Biology subjects

Chen, Y.

Publications and source records attributed to Chen, Y..

At least 163 records · Page 9Linked to original sources

bioRxiv2026

Revising the genetic and epigenetic architecture of in vitro regeneration capacity in natural Arabidopsis thaliana populations

Plant regeneration is a dynamic developmental process that spans from cell dedifferentiation to organ reconstruction in response to inductive cues, such as wounding stress and hormonal signals. Although this capacity varies widely both between and within species, a comprehensive understanding of the genetic and epigenetic bases of this variation remains incomplete. To address this issue, we revisited published datasets on natural variation in in vitro regeneration capacity in Arabidopsis thaliana. Using quantitative genetic approaches, including meta-analyses of genome-wide association studies (GWAS) and multi-locus models, we dissected the genetic architecture underlying regeneration traits. Our results showed that shoot regeneration capacity is primarily explained by allelic variation in the cis-regulatory region of WUSCHEL (WUS), a key regulator of shoot meristem formation. Notably, these polymorphisms are also associated with epigenetic variants of the DNA transposon ATDNA2T9C, which is located within the regulatory region. Furthermore, allelic variation in ARABIDOPSIS RESPONSE REGULATOR 2 (ARR2), a positive regulator of cytokinin signaling, is associated with callus formation and greening traits and may promote shoot formation through genetic interactions with WUS alleles. Although in vitro regeneration is controlled by complex, multilayered gene regulatory networks, our results suggest that, in A. thaliana, natural variation in regeneration capacity is largely shaped by a small number of major-effect modifiers together with epigenetic variation and genetic interactions, despite the substantial heterogeneity observed among natural populations.

genetics↗

bioRxiv2026

mirCCC: Repression-aware graph learning for miRNA-mediated cell-cell communication inference

Cell-cell communication analyses usually focus on protein ligands and receptors and therefore miss extracellular vesicle transfer of microRNAs, an important route of signalling in cancer. Here we show that microRNA-mediated communication can be inferred from standard single-cell RNA sequencing by detecting coordinated decreases in the expression of validated miRNA target genes. We developed mirCCC, a computational framework that estimates cell-specific microRNA activity, models cellular sending and receiving capacity for extracellular vesicle transfer, and learns microRNA-resolved communication graphs from transcriptomic data. In synthetic benchmarks with strong confounding signals, mirCCC improved whereas all comparison methods declined. Applied to a human colorectal cancer atlas, mirCCC recovered known colorectal cancer-associated microRNAs and identified stromal- and myeloid-to-epithelial communication converging on a plasticity program linked to TGF-{beta} and Wnt/{beta}-catenin signalling. These results provide a practical route for studying extracellular vesicle-mediated communication in existing single-cell atlases. Author summaryCell-cell communication plays important roles across a wide range of biological processes. Most studies of cell-cell communication focus on interactions between ligands and receptors. However, cells can also use extracellular vesicles to deliver microRNAs (miRNAs), which regulate gene activity in receiving cells and contribute to cancer progression, immune regulation, and changes in the tissue environment. Since standard single-cell sequencing does not directly capture miRNAs, this mode of communication remains largely unexplored. Here we developed mirCCC, a computational method for inferring miRNA-mediated communication from standard single-cell transcriptomic data. Instead of detecting miRNAs directly, mirCCC examines the effects they leave in receiving cells. Active miRNAs often cause coordinated suppression of their target genes. mirCCC uses these coordinated reductions in the expression of known target genes to estimate miRNA activity and combines them with the ability of sending cells to package and release miRNAs and of receiving cells to process them. It can therefore reconstruct directional communication networks for individual miRNAs. Our evaluations show that mirCCC remains reliable in the presence of misleading signals and reveals biologically meaningful regulatory patterns in human colorectal cancer data. Overall, mirCCC provides a practical way to study miRNA-mediated cell-cell communication using existing single-cell transcriptomics datasets.

bioinformatics↗

bioRxiv2026

Boosting carbon fixation and microbial dynamics in the coastal sediment ecosystem through large-scale cultivation of Gracilariopsis lemaneiformis

