Birds and mammals are shrinking and shapeshifting as global temperatures rise. Ecogeographic rules predict that such changes should ease heat stress by increasing surface-area-to-volume ratios, and thus, the capacity for heat exchange. This has led to the hypothesis that body size reductions are driven by thermoregulatory selection or adaptive plasticity, although recent syntheses point to more complex, multifactorial causes. Crucially, recent theoretical models predict that thermoregulatory benefits of smaller body size only emerge at extreme deviations from average phenotypes. Here, we exploit agricultural selection in Japanese quail to directly test this hypothesis, using three breeds spanning extreme differences in body mass, surface area, and relative appendage lengths. Evaporative cooling capacity and the scope for evaporative water loss broadly followed allometric predictions when contrasting small and larger breeds. As expected, this allowed the smallest breed to tolerate higher air temperatures. However, differences in heat tolerance limits between breeds were consistently much smaller than predicted. Additionally, the breadth of thermoneutral zones overlapped in full, and upper critical temperatures were remarkably similar, between breeds. Together, these results show that heat tolerance is only weakly linked to surface-area-to-volume relationships and cannot be explained by size alone. Thus, although smaller bodies may modestly enhance heat dissipation when size variation in a population is substantial, our findings suggest that recent body size reductions and morphological shifts are unlikely to be driven primarily by thermoregulatory benefits.
Science Journals
The deployment of clothianidin-based insecticide formulations in malaria vector control has highlighted the capacity of Anopheles funestus to displace more susceptible mosquito species in treated areas and to rapidly evolve resistance under selection pressure. Metabolic detoxification, together with structural and genetic changes in nicotinic acetylcholine receptors (nAChRs), the primary molecular targets of neonicotinoids, can reduce insecticide efficacy. Here, we characterized amino acid substitutions across all 11 nAChR subunits in An. funestus to assess standing variation that may facilitate adaptive responses to chemical exposure. Using whole-genome sequencing data from 656 mosquitoes sampled in 13 African countries, we found marked contrasts in the distribution of nonsynonymous variants among nAChR subunits. Most subunits are strongly constrained and carry no missense variants, whereas two loci (3 and 7) display three geographically widespread amino acid substitutions across the continent. In contrast, 9 and {beta}2 accumulate dozens of nonsynonymous mutations occurring at intermediate to high frequencies, including within domains involved in orthosteric ligand binding and channel gating. Genetic differentiation at nAChR loci among populations from different countries is low to moderate, although several nonsynonymous mutations display high FST values consistent with geographic structuring. These results highlight relaxed constraint on two subunits that may provide opportunities for evolutionary diversification within a conserved family of multimeric receptor assemblies. Such diversification has not been observed in vector species displaced by An. funestus in indoor residual spraying areas, and the potential implications for reduced sensitivity to neonicotinoids are discussed.
Genetic variation is the raw material for evolution. One source of variation is chromosomal rearrangements, which can bring genes together and form genetic linkage. Rearrangements can also suppress recombination and gene flow, as in the case of sex chromosome evolution. We conducted the first population genomic study of the red harvester ant Pogonomyrmex barbatus to investigate genomic rearrangements that differentiate the lineages J1 and J2 in the "dependent-lineage system" (also known as "social hybridogenesis"). In this unusual reproductive system, males and females from different lineages mate to create hybrids, yet these hybrids develop into sterile offspring (workers), and so the two lineages remain reproductively isolated. We sequenced high-quality reference genomes for the two lineages to search for a potential explanation of the suppression of gene flow between them. Comparison of the two genome assemblies revealed multiple large-scale genomic rearrangements, all of which occurred in the J1 lineage. The rearrangements formed some of the largest J1 chromosomes, including the largest scaffold in the assembly that was formed by at least two translocation events and additional intra-chromosomal rearrangements. The translocations brought together 118 odorant receptor (OR) genes on this rearranged chromosome, 44 of which are 9-exon ORs, which are implicated in chemical communication in ants. We also identified an enrichment of transposable elements in a large synteny gap between the translocated segments. The discovery of multiple translocations that formed large rearranged chromosomes provides a potential explanation for the reproductive isolation between the pair of dependent lineages in this system, and opens the way for the study of the molecular genetic basis of an intriguing evolutionary phenomenon in these and in other ant lineages.
