Biology subjects

Tang, W.

Publications and source records attributed to Tang, W..

At least 19 recordsLinked to original sources

bioRxiv2026

The cleaved C-terminal domain of GmERS1-1 modulates cell cycle via GmACR1

Ethylene signaling orchestrates plant development and stress adaptation, yet how post-translational modifications of its receptors coordinate growth regulation remains unresolved. Here, we uncover a proteolytic processing mechanism of the soybean ethylene receptor GmERS1-1 that directly gates cell cycle progression. The GmERS1-1 mutants exhibit elevated yield under field conditions, whereas overexpression suppresses growth and hypersensitizes plants to ethylene. Ethylene triggers nuclear translocation of C-terminal domain (GmERS1-1-CEND), which is indispensable for receptor function. Mechanistically, GmERS1-1-CEND scaffolds a trimeric complex with GmACR1 and GmCDK7, enforcing G2/M phase arrest, thereby decoupling cell division from canonical ethylene transcriptional responses. Strikingly, ethylene-induced cell cycle blockade during apple fruit maturation mirrors this pathway, suggesting deep conservation across angiosperms. Our work defines a receptor processing-dependent signaling axis that directly interlinks phytohormone perception with cell cycle control, proposing tunable targets (e.g., GmERS1-1 cleavage efficiency) for engineering crop architecture and productivity.

plant biology↗

bioRxiv2026

SMORE: joint dimension reduction and cell population discovery on single-cell methylome data

Single-cell DNA methylation profiling technology captures novel epigenetic data modality but are challenging to analyze because of their heterogeneity, high dimensionality, and ultra-sparsity. Here we present SMORE (Single-cell MethylOme Reduction and Embedding), a computational method for joint dimensionality reduction and cell population discovery dedicated to single-cell DNA methylation data. SMORE operates on a Bayesian framework that converts methylation proportions into ordered methylation states and jointly infers a low-dimensional representation, cell populations and their number. By using low-rank latent Gaussian factorization and adopting a mixture-of-finite-mixtures prior on latent cell scores, SMORE infers cell assignments without requiring a prespecified cluster number, and propagates uncertainty from methylation measurements to cell assignments. Across simulations spanning varying sample sizes, population imbalance, signal strengths and model misspecification, SMORE accurately recovered latent population structure and outperformed existing methods. Applied to human single-cell methylation datasets from lung, peripheral blood and primary motor cortex, SMORE recovered biologically supported cell population structures. SMORE provides an uncertainty-aware framework for dimension reduction and population discovery for single-cell methylomes.

bioinformatics↗

bioRxiv2026

Eastern equine encephalitis virus-vaccinated mice are protected against Madariaga virus despite negligible neutralizing antibody titers

Madariaga virus (MADV) is an understudied member of the eastern equine encephalitis virus (EEEV) complex that circulates widely in Latin America and may be geographically expanding. Spillover infections can cause severe disease in humans and equids. Despite these public and animal health concerns, no MADV vaccines or treatments are available. In this context, commercially available equine vaccines against the closely related North American EEEV (NA EEEV) could potentially provide heterologous protection against MADV. However, previous studies have shown weak or undetectable MADV-neutralizing antibody responses in equids and humans immunized with inactivated NA EEEV vaccines, and whether protection can occur despite these limited neutralizing antibody responses remains unknown. We evaluated a commercial equine trivalent inactivated NA EEEV vaccine against MADV challenge in NIH Swiss mice. Animals received two vaccine doses 14 days apart and were challenged 14 days later. Vaccination provided protection against lethal disease, whereas 36% mortality occurred in the unvaccinated group. Overall, vaccinated animals developed fewer and less severe clinical signs. MADV RNAemia was not detected following vaccination, and tissue dissemination was significantly reduced compared with the unvaccinated group. Central nervous system lesions were observed only in the unvaccinated group. Despite protection, most vaccinated mice had no detectable MADV-neutralizing antibody titers, and those that seroconverted developed only low titers, whereas most unvaccinated mice developed intermediate to high titers. These findings demonstrate that an inactivated NA EEEV-containing vaccine can protect against severe MADV disease despite limited MADV-neutralizing antibody responses.

systems biology↗

bioRxiv2026

Multiparametric in vivo mapping reveals tissue-specific mitochondrial aging trajectories

