Maximum utilization of existing genetic variability in a breeding program depends on the efficient classification of the inbred lines into heterotic groups, particularly under stress conditions. This study applied practical breeding approaches to determine the mode of genetic inheritance for Striga resistance and proposes a weighted heterotic grouping method based on the general combining ability of multiple traits (WHGCAMT) and compares its effectiveness with other existing methods in classifying the inbred lines into heterotic groups in Striga-infested and optimum environments. Using Diallel design IV, 300 crosses were generated from 21 inbred lines and 4 standard testers. The crosses, along with six checks, were evaluated in an 18 x 17 alpha lattice design with two replications at two locations, in both artificial Striga-infested and Striga-free environments. The inbred lines were genotyped using DArTtag SNP markers. Phenotypic and genotypic data were analyzed using R. Analysis of variance revealed significant mean squares for hybrid, general combining ability (GCA), specific combining ability (SCA) and their interactions with environment. Significant positive and negative GCA and SCA effects were detected for grain yield and other measured traits. However, a larger proportion of additive gene action than non-additive gene action was observed for grain yield and most measured traits. The analysis of molecular variance also showed substantial genetic differences within and between clusters. Except for HSCA, the mean grain yield between the inter-group and intra-group hybrids was significant for each method. Pairwise comparison of the inter- and intra-group hybrids of all the methods showed significant differences between the WHGCAMT and all other methods in most cases. WHGCAMT consistently produced higher-yielding inter-group hybrids and lower-yielding intra-group hybrids, achieving breeding efficiency improvements of 55.8%, 4.3%, 15.7%, and 11.4% over the HSCA…
Science Journals
Gross chromosomal rearrangements are a hallmark of many diseases and cancers. The study of their biogenesis and the mechanisms underlying their formation is greatly facilitated by the availability of genetic reporter assays in model organisms. We present here a novel GCR assay developed in fission yeast, a highly relevant model for understanding genome instability related to human biology. The reporter employs canavanine counter-selection to detect GCRs within a chromosomal context. Using this assay, we identified natural hotspots for GCRs, including inverted long terminal repeats (IR-LTRs). Structural analysis of GCR events showed that IR-LTR-induced GCRs mainly result in either terminal deletions with adjacent inverted duplications or repair via long-range break-induced replication (BIR). Deleting IR-LTRs reduces the GCR rate and reveals another hotspot driven by BIR between homeologous aldo/keto reductase genes on opposite arms of chromosome I. This is the first evidence that BIR can occur in S. pombe on long tracks reaching up to 600 kb. Besides highlighting genome rearrangement hotspots, the assay also identifies regulators of genome instability in fission yeast. Loss of Nup132, a component of the nuclear pore complex, increases IR-LTRs-induced GCRs, while the budding yeast homolog Nup133 has no effect on the stability of a structurally similar IR. In contrast, disrupting djc9, which encodes a conserved histone H3-H4 binding protein, decreases GCR rates. Overall, this sensitive GCR assay enables the identification of factors that control spontaneous and fragile motif-induced chromosomal instability, including those conserved in humans but lost through evolution in other organisms.
