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Le Bohec, C.

Publications and source records attributed to Le Bohec, C..

18 recordsLinked to original sources

An epigenetic palimpsest: the King penguin's blood methylome reveals conserved hematopoietic ageing

Age-associated DNA methylation is conserved across vertebrates, but whether epigenetic ageing reflects cellular ageing programmes or age-dependent shifts in cell composition remains unresolved. Here, using 126 whole-blood methylomes from known-age King penguins (Aptenodytes patagonicus), we exploit a vertebrate system in which nucleated erythrocytes dominate peripheral blood, minimizing the influence of leukocyte heterogeneity. We identify a core set of 409 ageing-associated genes showing lifelong, clock-like methylation change. These genes are strongly enriched for regulators of hematopoietic stem and progenitor cell (HSPC) function and niche communication. Integration of methylome, transcriptome and chromatin-accessibility data reveals that many of the strongest ageing signals derive from genes inactive in mature erythrocytes, consistent with the persistence of epigenetic states from ancestral hematopoietic progenitors. A comparison with methylation profiles from 1,501 humans identified a conserved cross-species subset of ageing genes, and a human epigenetic age model constructed solely from orthologues of penguin ageing genes predicts chronological age with high accuracy while remaining largely insensitive to blood cell composition. We propose that blood epigenetic ageing signatures contain a long-lived cellular memory of stem-cell ageing, that may represent an evolutionarily ancient layer of the vertebrate ageing process.

systems biology↗

Monte Carlo simulations to propagate the uncertainty of machine-learning classification into ecological models

Deep learning (DL) is increasingly integrated into quantitative ecology, particularly for automating the classification of sensor data in biodiversity monitoring. In addition to substantially reducing data processing effort, DL models often achieve high classification performance. However, despite ongoing improvements, certain species or classification tasks remain challenging, and predictions are rarely error-free. Manual verification is frequently included into data processing pipelines to mitigate misclassifications, but this approach may mask rather than quantify uncertainty. Here, we propose directly incorporating classification uncertainty into ecological inference, rather than filtering it afterwards. Specifically, we treat model predictions as probabilistic outputs rather than fixed class assignments, by using Monte Carlo simulations to propagate uncertainty from the classification process into downstream ecological models. We illustrate this approach using two case studies. The first estimates stochastic population growth rates for a penguin population using detection time series derived from Radio Frequency IDentification (RFID). The second propagates uncertainty in species identification from camera trap images into occupancy estimates. For both, we compare results obtained propagating classification uncertainty with those from conventional single-class attribution at two confidence score thresholds. Our findings show that propagating uncertainty typically leads to higher, more optimistic ecological estimates compared to the single-class confidence approach. Importantly, this method expands the total uncertainty interval by explicitly introducing the confidence score produced by automatic classification as a representation of uncertainty. Quantifying this uncertainty in parameter estimation allows for more informed and reliable ecological interpretations. Monte Carlo simulations offer a flexible and accessible means to integrate classification uncertainty into diverse ecological modelling workflows.

ecology↗

Multiannual environmental forcing shapes breeding phenology and success in a subantarctic seabird

Climate-driven phenological mismatches threaten avian reproduction by disrupting food availability during critical breeding stages. In marine ecosystems, time lags between environmental changes and their effects on food webs are challenging to model, yet they can have a profound impact on top-predator reproduction. We disentangle how oceanic and climatic variability influence the breeding phenology and success of a keystone seabird of the Southern Ocean drawing on 24 years of data from 17,000 marked king penguins. We document an exceptional 19-day advancement in breeding phenology, alongside increased breeding success (44% in 2000, 62% in 2023). A sliding-window analysis reveals that sea temperature and primary production in key foraging zones predict both phenology and breeding success, with lags ranging from several weeks to two years. While king penguins appear to be keeping pace with current changes, their dependence on multi-year environmental conditions underscores the vulnerability of top predators to unpredictable, fast-changing, and more frequent extreme conditions.

