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Results for “genetics”

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TigerAI: An AI-powered genetic evidence platform to support clinical development

Genetic evidence is a major determinant of clinical success in drug development, yet its aggregation has long relied on laborious human curation. Large language models (LLMs) have the potential to rapidly synthesize knowledge across biomedical resources, providing a route to scalable AI-driven genetic evidence generation. Here we develop a novel domain-grounded instruction framework to systematically evaluate GPT-5 for producing genetic evidence relevant to clinical trial success. Using 13,022 target-indication pairs from a comprehensive drug development database, we benchmark LLM-derived evidence against a recent exhaustive human expert-curated study. We find that GPT-5 yields genetic evidence that is at least as informative as expert curation for inferring clinical success, while substantially expanding coverage relative to traditional curation resources. Building on these results, we introduce TigerAI (https://tigerai.bio/), a dual-purpose platform for AI-powered genetic evidence that (i) benchmarks emerging state-of-the-art LLMs and (ii) provides an accessible service for querying reliable AI-generated genetic evidence. These contributions outline a practical, domain-grounded pathway for integrating AI-powered genetic evidence into drug development pipelines and for realizing the potential of LLMs to inform clinical success.

genetics

Genetic legacy in soil seedbanks after grassland conversion to plantation forests: evidence from Potentilla freyniana

Semi-natural grasslands are important ecosystems supporting biodiversity in Japan, but their area has declined rapidly due to land-use change and abandonment of traditional management practices such as mowing and burning. Although the conservation of genetic diversity is essential for the long-term persistence of grassland plants, little is known about the genetic diversity retained in soil seedbanks following conversion of grasslands to plantation forests. In this study, we compared the genetic diversity and population structure of above-ground and soil seedbank populations of the grassland perennial forb Potentilla freyniana across three sites in each of three land-use types: burned grasslands, deciduous plantation forests, and evergreen plantation forests (plantation ages approximately 21-62 years) on the Kaida Plateau, central Japan. Soil seedbank populations were obtained from soil samples through germination experiments, and genetic analyses were conducted using newly developed simple sequence repeat (SSR) markers. Genetic diversity was assessed using expected heterozygosity, allelic richness, and private allelic richness, population structure was evaluated using analysis of molecular variance (AMOVA), STRUCTURE analyses, and pairwise FST. Soil seedbank populations maintained levels of genetic diversity comparable to those of above-ground populations, and no significant differences were detected between the two population types. Furthermore, soil seedbank populations in evergreen plantation forests, where above-ground individuals of P. freyniana were absent, retained genetic diversity comparable to that observed in burned grasslands. AMOVA detected no significant genetic differentiation between above-ground and soil seedbank populations. These results suggest that high levels of genetic diversity can persist in soil seedbank populations for decades after forest establishment and highlight the potential importance of soil seedbanks as genetic resources for grassland restoration.

ecology

An agent-based 3D model of non-genetic adaptation in cancer tissues under electrical, mechanical, and hypoxic stress

Non-genetic adaptation enables cancer cells to alter their phenotype under stress without requiring new mutations. However, the mechanisms by which electrical, mechanical, and hypoxic cues combine to shape this process in 3D tissues remain poorly understood. This work presents an agent-based tumor model that integrates vascular oxygen supply, a globally imposed electric field, mechanically mediated crowding and compression cues, phenotype transitions, cell growth, mitosis, death, and inheritance of adaptive memory across division. The simulated tumors exhibit a three-stage trajectory consisting of necrosis onset, transient collapse of live mass, and partial regrowth accompanied by progressive accumulation of adapted cells. Continuous electrical stimulation produces a dose-dependent reduction in live mass while markedly increasing the adapted fraction, with comparatively limited changes in final necrotic burden. This response is strongly conditioned by mechanics and reshapes (and is reshaped by) adaptive capacity. Pulsed stimulation further shows that, in the model, electric field amplitude and temporal schedule jointly determine memory phenomena, phenotypic diversification, and growth recovery. These results show that coupling local oxygen availability, mechanical constraints, electrical forcing, and history-dependent phenotype transitions can generate distinct tissue-level patterns of phenotypic heterogeneity. Both stimulus magnitude and temporal protocol influenced the resulting population structure, suggesting that the history of physical stress may be an important determinant of adaptive dynamics in spatially organized tumor models.

