Biology subjects

Pfenninger, M.

Publications and source records attributed to Pfenninger, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Standing Genomic Variation inferred by popGWAS Predicts Seedling Drought Survival Experiment in Fagus sylvatica

Intensifying drought regimes across Central Europe, driven by global climate change, pose an increasing threat to forest regeneration, with the seedling stage representing the primary demographic bottleneck for long-lived tree species such as Fagus sylvatica. While intraspecific phenotypic variation in drought resistance among beech seedlings has been documented, the genomic basis of this variation remains poorly understood. Existing provenance trial approaches capture broad-sense heritability but lack the resolution to identify specific causal loci. To address this gap, we conducted a controlled soil drought experiment with Fagus sylvatica seedlings and applied a population-level genome-wide association study (GWAS), and leveraged individual survival length as a direct fitness proxy. We detected substantial variation in survival duration (10-40 days) among populations, with corresponding allele frequency differences at candidate loci whose functional annotations partially reflect known responses to environmental stress. Notably, seedlings sourced from an official seed bank consistently underperformed relative to wild-collected material, suggesting that current seed sourcing practices may inadvertently deplete adaptive genetic diversity. Our results demonstrate that standing genomic variation in natural Fagus sylvatica populations predicts differential seedling drought survival, and that the species retains substantial genetic potential to cope with prolonged spring drought when natural genetic diversity is preserved. These findings have direct implications for assisted migration strategies and seed sourcing guidelines under projected climate scenarios.

evolutionary biology↗

bioRxiv2026

Local Adaptation of the Spontaneous Mutation Rate: Divergent Thermal Reaction Norms in Chironomus riparius

The germline mutation rate {micro} is a fundamental evolutionary parameter, yet its plasticity in response to environmental factors, particularly temperature, remains poorly understood. While often modeled as a species-specific constant, we tested whether {micro} evolves in response to local thermal regimes. Using whole-genome sequencing of mutation accumulation lines in the non-biting midge Chironomus riparius, we demonstrate divergent thermal reaction norms between populations from climatically distinct regions: Central Europe (Germany) and the Mediterranean (Spain). The Central European population displays a highly plastic, U-shaped reaction norm, whereas the Mediterranean population exhibits a more canalized, temperature-insensitive response. This divergence conforms to theoretical expectations: the higher thermal variance of high-latitude habitats selects for plasticity, while thermally more stable Mediterranean habitats favour robustness and optimises the mutational load in the respective thermal regimes. Furthermore, population-specific mutational spectra (Ts/Tv ratios) indicated evolved differences in DNA repair machinery. However, this is only partially mirrored by Reactive Oxygen Species (ROS) dynamics, where Mediterranean larvae maintain lower ROS levels and a buffered response to thermal extremes. These findings provide evidence for evolution of the mutation rate itself, challenging the assumption of constancy.

evolutionary biology↗

bioRxiv2026

Climate change intensifies rapid genomic selection beyond the ancestral niche of Fagus sylvatica

As climate change accelerates, the persistence of long-lived organisms increasingly depends on their capacity to adapt in situ. While phenotypic plasticity provides an immediate buffer, it remains uncertain whether forest trees can evolve rapidly enough to track shifting climatic niches. Here, we investigate the adaptive potential of European beech (Fagus sylvatica L.), a keystone temperate species, by leveraging different growth classes as a quasi-time-series. This approach allows us to compare growth classes established under the relatively stable climate of the early 20th century against those regenerating under contemporary warming (+1.1{degrees}C global mean temperature increase). Integrating pool-seq data from three growth classes across 43 sites in Germany with satellite-derived environmental stress indicators, we characterised past, current and projected future climate-driven selection. We detected rapid, genome-wide selective sweeps between the oldest and youngest growth classes, particularly in sites already exceeding their historical climatic niche (defined as the 95% confidence interval of pre-warming conditions). Notably, selection signatures have shifted over time: while older classes show signatures related to biotic interactions, younger cohorts exhibit intense selection on genes managing abiotic heat and drought stress. In the warmest regions, we estimated exceptionally high selection coefficients (s{approx}2), suggesting intense selection where beech trees exceed their ancestral niche. In older growth classes, distance and geology account for genetic differences between populations but in young growth classes climate is the primary factor, highlighting the importance of climate change. However, predictive modelling reveals a critical threshold to this resilience. While adaptive potential appears sufficient to maintain population persistence under low-emission scenarios (SSP1-2.6), high-emission trajectories (SSP5-8.5) are projected to rapidly outpace the species evolutionary capacity. These findings demonstrate that while trees can undergo remarkably rapid genomic shifts, the sheer velocity of unmitigated climate change threatens to exceed the fundamental limits of forest adaptation.