Environmental heterogeneity across freshwater systems often promotes phenotypic variation, yet disentangling environmentally induced variation from heritable differentiation remains a central goal in evolutionary ecology. We investigated the geographic distribution and morphological differentiation, and heritability of shell traits among populations of the freshwater lymnaeid snail Pectinidens diaphanus in Patagonia. Extensive field surveys across 196 freshwater sites revealed that the species occupies a broad range of lentic and lotic habitats and constitutes the only lymnaeid inhabiting southern Patagonia. While reproductive anatomical structures were conserved across populations, shell shape differed markedly among populations from contrasting habitat types, with population identity explaining nearly 50% of total shape variation. Populations from hydrologically unstable habitats (ponds and streams) exhibited more elongated shells and relatively smaller apertures, a pattern consistent with functional responses to hydroperiod variability and desiccation risk. To assess the heritability of this differentiation, we conducted a common-garden experiment across two generations. Shell shape differences between permanent- (lagoon) and temporary- (pond) habitat-derived populations persisted into the G2 generation reared under standardized laboratory conditions, indicating that the observed variation is not solely a response to local environmental conditions but includes a heritable component. Together, our findings demonstrate that P. diaphanus constitutes the sole lymnaeid across southern Patagonia, occupying a broader range than previously documented, and that populations show heritable shell differentiation potentially associated with contrasting freshwater habitats. By integrating large-scale biogeographic surveys with morphometric and experimental approaches, this study provides new insight into how habitat variation may contribute to ecological and evolutionary di…
Strong population contractions can leave a persistent genomic legacy that can influence populations long after their demographic recovery. While bottlenecks facilitate the removal of strongly deleterious mutations, the effectiveness of purging may be limited in historically small populations. The Kirtlands warbler (Setophaga kirtlandii) is a rare North American songbird with an ancestrally small population. After narrowly evading extinction, they are one of few species that have been delisted from federal protections in the USA. Despite their recovery, a previous study showed evidence for recent inbreeding and a high burden of deleterious mutations that may have not been purged despite strong bottlenecks. Historical DNA offers a unique opportunity to understand the consequences of recent demographic declines on genetic diversity. Here, we use DNA from over 100-year-old museum specimens to estimate changes in genetic load in the Kirtlands warblers pre- and post-bottleneck. We validate our results with forward-in-time genetic simulations and explore how sample size and missing data can affect estimates. Both empirical data and simulations suggest a reduced ability to purge deleterious mutations in this historically small population. Our simulations also highlight that limited sampling design and data quality can constrain the ability to detect changes.
Cancer progression is increasingly understood as an evolutionary process shaped not only by competition but also by cooperative interactions including those mediated through diffusible ``public goods'' (PGs). Classical evolutionary game theory predicts that PG-producing (altruistic) subclones cannot invade well-mixed populations of non-producers, creating a paradox given their observed emergence in tumors. Here, we resolve this contradiction by combining stochastic spatial simulations with an analytically tractable Moran model to study the invasion dynamics of PG-producing cells in structured populations. Starting from a single producer cell, we explicitly model stochastic PG secretion, diffusion, binding/unbinding, and cell proliferation across biologically relevant parameter ranges. We demonstrate that spatial structure fundamentally alters invasion dynamics, enabling PG producers to invade and establish even when production incurs a fitness cost. Both numerical and analytical approaches converge on a key unifying parameter, a characteristic length scale {delta}, that captures the combined effects of diffusivity, binding kinetics, and degradation. This length scale determines the spatial extent of PG availability and thus the selective advantage of producers. We identify distinct regimes: when PGs are localized (small {delta}), producers preferentially benefit and invasion is likely; when PGs are widely dispersed (large {delta}), benefits are shared and invasion approaches neutrality or is suppressed by costs. Our results highlight that invasion of cooperative traits is governed by spatially mediated resource localization rather than intrinsic fitness alone. This framework provides a mechanistic basis for understanding the emergence of cooperative subclones in tumors and suggests that modulating biophysical transport properties of signaling molecules could influence tumor evolution, metastasis, and therapeutic resistance.