Microorganisms are the key drivers of carbon cycling in coastal marine sediment ecosystems, significantly influencing carbon storage and release during Gracilariopsis lemaneiformis cultivation. This study employed 16S rRNA sequencing, a high-throughput qPCR chip, and carbon isotope labeling to assess the impact of G. lemaneiformis cultivation on carbon cycling processes in coastal sediments. A comparative analysis was conducted between cultivated zones (GZ) of G. lemaneiformis and adjacent control zones (CZ). The results indicated that macroalgae cultivation significantly modified sediment-seawater exchange dynamics and accelerated carbon cycling within coastal marine sediment ecosystems. Furthermore, G. lemaneiformis cultivation increased the abundance of genes linked to polysaccharide degradation and carbon fixation pathways, thereby enhancing carbon cycling efficiency. The ecosystem multifunctional index, calculated based on carbon fixation gene abundance, was significantly higher in GZ compared to CZ. Incubation experiments using 13C-NaHCO3 demonstrated that cultivation markedly elevated the carbon fixation rate of sediment, emphasizing a higher potential for carbon sequestration in sedimentary environments cultivated with macroalgae. Additionally, cultivation significantly altered sediment microbial communities, simplifying their structural complexity. Key microbial taxa identified via k-core species analysis--including Subgroup10 of Desulfobacterota and MBNT15, correlated strongly with carbon fixation rates, indicating their pivotal roles in sediment carbon cycling processes. This study provides critical insights into how large-scale macroalgae cultivation influences coastal carbon dynamics and informs strategies for optimizing carbon management in aquaculture ecosystems. ImportanceGracilariopsis lemaneiformis cultivation is a widely promoted eco-aquaculture model along Southeast Chinas coast. This study finds it can drastically boost carbon sequestration efficiency in coastal sediments. Through field comparison and isotope tracing, we confirm that key carbon-fixing microbes in farmed sediments show significantly higher activity, with far stronger carbon storage potential than non-farmed zones. This research delivers direct scientific evidence for scaling up macroalgae farming to unlock new blue carbon gains, and offers a practical new solution for optimizing carbon management in aquaculture ecosystems.

microbiology↗

bioRxiv2026

IgG4⁺ plasma cell enrichment and {lambda}-chain-biased BCR remodeling drive low-grade autoimmunity in chronic obstructive pulmonary disease

BackgroundThis study aimed to elucidate B cell subset pathology in COPD, a poorly characterized area, with a focus on its similarities to and differences from classical autoimmune disorders. MethodsThe single-cell RNA-sequencing (scRNA-seq) data from COPD and autoimmune diseases were obtained from Gene Expression Omnibus (GEO) for comparative analyses of B cell subsets and functions via differentially expressed genes (DEGs), KEGG, protein-protein interaction (PPI), and cell-cell communication analyses. Serum IgG4 was measured by ELISA and correlated with clinical parameters. The peripheral blood B cells were sorted by flow cytometry for single-cell B cell receptor (BCR) sequencing. A v-Abl/Bcl2 pro-B cell line was stimulated with cigarette smoke extract (CSE) to assess abnormal development in vitro. ResultsIn lung tissue, IgG4+ plasma cells were enriched and expressed BCR activation/inflammatory genes and TNF/NF-{kappa}B/MAPK pathways. Serum IgG4 concentrations correlated negatively with pre-and post-bronchodilator FEV1/FVC. B cell interacted with monocytes, macrophages, fibroblasts and endothelial cells via IL-1{beta}/IL-6, integrin and chemokine signalling, contributing to chronic inflammation and remodelling. In peripheral blood, transitional T1 B cells were increased, accompanied by {lambda}-chain enrichment and increased IGLV1-47 usage, as well as enrichment of autoimmune pathways. In the bone marrow, the numbers of pre-B I cells were increased while those of small pre-B III cells were reduced, with altered expression of BCR development genes. CSE stimulation of the pro-B cell line reduced {lambda}5 expression in a concentration-dependent manner. ConclusionsThe autoimmune abnormalities in COPD appear more restricted, although IgG4 antibody generation may contribute to immune-mediated lung damage.

