TICI: a taxon-independent community index for eDNA-based ecological health assessment.

Global biodiversity is declining at an ever-increasing rate. Yet effective policies to mitigate or reverse these declines require ecosystem condition data that are rarely available. Morphology-based bioassessment methods are difficult to scale, limited in scope, suffer prohibitive costs, require skilled taxonomists, and can be applied inconsistently between practitioners. Environmental DNA (eDNA) metabarcoding offers a powerful, reproducible and scalable solution that can survey across the tree-of-life with relatively low cost and minimal expertise for sample collection. However, there remains a need to condense the complex, multidimensional community information into simple, interpretable metrics of ecological health for environmental management purposes. We developed a riverine taxon-independent community index (TICI) that objectively assigns indicator values to amplicon sequence variants (ASVs), and significantly improves the statistical power and utility of eDNA-based bioassessments. The TICI model training step uses the Chessman iterative learning algorithm to assign health indicator scores to a large number of ASVs that are commonly encountered across a wide geographic range. New sites can then be evaluated for ecological health by averaging the indicator value of the ASVs present at the site. We trained a TICI model on an eDNA dataset from 53 well-studied riverine monitoring sites across New Zealand, each sampled with a high level of biological replication (n = 16). Eight short-amplicon metabarcoding assays were used to generate data from a broad taxonomic range, including bacteria, microeukaryotes, fungi, plants, and animals. Site-specific TICI scores were strongly correlated with historical stream condition scores from macroinvertebrate assessments (macroinvertebrate community index or MCI; R2 = 0.82), and TICI variation between sample replicates was minimal (CV = 0.013). Taken together, this demonstrates the potential for taxon-independent eDNA analysis to provide a reliable, robust and low-cost assessment of ecological health that is accessible to environmental managers, decision makers, and the wider community.

A genomic predictor for age at sexual maturity for mammalian species.

Age at sexual maturity is a key life history trait that can be used to predict population growth rates and develop life history models. In many wild animal species, the age at sexual maturity is not accurately quantified. This results in a reduced ability to accurately model demography of wild populations. Recent studies have indicated the potential for CpG density within gene promoters to be predictive of other life history traits, specifically maximum lifespan. Here, we have developed a machine learning model using gene promoter CpG density to predict the mean age at sexual maturity in mammalian species. In total, 91 genomes were used to identify 101 unique gene promoters predictive of age at sexual maturity across males and females. We found these gene promoters to be most predictive of age at sexual maturity in females (R 2 = 0.881) compared to males (R 2 = 0.758). The median absolute error rate was also found to be lower in females (0.427 years) compared to males (0.785 years). This model provides a novel method for species-level age at sexual maturity prediction without the need for long-term monitoring. This study also highlights a potential epigenetic mechanism for the onset of sexual maturity, indicating the possibility of using epigenetic biomarkers for this important life history trait.

Calibrating epigenetic clocks with training data error.

Animal age data are valuable for management of wildlife populations. Yet, for most species, there is no practical method for determining the age of unknown individuals. However, epigenetic clocks, a molecular-based method, are capable of age prediction by sampling specific tissue types and measuring DNA methylation levels at specific loci. Developing an epigenetic clock requires a large number of samples from animals of known ages. For most species, there are no individuals whose exact ages are known, making epigenetic clock calibration inaccurate or impossible. For many epigenetic clocks, calibration samples with inaccurate age estimates introduce a degree of error to epigenetic clock calibration. In this study, we investigated how much error in the training data set of an epigenetic clock can be tolerated before it resulted in an unacceptable increase in error for age prediction. Using four publicly available data sets, we artificially increased the training data age error by iterations of 1% and then tested the model against an independent set of known ages. A small effect size increase (Cohen's d >0.2) was detected when the error in age was higher than 22%. The effect size increased linearly with age error. This threshold was independent of sample size. Downstream applications for age data may have a more important role in deciding how much error can be tolerated for age prediction. If highly precise age estimates are required, then it may be futile to embark on the development of an epigenetic clock when there is no accurately aged calibration population to work with. However, for other problems, such as determining the relative age order of pairs of individuals, a lower-quality calibration data set may be adequate.

