Biology subjects

Qiao, L.

Publications and source records attributed to Qiao, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Kinase-phosphatase cycles drive self-sustained oscillations of protein condensates

Phase-separated protein condensates organize biochemical processes in cells. ATP-driven enzymatic reactions can change the physical properties and even trigger the dissolution of such condensates. Here we use molecular simulations to show how ATP-driven kinase and phosphatase reactions modulate the organization of TDP-43 low complexity domain (LCD) condensates. TDP-43 phosphorylation is enhanced by condensation, as CK1{delta} preferentially binds to and acts in TDP-43 LCD condensates, whereas dephosphorylation by the phosphatase calcineurin occurs predominantly in the dilute phase. This differential recruitment of kinases and phosphatases, together with the slow redistribution of kinases into newly formed condensates, triggers oscillatory appearance and disappearance of TDP-43 LCD condensates. The oscillations are self-sustained, persisting at constant chemical driving, showing that an antagonistic kinase-phosphatase pair can endow a condensate with autonomous dynamics rather than only setting its structure.

biophysics↗

bioRxiv2026

Systematic analysis of genetic vulnerabilities caused by chromosome loss events in cancer

Chromosome loss events are common across tumor types but rarely occur in normal tissue, raising the possibility that these alterations could be exploited as cancer-specific therapeutic vulnerabilities. Here, we integrate genome-scale CRISPR screening data with chromosome-level copy number profiles from 1,150 cancer cell lines and identify 389 dependencies that are selectively associated with individual chromosome loss events. The most significant vulnerabilities uncovered by our analysis are paralogous gene pairs, in which the loss of a paralog on an aneuploid chromosome establishes a unique dependency on its redundant paralog encoded elsewhere in the genome. We experimentally validate two paralog dependencies: loss of chromosome 8p, which encodes the phosphatase PPP2CB, creates a specific dependency on its paralog PPP2CA, while loss of the Y chromosome, which encodes the helicase DDX3Y, creates a specific dependency on its paralog DDX3X. Systematic benchmarking of CRISPR screening data indicates that the selective dependency on DDX3X in loss-of-Y cells exceeds other published aneuploidy-associated vulnerabilities and matches or exceeds most clinically-validated biomarker-target relationships. Furthermore, we found that the acute degradation of DDX3X was sufficient to trigger apoptosis in vitro and tumor regressions in mice. Collectively, these findings establish chromosome loss as a recurrent source of biomarker-defined therapeutic targets, identify paralog insufficiency as a general vulnerability in aneuploid cells, and provide in vivo proof-of-concept for targeting DDX3X in cancers with Y chromosome loss.

cancer biology↗

bioRxiv2026

Scaling genetic discovery through automated post-GWAS interpretation

Genome-wide association studies (GWAS) have made association discovery systematic and cumulative, yet evidence for interpreting associated loci remains selective, heterogeneous and difficult to accumulate across studies. Here we present Post-GWAS Intelligence (PGI), which couples context-dependent post-GWAS analysis to a common representation of analysis-derived evidence. Its multi-agent engine, VariantAgent, executes workflows, records tool-derived results in standardized variant-centred units and generates trait-level interpretations linked to their analytical basis and evidential status. Complementary benchmarks showed that VariantAgent outperformed tested general-purpose and biomedical agents, with its largest advantage when success required both a correct answer and a valid analytical trace. Across 34 published GWAS, VariantAgent achieved a mean per-study recovery of 82.1% for directly comparable findings. The largest gains lay downstream of association mapping, where uniform analysis extended published interpretations and identified regulatory relationships at established risk loci not previously reported in the source studies. Analysis of 1,041 GWAS yielded 530,949 evidence units and corresponding reports, which PGI organized into a cross-trait catalogue. Catalogue interrogation resolved an apparent cross-trait overlap into distinct signals and trait-specific biological hypotheses. This work demonstrates how PGI can extend genetic discovery beyond association mapping by enabling biological evidence to accumulate across studies.