immunology↗

bioRxiv2026

Bidirectional modulation of aging-associated cellular phenotypes by mitochondrial genome replacement

Mitochondrial dysfunction is a hallmark of cellular aging, but whether age-associated cellular decline can be functionally reversed remains unclear. Here, we applied mitochondrial genome replacement to replicative senescent fibroblasts and aged T cells derived from mice and humans. In senescent fibroblasts, replacement with mitochondria from young cells extended proliferative lifespan, whereas replacement with aged mitochondria accelerated proliferative decline, indicating bidirectional modulation of aging-associated phenotypes. In aged mouse T cells, mitochondrial genome replacement restored proliferative capacity and significantly enhanced antitumor activity following adoptive transfer into tumor-bearing mice. Similarly, mitochondrial genome replacement in aged human T cells enhanced cytokine production and shifted the transcriptomic programs toward a more youthful state. Collectively, these findings identify mitochondrial genetic integrity as a functional regulator of aging-associated cellular states and support the emerging view that mitochondria actively influence cellular aging trajectories.

Cell Biology↗

bioRxiv2026

Spatial synaptic regularization stabilizes learning across biological and artificial neural networks

How the spatial organization of synapses contributes to stable learning remains a fundamental question in neuroscience. Using the H01 electron microscopy connectome of human temporal cortex, we found that dendritic spines clustered morphologically, whereas synaptic weights followed a center-elevated, surround-suppressed arrangement along dendrites. A regularized Hebbian model formalized this spatial signature, showing that strong synapses lower the probability that neighboring synapses reach high-weight states. Translating this principle into Spatial Synaptic Regularization (SSR) reduced forgetting and stabilized learning across diverse artificial networks and tasks, including continual visual learning, large language-model knowledge editing, and parameter-efficient adaptation of vision-language models, by preserving high-rank, low-overlap representations. These findings identify spatial synaptic organization as an unrecognized dimension for stabilizing learning and show that structural connectomics can yield actionable AI methods.

neuroscience↗

bioRxiv2026

Collapsing retroviruses for efficient delivery of viro-toxic cargoes

Retroviruses are excellent tools for delivering and expressing transgenic cargoes with broad utility in research and therapy. However, many cargoes including virus restriction factors can dramatically limit virus production and/or infectivity. An extreme viro-toxic cargo is the DNA cytosine deaminase APOBEC3B, which potently restricts retrovirus infectivity by a direct cDNA deamination-dependent mechanism. To overcome viro-toxicity, an APOBEC3B minigene cargo is disrupted by a translation stop cassette flanked by a direct repeat of its own sequence. The integrity of the minigene is reconstituted naturally by retroviral recombination during transduction. Efficiency can be improved from 90% to nearly 100% by coupling the minigene to the translation of a downstream selectable marker. Collapsing retrovirus (CRV) technology enables the functional delivery of APOBEC3B to a target cell population and may have broad utility for delivering viro-toxic cargoes. MotivationMany different proteins are detrimental to retrovirus production and/or to virus-producing cells. This problem can be circumvented by interrupting the genetic cargo with a direct repeat-flanked translation stop cassette and allowing transgene integrity to be restored naturally by recombination during reverse transcription. As exemplified by the retrovirus restriction factor APOBEC3B, this process is very efficient. HighlightsO_LICollapsing retroviruses (CRVs) prevent retrovirus restriction by viro-toxic proteins C_LIO_LITruncated tandem repeats recombine during transduction and restore virus integrity C_LIO_LITranslation-coupled selection enables near 100% transduction efficiency C_LIO_LICRVs have broad utility for delivering viro-toxic cargoes such as APOBEC3B C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=186 SRC="FIGDIR/small/735095v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@e96092org.highwire.dtl.DTLVardef@1c343f9org.highwire.dtl.DTLVardef@a3b53dorg.highwire.dtl.DTLVardef@1cfeb69_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2026

Peri-Locus Coeruleus Controls Endothelial Cell Heterogeneity in Enriched Environments via Region-Specific Norepinephrine Signaling

