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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

bioRxiv2026

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

bioRxiv2026

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗

bioRxiv2026

A reactivated thalamocortical plasticity window promotes learning and is reshaped by experience

Adult sensory loss can reactivate critical-period-like thalamocortical plasticity, but whether this reactivation defines a temporally gated circuit state that facilitates learning and is reciprocally shaped by experience remains unknown. Here we define its in vivo trajectory and functional consequences in adult mouse barrel cortex. Infraorbital nerve transection opened a transient window of enhanced layer 4 thalamocortical gain. Training during this window lowered whisker-detection thresholds and promoted learning by accelerating the transition to stable performance. Local GluN2B blockade prevented both cortical potentiation and the learning advantage, linking critical-period-associated plasticity mechanisms to adaptive behavior in the adult brain. Neuropixels recordings showed that weak inputs preferentially increased neuronal responses, whereas strong inputs produced sharper temporal coding. The relationship was reciprocal: experience reshaped the trajectory of this circuit state, with training before the normal peak advancing the emergence of potentiation, training during the active window prolonging the potentiated state, and training after closure failing to reinstate potentiation. State prolongation accompanied more persistent sensory memory. These findings establish a reciprocal, timing-dependent interaction between endogenous plasticity and experience, revealing a general principle by which adult circuits can convert transient plastic potential into adaptive behavioral change and informing strategies that align training with periods of heightened plasticity.

neuroscience↗

bioRxiv2026

spatialMET: an open and scalable framework for spatial metabolomics analysis

Mass spectrometry imaging (MSI) enables spatially resolved metabolomics in intact tissue sections, but analysis remains challenging at scale. Existing MSI workflows often require users to combine multiple software tools, while others rely on proprietary vendor software that limits interoperability and reproducibility. To address these challenges, we developed spatialMET, an open-source framework that provides an end-to-end workflow for MSI analysis. spatialMET provides a unified platform for preprocessing, spatial domain detection, and visualization. Downstream analyses include differential abundance testing, spatial autocorrelation and gradient analysis, dimensionality reduction, and correlation network analysis. Spatial domain detection uses hcdist, a C-based hierarchical clustering implementation that substantially reduces runtime and memory use relative to existing R-based approaches. spatialMET can be run through an interactive R Shiny application or as a standalone command-line workflow for larger datasets or high-performance computing environments. Applied to mouse small cell lung cancer MALDI-MSI data containing 284,673 pixels, spatialMET identified tumor-associated, stromal, and adjacent lung spatial domains that aligned with matched histology. Differential abundance analysis identified 117 m/z features that differed between tumor and stromal regions, while spatial autocorrelation analyses revealed spatially structured abundance patterns. Applying spatialMET to mouse lung adenocarcinoma data from an entire lung lobe containing 338,477 pixels further demonstrated scalability and captured spatial heterogeneity across tumor and surrounding lung tissue. In summary, spatialMET provides a scalable, open-source framework for end-to-end spatial metabolomics analysis, and it is distributed as a Docker container for reproducible deployment. Source code and installation instructions are available at https://github.com/biodatalab/spatialMET.

bioinformatics↗

bioRxiv2026

The histone demethylase Kdm5 and the ARGONAUTE proteins Piwi and Aubergine regulate female abdominal pigmentation in Drosophila melanogaster