evolutionary biology↗

bioRxiv2025

Genes shielded, repeats exposed: mutation bias in the midge Chironomus riparius

Mutation is the fundamental source of genetic variation, yet growing evidence shows that mutations are not uniformly distributed across genomes but are shaped by genomic architecture, DNA-repair dynamics, and environmental conditions. Here, we investigate fine-scale determinants of mutation distribution in the non-biting midge Chironomus riparius, an ecologically important freshwater insect widely used in ecotoxicology. We integrated mutation data from five independent studies, including spontaneous mutation-accumulation experiments and multigenerational exposure assays involving cadmium, benzo[a]pyrene, tyre and road wear particles, and varying generational time. In total, we analysed 420 single-nucleotide mutations mapped to the chromosome-scale C. riparius reference genome. Using a Bayesian modelling framework, we tested whether mutation density is (i) randomly distributed, (ii) non-randomly distributed, or predicted by (iii) distance to telomeres and centromeres, (iv) proximity to genes, or (v) distance to repetitive elements. Models were compared using leave-one-out cross-validation (LOO-CV). We also quantified the proportion of mutations in exons and evaluated the synonymous vs. non-synonymous spectrum using BayesFactor in R. The best-supported model incorporated non-linear effects of genomic position and distance to genes, identifying proximity to coding regions as the dominant predictor of mutation rate. Mutation density increased with distance from genes, indicating strong protection of genic regions. A model including repetitive elements showed nearly equivalent support, suggesting that functional and structural features jointly shape mutational landscapes. Only 9.8% of mutations occurred in exons despite exons representing 22.85% of callable sites, demonstrating marked depletion of exonic mutations. Among exonic mutations, 70.7% were non-synonymous--statistically indistinguishable from the neutral expectation (75%). These findings show that mutation processes in C. riparius are strongly structured by genome architecture, with implications for evolutionary genomics, ecotoxicology, and population-genetic inference.

evolutionary biology↗

bioRxiv2025

A Trade-off Between Developmental Speed and Replication Fidelity Governs the Spontaneous Mutation Rate

The spontaneous mutation rate () is shaped by two potentially opposing forces: the passage of chronological time, which is inevitably associated with mutation accumulation, and the speed of development, which may compromise replication fidelity. Disentangling these forces has been a major challenge, particularly in ectotherms. Testing the competing predictions of the classic time-dependent Generation Length Hypothesis and the replication-dependent speed-fidelity trade-off model, we experimentally assessed individuals with short (mean 15 days) and long (mean 37.7 days) generation time (GT) in the midge Chironomus riparius under constant temperature and estimated the de novo mutation rates by whole genome sequencing. We found that long-GT lines accumulated 1.3-fold more mutations per generation (/gen), consistent with time-dependent mutagenic processes. Conversely, short-GT lines exhibited a nearly two-fold higher mutation rate per day (/day) and a trend towards a transition-biased mutational spectrum (Ts/Tv ratio = 1.28 vs. 0.95), a pattern consistent with a speed-fidelity trade-off in DNA replication. These results suggest that two distinct processes shaped the overall mutation rate. Integrating our data with previous studies and life-history data, we show that the daily mutation rate followed a non-linear relationship with respect to generation time, and that the species generation time mode coincides with its minimum. This suggests that the generation time is, amongst other factors, selected to optimise the mutational load by balancing between replication accuracy and developmental speed. Teaser TextThe spontaneous mutation rate () is governed by a fundamental trade-off between the passage of time and the speed of development. We used the midge Chironomus riparius to experimentally disentangle these forces. We show that rapid development comes with a cost: compromised DNA replication fidelity and a high daily . Conversely, prolonged development accumulates mutations over time. Crucially, the species optimal generation time balances these opposing forces, falling precisely at the developmental speed that minimizes the overall mutational load, suggesting that selection for replication accuracy helps shape life-history evolution.