The enormous repetitive Antarctic krill genome reveals environmental adaptations and population insights.

Antarctic krill (Euphausia superba) is Earth's most abundant wild animal, and its enormous biomass is vital to the Southern Ocean ecosystem. Here, we report a 48.01-Gb chromosome-level Antarctic krill genome, whose large genome size appears to have resulted from inter-genic transposable element expansions. Our assembly reveals the molecular architecture of the Antarctic krill circadian clock and uncovers expanded gene families associated with molting and energy metabolism, providing insights into adaptations to the cold and highly seasonal Antarctic environment. Population-level genome re-sequencing from four geographical sites around the Antarctic continent reveals no clear population structure but highlights natural selection associated with environmental variables. An apparent drastic reduction in krill population size 10 mya and a subsequent rebound 100 thousand years ago coincides with climate change events. Our findings uncover the genomic basis of Antarctic krill adaptations to the Southern Ocean and provide valuable resources for future Antarctic research.

Fish species lifespan prediction from promoter cytosine-phosphate-guanine density.

Lifespan is a key attribute of a species' life cycle and varies extensively among major lineages of animals. In fish, lifespan varies by several orders of magnitude, with reported values ranging from less than 1 year to approximately 400 years. Lifespan information is particularly useful for species management, as it can be used to estimate invasion potential, extinction risk and sustainable harvest rates. Despite its utility, lifespan is unknown for most fish species. This is due to the difficulties associated with accurately identifying the oldest individual(s) of a given species, and/or deriving lifespan estimates that are representative for an entire species. Recently it has been shown that CpG density in gene promoter regions can be used to predict lifespan in mammals and other vertebrates, with variable accuracy across taxa. To improve accuracy of lifespan prediction in a non-mammalian vertebrate group, here we develop a fish-specific genomic lifespan predictor. Our new model includes more than eight times the number of fish species included in the previous vertebrate model (n = 442) and uses fish-specific gene promoters as reference sequences. The model predicts fish lifespan from genomic CpG density alone (measured as CpG observed/expected ratio), explaining 64% of the variance between known and predicted lifespans. The predictions are highly robust to variation in genome quality and are applicable to all classes of fish; a taxonomically diverse and speciose group. The results demonstrate the value of promoter CpG density as a universal predictor of fish lifespan that can applied where empirical data are unavailable, or impracticable to obtain.

A review of applications of environmental DNA for reptile conservation and management.

Reptile populations are in decline globally, with total reptile abundance halving in the past half century, and approximately a fifth of species currently threatened with extinction. Research on reptile distributions, population trends, and trophic interactions can greatly improve the accuracy of conservation listings and planning for species recovery, but data deficiency is an impediment for many species. Environmental DNA (eDNA) can detect species and measure community diversity at diverse spatio-temporal scales, and is especially useful for detection of elusive, cryptic, or rare species, making it potentially very valuable in herpetology. We aim to summarize the utility of eDNA as a tool for informing reptile conservation and management and discuss the benefits and limitations of this approach. A literature review was conducted to collect all studies that used eDNA and focus on reptile ecology, conservation, or management. Results of the literature search are summarized into key discussion points, and the review also draws on eDNA studies from other taxa to highlight methodological challenges and to identify future research directions. eDNA has had limited application to reptiles, relative to other vertebrate groups, and little use in regions with high species richness. eDNA techniques have been more successfully applied to aquatic reptiles than to terrestrial reptiles, and most (64%) of studies focused on aquatic habitats. Two of the four reptilian orders dominate the existing eDNA studies (56% Testudines, 49% Squamata, 5% Crocodilia, 0% Rhynchocephalia). Our review provides direction for the application of eDNA as an emerging tool in reptile ecology and conservation, especially when it can be paired with traditional monitoring approaches. Technologies associated with eDNA are rapidly advancing, and as techniques become more sensitive and accessible, we expect eDNA will be increasingly valuable for addressing key knowledge gaps for reptiles.

