Biology subjects

Chang, S.

Publications and source records attributed to Chang, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Joint localization and testing reveals spatial context of differential expression

Multi-subject spatial transcriptomics is increasingly used to identify molecular differences across individuals and conditions while resolving where in tissue those differences occur. Yet subject-level differential expression (DE) analyses commonly require spatial regions to be specified in advance, separating localization from testing. Here we present SpaceDX, a framework that uses gene-specific attention-based spatial weighting to jointly test differential expression and localize the spatial expression patterns contributing to these associations. In simulations, SpaceDX outperforms cluster-based DE methods when differential expression does not align with predefined spatial boundaries. Across two multi-subject mouse brain datasets, SpaceDX detected 45.8% more DE genes than regional DESeq2 pseudobulk in a chronic stress model, while in an Alzheimer's disease model combining SpaceDX with DESeq2 increased discovery by 19.1% relative to DESeq2 alone. Across both datasets, the learned maps provided spatial context for condition-associated expression signals in addition to gene-level significance. In the chronic stress model, for example, oligodendrocyte- and myelin-associated genes showed shared localization to corresponding brain structures. Together, these results show that the spatial context of differential expression can be inferred jointly with gene-level associations, recovering signals obscured by regional aggregation without requiring the relevant tissue context to be defined in advance.

bioinformatics↗

bioRxiv2026

geoGraph: Connectivity modelling across geographic space with hexagonal discrete global grids

1. Estimating the movement and connectivity of organisms across landscapes is central to research in ecology and evolutionary biology. Although graph-based approaches representing geographic space as weighted networks provide a flexible and computationally efficient framework for such analyses, existing tools either perform their computations only on rectangular raster grids, thus introducing systematic directional and area distortions at global scales, or rely on bespoke pipelines that limit the general applicability of recent hexagonal-grid analyses. 2. To overcome these shortcomings, here we present geoGraph, an R package that brings graph-based spatial modelling to discrete global hexagonal grids. By representing landscapes on an equal-area hexagonal tessellation of the sphere, geoGraph enables global-scale analysis without projection distortion while retaining the flexibility of the graph framework and the performance of the graph and RBGL/Boost libraries. The package integrates both raster- and vector-based GIS data into a single cost surface, supports custom grids at various resolutions, and provides a complete pipeline from raw GIS layers to graph-algorithmic outputs, together with tools for visualising and interactively editing graphs. 3. We illustrate geoGraph by revisiting previous studies of isolation by distance among human populations in the Human Genome Diversity Project panel. At a global scale, restricting movement to land raised the correlation between geographic and genetic distance from r = 0.74 (great-circle) to r = 0.84. On a finer grid within Asia, accounting for terrain ruggedness improved the fit, with the best-fitting models implying reduced movement across the Himalaya and Tibetan Plateau. These analyses demonstrate that geoGraph can model movement and connectivity appropriate to the desired spatial scale and that the level of geographic realism required is itself scale-dependent. 4. By combining discrete global grids with the power of graph algorithms, geoGraph enables seamless connectivity analysis from landscape to global scales. It is broadly applicable across landscape genetics, phylogeography, conservation planning, and studies of human dispersal, and is particularly suited to large-scale problems that rectangular-raster tools cannot address without distortion.

bioinformatics↗

bioRxiv2026

A lifespan-scale single-cell atlas defines an early-childhood immunometabolic transition linked to age-referenced immune states