biophysics

Genetic Disruption at the CIP2A Locus Modulates T Cell Responses and Attenuates Experimental Autoimmune Encephalomyelitis

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system (CNS) driven by pathogenic T cell-mediated inflammation. Fingolimod (FTY720), an approved therapy for MS, is an established activator of protein phosphatase 2A (PP2A). However the contribution of PP2A in autoimmune neuroinflammation remains incompletely understood. Here, we addressed this question using experimental autoimmune encephalomyelitis (EAE), a murine model of MS, in mice carrying a genetic disruption of the locus encoding cancerous inhibitor of protein phosphatase 2A (CIP2A), an endogenous inhibitor of PP2A. Mice with disruption of the CIP2A locus, the knock out (KO) mice, exhibited attenuated EAE severity compared with wild-type (WT) controls. Histological and flow-cytometric analyses revealed markedly reduced infiltration of mononuclear cells, including CD4 and CD4CXCR6 encephalitogenic T cells, in the CNS of diseased KO mice. Reduced numbers of these T cell populations were also observed in peripheral lymphoid organs of the Cip2a-deficient mice during EAE, while T cell abundance was comparable under steady-state conditions, suggesting impaired activation-induced expansion rather than altered homeostasis or migration. Single-cell RNA sequencing of CNS and lymph node immune cells revealed changes in cell-type abundance and gene expression. Notably, Il17a expression was reduced in CNS CD8+ T cells and showed a similar trend in {gamma}{delta} T cells. Together, our findings reveal that genetic disruption at the CIP2A locus attenuates EAE, possibly by limiting the expansion and accumulation of encephalitogenic T cell populations in CNS. These results identify the CIP2A locus as a previously unrecognized regulator of T cell-driven autoimmune neuroinflammation and provide new insights into mechanisms that restrain pathogenic T cell responses during EAE.

immunology

Paternal regulation of H3K4 methylation supports tumor suppressor networks in mammals intergenerationally

Paternally-inherited epigenetic information can influence phenotype in offspring (1). Here, we identify a critical mechanistic contribution of KDM6A (UTX), an X-linked histone modifier and tumor suppressor, in regulating transmissible epigenetic information in mammalian sperm. Paternal loss of KDM6A increases cancer risk in genetically wild type offspring, but how Kdm6a knockout sperm transmit this effect at the molecular level is unknown (2). We find that KDM6A functions in spermatogenesis to promote methylation of histone H3 lysine 4 (H3K4) via selective interaction with the COMPASS complex methyltransferase KMT2C (MLL3). KMT2C and KDM6A are coordinately recruited to promoters of active genes in spermatogenic cells, contrasting with recruitment to intergenic enhancers in other cell types (3, 4). Loss of KDM6A disrupts H3K4 methylation at promoters of tumor suppressor genes in spermatogonia, and some of these defects persist in epididymal sperm and correspond to impaired expression in preimplantation embryos. These genes are also misregulated in normal and malignant hematopoietic tissue of genetically wild type offspring, indicating that impaired H3K4 methylation in KDM6A-deficient male germ cells may preferentially alter regulation of tumor suppressor gene networks in development across generations.

genetics

Parallel evolution under constraint shapes echinocandin resistance in Candida auris

Drug resistance emerges repeatedly in outbreaks of Candida fungal pathogens, but little is known about its origins or persistence. Here, we investigated the evolutionary processes shaping echinocandin resistance in Candida auris, a globally emerging and predominantly clonal fungal pathogen. Genome-wide association across over 600 isolates identified mutations in the {beta}-1,3-glucan synthase gene FKS1 as the most significant driver of resistance to an echinocandin drug. Ancestral reconstruction of this population traced shared resistance mutations among small groups typically consisting of 2-3 closely related isolates, but clusters could include up to 16 isolates. Nearly all resistant clusters consisted of isolates collected in the same year and region, consistent with local transmission. To further examine population-level selection, we measured adaptive signatures in FKS1 and the highly diverged paralog FKS2 across 22,000 genomes. This revealed excess nonsynonymous polymorphisms in FKS1, primarily due to independent, recurrent mutations at resistance hotspots, consistent with parallel evolution and incomplete fixation of adaptive alleles. In FKS2, there is no evidence of hotspots and little support for diversifying selection. Together, these results indicate that resistance mutations emerge under strong genetic constraint, with adaptation restricted to only one FKS homolog and predominantly at mutational hotspots.