evolutionary biology↗

bioRxiv2025

Pollution-Driven Selection in Riparian Ecosystems: Genome-Wide Responses to Bacillus thuringiensis israelensis and Copper in a Non-biting Midge

Riparian ecosystems are vital interfaces between aquatic and terrestrial environments but are increasingly impacted by anthropogenic pollution. In these systems, merolimnic insects serve as crucial ecological links, occupying aquatic habitats as larvae and terrestrial environments as adults, thus being an essential food source in both. Consequently, pollutant exposure during the aquatic larval stage can have cascading effects across ecosystem boundaries. While the ecological consequences of such exposure are well documented, the evolutionary potential of merolimnic insects to adapt to chronic pollution remains poorly understood. To address this, we previously conducted a selection experiment exposing populations of the non-biting midge Chironomus riparius to the mosquito larvicide Bacillus thuringiensis israelensis (Bti) or heavy metal copper over approximately eight generations, which revealed only limited evidence of consistent phenotypic adaptation. Here we use whole-genome sequencing of these populations to assess their genomic responses to chronic pollutant exposure. Despite similar phenotypic sensitivity in pre-exposed and naive populations, we detected distinct stressor-specific genomic responses. Copper exposure induced a significant genome-wide reduction in nucleotide diversity and evidence of selection-driven allele frequency changes, while Bti effects were dominated by heterogeneous, replicate-specific shifts, potentially reflecting drift or selection on multiple redundant pathways. Functional enrichment analyses indicated early-stage adaptation: immune- and apoptosis-related pathways were enriched under Bti, while metal detoxification and DNA repair pathways were enriched under copper, highlighting distinct adaptive mechanisms despite weak genome-wide signals of selection. Our findings demonstrate that Evolve and Resequencing approaches enable the detection of early genomic signals of adaptation even when phenotypic change is subtle or absent, offering a powerful framework for studying evolutionary responses to environmental pollution.

evolutionary biology↗

bioRxiv2025

Pervasive and dynamic release of Cryptic Genetic Variation in Chironomus riparius: Rethinking adaptation in fluctuating environments

The interplay between phenotypic plasticity and cryptic genetic variation (CGV) is crucial for understanding adaptation, yet the prevailing paradigm suggests CGV is primarily exposed under novel or extreme conditions. By examining gene expression responses along a natural temperature gradient in Chironomus riparius, we challenged this view. We found that the vast majority of expressed genes (63%) exhibit dynamic CGV, where interindividual expression variability scales continuously with distance from the selectively optimal temperature, a pattern also observed in higher-level traits like mutation rate and ROS levels. Genes with lower overall expression levels were less temperature-regulated, and thermal reaction norm shapes varied with gene function. Unexpectedly, thermally plastic genes were more pleiotropic, often acting as hub genes, while CGV in gene expression was associated with lower pleiotropy. This pattern, and the observed strong recurrent selection on plastic genes with CGV, aligns with C. ripariuss adaptation to its highly fluctuating environment through selective tracking. We propose that this continuous, dynamic release of genetic variation is a necessary and inherent outcome of the polygenic nature of traits. This model fundamentally reshapes our understanding of adaptation, implying that populations can gradually and continuously adapt without requiring harsh conditions to expose hidden diversity. This leads to smoother adaptive landscapes, enhancing rapid adaptation and facilitating evolutionary innovation in the face of ongoing environmental change.