Insect pigmentation is an ecologically critical trait influencing many physiological processes. In Drosophila melanogaster, abdominal pigmentation is sexually dimorphic: males have fully pigmented posterior segments, while females exhibit a posterior melanin stripe. Pigmentation relies on the expression of pigmentation genes that encode enzymes involved in pigment synthesis. These genes are tightly regulated during pupal and young adult stages. To expand the gene regulatory network of pigmentation genes, we conducted an RNAi screen using the yellow-Gal4 driver, expressed during the pupal stage in abdominal epidermis. One of the candidates from this screen, Kdm5, encodes a histone demethylase erasing the H3K4me3 histone mark catalyzed by the histone methyl-transferase Trithorax (Trx). We show that Kdm5 down-regulation reduces abdominal pigmentation, mimicking trx down-regulation. Kdm5 activates melanin production through regulation of the pigmentation gene tan. Transcriptomic analyses reveal that Kdm5 and Trx share many targets in pupal abdominal epidermis, including piRNA pathway components such as piwi and aubergine. These piRNA components, originally associated with transposon silencing in the germline, also function in some somatic tissues such as the nervous system, the fat body or the gut. We demonstrate that Piwi and Aubergine participate in female abdominal pigmentation establishment, without evident piRNA production. We also show that Kdm5 and Piwi act not only in pupal abdominal epidermis but also in pupal fat body. This study therefore expands the regulatory network of pigmentation genes. It identifies a new somatic function for Kdm5 and Piwi and reveals a role for pupal fat body in female abdominal pigmentation regulation.

genetics↗

bioRxiv2026

Neural signatures of spontaneous transitions between internal and external thought

The human mind constantly shifts between internal representations and the external environment, yet the neural mechanisms underlying such spontaneous transitions remain underexplored. Here, we analyzed a think-aloud functional magnetic resonance imaging dataset, in which participants continuously verbalized their thoughts, to identify neural activity predicting transitions between internally and externally oriented thought. Internal-to-external transitions were preceded by increased activation in the salience/ventral attention network, with the strongest effect observed in the right temporoparietal junction. The spatial pattern of this pre-transition activation was positively associated with acetylcholine receptor density, suggesting a role for cholinergic signaling in cognitive reorientation. Pre-transition activation was itself preceded by a large-scale brain state proposed to serve as a flexible hub between functionally specialized states, indicating that spontaneous transitions are more likely when the brain occupies this intermediate configuration. Together, these findings suggest that multilevel neural mechanisms support flexible reorientation along the internal-external dimension of spontaneous cognition.

neuroscience↗

bioRxiv2026

A Microglial Regulatory Program Linked to Neuropsychiatric Disorders

Hoxb8 is a transcription factor required for the normal function of a specialized microglial population. Loss of Hoxb8 causes compulsive overgrooming and anxiety-like behaviors in mice, with greater severity in females after sexual maturity. However, the Hoxb8-dependent transcriptional program in microglia remains poorly understood. Here, we integrated Hoxb8 chromatin occupancy, transcriptional responses, and chromatin contacts to classify genes by their spatial relationship to Hoxb8 binding. Hoxb8 occupied thousands of genomic regions, but only a subset of associated genes responded transcriptionally. Locally associated, Hoxb8-activated genes were linked to immune signaling and hormone responsiveness, whereas locally associated, Hoxb8-suppressed genes were linked to cell-cycle and genome-maintenance processes. Distally associated genes contributed to neuronal and intercellular communication and were enriched for genes associated with obsessive-compulsive disorder and anxiety. These findings reveal a functionally organized Hoxb8-dependent transcriptional program and identify potential connections between Hoxb8 activity in microglia, hormone responsiveness, intercellular communication, and neuropsychiatric disease risk.

neuroscience↗

bioRxiv2026

Geometry of antigenic evolution improves influenza vaccine selection

Anticipating antigenic evolution is essential for selecting effective seasonal influenza A/H3N2 vaccine strains. To this end, we integrated hemagglutination-inhibition and neutralization titers spanning 2002 to 2025 into a unified Bayesian antigenic map. The map resolves twelve antigenic clusters advancing in discrete steps, with several clusters co-circulating in most seasons. In 15 of 21 seasons, the WHO-recommended vaccine belonged to an earlier cluster than the dominant circulating cluster. The direction of each vaccine update relative to recent viral drift predicted vaccine effectiveness one season ahead in out-of-sample forecasts. Antigenic distance, the conventional measure of vaccine-virus match, was weakly associated with effectiveness until update direction was accounted for. Retrospectively ranking candidate strains by predicted effectiveness would have selected a strain predicted to outperform the WHO recommendation in every season, raising mean predicted effectiveness by 10 percentage points.