genetics

Breeding cassava for intercropping with cowpea: monoculture selection captures most intercrop selection gain, but targeted testing remains necessary

Intercropping dominates smallholder cassava production in sub-Saharan Africa, yet cassava breeding programs evaluate genotypes exclusively under monoculture. Despite consistently reported system-level yield advantages, cassava yield is reduced by 17 to 51% under intercropping, indicating a need to reduce this competitive disadvantage through breeding. However, the quantitative-genetic foundations of intercrop breeding remain uncharacterized for tropical root crop systems. We hypothesized that monoculture selection would capture most, but not all, genetic merit for intercropping and that a limited tester set would be sufficient if general mixing ability predominated. We evaluated 120 cassava clones previously selected under monoculture in IITA advanced yield trials, testing them under monoculture and in intercrop with two contrasting cowpea varieties across two years at Ibadan, Nigeria. Spatial mixed models quantified genetic variation, genotype by cropping system interaction, cross system genetic relationships, realized selection gain, mixing ability, tester effects, and land equivalent ratio. Intercropping reduced cassava fresh root yield by 19%, but total land equivalent ratios exceeded 1.0 for all clones, confirming a system-level land use advantage. Cassava performance under intercropping was heritable, with estimates of 0.50 to 0.75, and genotype by cropping system interaction was not significant. Genetic correlations between monoculture and intercrop performance were high and approached unity (rg = 0.92 to 0.99), and selection efficiency was 26 to 44% at 10% intensity, confirming that high genetic correlation does not guarantee effective indirect selection. Monoculture selection captured approximately two-thirds of direct intercrop gain. General mixing ability dominated, specific mixing ability was negligible, and producer effects explained 20 to 47% of intercrop variance. The two architecturally and phenologically contrasting cowpea varieties had limited influence on cassava rankings. Here, we show for the first time that cassava breeding for intercropping can retain monoculture selection during early stages while adding two representative cowpea testers at the advanced trial stage. This staged strategy aligns cassava breeding with diversified smallholder systems without creating a separate pipeline.

plant biology

A patient-derived LMX1B variant causes tissue-specific manifestations of nail-patella syndrome in mice

Nail-patella syndrome (NPS) is a multisystem disorder caused by pathogenic variants in LMX1B and is characterized by dysplasia of the nails and patellae as well as extraskeletal complications such as progressive nephropathy and glaucoma. We generated a CRISPR/Cas9 knock-in mouse carrying the R252Q substitution, corresponding to a human LMX1B variant associated with renal-predominant disease. Phenotypic analysis revealed that homozygous mice were viable, but they displayed marked growth retardation and severe bilateral ocular opacity. Interestingly, while this model exhibited clear skeletal and ocular defects, the renal phenotype was relatively mild, although increased urinary albumin excretion, focal glomerular basement membrane abnormalities, and subtle changes in renal gene expression were detected. Beyond the classical NPS hallmarks, mutant mice also displayed midbrain morphological abnormalities, suggesting broader developmental consequences of this LMX1B variant. This patient-derived variant model not only recapitulates the pleiotropic features of NPS but also demonstrates organ-specific susceptibility to the R252Q substitution, providing a foundation for elucidating the complex molecular mechanisms underlying multisystem disease.

genetics

X-inactivation escapee domains are CTCF-cohesin independent chromatin compartments