ecology↗

Early-life stress as a potential resilience factor in king penguins

Climate change-driven environmental variability can cause species to shift their phenology, leading to an increase in phenological mismatches. Whether the fitness cost of such mismatches can be mitigated by plasticity remains poorly understood, especially in the context of wild populations. In this study, we quantified responses to phenological mismatch using capture-mark-recapture, morphological, and transcriptomic data from king penguins hatching during and after the seasonal peak of food availability (i.e., born early and late in the breeding season, respectively). Late-born chicks showed reduced survival to fledging and fledged smaller and in slightly poorer body condition than chicks born during the seasonal peak in food availability. Yet post-fledging return rates did not differ between late- and early-born chicks, suggesting that early-life stress was effectively mitigated among individuals that survived to fledging, with no detectable carryover effects in the first years post-fledging. Genes involved in oxidative stress response, homeostasis, and nutrient-sensing were differentially expressed between early- and late-born chicks, consistent with stress mitigation and homeostasis maintenance at the expense of growth in late-born chicks. A co-expression gene cluster whose primary expression pattern was associated with hatching phenology also contained central genes involved in stress mitigation. Together, our findings highlight molecular mechanisms that buffer the fitness costs of phenological mismatch, which may allow species to tolerate mismatch to some extent. Despite higher winter mortality of individuals born in mismatch, the plastic response observed in survivors hints towards molecular adaptations that could allow species resilience under increasing climate-driven environmental unpredictability.

genomics↗

Flexible foraging effort shapes Adelie penguin reproductive success across Antarctica and sea ice conditions

Understanding how species deal with diverse environmental conditions is crucial for predicting their future responses to climate change. In Antarctica, changing sea ice dynamics threaten ice-dependent species. Whilebehavioural adjustmentscould help mitigate these threats, their effectiveness under future environmental conditions and potential thresholds remain unclear. Long-term studies and circumpolar approaches could address this challenge. Our 15-year study (2010-2024) of over 23,000 foraging trips from Adelie penguins (Pygoscelis adeliae) in East Antarctica, identified a non-linear relationship between sea ice concentration (SIC) and foraging effort when landfast ice was absent, a situation anticipated to define the species future habitat during chick-rearing. Minimal effort occurred at 10-20% SIC, but more than doubled with the presence of landfast ice or heavy pack-ice, with females showing greater sensitivity to these ice changes. Acircumpolar analysis of similar data demonstrated that foraging effort during chick-guarding predicted reproductive success across ten Adelie penguin populations. Reproductive success remained high until foraging trips exceeded approximately 29 hours, after which performance declined sharply. This indicates that while behavioural flexibility can buffer against moderate environmental changes, it has clear limits. Our findings establish foraging trip duration as a valuable early warning indicator for population responses to environmental change.

ecology↗

A chromosome-level genome of the King penguin (Aptenodytes patagonicus): an emerging model-in-the-wild for studying evolution

The King penguin (Aptenodytes patagonicus) is an iconic species of the Southern Ocean and is currently being developed as a model-in-the-wild for understanding evolution. We present a high-quality, haplotype-resolved 1.35 Gb chromosome-level genome of an adult female King penguin - Pen/Se-guin - from the Crozet Archipelago, assembled using PacBio HiFi long-read sequencing and Hi-C proximity data. 94.93% of the assembly is assigned to 34 chromosomes (32 autosomes, plus the Z and W chromosomes), with a BUSCO completeness of 97.2%, a k-mer completeness of 99.7%, and a quality value (QV) of 63.8. We also assembled a circularised mitogenome (20,520 bp), which includes the avian tandem duplication (TD). Annotation of repetitive sequences revealed that 16.3% of the genome comprises repetitive elements, with LINEs being the most abundant transposable element class (5.6%). Gene prediction using an extensive multi-tissue RNA-seq dataset resulted in 18,081 predicted protein-coding genes, of which 17,081 were functionally annotated, with a BUSCO completeness of 98.4% and an OMArk completeness of 97.3%. The presented assembly substantially improves the quality of a previous draft genome, showing a 28-fold increase in assembly contiguity and a significantly improved genome annotation, exceeding the standards of the Earth BioGenome Project (EBP) and Vertebrate Genomes Project (VGP). This high-quality genome will enable ongoing and future studies harnessing the King penguin as a model-in-the-wild to test hypotheses on the genotype-to-fitness link, ageing, life-history trait evolution, and adaptation.