The evolution of reproductive isolation is central to speciation, yet the earliest stages of this process remain poorly understood. In particular, it is unclear how rapidly barriers to mating arise during adaptation, whether they accumulate predictably, and how they depend on ecological context. Here, we investigate the evolution of mating efficiency during prolonged asexual adaptation in diploid Saccharomyces cerevisiae. Twelve replicate populations were evolved for 1200 generations in two distinct carbon environments, glucose and galactose, under strictly asexual conditions. At regular intervals, we induced sporulation and quantified mating efficiency using three complementary assays: within-population crosses, crosses between populations evolved in different environments, and crosses between evolved populations and the ancestral strain. We find that mating efficiency evolves during asexual adaptation, with outcomes that depend strongly on the environment. While glucose-evolved populations remain largely stable, galactose-evolved populations exhibit a reversible decline. Overall, changes in mating efficiency are dynamic, heterogeneous, and often transient, with evidence for both intrinsic reductions in mating competence and context-dependent incompatibilities between populations. Together, these results show that asexual adaptation can generate rapid but non-monotonic changes in mating compatibility. Early reductions in mating efficiency are heterogeneous, environment-dependent, and often reversible, and do not accumulate into stable reproductive isolation over the timescale examined. Our findings suggest that the initial stages of divergence are characterized by dynamic and contingent perturbations of reproductive traits, rather than a steady progression toward speciation.
Biodiversity is commonly summarized by macroecological mean patterns, most prominently the species-area relationship (SAR) linking habitat area to expected species richness. Yet conservation, policy, and economic decisions increasingly require risk metrics: probabilities of rare but consequential biodiversity shortfalls, including local collapse. Such tail risks are central in finance and insurance but remain difficult to quantify in ecology because the data needed to estimate full richness distributions are rarely available at decision scales. Here we provide a mechanistic route from species-area relationships to biodiversity risk metrics. We show that when regional species abundances are well approximated by Fisher's log-series, a minimal immigration-extinction mechanism yields a closed-form stationary distribution for local richness whose structure tightly couples the mean SAR to richness variability and lower-tail probabilities. This coupling implies exact fluctuation-response identities and an explicit integral transform that reconstructs collapse probabilities and other tail risk measures directly from the mean SAR. These results define ecological analogues of financial risk metrics---such as collapse probability and lower-tail quantiles---without requiring direct estimation of the full richness distribution. Using high-resolution ForestGEO tree censuses spanning tropical, subtropical, and temperate forests, we find empirical support for these predictions across spatial scales. Together, our results show how widely measurable species-area relationships can be elevated from descriptive averages to operational tools for biodiversity risk assessment and reliability-based conservation planning.
Although resources are typically distributed continuously in space, species distributions often organize into discrete clusters. In his seminal paper, Turing demonstrated that such clusters can spontaneously arise in population densities, even when populations evolve in environments with continuously varying conditions. This phenomenon is known as Turing instability. In this work, we focus on two models grounded in population dynamics: a one-dimensional model based on the nonlocal Fisher-KPP equation, and a two-dimensional model involving an environmental gradient. We show that phenotypic clusters (sometimes referred to as "species") emerge in these models. We prove that they do not emerge because of Turing instability, but because of stochasticity, and that they disappear when stochasticity is reduced. First, for both models, we start our simulations with initial populations uniformly distributed in the state space. We show that phenotypic clusters quickly emerge and that the distances between them depend on the population size, that is, on the degree of stochasticity. Next, we start from already clearly defined phenotypic clusters. We identify three regimes in the connection between population size, the initial distances between clusters, and the distances between clusters at equilibrium. Last, on the two-dimensional model, we relax the hypothesis of complete clonality by varying the effective recombination rate, explore its effect on phenotypic clustering, and show that phenotypic clustering decays drastically with slight recombination.