X-chromosome inactivation involves chromosome-wide gene silencing accompanied by extensive chromatin changes, as well the loss of topologically associating domains. Yet discrete regions of the inactive X chromosome retain activity within localised 3D domains, which contain active genes that variably escape from X inactivation. The transcription factor and architectural protein CTCF has been proposed to be implicated in escape by insulating escape domains or sustaining their topology via cohesin-mediated loop extrusion. Here, we test the role of CTCF and cohesin in escape using acute degron-mediated depletion of CTCF and RAD21 in neural progenitor cells with established escape profiles. Although CTCF occupancy correlates with escape status on the inactive X chromosome, its removal - together with loss of loop extrusion - does not disrupt escapee gene expression, or domain organization, nor does it result in spreading of silencing or activation of genes in cis. Rather, we show that facultative escape regions are self-sustaining compartments of active chromatin enriched in H3K27 acetylation and depleted in H3K27 methylation, with the magnitude of compartment strength scaling up with the degree of transcriptional activity on the inactive X chromosome. These active escapee compartments are propagated independently of CTCF and RAD21-dependent 3D architecture. Our findings identify chromatin compartmentalization as the primary feature of facultative escapee domains.

genetics

A mutation-agnostic and allele-specific ASO strategy demonstrates potent functional rescue and retinal preservation in RHO-linked retinitis pigmentosa

Autosomal dominant retinitis pigmentosa (adRP) caused by RHO mutations is a leading form of inherited retinal degeneration. Extensive allelic heterogeneity of RHO pathogenic variants limits the translational applicability of mutation-specific gene therapies. To address this, we developed SNARE (SNP-guided Silencing of Aberrant RHO Expression), a mutation-independent, allele-specific antisense oligonucleotide (ASO) strategy. SNARE selectively suppresses mutant RHO transcripts by targeting the common, benign c.-26A/G single-nucleotide polymorphism (SNP) as an allelic discriminator. Candidate gapmer ASOs were screened in engineered reporter lines and validated in patient-derived retinal organoids, identifying RHOligo-A as the lead c.-26A-targeting candidate. In vitro, RHOligo-A achieved robust, preferential knockdown of the target allele, improving RHO localization in retinal organoids, and demonstrated a favorable safety profile with minimal transcriptomic off-target effects and no detectable immunostimulatory activity. Subsequent validation in a novel, humanized RHOP347L/WT mouse model, achieved sustained c.-26A-linked allele-selective suppression, retinal structure preservation, and significantly restored visual function, upon a single intravitreal administration. These findings establish RHOligo-A and SNARE as a scalable, mutation-independent therapeutic platform with strong translational potential and substantial clinical reach for RHO-associated adRP.

genetics

Hidden drivers of restoration: Persistent divergence in soil microbiome functional capacity post-habitat reconstruction

Ecosystems today are facing unprecedented environmental stress, leading to large-scale losses of habitat and ecosystem services. To address this, reconstructive efforts aim to restore habitat features and their natural complexity, biodiversity, and function. However, many reconstructive efforts fail to consider microbial communities, even though they play key roles in decomposition, nutrient cycling, and plant and animal health. Here, we use shotgun metagenomic sequencing to compare the structure and functional capacity of soil microbial communities from natural Everglades tree islands and islands constructed within a landscape-scale experimental Everglades restoration effort, followed by a manipulative greenhouse experiment to link tree sapling traits with microbiome functional genetic divergence. We found that constructed and natural island microbiomes exhibited strong, robust, and persistent divergence in both taxonomic and functional composition, with natural island microbial communities having greater functional genetic diversity and redundancy. Furthermore, we identified enrichment in functional pathways in constructed island microbiomes such as those involved in pollutant degradation that may reflect continued disturbance leading to shifts in microbiome functional profiles. Despite their capacity for functions such as nitrogen cycling we found to be important for supporting sapling growth, constructed island microbiomes displayed reduced functional genetic diversity and redundancy and were enriched in pathways associated with environmental disturbance, suggesting a potentially diminished capacity for long-term resilience. Overall, our assessment of soil microbial communities in reconstructed and natural habitats emphasizes how reconstructive restoration can impact microbial functional repertoires and highlights the importance of these hidden players in management and restoration of ecosystem health.