Childhood represents a critical period with rapid metabolic and immune remodeling, during which perturbations may have lasting consequences for health. We integrated single-cell RNA sequencing (scRNA-seq) profiles of peripheral blood mononuclear cells (PBMCs) from 2,008 healthy individuals aged 0-100 years. Age-resolved modeling highlighted an early-childhood transition centered at age 6, characterized by coordinated remodeling of metabolism-related transcriptional programs, particularly in monocyte and B-lineage cells. Matched serum metabolomics and lipidomics in a pediatric subcohort detected a temporally concordant wave of metabolite and lipid changes around ages 6-8 and extensive metabolite/lipid-transcript associations, prominently involving steroid and phospholipid species. Building on these findings, we developed an immunometabolic transition score and age-specific reference chart, which were evaluated in an independent healthy cohort and applied to quantify deviations in pediatric immune disorders. These findings highlight a coordinated immunometabolic transition in early childhood and provide an age-referenced framework for distinguishing atypical immune-state variation from healthy age-associated variation.

immunology↗

bioRxiv2026

The bZIP transcription factor PnAda1 functions as a regulator of virulence, fungicide tolerance and necrotrophy in the wheat pathogen Parastagonospora nodorum

Ada1 (All Development Altered-1) is a conserved but poorly characterised basic leucine zipper (bZIP) transcription factor found throughout filamentous fungi. In the wheat pathogen Parastagonospora nodorum, PnAda1 is required for full virulence and is transcriptionally associated with the virulence regulator PnPf2, but its biological functions remain unclear. Here, we combined comparative RNA sequencing with targeted phenotypic analyses to define the role of PnAda1 during vegetative growth and host infection. Deletion of PnAda1 did not abolish pathogenicity but delayed disease progression, with the PnAda1-deletion mutant transcriptome at 7 days post-inoculation resembling that of the wildtype SN15 at 3 days. This developmental delay was associated with impaired activation of early infection-associated genes, including putative carbohydrate-active enzymes, proteases, transporters and other host-colonisation factors. In contrast, expression of major necrotrophic effector genes was not reduced and instead remained elevated during later stages of infection, indicating that PnAda1 is required for the timely progression of infection-associated transcriptional regulation rather than direct activation of effector genes. Beyond virulence, transcriptomic and phenotypic analyses revealed roles for PnAda1 in nitrogen assimilation, carbon utilisation, abiotic stress responses and fungicide sensitivity. Notably, PnAda1 deletion increased sensitivity to succinate dehydrogenase inhibitor fungicides and reduced expression of succinate dehydrogenase subunit genes. Collectively, our findings identify PnAda1 as a broad regulator of developmental and infection-associated transitions in P. nodorum and expand current understanding of the transcriptional network underlying virulence, metabolism and stress adaptation in an important fungal wheat pathogen.

molecular biology↗

bioRxiv2026

Chromosome topology gates productive RecA homology search

In homologous recombination, DNA repair depends on recombinase filaments finding homologous templates on chromosomes whose topology is continually remodeled by replication and transcription. How dynamic chromosome topology affects homology search and DNA repair remains unknown. By combining live-cell imaging of RecA-mediated homology search with single-molecule assays on topologically-defined DNA substrates, we show that DNA supercoiling acts as a selectivity filter for productive homology search. In Caulobacter crescentus cells, supercoiling is dispensable for the filament movement required for homology search, but required for homology target capture and repair. In vitro, filaments transiently sample both relaxed and supercoiled DNA, yet selectively commit to capture only on negatively supercoiled targets. Mechanistically, we find an extreme kinetic preference (~100-fold) of filaments towards negatively supercoiled DNA targets; this topological preference is independent of DNA compaction, pins plectonemes at the capture site, and is conserved across diverse bacterial RecA homologs. Our findings establish that chromosome topology physically regulates homology search and DNA repair.

biophysics↗

bioRxiv2026

CellOS: Learning a World Model of Cellular State through Joint Embedding Prediction