genetics↗

bioRxiv2026

CHPT1-LCAT rewires lipolysis towards ferroptosis

Ferroptosis is driven by iron-dependent lipid peroxidation, yet how metabolic flux through central lipid pathways is selectively routed towards pro-ferroptotic lipid species remains unclear. Here, through an unbiased chemical-genetic screen targeting core metabolic enzymes, we identify diacylglycerol (DAG) as a licensing lipid intermediate whose pro-ferroptotic activity depends on its intracellular routing. Systematic manipulation of lipolytic flux reveals that ferroptotic vulnerability is not determined by bulk lipolytic output or downstream intermediates, but by the selective channelling of DAG into a distinct metabolic fate. Mechanistically, DAG is selectively routed through a previously unrecognized intracellular metabolic axis composed of choline phosphotransferase 1 (CHPT1) and lecithin-cholesterol acyltransferase (LCAT). We uncover an enzymatically active intracellular pool of LCAT (iLCAT) that cooperates with CHPT1 on Golgi-trans-Golgi network membranes to generate polyunsaturated cholesteryl esters that execute ferroptosis. Functionally, enforced DAG routing through this axis suppresses tumour growth via ferroptosis in vivo, whereas hepatocyte-specific inhibition of the CHPT1-iLCAT axis attenuates lipid peroxidation and disease progression in metabolic dysfunction-associated steatohepatitis. Together, these findings establish subcellular lipid routing, rather than lipid abundance per se, as a fundamental determinant of ferroptotic vulnerability.

cell biology↗

bioRxiv2026

Fluorescence anisotropy structured illumination microscopy for quantitative super-resolved mapping of cell microenvironment and cytoskeletal dynamics

The crowded intracellular milieu shapes organelle architecture and dynamics, yet nanoscale heterogeneity in its physicochemical properties remains difficult to visualize with conventional fluorescence anisotropy (FA) imaging. Here, we develop fluorescence anisotropy structured illumination microscopy (FA-SIM), which employs orthogonal-polarization structured illumination with dual-angle detection to achieve [~]100-nm resolution and quantitative FA retrieval with 0.56% relative error, representing over 20-fold higher accuracy than conventional FA imaging. With low phototoxicity, FA-SIM enables dual-color, hour-long quantitative super-resolution imaging in cells. Using viscosity standards, defined nanoparticles and small-molecule drug binding assays, we validate FA-SIM as a quantitative reporter of rotational mobility and molecular interactions. In cells, FA-SIM resolves nanoscale crowding heterogeneity, correlates anisotropy landscapes with condensate dynamics, and uncovers a radial crowding gradient across the microtubule network and mitotic spindle. Long-term dual-color imaging further resolves coordinated actin-microtubule remodeling and associated microenvironmental changes. By enabling quantitative, super-resolved mapping of intracellular physical properties in living systems, FA-SIM provides a powerful platform for investigating the physical regulation of cellular organization and dynamics in health and disease.

cell biology↗

bioRxiv2026

Brca1 heterozygosity leads to hepatic steatosis in male and female mice despite sexually dimorphic effects on systemic metabolism

Carrying a germline mutation in BRCA1 is associated with an increased risk of several cancers, including breast and ovarian. Our recent work has demonstrated that obesity is associated with elevated levels of DNA damage in breast glands in this high-risk population. BRCA1 is a canonical tumor suppressor gene primarily recognized for its role in DNA damage repair, yet emerging evidence suggests broader functions in metabolic regulation. To determine whether heterozygous loss of Brca1, as seen in individuals who carry a germline mutation, modifies susceptibility to diet-induced metabolic dysfunction in a sex-dependent manner, we subjected wild-type (WT) and Brca1+/- mice of both sexes to a high-fat diet (HFD) and performed longitudinal metabolic phenotyping. Female Brca1+/- mice exhibited pronounced obesity, increased adiposity, hyperinsulinemia, and impaired glucose tolerance. In contrast, male Brca1+/- mice showed modest resistance to HFD-induced weight gain and displayed improved glucose tolerance compared to WT controls. Notably, Brca1 heterozygosity led to more severe hepatic steatosis with HFD, indicating a shared susceptibility to liver lipid accumulation despite divergent systemic outcomes. In females, steatosis was associated with reduced mitochondrial respiratory complex IV activity and transcriptional remodeling that favored lipid storage. Treatment with the dual GLP1/GIP receptor agonist tirzepatide ameliorated systemic metabolic dysfunction and hepatic steatosis in HFD-fed female Brca1+/- mice. These findings identify Brca1 heterozygosity as a modifier of metabolic disease risk, expanding BRCA1 biology beyond tumor suppression. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/708005v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@17f9592org.highwire.dtl.DTLVardef@134c2c2org.highwire.dtl.DTLVardef@de69d8org.highwire.dtl.DTLVardef@1f6f1af_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2026

