Evolutionary Applications最新文献

Understanding crop domestication offers crucial insights into the evolutionary processes that drive population divergence and adaptation. It also informs the identification of genetically diverse wild germplasm, which is essential for breeding and conservation efforts. While domestication has been extensively studied in many Mediterranean fruit trees, the evolutionary history of the almond (Prunus dulcis) remains comparatively underexplored. To address this, we analyzed 209 wild and cultivated almond accessions sampled across Eurasia and genotyped with 23 microsatellite markers. Using population genetics and coalescent-based inference, we reconstructed the domestication history of P. dulcis and its relationships with wild relatives. Bayesian clustering revealed four genetically distinct clusters of cultivated almonds: Turkish, Caucasian–Central Asian, Southern Spanish, and European/North American. These groups were differentiated from wild almond species—including Prunus turcomanica, Prunus orientalis, Prunus fenzliana, and Prunus spinosissima—each forming its gene pool across the Middle East and Central Asia. Approximate Bayesian Computation (ABC) supported a single domestication event in the Middle East, originating from either P. orientalis or P. turcomanica, with subsequent gene flow from P. fenzliana and P. spinosissima into the Turkish and Central Asian cultivated gene pools, respectively. We also inferred reciprocal introgression from cultivated almonds back into wild populations. Notably, sharka resistance—caused by plum pox virus (PPV)—was identified in three P. dulcis clusters and P. fenzliana, suggesting that resistance may have arisen independently or been maintained through crop–wild introgression. Together, our results highlight a complex and protracted domestication history for almond, shaped by contributions from multiple wild relatives and recurrent gene flow. These findings enhance our understanding of perennial crop evolution and underscore the value of wild germplasm in breeding programs aimed at increasing resilience in fruit trees.

The main theory of the evolution of virulence relies on a trade-off between virulence and transmission rate. However, it has been difficult to measure the required trade-off. A recent transmission decomposition framework explains that this might be partly due to a lack of information about the parasite's survival in the environment outside its hosts, where the parasite finds itself during transmission to its next host. In this study, we used parasite lines of the microsporidian Vavraia culicis with varying levels of virulence upon infecting their host, the mosquito Anopheles gambiae, to explore the interaction between parasite-driven virulence within its host and its survival outside of the host. The parasite lines with greater virulence and growth within their hosts had a cost in their intrinsic ability to withstand the environment, irrespective of temperature. These results underscore the importance of considering the full context of transmission and other parasite fitness traits in studying and predicting the evolution and spread of infectious diseases.

Genomic tools are becoming increasingly necessary for mitigating biodiversity loss and guiding management decisions in the context of climate change. Freshwater fish species are particularly susceptible to the impacts of changing environments, including kokanee, the resident form of sockeye salmon (Oncorhynchus nerka), which has already been negatively impacted by increases in extreme temperature throughout its distribution. A previous study using whole genome resequencing of wild kokanee stocks identified 1412 environmentally associated SNPs and demonstrated genomic offset, a measure of climate vulnerability, to be significantly correlated with higher increases in extreme warm temperatures across much of the species' range in western Canada. Here, we aimed to operationalize this information for fisheries management by first developing a Genotyping-in-Thousands by sequencing (GT-seq) panel populated exclusively with environment associated SNPs. We then evaluated the robustness of the GT-seq panel relative to the signal in the whole genome resequencing baseline and demonstrated a novel application of donor and recipient importance (DI/RI) analysis to inform recreational fisheries stocking decisions. We found that a reduced GT-seq panel of 616 SNPs exhibited a significant positive correlation with those calculated from the full set of 1412 SNPs across the climate change scenarios tested; similar results were obtained when adding new reference populations not included in the original whole genome resequencing baseline. The DI/RI analysis revealed clear spatial trends, with populations situated in the warmest regions of southern interior British Columbia (Canada) having the highest probability for successful translocations to different recipient locations to the north. Similarly, candidate recipient lakes for stocking at the center of the distribution had higher recipient importance values than those located towards the eastern and western range peripheries. Although further refinement is required, pairing targeted genotyping with genomic offset and DI/RI predictions holds great promise for informing freshwater fisheries management moving forward.