Comparison of materials for rapid passive collection of environmental DNA.

Passive collection is an emerging sampling method for environmental DNA (eDNA) in aquatic systems. Passive eDNA collection is inexpensive and efficient, and requires minimal equipment, making it suited to high-density sampling and remote deployment. Here, we compare the effectiveness of nine membrane materials for passively collecting fish eDNA from a 3-million-litre marine mesocosm. We submerged materials (cellulose, cellulose with 1% and 3% chitosan, cellulose overlayed with electrospun nanofibres and 1% chitosan, cotton fibres, hemp fibres, and sponge with either zeolite or active carbon) for intervals between 5 and 1080 min. We show that for most materials, with as little as 5 min of submersion, mitochondrial fish eDNA measured with qPCR, and fish species richness measured with metabarcoding, was comparable to that collected by conventional filtering. Furthermore, PCR template DNA concentrations and species richness were generally not improved significantly by longer submersion. Species richness detected for all materials ranged between 11 and 37 species, with a median of 27, which was comparable to the range for filtered eDNA (19-32). Using scanning electron microscopy, we visualized biological matter adhering to the surface of materials, rather than entrapped, with images also revealing a diversity in size and structure of putative eDNA particles. eDNA can be collected rapidly from seawater with a passive approach and using a variety of materials. This will suit cost- and time-sensitive biological surveys, and where access to equipment is limited.

Age prediction of green turtles with an epigenetic clock.

Age is a fundamental life history attribute that is used to understand the dynamics of wild animal populations. Unfortunately, most animals do not have a practical or nonlethal method to determine age. This makes it difficult for wildlife managers to carry out population assessments, particularly for elusive and long-lived fauna such as marine turtles. In this study, we present an epigenetic clock that predicts the age of marine turtles from skin biopsies. The model was developed and validated using DNA from known-age green turtles (Chelonia mydas) from two captive populations, and mark-recapture wild turtles with known time intervals between captures. Our method, based on DNA methylation levels at 18 CpG sites, was highly accurate with a median absolute error of 2.1 years (4.7% of maximum age in data set). This is the first epigenetic clock developed for a reptile and illustrates their broad applicability across a broad variety of vertebrate species. It has the potential to transform marine turtle management through a nonlethal and inexpensive method to provide key life history information.

Individual haplotyping of whale sharks from seawater environmental DNA.

Population genetic data can provide valuable information on the demography of a species. For rare and elusive marine megafauna, samples for generating the data are traditionally obtained from tissue biopsies, which can be logistically difficult and expensive to collect and require invasive sampling techniques. Analysis of environmental DNA (eDNA) offers an alternative, minimally invasive approach to provide important genetic information. Although eDNA approaches have been studied extensively for species detection and biodiversity monitoring in metabarcoding studies, the potential for the technique to address population-level questions remains largely unexplored. Here, we applied "eDNA haplotyping" to obtain estimates of the intraspecific genetic diversity of a whale shark (Rhincodon typus) aggregation at Ningaloo reef, Australia. Over 2 weeks, we collected seawater samples directly behind individual sharks prior to taking a tissue biopsy sample from the same animal. Our data showed a 100% match between mtDNA sequences recovered in the eDNA and tissue sample for all 28 individuals sampled. In the seawater samples, >97% of all reads were assigned to six dominant haplotypes, and a clear dominant signal (~99% of sample reads) was recovered in each sample. Our study demonstrates accurate individual-level haplotyping from seawater eDNA. When DNA from one individual clearly dominates each eDNA sample, it provides many of the same opportunities for population genetic analyses as a tissue sample, potentially removing the need for tissue sampling. Our results show that eDNA approaches for population-level analyses have the potential to supply critical demographic data for the conservation and management of marine megafauna.

