Evolutionary Applications最新文献

Intraspecific genetic diversity across a species' geographic range is relevant to adaptive potential and long-term population persistence, and identifying genetically distinct groups within species can direct management decisions focused on conserving species-level genetic diversity. Comparative phylogeography using whole genome techniques allows for investigation of whether co-distributed species exhibit shared spatial genetic differentiation at fine spatial scales, thereby facilitating a comparative approach to both landscape and conservation genetics. By sequencing over 900 low-coverage whole genomes, we evaluated the concordance of genetic structure and diversity from 12 co-occurring species of migratory birds whose breeding ranges span adjacent North American ecogeographic regions: the vast boreal forest belt and the temperate montane Appalachian forests. We detected concordant phylogeographic patterns in 11 of 12 species wherein populations from the southern Appalachians were genetically distinct from boreal belt populations. Our results reveal that small populations persisting in the southern Appalachian Mountains consistently harbor genetic diversity that is subtly distinct from much larger, widespread boreal populations of the same species. However, in most species, levels of standing genetic diversity were not significantly different between Appalachian and boreal populations despite the drastic difference in geographic extent of these populations. We found no evidence for shared signatures of selection across the genome, suggesting that the concordance of spatial genetic structure across species emerges from species-specific patterns of molecular divergence across the genome rather than parallel patterns of selection. Conservation of the Appalachian ecosystem would likely support maintenance of distinct genetic diversity in several migratory avian species with widespread distributions.

The western chimpanzee (Pan troglodytes verus) is a Critically Endangered taxon. In Guinea-Bissau (GB), the subspecies is increasingly threatened, but there is a lack of understanding regarding the degree of genetic threat faced by populations. This hinders the development of targeted conservation strategies and the prioritization of efforts by national agencies. In this study, we use microsatellite data from four parks located in southern GB and five whole-genome sequences to estimate the effective population size (N_e) and infer the recent and ancient demographic history of populations using different methods. We also aim to integrate the different N_e estimates to improve our understanding of the evolutionary history and current demography of this great ape and to discuss the strengths and limitations of each estimator and their complementarity in informing conservation decisions. Results from the PSMC method suggest a large ancestral N_e, likely due to ancient structure over the whole subspecies distribution until approximately 10,000–15,000 years ago. After that, a change in connectivity, a real decrease in size, or a combination of both occurred, which reduced the then still large ancestral population to a smaller size (MSVAR: ~10,000 decreasing to 1,000–6,000 breeding individuals), possibly indicating a fragmentation into coastal and inland subpopulations. In the most recent past, contemporary N_e is close to 500 (GONE: 395–583, NeEstimator: 107–549), suggesting a high risk of extinction. The populations located at the coastal parks may have been small or isolated for several generations and are at higher risk, whereas the ones located inland exhibit higher long-term N_e and can be considered a stronghold for chimpanzee conservation. Through combining different types of molecular markers and analytical methodologies, we tried to overcome the limitations of obtaining high-quality DNA samples from wild threatened populations and estimated N_e at different temporal and spatial scales, which is crucial information to make informed conservation decisions at local and regional scales.

Hybridization, the interbreeding of distinct genotypes, drives evolutionary processes like speciation and adaptation, potentially via phenotypic transgression, where hybrids exhibit novel traits. In crop breeding, research has largely focused on optimizing heterosis to enhance hybrid performance, particularly for traits such as biomass. It is only recently that the ecological implications of hybridization have been considered, highlighting hybridization as a biotic interaction occurring within populations and communities. This shift raises fundamental questions about whether hybrid performance shows consistent patterns across individual and population scales, particularly regarding predictions based on parental genetic distance. Here, we address this question by examining Arabidopsis thaliana F2 hybrids across a wide range of genetic distances, to compare hybrid performance at individual and stand levels. Our results reveal scale-dependent patterns: individual performance peaks at intermediate parental genetic distances, while stand-level performance increases with genetic divergence, particularly in hybrids between relict and non-relict lineages. These results underscore the importance of scale when evaluating hybrid performance, as plant–plant interactions at the group level can alter the collective outcomes of individual performance. Finally, this framework underscores the importance of integrating individual and population perspectives to better understand the outcomes and potential applications of hybridization.

