Infectious diseases impact numerous organisms. Knowledge of host-pathogen interactions and host responses to infection is crucial for conservation and management. Obtaining this knowledge quickly is made increasingly possible by a variety of genomic approaches, yet, for many species the bottleneck to understanding this, remains access to appropriate samples and data. Lack of sample availability has also limited our understanding of how pathogens and the immune responses of hosts change over time. Archival materials may provide a way to explore pathogen emergence and host responses over multiple-possibly hundreds-of years. Here, we tested whether formalin-fixed paraffin-embedded (FFPE) tissue samples could be used to understand an unknown pathology, lamprey reddening syndrome (LRS), affecting pouched lampreys (Geotria australis). Our differential expression analyses of dermal tissues from four unaffected lampreys and eight affected lampreys collected in 2012 alluded to several potential agents associated with LRS. Interestingly, the pathways associated with viral infections were overrepresented in affected versus unaffected lamprey. Gene ontology analyses of the affected and non-affected lampreys also provided new insights into the largely understudied immune responses of pouched lampreys. Our work confirms that FFPE samples can be used to infer information about the transcriptional responses of a wildlife species affected by unknown historical pathologies/syndromes. In addition, the use of FFPE samples for transcriptomics offers many opportunities to investigate the genomic responses of a species to a variety of environmental changes. We conclude with a discussion about how to best sample and utilize these unique archival resources for future wildlife transcriptomic studies.

Molecular methods including metabarcoding and quantitative polymerase chain reaction have shown promise for estimating species abundance by quantifying the concentration of genetic material in field samples. However, the relationship between specimen abundance and detectable concentrations of genetic material is often variable in practice. DNA mixture analysis represents an alternative approach to quantify specimen abundance based on the presence of unique alleles in a sample. The DNA mixture approach provides novel opportunities to inform ecology and conservation by estimating the absolute abundance of target taxa through molecular methods; yet, the challenges associated with genotyping many highly variable markers in mixed-DNA samples have prevented its widespread use. To advance molecular approaches for abundance estimation, we explored the utility of microhaplotypes for DNA mixture analysis by applying a 125-marker panel to 1179 Chinook salmon (Oncorhynchus tshawytscha) smolts from the Sacramento-San Joaquin Delta, California, USA. We assessed the accuracy of DNA mixture analysis through a combination of mock mixtures containing DNA from up to 20 smolts and a trophic ecological application enumerating smolts in predator diets. Mock DNA mixtures of up to 10 smolts could reliably be resolved using microhaplotypes, and increasing the panel size would likely facilitate the identification of more individuals. However, while analysis of predator gastrointestinal tract contents indicated DNA mixture analysis could discern the presence of multiple prey items, poor and variable DNA quality prevented accurate genotyping and abundance estimation. Our results indicate that DNA mixture analysis can perform well with high-quality DNA, but methodological improvements in genotyping degraded DNA are necessary before this approach can be used on marginal-quality samples.

The negative genetic impacts of gene flow from domestic to wild populations can be dependent on the degree of domestication and exacerbated by the magnitude of pre-existing genetic differences between wild populations and the domestication source. Recent evidence of European ancestry within North American aquaculture Atlantic salmon (Salmo salar) has elevated the potential impact of escaped farmed salmon on often at-risk wild North American salmon populations. Here, we compare the ability of single nucleotide polymorphism (SNP) and microsatellite (SSR) marker panels of different sizes (7-SSR, 100-SSR and 220K-SNP) to detect introgression of European genetic information into North American wild and aquaculture populations. Linear regression comparing admixture predictions for a set of individuals common to the three datasets showed that the 100-SSR panel and 7-SSR panels replicated the full 220K-SNP-based admixture estimates with low accuracy (r2 of .64 and .49, respectively). Additional tests explored the effects of individual sample size and marker number, which revealed that ~300 randomly selected SNPs could replicate the 220K-SNP admixture predictions with greater than 95% fidelity. We designed a custom SNP panel (301-SNP) for European admixture detection in future monitoring work and then developed and tested a python package, salmoneuadmix (https://github.com/CNuge/SalmonEuAdmix), which uses a deep neural network to make de novo estimates of individuals' European admixture proportion without the need to conduct complete admixture analysis utilizing baseline samples. The results demonstrate the mobilization of targeted SNP panels and machine learning in support of at-risk species conservation and management.

Phytophthora agathidicida is a virulent soil pathogen of Aotearoa New Zealand's iconic kauri tree species (Agathis australis (D. Don) Lindl.) and the primary causal agent of kauri dieback disease. To date, only a few control options are available to treat infected kauri that are expressing symptoms of dieback disease. Previous research has identified strains of Penicillium and Burkholderia that inhibited the mycelial growth of P. agathidicida in vitro. However, the mechanisms of inhibition remain unknown. By performing whole genome sequencing, we screened the genomes of four Penicillium and five Burkholderia strains to identify secondary metabolite encoding biosynthetic gene clusters (SM-BGCs) that may be implicated in the production of antimicrobial compounds. We identified various types of SM-BGCs in the genome of each strain, including polyketide synthases (PKSs), non-ribosomal peptide synthetases (NRPSs), and terpenes. Across all four of the Penicillium strains, five SM-BGCs were detected that encoded the biosynthesis of napthopyrone, clavaric acid, pyranonigrin E, dimethyl coprogen and asperlactone. Across all five of the Burkholderia strains, three SM-BGCs were detected that encoded the biosynthesis of ornibactin, pyochelin and pyrrolnitin. Our analysis detected numerous SM-BGCs which could not be characterised. Further efforts should be made to identify the compounds encoded by these SM-BGCs so that we can explore their antimicrobial potential. The potential inhibitory effects of the compounds encoded by the SM-BGCs identified in this study may be worthy of further investigation for their effect on the growth and virulence of P. agathidicida.

Dispersal is a crucial mechanism to living beings, allowing them to reach new resources such that populations and species can occupy new environments. However, directly observing the dispersal mechanisms of widespread species can be costly or even impractical, which is the case for mangrove trees. The influence of ocean currents on mangrove dispersal is increasingly evident; however, few studies mechanistically relate the patterns of population distribution with the dispersal by oceanic currents under an integrated framework. Here, we evaluate the role of oceanic currents on connectivity of Rhizophora mangle along the Southwest Atlantic. We inferred population genetic structure and migration rates, simulated the displacement of propagules and tested our hypotheses with Mantel tests and redundancy analysis. We observed populations structured in two major groups, north and south, which is corroborated by other studies with Rhizophora and other coastal plants. Inferred recent migration rates do not indicate ongoing gene flow between sites. Conversely, long-term migration rates were low across groups and contrasting dispersal patterns within each one, which is consistent with long-distance dispersal events. Our hypothesis tests suggest that both isolation by distance and isolation by oceanography (derived from the oceanic currents) can explain the neutral genetic variation of R. mangle in the region. Our findings expand current knowledge of mangrove connectivity and highlight how the association of molecular methods with oceanographic simulations improve the interpretation of the dispersal process. This integrative approach is a cost- and time-efficient strategy to include dispersal and connectivity data into marine protected areas planning and management.