Elucidating how habitat degradation facilitates extinction is critical for effective conservation efforts. Here, we propose integrating physiologically-structured population models into stochastic population viability analyses to assess how differing consequences of habitat degradation interact to drive extinction dynamics in a focal population. Using the isolated spectacled caiman Caiman crocodilus population/ecomorph from the Apaporis River as a case study, we find that threatening the resource base, which individuals increasingly rely upon, to outgrow vulnerable size ranges and mature accelerates extinction. We also found that when habitat degradation impacts both the primary adult and juvenile resource bases, this can have marked synergistic effects on threatening population viability. By contrast, destroying nesting sites has only a small effect on accelerating the impact of deteriorating prey availability. Through integrating community-level feedback between habitat degradation/change and population dynamics/structure, our approach provides a comparative framework for assessing the relative importance of distinct mechanisms through which habitat degradation ultimately drives extinction risk.
Wildlife vaccination could become a powerful strategy to mitigate disease-induced biodiversity losses, yet many vaccines for wildlife diseases provide only limited protection. Notably, tools to control the fungal pathogen Batrachochytrium dendrobatidis (Bd) are urgently needed for amphibian conservation. Laboratory experiments have demonstrated that prophylactic exposure to Bd metabolites increases host resistance, significantly reducing infection intensity in amphibians subsequently challenged with live Bd. Because Bd metabolites are non-infectious and applied topically, this treatment has potential to be administered to waterbodies to vaccinate and protect amphibians. We developed an agent-based model that indicated imperfect vaccination could reduce or amplify Bd infections at the population level, depending on degree of enhanced resistance or tolerance. Utilizing a Before-After-Control-Impact design with ten years of data, we conducted an ecosystem-level trial where we applied low levels of Bd metabolites or a sham control treatment to ponds in California and subsequently quantified Bd prevalence and infection intensity in metamorphosing Pacific chorus frogs (Pseudacris regilla). Unexpectedly, infection intensity was significantly greater in treated ponds relative to control ponds following metabolite addition. Additional model simulations indicated that this could occur via two mechanisms: (1) if treatment greatly increased tolerance alone or in combination with smaller increases in resistance, or (2) if a deleterious environmental interaction caused the treatment to increase susceptibility, rather than promote resistance. Future research is needed to determine whether tolerance or environmental factors drove heightened Bd infection intensities in this field trial to identify contexts in which this treatment can be used as a conservation tool.
Cliffs are environmentally extreme yet biodiversity-rich ecosystems that harbour specialist plants, many endemic and threatened. Plant persistence in these nutrient-poor substrates may depend on tightly linked soil- and root-associated microbial communities, which remain poorly understood. These interactions may become increasingly important with the global expansion of recreational climbing. While physical climbing impacts on vegetation are documented, potential chemical effects, from the use of climbing chalk (magnesium carbonate), on soil properties and plant-associated microbiota remain unknown. We sampled soils and roots beneath cliff-specialist and generalist plants, and unvegetated soils, across climbed and unclimbed routes in northern, central, and southern Spain. Soil physicochemical properties were quantified, fungal communities were characterized using ITS-metabarcoding, and structural equation modelling was used to disentangle direct and indirect effects. Climbing increased soil pH and altered soil chemical properties, driving shifts in fungal diversity and functional composition in soil and roots. The relative read abundance of root-associated symbiotrophic fungi declined, whereas arbuscular mycorrhizal fungi and pathogens increased in climbed cliffs. Overall effects were consistent, with cliff-specialist plants mediating nutrient and fungal shifts. Our findings show that climbing can reshape cliff soil chemistry and fungal communities, with potential cascading consequences for plant functional performance, nutrient dynamics, and ecosystem resilience.