The brain acts as a central integrator that enables organisms to interpret environmental stimuli and coordinate adaptive responses across the body. While enriched environments are known to enhance neural plasticity and cognitive function, their impact on peripheral organ systems remains less understood. Here, we show that enriched environmental conditions activate a peri-locus coeruleus (peri-LC) neuronal ensemble that preserves CD31hiEMCNhi type H endothelium, a specialized bone-associated endothelial subtype, against age-associated decline, thereby enhancing femoral bone density. Chemogenetic activation and ablation experiments further revealed that this peri-LC ensemble is functionally distinct from other sympathetic regulatory brain regions in its control of bone endothelial heterogeneity and skeletal mass. Three-dimensional bone clearing and spatial analyses showed that CD31hiEMCNhi endothelium is closely associated with sympathetic nerve terminals. The peri-LC mediates this process through sympathetic signaling and {beta}2-adrenergic receptors on bone vascular endothelial cells. In vivo imaging further demonstrated that norepinephrine release is spatially restricted, with sprouting endothelial cells near the growth plate exhibiting the highest sensitivity. Together, these findings reveal a refined brain-periphery regulatory logic in which distinct sympathetic brain circuits engage spatially restricted norepinephrine signaling to coordinate organ-specific vascular and skeletal adaptations.

neuroscience↗

bioRxiv2026

eRNAformer enables genome-wide de novo mapping of enhancer-derived RNA loci

Enhancer-derived RNAs (eRNAs) are critical regulators of gene transcription, yet their genome-wide annotation remains challenging. Here, we present eRNAformer, a multi-modal deep learning framework that integrates convolutional neural networks with transformers, specifically designed to capture long-range genetic features associated with bidirectional transcription. This approach enables de novo mapping of eRNA loci using DNA sequence and aggregated conventional RNA-seq data. When evaluated on ENCODE datasets, eRNAformer demonstrated high sensitivity and specificity in discriminating known eRNA loci from non-eRNA loci. Notably, the newly identified eRNA loci were enriched with evolutionarily constrained variants and genetic risk factors for complex diseases, and exhibit potential relevance for cancer therapy. Applied to GEO datasets, eRNAformer identified a range from 14,219 to 56,451 eRNA loci across multiple hematologic malignancies, facilitating the construction of a comprehensive eRNA database for blood cancers. We further identified and experimentally validated FOXO1e, a cluster of eRNAs located approximately 120 kb upstream of FOXO1, a known oncogene that drives t(8;21) acute myeloid leukemia (AML) preleukemic program. Together, these findings establish eRNAformer as a powerful tool for genome-wide eRNA annotation, provide a valuable resource for eRNA studies in hematologic cancers, and underscore the functional importance of eRNAs in AML pathogenesis.

bioinformatics↗

bioRxiv2026

The Vertebrate Genomes Project Phase I: A global reference genome resource

The Vertebrate Genomes Project (VGP) aims to produce complete and near-error-free reference genomes for all [~]70,000 extant vertebrate species1. Organized in four phases, it progressively targets all vertebrate orders, families, genera, and eventually all species. Here we present the completion of VGP Phase I, delivering reference genomes for [~]95% of vertebrate orders, along with additional lineages within those orders, totaling 816 species and 1.6 trillion base pairs of main haplotype sequence. These genomes were assembled and annotated over an 8-year period (2018-2026) of rapid advances in genome sequencing, assembly, and annotation methods2-4, alongside the growth of associated consortium initiatives and international collaborations5-9. They represent some of the highest-quality vertebrate genomes currently available, and most have become the primary reference for their respective species in public databases. Comparative analyses across a subset of 579 species when we reached a threshold of 85% of orders allowed us to reconstruct the genome of the last common ancestor of all vertebrates 500 million years ago, identify diverse modes of sex chromosome evolution, reveal clade-specific three-dimensional genome architecture, discover methylated epigenetic landscapes across vertebrates, and provide a framework for studying gene and pseudogene evolution, immune loci, cancer-associated genes, and other trait-associated loci. Approximately a quarter of this subset are listed as Vulnerable to Critically Endangered by the IUCN Red List of Threatened Species, and have enabled more advanced genomic investigations of extinction risk. VGP Phase I delivers a reference backbone for vertebrate genomics, enabling discoveries that would otherwise remain out of reach across evolution, conservation, and medicine. Talking pointsO_LIThe flagship paper of VGP Phase I C_LIO_LIThe highest quality collection of genomes within the eukaryotic domain of life C_LIO_LIEvolution of genome sequencing technology quality throughout VGP Phase I C_LIO_LIA driver project that has been a model for multiple large-scale, high-quality reference genome projects C_LIO_LIReleases all currently unpublished genomes in Phase I from scientific study embargoes C_LIO_LIMultiple biological discoveries across the vertebrate tree of life C_LI