genomics↗

Sedentary life accelerates epigenetic ageing in King penguins

Introductory paragraphAdvances in medicine and food security have contributed to an increase in human lifespan1. Yet, the associated rise in sedentary behaviour and in obesity2,3 already threatens these gains4. Indeed, a growing body of evidence supports the central role of nutrient sensing and energy management pathways in regulating ageing rate and healthspan5,6, but the diversity of human lifestyles challenges our ability to identify the genetic and epigenetic drivers of this age acceleration. Here, we examine how the transition of wild King penguins to zoo husbandry can closely mimic the shift to a Western lifestyle in humans, and shed light on evolutionarily conserved epigenetic changes in responses to sedentary conditions. We show that, just like modern humans, zoo-housed King penguins experience an extended lifespan, but this comes at the cost of accelerated epigenetic ageing throughout life. This accelerated ageing is associated with differential methylation in key growth and maintenance pathways including the mTOR and PI3K/Akt networks, as well as in specific pathways of lipid-rich diet adaptation and heart-function. Our results demonstrate the deeply conserved link between sedentary behaviour and food availability on the one hand, and age acceleration on the other. Such evolutionary evidence may in turn help us to improve risk detection and, ultimately, therapeutics for lifestyle-induced age acceleration in humans7.

genomics↗

Declining juvenile survival of Adelie penguins in Antarctica

As summer sea ice around Antarctica reaches modern lows, quantifying the demographic response of polar species to such environmental changes becomes critical. To achieve this, synthesizing results across species ranges and elucidating the environmental factors driving population dynamics are key. Adelie penguins are considered reliable indicators of changes in Antarctica but the processes through which sea ice and other environmental factors shape their population dynamics are still unclear, especially for critical age groups such as juveniles. Using a 17-year dataset of Adelie penguins electronically tagged in Adelie Land (Antarctica), we found that juvenile survival probability was most impacted by sea ice concentration near their natal colony right after fledging, with lower ice concentrations detrimental to survival. Importantly, we found that juvenile survival declined by 32% from 2007 to 2020, mirroring trends at other distant colonies. The emergence of similar patterns at opposite ends of the continent may be an early signal for shifts in population trends expected from climate change.

ecology↗

Gene expression shifts in Emperor penguin adaptation to the extreme Antarctic environment

Gene expression can accelerate ecological divergence by rapidly tweaking the response of an organism to novel environments, with more divergent environments exerting stronger selection and supposedly, requiring faster adaptive responses. Organisms adapted to extreme environments provide ideal systems to test this hypothesis, particularly when compared to related species with milder ecological niches. The Emperor penguin (Aptenodytes forsteri) is the only warm-blooded vertebrate breeding in the harsh Antarctic winter, in stark contrast with the less cold-adapted sister species, the King penguin (A. patagonicus). Assembling the first de novo transcriptomes and analysing multi-tissue (brain, kidney, liver, muscle, skin) RNAseq data from natural populations of both species, we quantified the shifts in tissue-enhanced genes, co-expression gene networks, and differentially expressed genes characterising Emperor penguin adaptation to extreme Antarctic ecology. Our analyses revealed the crucial role played by muscle and liver in temperature homeostasis, fasting and whole-body energy metabolism (glucose/insulin regulation, lipid metabolism, fatty acid beta-oxidation, and blood coagulation). Repatterning at the regulatory level appears as more important in the brain of the Emperor penguin, showing the lowest signature of differential gene expression but the largest co-expression gene network shift. Nevertheless, over-expressed genes related to mTOR signalling in the brain and the liver support their central role in cold and fasting responses. Besides contributing to understanding the genetics underlying complex traits, like body energy reservoir management, our results provide a first insight into the role of gene expression in adaptation to one of the most extreme environmental conditions endured by an endotherm.

evolutionary biology↗

A tipping point in West Antarctica in 2023's circumpolar 5-sigma event? a glimpse from the emperor penguin's perspective

Emperor penguins are one of the seabird species most vulnerable to climate change in Antarctica, as they depend on stable sea ice for breeding and molting. Recent extremes of warming have taken to the lowest records of sea ice in West Antarctica in 2022 and 2023, raising concerns to the extent that emperor penguins have been affected. We evaluated historical satellite data (1985-2022) of sea ice around the 10 emperor penguin breeding colonies, identified so far along the coast of the Amundsen and Bellingshausen Seas, and compared them to recent sea ice cover (2022-2023) to identify where and when critical thresholds of sea ice cover have been crossed. We found that the sea ice retreated below the critical thresholds in 2022-2023 during the chick-rearing and in some cases failed to return at the start of the following breeding season, hence likely affecting 9 of the 10 emperor penguin colonies in the region. This is an unprecedented climatic phenomena affecting breeding habitat of emperor penguin colonies over a large area, potentially affecting numerically important colonies in West Antarctica.