Habitat loss and fragmentation are major drivers of biodiversity decline, reducing connectivity among populations and leading to genetic isolation, loss of diversity, increased inbreeding, and reduced fitness. Translocations that promote gene flow by introducing genetically distinct individuals—a process known as genetic rescue—can mitigate these effects by increasing genetic diversity, alleviating inbreeding, and improving adaptive capacity. However, a limited understanding of a population's demographic history, genetic differentiation, and connectivity can hinder the effective application of genetic rescue. We used the Stephens' kangaroo rat (Dipodomys stephensi), a species threatened by habitat loss and fragmentation in southern California, as a model for developing range-wide genetic management strategies. We analyzed mitochondrial DNA and microsatellite data to investigate genetic structure and estimate both historical and recent demographic patterns, and we used landscape resistance modeling to assess the impacts of natural and anthropogenic barriers on gene flow. Genetic analyses suggest a relatively recent diversification of Stephens' kangaroo rat populations, with higher allelic diversity concentrated in central populations and reduced diversity in isolated northern and southern populations. Although natural geographic features explain much of the genetic structure, landscape resistance models showed that anthropogenic barriers (e.g., roads, development) play a key role in current genetic isolation and are expected to continue driving population differentiation. To guide management, we used population viability simulations to test translocation strategies aimed at reversing genetic erosion. Repeated translocations were far more effective than single events at boosting heterozygosity and population persistence. The frequency and size of translocations were less important than their continued implementation. For very small populations, concurrent habitat restoration to increase carrying capacity was essential to prevent extirpation. Our findings highlight the value of integrating genetic, demographic, and landscape data into conservation planning. This approach is broadly applicable to other species experiencing habitat fragmentation and population isolation.

Behaviour has crucial importance in dogs' adaptation to the anthropogenic environment. Functional breed selection, a relatively recent evolutionary event, resulted in strong differences regarding dogs' capacity for observational learning from humans. However, genetic distance among dog breeds has thus far not been connected to their social learning performance. Here we show first evidence that ancestry-based clustering of dog breeds can result in biologically relevant phenotypic differences in their capacity to learn from humans. We analysed a large database of spatial problem-solving (detour) tests, where a representative sample (N = 174) of cooperative and independent working dogs were sorted into 8 ancestry groups based on a genetic cladogram. We analysed whether ancestry would affect individual and social learning-based spatial problem-solving of dog breeds. Our results showed that ancestry groups with today's utility dog breeds performed this task best. Social learning was also prevalent in the ancestry group that collects English herding breeds and sight hounds as well—showing that genetically closely related cooperative and independent working dog breeds can possess similar sociocognitive traits. These results strengthen the notion that the behaviour of dog breeds can provide ecologically valid research opportunities both for proximate and ultimate evolutionary events.

The United Kingdom aims to dramatically accelerate the establishment of new woodlands by 2050, yet the impact of different afforestation strategies on landscape genetic diversity and resilience remains unclear. This study integrates environmental data, whole-genome sequencing and phenotypic assessments to compare bioclimatic envelopes, genetic diversity and plant health indicators in naturally colonised versus planted populations of pedunculate oak and silver birch. We found that registered seed stands significantly under-represent the wild bioclimatic envelopes of both species, as well as those of 21 out of 39 UK native species assessed, potentially limiting adaptive diversity in planted populations. Yet, genetic diversity metrics (π, H_O and A_R) based on genome-wide markers in planted populations were comparable to naturally colonised woodlands. Planted populations exhibited higher within-group coancestry and moderate genetic homogenisation among sites, possibly reducing adaptive differentiation. Naturally colonised populations showed higher inbreeding coefficients (F_ROH) in both species, potentially due to fragmentation of source populations. Genotype–environment associations based on redundancy analysis revealed divergent selection at functionally relevant loci, indicating distinct selective pressures in commercial tree production versus natural colonisation. Health indicators revealed reduced browsing in planted trees, and differences in mildew and leaf-spot incidence, suggesting potential selection divergence between afforestation strategies. These findings support a role for both afforestation strategies in enhancing the resilience of future woodlands while highlighting pathway-specific risks of introducing unintended impacts on forest diversity.

Golden pompano (Trachinotus ovatus) is a rapidly growing marine aquaculture species along the southeast coast of China due to its favorable biological traits. However, the relatively short domestication history of marine species compared to terrestrial livestock and crops indicates untapped genetic potential. Therefore, selective breeding in marine aquaculture presents a significant opportunity for genetic improvement. This study aimed to establish a comprehensive genomic prediction to support the selection of new fast-growing varieties of golden pompano. Body weight was selected as the primary trait for evaluating growth traits. Whole-genome sequencing was performed on 692 samples, resulting in 4,886,850 high-quality SNPs after filtering. Three SNP selection strategies were used for evaluating the genomic prediction accuracy, including the Evenly method, GWAS-based method, and Random method. We addressed the issue of overestimation in the GWAS-based method. After implementing cross-validation, the GWAS-based method demonstrated superior predictive accuracy across most SNP sets. Additionally, six breeding models were evaluated for their performance in genomic prediction, with GBLUP showing higher predictive ability. In terms of SNP density, we determined that 5000 SNPs selected via the Evenly method and 7000 SNPs selected via the GWAS-based method represent optimal densities for accurately predicting body weight in golden pompano. These findings provide valuable insights for reducing breeding costs while improving selection accuracy, providing a practical strategy for the selection of golden pompano with economically valuable growth traits in aquaculture breeding programs.