IntelliFold-2: Surpassing AlphaFold 3 via Architectural Refinement and Structural Consistency

IntelliFold-2 is an open-source biomolecular structure prediction model that improves accuracy and robustness through architectural refinement and multiscale structural consistency. We introduce latent space scaling in Pairformer blocks, a principled atom-attention formulation with stochastic atomization, policy-guided optimization for diffusion sampling and difficulty-aware loss reweighting. On Foldbench, IntelliFold-2 improves performance in therapeutically relevant settings, with particularly strong gains for antibody-antigen interactions and protein-ligand co-folding relative to AlphaFold 3. We release three variants (Flash, v2, and Pro) to cover efficient fine-tuning through high-precision server-side inference.

bioinformatics↗

bioRxiv2026

The BELL-type homeobox transcription factor RLC3/OsBLH4 controls leaf rolling and drought tolerance via KNOX-BELL-lignin regulatory network in rice

O_LIModerate leaf rolling in rice is crucial for plant architecture and stress adaptation, but its molecular regulation remains unclear. We investigated the role of RLC3/OsBLH4, a BELL-type homeobox transcription factor, in controlling leaf rolling and drought tolerance, addressing gaps in lignin biosynthesis and cell wall development mechanisms. C_LIO_LIWe used gene map-based cloning (rlc3-1, rlc3-2), CRISPR/Cas9 knockout lines (rlc3-ko#11, rlc3-ko#12), and allelic complementation to validate RLC3s function. Additionally, we employed biochemical assays, gene expression analysis, and protein interaction studies to explore its regulatory network. C_LIO_LIRLC3 mutations impaired lignin biosynthesis and secondary cell wall formation, reducing bulliform cells area and causing midrib defects. These structural abnormalities accelerated water loss, leading to excessive leaf rolling and compromised drought tolerance. Mechanistically, RLC3 directly activates lignin synthesis genes (OsPAL5, OsCOMT5, OsCCR4, OsCAld5H1) and interacts with KNOX transcription factors (OSH1, OSH45, OSH71) to form a KNOX-BELL complex, further regulating lignin content and cell wall development. C_LIO_LIRLC3 orchestrates lignin deposition and secondary cell wall development to control leaf rolling, water transport, and drought tolerance. This study reveals a novel KNOX-BELL-lignin regulatory module governing leaf morphology and stress adaptation, offering targets for crop improvement under drought conditions. C_LI

plant biology↗

bioRxiv2025

Systems modeling of mitochondrial dynamics in different exercise regimes

Exercise stimulates skeletal muscle signaling and mitochondrial metabolism. Emerging evidence shows that mitochondrial dynamics (i.e., fission and fusion) could be regulated by exercise. Yet, there are knowledge gaps on the following questions: (i) which upstream signals are necessary and sufficient to bias mitochondria toward fission versus fusion? (ii) How does cellular energy status and ROS partition control between DRP1 and MFN/OPA1? And (iii) which combinations of intensity and duration produce similar cytosolic signals but distinct mitochondrial remodeling? To address these gaps, we developed an integrative computational framework that connects exercise regimens to mitochondria fission-fusion machinery by linking blood-myofiber energetics in cytosol and mitochondria to skeletal muscle signaling network. The influence of three exercise regimen (i.e., sprint, resistance, and endurance) on mitochondrial fission and fusion was simulated. Classified qualitative validation of signaling network model against studies not used in developing the model achieved 80% accuracy. The model predicts regimen-specific dynamics starting with acute DRP1-driven fission during exercise followed by MFN1/2-OPA1-mediated re-fusion as energy stress declines, consistent with a cyclical triage-then-rebuild paradigm. Changes are most pronounced and sustained with endurance, sharp but brief with sprint, and minimal with resistance. Global sensitivity analysis identified AMPK/PGC-1[->]MFN1/2 as dominant fusion drivers, ROS and AMPK[->]MFF/DRP1 as primary fission switches, and Ca{superscript 2}-calmodulin, ERK, and LKB1/AMPK as shared regulators of fission and fusion. Our model also predicts that an endurance base, augmented with 1-2 weekly high intensity interval traning (HIIT)/ sprint interval training (SIT) sessions could maximize AMPK-ROS pulses and mitochondrial fission-fusion. This framework unifies muscles signaling logic with the energetic state to explain how intensity-volume combinations, bout spacing, and kinase modulation tune mitochondrial remodeling, yielding testable predictions for optimizing training and adjuvant therapies for enhanced human performance.