LINE-1 retrotransposons are the only autonomous mobile elements still active in human genomes and remain a potent source of mutation, genome remodeling, and disease risk. However, young, full-length, potentially active copies (the elements most likely to shape present-day genomes) have been largely inaccessible to population-scale analysis because they are long, repetitive, and poorly resolved by short-read sequencing. Here, we use 47 phased long-read assemblies from the Human Pangenome Reference Consortium, representing 94 haplotypes, to build an allele-resolved view of recent human LINE-1 evolution. We identify 13,617 LINE-1 alleles with intact ORF1 and ORF2 across 683 unique insertion sites, revealing that every genome carries a distinct repertoire of potentially active source elements. These intact LINE-1 profiles recapitulate broad human population structure while exposing a large, rare, and population-enriched reservoir of mobile-element diversity missed by single-reference approaches. We also resolve a structurally variable chromosome 11 LINE-1 array, demonstrating that local duplication and rearrangement can amplify LINE-1 sequence independently of canonical retrotransposition. By comparing full-length LINE-1 sequences, we define activity signatures that separate ancient remnants from recently expanding lineages and uncover young LINE-1 groups whose activity is not fully explained by canonical subfamily labels. Sequence-network analyses further reveal a dynamic history of lineage turnover, in which successful source elements rise, seed new insertions, and are replaced by descendants marked by specific nucleotide changes. Together, these data transform human LINE-1s from a repetitive background into a resolved evolutionary system, linking insertion polymorphism, coding potential, population history, and recent retrotransposon adaptation. Our findings establish the human pangenome as a framework for discovering active source elements and for testing how mob…
Anxiety has been extensively studied in relation to memory, yet its dynamic association with spatial episodic memory in naturalistic clinical settings remains largely unexplored. We developed an anxiety-spatial-memory EMA protocol (asm-EMA) and deployed it in 30 epilepsy patients undergoing inpatient EEG monitoring, delivering combined momentary anxiety ratings and a validated spatial memory task pseudo-randomly every 90-150 minutes across multiple days. Subject-level asm-EMA means and session-to-session variability both correlated significantly with standard neuropsychological assessments, supporting the clinical validity of our design. Elevated within-person STAI-6 was selectively associated with faster retrieval responses, yet spatial memory accuracy was independent of all three anxiety measures, suggesting a shift in response strategy rather than memory impairment. Within-day anxiety showed short-term carryover between consecutive sessions, with little persistence beyond the next session. The asm-EMA protocol provides a feasible, autonomous framework for capturing moment-to-moment anxiety-memory dynamics in naturalistic settings.
As one of the earliest-diverging multicellular eukaryotic lineages, the bladed Bangiales (Rhodophyta) possess a deep evolutionary history with a central role in the multi-billion-dollar global seaweed aquaculture industry. Although North Atlantic representatives are emerging candidates for regional mariculture, the scarcity of high-quality genomic resources for these taxa hinders both fundamental research and commercial optimization. To address this, we present the first chromosome-level genome assemblies for two native European species: Porphyra dioica (150.44 Mbp) and Porphyra linearis (95.22 Mbp). By integrating Oxford Nanopore Technologies (ONT) long-read sequencing with Hi-C proximity ligation, we generated highly contiguous nuclear genomes resolved into five chromosomes. Structural gene models were predicted through the BRAKER3 pipeline, identifying 12,548 and 10,382 protein-coding genes for P. dioica and P. linearis, respectively. Subsequent homology-based functional annotation characterized 57.4% and 59.8% of these predicted proteins. Supplemented by circularized organellar genomes, these reference genomes provide a critical framework for future research, enabling comparative studies of Atlantic-Pacific divergence and facilitating the development of selective breeding programs for sustainable European aquaculture.
Biological sequences are known to be not random. Thus, the comparison of in silico restriction fragment distributions of random and biological sequences may be an indicator of this non-randomness. Our analyses show that for most of the tested combinations of restriction enzyme and genome sequence the fragments per Megabase of the biological sequence deviate at least more then 10% from the corresponding random sequence. This deviation goes into both directions, i.e. clearly increased values are as common as clearly decreased values. Although there is no species- or restriction-enzyme-specific effect, a clear impact of the GC content both of the restriction site and of the genome sequence can be seen. In contrast to the random sequences, the genome sequences show distinct peaks in their fragment length distributions, hinting to repetitive elements such as transposons.
Abstract As part of preparedness activities supporting pathogens classified under the UK High Consequence Infectious Diseases (HCID) framework, we previously evaluated both a whole-genome tiling amplicon sequencing scheme and a pan-viral hybridisation capture approach (TWIST-CVRP) for sequencing Andes virus (ANDV). In light of the recent outbreak, we make available viral sequencing datasets generated using a historical ANDV isolate (Chile, 1997). In addition, we provide an evaluation of tiling amplicon scheme performance and present recommended primer updates informed by in silico comparison with the recently released outbreak genome. These datasets are intended to support benchmarking, validation, and optimisation of bioinformatic pipelines across the community.