Reef restoration practitioners aim to preserve coral genetic diversity by protecting reefs and cultivating diverse genotypes in coral nurseries. However, cryptic genetic lineages in most corals complicate restoration strategies, as the role of between-lineage genetic divergence remains unclear regarding adaptation. In Montastraea cavernosa, researchers have identified cryptic lineages, some strongly segregated by depth. We conducted a ten-week reciprocal transplantation experiment using two cryptic lineages restricted to shallow water (<10m depth), with one lineage more common on nearshore reefs and the other on offshore reefs. We aimed to quantify lineage-specific responses to the environment that explain the genetic and ecological divergence between the two lineages. Surprisingly, the strongest response was not lineage-specific. Instead, both lineages exhibited strong and similar changes in growth and metabolomic profiles, depending on the transplantation habitat. These results suggest that cryptic lineages employ similar mechanisms of adaptation and acclimatization to environmental challenges, despite their genetic distinction.
Nature-Based Solutions are increasingly promoted to address current urban challenges. While their potential effects on vector-borne disease risks have been documented, data on Aedes albopictus, a known arbovirus vector, remain limited in France. A previous study showed that urban vegetation moderately increases the abundance of adult mosquitoes of this species, but the monitoring period lasted only six months. Using ovitraps, we monitored Ae. albopictus egg density dynamics over multiple years (2022 to 2024) and analysed its environmental predictors in various urban environments. We included lagged meteorological variables, land cover metrics, and the cumulated egg densities recorded in the previous weeks as environmental predictors. Both parametric (GLMM) and non-parametric (Random Forest) models were fitted to weekly egg counts per trap. Our findings highlight that (i) egg density dynamics were related to how vegetation classes structured the landscape, (ii) growing degree days and cumulated number of eggs recorded in specific lagged time windows were the main contributors to egg density, and (iii) the non-parametric and parametric models performed similarly in terms of prediction accuracy.
Mapping the genetic basis of inter-individual heterogeneity in multifactorial diseases opens the door to mechanistic insights and opportunities for targeted intervention. In Alzheimer's disease (AD), clinical and pathological heterogeneity is well recognized, but genetic dissection is limited by a lack of well-powered cohorts with deep phenotypic characterization. Here, we introduce a polygenic score (PGS) analysis strategy to address these limitations by leveraging the inherent pleiotropy in complex trait genetics. We perform a cross-cohort, cross-trait application of pre-trained PGS, integrating 713 UK Biobank-derived PGS with 36 deep AD phenotypes across 1678 ROSMAP participants. We identify 268 statistically significant (FDR<0.1) associations between 12 prioritized PGS and 36 AD phenotypes. Prioritized PGS include blood lipid measurements, inflammatory biomarkers, and cancer traits; observed AD phenotypes include cognition, amyloid, and tangles. Of the 268 associations, 49 persist with APOE-excluded PGS. Predictive models trained on multiple prioritized PGS outperform the AD PGS or APOE alone for predicting amyloid and cognition. Lastly, our approach identifies six individual-level AD polygenic subtypes supported by distinct pathological patterns. Overall, we combine large-scale biobank resources and deeply-phenotyped cohorts using PGS, reveal genetic features underlying AD heterogeneity, and provide a general model for stratifying heterogeneous disease-focused cohorts using genomics.
Conventional diagonal stride skiing traditionally includes a glide phase, characterised by a period of relatively passive gliding on one ski. While the glide phase may take advantage of low ski-snow friction, it does not exhibit the same whole-cycle mechanical energy fluctuations seen in running or walking on foot. A new sub-technique, known as running style, substantially reduces the glide phase and may alter the role of elastic tissues, making the movement pattern more similar to uphill running on foot in its temporal organisation. We examined knee extensor and plantar flexor muscle-tendon behaviour in eight competitive skiers performing conventional diagonal and running techniques on a treadmill inclined at 10 deg. Using synchronised ultrasonography, 3D kinematics, ski forces and EMG, we quantified gastrocnemius medialis and vastus lateralis fascicle and muscle-tendon unit (MTU) dynamics in both the running (RUN) and conventional (CON) styles. Shorter glide and total cycle durations during RUN shifted MTU peak length and velocity earlier during the kick phase. Fascicles in both muscles operated at similar velocities across techniques, showing MTU-fascicle decoupling. Vastus lateralis fascicles shortened at higher absolute peak velocities than gastrocnemius in both conditions, while normalised velocities were similar. RUN increased preactivation and advanced EMG timing, while integrated EMG during the kick was lower compared to CON. These findings suggest that, despite large shifts in external mechanics between glide-based and more running-like skiing, elastic tissues may help stabilise fascicle behaviour and preserve a similar contractile strategy across muscles and techniques.
