Correction: Fraik et al. The Impacts of Dam Construction and Removal on the Genetics of Recovering Steelhead (Oncorhynchus mykiss) Populations across the Elwha River Watershed. Genes 2021, 12, 89.

In the original publication [...].

Spatial variation in gene expression of Tasmanian devil facial tumors despite minimal host transcriptomic response to infection.

BACKGROUND: Transmissible cancers lie at the intersection of oncology and infectious disease, two traditionally divergent fields for which gene expression studies are particularly useful for identifying the molecular basis of phenotypic variation. In oncology, transcriptomics studies, which characterize the expression of thousands of genes, have identified processes leading to heterogeneity in cancer phenotypes and individual prognoses. More generally, transcriptomics studies of infectious diseases characterize interactions between host, pathogen, and environment to better predict population-level outcomes. Tasmanian devils have been impacted dramatically by a transmissible cancer (devil facial tumor disease; DFTD) that has led to widespread population declines. Despite initial predictions of extinction, populations have persisted at low levels, due in part to heterogeneity in host responses, particularly between sexes. However, the processes underlying this variation remain unknown. RESULTS: We sequenced transcriptomes from healthy and DFTD-infected devils, as well as DFTD tumors, to characterize host responses to DFTD infection, identify differing host-tumor molecular interactions between sexes, and investigate the extent to which tumor gene expression varies among host populations. We found minimal variation in gene expression of devil lip tissues, either with respect to DFTD infection status or sex. However, 4088 genes were differentially expressed in tumors among our sampling localities. Pathways that were up- or downregulated in DFTD tumors relative to normal tissues exhibited the same patterns of expression with greater intensity in tumors from localities that experienced DFTD for longer. No mRNA sequence variants were associated with expression variation. CONCLUSIONS: Expression variation among localities may reflect morphological differences in tumors that alter ratios of normal-to-tumor cells within biopsies. Phenotypic variation in tumors may arise from environmental variation or differences in host immune response that were undetectable in lip biopsies, potentially reflecting variation in host-tumor coevolutionary relationships among sites that differ in the time since DFTD arrival.

Contemporary and historical selection in Tasmanian devils (Sarcophilus harrisii) support novel, polygenic response to transmissible cancer.

Tasmanian devils (Sarcophilus harrisii) are evolving in response to a unique transmissible cancer, devil facial tumour disease (DFTD), first described in 1996. Persistence of wild populations and the recent emergence of a second independently evolved transmissible cancer suggest that transmissible cancers may be a recurrent feature in devils. Here, we compared signatures of selection across temporal scales to determine whether genes or gene pathways under contemporary selection (six to eight generations) have also been subject to historical selection (65-85 Myr). First, we used targeted sequencing, RAD-capture, in approximately 2500 devils in six populations to identify genomic regions subject to rapid evolution. We documented genome-wide contemporary evolution, including 186 candidate genes related to cell cycling and immune response. Then we used a molecular evolution approach to identify historical positive selection in devils compared to other marsupials and found evidence of selection in 1773 genes. However, we found limited overlap across time scales, with only 16 shared candidate genes, and no overlap in enriched functional gene sets. Our results are consistent with a novel, multi-locus evolutionary response of devils to DFTD. Our results can inform conservation by identifying high priority targets for genetic monitoring and guiding maintenance of adaptive potential in managed populations.

The Impacts of Dam Construction and Removal on the Genetics of Recovering Steelhead (Oncorhynchus mykiss) Populations across the Elwha River Watershed.