ecology↗

Remote sensing of emperor penguin abundance and breeding success

Emperor penguins (Aptenodytes forsteri) are under increasing environmental pressure. Monitoring colony size and trends of this Antarctic seabird relies primarily on satellite imagery recorded near the end of the breeding season, when illumination levels are sufficient to capture images, but colony occupancy is highly variable. To correct population estimates for this variability, we develop a phenological model that accurately predicts the number of breeding pairs and fledging chicks, as well as key phenological events such as arrival, hatching and foraging times, from as few as six data points from a single season. The ability to extrapolate occupancy from sparse data makes the model particularly useful for monitoring remotely sensed animal colonies where ground-based population estimates are very rare or unavailable. TeaserThe Emperor penguin becomes the Southern Oceans canary in a coal mine through remote sensing its annual breeding success.

ecology↗

Gene expression is the main driver of purifying selection in large penguin populations

Purifying selection is the most pervasive type of selection, as it constantly removes deleterious mutations arising in populations, directly scaling with population size. Highly expressed genes appear to accumulate fewer deleterious mutations between divergent species lineages (known as E-R anticorrelation), pointing towards gene expression as an additional driver of purifying selection. However, estimates of the effect of gene expression on segregating deleterious variants in natural populations are scarce, as is an understanding of the relative contribution of population size and gene expression to purifying selection. Here, we analyse genomic and transcriptomic data from two natural populations of closely related sister species with different demographic histories, the Emperor penguin (Aptenodytes forsteri) and the King penguin (A. patagonicus), and show that purifying selection at the population-level depends on gene expression rate, resulting in very high selection coefficients at highly expressed genes. Leveraging realistic forward simulations, we estimate that the top 10% of the most highly expressed genes in a genome experience a selection pressure corresponding to an average selection coefficient of -0.1, which decreases to a selection coefficient of -0.01 for the top 50%. Gene expression rate can be regarded as a fundamental parameter of protein evolution in natural populations, maintaining selection effective even at small population size. We suggest it could be used as a proxy for gene selection coefficients, which are notoriously difficult to derive in non-model species under real-world conditions.

evolutionary biology↗

RFIDeep: Unfolding the Potential of Deep Learning forRadio-Frequency Identification

O_LIAutomatic monitoring of wildlife is becoming a critical tool in the field of ecology. In particular, Radio-Frequency IDentification (RFID) is now a widespread technology to assess the phenology, breeding, and survival of many species. While RFID produces massive datasets, no established fast and accurate methods are yet available for this type of data processing. Deep learning approaches have been used to overcome similar problems in other scientific fields and hence might hold the potential to overcome these analytical challenges and unlock the full potential of RFID studies. C_LIO_LIWe present a deep learning workflow, coined "RFIDeep", to derive ecological features, such as breeding status and outcome, from RFID mark-recapture data. To demonstrate the performance of RFIDeep with complex datasets, we used a long-term automatic monitoring of a long-lived seabird that breeds in densely packed colonies, hence with many daily entries and exits. C_LIO_LITo determine individual breeding status and phenology and for each breeding season, we first developed a one-dimensional convolution neural network (1D-CNN) architecture. Second, to account for variance in breeding phenology and technical limitations of field data acquisition, we built a new data augmentation step mimicking a shift in breeding dates and missing RFID detections, a common issue with RFIDs. Third, to identify the segments of the breeding activity used during classification, we also included a visualisation tool, which allows users to understand what is usually considered a "black box" step of deep learning. With these three steps, we achieved a high accuracy for all breeding parameters: breeding status accuracy = 96.3%; phenological accuracy = 86.9%; breeding success accuracy = 97.3%. C_LIO_LIRFIDeep has unfolded the potential of artificial intelligence for tracking changes in animal populations, multiplying the benefit of automated mark-recapture monitoring of undisturbed wildlife populations. RFIDeep is an open source code to facilitate the use, adaptation, or enhancement of RFID data in a wide variety of species. In addition to a tremendous time saving for analyzing these large datasets, our study shows the capacities of CNN models to autonomously detect ecologically meaningful patterns in data through visualisation techniques, which are seldom used in ecology. C_LI

ecology↗

Selection-driven adaptation to the extreme Antarctic environment in the Emperor penguin

