Intergenomic signatures of coevolution between Tasmanian devils and an infectious cancer.

Coevolution is common and frequently governs host-pathogen interaction outcomes. Phenotypes underlying these interactions often manifest as the combined products of the genomes of interacting species, yet traditional quantitative trait mapping approaches ignore these intergenomic interactions. Devil facial tumor disease (DFTD), an infectious cancer afflicting Tasmanian devils (Sarcophilus harrisii), has decimated devil populations due to universal host susceptibility and a fatality rate approaching 100%. Here, we used a recently developed joint genome-wide association study (i.e., co-GWAS) approach, 15 y of mark-recapture data, and 960 genomes to identify intergenomic signatures of coevolution between devils and DFTD. Using a traditional GWA approach, we found that both devil and DFTD genomes explained a substantial proportion of variance in how quickly susceptible devils became infected, although genomic architectures differed across devils and DFTD; the devil genome had fewer loci of large effect whereas the DFTD genome had a more polygenic architecture. Using a co-GWA approach, devil-DFTD intergenomic interactions explained ~3× more variation in how quickly susceptible devils became infected than either genome alone, and the top genotype-by-genotype interactions were significantly enriched for cancer genes and signatures of selection. A devil regulatory mutation was associated with differential expression of a candidate cancer gene and showed putative allele matching effects with two DFTD coding sequence variants. Our results highlight the need to account for intergenomic interactions when investigating host-pathogen (co)evolution and emphasize the importance of such interactions when considering devil management strategies.

Spatial variation in genomic signatures of local adaptation during the cane toad invasion of Australia.

Adaptive evolution can facilitate species' range expansions across environmentally heterogeneous landscapes. However, serial founder effects can limit the efficacy of selection, and the evolution of increased dispersal during range expansions may result in gene flow swamping local adaptation. Here, we study how genetic drift, gene flow and selection interact during the cane toad's (Rhinella marina) invasion across the heterogeneous landscape of Australia. Following its introduction in 1935, the cane toad colonised eastern Australia and established several stable range edges. The ongoing, more rapid range expansion in north-central Australia has occurred concomitant with an evolved increase in dispersal capacity. Using reduced representation genomic data of Australian cane toads from the expansion front and from two areas of their established range, we test the hypothesis that high gene flow constrains local adaptation at the expansion front relative to established areas. Genetic analyses indicate the three study areas are genetically distinct but show similar levels of allelic richness, heterozygosity and inbreeding. Markedly higher gene flow or recency of colonisation at the expansion front have likely hindered local adaptation at the time of sampling, as indicated by reduced slopes of genetic-environment associations (GEAs) estimated using a novel application of geographically weighted regression that accounts for allele surfing; GEA slopes are significantly steeper in established parts of the range. Our work bolsters evidence supporting adaptation of invasive species post-introduction and adds novel evidence for differing strengths of evolutionary forces among geographic areas with different invasion histories.

Geography is more important than life history in the recent diversification of the tiger salamander complex.

The North American tiger salamander species complex, including its best-known species, the Mexican axolotl, has long been a source of biological fascination. The complex exhibits a wide range of variation in developmental life history strategies, including populations and individuals that undergo metamorphosis; those able to forego metamorphosis and retain a larval, aquatic lifestyle (i.e., paedomorphosis); and those that do both. The evolution of a paedomorphic life history state is thought to lead to increased population genetic differentiation and ultimately reproductive isolation and speciation, but the degree to which it has shaped population- and species-level divergence is poorly understood. Using a large multilocus dataset from hundreds of samples across North America, we identified genetic clusters across the geographic range of the tiger salamander complex. These clusters often contain a mixture of paedomorphic and metamorphic taxa, indicating that geographic isolation has played a larger role in lineage divergence than paedomorphosis in this system. This conclusion is bolstered by geography-informed analyses indicating no effect of life history strategy on population genetic differentiation and by model-based population genetic analyses demonstrating gene flow between adjacent metamorphic and paedomorphic populations. This fine-scale genetic perspective on life history variation establishes a framework for understanding how plasticity, local adaptation, and gene flow contribute to lineage divergence. Many members of the tiger salamander complex are endangered, and the Mexican axolotl is an important model system in regenerative and biomedical research. Our results chart a course for more informed use of these taxa in experimental, ecological, and conservation research.

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.

Quantifying 25 years of disease-caused declines in Tasmanian devil populations: host density drives spatial pathogen spread.