Foundation models learned from single-cell transcriptomes are central to the prospect of AI virtual cell that can represent, query and predict cellular state. However, most current single-cell foundation models learn from a single view of gene expression and are optimized primarily through reconstruction or next-token prediction. As a result, they capture expression abundance but cannot explicitly reconcile complementary views of cellular state. Here we present CellOS, a multi-view foundation model that learns cellular representations from paired expression and perception views. CellOS integrates complementary views through a scalable three-stage training strategy that combines causal cell-sentence language modelling, function-preserving dense-to-mixture-of-experts expansion and latent-space alignment via an LLM-JEPA objective. Using this framework, we trained a 12-billion-parameter model on 390.5 million single-cell transcriptomes. Across diverse benchmarks spanning cell-state annotation, batch integration and perturbation-response prediction, CellOS consistently outperformed state-of-the-art single-cell foundation models. Together, these results suggest that predictive alignment between complementary cellular views provides a scalable path toward representation-centric cellular world models and transferable AI virtual cells.

bioinformatics↗

bioRxiv2026

The Logic of Thalamic Inputs onto the Molecular Taxonomy of Cortical Neurons Reveals a Visual Hierarchy

The hierarchical organization of sensory cortices and the rich molecular taxonomy of their cell types are defining features of the mammalian cortex. Cortical areas along this hierarchy are reciprocally connected via the thalamus through bottom-up and top-down projections. The logic through which these projections map onto the cellular taxonomy of the cortex is, however, poorly understood. Here we combine an anterograde transsynaptic tracer with spatial transcriptomics to reveal the molecular and spatial identity of mouse visual cortical neurons downstream of thalamic starter neurons across visual cortical areas. Distinct thalamic inputs target characteristic sets of molecularly defined cortical neurons, forming bottom-up or top-down "signatures" defined by cell-type composition and the ratio of GABAergic to glutamatergic neurons. These signatures reveal a hierarchy spanning thalamic nuclei and visual cortical areas, independently predicted by the molecular and cellular similarities between cortical areas. This work uncovers basic principles of how bottom-up and top-down thalamic inputs map onto the cellular taxonomy in the visual cortex and establishes a cellular framework for the cortical hierarchy.

neuroscience↗

bioRxiv2026

Chemogenetic Inhibition of Lateral Hypothalamus Inputs to the Paraventricular Thalamus Reduces Goal-Tracking in a Behaviorally Flexible Subgroup of Male Rats

The paraventricular nucleus of the thalamus (PVT) has emerged as an important node in circuits regulating motivated behavior. The neuronal pathway from the lateral hypothalamus (LH) to the PVT has specifically been shown to regulate arousal, feeding, and reward seeking. However, the involvement of the LH-PVT pathway in individual differences in cue-motivated behavior remains unclear. During a Pavlovian conditioned approach paradigm, when a reward is repeatedly preceded by the presentation of a cue, rats come to exhibit a conditioned response to the cue. One extreme of the population, sign-trackers (STs), approach and interact with the cue itself; while the other extreme, goal-trackers (GTs), approach the location of reward delivery. Intermediate responders (IRs) approach and interact with both the cue and reward location, without a clear preference. We utilized a Pavlovian conditioned approach paradigm to examine the effects of LH-PVT pathway inhibition on individual differences in cue-motivated behavior. A dual-vector approach was used to selectively express inhibitory chemogenetic receptors in the LH-PVT pathway. We found that inhibition of the LH-PVT pathway selectively attenuates the expression of goal-tracking behavior, without affecting sign-tracking. This effect is driven primarily by IR rats, as inhibition of LH-PVT neurons attenuates goal-tracking behavior in IRs, without impacting the response of STs or GTs. We speculate that the flexibility of responding in IR rats made them especially vulnerable to this manipulation. These findings identify the LH-PVT pathway as a selective contributor to reward-directed conditioned responding and a circuit substrate for behavioral flexibility. Significance StatementIndividuals differ in how reward-predictive cues motivate behavior, a feature linked to vulnerability and resilience to maladaptive reward seeking. The paraventricular thalamus (PVT), a midline hub with broad limbic connectivity, and its input from the lateral hypothalamus (LH) influences arousal, feeding, and reward seeking, but the role of the LH-PVT pathway in individual variability in cue-motivated behavior is unclear. We used chemogenetics to selectively suppress LH-PVT neurons during a Pavlovian conditioned approach paradigm. Inhibiting this projection reduced goal-tracking without altering sign-tracking, and this effect was driven primarily by intermediate responders, a phenotype characterized by behavioral flexibility. These results implicate LH-PVT signaling in reward-directed conditioned responding and suggest that this pathway contributes to flexible cue-motivated behavior.