evolutionary biology↗

bioRxiv2025

Influence of geography, seasonality and experimental selection on Chironomus riparius recombination rates

BackgroundUnderstanding recombination rates is crucial in evolutionary biology, as recombination shapes genetic diversity, natural selection, and adaptation. We investigated recombination rate variation in Chironomus riparius across different latitudes, seasons, and experimental treatments using Pool-seq data from five studies and the ReLERNN neural network-based method. We examined its relationship with genetic diversity, GC content, and FST, assessing causality through structural equation modeling. ResultsIn natural populations, recombination rates showed no clear latitudinal pattern, likely due to interactions between climate-driven selection and regional environmental heterogeneity. However, seasonal variation was evident, with higher recombination rates in autumn than winter, possibly due to temperature-induced plasticity or seasonal bottlenecks. A cold snap in March 2018 triggered a sharp recombination increase, potentially suggesting a stress-induced adaptive response. In experimental populations, thermal regimes had no direct effect on recombination, but adaptation to lab conditions was significant. Environmental stressors produced distinct responses: microplastic exposure reduced recombination genome-wide, likely due to stress-induced DNA repair prioritizing genome integrity, while cadmium exposure generally suppressed recombination. ConclusionsOur findings reveal recombination as a highly dynamic process influenced by environment, selection, and genetic background, underscoring the importance of the context in shaping genomic architecture under both natural and experimental conditions.

evolutionary biology↗

bioRxiv2025

Dissecting Oxidative Stress and Organismic Response to various Temperature Regimes in the midge C. riparius

Oxidative stress, driven by reactive oxygen species (ROS), poses a major challenge for organisms facing temperature fluctuations. This study provides the first direct in vivo measurements of ROS production in an insect, Chironomus riparius, across a broad range of ecologically relevant temperatures. We observed a U-shaped pattern of oxidative stress, with minimal ROS levels within an optimal thermal window (12-18{degrees}C) and significantly elevated stress at both cold and warm extremes. Crucially, our findings reveal distinct underlying molecular mechanisms for ROS generation at these extremes: at low temperatures, ROS production is predominantly of the superoxide group, linked to hypoxia-induced hemoglobin autoxidation. Conversely, at high temperatures, the hydrogen peroxide group dominates, associated with increased metabolic rate and heat stress signaling pathways. Transcriptomic analysis shows that C. ripariuss antioxidant defense system adapts accordingly, selectively upregulating mechanisms to counteract the specific dominant ROS type at different temperatures. This mechanistically differentiated oxidative stress and the modulated organismic response profoundly impacts the overall ecological success and evolution of C. riparius as a model for thermal stress in ectotherms. Summary StatementThis study shows that cold and heat stress activate different oxidative damage pathways in midge larvae, explaining how organisms face unique physiological limits in thermal extremes.

ecology↗

bioRxiv2025

The Genomic Basis of Social Parasitism: A Geographical Mosaic of Behavioural, Chemical, and Environmental Adaptations in a Widespread Host-Parasite System

Coevolutionary dynamics in host-parasite systems are driven by reciprocal selection and environmental pressures. When parasite and host are closely related and have similar evolutionary potentials, evolution may follow parallel trajectories, affecting the same traits and underlying genes. We investigated coevolution and its genomic basis in the dulotic ant parasite Temnothorax americanus and its host T. longispinosus across a broad climatic gradient using population genomics, genome-wide association and transcriptome analyses. Population genomics revealed a striking contrast: panmictic host populations versus structured parasite populations, consistent with geographic mosaic dynamics. Genomic responses to parasite prevalence were strongly asymmetric: hosts showed strong selection on immune and structural defence genes, potentially with pleiotropic social functions. Parasites exhibited weaker signals, often in regulatory genes linked to behavioural shifts critical for raiding. Both species displayed shared genomic signatures of climate adaptation (e.g., desiccation resistance, stress response), suggesting convergent physiological responses. Genes associated with host-parasite encounters (mechanosensation, circadian rhythms, venom) also showed parallel selection. Behavioural traits such as aggression showed limited genomic signals but potentially higher transcriptional plasticity. Associations with chemical traits revealed shared selection on genes involved in cuticular hydrocarbon biosynthesis and chemosensory perception, indicating evolutionary coupling of signal production and perception. Constitutive gene expression patterns diverged: host expression correlated with parasite prevalence, while parasite expression was more strongly linked to climate, reflecting contrasting regulatory pressures. Our study demonstrates how differing population structures, asymmetric reciprocal selection, and environmental context shape divergent genomic trajectories of coadaptation, reflecting distinct evolutionary architectures across a heterogeneous landscape.