Mitochondrial dysfunction is a hallmark of aging, yet how mitochondrial states are remodeled across tissues and subcellular compartments in vivo remains elusive. Progress has been limited, in part, because mitochondrial physiology is highly sensitive to experimental perturbations, underscoring the need for minimally disruptive measurement strategies. Here, we establish a tissue-resolved, in vivo framework for the quantitative analysis of mitochondrial states in live, intact Caenorhabditis elegans without confounding effects from mounting-induced hypoxia. This platform couples two-photon fluorescence lifetime imaging microscopy (2p-FLIM) with a custom segmentation pipeline, MitoSLIT, to track functional and structural features across multiple tissues and single neurons. By integrating membrane potential-associated TMRM intensity, lifetime-based microenvironmental metrics, and morphological descriptors, we uncover localized metabolic heterogeneity masked by conventional intensity analysis. Leveraging this framework, we mapped physiological aging against mitochondrial shifts induced by acute stress and fission-fusion mutations. Our analyses reveal that mitochondrial aging is highly tissue-specific, executing distinct trajectories across cell types. Extending the framework to genetically identified neurons revealed age-dependent divergence between somatic and axonal mitochondrial states, accompanied by structural remodeling and a late shift in optical redox ratio. Together, our findings demonstrate that mitochondrial populations do not converge on a uniform bioenergetic endpoint during aging, but rather follow highly compartmentalized, tissue-specific spatiotemporal trajectories in vivo.

physiology↗

bioRxiv2026

OmicOS: A Comprehensive Omics Ecosystem Infrastructure and Agent System for the AI Era

Biology has accumulated a vast ecosystem of omics methods, but much of this ecosystem remains built for expert humans rather than scientific agents. Methods are scattered across Python packages, R/Bioconductor and CRAN workflows, command-line tools, incompatible data containers and implicit object states, making even routine analyses difficult for an AI system to choose, execute and verify reliably. Here we introduce OmicOS, a comprehensive omics ecosystem infrastructure and agent system that turns OmicVerse V2, an open-source omics community, into an executable foundation for agentic biology. OmicVerse V2 provides the community substrate: scalable AnnDataOOM-compatible rust backends, agent-friendly Python algorithms for single-cell, spatial, bulk and multi-omics analysis, interfaces to single-cell foundation models, and Python-native reconstructions of historically R-centred Bioconductor/CRAN-style workflows. OmicOS makes this substrate actionable by registering analytical functions as state-aware capability contracts, allowing agents to inspect live data objects, select valid methods, execute controlled workflows and record provenance. The result is not a fixed pipeline, but a programmable omics environment in which agents compose real analyses from verified community methods rather than inventing tools. Across external and purpose-built benchmarks, OmicOS ranked first among the evaluated systems, reaching 81.2% on BiomniBench. Adding OmicVerse to a minimal agent improved task completion by up to 34.2 percentage points with qwen-3.6-35b, and controlled ablations showed that the gains came from registry-grounded execution rather than from larger models, documentation retrieval or unrestricted tool exposure. The same infrastructure scaled to atlas-sized data, reproduced R-centred workflows in Python and converted external pathology software into agent-usable skills. In a discovery task starting from a whole-body spatial map and the term "Alzheimers disease", OmicOS composed a non-canonical workflow that integrated spatial expression, genetic association, eQTL and colocalization evidence to nominate a colon epithelial risk axis centred on PICALM, CD2AP and CR1. Together, OmicVerse and OmicOS define an open foundation for AI-era omics, showing how a community of biological methods can be transformed into a reliable, extensible and agent-operable system for discovery. HighlightO_LIOmicVerse 2.0 consolidates 694 methods spanning 11 omics domains into agent-callable high-level APIs. C_LIO_LIRebuildR automatically reconstructs and evolves R/Bioconductor methods as Python-native implementations under output-equivalence gates. C_LIO_LIOmicOS establishes a state-of-the-art omics agent harness, ranking first on general omics benchmarks across models and substantially improving the analytical capability of local open-source models. C_LIO_LICompositional use of ecosystem modules nominates a colon epithelial axis associated with Alzheimers disease risk. C_LIO_LIExternal algorithm packages supporting automatic iterative evolution can be integrated into the OmicOS ecosystem. C_LI

bioinformatics↗

bioRxiv2026

Cellfm-datasets: A Unified Data Infrastructure for Single-Cell and Spatial Transcriptomics Foundation Model Pretraining