neuroscience↗

bioRxiv2026

Rapid centromere turnover and the adaptive radiation of lemurs

Centromeres represent essential chromosomal structures required for faithful chromosome segregation during cell division but are paradoxically hypermutable, leading to centromere drive and reproductive isolation in closely related species. Using long-read sequencing, we generate nearly complete genomes (2.1-2.5 Gbp) from eight lemur species and characterize the sequence, epigenetic and cytogenetic structure of 223 strepsirrhini centromeres providing an alternative primate perspective of centromere evolution. No lemur centromere consists of -satellite DNA that typifies the haplorhine lineage; instead, each species evolved its own distinct higher-order centromeric repeat sequence, varying substantially in both monomer length (ranging from 41-548 bp) and primary sequence composition (GC percentages 28.7-67.9%) including centromere cooption of telomeric repeats in brown lemurs. Most centromeres show characteristic hypomethylation dip regions (110-300 kbp) as candidates for kinetochore attachment. The centromere sequence motif shows no apparent sequence homology among lemur genera, even for species separated by less than 15 million years (Lemur and Eulemur). We estimate a >6-fold increased rate in primary centromeric motif turnover in strepsirrhines when compared to haplorhines and this occurred in conjunction with positive selection of the CENP-B protein in lemur lineages. We propose that lemur radiation and centromere diversification are linked, whereby accelerated motif turnover provides a stasipatric barrier contributing to rapid chromosomal evolution.

genomics↗

bioRxiv2026

Dual Pathways of Extracellular ATP Action in Cancer Cells: Purinergic Signaling Driven Senescence and Macropinocytic ATP Internalization

BackgroundOpportunistic nutrient uptake is a hallmark of cancer metabolism. Cancer cells upregulate macropinocytosis to acquire extracellular nutrients to support growth and stress adaptation. We previously showed that extracellular ATP (eATP) is internalized by macropinocytosis and promotes multiple cancer phenotypes. Here, we tested whether eATP uptake is prevalent across cancers and whether eATP also induces senescence through purinergic receptor (PR) signaling. MethodsIntracellular ATP (iATP) levels were measured following eATP exposure across multiple cancer cell lines. eATP internalization was visualized in vitro and in vivo using a non-hydrolyzable fluorescent ATP analog together with high-molecular-weight dextran as a macropinocytosis marker. Senescence was quantified using three SA-{beta}-galactosidase assays and flow cytometry. Pharmacologic inhibitors of macropinocytosis and purinergic receptors were used to define pathway dependence. Combination treatments with the glucose transporter inhibitor DRB18 and the senolytic navitoclax were evaluated for antiproliferative effects. ResultseATP produced dose- and time-dependent increases in iATP across diverse cancer cell types. Imaging demonstrated widespread macropinocytic internalization of ATP in vitro and in tumor xenografts. eATP induced senescence in NSCLC cells, confirmed by multiple {beta}-gal assays and flow cytometry. PR inhibition significantly reduced senescence, whereas macropinocytosis inhibition had minimal effect on senescence induction. ConclusionseATP acts through dual pathways in cancer cells: macropinocytic internalization that elevates iATP and PR signaling that drives senescence. Targeting metabolic uptake together with senolytic therapy may offer a novel anticancer strategy.

cancer biology↗

bioRxiv2026

Scalable, Generalizable, and Uncertainty-Aware Integration of Spatial Multi-Omics Across Diverse Modalities and Platforms with SCIGMA