Nonlethal age estimation of three threatened fish species using DNA methylation: Australian lungfish, Murray cod and Mary River cod.

Age-based demography is fundamental to management of wild fish populations. Age estimates for individuals can determine rates of change in key life-history parameters such as length, maturity, mortality and fecundity. These age-based characteristics are critical for population viability analysis in endangered species and for developing sustainable harvest strategies. For teleost fish, age has traditionally been determined by counting increments formed in calcified structures such as otoliths. However, the collection of otoliths is lethal and therefore undesirable for threatened species. At a molecular level, age can be predicted by measuring DNA methylation. Here, we use previously identified age-associated sites of DNA methylation in zebrafish (Danio rerio) to develop two epigenetic clocks for three threatened freshwater fish species. One epigenetic clock was developed for the Australian lungfish (Neoceratodus forsteri) and the second for the Murray cod (Maccullochella peelii) and Mary River cod (Maccullochella mariensis). Age estimation models were calibrated using either known-age individuals, ages derived from otoliths or bomb radiocarbon dating of scales. We demonstrate a high Pearson's correlation between the chronological and predicted age in both the Lungfish clock (cor = .98) and Maccullochella clock (cor = .92). The median absolute error rate for both epigenetic clocks was also low (Lungfish = 0.86 years; Maccullochella = 0.34 years). This study demonstrates the transferability of DNA methylation sites for age prediction between highly phylogenetically divergent fish species. Given the method is nonlethal and suited to automation, age prediction by DNA methylation has the potential to improve fisheries and other wildlife management settings.

An epigenetic clock to estimate the age of living beluga whales.

DNA methylation data facilitate the development of accurate molecular estimators of chronological age or "epigenetic clocks." We present a robust epigenetic clock for the beluga whale, Delphinapterus leucas, developed for an endangered population in Cook Inlet, Alaska, USA. We used a custom methylation array to measure methylation levels at 37,491 cytosine-guanine sites (CpGs) from skin samples of dead whales (n = 67) whose chronological ages were estimated based on tooth growth layer groups. Using these calibration data, a penalized regression model selected 23 CpGs, providing an R 2 = 0.92 for the training data; and an R 2 = 0.74 and median absolute age error = 2.9 years for the leave one out cross-validation. We applied the epigenetic clock to an independent dataset of 38 skin samples collected with a biopsy dart from living whales between 2016 and 2018. Age estimates ranged from 11 to 27 years. We also report sex correlations in CpG data and describe an approach of identifying the sex of an animal using DNA methylation. The epigenetic estimators of age and sex presented here have broad applications for conservation and management of Cook Inlet beluga whales and potentially other cetaceans.

Optimal sample size for calibrating DNA methylation age estimators.

Age is a fundamental parameter in wildlife management as it is used to determine the risk of extinction, manage invasive species, and regulate sustainable harvest. In a broad variety of vertebrates species, age can be determined by measuring DNA methylation. Animals with known ages are initially required during development, calibration, and validation of these epigenetic clocks. However, wild animals with known ages are frequently difficult to obtain. Here, we perform Monte-Carlo simulations to determine the optimal sample size required to create an accurate calibration model for age estimation by elastic net regression modelling of cytosine-phosphate-guanine methylation data. Our results suggest a minimum calibration population size of 70, but ideally 134 individuals or more for accurate and precise models. We also provide estimates to the extent a model can be extrapolated beyond a distribution of ages that was used during calibration. The findings can assist researchers to better design age estimation models and decide if their model is adequate for determining key population attributes.

Passive eDNA collection enhances aquatic biodiversity analysis.

Environmental DNA (eDNA) metabarcoding is a sensitive and widely used approach for species detection and biodiversity assessment. The most common eDNA collection method in aquatic systems is actively filtering water through a membrane, which is time consuming and requires specialized equipment. Ecological studies investigating species abundance or distribution often require more samples than can be practically collected with current filtration methods. Here we demonstrate how eDNA can be passively collected in both tropical and temperate marine systems by directly submerging filter membranes (positively charged nylon and non-charged cellulose ester) in the water column. Using a universal fish metabarcoding assay, we show that passive eDNA collection can detect fish as effectively as active eDNA filtration methods in temperate systems and can also provide similar estimates of total fish biodiversity. Furthermore, passive eDNA collection enables greater levels of biological sampling, which increases the range of ecological questions that eDNA metabarcoding can address.