ecology

A Sequential Assembly Mechanism for Stable Cdc13 Dimerization on Telomeric DNA

The telomere-binding protein Cdc13 specifically binds to single-stranded telomeric DNA, playing a critical role in telomere protection and length regulation. While extensive biochemical, molecular biological, and genetic studies have shown that Cdc13 can form dimers or oligomers in solution and bind telomeric DNA with high specificity, the dynamic mechanism of its loading onto telomeres is less well characterized. Using two single-molecule methods, single-molecule fluorescence resonance energy transfer (smFRET) and colocalization single-molecule spectroscopy (CoSMoS), we demonstrate that Cdc13 initially loads onto telomeres as a monomer. This is followed by the recruitment of a second monomer, forming a stable Cdc13 dimer on a 12-nucleotide telomeric DNA segment. Although genetic studies suggest that monomeric Cdc13 binding alone is insufficient to maintain telomere length, it underscores the Cdc13 monomers regulatory importance in coordinating telomere synthesis and protection. This monomer-to-dimer transition provides a mechanistic basis for understanding the multi-tasked roles of Cdc13 in telomere replication and protection.

biophysics

A transcriptomic and spatial map of serotonin autoreceptor expression in Drosophila

Serotonin is an evolutionarily ancient neurotransmitter that modulates an array of behaviors such as mood, sleep, and appetite across species. Serotonin acts primarily by binding to serotonin receptors, which are expressed in post-synaptic neurons (heteroreceptors) and serotonergic neurons themselves (autoreceptors). Serotonin autoreceptors modulate serotonergic tone, the foundational principles of which have been excellently demonstrated in vertebrate and invertebrate models. However, many aspects of the mechanisms and contexts in which this modulation occurs are still unclear. Drosophila melanogaster is a powerful model organism that can provide unique insights into autoreceptor function by the ability to perform precise spatial and temporal genetic manipulation with structural and functional readouts / behaviors of serotonin systems. However, a systematic characterization of serotonin autoreceptor expression in Drosophila has not been conducted. Here we use single-cell sequencing and genetic labeling to show that all five serotonin receptors are expressed in serotonergic neurons and map their expression at both the larval and adult stages of development. This is the first evidence of 5-HT2A and 5-HT7 expression in serotonergic neurons in any organism. Moreover, the unique combinations of autoreceptor expression in specific neuronal clusters will aid in the development of novel hypotheses for autoreceptor function, and demonstrates the utility of Drosophila as a model organism to study the function of serotonin autoreceptors.

neuroscience

Cross-Kingdom Control: Yeast Prion Protein Modulates Host Physiology in Drosophila

Prions, once mainly studied for their pathogenic roles, are now gaining recognition as adaptive elements in microbial physiology. Over one-third of wild yeast isolates harbor prion proteins, yet their impact on host-microbe interactions remains poorly characterized. Given the ecological dominance of yeasts in the Drosophila mycobiome, we leveraged the Drosophila melanogaster-Saccharomyces cerevisiae system to investigate how the mycobiome-derived prion, [MRPL10+], modulates host physiology. We show that flies exposed to [MRPL10+] yeast exhibit significantly enhanced cold tolerance and increased locomotor activity. This effect persists with heat-killed yeast and diluted culture, suggesting a stable, potent bioactive factor. Using the genetically diverse Drosophila Global Diversity Lines (GDL), we identified natural variation in responsiveness to [MRPL10+] yeast. Genome-wide association and functional RNAi screening revealed a gut-brain signaling axis involving genes critical for digestion, intercellular communication, transcription regulation, and neural transmission. Notably, serotonin and octopamine pathways were essential for [MRPL10+]-induced changes in cold tolerance and locomotion, implicating neuromodulatory circuits in prion-mediated microbial signaling. Our findings establish a mechanistic link between a fungal prion and host metabolic and neural adaptation. This work provides the first genetic dissection of a prion-mediated host-microbe interaction, laying the groundwork for investigating beneficial prions in complex microbial communities and highlighting a new dimension of the mycobiomes influence on animal physiology.

evolutionary biology

Accurate detection of metagenomic strain-level associations using average nucleotide identity with StrainSpy

