited. Research into microbe–microbe and microbe–substrate interactions requires knowledge of community phylogenetic composition but also tools to visualize spatial distributions of intact microbial biofilm communities. We developed a CLASI‐FISH (combinatorial labelling and spectral imaging – fluorescence in situ hybridization) method using confocal microscopy to study Plastisphere communities. We created a probe set consisting of three existing phylogenetic probes (targeting all Bacteria, Alpha‐, and Gammaproteobacteria) and four newly designed probes (targeting Bacteroidetes, Vibrionaceae, Rhodobacteraceae and Alteromonadaceae) labelled with a total of seven fluorophores and validated this probe set using pure cultures. Our nested probe set strategy increases confidence in taxonomic identification because targets are confirmed with two or more probes, reducing false positives. We simultaneously identified and visualized these taxa and their spatial distribution within the microbial biofilms on polyethylene samples in colonization time series experiments in coastal environments from three different biogeographical regions. Comparing the relative abundance of 16S rRNA gene amplicon sequencing data with cell‐count abundance data retrieved from the microscope images of the same samples showed a good agreement in bacterial composition. Microbial communities were heterogeneous, with direct spatial relationships between bacteria, cyanobacteria and eukaryotes such as diatoms but also micro‐metazoa. Our research provides a valuable resource to investigate biofilm development, succession and associations between specific microscopic taxa at micrometre scales.

Ribosomal RNA genes have long been a favoured locus in phylogenetic and metabarcoding studies. Within a genome, rRNA loci are organized as tandem repeated arrays and the copies are homogenized through the process of concerted evolution. However, some level of rRNA variation (intragenomic polymorphism) is known to persist and be maintained in the genomes of many species. In nematode worms, the extent of rRNA polymorphism (RP) across species and the evolutionary and life history factors that contribute to the maintenance of intragenomic RP is largely unknown. Here, we present an extensive analysis across 30 terrestrial nematode species representing a range of free‐living and parasitic taxa isolated worldwide. Our results indicate that RP is common and widespread, ribosome function appears to be maintained despite mutational changes, and intragenomic variants are stable in the genome and neutrally evolving. However, levels of variation were varied widely across rRNA locus and species, with some taxa observed to lack RP entirely. Higher levels of RP were significantly correlated with shorter generation time and high reproductive rates, and population‐level factors may play a role in the geographic and phylogenetic structuring of rRNA variants observed in genera such as Rotylenchulus and Pratylenchus. Although RP did not dramatically impact the clustering and recovery of taxa in mock metabarcoding analyses, the present study has significant implications for global biodiversity estimates of nematode species derived from environmental rRNA amplicon studies, as well as our understanding of the evolutionary and ecological factors shaping genetic diversity across the nematode Tree of Life.

High‐throughput DNA metabarcoding of amplicon sizes below 500 bp has revolutionized the analysis of environmental microbial diversity. However, these short regions contain limited phylogenetic signal, which makes it impractical to use environmental DNA in full phylogenetic inferences. This lesser phylogenetic resolution of short amplicons may be overcome by new long‐read sequencing technologies. To test this idea, we amplified soil DNA and used PacBio Circular Consensus Sequencing (CCS) to obtain an ~4500‐bp region spanning most of the eukaryotic small subunit (18S) and large subunit (28S) ribosomal DNA genes. We first treated the CCS reads with a novel curation workflow, generating 650 high‐quality operational taxonomic units (OTUs) containing the physically linked 18S and 28S regions. To assign taxonomy to these OTUs, we developed a phylogeny‐aware approach based on the 18S region that showed greater accuracy and sensitivity than similarity‐based methods. The taxonomically annotated OTUs were then combined with available 18S and 28S reference sequences to infer a well‐resolved phylogeny spanning all major groups of eukaryotes, allowing us to accurately derive the evolutionary origin of environmental diversity. A total of 1,019 sequences were included, of which a majority (58%) corresponded to the new long environmental OTUs. The long reads also allowed us to directly investigate the relationships among environmental sequences themselves, which represents a key advantage over the placement of short reads on a reference phylogeny. Together, our results show that long amplicons can be treated in a full phylogenetic framework to provide greater taxonomic resolution and a robust evolutionary perspective to environmental DNA.