Measles virus remains a significant global health threat, and despite the availability of an effective vaccine, measles cases continue to increase worldwide in recent years. Genomic surveillance has become an essential tool for monitoring virus circulation and investigating outbreaks. Here, we describe a wet laboratory method for whole genome sequencing of measles virus using a tiled amplicon approach and Illumina sequencing technology. A previously published Oxford Nanopore based tiled primer scheme was adapted to include both circulating measles genotypes and for use on the Illumina platform. Two Illumina library preparation kits, Illumina DNA Prep (IDP) and Nextera XT (XT), were evaluated for performance. The IDP kit demonstrated more complete genomes and consistent genome coverage compared with XT. Using quantified reference genomes, the limit of detection was determined to be 10,000 genome copies for genotype B3 and D8. Sequence accuracy was evaluated using previously characterized clinical samples and showed high concordance. This method provides a reliable and sensitive approach for measles virus whole-genome sequencing using Illumina platforms and is suitable for genomic surveillance applications.
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.
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.
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.
Holcosus orcesi, the Orces Blue Whiptail, is a Critically Endangered lizard endemic to the upper Jubones River basin in southern Ecuador. Restricted to a narrow elevational range within semi-arid Andean shrublands, it represents one of the few montane members of a predominantly lowland lineage. Here we present the first high-quality reference genome for H. orcesi, generated using Oxford Nanopore Technologies long-read sequencing. The assembly spans 1.68 Gb across only 91 contigs, with an N50 of 76.2 Mb and a BUSCO completeness of 96.8%, making it among the most contiguous and complete squamate genomes to date. Structural annotation predicted 25,682 genes, of which 85% showed homology to known proteins and 45% were assigned Gene Ontology terms. Repetitive elements accounted for 46.3% of the genome, with LINEs representing the predominant class. This genome provides a foundational resource for future evolutionary, comparative and conservation-genomic research of H. orcesi and other mountain reptiles, enabling studies of population genomics, local adaptation, and genomic erosion in isolated populations. By expanding the genomic representation of tropical montane reptiles, this work helps address longstanding phylogenetic and geographic gaps in global biodiversity genomics and provides a foundation for evidence-based conservation of H. orcesi and related taxa.
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.
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.
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.
Avoiding fertilization with genetically incompatible partners, whether too similar or too divergent, is a central challenge for sexually reproducing organisms. Selection can favor mechanisms acting before and after mating, with postmating processes potentially compensating for constraints on premating choice. In the postmating context, female reproductive fluid (FRF) can modulate sperm performance and bias fertilization outcomes, but its contribution to reproductive isolation remains unclear. We tested whether FRF mediates discrimination against heterospecific and related sperm in two naturally hybridizing sister species of swordtails, Xiphophorus birchmanni and X. malinche, that diverge in premating behavior towards heterospecifics. Effects of FRF differed sharply between species. In X. malinche, FRF enhanced the velocity of conspecific sperm relative to heterospecifics, consistent with postmating discrimination against hybridization. In contrast, FRF in X. birchmanni did not favor conspecific sperm. Evidence for inbreeding avoidance was weaker, and we found no indication of a trade-off between discrimination against genetically similar and dissimilar sperm. These results show that female reproductive fluid can serve as a rapidly evolving axis of reproductive isolation through postmating female choice.
The hippocampus is organized along dorsal-ventral and left-right axes, but whether and how these axes interact within defined neuronal populations across behavioral states remains unresolved. Here, we combined within-animal slice electrophysiology with dual-site fiber photometry to compare dorsal and ventral CA1 activity across contralateral hemispheric configurations in mice expressing CaMKII-jGCaMP8s and SynI-jRCaMP1b at distinct longitudinal sites. Ventral CA1 pyramidal neurons exhibited greater intrinsic excitability and stronger AMPAR-mediated synaptic responses than dorsal CA1 neurons. In vivo, CaMKII-defined pyramidal recordings during home cage rest revealed a left-biased event-rate asymmetry within dorsal but not ventral CA1, with no comparable asymmetry in pan-neuronal SynI recordings. Apparent dorsal-ventral differences in spontaneous event rate were therefore configuration-dependent and resolved into a hemispheric, cell-type-specific effect restricted to the CaMKII-defined population. Lead-lag analysis showed that dorsal-ventral temporal coordination was likewise reorganized across configurations and was restricted to pyramidal-cell-biased recordings. During open-field center entries, dorsal CA1 was preferentially recruited before entry across both configurations, whereas non-coordinated entries revealed a relative post-entry suppression of contralateral ventral CA1. Together, these findings suggest that dorsal-ventral CA1 organization cannot be inferred from hemisphere-pooled designs and identify a pyramidal-cell-specific left dorsal CA1 asymmetry as a structural feature that shapes both spontaneous activity and behaviorally driven recruitment along the longitudinal hippocampal axis.