How post-mitotic neurons maintain precise transcription factor (TF) levels throughout life remains a fundamental open question. Here, we challenge the prevailing model of positive autoregulation by demonstrating that UNC-3 (Collier/EBF1-4), a dosage-sensitive TF continuously required for cholinergic motor neuron identity in C. elegans, negatively regulates its own expression. Using genetics, biochemistry, and inducible protein depletion, we show this self-repression occurs directly at the transcriptional level and persists beyond development. CRISPR/Cas9 disruption of negative autoregulation causes motor neuron identity and locomotion defects, establishing its functional necessity. Mechanistically, the UNC-3 DNA-binding domain is required and sufficient for self-repression, with an AlphaFold2 screen implicating chromatin factors as interaction partners. Critically, UNC-3 self-repression is continuously counterbalanced by positive input from the HOX cofactor CEH-20/PBX, revealing a dynamic "balancing act" between opposing regulatory inputs that stabilize TF dosage over time. Mutations in the unc-3 ortholog EBF3 cause a neurodevelopmental syndrome, and disease-associated variants disrupt UNC-3 self-repression, revealing a key molecular mechanism underlying the disorder. We propose that negative autoregulation continuously counteracted by positive input represents a broadly applicable principle for maintaining dosage-sensitive TF expression to secure post-mitotic cell identity.
Despite sharing the same genes and the same environment, individuals often develop substantial phenotypic differences. While this pattern has been documented across diverse species and traits, the processes giving rise to this 'stochastic' or non-shared environmental variation remain unclear. Recent mathematical models of development in which phenotypes are gradually constructed may offer some clues. These models show that imperfect environmental cues can generate striking variation in developmental trajectories and adult phenotypes. At the population level, such imperfect cues produce increasing stability of individual differences across ontogeny (e.g. animal personality) and patterned distributions of mature phenotypes (e.g. normal or skewed) that resemble those observed in real organisms. Our paper synthesizes existing models in which stochastic phenotypic variation arises solely as a by-product of mechanisms missing their phenotypic targets because of imperfect cues. We then link these models to related, but independent, mathematical theory exploring the environmental conditions under which stochastic phenotypic variation is favoured by natural selection. Our integration shows that stochastic sampling is often favoured over classic bet-hedging strategies involving non-plastic generalist or specialist strategies. Our findings provide new directions of research on stochastic sampling as a mechanism for adaptive stochastic variation within and across generations.
Dendritic arbor morphology is shaped in part by interactions with neighboring dendrites, and its geometry strongly influences the spatial distribution and strength of synapses. These observations raise the possibility that local dendritic contacts help determine where synapses accumulate and strengthen. Previous work in cultured hippocampal neurons showed that dendrite-dendrite contact sites are non-random and associated with local synaptic clustering. Here we asked whether a different type of dendritic contact, formed between a dendrite and the soma of a neighboring neuron, behaves similarly. Using dissociated hippocampal cultures, immunofluorescence imaging, time-lapse microscopy, quantitative image analysis, stochastic spatial simulations, and minimal quantitative modeling, we identified three recurrent classes of dendrite-soma interactions (DSIs): dendrites crossing directly over a neighboring soma, growing tangentially along the soma perimeter, or contacting the proximal region where a neighboring dendrite emerges from the soma. These interactions were abundant, occurred exclusively between different neurons, and showed substantial structural persistence over several days. Their overall frequency exceeded stochastic predictions across culture densities, and two configurations - proximal and tangential contacts - were selectively enriched above random expectation, whereas soma-crossing contacts were largely consistent with stochastic overlap. DSI composition also changed over development, with proximal contacts becoming progressively more prevalent. At DSI sites, synaptophysin-positive puncta were significantly denser and more intense than on non-interacting dendritic segments, consistent with local enrichment and strengthening of presynaptic specializations. Minimal modeling further indicated that biased formation together with developmental stabilization explains the observed organization better than stochastic geometry alone. These findings identify DSIs a…
Transcriptomics has transformed our understanding of the brain, but assigning transcriptomic identities to neurons recorded in vivo remains challenging at scale. Existing platforms can pair transcriptomic identity with two-photon calcium imaging in small populations of approximately 100 neurons, but they require recorded cells to be sparse and therefore cannot be applied to large population recordings. Here, we present coppaFISH 3D, a spatially resolved transcriptomics method, and CASTalign, an in silico alignment framework, which together enable transcriptomic identification of thousands of simultaneously recorded cells. coppaFISH 3D detects hundreds of genes in thick 50m fixed sections while preserving tissue integrity, enabling both 3D registration to in vivo imaging and integration with immunofluorescence labelling. The platform is fully powered by open chemistry and open source software, runs on commodity hardware, and can be performed at very low cost per section. It therefore enables transcriptomic identification of recorded neurons at scale, making it possible to study how transcriptomic identity shapes activity in neural populations.