Advances in gene-editing technologies offer opportunities to improve disease management in aquaculture. Gene-editing applications for farmed Atlantic salmon (Salmo salar) include harnessing innate parasite resistance to protect against salmon lice (Lepeophtheirus salmonis). The potential for salmon lice to counter-adapt to changes in the host should be considered. However, salmon farms are highly connected through louse transmission, and so it is important to gauge the impact of new technologies over large scales. Exploring the epidemiology and evolution of lice across a farm network is possible using metapopulation models. Here, we expand upon an eco-evolutionary model to simulate the stocking of theoretical gene-edited Atlantic salmon that rejected lice to a similar degree as the more resistant coho salmon (Oncorhynchus kisutch). Model outputs suggested that such louse resistance would be highly effective at controlling outbreaks and reducing the need for additional delousing treatments. Lice were controlled more efficiently when gene edits were prioritized at key farms in the louse dispersal network. In scenarios where gene edits selected for adaptive traits in the louse population, however, lice rapidly evolved counter-resistance, leading to a significant reduction in treatment efficacy. When highly connected farms were left as refugia (not stocked with edited salmon), the rate of adaptation was slowed, thus extending the effectiveness of gene edits through time. The refuge effect was further enhanced if there were fitness trade-offs to counter-resistance in lice. We note that the long-term benefits of the refugia approach—to individual farms and to the wider industry—must be balanced with the costs in the short term, especially for the refuge farms. Careful planning of how to distribute new technologies can maximize efficiency and help safeguard them against parasite evolution. Spatial eco-evolutionary models are powerful tools for scenario testing that assist with decision making.

Scots pine (Pinus sylvestris L.) is characterized by considerable intraspecific adaptive variability in response to environmental stress factors due to its wide geographical range. Adaptability is key for forestry, promising resilience against upcoming Europe's climate-driven droughts. We studied three provenances of pedigreed Scots pine seedlings from distinct upland and lowland habitats in the Czech Republic. A water deficit was induced in 2-year-old, potted seedlings in a greenhouse. Their physiological responses to drought were investigated at the beginning of growing season during the development of new shoots, and after subsequent summer rewatering. (1) We analyzed several physiological traits to assess their effectiveness in detecting treatment effects: steady-state quantum yield of PSII (QY Lss), maximum quantum yield of PSII (QY max), steady-state non-photochemical quenching (NPQ Lss), needle chlorophyll fluorescence ratio (SFR_R), and needle temperature normalized to ambient temperature (∆T), using a high-throughput phenotyping unit. The divergence in SFR_R, QY max, QY Lss, NPQ Lss, and ΔT suggests that drought stress significantly impacts photosynthetic efficiency and heat dissipation, with recovery occurring after rewatering. (2) We detected differences within and among provenances utilizing a single nucleotide polymorphism genotyping array and linear mixed models integrating estimated genomic relationships to investigate genetic variation in needle functional traits in time. Throughout the experiment, heritability (h² ) varied widely among traits—with QY max and QY Lss showing the greatest variability (from 0 to 0.37), NPQ Lss exhibiting a narrower range aside from two outlier peaks, and SFR_R and ∆T displaying lower variability and lower h² values (0–0.24). The photosynthesis-related traits (QY max, QY Lss) showed the highest genetic variation, underscoring their potential for early-age phenotyping and selection of drought-tolerant genotypes. These findings address practical problems in forest management, particularly in light of changing weather patterns and climate variability, and provide a foundation for advanced optically based, early-age phenotyping to enhance forest resilience.