Rapid connectivity alterations of thalamic nuclei during initial learning of goal-directed behaviour
The thalamus is essential for learning, dynamically engaging with other subcortical and cerebral cortex regions throughout the learning process. Here, the thalamus serves as a critical connector hub and synchroniser within the thalamocortical system of the brain. However, whilst higher order thalamic nuclei are known to be particularly important for this process, the exact contributions of individual higher order and first order thalamic nuclei, alongside their individual involvement with cortical networks and subcortical regions, remains unexplored within the initial phase of learning. In light of this, we analysed fMRI data obtained within a paradigm which is designed to examine initial learning processes within feedback-driven stimulus-response learning, in order to explore thalamic contributions. We investigated dynamic learning-related functional connectivity alterations between various thalamic nuclei with other subcortical regions and cortical networks. Our results show that the initial phase of learning was associated with: (1) decreasing functional connectivity between thalamic nuclei and frontoparietal and cingulo-opercular networks, (2) increasing functional connectivity between thalamic nuclei with default mode and salience networks, (3) decreasing functional connectivity between thalamic nuclei and the putamen, and (4) decreasing functional connectivity amongst higher order thalamic nuclei. Furthermore (5) these dynamic alterations were associated primarily by mediodorsal thalamus. Altogether, these results indicate that higher order thalamic nuclei play a crucial role within initial learning and in the generation of novel goal-directed behaviour. This was demonstrated through enhanced functional connectivity with selected cortical networks which drive goal-directed behaviour, alongside decreased functional connectivity with striatal regions which drive motor selectivity.
Allostery enables proteins to couple environmental signals to functional outputs, yet how allosteric mechanisms diversify during evolution remains poorly understood. Here, we address this question in the ubiquitous and functionally diverse arsenic repressor (ArsR) superfamily by integrating information-theoretic bioinformatics, structural characterization of DNA recognition and NMR measurements of fast internal dynamics. We identify conserved residues that define the structural scaffold of ArsR proteins and subfamily-specific positions that encode inducer and DNA specificity. In the persulfide sensor SqrR, the crystal structure of the DNA-bound complex reveals how operator specificity is encoded by a limited set of residues, consistent with sequence-derived predictions functionally validated by in vitro transcription assays across divergent ArsR regulators. We further show that allosteric inhibition of DNA binding in SqrR occurs without large-scale conformational rearrangements and is instead associated with changes in internal dynamics, as previously observed for the zinc sensor CzrA. Together, these results support a model in which conformational entropy preserves allosteric connectivity while relaxing sequence constraints, thereby enabling functional diversification within a protein superfamily.
Most species are geographically structured, leaving characteristic signatures in neutral regions of the genome. These signatures can be distorted when neutral regions are linked to deleterious mutations. In such regions, purifying selection can reduce genetic diversity through Background Selection (BGS) or, for recessive mutations, increase diversity through Associative Overdominance (AOD). While the effect of BGS and AOD are well characterized in panmictic populations, their effects remain largely unexplored in structured populations. Here, we investigated an Isolation with Migration model using forward simulations across a range of migration, selection, dominance, and recombination parameters. We first used a genotype-based approach to quantify the effects of deleterious mutations on standard summary statistics ({pi}, Dxy, FST, DAFi). We then showed that an Ancestral Recombination Graph-based approach, tracking tree sequences from a sample of one diploid per deme, recovers the same patterns while directly relating genetic variation to the underlying coalescent processes. When recombination is sufficiently low, we found a BGS-driven regime for weakly co-dominant mutations, characterized by lower diversity and increased genetic differentiation (FST). For recessive mutations, we first identified an AOD-driven regime, characterized by increased diversity and lower FST values followed by a transition to a subsequent BGS-driven regime. Genealogies were similarly impacted by deleterious mutations: BGS shrunk coalescent times and produces a shift towards lineage sorting topologies, while AOD stretched coalescent times and produces a shift toward incomplete lineage-sorting topologies. These patterns were weakened by gene flow, with FST and topologies remaining close to expected under neutrality, while diversity and coalescence times remained robust to demography. Our results provide clear evidence of BGS, AOD, and of their transition in a structured model with gene flow…
Susceptibility to viral infection varies widely but is not fully explained by genetics, immune status, or exposure level. We show that time of day strongly influences infection outcome, with up to 100-fold differences in enteric viral burden depending on infection timing. This temporal gating is abolished in mice lacking a functional circadian clock. We identify the antiviral transcription factor IRF1 as a direct target of the circadian transcription factor BMAL1, resulting in rhythmic expression of a basal antiviral gene program prior to infection. Loss of IRF1 eliminates this program and abrogates time-of-day dependent differences in viral replication. This circuit operates within intestinal myeloid cells, establishing a preexisting antiviral state. These findings indicate that the circadian clock programs host susceptibility in the intestine, before infection occurs.