Recent advances in spatial omics technologies have enabled simultaneous profiling of transcriptomic, proteomic, epigenomic, metabolomic, and imaging data at high spatial resolution, offering unprecedented opportunities to dissect tissue complexity. However, integrating these diverse and large-scale spatial multi-modal datasets remains a major computational challenge. We present SCIGMA, a scalable and generalizable deep learning framework for spatial multiomics integration. SCIGMA introduces a novel uncertainty-aware contrastive learning objective and multi-view graph neural networks to preserve modality-specific signals while learning biologically meaningful joint representations. Unlike existing methods, SCIGMA provides spatially resolved uncertainty estimates, improving interpretability and identifying regions of biological or technical heterogeneity. SCIGMA is the first spatial multi-omics method to support integration of up to five modalities--as demonstrated on Spatial-Mux-Seq data--and its modular framework is extensible to future technologies with even more modalities. It also scales to over one million spatial locations, enabling analysis of ultra-high-resolution datasets such as VisiumHD and Xenium Prime. We evaluated SCIGMA across 19 datasets spanning 8 modalities, 10 tissues, and 9 platforms. On benchmarkable datasets, SCIGMA outperformed existing methods in spatial domain detection, modality preservation, feature reconstruction, and reproducibility. Across applications, it uncovered biologically meaningful structures, refined spatial domains, and modality-specific regulatory programs, while its uncertainty estimates revealed tissue regions with potential biological or technical variation. Together, SCIGMA provides a robust, flexible, and future-ready solution for scalable spatial multi-modal integration.

bioinformatics↗

bioRxiv2026

AI-Guided Structure-Aware Modeling and Thermal Proteomics Reveal Direct Demethylzeylasteral-ACLY Interaction

Target deconvolution of bioactive natural products (NPs) is frequently hampered by the inability of traditional thermal shift assays to distinguish direct ligand binding from indirect proteomic stabilization. Here, we developed an integrated target discovery framework combining MAPS-iTSA thermal proteomics with a structure-aware graph neural network (HoloGNN). This strategy identified ATP-citrate lyase (ACLY) as a high-confidence target of Demethylzeylasteral, a bioactive triterpenoid from Tripterygium wilfordii. Crucially, orthogonal biochemical assays, including surface plasmon resonance and limited proteolysis, validated its direct binding (KD = 9.86 M) and profound enzymatic inhibition (IC50 = 3.84 M). To establish the relevance of this interaction in the context of the source herb, thermal profiling of Tripterygium wilfordii extract together with ACLY-based affinity-ultrafiltration mass spectrometry supported ACLY engagement and identified Demethylzeylasteral as an ACLY-binding constituent. Given the established role of ACLY-mediated lipid metabolic reprogramming in psoriasis, we further evaluated the pharmacological significance of this interaction. Demethylzeylasteral suppressed keratinocyte proliferation, alleviated imiquimod-induced psoriasiform dermatitis, and reduced inflammatory cytokine expression in vivo. Single-cell RNA sequencing further revealed reversal of ACLY-SREBP-associated lipogenic reprogramming in keratinocytes. Collectively, these findings establish ACLY as a functionally relevant target of DEM and provide a robust AI-chemoproteomic paradigm for mechanism-guided NP drug discovery.

biochemistry↗

bioRxiv2026

A novel fracture lattice in spiny mouse skin facilitates tissue autotomy and regeneration