evolutionary biology↗

bioRxiv2025

Beyond acute toxicity: evolutionary response by rapid polygenic adaptation to a complex environmental stressor in Chironomus riparius

Anthropogenic stressors, such as pollution, habitat degradation, and climate change, are altering selective pressures on natural populations, but the evolutionary consequences of chronic exposure to complex mixtures of contaminants remain poorly understood. Addressing this knowledge gap is critical to the emerging field of evolutionary ecotoxicology, which aims to understand how long-term exposure to environmental contaminants shapes adaptive evolution and genome-wide variation. In this study, we employed urban runoff sediment as complex and environmentally realistic model stressor to investigate how multigenerational exposure affects fitness and potentially drives genomic adaptation in the freshwater midge Chironomus riparius. We combined an evolutionary life-cycle test with the Evolve and Resequence (E&R) approach, exposing replicate populations over seven generations to three treatments: an uncontaminated control and two concentrations of urban runoff sediment (0.5% and 10%). Key fitness traits, including mortality, mean emergence time (EmT50), fertility, and population growth rate (PGR), were measured, while allele frequency changes (AFC) were tracked to identify genomic signatures of selection. The results revealed distinct and non-linear fitness responses across treatments, including transgenerational effects, recovery of performance, and evidence of life-history trade-offs. Candidate haplotypes were enriched for genes involved in membrane transport, metabolism, and gene regulation, suggesting selection on general stress-response pathways consistent with polygenic adaptation. Signals of selection were also detected in control populations, underscoring the evolutionary influence of laboratory conditions. Overall, our findings demonstrate how evolutionary ecotoxicology can reveal both the potential and the constraints of rapid adaptation to realistic environmental stressors and highlight the importance of integrating evolutionary perspectives into ecological risk assessment.

evolutionary biology↗

bioRxiv2025

Predicting forest tree leaf phenology under climate change using satellite monitoring and population-based GWAS

Leaf phenology, a critical determinant of plant fitness and ecosystem function, is undergoing rapid shifts due to climate change, yet its complex genetic and environmental drivers remain incompletely understood. Understanding the genetic basis of phenological adaptation is crucial for forecasting forest responses to a changing climate. Here, we integrate multi-year satellite-derived phenology from 46 Fagus sylvatica (European beech) populations across Germany with a population-based genome-wide association study to dissect the environmental and genetic drivers of leaf-out day (LOD) and leaf shedding day (LSD). We show that environmental factors, particularly temperature forcing and water availability, are the primary drivers of LOD variation, while LSD is influenced by a more complex suite of climatic cues. Our genomic analysis identifies candidate genes associated with LOD and LSD, primarily linked to circadian rhythms and dormancy pathways, respectively. Furthermore, genomic prediction models incorporating these loci accurately reconstruct past phenological dynamics, providing a powerful framework to forecast forest vulnerability and adaptation to future climate change.

evolutionary biology↗

bioRxiv2024

Enhancing Detection of Polygenic Adaptation: A Comparative Study of Machine Learning and Statistical Approaches Using Simulated Evolve-and-Resequence Data