A DNA methylation age predictor for zebrafish.

Changes in DNA methylation at specific CpG sites have been used to build predictive models to estimate animal age, predominantly in mammals. Little testing for this effect has been conducted in other vertebrate groups, such as bony fish, the largest vertebrate class. The development of most age-predictive models has relied on a genome-wide sequencing method to obtain a DNA methylation level, which makes it costly to deploy as an assay to estimate age in many samples. Here, we have generated a reduced representation bisulfite sequencing data set of caudal fin tissue from a model fish species, zebrafish (Danio rerio), aged from 11.9-60.1 weeks. We identified changes in methylation at specific CpG sites that correlated strongly with increasing age. Using an optimised unique set of 26 CpG sites we developed a multiplex PCR assay that predicts age with an average median absolute error rate of 3.2 weeks in zebrafish between 10.9-78.1 weeks of age. We also demonstrate the use of multiplex PCR as an efficient quantitative approach to measure DNA methylation for the use of age estimation. This study highlights the potential further use of DNA methylation as an age estimation method in non-mammalian vertebrate species.

Lifespan estimation in marine turtles using genomic promoter CpG density.

Maximum lifespan for most animal species is difficult to define. This is challenging for wildlife management as it is critical for estimating important aspects of population biology such as mortality rate, population viability, and period of reproductive potential. Recently, it has been shown cytosine-phosphate-guanine (CpG) density is predictive of maximum lifespan in vertebrates. This has made it possible to predict lifespan in long-lived species, which are generally the most intractable. In this study, we use gene promoter CpG density to predict the lifespan of five marine turtle species. Marine turtles are a particularly difficult group for lifespan estimation because of their migratory behaviour, longevity and high juvenile mortality rates, which all restrict individual tracking over their lifespan. Sanger sequencing was used to determine the CpG density in selected promoters. We predicted the lifespans for marine turtle species ranged from 50.4 years (flatback turtle, Natator depressus) to 90.4 years (leatherback turtle, Dermochelys coriacea). These lifespan predictions have broad applications in marine turtle research such as better understanding life cycles and determining population viability.

Partitioning of diet between species and life history stages of sympatric and cryptic snappers (Lutjanidae) based on DNA metabarcoding.

Lutjanus erythropterus and L. malabaricus are sympatric, sister taxa that are important to fisheries throughout the Indo-Pacific. Their juveniles are morphologically indistinguishable (i.e. cryptic). A DNA metabarcoding dietary study was undertaken to assess the diet composition and partitioning between the juvenile and adult life history stages of these two lutjanids. Major prey taxa were comprised of teleosts and crustaceans for all groups except adult L. erythropterus, which instead consumed soft bodied invertebrates (e.g. tunicates, comb jellies and medusae) as well as teleosts, with crustaceans being notably absent. Diet composition was significantly different among life history stages and species, which may be associated with niche habitat partitioning or differences in mouth morphology within adult life stages. This study provides the first evidence of diet partitioning between cryptic juveniles of overlapping lutjanid species, thus providing new insights into the ecological interactions, habitat associations, and the specialised adaptations required for the coexistence of closely related species. This study has improved our understanding of the differential contributions of the juvenile and adult diets of these sympatric species within food webs. The diet partitioning reported in this study was only revealed by the taxonomic resolution provided by the DNA metabarcoding approach and highlights the potential utility of this method to refine the dietary components of reef fishes more generally.

Phylogenomic Resolution of the Cetacean Tree of Life Using Target Sequence Capture.