Infectious diseases are strong drivers of wildlife population dynamics, however, empirical analyses from the early stages of pathogen emergence are rare. Tasmanian devil facial tumour disease (DFTD), discovered in 1996, provides the opportunity to study an epizootic from its inception. We use a pattern-oriented diffusion simulation to model the spatial spread of DFTD across the species' range and quantify population effects by jointly modelling multiple streams of data spanning 35 years. We estimate the wild devil population peaked at 53 000 in 1996, less than half of previous estimates. DFTD spread rapidly through high-density areas, with spread velocity slowing in areas of low host densities. By 2020, DFTD occupied >90% of the species' range, causing 82% declines in local densities and reducing the total population to 16 900. Encouragingly, our model forecasts the population decline should level-off within the next decade, supporting conservation management focused on facilitating evolution of resistance and tolerance.

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.

Contemporary Demographic Reconstruction Methods Are Robust to Genome Assembly Quality: A Case Study in Tasmanian Devils.

Reconstructing species' demographic histories is a central focus of molecular ecology and evolution. Recently, an expanding suite of methods leveraging either the sequentially Markovian coalescent (SMC) or the site-frequency spectrum has been developed to reconstruct population size histories from genomic sequence data. However, few studies have investigated the robustness of these methods to genome assemblies of varying quality. In this study, we first present an improved genome assembly for the Tasmanian devil using the Chicago library method. Compared with the original reference genome, our new assembly reduces the number of scaffolds (from 35,975 to 10,010) and increases the scaffold N90 (from 0.101 to 2.164 Mb). Second, we assess the performance of four contemporary genomic methods for inferring population size history (PSMC, MSMC, SMC++, Stairway Plot), using the two devil genome assemblies as well as simulated, artificially fragmented genomes that approximate the hypothesized demographic history of Tasmanian devils. We demonstrate that each method is robust to assembly quality, producing similar estimates of Ne when simulated genomes were fragmented into up to 5,000 scaffolds. Overall, methods reliant on the SMC are most reliable between ∼300 generations before present (gbp) and 100 kgbp, whereas methods exclusively reliant on the site-frequency spectrum are most reliable between the present and 30 gbp. Our results suggest that when used in concert, genomic methods for reconstructing species' effective population size histories 1) can be applied to nonmodel organisms without highly contiguous reference genomes, and 2) are capable of detecting independently documented effects of historical geological events.

Emerging Frontiers in the Study of Molecular Evolution.

A collection of the editors of Journal of Molecular Evolution have gotten together to pose a set of key challenges and future directions for the field of molecular evolution. Topics include challenges and new directions in prebiotic chemistry and the RNA world, reconstruction of early cellular genomes and proteins, macromolecular and functional evolution, evolutionary cell biology, genome evolution, molecular evolutionary ecology, viral phylodynamics, theoretical population genomics, somatic cell molecular evolution, and directed evolution. While our effort is not meant to be exhaustive, it reflects research questions and problems in the field of molecular evolution that are exciting to our editors.

Infectious disease and sickness behaviour: tumour progression affects interaction patterns and social network structure in wild Tasmanian devils.

Infectious diseases, including transmissible cancers, can have a broad range of impacts on host behaviour, particularly in the latter stages of disease progression. However, the difficulty of early diagnoses makes the study of behavioural influences of disease in wild animals a challenging task. Tasmanian devils (Sarcophilus harrisii) are affected by a transmissible cancer, devil facial tumour disease (DFTD), in which tumours are externally visible as they progress. Using telemetry and mark-recapture datasets, we quantify the impacts of cancer progression on the behaviour of wild devils by assessing how interaction patterns within the social network of a population change with increasing tumour load. The progression of DFTD negatively influences devils' likelihood of interaction within their network. Infected devils were more active within their network late in the mating season, a pattern with repercussions for DFTD transmission. Our study provides a rare opportunity to quantify and understand the behavioural feedbacks of disease in wildlife and how they may affect transmission and population dynamics in general.

Mixed support for gene flow as a constraint to local adaptation and contributor to the limited geographic range of an endemic salamander.

Understanding mechanisms that underlie species range limits is at the core of evolutionary ecology. Asymmetric gene flow between larger core populations and smaller edge populations can swamp local adaptation at the range edge and inhibit further range expansion. However, empirical tests of this theory are exceedingly rare. We tested the hypothesis that asymmetric gene flow can constrain local adaptation and thereby species' range limits in an endemic US salamander (Ambystoma barbouri) by determining if gene flow is asymmetric between the core and peripheries of the species' geographic distribution and testing whether local adaptation is swamped at range edges with a reciprocal transplant experiment. Using putatively neutral loci from populations across three core-to-edge transects that covered nearly the entire species' geographic range, we found evidence for asymmetric, core-to-edge gene flow along western and northern transects, but not along a southern transect. Subsequently, the reciprocal transplant experiment suggested that northern and western edge populations are locally adapted despite experiencing asymmetric gene flow, yet have lower fitness in their respective home regions than those of centre population. Conversely, southern populations exhibit low deme quality, experiencing high mortality regardless of where they were reared, probably due to harsher edge habitat conditions. Consequently, we provide rare species-wide evidence that local adaptation can occur despite asymmetric gene flow, though migration from the core may prohibit range expansion by reducing fitness in edge populations. Further, our multitransect study shows that multiple, nonmutually exclusive mechanisms can lead to range limits within a single species.