The eco-evolutionary history of penguins is profoundly influenced by their shift from temperate to cold environments. Breeding only in Antarctica during the winter, the Emperor penguin appears as an extreme outcome of this process, with unique features related to insulation, heat production and energy management. However, whether this species actually diverged from a less cold-adapted ancestor, thus more similar in ecology to its sister species, the King penguin, is still an open question. As the Antarctic niche shift likely resulted in vast changes in selective pressure experienced by the Emperor penguin, the identification and relative quantification of the genomic signatures of selection, unique to each of these sister species, could answer this question. Applying a suite of phylogeny-based methods on 7,651 orthologous gene alignments of seven penguins and 13 other birds, we identified a set of candidate genes showing significantly different selection regimes either in the Emperor or in the King penguin lineage. Our comparative approach unveils a more pervasive selection shift in the Emperor penguin, supporting the hypothesis that its extreme cold adaptation is a derived state from a more King penguin-like ecology. Among the candidate genes under selection in the Emperor penguin, four genes (TRPM8, LEPR, CRB1, and SFI1) were identified before in other cold adapted vertebrates, while, on the other hand, 161 genes can be assigned to functional pathways relevant to cold adaptation (e.g., cardiovascular system, lipid, fatty acid and glucose metabolism, insulation, etc.). Our results show that extreme cold adaptation in the Emperor penguin largely involved unique genetic options which, however, affect metabolic and physiological traits common to other cold-adapted homeotherms.

evolutionary biology↗

Biologging of emperor penguins - attachment techniques and associated deployment performance

An increasing number of marine animals are equipped with biologgers, to study their physiology, behaviour and ecology, often for conservation purposes. To minimise the impacts of biologgers on the animals welfare, the Refinement principle from the Three Rs framework (Replacement, Reduction, Refinement) urges to continuously test and evaluate new and updated biologging protocols. Here, we propose alternative and promising techniques for emperor penguin (Aptenodytes forsteri) capture and on-site logger deployment that aim to mitigate the potential negative impacts of logger deployment on these birds. We equipped adult emperor penguins for short-term (GPS, Time-Depth Recorder (TDR)) and long-term (i.e. planned for one year) deployments (ARGOS platforms, TDR), as well as juvenile emperor penguins for long-term deployments (ARGOS platforms) in the Weddell Sea area where they had not yet been studied. We describe and qualitatively evaluate our protocols for the attachment of biologgers on-site at the colony, the capture of the animals and the recovery of the devices after deployment. We report unprecedented recaptures of long-term equipped adult emperor penguins (50% of equipped individuals recaptured after 290 days). Our data demonstrate that the traditional technique of long-term attachment by gluing the biologgers directly to the back feathers is detrimental to the birds. It causes excessive feather breakage and the loss of the devices at an early stage. We therefore propose an alternative method of attachment for back-mounted devices. This technique led to successful year-round deployments on 37.5% of the equipped juveniles. Finally, we also disclose the first deployments of leg-bracelet mounted TDRs on emperor penguins. Our findings highlight the importance of monitoring potential impacts of biologger deployments on the animals and the need to remain critical towards established and new protocols.

ecology↗

Juvenile emperor penguin range calls for extended conservation measures in the Southern Ocean

To protect the unique Southern Ocean biodiversity, conservation measures like marine protected areas (MPAs) are implemented based on the known habitat distribution of ecologically important species. However, distribution models focus on adults, neglecting that immatures animals can inhabit vastly different areas. Here, we show that current conservation efforts in the Southern Ocean are insufficient for ensuring the protection of the highly mobile Emperor penguin. We find that juveniles spend [~]90% of their time outside the boundaries of proposed and existing MPAs, and that their distribution extends far beyond (> 1500 km) the species extent of occurrence as defined by the International Union for Conservation of Nature. We argue that strategic conservation plans for Emperor penguin and long-lived ecologically important species must consider the dynamic habitat range of all age classes.

ecology↗

Climate-driven range shifts in fragmented ecosystems

Range shift is the primary short-term response of species to rapid climate change but it is hampered by natural or anthropogenic habitat fragmentation. Fragmented habitats expose different critical areas of a species niche to heterogeneous environmental changes resulting in uncoupled effects. Modelling species distribution under complex real-life scenarios and incorporating such uncoupled effects has not been achieved yet. Here we identify the most vulnerable areas and the potential cold refugia of a top-predator with fragmented niche range in the Southern ocean by integrating genomic, ecological and behavioural data with atmospheric and oceanographic models. Our integrative approach constitutes an indispensable example for predicting the effect of global warming on species relying on spatially and ecologically distinct areas to complete their life-cycle (e.g., migratory animals, marine pelagic organisms, central-place foragers) and, in general, on species constrained in fragmented landscapes due to continuously-growing anthropogenic pressure.

evolutionary biology↗