genomics↗

bioRxiv2026

Regulatory co-option of a homeobox gene drives parasitoid venom evolution

How gene regulatory networks are rewired to generate phenotypic and functional innovation remains a central question in evolutionary biology. Parasitoid wasp venoms provide a powerful system for addressing this question, as their repertoires evolve rapidly through extensive lineage-specific turnover, yet the regulatory principles underlying such flexibility are largely unknown. Here we integrate tissue-resolved transcriptomic, chromatin-accessibility and histone-modification profiling to reconstruct the venom regulatory network of the parasitoid wasp Pteromalus puparum. We show that venom expression is embedded in distinct chromatin states and shaped by regulatory elements associated with venom-gland transcription. Comparative and functional analyses support a general model in which regulators related to the endoplasmic reticulum stress and unfolded protein response pathways have been repeatedly recruited to venom regulation across venomous lineages. Unexpectedly, we identify the recently co-opted homeobox gene Lbx as a lineage-specific hub that regulates more than half of venom genes and is linked to enhancer evolution. These results reveal a nested model of venom regulatory evolution, in which an ancestral secretory programme provides a reusable regulatory backbone, while newly co-opted homeobox gene specify a lineage-specific venom expression. Our study highlights regulatory co-option as a mechanism by which conserved developmental genes can acquire new physiological functions during adaptive evolution.

evolutionary biology↗

bioRxiv2026

A Spectrum of Free Energy Landscape Topologies Encodes Chromatin Polymorphism and Phase Separation

Chromatin exhibits structural polymorphism, yet how such substantial structural heterogeneity is encoded in its underlying free-energy landscape remains unknown. Here we map the folding landscapes of tetra-nucleosome arrays using adaptive Markov state models constructed from near-atomistic coarse-grained simulations. We find that chromatin is not governed by a single folding funnel analogous to those of many globular proteins. Instead, it spans a continuum of free-energy landscape topologies, ranging from funnelled to rugged to flat. Remarkably, phase separation reshapes chromatins free-energy landscape by stabilising conformations that maximise intermolecular connectivity, demonstrating that the landscape is determined not only by intrinsic molecular parameters but also by the environment and intermolecular interactions. Linker DNA geometry selects among landscape regimes through geometric frustration of zig-zag nucleosome stacking. At short and intermediate linker lengths, canonical 10N bp linkers produce funnelled landscapes dominated by compact zig-zag structures, whereas 10N +5 bp linkers generate rugged landscapes with multiple competing minima. Long linkers relieve frustration and flatten the landscape into a broad entropic basin. This control operates with single-base-pair precision, such that changing linker length by one base pair is sufficient to reorganise both the thermodynamics and kinetics of chromatin folding. DNA sequence provides a second level of control by modulating linker deformability, but only when zig-zag geometric frustration is present. These results establish free-energy landscapes as a framework for understanding the physical origin of chromatin polymorphism and its coupling to phase separation.

