Characterising the Tasmanian devil (Sarcophilus harrisii) pouch microbiome in lactating and non-lactating females.

Wildlife harbour a diverse range of microorganisms that affect their health and development. Marsupials are born immunologically naïve and physiologically underdeveloped, with primary development occurring inside a pouch. Secretion of immunological compounds and antimicrobial peptides in the epithelial lining of the female's pouch, pouch young skin, and through the milk, are thought to boost the neonate's immune system and potentially alter the pouch skin microbiome. Here, using 16S rRNA amplicon sequencing, we characterised the Tasmanian devil pouch skin microbiome from 25 lactating and 30 non-lactating wild females to describe and compare across these reproductive stages. We found that the lactating pouch skin microbiome had significantly lower amplicon sequence variant richness and diversity than non-lactating pouches, however there was no overall dissimilarity in community structure between lactating and non-lactating pouches. The top five phyla were found to be consistent between both reproductive stages, with over 85% of the microbiome being comprised of Firmicutes, Proteobacteria, Fusobacteriota, Actinobacteriota, and Bacteroidota. The most abundant taxa remained consistent across all taxonomic ranks between lactating and non-lactating pouch types. This suggests that any potential immunological compounds or antimicrobial peptide secretions did not significantly influence the main community members. Of the more than 16,000 total identified amplicon sequence variants, 25 were recognised as differentially abundant between lactating and non-lactating pouches. It is proposed that the secretion of antimicrobial peptides in the pouch act to modulate these microbial communities. This study identifies candidate bacterial clades on which to test the activity of Tasmanian devil antimicrobial peptides and their role in pouch young protection, which in turn may lead to future therapeutic development for human diseases.

The genome sequence of the critically endangered Kroombit tinkerfrog ( Taudactylus pleione).

The Kroombit tinkerfrog ( Taudactylus pleione) is a stream-dwelling amphibian of the Myobatrachidae family. It is listed as Critically Endangered and is at high risk of extinction due to chytridiomycosis. Here, we provide the first genome assembly of the evolutionarily distinct Taudactylus genus. We sequenced PacBio HiFi reads to assemble a high-quality long-read genome and identified the mitochondrial genome. We also generated a global transcriptome from a tadpole to improve gene annotation. The genome was 5.52 Gb in length and consisted of 4,196 contigs with a contig N50 of 8.853 Mb and an L50 of 153. This study provides the first genomic resources for the Kroombit tinkerfrog to assist in future phylogenetic, environmental DNA, conservation breeding, and disease susceptibility studies.

Koala Genome Survey: An Open Data Resource to Improve Conservation Planning.

Genome sequencing is a powerful tool that can inform the management of threatened species. Koalas (Phascolarctos cinereus) are a globally recognized species that captured the hearts and minds of the world during the 2019/2020 Australian megafires. In 2022, koalas were listed as 'Endangered' in Queensland, New South Wales, and the Australian Capital Territory. Populations have declined because of various threats such as land clearing, habitat fragmentation, and disease, all of which are exacerbated by climate change. Here, we present the Koala Genome Survey, an open data resource that was developed after the Australian megafires. A systematic review conducted in 2020 demonstrated that our understanding of genomic diversity within koala populations was scant, with only a handful of SNP studies conducted. Interrogating data showed that only 6 of 49 New South Wales areas of regional koala significance had meaningful genome-wide data, with only 7 locations in Queensland with SNP data and 4 locations in Victoria. In 2021, we launched the Koala Genome Survey to generate resequenced genomes across the Australian east coast. We have publicly released 430 koala genomes (average coverage: 32.25X, range: 11.3-66.8X) on the Amazon Web Services Open Data platform to accelerate research that can inform current and future conservation planning.

Restoring faith in conservation action: Maintaining wild genetic diversity through the Tasmanian devil insurance program.