Comparative landscape genetics reveals differential effects of environment on host and pathogen genetic structure in Tasmanian devils (Sarcophilus harrisii) and their transmissible tumour.

Genetic structure in host species is often used to predict disease spread. However, host and pathogen genetic variation may be incongruent. Understanding landscape factors that have either concordant or divergent influence on host and pathogen genetic structure is crucial for wildlife disease management. Devil facial tumour disease (DFTD) was first observed in 1996 and has spread throughout almost the entire Tasmanian devil geographic range, causing dramatic population declines. Whereas DFTD is predominantly spread via biting among adults, devils typically disperse as juveniles, which experience low DFTD prevalence. Thus, we predicted little association between devil and tumour population structure and that environmental factors influencing gene flow differ between devils and tumours. We employed a comparative landscape genetics framework to test the influence of environmental factors on patterns of isolation by resistance (IBR) and isolation by environment (IBE) in devils and DFTD. Although we found evidence for broad-scale costructuring between devils and tumours, we found no relationship between host and tumour individual genetic distances. Further, the factors driving the spatial distribution of genetic variation differed for each. Devils exhibited a strong IBR pattern driven by major roads, with no evidence of IBE. By contrast, tumours showed little evidence for IBR and a weak IBE pattern with respect to elevation in one of two tumour clusters we identify herein. Our results warrant caution when inferring pathogen spread using host population genetic structure and suggest that reliance on environmental barriers to host connectivity may be ineffective for managing the spread of wildlife diseases. Our findings demonstrate the utility of comparative landscape genetics for identifying differential factors driving host dispersal and pathogen transmission.

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 modeling 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 10 yr 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 (initial dynamics after disease emergence). Only 21% of matching scenarios led to devil extinction within 100 yr following devil facial tumor 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 yr, 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 modeling approach is widely applicable to other host-pathogen systems to predict disease impact beyond transient dynamics.

Conserving adaptive potential: lessons from Tasmanian devils and their transmissible cancer.

Maintenance of adaptive genetic variation has long been a goal of management of natural populations, but only recently have genomic tools allowed identification of specific loci associated with fitness-related traits in species of conservation concern. This raises the possibility of managing for genetic variation directly relevant to specific threats, such as those due to climate change or emerging infectious disease. Tasmanian devils (Sarcophilus harrisii) face the threat of a transmissible cancer, devil facial tumor disease (DFTD), that has decimated wild populations and led to intensive management efforts. Recent discoveries from genomic and modeling studies reveal how natural devil populations are responding to DFTD, and can inform management of both captive and wild devil populations. Notably, recent studies have documented genetic variation for disease-related traits and rapid evolution in response to DFTD, as well as potential mechanisms for disease resistance such as immune response and tumor regression in wild devils. Recent models predict dynamic persistence of devils with or without DFTD under a variety of modeling scenarios, although at much lower population densities than before DFTD emerged, contrary to previous predictions of extinction. As a result, current management that focuses on captive breeding and release for maintaining genome-wide genetic diversity or demographic supplementation of populations could have negative consequences. Translocations of captive devils into wild populations evolving with DFTD can cause outbreeding depression and/or increases in the force of infection and thereby the severity of the epidemic, and we argue that these risks outweigh any benefits of demographic supplementation in wild populations. We also argue that genetic variation at loci associated with DFTD should be monitored in both captive and wild populations, and that as our understanding of DFTD-related genetic variation improves, considering genetic management approaches to target this variation is warranted in developing conservation strategies for Tasmanian devils.

Sex bias in ability to cope with cancer: Tasmanian devils and facial tumour disease.

Knowledge of the ecological dynamics between hosts and pathogens during the initial stages of disease emergence is crucial to understanding the potential for evolution of new interspecific interactions. Tasmanian devil (Sarcophilus harrisii) populations have declined precipitously owing to infection by a transmissible cancer (devil facial tumour disease, DFTD) that emerged approximately 20 years ago. Since the emergence of DFTD, and as the disease spreads across Tasmania, the number of devils has dropped up to 90% across 80% of the species's distributional range. As a result, the disease is expected to act as a strong selective force on hosts to develop mechanisms of tolerance and/or resistance to the infection. We assessed the ability of infected devils to cope with infection, which translates into host tolerance to the cancer, by using the reaction norm of the individual body condition by tumour burden. We found that body condition of infected hosts is negatively affected by cancer progression. Males and females presented significant differences in their tolerance levels to infection, with males suffering declines of up to 25% of their body condition, in contrast to less than 5% in females. Sex-related differences in tolerance to cancer progression may select for changes in life-history strategies of the host and could also alter the selective environment for the tumours.