Island populations are at heightened risk of inbreeding due to reduced mating opportunities with unrelated conspecifics. Extensive inbreeding can result in inbreeding depression (reduced fitness of individuals with related parents). Alexander Archipelago wolves (Canis lupus ligoni) are a geographically isolated subspecies that occur in the Southeast Alaskan panhandle, USA, and coastal British Columbia, Canada. Wolves on the Prince of Wales Island complex (POW) in Southeast Alaska are expected to have lower levels of resiliency because they are a small, insular population that has experienced habitat fragmentation and cycles of moderate to heavy harvest. To understand the extent of population structure and inbreeding in Alexander Archipelago wolves, we designed a DNA hybridization capture for wolves and sequenced captured DNA from 58 individuals sampled from across Southeast Alaska during 2002–2016. Estimates of the proportion of the genome in runs of homozygosity (F_ROH) regardless of run length, revealed that POW wolves were most inbred compared to wolves in other areas of Southeast Alaska. Wolves on POW also had more long (≥ 10 Mb) runs of homozygosity than the other populations we assessed, indicating more frequent mating between individuals with recent common ancestors (1–10 generations ago). This pattern indicates a smaller population size for POW wolves in the recent past compared to other Southeast Alaskan populations. Wolves on POW exhibit an extent of inbreeding similar to that observed in Isle Royale National Park wolves, a population that has exhibited severe inbreeding depression. Our work demonstrates the utility of using genomic capture data to infer individual inbreeding so that proactive management (e.g., setting population targets and harvest quotas, curtailing habitat alteration, etc.) can be considered to ensure the long-term sustainability of small, isolated populations.

RNA viruses often comprise multiple variants that co-circulate in a host population, with potentially complex dynamics. Deformed wing virus (DWV), arguably the most impactful virus of honey bees (Apis mellifera), nowadays exists as two major variants, genotypes A (DWV-A) and B (DWV-B), which provide an amenable window into the dynamics of multi-variant pathogens. DWV-B has increased in prevalence over the past two decades in honey bees in Europe, largely replacing DWV-A. DWV-B arrived over a decade ago in the New World, where its prevalence has also increased markedly in temperate North American honey bees. The Yucatan Peninsula of Mexico is home to a high density of both managed and feral Africanized honey bees (AHBs), which are also known to be infected by DWV, though variant dynamics in this tropical location have not been explored. Here, we present two temporally separated datasets on viral prevalence that demonstrate the presence of both DWV genotypes in Yucatecan AHBs in 2010, though with surprisingly little change in the high prevalence of DWV-A and low prevalence of DWV-B through to 2019. Epidemiological modeling suggests that the dynamics of DWV genotypes in AHBs of Yucatan may be due to a form of superinfection exclusion (SIE). We model one potential form of SIE, inter-genotype recombination meltdown. In addition to providing information on the epidemiology of a major honey bee virus in the Neotropics, our results provide broader insight into the evolutionary dynamics of viruses that comprise two or more co-occurring variants.

Insect pollinators play vital regulatory roles within ecosystems and provide humanity with essential services that support our health, wellbeing, and economies. Despite their importance, reported declines at regional and national levels have raised concerns over the continuation of such benefits. Island pollinator populations are of particular conservation interest as they may harbor lower genetic diversity due to restricted gene flow caused by geographical barriers, which may in turn influence local selective processes. In this study, we investigated the population structure and potential targets of selection within the genomes of a bumblebee subspecies, Bombus terrestris audax, native to the islands of Ireland and Great Britain. In particular, we compared the genomes of wild-caught populations from each island alongside representatives of other European subspecies and commercial imports to ascertain patterns of historical admixture. Our analysis identified a largely genetically distinct population of B. t. audax on the island of Ireland, with weak evidence of admixture. In addition, we find differential signatures of positive selection between the two island populations in genes associated with neurology and development, indicating potential local adaptation. Furthermore, we identified an extremely polymorphic region on chromosome 10 with evidence of shared haplotypes in both wild and commercial bees, which may represent long-standing genetic variation at the continental level or potential localized admixture between wild and commercial bees. Collectively, our findings inform on the genetic distinctiveness of these island bumblebees, emphasizing the applied need to genetically characterize natural populations to ensure the conservation of genetic resources-in the context of this study, by informing risk-assessment and management of commercial bumblebees. In addition, our study reinforces the utility of genomic approaches in the biomonitoring of isolated or regionally adapted insect pollinator populations, which will contribute towards the effective conservation of these ecologically vital organisms.