evolutionary biology↗

bioRxiv2026

Comparative study of chlorophyll measurement in Physcomitrium patens moss using a conventional microscope adapted for combined 2D+1D imaging and spectral analysis

Imaging spectroscopy often requires expensive and complex equipment. Here we show a simple procedure for attaching a standard miniature fiber spectrometer to a conventional microscope, allowing easy integration of 2D imaging with 1D high-resolution spectral measurements. This combination provides much of the benefit of a full imaging spectrometer without the large equipment investment, and we provide instructions for modifying microscopes to this setup and the present measurements of living cells that demonstrate their performance. Using this setup, we compare the quantitative measurement of chlorophyll concentration in Physcomitrium patens moss using color imaging and spectral sampling.

bioengineering↗

bioRxiv2026

Probing the transcriptome response to shivering in skeletal muscle using a multilayered bioinformatics approach

Cold acclimation holds therapeutic potential for improving metabolic health. We previously demonstrated that repeated cold-induced shivering enhances insulin sensitivity in humans. However, the molecular pathways that underlie the skeletal muscle shivering response, and how these relate to beneficial physiological effects, remain poorly understood. In this study, we combined complementary bioinformatics approaches to allow in-depth analysis of the transcriptomic response of human skeletal muscle to repeated shivering. We identified a robust transcriptional signature and show a sex-specific component in the shivering skeletal muscle response, which seemed to diminish following cold adaptation. Our findings provide mechanistic insights into cold-induced muscle adaptations, shed light on potential interesting molecular targets for further investigation, and emphasize the importance of including both sexes in future cold acclimation studies.

bioinformatics↗

bioRxiv2026

An Information Geometry approach to model topological trajectories and Gene Expression Radius from UMAP geometry.

Understanding the relationship between gene expression dynamics and cellular identity remains a central challenge in single cell biology. Here, we introduce a novel computational and mathematical framework that integrates information geometry, fuzzy topology, and UMAP analysis to model gene expression landscapes derived from single cell RNA sequencing data. We formalize gene expression data as a fuzzy topological space, where interactions between expression points are governed by probabilistic distributions inspired by manifold learning approaches such as UMAP. Within this framework, we define an information geometric structure through a Fisher metric induced by these distributions, enabling the computation of geodesic trajectories that capture cellular differentiation processes. A key contribution of this work is the derivation of analytical conditions, expressed as expression radius formulas, that characterize local neighborhoods in gene expression space. These conditions allow for the identification of genes associated with stem cell states and predictions in transitional cell types in future work. Application of the proposed framework to single cell datasets reveals biologically meaningful gene sets enriched in key regulatory pathways and transcription factors, demonstrating the capacity of our approach to uncover latent structure in complex gene expression data. Our results suggest that integrating differential geometry with statistical learning theory offers a powerful paradigm for modeling genotype and phenotype relationships and cellular state transitions, with potential implications for precision medicine and systems biology.

bioinformatics↗

bioRxiv2026

Aberrant accumulation of α-synuclein might be linked with the progressive motor deficits in a mouse model of Angelman syndrome