Large-scale cell foundation models are increasingly limited not only by model architecture, but also by the data infrastructure required to repeatedly sample sparse transcriptomic profiles from out-of-core cohorts. AnnData/H5AD has become a standard exchange format for single-cell and spatial omics analysis, yet its HDF5-backed layout is not designed for high-frequency random mini-batch loading under multi-worker and distributed pretraining. We present Cellfm-datasets, a data infrastructure artifact that converts H5AD cohorts into a self-describing compressed sparse row (CSR) memmap layout and exposes the resulting corpus through Hugging Face Dataset and IterableDataset interfaces. The artifact stores a shared gene vocabulary, per-sample metadata, optional spatial coordinates, observation metadata, manifests, and checksums, and reconstructs sparse cell or group records at runtime without dense expansion. A unified sampling abstraction supports random-cell groups, manifest-defined biological regions, and coordinate-based spatial blocks, with deterministic sharding across distributed ranks and data-loader workers. Spatial demonstrations on P14 mouse brain transcriptomics sections illustrate region- and block-level sampling over real anatomical structures. In controlled benchmarks on a public heterogeneous ModelScope scRNA-seq subset, Cellfm-datasets reached 60,571 {+/-} 1,734 samples/s in single-core random loading, scaled to approximately 160,000 samples/s with eight workers, and maintained near-constant process-private memory while reading up to one million cells. By moving sparse single-cell and spatial corpora from model-specific loader code into reusable, validated, and framework-native dataset artifacts, this design may reduce the engineering burden of reproducible cell foundation model pretraining and make repeated training runs, model comparisons, and mixed-modality data reuse easier to standardize. Code availabilityhttps://github.com/PangJiangShuan/cellfm-datasets

bioinformatics↗

bioRxiv2026

De novo design of transmembrane accessory subunits for fold stabilization and expansion

Transmembrane (TM) proteins play essential roles in biology as transporters, ion channels, chaperones, enzymes, and mediators of signal transduction. However, membrane proteins often suffer from inefficient folding and intrinsic instability. Misfolding in cells can cause numerous loss-of-function pathologies. Likewise, denaturation upon purification in the laboratory is a critical barrier to structure determination and characterization of key biochemical mechanisms. Generalizable strategies to stabilize membrane proteins remain limited. Here, we developed an informatics-based de novo design strategy to create synthetic auxiliary subunits that interact with the TM helices of a model pentameric ion channel, thereby bolstering folding while maintaining channel function. Biochemical and structural characterization reveal the synthetic TM subunits can also be used to create larger multi-spanning designer proteins of custom topology. This proof-of-concept motivates the feasibility of computationally designed accessory TM helices as potential pharmacological chaperone "folding correctors" of membrane proteins in disease and as tools in structural biology.

biochemistry↗

bioRxiv2026

A Multi-Objective Scoring (MOS) Framework for Detecting Cross-Modal Spatial Similarity: Conceptual and Direct Formulations

Spatial multi-omics methods allow researchers to study complex biological systems by integrating multiple molecular layers while preserving their spatial organization. However, integrating spatial transcriptomics and mass spectrometry imaging (MSI) remains challenging due to the differences between the two modalities, including sampling geometry, spatial resolution, signal scaling, and measurement principles. For example, 10x Genomics Visium captures transcriptomic data on a discrete hexagonal grid of spots; however, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) produces dense Cartesian pixel maps of molecular distributions. These differences make exact spatial co-registration difficult and limit the effectiveness of single-metric similarity approaches. Here, we introduce a Multi-Objective Scoring (MOS) framework designed to detect cross-modal spatial similarity without requiring exact pixel-to-pixel alignment. The MOS framework integrates multiple complementary spatial descriptors into a unified similarity score, including coordinate-based metrics (value correlation, importance-based Intersection-over-Union (IoU), and importance-map correlation) and descriptor-based metrics that capture higher-order spatial organization, such as spatial histograms, radial profiles, quadrant statistics, and Morans I spatial autocorrelation. These metrics are combined through a weighted ensemble model. This model calculates the weights using synthetic spatial datasets that simulate realistic tissue geometry, sampling differences, and spatial distortions. The framework was applied to a spatial multi-omics dataset from murine brain tissue, integrating spatial transcriptomics with MALDI-MSI lipidomics across young and aged control and Alzheimers disease (AD) models. Synthetic data validation results demonstrated strong pattern-matching performance (96.14% accuracy), and application to experimental data identified several MSI analyte features whose spatial distributions closely matched transcriptomic patterns. In particular, strong and reproducible associations were observed between myelin-related genes (Mbp and Plp1) and multiple analyte features enriched in white matter regions. Overall, whether applied conceptually or directly, the MOS framework provides a strong strategy for cross-modal spatial integration and offers a scalable tool for discovering spatial relationships across diverse multi-omics datasets and facilitating hypothesis generation.