The evolution of cetaceans, from their early transition to an aquatic lifestyle to their subsequent diversification, has been the subject of numerous studies. However, although the higher-level relationships among cetacean families have been largely settled, several aspects of the systematics within these groups remain unresolved. Problematic clades include the oceanic dolphins (37 spp.), which have experienced a recent rapid radiation, and the beaked whales (22 spp.), which have not been investigated in detail using nuclear loci. The combined application of high-throughput sequencing with techniques that target specific genomic sequences provide a powerful means of rapidly generating large volumes of orthologous sequence data for use in phylogenomic studies. To elucidate the phylogenetic relationships within the Cetacea, we combined sequence capture with Illumina sequencing to generate data for $\sim $3200 protein-coding genes for 68 cetacean species and their close relatives including the pygmy hippopotamus. By combining data from $>$38,000 exons with existing sequences from 11 cetaceans and seven outgroup taxa, we produced the first comprehensive comparative genomic data set for cetaceans, spanning 6,527,596 aligned base pairs (bp) and 89 taxa. Phylogenetic trees reconstructed with maximum likelihood and Bayesian inference of concatenated loci, as well as with coalescence analyses of individual gene trees, produced mostly concordant and well-supported trees. Our results completely resolve the relationships among beaked whales as well as the contentious relationships among oceanic dolphins, especially the problematic subfamily Delphinidae. We carried out Bayesian estimation of species divergence times using MCMCTree and compared our complete data set to a subset of clocklike genes. Analyses using the complete data set consistently showed less variance in divergence times than the reduced data set. In addition, integration of new fossils (e.g., Mystacodon selenensis) indicates that the diversification of Crown Cetacea began before the Late Eocene and the divergence of Crown Delphinidae as early as the Middle Miocene. [Cetaceans; phylogenomics; Delphinidae; Ziphiidae; dolphins; whales.].

A genomic predictor of lifespan in vertebrates.

Biological ageing and its mechanistic underpinnings are of immense biomedical and ecological significance. Ageing involves the decline of diverse biological functions and places a limit on a species' maximum lifespan. Ageing is associated with epigenetic changes involving DNA methylation. Furthermore, an analysis of mammals showed that the density of CpG sites in gene promoters, which are targets for DNA methylation, is correlated with lifespan. Using 252 whole genomes and databases of animal age and promotor sequences, we show a pattern across vertebrates. We also derive a predictive lifespan clock based on CpG density in a selected set of promoters. The lifespan clock accurately predicts maximum lifespan in vertebrates (R2 = 0.76) from the density of CpG sites within only 42 selected promoters. Our lifespan clock provides a wholly new method for accurately estimating lifespan using genome sequences alone and enables estimation of this challenging parameter for both poorly understood and extinct species.

Advancing the integration of multi-marker metabarcoding data in dietary analysis of trophic generalists.

The application of DNA metabarcoding to dietary analysis of trophic generalists requires using multiple markers in order to overcome problems of primer specificity and bias. However, limited attention has been given to the integration of information from multiple markers, particularly when they partly overlap in the taxa amplified, and vary in taxonomic resolution and biases. Here, we test the use of a mix of universal and specific markers, provide criteria to integrate multi-marker metabarcoding data and a python script to implement such criteria and produce a single list of taxa ingested per sample. We then compare the results of dietary analysis based on morphological methods, single markers, and the proposed combination of multiple markers. The study was based on the analysis of 115 faeces from a small passerine, the Black Wheatears (Oenanthe leucura). Morphological analysis detected far fewer plant taxa (12) than either a universal 18S marker (57) or the plant trnL marker (124). This may partly reflect the detection of secondary ingestion by molecular methods. Morphological identification also detected far fewer taxa (23) than when using 18S (91) or the arthropod markers IN16STK (244) and ZBJ (231), though each method missed or underestimated some prey items. Integration of multi-marker data provided far more detailed dietary information than any single marker and estimated higher frequencies of occurrence of all taxa. Overall, our results show the value of integrating data from multiple, taxonomically overlapping markers in an example dietary data set.