Conservation breeding programs aim to maintain 90% wild genetic diversity, but rarely assess functional diversity. Here, we compare both genome-wide and functional diversity (in over 500 genes) of Tasmanian devils (Sarcophilus harrisii) within the insurance metapopulation and across the species' range (64,519 km2). Populations have declined by 80% since 1996 due to a contagious cancer, devil facial tumor disease (DFTD). However, predicted local extinctions have not occurred. Recent suggestions of selection for "resistance" alleles in the wild precipitated concerns that insurance population devils may be unsuitable for translocations. Using 830 wild samples collected at 31 locations between 2012 and 2021, and 553 insurance metapopulation devils, we show that the insurance metapopulation is representative of current wild genetic diversity. Allele frequencies at DFTD-associated loci were not substantially different between captive and wild devils. Methods presented here are valuable for others investigating evolutionary potential in threatened species, particularly ones under significant selective pressures.

DNA metabarcoding reveals a broad dietary range for Tasmanian devils introduced to a naive ecosystem.

Top carnivores are essential for maintaining ecosystem stability and biodiversity. Yet, carnivores are declining globally and current in situ threat mitigations cannot halt population declines. As such, translocations of carnivores to historic sites or those outside the species' native range are becoming increasingly common. As carnivores are likely to impact herbivore and small predator populations, understanding how carnivores interact within an ecosystem following translocation is necessary to inform potential remedial management and future translocations. Dietary analyses provide a preliminary assessment of the direct influence of translocated carnivores on a recipient ecosystem. We used a metabarcoding approach to quantify the diet of Tasmanian devils introduced to Maria Island, Tasmania, a site outside the species' native range. We extracted DNA from 96 scats and used a universal primer set targeting the vertebrate 12S rRNA gene to identify diet items. Tasmanian devils on Maria Island had an eclectic diet, with 63 consumed taxa identified. Cat DNA was detected in 14% of scats, providing the first instance of cats appearing as part of Tasmanian devil diets either via predation or scavenging. Short-tail shearwaters and little penguins were commonly consumed, corresponding with previous surveys showing sharp population declines in these species since the introduction of Tasmanian devils. Our results indicate that the introduction of carnivores to novel ecosystems can be very successful for the focal species, but that commonly consumed species should be closely monitored to identify any vulnerable species in need of remedial management.

How much is enough? Sampling intensity influences estimates of reproductive variance in an introduced population.

Conservation introductions to islands and fenced enclosures are increasing as in situ mitigations fail to keep pace with population declines. Few studies consider the potential loss of genetic diversity and increased inbreeding if released individuals breed disproportionately. As funding is limited and post-release monitoring expensive for conservation programs, understanding how sampling effort influences estimates of reproductive variance is useful. To investigate this relationship, we used a well-studied population of Tasmanian devils (Sarcophilus harrisii) introduced to Maria Island, Tasmania, Australia. Pedigree reconstruction based on molecular data revealed high variance in number of offspring per breeder and high proportions of unsuccessful individuals. Computational subsampling of 20%, 40%, 60%, and 80% of observed offspring resulted in inaccurate estimates of reproductive variance compared to the pedigree reconstructed with all sampled individuals. With decreased sampling effort, the proportion of inferred unsuccessful individuals was overestimated and the variance in number of offspring per breeder was underestimated. To accurately estimate reproductive variance, we recommend sampling as many individuals as logistically possible during the early stages of population establishment. Further, we recommend careful selection of colonizing individuals as they may be disproportionately represented in subsequent generations. Within the conservation management context, our results highlight important considerations for sample collection and post-release monitoring during population establishment.

A demonstration of conservation genomics for threatened species management.