Autotomy is a unique phenotype whereby an animal sheds a body part to escape predation1-3. The timing and location of autotomy are tightly regulated by preformed planes of weakness (aka fracture planes) which facilitate tissue loss. While autotomy is often followed by regeneration, these phenotypes are rarely reported in mammals4-9. A notable exception are spiny mice (Acomys) which exhibit skin autotomy and more remarkably, complete tissue regeneration10-14. Presently, mechanisms underlying autotomy and complete regeneration in Acomys skin remain elusive. Here, we report the discovery of a honeycomb-like fracture lattice in Acomys skin whose design directs tissue destruction but also facilitates regenerative healing. Unlike the single continuous surface of a fracture plane, this fracture lattice consists of a three-dimensional array of hexagonal units whose boundaries guide tissue breakage. Moreover, we identify collagen VI as the main constituent of the fracture lattice and find that it is distinctly arranged to initiate fracturing and propagation of skin tearing. By preconditioning the tissue for autotomy, the fracture lattice dampens the damage-induced inflammatory response but also upregulates a pro-regenerative gene signature, accelerating skin appendage regeneration. Lastly, we discovered the key role of spiny hairs in fracture lattice formation, as inhibiting their development leads to abnormal pattern formation and changes in skin fracture mechanics. Our results present a novel example of a uniquely evolved structural adaptation in mammalian skin that links tissue patterning, autotomy and regeneration. We expect that the application of a modular compartment structure to artificial skin and other organ engineering may enhance resilience to injury and facilitate efficient regeneration.

developmental biology↗

bioRxiv2026

Cell type-specific gene regulatory network inference from single cell transcriptomics with ctOTVelo

Inferring gene regulatory networks (GRNs) from gene expression is a crucial task for understanding functional relationships. Gene expression data (transcriptomics) provide a snapshot of gene activity, encoding information about gene regulatory relationships. However, gene regulation is a dynamic process, modulating across time and with different cell types. Temporal GRN inference methods aim to capture these dynamics by utilizing time-stamped transcriptomics, gene expression data of similar samples captured across discrete timepoints, or pseudotime transcriptomics, computationally ordering cells based on an inferred trajectory. These methods can estimate constant or temporal gene regulatory relationships, but may not capture finer, cell type specific relationships. We propose ctOTVelo, an extension to our previous work to account for cell type specificity during GRN inference. ctOTVelo incorporates cell type labels or proportions when inferring the GRN from single cell transcriptomics data. Our methods achieve state-of-the-art performance in GRN prediction in time-stamped and pseudotime-stamped transcriptomics. Furthermore, ctOTVelo is able to generate cell type specific GRNs, allowing cell type resolution analysis of gene regulatory relationships.

genomics↗

bioRxiv2025

Vitreous Inflammation as an Early Indicator of Retinal Ganglion Cell Loss Following Acute Optic Nerve Injury in Mice

Retinal ganglion cell (RGC) degeneration in optic neuropathies is often preceded by neuroinflammatory changes, yet the earliest in vivo indicators of this process remain poorly defined. Here, we identified vitreous hyperreflective foci (VHRFs) by visible-light optical coherence tomography (vis-OCT) as an early inflammatory signature of RGC injury. Longitudinal vis-OCT imaging after optic nerve crush (ONC) revealed that VHRFs emerged as early as 6 hours post-injury and peaked before the significant RGC loss. Confocal analysis showed that these VHRFs corresponded to activated amoeboid microglia undergoing vertical migration from the outer to inner retina and horizontal movement toward the optic nerve head area. Similar amoeboid microglia were also observed in the anterior segment, suggesting a global ocular inflammatory response to the ONC injury. RNAscope in situ hybridization further demonstrated elevated IL-1{beta} expression in vitreous amoeboid microglia. Moreover, pharmacological blockade of IL-1 signaling with an IL-1 receptor antagonist significantly reduced VHRFs, suppressed microglial migration, and delayed RGC loss. Taken together, our findings identify VHRFs as a previously unrecognized early danger signal for RGC degeneration and highlight IL-1-mediated inflammation as a tractable early therapeutic target for preventing RGC degeneration and vision loss. Graphical Overview O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/694725v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1598c4aorg.highwire.dtl.DTLVardef@9637borg.highwire.dtl.DTLVardef@623bf4org.highwire.dtl.DTLVardef@14e21ce_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