biochemistry↗

bioRxiv2026

MolClaw: An Autonomous Agent with Hierarchical Skills for Drug Molecule Evaluation, Screening, and Optimization

Computational drug discovery, particularly the complex workflows of drug molecule screening and optimization, requires orchestrating dozens of specialized tools in multi-step workflows, yet current AI agents struggle to maintain robust performance and consistently underperform in these high-complexity scenarios. Here we present MolClaw, an autonomous agent that leads drug molecule evaluation, screening, and optimization. It unifies over 30 specialized domain resources through a three-tier hierarchical skill architecture (70 skills in total) that facilitates agent long-term interaction at runtime: tool-level skills standardize atomic operations, workflow-level skills compose them into validated pipelines with quality check and reflection, and a discipline-level skill supplies scientific principles governing planning and verification across all scenarios in the field. Additionally, we introduce MolBench, a benchmark comprising molecular screening, optimization, and end-to-end discovery challenges spanning 8 to 50+ sequential tool calls. MolClaw achieves state-of-the-art performance across all metrics, and ablation studies confirm that gains concentrate on tasks that demand structured workflows while vanishing on those solvable with ad hoc scripting, establishing workflow orchestration competence as the primary capability bottleneck for AI-driven drug discovery.

bioinformatics↗

bioRxiv2026

Hyperactive STAT1 Promotes T Follicular Helper Type 1 Cell Differentiation to Trigger Autoimmunity

ABSTRACTSHeterozygous gain-of-function (GOF) mutations in signal transducer and activator of transcription 1 (STAT1) cause an inborn error of immunity characterized by immune dysregulation, recurrent infections and various autoimmune manifestations. However, the precise pathogenic mechanism by which STAT1 GOF contributes to autoimmunity remains elusive. In our cohort, STAT1-GOF patients exhibit biased circulating follicular helper T (cTfh) populations with CXCR3+ Tfh1-like features. Using a Stat1 GOF mouse model that spontaneously developed autoimmunity, we found that overactivated STAT1 promotes Tfh differentiation and disrupted T cell-dependent humoral responses with skewed immunoglobulin class switching towards IgG2. Furthermore, STAT1 GOF directly targets to Tfh and Th1 cell signature genes and thereby drives the development of Tfh1 cells with excessive IFN-{gamma} production, which implicated in autoantibody production and the development of autoimmunity. Notably, IFN-{gamma} neutralization significantly alleviated autoimmune cellular responses and autoantibody levels in mutant mice, highlighting IFN-{gamma} blockade as a promising targeted therapy for the STAT1-GOF patients with autoimmunity. Our findings suggest that proper regulation of STAT1 activity within a reasonable magnitude is crucial for ensuring optimal host-protective humoral immunity. One-sentence summaryOveractivated STAT1 promotes Tfh1 differentiation to drive autoimmunity.

immunology↗

bioRxiv2026

HMA proteins produce 2',3'-cNMP signaling molecules and activate CNL-mediated immunity in rice

Plants deploy a sensor repertoire, usually NLRs, to perceive pathogen effectors and activate executor NLR-triggered immunity. Here we reveal that rice HMA proteins function as sensors detecting the Magnaporthe oryzae MAX effector AvrPigm to trigger broad-spectrum blast resistance mediated by the CNL PigmR. AvrPigm is conserved with multiple copies in blast genomes and targets HMA proteins, facilitating HMA translocation into the cytoplasm. Cryo-EM structure of the HPP04HMA reveals a filament-like oligomer with ssDNA/RNA bound inside the filament, which display cyclic nucleotide synthase activity to generate 2',3'-cNMP in a CNL-dependent manner. We further discovered that the LRR domains of the executor CNLs perceive 2',3'-cNMP to mount immunity. Our study thus establishes an unrecognized immunity mode with a distinct repertoire of sensor receptors that produce signaling molecules that are perceived by the LRR domains of executor NLRs to mediate immunity, shedding new light on the sensor-executor conception and immune activation in plants. HighlightsO_LIHMA proteins and CNL receptors form a new sensor-executor mode in plant immunity C_LIO_LICryo-EM reveals the filament-like structure of HMA-ssRNA/ssDNA C_LIO_LIHMA proteins are cyclic nucleotide synthetases to generate 2',3'-cNMP C_LIO_LILRR domains of CNLs perceive 2',3'-cNMP to mediate immunity C_LI