As species extinction rates increase, genomics provides a powerful tool to support intensive management of threatened species. We use the Tasmanian devil (Sarcophilus harrisii) to demonstrate how conservation genomics can be implemented in threatened species management. We conducted whole genome sequencing (WGS) of 25 individuals from the captive breeding programme and reduced-representation sequencing (RRS) of 98 founders of the same programme. A subset of the WGS samples was also sequenced by RRS, allowing us to directly compare genome-wide heterozygosity with estimates from RRS data. We found good congruence in interindividual variation and gene-ontology classifications between the two data sets, indicating that our RRS data reflect the genome well. We also attempted genome-wide association studies with both data sets (regarding breeding success), but the genomic data suffered from small sample size, while the RRS data suffered from lack of precision, highlighting a key trade-off in the design of conservation genomic research. Nevertheless, we identified a number of candidate genes that may be associated with variation in breeding success. Individual heterozygosity, as measured by WGS or RRS, was not associated with breeding success in captivity but was negatively associated with litter sizes of breeding females in the RRS data set. Our findings enable conservation managers to have confidence in RRS data while understanding its limitations, and provide avenues for further investigation into which processes underlie variation in breeding success in captive Tasmanian devils. We caution, however, that deep functional insights using RRS may be impaired by a lack of precision, especially when marker density is low.

From reference genomes to population genomics: comparing three reference-aligned reduced-representation sequencing pipelines in two wildlife species.

BACKGROUND: Recent advances in genomics have greatly increased research opportunities for non-model species. For wildlife, a growing availability of reference genomes means that population genetics is no longer restricted to a small set of anonymous loci. When used in conjunction with a reference genome, reduced-representation sequencing (RRS) provides a cost-effective method for obtaining reliable diversity information for population genetics. Many software tools have been developed to process RRS data, though few studies of non-model species incorporate genome alignment in calling loci. A commonly-used RRS analysis pipeline, Stacks, has this capacity and so it is timely to compare its utility with existing software originally designed for alignment and analysis of whole genome sequencing data. Here we examine population genetic inferences from two species for which reference-aligned reduced-representation data have been collected. Our two study species are a threatened Australian marsupial (Tasmanian devil Sarcophilus harrisii; declining population) and an Arctic-circle migrant bird (pink-footed goose Anser brachyrhynchus; expanding population). Analyses of these data are compared using Stacks versus two widely-used genomics packages, SAMtools and GATK. We also introduce a custom R script to improve the reliability of single nucleotide polymorphism (SNP) calls in all pipelines and conduct population genetic inferences for non-model species with reference genomes. RESULTS: Although we identified orders of magnitude fewer SNPs in our devil dataset than for goose, we found remarkable symmetry between the two species in our assessment of software performance. For both datasets, all three methods were able to delineate population structure, even with varying numbers of loci. For both species, population structure inferences were influenced by the percent of missing data. CONCLUSIONS: For studies of non-model species with a reference genome, we recommend combining Stacks output with further filtering (as included in our R pipeline) for population genetic studies, paying particular attention to potential impact of missing data thresholds. We recognise SAMtools as a viable alternative for researchers more familiar with this software. We caution against the use of GATK in studies with limited computational resources or time.

Complex problems need detailed solutions: Harnessing multiple data types to inform genetic management in the wild.

For bottlenecked populations of threatened species, supplementation often leads to improved population metrics (genetic rescue), provided that guidelines can be followed to avoid negative outcomes. In cases where no "ideal" source populations exist, or there are other complicating factors such as prevailing disease, the benefit of supplementation becomes uncertain. Bringing multiple data and analysis types together to plan genetic management activities can help. Here, we consider three populations of Tasmanian devil, Sarcophilus harrisii, as candidates for genetic rescue. Since 1996, devil populations have been severely impacted by devil facial tumour disease (DFTD), causing significant population decline and fragmentation. Like many threatened species, the key threatening process for devils cannot currently be fully mitigated, so species management requires a multifaceted approach. We examined diversity of 31 putatively neutral and 11 MHC-linked microsatellite loci of three remnant wild devil populations (one sampled at two time-points), alongside computational diversity projections, parameterized by field data from DFTD-present and DFTD-absent sites. Results showed that populations had low diversity, connectivity was poor, and diversity has likely decreased over the last decade. Stochastic simulations projected further diversity losses. For a given population size, the effects of DFTD on population demography (including earlier age at death and increased female productivity) did not impact diversity retention, which was largely driven by final population size. Population sizes ≥500 (depending on the number of founders) were necessary for maintaining diversity in otherwise unmanaged populations, even if DFTD is present. Models indicated that smaller populations could maintain diversity with ongoing immigration. Taken together, our results illustrate how multiple analysis types can be combined to address complex population genetic challenges.