Salmon lice (Lepeophtheirus salmonis) pose a major challenge to the sustainability of salmon aquaculture due to their capacity to rapidly evolve resistance to parasite control methods. As the effectiveness of chemical treatments has declined, the industry has increasingly relied on preventive strategies to limit initial infections. One such approach is depth-based farming, where fish are held deeper in the water column using submerged cages. These systems reduce exposure to lice, which typically concentrate near the surface. However, there is growing concern that such practices may inadvertently select for lice that are better adapted to deeper swimming, potentially enabling resistance to depth-based interventions. In this study, we investigated whether vertical swimming behaviour in salmon lice larvae is influenced by the depth at which their parents were collected. We sampled 122 adult female lice carrying egg strings from commercial salmon farms using either standard cages (0–20 m) or submerged cages (20–40 m). The first-generation larvae were reared under controlled conditions, and the vertical positioning of 11,291 copepodid larvae was tested in pressure columns simulating a depth of 10 m. Our results revealed a significant interaction between larval depth distribution and the cage type from which the parental lice were sourced (χ² = 278.85, df = 1, p < 0.001). Larvae from standard cages showed a greater tendency to ascend (35% vs. 23%) and were less likely to sink (19% vs. 27%) compared to larvae from submerged cages. These findings suggest that vertical swimming behaviour may be heritable, with submerged cages potentially selecting for deeper-dwelling lice over time. This study provides the first evidence that the depth preference of salmon lice larvae may be influenced by their parents' environment. Understanding this behavioural inheritance is crucial for evaluating the long-term sustainability of submerged cage systems and for developing lice management strategies that anticipate evolutionary responses.

The risk of climate maladaptation is increasing for numerous species, including trees. Developing robust methods to assess population maladaptation remains a critical challenge. Genomic offset approaches aim to predict climate maladaptation by characterizing the genomic changes required for populations to maintain their fitness under changing climates. In this study, we assessed the risk of climate maladaptation in European populations of English yew (Taxus baccata), a long-lived tree with a patchy distribution across Europe, the Atlas Mountains, and the Near East, where many populations are small or threatened. We found evidence suggesting local climate adaptation by analyzing 8616 SNPs in 475 trees from 29 European T. baccata populations, with climate explaining 18.1% of genetic variance and 100 unlinked climate-associated loci identified via genotype-environment association (GEA). Then, we evaluated the deviation of populations from the overall gene-climate association to assess variability in local adaptation or different adaptation trajectories across populations and found the highest deviations in low latitude populations. Moreover, we predicted genomic offsets and successfully validated these predictions using phenotypic traits assessed in plants from 26 populations grown in a comparative experiment. Finally, we integrated information from current local adaptation, genomic offset, historical genetic differentiation, and effective migration rates to show that Mediterranean and high-elevation T. baccata populations face higher vulnerability to climate change than low-elevation Atlantic and continental populations. Our study demonstrates the practical use of the genomic offset framework in conservation genetics, offers insights for its further development, and highlights the need for a population-centered approach that incorporates additional statistics and data sources to credibly assess climate vulnerability in wild plant populations.

The restoration of swampland is vital for the recovery of both biodiversity and cultural values in Aotearoa New Zealand. Syzygium maire, an endemic wetland tree species, is a focus of many wetland restoration efforts. Formerly widespread, extant populations are small, fragmented, and under pressure from myrtle rust. Restoration initiatives may be unknowingly compounding these threats to the species by failing to represent the complete genetic diversity of populations. What genetic diversity remains in remnants and how it is distributed is not known. We therefore aimed to assess the national scale population structure, genetic diversity, and adaptive potential of S. maire to inform species conservation. We identified over 760,000 high-quality single nucleotide variants in 269 reproductive age trees from across the species' range, using low coverage whole genome resequencing. At a national scale, we found five distinct regional-scale genetic clusters, which in turn exhibit local structure and admixture. In the North Island: Northland, Bay of Plenty in the central east, Taranaki in the central west, and Greater Wellington/Manawatū in the south. A single cluster was identified in the South Island, Marlborough. Within-cluster substructure was particularly evident for Greater Wellington/Manawatū. Genetic diversity and fixation indices (F_ST) were relatively uniform across all clusters, and there was some evidence of north to south increase in kinship and shorter time since radiation. These patterns are likely to reflect glaciation cycles that resulted in complex contractions into local microrefugia and subsequent re-radiations of the species over time. Genotype by environment analysis detected genetic variants potentially contributing to environmental adaptation, notably precipitation seasonality. Restoration and conservation goals would best be served by capturing diversity within regional clusters. Information on the geographic and environmentally structured distribution of this tree's genetic diversity supports conservation and restoration strategies through ensuring the complete extant diversity is captured, identifying regions at most risk of genetic degradation, and facilitating planning regarding the movement of adaptive diversity in a changing environment.