plant biology↗

bioRxiv2026

Dynamic shifts in brain criticality support cognitive processing

Systems operating near their critical point, or close to a transition between order and disorder, have computational advantages. In the case of neural networks, proximity to criticality is proposed to support optimal brain function. However, different cognitive processes rely on disparate computational demands. Using large-scale electrophysiological recordings in behaving rodents, we examined how critical dynamics in the hippocampus are regulated during learning and sleep-dependent memory consolidation. We found that operating near criticality enables learning by facilitating hippocampal coordination with input regions and maximizing flexibility of neural representations. In contrast, the hippocampal network shifts toward a more ordered, subcritical regime during sleep memory replay, and recovers its proximity to criticality through cholecystokinin interneurons-mediated inhibition. Overall, our findings provide a biophysical substrate for understanding how critical dynamics in neuronal networks can support a variety of brain functions. Importantly, our results suggest that optimal learning systems, whether biological or artificial, may require a dynamic regulation between flexible and rigid states, and can offer biophysical constraints to guide the design of Large Language Models (LLM) tuned to criticality.

neuroscience↗

bioRxiv2026

Longitudinal modality prediction learns gene regulatory patterns: insights from a single-cell competition

Simultaneous measurement of chromatin, transcriptomic, and proteomic features in single cells opens new avenues for modeling interactions between molecular layers during dynamic biological processes. Predicting one modality from another - such as inferring gene expression from chromatin profiles or protein abundance from RNA - has the potential to reveal regulatory relationships and enhance downstream analyses. However, conventional approaches for predicting gene regulation have largely failed and method development in modality prediction for regulatory inference has been limited. To explore effective modeling strategies and stimulate innovation, we generated a purpose-built longitudinal multimodal benchmarking dataset that captures early hematopoietic differentiation and organized the largest single-cell data competition to date, receiving over 27,000 submissions from 1,602 competitors worldwide. In our extensive analysis of the competition results, we demonstrated that top-performing approaches outperform state-of-the-art methods, and uncover how best-performing models captured biologically meaningful regulatory relationships between modalities. With ablation studies of the winning models, we identified feature-engineering strategies, model architectures and cross-validation schemes that are crucial for outstanding performance, and provide simplified, reproducible, light-weight code for state-of-the-art models. Together, the benchmark and analyses serve as an evaluation standard and guide future method development, including recently emerging foundation models, to advance our understanding of regulatory interactions in longitudinal, multimodal single-cell data.

bioinformatics↗

bioRxiv2026

LOTUS-domain proteins activate Vasa to drive germ granule assembly

Germline development relies on perinuclear membraneless germ granules, yet the mechanisms underlying their assembly remain incompletely understood. Here we uncover a conserved and central role for LOTUS-domain proteins in driving germ granule assembly. In C. elegans, the LOTUS-domain protein EGGD-1/MIP-1 at sub-stoichiometric levels recruits Vasa protein GLH-1 to the nuclear periphery. Acting as a catalyst, EGGD-1 impacts the ATPase cycles of GLH-1 by preferentially binding to its open conformation, enhancing its RNA binding activities, and facilitating its transition to the closed conformation. GLH-1 in the closed state enriches mRNAs at the nuclear periphery, which enables the accumulation of RNA-binding proteins including PGL-1 and PGL-3. Using human cells, we demonstrate the LOTUS-domain protein TDRD5 similarly recruits DDX4, the human Vasa homolog, and stimulates the formation of intermitochondrial cement. Collectively, these findings reveal evolutionarily conserved stimulatory effect of LOTUS-domain protein in Vasa activity and provide a unified model for germ granule assembly across species.