Detecting signals of polygenic adaptation remains a significant challenge in population genomics, as traditional methods often struggle to identify the associated subtle, multi-locus allele-frequency shifts. Here, we introduced and tested several novel approaches combining machine learning techniques with traditional statistical tests to detect polygenic adaptation patterns in time-series of allele frequency changes from whole genome data. We implemented a Naive Bayesian Classifier (NBC) and One-Class Support Vector Machines (OCSVM), and compared their performance against the classical Fishers Exact Test (FET). Furthermore, we combined machine learning and statistical models (OCSVM-FET and NBC-FET), resulting in 5 competing approaches. Using a simulated data set based on empirical evolve-and-resequencing Chironomus riparius genomic data, we evaluated methods across evolutionary scenarios, varying in generations, selection strength and numbers of loci under selection. Our results demonstrate that the combined OCSVM-FET approach consistently outperformed competing methods, achieving the lowest false positive rate, highest area under the curve, and high accuracy. The performance peak aligned with what we term the late dynamic phase of adaptation--the period after initial selection has occurred but before fixation--highlighting the methods sensitivity to ongoing selective processes and thus its value for experimental approaches. Furthermore, we emphasize the critical role of parameter tuning, balancing biological assumptions with methodological rigor. Our approach offers a powerful tool for detecting polygenic adaptation from time series, e.g. pool sequencing data from evolve-and-resequence experiments.

genetics↗

bioRxiv2024

Transcriptomics predicts Artificial Light at Night's (ALAN) impact on fitness: nightly illumination alters gene expression pattern and negatively affects fitness components in the midge Chironomus riparius (Diptera:Chironomidae)

The emission of artificial light at night (ALAN) is rapidly increasing worldwide. Yet, evidence for its detrimental effects on various species is accumulating. While the effects of ALAN on phenotypic traits have been widely investigated, effects on the molecular level are less well understood. Here we aimed to integrate the effects of ALAN at the transcriptomic and the phenotypic level. We tested these effects on Chironomus riparius, a multivoltine, holometabolous midge with high ecological relevance for which genomic resources are available. We performed life-cycle experiments in which we exposed midges to constant light and control conditions for one generation. We observed higher EmT50 and reduced fertility under ALAN. From the observed decline in population size due to the reduced fertility, we predicted the population size to decline to 1% after 200 days. The transcriptomic analysis revealed expression changes of genes related to circadian rhythmicity, moulting, catabolism and oxidative stress. From the transcriptomic analysis we hypothesised that under ALAN, oxidative stress is increased, and that moulting begins earlier. We were able to confirm both hypotheses in two posthoc experiments, showing that transcriptomics are a powerful tool in predicting physiological outcomes before they are even observable.

molecular biology↗

bioRxiv2024

Exposure to complex mixtures of urban sediments containing Tyre and Road Wear Particles (TRWPs) increases the germ-line mutation rate in Chironomus riparius

Tyre and road wear particles (TRWPs) are a significant yet often underestimated source of environmental pollution, contributing to the accumulation of microplastics and a complex mixture of contaminants in both terrestrial and aquatic ecosystems. Despite their prevalence, the long-term evolutionary effects of TRWPs, beyond their immediate toxicity, remain largely unknown. In this study, we assessed mutagenicity in the non-biting midge Chironomus riparius, upon exposure to urban sediment collected from a runoff sedimentation basin. To assess the extent of mutagenic effects over multiple generations, we combined the urban sediment exposure model with short-term mutation accumulation lines (MALs) and subsequent whole genome sequencing (WGS). Our results reveal that the exposure to urban sediment significantly increases mutation rates compared to control groups by 50%, independent of concentration (0.5% and 10%). To infer potential causal processes, we conducted a comparative analysis with known mutational spectra from experiments with other studies. This comparison showed that the mutation profiles induced by urban sediment clearly clustered with those caused by Benzo[a]Pyrene (BaP), a known polycyclic aromatic hydrocarbon (PAH). A comprehensive chemical characterization of the sediment confirmed a considerable impact of road runoff and traffic-related contamination, including PAHs of primarily petrogenic origin. This suggests that PAH-like compounds present in urban sediments may play a significant role in the observed mutagenic effects. Our study shows that urban sediments influence mutation rates and alter mutational spectra in exposed organisms, potentially compromising genomic stability and shaping evolutionary trajectories. Additionally, we show that comparatively analysing mutational spectra may provide valuable insights into mutational processes. These genetic changes may have profound long-term effects on population dynamics and ecosystem health, underscoring the importance of understanding the evolutionary consequences of environmental pollution.