biophysics↗

bioRxiv2026

Ventral pallidal GABAergic neurons control hedonic feeding and obesity

Food intake is governed by two interacting drives. The homeostatic hunger drive regulates food intake to fulfill caloric needs while the hedonic drive promotes intake of palatable foods outside of caloric need. It is unclear which neural substrates can control the hedonic drive and thereby reduce overeating of palatable foods and associated obesity. Here, we show that ventral pallidal GABAergic neurons (VPGABA) preferentially control hedonic feeding and are necessary for diet-induced obesity in mice. Stimulating VPGABA neurons drove robust consumption of high-fat diet and liquids, but not regular laboratory chow. Despite driving intake of palatable foods, VPGABA neurons are relatively insensitive to homeostatic signals - they express few hunger-hormone receptors and are not activated by ghrelin administration or fasting. Single-cell calcium imaging revealed stronger engagement of VPGABA neurons during long vs short feeding bouts, suggesting control over bout duration, which has been linked to palatability. This was confirmed with closed-loop optogenetic stimulation. Finally, taCasp3-mediated ablation of VPGABA neurons reduced intake of palatable liquids and blocked high-fat diet-induced obesity without impacting homeostatic feeding. Together, these findings establish VPGABA neurons as a neural population that preferentially controls hedonic over homeostatic feeding and can be leveraged to block obesity in mice.

neuroscience↗

bioRxiv2026

Systematic benchmarking of zero-shot utility and robustness in single-cell transcriptomic foundation models

Single-cell foundation models (scFMs) have emerged as powerful representation learning approaches for single-cell transcriptomics. However, the utility and robustness of their pretrained representations across diverse analytical tasks and data conditions remain insufficiently characterized, particularly in zero-shot settings without task-specific fine-tuning. Here, we systematically analyze zero-shot performance of single-cell transcriptomic representations across 20 methods, 6 downstream tasks and 1,607 datasets comprising nearly 21.8 million cells. We evaluate model behavior along three complementary dimensions: utility on original datasets, robustness to controlled changes in dataset structure, and exploratory associations between dataset characteristics and performance variation. Our results show that scFM performance is strongly task dependent, with no single method consistently outperforming others across cell- and gene-level analyses. Notably, high utility on original datasets did not necessarily translate into robustness under structural perturbations, and several top-ranking methods were sensitive to changes in cell number, gene number, class composition, class imbalance, and batch complexity. Conventional statistical and task-specific methods remained competitive in several settings, while greater computational cost did not consistently correspond to better performance. Driver analyses further identified task-specific associations between performance and dataset characteristics, including cell-type complexity, train-test class overlap, batch number, and regulatory target-set size. Together, these findings show that the zero-shot utility and robustness of pretrained scFM representations depend jointly on analytical task and dataset structure. Our study provides a practical basis for context-aware representation selection and underscores the importance of evaluating structural robustness alongside utility when developing and applying scFMs.

bioinformatics↗

bioRxiv2026

CellTosg2Sequence: A Unified Text-Omics-Signaling-Graph Large Language Model for Single-Cell Analysis

In single-cell (sc)-based scientific discovery, text-formatted biomedical prior knowledge and signaling graphs are essential for annotating and interpreting numeric sc-omics data and for generating novel testable hypotheses. A major limitation of existing single-cell large language models (scLLMs) is that they rely on numeric expression data with gene names as the only textual signal, while comprehensive biomedical priors -- cellular localization, gene function, disease associations, and signaling interaction patterns -- remain absent from the model input. We introduce CellTosg2Sequence, a textual-prior- and signaling-graph-augmented cell-omics-sentence language model. A lightweight heterogeneous graph encoder maps a curated 62,507-node biomedical knowledge graph (KG) into compact virtual tokens that are prepended to each cell sentence, allowing the language model to condition on biological structure with minimal sequence-length overhead. We train CellTosg2Sequence with a three-stage objective: Stage I anchors the KG channel under autoregressive language-model pretraining, leveraging Qwen2.5-32Bs own language reasoning for rapid KG alignment; Stage II aligns labels via supervised fine-tuning with KG-anchored InfoNCE; Stage III applies Group Relative Policy Optimization (GRPO) with an ontology-hierarchy reward, enabling free-generation cell-type prediction that generalizes beyond the closed training vocabulary. Across multiple benchmarks and ablation experiments, CellTosg2Sequence outperforms strong baselines. All results are achieved with lightweight LoRA training and a single unified checkpoint. Data ethicsThis work uses publicly available single-cell datasets from the Human Cell Atlas (https://www.humancellatlas.org) and the Tahoe-100M consortium. All HCA constituent studies were collected under appropriate donor consent and institutional oversight as described in their original publications; we perform computational re-analysis only and introduce no new human subjects data. HCA data access follows the HCA Data Portal terms of use. No new patient data are collected in this study; no additional IRB approval is required for this secondary computational analysis.