Genetic variation among microbial strains of the same species can profoundly influence their phenotypes, ecological functions, and impacts on human health. Traditionally, the relative abundance of a species has been used to identify associations between the microbiome and disease. However, this approach overlooks intra-species genetic variation and is susceptible to spurious correlations arising from the compositional nature of abundance data and microbial load. Fast, k-mer-based algorithms can now accurately estimate strain-level Average Nucleotide Identity (ANI) in metagenomes. Despite its value as an orthogonal metric for strain-level analysis, methods for conducting ANI-based association studies remain limited. To address this, we developed StrainSpy, a statistical algorithm that identifies associations between containment ANI and variables of interest across a wide range of study designs, including longitudinal and multi-cohort designs. Re-analysis of a study examining gut microbiota recovery in 12 healthy adults following antibiotic exposure revealed novel strain-level associations, including a reduction in strain-level diversity despite species persistence. Applying StrainSpy to a multi-cohort analysis of 3,414 colorectal cancer metagenomes identified novel strain-level associations with colorectal cancer. However, in a separate collection of microbiome-immunotherapy studies, no individual strain was consistently associated across cohorts. Importantly, across both datasets, StrainSpy informed containment ANI-based machine learning models achieved comparable accuracy to traditional abundance-based methods. StrainSpy is publicly available as an R package github.com/gtonkinhill/strainspy.

microbiology

Mechanism-based prediction of insertion-driven high pathogenicity avian influenza virus emergence

High pathogenicity avian influenza viruses (HPAIVs) emerge from H5 and H7 low-pathogenicity avian influenza virus progenitors through mutations that introduce a multibasic cleavage site in haemagglutinin. Although nucleotide insertions recurrently generate this motif, the molecular determinants of insertion and whether particular HA sequences are genetically predisposed to evolve toward HPAIV remain unknown. Combining experimental virology and thermodynamic modelling, we show that insertions arise through polymerase slippage controlled by local product-template duplex thermodynamics within the viral polymerase catalytic site. Predicted RNA secondary structures outside the polymerase are not required for high-frequency insertions and only modestly modulate insertion rates. We formalize this mechanism in HPAIVpredict, which predicts insertion profiles, recapitulates intermediates associated with documented HPAIV emergence events and identifies H5 and H7 sequence backgrounds predisposed to acquire functional multibasic cleavage sites.

microbiology

Autism-risk gene mutations convergently disrupt sexually dimorphic oxytocin circuits to lower social engagement

Autism arises from diverse genetic risk factors, yet how they converge to produce core symptoms and contribute to its sex bias remains unestablished. Oxytocin increases sociability in multiple murine autism models, presenting an opportunity to identify a potentially shared mechanistic basis across etiologies. Here we show that spontaneous social investigation triggers overlapping patterns of aberrant functional connectivity across social and sensory brain regions in two knockout (KO) mouse models, which are rescued by oxytocin. We also report that, during social investigation, wildtype mice exhibit sexually dimorphic oxytocin release and neuronal activity dynamics in the nucleus accumbens and the amygdala. These patterns are disrupted in both KO models, but can be restored by sex- and circuit-specific stimulation of endogenous oxytocin release, accompanied by enhanced social engagement. These findings identify impaired oxytocin recruitment of sexually dimorphic social circuits as a convergent consequence of autism-risk gene mutations that may underlie low sociability.

animal behavior and cognition

Characterization and pharmacological modulation of Alzheimers disease-associated human microglial states

Microglia are central mediators of Alzheimers disease (AD) pathogenesis, yet the mechanisms driving disease-associated microglial states and their therapeutic modulation remain poorly understood. Here, we integrated single-nucleus transcriptomic datasets across the AD spectrum and identified disease- and lipid-associated microglia (DLaM) as a major AD-enriched population linked to genetic risk, neuropathology and cognitive decline. To model this state experimentally, we screened AD-relevant perturbations in human induced pluripotent stem cell (hiPSC)-derived microglia and found that ferric ammonium citrate (FAC) reproducibly induced a DLaM-like state characterized by lipid accumulation, lysosomal dysfunction and impaired A{beta} phagocytosis. Using a transcriptomics-based state-reversion screen, we identified LY2090314 as a potent modulator that restored microglial function and induced a distinct lysosomal-metabolic state. These findings establish a framework for transcriptomic disease-state-guided therapeutic discovery in AD.

neuroscience