evolutionary biology↗

bioRxiv2024

On the potential for GWAS with phenotypic population means and allele-frequency data (popGWAS)

It is vital to understand the genomic basis of differences in ecologically important traits if we are to understand the impact of global change on biodiversity and enhance our ability for targeted intervention. This study explores the potential of a novel genome-wide association study (GWAS) approach for identifying loci underlying quantitative polygenic traits in natural populations, based on phenotypic population means and genome-wide allele frequency data as obtained e.g. by PoolSeq approaches. Extensive population genetic forward simulations demonstrate that the approach is generally effective for oligogenic and moderately polygenic traits and relatively insensitive to low heritability. However, applicability is limited for highly polygenic architectures and pronounced population structure. The required sample size is moderate with very good results being obtained already for a few dozen populations scored. When combined with machine learning for feature selection, the method performs very well in predicting population means. The data efficiency of the method, particularly when using pooled sequencing and bulk phenotyping, makes GWAS studies more accessible for research in biodiversity genomics. Moreover, in a direct comparison to individual based GWAS, the proposed method performed constistently better with regard to the number of true positive loci identified and prediction accuracy. Overall, this study highlights the promise of popGWAS for dissecting the genetic basis of complex traits in natural populations.

evolutionary biology↗

bioRxiv2023

Phenotypic drought stress prediction of European beech (Fagus sylvatica) by genomic prediction and remote sensing

Current climate change species response models usually not include evolution. We integrated remote sensing with population genomics to improve phenotypic response prediction to drought stress in the key forest tree European beech (Fagus sylvatica L.). We used whole-genome sequencing of pooled DNA from natural stands along an ecological gradient from humid-cold to warm-dry climate. We phenotyped stands for leaf area index (LAI) and moisture stress index (MSI) for the period 2016-2022. We predicted this data with matching meteorological data and a newly developed genomic population prediction score in a Generalised Linear Model. Model selection showed that addition of genomic prediction decisively increased the explanatory power. We then predicted the response of beech to future climate change under evolutionary adaptation scenarios. A moderate climate change scenario would allow persistence of adapted beech forests, but not worst-case scenarios. Our approach can thus guide mitigation measures, such as allowing natural selection or proactive evolutionary management.

evolutionary biology↗

bioRxiv2022

Genomic profiling of climate adaptation in Aedes aegypti along an altitudinal gradient in Nepal indicates non-gradual expansion of the disease vector

BackgroundDriven by globalization, urbanization and climate change, the distribution range of invasive vector species has expanded to previously colder ecoregions. To reduce health-threatening impacts on humans, insect vectors are extensively studied. Population genomics can reveal the genomic basis of adaptation and help to identify emerging trends of vector expansion. ResultsBy applying whole genome analyses and genotype-environment associations to populations of the main dengue vector Ae. aegypti, sampled along an altitudinal temperature gradient in Nepal (200- 1300m), we identify adaptive traits and describe the species genomic footprint of climate adaptation to colder ecoregions. We found two clusters of differentiation with significantly different allele frequencies in genes associated to climate adaptation between the highland population (1300m) and all other lowland populations ([≤] 800 m). We revealed non-synonymous mutations in 13 of the candidate genes associated to either altitude, precipitation or cold tolerance and identified an isolation-by-environment differentiation pattern. ConclusionOther than the expected gradual differentiation along the altitudinal gradient, our results reveal a distinct genomic differentiation of the highland population. This finding either indicates a differential invasion history to Nepal or local high-altitude adaptation explaining the populations phenotypic cold tolerance. In any case, this highland population can be assumed to carry pre-adapted alleles relevant for the species invasion into colder ecoregions worldwide that way expanding their climate niche.

genomics↗