Regional variation in drivers of connectivity for two frog species (Rana pretiosa and R. luteiventris) from the U.S. Pacific Northwest.

Comparative landscape genetics has uncovered high levels of variability in which landscape factors affect connectivity among species and regions. However, the relative importance of species traits versus environmental variation for predicting landscape patterns of connectivity is unresolved. We provide evidence from a landscape genetics study of two sister taxa of frogs, the Oregon spotted frog (Rana pretiosa) and the Columbia spotted frog (Rana luteiventris) in Oregon and Idaho, USA. Rana pretiosa is relatively more dependent on moisture for dispersal than R. luteiventris, so if species traits influence connectivity, we predicted that connectivity among R. pretiosa populations would be more positively associated with moisture than R. luteiventris. However, if environmental differences are important drivers of gene flow, we predicted that connectivity would be more positively related to moisture in arid regions. We tested these predictions using eight microsatellite loci and gravity models in two R. pretiosa regions and four R. luteiventris regions (n = 1,168 frogs). In R. pretiosa, but not R. luteiventris, connectivity was positively related to mean annual precipitation, supporting our first prediction. In contrast, connectivity was not more positively related to moisture in more arid regions. Various temperature metrics were important predictors for both species and in all regions, but the directionality of their effects varied. Therefore, the pattern of variation in drivers of connectivity was consistent with predictions based on species traits rather than on environmental variation.

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.

Infection of the fittest: devil facial tumour disease has greatest effect on individuals with highest reproductive output.

Emerging infectious diseases rarely affect all members of a population equally and determining how individuals' susceptibility to infection is related to other components of their fitness is critical to understanding disease impacts at a population level and for predicting evolutionary trajectories. We introduce a novel state-space model framework to investigate survival and fecundity of Tasmanian devils (Sarcophilus harrisii) affected by a transmissible cancer, devil facial tumour disease. We show that those devils that become host to tumours have otherwise greater fitness, with higher survival and fecundity rates prior to disease-induced death than non-host individuals that do not become infected, although high tumour loads lead to high mortality. Our finding that individuals with the greatest reproductive value are those most affected by the cancer demonstrates the need to quantify both survival and fecundity in context of disease progression for understanding the impact of disease on wildlife populations.

An approach for identifying cryptic barriers to gene flow that limit species' geographic ranges.

Species' geographic range limits are most often not demarcated by obvious dispersal barriers. Poor-quality habitat at the edge of a species' range can prevent range expansion by preventing outward migration or through reducing adaptive potential resulting from decreased genetic diversity. We identified habitat variables that constrain gene flow across the entire geographic range of an endemic salamander (Ambystoma barbouri) in the eastern United States, and we tested whether increased resistance resulting from these variables provides cryptic dispersal barriers at the range edges. Using polymorphic microsatellite loci, we first identified three genetic clusters that are separated by the Ohio and Kentucky rivers. Through a combination of landscape genetic analyses and generalized dissimilarity modelling, we then classified variables that (i) restrict gene flow in each of the genetic clusters across the geographic distribution of A. barbouri and (ii) become more common towards the peripheries of the distribution. A decrease in limestone availability and an increase in growing season precipitation were correlated with high resistance to gene flow across the range, and both became more common at the edges of the species' distribution. However, other landscape variables were more important for explaining variation in geneflow rates in different portions of the range, such as increased mean annual temperature and frost-free period in the south vs. growing season precipitation in the north. Taken together, these results suggest that there are both range-wide and regionally specific cryptic habitat barriers preventing geographic range expansion. Species 'geographic range limits are probably governed by a set of ecological and evolutionary factors, and our landscape genetic approach could be applied to gain additional insight into many systems.

Conservation implications of limited genetic diversity and population structure in Tasmanian devils (Sarcophilus harrisii).

Tasmanian devils face a combination of threats to persistence, including Devil Facial Tumor Disease (DFTD), an epidemic transmissible cancer. We used RAD sequencing to investigate genome-wide patterns of genetic diversity and geographic population structure. Consistent with previous results, we found very low genetic diversity in the species as a whole, and we detected two broad genetic clusters occupying the northwestern portion of the range, and the central and eastern portions. However, these two groups overlap across a broad geographic area, and differentiation between them is modest (FST = 0.1081). Our results refine the geographic extent of the zone of mixed ancestry and substructure within it, potentially informing management of genetic variation that existed in pre-diseased populations of the species. DFTD has spread across both genetic clusters, but recent evidence points to a genomic response to selection imposed by DFTD. Any allelic variation for resistance to DFTD may be able to spread across the devil population under selection by DFTD, and/or be present as standing variation in both genetic regions.

Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions.

Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species' demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.