Humans comprehend language incrementally, updating the representation of sentence meaning with each incoming word. These updates are guided by the distance between each perceived word and prior expectations--the prediction error. The alignment between large language models (LLMs) and cortical activity inspires the hypothesis that the cortical computation of prediction error is Surface-based, driven by statistical patterns of word form co-occurrence. In contrast, psycholinguistic models propose that prediction error computation is Meaning-based, driven by word semantics. We used polysemic words with ambiguous semantics to distinguish these models: ambiguity would introduce uncertainty into meaning representations and hence the prediction error, if Meaning-based, but would not affect the prediction error, if Surface-based. We examined how ambiguity influenced prediction error signatures in self-paced reading times and magnetoencephalographic (MEG) neural responses during sentence processing. While an LLM-based proxy of prediction error robustly predicted reading times and neural responses to unambiguous words, it failed to predict either under ambiguity. That is, prediction error computation was altered by uncertainty in word meaning, which supports the Meaning-based model and corroborates the essential role of word meaning in predictive language processing. Our findings highlight an important limitation of LLMs as in silico models of the human language faculty.
How do humans store sequences that far exceed working memory capacity? Using visuo-spatial and binary auditory sequences, we previously showed that a Language of Thought (LoT) architecture, in which simple primitives are recursively combined into hierarchical programs, enables efficient storage of structured sequences. Here we ask whether this principle extends to purely ordinal structure: sequences defined by how items repeat and in what order, as in AABBCCAABBCC, independently of their spatial content. Across three experiments, participants reproduced 12-item sequences of spatial locations with various ordinal structures. The minimal description length derived from the LoT model predicted recall accuracy with remarkable precision (r = .96), substantially outperforming Shannon entropy, Lempel-Ziv complexity, chunking models and subjective complexity ratings. Critically, fine-grained analyses of participants' inter-click intervals during reproduction revealed systematic slowdowns at the hierarchical boundaries predicted by the LoT programs, providing a behavioral signature of the underlying mental syntax. These results identify a compact vocabulary of mental primitives, repetition, mirroring, and interleaving, whose composition accounts for the symbolic compression of ordinal structures. For ordinal regularities, human sequence memory operates as a form of program induction, leveraging a domain-general capacity for hierarchical compression to encode complex structured information.
