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Storfer, A.

Publications and source records attributed to Storfer, A..

6 recordsLinked to original sources

Response to "No evidence that transmissible cancer has shifted from emergence to endemism in Tasmanian devils"

Herein, we rebut the critique of Patton et al. (2020), entitled, "No evidence that a transmissible cancer has shifted from emergence to endemism", by Stammnitz et al. (2024). First and foremost, the authors do not conduct any phylogenetic or epidemiological analyses to rebut the inferences from the main results of the Patton et al. (2020) article, rendering the title of their rebuttal without evidence or merit. Additionally, Stammnitz et al. (2024) present a phylogenetic tree based on only 32 copy number variants (not typically used in phylogenetic analyses and evolve in a completely different way than DNA sequences) to "rebut" our tree that was inferred from 436.1 kb of sequence data and nearly two orders of magnitude more parsimony-informative sites (2520 SNPs). As such it is not surprising that their phylogeny did not have a similar branching pattern to ours, given that support for each branch of their tree was weak and the essentially formed a polytomy. That is, one could rotate their resulting tree in any direction and by nature, it would not match ours. While the authors are correct that we used suboptimal filtering of our raw whole genome sequencing data, re-analyses of the data with 30X coverage, as suggested, resulted in a mutation rate similar to that reported in Stammnitz et al. (2024). Most importantly, when we re-analyzed our data, as well as Stammnitz et al.s own data, the results of the Patton et al. (2020) article are supported with both datasets. That is, the effective transmission rate of DFTD has transitioned over time to approach one, suggesting endemism; and, the spread of DFTD is rapid and omnidirectional despite the observed east-to-west wave of spread. Overall, Stammnitz et al. (2024) not only fail to provide evidence to contradict the findings of Patton et al. (2020), but rather help support the results with their own data.

evolutionary biology↗

Effects of a transmissible cancer on life-history traits in Tasmanian devils

Shifts in life history traits, such as timing of reproduction, can help mediate population declines following perturbations, and early reproduction should be favoured when adult survival is impacted more than juvenile survival. In Tasmanian devils, following the emergence of a fatal transmissible cancer, females started to breed precocially (i.e., at age one instead of typically age two) and the same time as populations started to decline following disease emergence. Here, we focus on a diseased site (Freycinet Peninsula, Tasmania, Australia) with 18 years of continuous mark-recapture data to test: (1) whether rates of precocial breeding in females continued to increase after the initial rise after the emergence of the disease, (2) whether there was a relationship between body size and breeding success for either one-year-olds or adult females (i.e., at least two-years-old), and (3) whether there was inbreeding depression in breeding success for either age category. We show that rates of precocial breeding did not continue to rise, and that the proportion of precocially breeding females has plateaued at around 50%. We also show that there was no effect of body size on the probability of breeding for either one-year-old or for adult females. Finally, we show that there was no evidence for inbreeding depression in breeding success for either age class. We discuss possible constraints that may have inhibited further rise in rates of precocial breeding in the context of limitations to growth in the offspring of precocially breeding (and therefore smaller) females.

evolutionary biology↗

Historical and contemporary signatures of selection in response to transmissible cancer in the Tasmanian Devil (Sarcophilus harrisii)

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 (6-8 generations) have also been subject to historical selection (65-85 million years), and test for recurrent selection in devils. First, we used a targeted sequencing approach, RAD-capture, to identify genomic regions subject to rapid evolution in approximately 2,500 devils in six populations as DFTD spread across the species range. 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 1,773 genes. However, we found limited overlap across time scales, with historical selection detected in only 16 contemporary 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 management actions to conserve adaptive potential of devils by identifying high priority targets for genetic monitoring and maintenance of functional diversity in managed populations.

evolutionary biology↗

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 such as disease. The Tasmanian devil (Sarcophilus harrisii) is found only on the environmentally heterogeneous island of Tasmania and is threatened with extinction by a nearly 100% fatal, 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 and/or by DFTD. We employ genetic-environment association (GEAs) analyses using a RAD-capture panel consisting of 6,886 SNPs from 3,286 individuals sampled pre- and post-disease arrival. Pre-disease, we find significant correlations of allele frequencies with environmental variables, including 349 unique loci linked to 64 genes, suggesting local adaptation to abiotic environment. Following DFTD arrival, however, we detected few of the pre-disease candidate loci, but instead frequencies of candidate loci linked to 14 genes correlated with disease prevalence. Loss of apparent signal of abiotic local adaptation following disease arrival suggests swamping by the strong selection imposed by DFTD. Further support for this result comes from the fact that post-disease candidate loci are in linkage disequilibrium with genes putatively involved in immune response, tumor suppression and apoptosis. This suggests the strength GEA associations of loci with the abiotic environment are swamped resulting from the rapid onset of a biotic selective pressure.

evolutionary biology↗

Hybridizing salamanders experience accelerated diversification

Whether hybridization generates or erodes species diversity has long been debated, but to date most studies have been conducted at small taxonomic scales. Salamanders (order Caudata) represent a taxonomic order in which hybridization plays a prevalent ecological and evolutionary role. We employed a recently developed model of trait-dependent diversification to test the hypothesis that hybridization impacts the diversification dynamics of species that are currently hybridizing. We find strong evidence supporting this hypothesis, showing that hybridizing salamander lineages have significantly greater net-diversification rates than non-hybridizing lineages. This pattern is driven by concurrently increased speciation rates and decreased extinction rates in hybridizing lineages. Our results support the hypothesis that hybridization can act as a generative force in macroevolutionary diversification.

evolutionary biology↗

Individual and temporal variation in pathogen load predicts long-term impacts of an emerging infectious disease

Emerging infectious diseases increasingly threaten wildlife populations. Most studies focus on managing short-term epidemic properties, such as controlling early outbreaks. Predicting long-term endemic characteristics with limited retrospective data is more challenging. We used individual-based modelling informed by individual variation in pathogen load and transmissibility to predict long-term impacts of a lethal, transmissible cancer on Tasmanian devil (Sarcophilus harrisii) populations. For this, we employed Approximate Bayesian Computation to identify model scenarios that best matched known epidemiological and demographic system properties derived from ten years of data after disease emergence, enabling us to forecast future system dynamics. We show that the dramatic devil population declines observed thus far are likely attributable to transient dynamics. Only 21% of matching scenarios led to devil extinction within 100 years following devil facial tumour disease (DFTD) introduction, whereas DFTD faded out in 57% of simulations. In the remaining 22% of simulations, disease and host coexisted for at least 100 years, usually with long-period oscillations. Our findings show that pathogen extirpation or host-pathogen coexistence are much more likely than the DFTD-induced devil extinction, with crucial management ramifications. Accounting for individual-level disease progression and the long-term outcome of devil-DFTD interactions at the population-level, our findings suggest that immediate management interventions are unlikely to be necessary to ensure the persistence of Tasmanian devil populations. This is because strong population declines of devils after disease emergence do not necessarily translate into long-term population declines at equilibria. Our modelling approach is widely applicable to other host-pathogen systems to predict disease impact beyond transient dynamics.

epidemiology↗