bioinformatics↗

bioRxiv2026

Visual uncertainty and task demands shape active sensing strategies in mice

In natural environments, animals actively sample visual information to guide behavior. Sensory feedback is dynamic and often requires active movements, whether saccading across the lines of this page or walking through a park. From high-acuity vision in hawks to low-acuity mice, many animals actively navigate to seek information, which can be called infotaxis. Although mice have relatively low-acuity vision, they still rely on sight for critical behaviors including navigation and prey capture. Yet, how sensitive they are to visual information and performing infotaxis has not been established. Here, we develop a virtual reality object discrimination task to investigate visual decision-making under naturalistic conditions. We show that mice perform infotaxis by actively seeking out informative views to guide their choices. Stimulus manipulations confirm that this strategy is modulated by the amount of available visual information. These results reveal that mice use principled active strategies to resolve visual uncertainty, highlighting a key role for information-seeking in natural vision. HighlightsO_LIMice perform active visual sensing in a free-range VR object discrimination task. C_LIO_LIThey perform infotaxis and select the correct object under variable visibility. C_LIO_LIDecisions decoded from head-body movements and speed reflect occlusion sensitivity. C_LI

neuroscience↗

bioRxiv2026

A recombinant dilp2GS-rpr donor line for adult-inducible IPC ablation across Drosophila genetic backgrounds

Genetic-background studies require defined perturbations that can be crossed reproducibly into many recipient backgrounds. We generated a Drosophila dilp2GS-rpr donor line for adult-inducible ablation of insulin-producing cells (IPCs), which secrete insulin-like peptides and provide a tractable model of insulin-deficient metabolic physiology. This line carries dilp2-GeneSwitch-GAL4 and UAS-reaper in cis on the same second chromosome homolog over a balancer. PCR genotyping and sequencing confirmed both transgenic elements in the candidate recombinant line. RU486 induction reduced dilp2 mRNA expression, supporting partial IPC ablation. Treatment-duration testing identified 8 days of RU486 as sufficient to increase whole-body glucose in the dilp2GS-rpr line but not in the background-matched control; food intake did not differ between RU486- and vehicle-treated flies. Across metabolic assays, whole-body glucose showed the clearest RU486- and line-dependent phenotype. This validated dilp2GS-rpr line enables testing how recipient genetic backgrounds modify inducible IPC/DILP metabolic phenotypes and provides a framework for similar linked donor-line resources.

genetics↗

bioRxiv2026

Accurate detection of tumor clonality and ongoing expansion mode from genomic data

Recent evidence shows that despite considerable effort, currently available algorithms for estimating intratumor heterogeneity (ITH) remain limited. We developed DECODE (Deciphering Cancer Origin from DNA Evolution), a novel mutation clustering method that incorporates the impact of sample-specific sequencing coverage and mutation calling biases. On synthetic data, DECODE outperformed existing methods across multiple clonality metrics and accurately detected and characterized the neutral tail in the site frequency spectrum (SFS), which encodes the tumors ongoing expansion mode. In acute myeloid leukemia, accounting for the neutral tail enabled DECODE to yield more parsimonious clonal decompositions that align more closely with known subclonal dynamics that drive relapse. Applied to data from The Cancer Genome Atlas, DECODE not only detected a neutral SFS tail in most samples across tumor types but also uncovered a clinically meaningful link between ITH and survival in low-grade glioma. By jointly inferring clonality and expansion mode, DECODE provides two complementary and prognostically relevant readouts of tumor evolution from single tumor genomic samples.

bioinformatics↗