WD40 domains share a widespread {beta}-propeller fold, and often act as versatile scaffold proteins. Despite their central role in organizing dynamic cellular complexes, the molecular and structural mechanisms of many WD40 proteins remain poorly understood. Among them, DCAF7, an ubiquitously expressed and essential gene in human, also encodes a highly conserved WD40 protein in eukaryotic organisms. It is known to interact with multiple and functionally diverse partners to coordinates cellular activity of several protein kinases as well as transcriptional regulators, thereby modulating key cellular processes such as cell growth, differentiation, and transcriptional regulation. However, the precise mode of action of DCAF7 is unknown and its important divergence in sequence from better characterize WD40 prevent information transfer by similarity. Structural interactomic can reveal how protein-protein interactions (PPIs) occur within an organism and are essential for understanding biological functions and developing new therapeutic strategies. Using SLiMAn2, AlphaFold2/3 and PSSMsearch, we identified a conserved -helical short linear motif (SLiM) in several well known DCAF7 partners that binds to the top surface of its {beta}-propeller. This motif was subsequently used to generate a regular expression, to identify potential new direct binders across the DCAF7 meta-interactome and the human proteome. Domain-domain interactions were also predicted for some other partners. Finally, modeling of oligomeric complexes with such new hits reveals the structural basis of DCAF7 scaffolding, with links to neurodevelopmental disorders such as autism.
Short-read amplicon sequencing is widely used for fungal surveys but can limit taxonomic resolution. Long-read sequencing enables recovery of the full internal transcribed spacer (ITS) region and may improve ecological and taxonomic inference. Here, we conducted a paired comparison of Illumina ITS2 and PacBio HiFi full-length ITS sequencing using identical DNA extracts from built-environmental air and surface samples (n = 68) collected across homes, a dormitory, and laboratories. Both datasets were taxonomically assigned using the same algorithm and reference database. We performed paired statistics, in-silico ITS2 trimming of long-read sequences, and cross-platform mapping at multiple identity thresholds. Full-length ITS provided higher taxonomic resolution, assigning a greater fraction of ASVs at the family (98% vs. 88%) and species (42% vs. 32%) ranks than ITS2 (paired Wilcoxon q=0.002). Alpha-diversity comparisons showed similar Shannon diversity across pipelines, whereas richness metrics were consistently higher for full-length ITS. Beta-diversity analyses indicated broadly comparable community-level patterns, although full-length ITS revealed stronger sample-type- and location-associated structure (PERMANOVA R{superscript 2} 0.06, p=0.0001). In-silico ITS2 trimming reduced these differences, indicating that amplicon length is a major contributor to enhanced taxonomic resolution and ecological inference. Cross-platform mapping further showed extensive one-to-many relationships between ITS2 and full-length ITS ASVs, consistent with increased sequence resolution in long-read data.Together, these results show that ITS2 sequencing provides robust community-level profiling, while full-length ITS enables improved richness estimates and finer ecological and taxonomic resolution. This paired, bias-aware framework provides a practical template for selecting fungal amplicon sequencing strategies in built-environment mycobiome studies.
Coxiella burnetii is the only member of the order Legionellales known to primarily infect vertebrates. The Q fever pathogen is also unusual in that it replicates within an acidified phagolysosome-like vacuole. The evolutionary origins of the virulence determinants underlying this lifestyle remain unclear. More broadly, little is known about how virulence-related traits arise in specialized intracellular lineages, where access to foreign-origin DNA may be more episodic. To address this question, we used Legionellales-wide comparative phylogenomics to reconstruct the gain and loss of traits affecting host interaction, immune evasion, intracellular survival, and metabolism. We found that many virulence-associated traits in C. burnetii predate the modern pathogen and were assembled stepwise in ancestors that likely occupied niches distinct from the acidified vacuolar niche of modern C. burnetii. The common ancestor shared with soft-tick Coxiella endosymbionts likely encoded most C. burnetii type IVB secretion system effectors, indicating that much of the host-manipulation repertoire in C. burnetii was already present before the emergence of the modern pathogen. Distinctive lipopolysaccharide features associated with immune evasion also appear to have accumulated progressively within the Coxiella lineage, including genes implicated in synthesis of virenose, a unique O-antigen sugar critical for C. burnetii virulence. Traits likely to support replication in the acidic Coxiella-containing vacuole likewise accumulated gradually, with generalized stress-tolerance functions predating acquisition of an Mrp cation/proton antiporter that may have further supported pH homeostasis. Additional changes in sugar transport and catabolism, glycolytic control, and respiratory metabolism may have enhanced metabolic flexibility and access to diverse substrates in this nutrient-rich niche. Together, these findings support a model in which vertebrate pathogenicity in C. burnetii emerged …