cell biology↗

bioRxiv2026

Dynamic RNA Polymerase compartments organize the transcription of gene clusters

Spatial organization of transcription machinery is emerging as a key regulator of gene expression, yet how RNA polymerases are organized at gene clusters remains unclear. Here, we show that RNA polymerases II and polymerase III form distinct nuclear foci at the 5S ribosomal DNA (rDNA)-Spliced leader 1 (SL1) cluster in C. elegans. Within this cluster, polymerase II binds to the SL1 gene, while polymerase III associates with 5S rDNA. Both polymerase foci display dynamic but distinct behaviors within the nucleus. The assembly of these polymerase foci is regulated across the cell cycle. ATTF-6, an AT-hook transcription factor, is essential for polymerases II foci formation but dispensable for polymerases III foci. While Pol III foci are largely resistant to temperature changes, Pol II foci are temperature-sensitive, and their dissolution correlates with reduced SL1 expression. Together, these results reveal a spatial and temporal regulation of two RNA polymerases that organize gene cluster transcription.

cell biology↗

bioRxiv2025

Two-photon in vivo imaging reveals cell type-specific mitophagy dynamic changes in mouse somatosensory cortex during aging

Mitochondrial homeostasis is maintained through mitochondrial autophagy, a process commonly known as mitophagy. Recent research has begun to highlight the region- and cell type-specific nature of mitophagy during brain aging; however, these dynamics have largely remained unexplored in living brains. To address this gap, we conducted two-photon mt-Keima imaging in somatosensory cortical neurons and astrocytes in behaving mice across two age groups. Our observations revealed a reduction in mitophagy levels in both cell types during aging, and we consistently found a higher level of mitophagy in astrocytes compared to neurons across both age groups, indicating a cell type-specific mitophagy dynamics that is independently of the aging process. NAD+ augmentation improved mitophagy level in both neurons and astrocytes in old-aged mice at the dose and method of administration tested. Collectively, our data underscore the critical importance of both neuronal and astrocytic metabolic roles in brain aging. The findings also suggest that NAD+ repletion has clinical value in potentially improving these cell type-specific mitophagy dynamics during aging.

neuroscience↗

bioRxiv2025

PDS5 proteins control genome architecture by limiting the lifetime of cohesin-NIPBL complexes

Cohesin-NIPBL complexes extrude genomic DNA into loops that are constrained by CTCF boundaries. This process has important regulatory functions and weakens the separation between euchromatic and heterochromatic compartments. Cohesin can also bind PDS5A or PDS5B, which do not support loop extrusion but are required for the formation of CTCF boundaries. How PDS5 proteins perform this function is unknown. Here we show by in vitro single-molecule imaging that PDS5 proteins stop loop extrusion by facilitating the dissociation of NIPBL from cohesin. Hi-C experiments suggest that this function is required for the establishment of CTCF boundaries in cells. In silico modelling indicates that PDS5 proteins enable the separation between compartments by limiting cohesins velocity and chromatin-residence time. The degree of this compartmentalization depends on the frequency with which chromatin is extruded relative to the time it takes for compartments to form. These results identify PDS5 proteins as key regulators of genome organization. HighlightsO_LIPDS5 proteins stop loop extrusion by facilitating dissociation of NIPBL from cohesin. C_LIO_LIPDS5 proteins strengthen CTCF boundaries by limiting the lifetime of cohesin-NIPBL. C_LIO_LIPDS5 proteins regulate compartmentalization. C_LIO_LICompartmentalization is governed by polymer relaxation and loop extrusion dynamics. C_LI

molecular biology↗

bioRxiv2025

Goal-directed hippocampal theta sweeps during memory-guided navigation

During navigation, animals continually sample their surrounding space and plan routes to distant goals. The brain mechanisms underlying these behaviors and how they coordinate to support memory-guided navigation in open environments are not understood. Using large-scale recordings in rats, we found two distinct types of place cell sequences within theta cycles that encoded trajectories sweeping beyond the animals location: stereotypic left-right alternating sweeps and learning-dependent goal-directed sweeps. Goal-directed sweeps predicted upcoming trajectories to remembered goal locations, were coordinated with prefrontal cortex activity and preferentially replayed during sharp-wave ripples. We further describe a circuit mechanism in which a subpopulation of CA1 cells encodes egocentric goal direction, combined with reduced feedback inhibition, to generate goal-directed theta sweeps. These results indicate a flexible mechanism to support different behavioral demands during navigation.

neuroscience↗