Dam construction and longitudinal river habitat fragmentation disrupt important life histories and movement of aquatic species. This is especially true for Oncorhynchus mykiss that exhibits both migratory (steelhead) and non-migratory (resident rainbow) forms. While the negative effects of dams on salmonids have been extensively documented, few studies have had the opportunity to compare population genetic diversity and structure prior to and following dam removal. Here we examine the impacts of the removal of two dams on the Elwha River on the population genetics of O. mykiss. Genetic data were produced from >1200 samples collected prior to dam removal from both life history forms, and post-dam removal from steelhead. We identified three genetic clusters prior to dam removal primarily explained by isolation due to dams and natural barriers. Following dam removal, genetic structure decreased and admixture increased. Despite large O. mykiss population declines after dam construction, we did not detect shifts in population genetic diversity or allele frequencies of loci putatively involved in migratory phenotypic variation. Steelhead descendants from formerly below and above dammed populations recolonized the river rapidly after dam removal, suggesting that dam construction did not significantly reduce genetic diversity underlying O. mykiss life history strategies. These results have significant evolutionary implications for the conservation of migratory adaptive potential in O. mykiss populations above current anthropogenic barriers.

Spontaneous Tumor Regression in Tasmanian Devils Associated with RASL11A Activation.

Spontaneous tumor regression has been documented in a small proportion of human cancer patients, but the specific mechanisms underlying tumor regression without treatment are not well understood. Tasmanian devils are threatened with extinction from a transmissible cancer due to universal susceptibility and a near 100% case fatality rate. In over 10,000 cases, <20 instances of natural tumor regression have been detected. Previous work in this system has focused on Tasmanian devil genetic variation associated with the regression phenotype. Here, we used comparative and functional genomics to identify tumor genetic variation associated with tumor regression. We show that a single point mutation in the 5' untranslated region of the putative tumor suppressor RASL11A significantly contributes to tumor regression. RASL11A was expressed in regressed tumors but silenced in wild-type, nonregressed tumors, consistent with RASL11A downregulation in human cancers. Induced RASL11A expression significantly reduced tumor cell proliferation in vitro The RAS pathway is frequently altered in human cancers, and RASL11A activation may provide a therapeutic treatment option for Tasmanian devils as well as a general mechanism for tumor inhibition.

Disease swamps molecular signatures of genetic-environmental associations to abiotic factors in Tasmanian devil (Sarcophilus harrisii) populations.

Landscape genomics studies focus on identifying candidate genes under selection via spatial variation in abiotic environmental variables, but rarely by biotic factors (i.e., disease). The Tasmanian devil (Sarcophilus harrisii) is found only on the environmentally heterogeneous island of Tasmania and is threatened with extinction by a transmissible cancer, devil facial tumor disease (DFTD). Devils persist in regions of long-term infection despite epidemiological model predictions of species' extinction, suggesting possible adaptation to DFTD. Here, we test the extent to which spatial variation and genetic diversity are associated with the abiotic environment (i.e., climatic variables, elevation, vegetation cover) and/or DFTD. We employ genetic-environment association analyses using 6886 SNPs from 3287 individuals sampled pre- and post-disease arrival across the devil's geographic range. Pre-disease, we find significant correlations of allele frequencies with environmental variables, including 365 unique loci linked to 71 genes, suggesting local adaptation to abiotic environment. The majority of candidate loci detected pre-DFTD are not detected post-DFTD arrival. Several post-DFTD candidate loci are associated with disease prevalence and were in linkage disequilibrium with genes involved in tumor suppression and immune response. Loss of apparent signal of abiotic local adaptation post-disease suggests swamping by strong selection resulting from the rapid onset of DFTD.

Transcriptomics of Tasmanian Devil (Sarcophilus Harrisii) Ear Tissue Reveals Homogeneous Gene Expression Patterns across a Heterogeneous Landscape.