Dysfunction of maternal UBE3A leads to Angelman syndrome (AS), which is characterized by significant intellectual and motor debilities. However, the molecular underpinnings of the behavioral deficits associated with UBE3A dysfunction remain obscure. In this study, we utilized a model mouse of AS and report, for the first time, that the aberrant accumulation of -synuclein may be linked to the development of AS. Firstly, we demonstrated a progressive deterioration of various motor functions in AS mice beginning from the early adolescent phase. Subsequently, we observed an age-dependent increase in the accumulation of both soluble and insoluble -synuclein, including its pathological variant (pSer129), in the striatum and substantia nigra dopaminergic neurons of AS mice. We also found that Ube3a interacts with -synuclein and promotes its proteasome-mediated degradation, as evidenced by decreased levels of K48-linked polyubiquitinated -synuclein in the brain samples of AS mice in comparison to wild-type animals. Finally, using an RT2 Profiler PCR Array that analysed 84 genes specifically related to dopamine and serotonin pathways, we identified altered transcript level of various genes in the striatal tissues of AS mice that are commonly associated with nigrostriatal dysfunctions in Parkinson's disease. These findings highlight -synuclein as a novel target of Ube3a and suggest that -synuclein pathology may contribute to the progressive motor and other behavioral abnormalities witnessed in AS mice.

neuroscience↗

bioRxiv2026

Beyond Single-Metric Assessments: Uncovering Masked Butterfly Declines via Multi-Scalar Analysis in Central Alberta

1. This study analyzed 21 years (2000-2025) of butterfly count data from Central Alberta, integrated with intensive 5-year (2021-2025) high-resolution intra-seasonal sampling. 2. Long-term macro-scale analysis revealed a significant decline in Shannon Diversity, a change that remained obscured when relying solely on traditional metrics of species richness and evenness. 3. This diversity decline was primarily driven by the severe, long-term collapse of the native Common Ringlet (Coenonympha tullia). 4. Four other dominant species--Cabbage White (Pieris rapae), Clouded Sulphur (Colias eriphyle), European Skipper (Thymelicus lineola), and Common Wood Nymph (Cercyonis pegala)--maintained long-term population stability, though their abundances were significantly constrained by extreme winter minimum temperatures and rapid spring warming. 5. High-resolution intra-seasonal analysis (2021-2025) demonstrated that community indices and species-specific abundances were strongly limited by daily weather, particularly wind velocity and temperature. 6. These findings illustrate that while traditional metrics like richness and evenness are fundamental to community ecology, they provide incomplete insights when applied in isolation; they are most effective when utilized as part of a complementary, multi-scalar framework. 7. This study highlights the necessity of coupling multi-decadal historical datasets with high-frequency, fine-scale sampling to accurately identify the mechanisms of community turnover that simpler metrics may overlook. 8. The results underscore the critical importance of standardized citizen science monitoring in quantifying environmental impacts and establishing conservation priorities for terrestrial insect groups.

ecology↗

bioRxiv2026

Who rests with whom? Sex composition and group demography shape resting associations in free-ranging dogs

Free-ranging dogs frequently rest near conspecifics, but the demographic factors structuring their resting associations remain poorly understood. We quantified dyadic resting associations in 26 free-ranging dog groups in West Bengal, India, observed between 2019 and 2023. Association strength was estimated from scan based resting co-occurrences using the Half-Weight Index. We tested whether dyadic association strength varied with dyad sex composition, dyad life stage composition, group size, and group sex ratio using a generalised additive model for location, scale and shape that accounted for group identity and repeated occurrence of individuals across dyads. Male-male dyads had lower association strengths than female-female dyads, whereas mixed-sex dyads did not differ from female-female dyads. Association strength decreased with increasing group size but increased as the male-to-female ratio within the group increased, while life-stage composition had no detectable effect. Individual level network metrics, including strength, reach, clustering coefficient, affinity, and eigenvector centrality, did not vary with sex or season. Mixed-sex pairs were also frequently represented among the strongest dyadic associations within groups. These findings indicate that resting associations in free-ranging dogs vary with dyad sex composition and group demography. Further opportunity-controlled analyses are required to determine whether the prominence of mixed-sex dyads reflects preferential association rather than group composition alone.