The sterile insect technique (SIT), traditionally reliant on gamma irradiation, has been an effective strategy for controlling Bactrocera dorsalis. However, strict regulations governing gamma radiation sources and the limited research on the responses of B. dorsalis to X-ray irradiation have hindered the further development of SIT. This study demonstrated that X-ray dosage, pupal age, and their interaction significantly influenced the emergence parameters of B. dorsalis. Further experiments revealed that irradiating 8-day-old pupae resulted in a significant reduction in flight ability, lifespan, and fecundity in emerging adults. However, optimized doses ranging from 70 to 100 Gy effectively induced complete sterility while exerting minimal adverse effects on male quality. X-ray irradiation induced notable shifts in the gut microbiota composition of B. dorsalis, marked by a reduction in the abundance of Enterobacter, Citrobacter, and Proteus, accompanied by an enrichment of Providencia. Additionally, broad correlations among dominant bacterial genera were observed. Transcriptomic analysis further indicated that irradiation had a profound impact on gene expression in both male and female adults, with 100 and 34 differentially expressed genes (DEGs) identified in females and males, respectively. Gene Ontology (GO) enrichment analysis revealed six enriched GO terms common to both sexes. Correlation analysis suggested potential associations between specific differentially abundant bacterial genera and DEGs. These findings optimize X-ray-based SIT for B. dorsalis and provide new insights into its effects on gut microbiota and gene expression, offering theoretical support for the refinement of SIT strategies.

Biodiversity is under increasing pressure from environmental change, although the scope and severity of these impacts remain incompletely understood. For many species, a lack of information about population-specific responses to future environmental change hinders the development of effective conservation strategies. Here, we use an East African reed frog species complex as a model to explore spatial variation in vulnerability to future environmental changes. Our sampling across two threatened biodiversity hotspots spans the entire geographic range of H. mitchelli and H. rubrovermiculatus in Kenya, Tanzania, and Malawi. Using genome-wide (ddRAD-seq) data, we evaluate levels of neutral genetic diversity and local adaptations across sampling localities. We then integrate spatial approaches (genomic offset, modeled dispersal barriers, and Species Distribution Models) to predict how populations may respond differently to future environmental changes, such as climate warming and predicted land use changes. Based on our analyses, we characterize population structure and identify region-specific management needs that reflect genetic variation among populations and the uneven impacts of predicted change across the landscape. Peripheral populations are most vulnerable to future environmental changes due to (i) low levels of neutral genetic diversity (Malawi and Pare mountains in Tanzania), (ii) putative signals of local adaptation to wetter conditions with predicted disruptions to genotype–environment associations (i.e., high genomic offset, Kenya and Northern Tanzania), and (iii) the projected contraction of suitable habitat, which is a pervasive threat to the species complex in general. Populations in Northern, Central, and Southern Tanzania show the lowest vulnerability to environmental change and may serve as important reservoirs of genetic diversity for potential future genetic rescue initiatives. Our study highlights how populations across different parts of species ranges may be unevenly affected by future global changes and provides a framework to predict which conservation actions may help mitigate these effects.