In an era of unprecedented global change, exploring patterns of gene expression among wild populations across their geographic range is crucial for characterizing adaptive potential. RNA-sequencing studies have successfully characterized gene expression differences among populations experiencing divergent environmental conditions in a wide variety of taxa. However, few of these studies have identified transcriptomic signatures to multivariate, environmental stimuli among populations in their natural environments. Herein, we aim to identify environmental and sex-driven patterns of gene expression in the Tasmanian devil (Sarcophilus harrisii), a critically endangered species that occupies a heterogeneous environment. We performed RNA-sequencing on ear tissue biopsies from adult male and female devils from three populations at the extremes of their geographic range. There were no transcriptome-wide patterns of differential gene expression that would be suggestive of significant, environmentally-driven transcriptomic responses. The general lack of transcriptome-wide variation in gene expression levels across the devil's geographic range is consistent with previous studies that documented low levels of genetic variation in the species. However, genes previously implicated in local adaptation to abiotic environment in devils were enriched for differentially expressed genes. Additionally, three modules of co-expressed genes were significantly associated with either population of origin or sex.

Large-effect loci affect survival in Tasmanian devils (Sarcophilus harrisii) infected with a transmissible cancer.

Identifying the genetic architecture of complex phenotypes is a central goal of modern biology, particularly for disease-related traits. Genome-wide association methods are a classical approach for identifying the genomic basis of variation in disease phenotypes, but such analyses are particularly challenging in natural populations due to sample size difficulties. Extensive mark-recapture data, strong linkage disequilibrium and a lethal transmissible cancer make the Tasmanian devil (Sarcophilus harrisii) an ideal model for such an association study. We used a RAD-capture approach to genotype 624 devils at ~16,000 loci and then used association analyses to assess the heritability of three cancer-related phenotypes: infection case-control (where cases were infected devils and controls were devils that were never infected), age of first infection and survival following infection. The SNP array explained much of the phenotypic variance for female survival (>80%) and female case-control (>61%). We found that a few large-effect SNPs explained much of the variance for female survival (~5 SNPs explained >61% of the total variance), whereas more SNPs (~56) of smaller effect explained less of the variance for female case-control (~23% of the total variance). By contrast, these same SNPs did not account for a significant proportion of phenotypic variance in males, suggesting that the genetic bases of these traits and/or selection differ across sexes. Loci involved with cell adhesion and cell-cycle regulation underlay trait variation, suggesting that the devil immune system is rapidly evolving to recognize and potentially suppress cancer growth through these pathways. Overall, our study provided necessary data for genomics-based conservation and management in Tasmanian devils.

Navigating the Interface Between Landscape Genetics and Landscape Genomics.

As next-generation sequencing data become increasingly available for non-model organisms, a shift has occurred in the focus of studies of the geographic distribution of genetic variation. Whereas landscape genetics studies primarily focus on testing the effects of landscape variables on gene flow and genetic population structure, landscape genomics studies focus on detecting candidate genes under selection that indicate possible local adaptation. Navigating the transition between landscape genomics and landscape genetics can be challenging. The number of molecular markers analyzed has shifted from what used to be a few dozen loci to thousands of loci and even full genomes. Although genome scale data can be separated into sets of neutral loci for analyses of gene flow and population structure and putative loci under selection for inference of local adaptation, there are inherent differences in the questions that are addressed in the two study frameworks. We discuss these differences and their implications for study design, marker choice and downstream analysis methods. Similar to the rapid proliferation of analysis methods in the early development of landscape genetics, new analytical methods for detection of selection in landscape genomics studies are burgeoning. We focus on genome scan methods for detection of selection, and in particular, outlier differentiation methods and genetic-environment association tests because they are the most widely used. Use of genome scan methods requires an understanding of the potential mismatches between the biology of a species and assumptions inherent in analytical methods used, which can lead to high false positive rates of detected loci under selection. Key to choosing appropriate genome scan methods is an understanding of the underlying demographic structure of study populations, and such data can be obtained using neutral loci from the generated genome-wide data or prior knowledge of a species' phylogeographic history. To this end, we summarize recent simulation studies that test the power and accuracy of genome scan methods under a variety of demographic scenarios and sampling designs. We conclude with a discussion of additional considerations for future method development, and a summary of methods that show promise for landscape genomics studies but are not yet widely used.