Environmental DNA (eDNA) sampling, the detection of species‐specific genetic material in water samples, is an emerging tool for monitoring aquatic invasive species. Optimizing eDNA sampling protocols can be challenging because there is imperfect understanding of how each step of the protocol influences its sensitivity. This paper develops a probabilistic model that characterizes each step of an eDNA sampling protocol to evaluate the protocol's overall detection sensitivity for one sample. The model is then applied to analyse how changes over time made to the eDNA sampling protocol to detect bighead (BH) and silver carp (SC) eDNA have influenced its sensitivity, and hence interpretation of the results. The model shows that changes to the protocol have caused the sensitivity of the protocol to fluctuate. A more efficient extraction method in 2013, new species‐specific markers with a qPCR assay in 2014, and a more efficient capture method in 2015 have improved the sensitivity, while switching to a larger elution volume in 2013 and a smaller sample volume in 2015 have reduced the sensitivity. Overall, the sensitivity of the current protocol is higher for BH eDNA detection and SC eDNA detection compared to the original protocol used from 2009 to 2012. The paper shows how this model of eDNA sampling can be used to evaluate the effect of proposed changes in an eDNA sampling and analysis protocol on the sensitivity of that protocol to help researchers optimize their design.

Advances in DNA sequencing have made it feasible to gather genomic data for non‐model organisms and large sets of individuals, often using methods for sequencing subsets of the genome. Several of these methods sequence DNA associated with endonuclease restriction sites (various RAD and GBS methods). For use in taxa without a reference genome, these methods rely on de novo assembly of fragments in the sequencing library. Many of the software options available for this application were originally developed for other assembly types and we do not know their accuracy for reduced representation libraries. To address this important knowledge gap, we simulated data from the Arabidopsis thaliana and Homo sapiens genomes and compared de novo assemblies by six software programs that are commonly used or promising for this purpose (ABySS, CD‐HIT, Stacks, Stacks2, Velvet and VSEARCH). We simulated different mutation rates and types of mutations, and then applied the six assemblers to the simulated data sets, varying assembly parameters. We found substantial variation in software performance across simulations and parameter settings. ABySS failed to recover any true genome fragments, and Velvet and VSEARCH performed poorly for most simulations. Stacks and Stacks2 produced accurate assemblies of simulations containing SNPs, but the addition of insertion and deletion mutations decreased their performance. CD‐HIT was the only assembler that consistently recovered a high proportion of true genome fragments. Here, we demonstrate the substantial difference in the accuracy of assemblies from different software programs and the importance of comparing assemblies that result from different parameter settings.

We have compiled a database of functional traits for two widespread and ecologically important groups of protists, Cercozoa and Endomyxa (Rhizaria). The functional traits of microorganisms are crucially important for interpreting results from environmental sequencing surveys. Linking morphological and ecological traits to environmental factors is common practice in studies involving micro‐ and macroorganisms, but is rarely applied to protists. Our database provides functional and ecologically significant traits linked to morphology, nutrition, locomotion and habitats. We discuss how the use of functional traits may help to unveil underlying ecosystem processes. This database is intended as a common reference for the molecular ecology community and will boost the understanding of ecosystem functions, especially those driven by biological interactions.

Age‐related changes in DNA methylation do occur. Taking advantage of this, mammalian and avian epigenetic clocks have been constructed to predict age. In fish, studies on age‐related DNA methylation changes are scarce and no epigenetic clocks have been constructed. However, in fisheries and population dynamics studies there is a need for accurate estimation of age, something that is often impossible for some economically important species with the currently available methods. Here, we used the European sea bass, a marine fish the age of which can be determined with accuracy, to construct a piscine epigenetic clock, the first one in a cold‐blooded vertebrate. We used targeted bisulfite sequencing to amplify 48 CpGs from four genes in muscle samples and applied penalized regressions to predict age. We thus developed an age predictor in fish that is highly accurate (0.824) and precise (2.149 years). In juvenile fish, accelerated growth due to elevated temperatures had no effect on age prediction, indicating that the clock is able to predict the chronological age independently of environmentally‐driven perturbations. An epigenetic clock developed using muscle samples accurately predicted age in samples of testis but not ovaries, possibly reflecting the reproductive biology of fish. In conclusion, we report the development of the first piscine epigenetic clock, paving the way for similar studies in other species. Piscine epigenetic clocks should be of great utility for fisheries management and conservation purposes, where age determination is of crucial importance.