animal behavior and cognition↗

bioRxiv2026

Detection of Stress in Naturalistic Settings Through Passive Mobile Sensing

Unobtrusive stress detection using wearable sensors could enable scalable, continuous mental-health monitoring. However, stress is an inherently subjective state that can only be inferred indirectly from physiological signals, making generalizable detection in naturalistic settings challenging. Although prior work has focused on improving model performance, it remains unclear whether wearable physiology supports a shared cross-individual mapping to subjective stress or whether this relationship is fundamentally person-specific. We evaluated feature-based and deep-learning models across multiple physiological modalities using ecological momentary assessment (EMA) as the reference standard, comparing within- and between-individual modeling approaches. Within-individual models achieved modest but consistent improvements in stress detection, whereas between-individual models consistently failed to generalize, yielding negative R2 values despite multimodal fusion and high-capacity architectures. Error analyses revealed regression to the mean, reduced sensitivity to high-stress states, and residual associations with general physiological activation, highlighting the limited stress specificity of wearable physiology. These findings suggest that wearable stress detection is fundamentally a personalized inference problem and that future systems should prioritize individual adaptation and contextual modeling over universal stress predictors.

neuroscience↗

bioRxiv2026

PURELIGHT: a quantitative photon-counting framework unifying intensity and lifetime imaging at video rate across detector technologies

Quantitative fluorescence microscopy requires photon-efficiency, speed and accurate intensity and lifetime measurements. Time-correlated single-photon counting (TCSPC) simultaneously captures intensity and lifetime, but photon pile-up distorts both signals at high count rates, preventing fast acquisitions. Existing corrections discard photons, distort intensity, or require specialized detectors. Here we introduce PURELIGHT, an integrated hardware and software framework that simultaneously recovers undistorted intensities and lifetimes at count rates far beyond conventional pile-up limits. PURELIGHT works with hybrid photodetectors, silicon photomultipliers and photomultiplier tubes while retaining over three times more photons than alternative approaches. Using two-photon imaging, we showcase PURELIGHT's superior accuracy and spatial contrast, demonstrating video-rate subcellular lifetime imaging in awake mice, a unique lifetime-calibrated ratiometric modality and crosstalk-free temporal multiplexing. By removing the limits that have confined TCSPC to low-signal applications, PURELIGHT promotes the adoption of quantitative, photon-efficient microscopy across the life sciences.

neuroscience↗

bioRxiv2026

Feeling the Music: Preceding Vibroacoustic Stimulation Modulates Oscillatory Brain Dynamics During Music Listening

Background: Although typically considered an auditory experience, music listening engages multiple sensory systems, including somatosensory and motor pathways, making it an inherently multisensory phenomenon. However, research has predominantly examined the influence of music on other sensory systems, while the reciprocal question - how the existing state of a sensory system modulates the music listening experience- has received considerably less attention. To address this gap, we examined neural activity during music listening in two somatosensory states: one preceded by vibroacoustic stimulation (VAS) and one preceded by rest alone. Methods: Forty participants completed two MEG sessions in a within-subject crossover design. In one session, they received 20 minutes of 40 Hz VAS before listening to 10 minutes of self-selected relaxing music (VAS_ML); in the other, they lay on the same mattress without stimulation (NoVAS_ML). Oscillatory and aperiodic activity were estimated using DICS beamforming and FOOOF decomposition for the whole music period and for early and late listening segments. Results: Across the full listening period, the VAS condition was associated with reduced alpha power in the posterior temporal lobe and increased low-gamma power in the medial somatosensory and motor cortices compared to the NoVAS condition, suggesting enhanced cortical excitability and stronger auditory-motor engagement. Over time, both music listening conditions showed increases in alpha and beta power, consistent with habituation to the musical stimulus, though the spatial distribution differed qualitatively: changes were widespread across temporal and occipital regions in the NoVAS condition but remained localized to temporal areas after VAS. Additionally, VAS uniquely increased temporal-lobe theta power over time, whereas the NoVAS condition showed a decrease in the aperiodic exponent. Subjectively, participants reported stronger emotional intensity during music listening after VAS. Conclusion: These findings suggest that preceding VAS induces a more engaged neural state and qualitatively alters the temporal dynamics of music processing.

neuroscience↗