Evolutionary Applications最新文献

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.

The elongate ilisha (Ilisha elongata) is an important commercial species found along the Northwestern Pacific Coast. A sharp decline in the annual catch of I. elongata over recent decades implies a concerning situation regarding its fishery stocks. Nonetheless, inadequate knowledge of the genetic diversity, population structure, and historical demography of this species has hindered the establishment of sustainable fishery policies and appropriate conservation measures. In this study, the genetic structure and population demography of I. elongata stocks along the Northwestern Pacific Coast were examined using target-gene enrichment data from 144 I. elongata individuals collected from 18 locations. The analysis revealed an average heterozygosity value of 0.2321 across variable sites in all I. elongata populations. Furthermore, inter-population differentiation is relatively low, with most geographical populations displaying minimal genetic distinctions or none from one another. Population clustering analysis identified four lineages of I. elongata stocks. Through historical demography simulations, it was proposed that the Yalu River Estuary population diverged initially around 32,802 generations before present, while the remaining lineage split into two about 9120 generations ago. One lineage represents the southern population, while the other further separated into the northern population and the Japanese population approximately 4200 generations ago. Furthermore, secondary contact between the southern and northern population was evidenced by either population clustering or demography simulation results. These results underscore that the current phylogeographic patterns of I. elongata may result from directional selection due to low temperature and geographic barriers during and post glacial periods.

The fall armyworm (FAW), scientifically known as Spodoptera frugiperda, is an agricultural pest native to the American continents. Its larvae display voracious feeding behavior with a host range of over 350 plant species. The pest was first detected outside the Americas in 2016, subsequently spreading across Africa, Asia, and Oceania. As a country with substantial agricultural imports and exposure to regional migration routes, Malaysia presents a valuable case study for investigating the establishment and adaptation of invasive FAW populations. Forty-two novel Malaysian FAW genomes were sequenced on the DNBSEQ-G400 platform via DNBSeq. A subset of high-quality genome-wide single nucleotide polymorphisms was used to compare the evolution of both native and invasive FAW populations, with publicly available samples from another 18 countries from across the world. Our analyses revealed clear genetic differentiation between native and invasive FAW populations. We found little evidence to support West African populations as the founding source for Asian or East African invasions. Instead, Malaysian FAW clustered closely with populations from India, China, and East African countries, suggesting multiple, independent introductions into the region. Genomic outliers related to sensory perception, insecticide resistance, and heat tolerance were detected, likely contributing to the recent global success of FAW invasions. This study provides new genomic insights into the invasion history and adaptive strategies of FAW in Malaysia, contributing to a clearer picture of FAW movement across Asia and Africa. The results provide critical information for future pest management and policy-making to mitigate the spread of this invasive pest.

Musk deer (Moschus), the sole genus in the family Moschidae, are critically endangered and face an uncertain future due to the limited understanding of their taxonomy, evolutionary history, genetic load, and adaptive evolution. These knowledge gaps hinder conservation efforts at crucial stages. Here, we conducted a comprehensive conservation genomic analysis by sequencing eight M. anhuiensis genomes and integrating public data from 15 M. berezovskii individuals. Phylogenomic and population genomic analyses confirmed that M. anhuiensis is a distinct phylogenetic species that diverged approximately 260 thousand years ago (kya). Both species experienced severe population bottlenecks, subsequently exhibiting marked genetic divergence. Over the past 200 kya, M. berezovskii has undergone multiple admixture events and bottlenecks, whereas M. anhuiensis has steadily declined and maintained a small, stable population. Anthropogenic activities have intensified these pressures, leading to sharp declines in both species. Notably, M. anhuiensis has accumulated homozygous deleterious mutations, thereby heightening its extinction risk. Moreover, selective sweep analysis revealed 32 positively selected genes, including olfactory receptor genes (OLF3 and OR6B1), which are essential for foraging, reproduction, and social interactions; the proliferation-related gene (PDGFRA), which responds to environmental changes and injury; and the thermoregulation gene (CDH13), which helps maintain body temperature stability in extreme conditions. These findings shed light on the speciation and evolutionary history of musk deer, offering crucial insights into their local adaptations and vulnerabilities. This work provides a foundation for targeted conservation efforts to avert extinction and safeguard biodiversity.

Next-generation-sequencing has broadened perspectives regarding the estimation of the effective population size (Ne) by providing high-density genomic information. These technologies have expanded data collection and analytical tools in population genetics, increasing understanding of populations with high abundance, such as marine species with high commercial or conservation priority. Several common methods for estimating Ne are based on allele frequency spectra or linkage disequilibrium between loci. However, their specific constraints make it difficult to apply them to large populations, especially with confounding factors such as migration rates, complex sampling schemes or non-independence between loci. Computer simulations have long represented invaluable tools to explore the influence of biological or logistical factors on Ne estimation and to assess the robustness of dedicated methods. Here, we outline several Ne estimation methods and their foundational principles, requirements and likely caveats regarding application to populations of high abundance. Thereafter, we present a simulation framework built upon recent computational genomic tools that combine the possibility to generate biologically realistic data sets with realistic patterns of long-term neutral genetic diversity. This framework aims at reproducing and tracking the main critical features of data derived from a large natural population when running a simulation-based population genetics study, for example, evaluating the strengths and limitations of various Ne estimation methods. We illustrate this framework by generating genotype data sets with varying sample sizes and locus numbers and analysing them with three software tools (NeEstimator2, GONE and GADMA). Detailed and annotated simulation scripts are provided to ensure reproducibility and to support future research on Ne estimation. These resources can support method comparisons and validations, particularly for non-specialists, such as conservation practitioners and students.