Comparability of findings from qPCR‐based telomere studies is hampered by such measurement results being assay‐specific, precluding a direct quantitative comparisons of observed differences and/or slopes of associations between studies. It is proposed that this can be partially alleviated by expressing qPCR‐based telomere data as Z‐scores.

Reptiles and other nonmammalian vertebrates have transcriptionally active nucleated red blood cells. If blood transcriptomes can provide quantitative data to address questions relevant to molecular ecology, this could circumvent the need to euthanize animals to assay tissues. This would allow longitudinal sampling of animals’ responses to treatments, as well as sampling of protected taxa. We developed and annotated blood transcriptomes from six reptile species and found on average 25,000 proteins are being transcribed in the blood, and there is a CORE group of 9,282 orthogroups that are found in at least four of six species. In comparison to liver transcriptomes from the same taxa, approximately two‐thirds of the orthogroups were found in both blood and liver; and a similar percentage of ecologically relevant gene groups (insulin and insulin‐like signalling, electron transport chain, oxidative stress, glucocorticoid receptors) were found transcribed in both blood and liver. As a resource, we provide a user‐friendly database of gene ids identified in each blood transcriptome. Although on average 37% of reads mapped to haemoglobin, importantly, the majority of nonhaemoglobin transcripts had sufficient depth (e.g., 97% at ≥10 reads) to be included in differential gene expression analysis. Thus, we demonstrate that RNAseq blood transcriptomes from a very small blood sample (<10 μl) is a minimally invasive option in nonmammalian vertebrates for quantifying expression of a large number of ecologically relevant genes that would allow longitudinal sampling and sampling of protected populations.

A broad body of literature has been published regarding roof-harvested rainwater quality around the world. In particular, the presence of fecal indicator bacteria and pathogenic microorganisms has raised concerns regarding the acceptability of rainwater for potable and non-potable uses. As the use of molecular assays has improved understanding of the diverse microbial communities present in rainwater tanks and their role in providing benefits or harm to human health, a comprehensive review is needed to summarize the state of the science in this area. To provide a summary of microbial contaminants in rainwater tanks and contextual factors, a comprehensive review was conducted here to elucidate the uses of rainwater, factors affecting water quality, concentrations of fecal indicators and pathogens, the attribution of pathogens to host sources using microbial source tracking, microbial ecology, human health risks determined using epidemiological approaches and quantitative microbial risk assessment, and treatment approaches for mitigating risks. Research gaps were identified for pathogen concentration data, microbial source tracking approaches for identifying the sources of microbial contamination, limitations to current approaches for assessing viability, treatment, and maintenance practices. Frameworks should be developed to assess and prioritize these factors in order to optimize public health promotion for roof-harvested rainwater.

The routine use of multiple water sources to meet household water needs is widely practiced and has been reported in many developing countries. However, it is typically neglected by implementers, development organizations, and researchers who tend to focus exclusively on the “main source of drinking water.” In this Perspective, we explain the nature and scope of multiple water source use (MWSU) at the household level in developing countries. We also describe the implications of MWSU for human health and water resilience, and identify key knowledge gaps, risks, and opportunities associated with MWSU. Finally, we argue that understanding MWSU is feasible for researchers and implementers and is essential for properly designing research studies and water supply projects.

In the original version of this Review Article the affiliation and address for Lorenzo Rosa were incorrectly given as “University of Parma, Department of Information Engineering, Parma 43121, Italy”.