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.
Linkage disequilibrium (LD) makes causal GWAS variants indistinguishable from correlated neighbours; resolving them is the fine-mapping problem, and the challenge is species-specific: humans face dense ancestry-imbalanced LD, yeast and *Arabidopsis* exceptionally long LD, and crop germplasm sparse and fragmented annotations that defeat human-biobank curation pipelines. Bayesian fine-mappers integrate annotations as flat per-variant priors, discarding the relational structure linking variants to tissue-specific eQTLs, pathways and protein-protein interactions. Hierarchical belief propagation (HBP) on a variant-gene-pathway factor graph matches Bayesian baselines at 5-40x speed; an annotation-adaptive complement, graph-augmented fine-mapping (GAFM), wins 27-2 against SuSiE at weak signal and recovers *LDLR*, *APOE*, *LPL*, *GCKR* and *ANGPTL3* at single-variant resolution across four Pan-UK Biobank ancestries. On the 3,000 Rice Genomes grain weight + shape panel, mixture-prior posterior reweightings of GAFM/HBP and their ensemble (GAFM-MX, HBP-MX, ENS) reach 47.6% top-1-PIP exact-position recovery of 21 panel-matched stable QTNs - the highest of any method, exceeding SuSiE (28.6%) and SBayesRC (14.3%) - at 200-700x SuSiE's per-locus speed. Across 692 leads in four species, a non-uniform per-variant prior, not uniform high coverage, lets the graph break LD ties: adding a regulatory-element flag to an otherwise uniform human cache flips HBP narrower than GAFM from 0% to 88% on 321 Pan-UKB leads. These results recast multi-omics fine-mapping as a non-uniform-prior-curation problem rather than a uniform-coverage problem, and reframe post-GWAS analysis as message passing over biological structure rather than weighted regression on flattened annotations.
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.
Staphylococcus aureus encounters diverse environmental conditions during colonization and infection, including fluctuations in nutrient availability, oxidative stress, and oxygen limitation. Adaptation to these environments requires regulatory systems that coordinate stress responses with metabolic remodeling. The extracytoplasmic function sigma factor SigS contributes to stress adaptation and virulence in S. aureus and directly activates expression of the sroAB operon, which encodes the small proteins SroA and SroB. While previous work demonstrated that SroA participates in feedback regulation of sigS expression, the broader physiological role of SroA has remained unclear. To define the regulatory functions of SroA, we performed RNA sequencing following inducible overexpression of sroA in S. aureus. Transcriptome analysis revealed extensive remodeling of gene expression, with approximately 200 transcripts significantly altered. Transcriptome analysis revealed coordinated repression of metabolic pathways (including nitrate respiration and nucleotide biosynthesis) alongside activation of stress-response and nutrient acquisition genes. Northern blot and quantitative RT-PCR analysis confirmed repression of narG and narJ transcripts following SroA overexpression. Consistent with these transcriptional changes, nitrate reduction assays demonstrated that SroA overexpression reduces nitrate respiration activity. In addition to repression of nitrate respiration genes, SroA overexpression broadly suppressed genes involved in de novo purine and pyrimidine biosynthesis. In contrast, transcripts associated with stress responses and nutrient acquisition, including the SOS-associated gene sosA and the phosphate transport gene pstS, were upregulated. Together, these findings identify SroA as a regulator that links stress-responsive signaling to metabolic remodeling in S. aureus, particularly through modulation of nitrate respiration pathways.