Metabolic dysfunction related to specific genetic variant sites of methylmalonic acidemia

Methylmalonic acidemia (MMA) is a genetic metabolic disease, with mut (mut-MMA, caused by MMUT gene variation) and cblC (cblC-MMA, caused by MMACHC gene variation) being the predominant subtypes. MMA patients carrying c.729_730insTT and c.609G>A exhibit severe clinical manifestations and have poorer outcomes. Little information is known on the potential mechanism. The metabotypes of MMA patients carrying c.729_730insTT and c.609G>A were profiled. The potential effect of genetic variation sites on the metabolism were explored. Leveraging the gene variation spectrum and the targeted metabolomics, propionic acid, indolelactic acid, myristoleic acid, tetradecenoic acid, tridecanoic acid, and oxoadipic acid showed strong enrichment in c.729_730insTT carrying mut-MMA patients. Whereas mutation c.609G>A caused adipic acid, pimelic acid, fructose, AMP, hexanylcarnitine, and methionine significnatly altered in cblC-MMA patients. Furthermore, the metabolomic profiles were obviously different in c.729_730insTT and non-c.729_730insTT carrying mut-MMA patients after treatment. Different metabolic alterations in cblC-MMA patients carrying c.609G > A and non-c.609G > A under treatment were also observed. Our findings provide unique insights into the metabolic basis of MMA specific subtypes and its implications across different variants.

molecular biology↗

bioRxiv2025

Loss of noradrenergic Fkbp5 disrupts social behavior and norepinephrine dynamics in the basolateral amygdala

Social dysfunction is common in depression and varies with stress exposure and genetic risk. The current study identifies a cell-type specific role for Fkbp5, a glucocorticoid receptor co-chaperone, in noradrenergic neurons engaged during social stress. Acute social stress upregulated Fkbp5 in the locus coeruleus (LC), whereas repeated exposure attenuated this effect. Noradrenergic Fkbp5 deletion (Fkbp5Nat) increased pro-social behavior exclusively in male mice. In the basolateral amygdala (BLA), social interaction reduced norepinephrine (NE) turnover in wild-type but not Fkbp5Nat mice. Consistently, proteomics revealed mitochondrial/energy and synapse-related remodeling in BLA neurons. Miniscope imaging showed that behavior-locked NE transients in BLA were selectively blunted in Fkbp5Nat mice during interaction with outbred CD1 conspecifics, while same-strain C57BL/6N encounters preserved NE dynamics. Together, this study indicates that Fkbp5 tunes LC-BLA output to social salience in a sex- and context-dependent manner, suggesting a circuit-specific route to normalize social salience without broadly suppressing noradrenergic function.

neuroscience↗

bioRxiv2025

A 5'-end based Molecular Marker Enables Identification and Deployment of a Functional Rpi-vnt1.1 Allele for Durable Late Blight Resistance in Potato

Potato (Solanum tuberosum) is a globally important food crop, yet its production is severely threatened by late blight, caused by Phytophthora infestans. Deploying resistance (R) genes in breeding programs offers a sustainable approach for disease management. Rpi-vnt1.1 is a broad-spectrum R gene cloned from wild Solanum species Solanum venturii. Here, we developed a PCR marker targeting the 5'-end extension of Rpi-vnt1.1, which enables efficient and specific detection of the resistant alleles. Screening of advanced breeding lines from the International Potato Center (CIP) identified line C1848, which carries a functional Rpi-vnt1.1 allele. Inoculation assays confirmed C1848 confers strong resistance to P. infestans. Subsequent functional assays, including RNAi-mediated silencing in C1848 and heterologous expression in Nicotiana benthamiana, demonstrated that this resistance is specifically mediated by the Rpi-vnt1.1 allele. This specific marker provides a rapid, low-cost tool for marker-assisted breeding, facilitating the deployment of potato cultivars carrying Rpi-vnt1.1.

plant biology↗