Too much of a good thing? Finding the most informative genetic data set to answer conservation questions.

Molecular markers are a useful tool allowing conservation and population managers to shed light on genetic processes affecting threatened populations. However, as technological advancements in molecular techniques continue to evolve, conservationists are frequently faced with new genetic markers, each with nuanced variation in their characteristics as well as advantages and disadvantages for informing various questions. We used a well-studied population of Tasmanian devils (Sarcophilus harrisii) from Maria Island, Tasmania, to illustrate the issues associated with combining multiple genetic data sets and to help answer a question posed by many population managers: which data set will provide the most precise and accurate estimates of the population processes we are trying to measure? We analysed individual heterozygosity (as internal relatedness, IR) of 96 individuals, calculated using four genetic marker types (putatively neutral microsatellites, major histocompatibility complex-linked microsatellites, reduced representation sequencing, and candidate region resequencing). We found no correlation in IR values across marker types, suggesting that various genetic markers reflect different aspects of genomic diversity. In addition, some marker types were more informative than others for conservation decision-making. Reduced representation sequencing provided the highest precision (lowest error) for estimating population-level genetic diversity, and most closely reflected genome-wide heterozygosity both theoretically and empirically. Within the conservation context, our results highlight important considerations when choosing a molecular technique for wildlife genetics.

Immunization Strategies Producing a Humoral IgG Immune Response against Devil Facial Tumor Disease in the Majority of Tasmanian Devils Destined for Wild Release.

Devil facial tumor disease (DFTD) is renowned for its successful evasion of the host immune system. Down regulation of the major histocompatabilty complex class I molecule (MHC-I) on the DFTD cells is a primary mechanism of immune escape. Immunization trials on captive Tasmanian devils have previously demonstrated that an immune response against DFTD can be induced, and that immune-mediated tumor regression can occur. However, these trials were limited by their small sample sizes. Here, we describe the results of two DFTD immunization trials on cohorts of devils prior to their wild release as part of the Tasmanian Government's Wild Devil Recovery project. 95% of the devils developed anti-DFTD antibody responses. Given the relatively large sample sizes of the trials (N = 19 and N = 33), these responses are likely to reflect those of the general devil population. DFTD cells manipulated to express MHC-I were used as the antigenic basis of the immunizations in both trials. Although the adjuvant composition and number of immunizations differed between trials, similar anti-DFTD antibody levels were obtained. The first trial comprised DFTD cells and the adjuvant combination of ISCOMATRIX™, polyIC, and CpG with up to four immunizations given at monthly intervals. This compared to the second trial whereby two immunizations comprising DFTD cells and the adjuvant combination ISCOMATRIX™, polyICLC (Hiltonol®) and imiquimod were given a month apart, providing a shorter and, therefore, more practical protocol. Both trials incorporated a booster immunization given up to 5 months after the primary course. A key finding was that devils in the second trial responded more quickly and maintained their antibody levels for longer compared to devils in the first trial. The different adjuvant combination incorporating the RNAase resistant polyICLC and imiquimod used in the second trial is likely to be responsible. The seroconversion in the majority of devils in these anti-DFTD immunization trials was remarkable, especially as DFTD is hallmarked by its immune evasion mechanisms. Microsatellite analyzes of MHC revealed that some MHC-I microsatellites correlated to stronger immune responses. These trials signify the first step in the long-term objective of releasing devils with immunity to DFTD into the wild.