systems biology↗

bioRxiv2025

Engineered Promoter System Enables High-efficiency Transgenic CRISPR Editing in Malaria Transmitting Mosquito Anopheles sinensis

The CRISPR/Cas9 system deployed through crosses of transgenic lines expressing Cas9 and gRNA facilitates efficient mutagenesis. However, its application in non-model insects remains limited, primarily due to a lack of well-characterized promoters capable of driving robust and stable expression of Cas9 and gRNA. In the malaria mosquito Anopheles sinensis, we evaluated several ovary-biased promoters--Asvasa2, Aszpg, and Asnanos--for driving Cas9 expression. Notably, the Asvasa2 promoter mediated mutagenesis in nearly 60% of G0 individuals following microinjection of gRNAAswhite. Among four RNA polymerase III promoters derived from AsU6 genes, AsU6-1 yielded the highest gRNA transcriptional output, enabling 62% editing efficiency in G0 offspring. In addition, hybrid crosses between established transgenic lines demonstrated that the Asvasa2-Cas9 and AsU6-1-gRNA combination enabled complete germline editing penetrance, where all F2 progeny inherited the intended mutations. This work provides a essential genetic toolkit for synthetic biology applications in Anopheles mosquitoes and a scalable framework for engineering other non-model insects.

genetics↗

bioRxiv2025

Evolutionary patterns and repeated adaptive strategies of deep-sea anemones

Sea anemones occupy the full depth of the oceans, yet their evolutionary patterns and adaptive strategies to the enigmatic deep sea have remained contentious and poorly resolved. Here, we assemble genomes (n = 13) and transcriptomes for 15 species collected between 432 and 6,000 m and integrate them with all publicly available actiniarian data. Phylogenomic analyses reveal a mosaic topology among deep-sea and shallow-water clades. Using a novel framework that contrasts convergent gene-loss patterns, we show that a large number of light-associated gene families-- including the complete circadian toolkit--were independently deleted after lineages entered the aphotic realm, whereas comparable loss in shallow taxa is negligible, providing decisive support for a shallow-water origin followed by multiple descents. Intriguingly, some deep-sea lineages further streamline energy budgets by recurrent loss or pseudogenisation of key meiotic genes (e.g., Meiosin, Ythdc2, Spo11, Rad21, Mlh3), indicating a shift towards asexual reproduction. Despite this extensive genomic erosion, deep-sea anemones exhibit sophisticated molecular tuning: specific amino-acid substitutions enhance protein stability and activity under deep-sea conditions, while selective expansions of gene families related to neural excitability, membrane systems, etc., likely mitigate the suppressive environmental effects on vital physiological processes. Enzyme activity assays in the yeast system confirm that the deep-sea variants exhibit superior activity and enhanced growth at 4{degrees}C. These results define a "loss-optimization-innovation" triad that underlies bathymetric adaptations and may apply to other deep-sea fauna worldwide.

evolutionary biology↗

bioRxiv2025

On-target toxicity limits the efficacy of CDK11 inhibition against cancers with 1p36 deletions

The cyclin-dependent kinase CDK11 is an understudied kinase that has been the subject of conflicting reports regarding its function in cancer. Here, we combine genetic and pharmacological approaches to demonstrate that CDK11 is a critical regulator of cancer cell survival that is required for RNA splicing and the expression of homologous recombination genes. Inhibition of CDK11 disrupts genome stability, promotes the retention of intronic sequences in mature mRNAs, and induces synthetic lethality with PARP inhibitors. Through integrative analysis of functional genomics datasets, we identify heterozygous deletions of chromosome 1p36 - which encompasses CDK11 and its activating cyclin CCNL2 - as a recurrent and predictive biomarker of sensitivity to CDK11 inhibition. To assess the therapeutic potential of CDK11, we develop MEL-495R, a selective and orally bioavailable CDK11 inhibitor. Additionally, we establish a genetically-engineered mouse model that allows us to differentiate between the on-target and off-target effects of CDK11 inhibitors in vivo. Using this platform, we demonstrate that MEL-495R induces widespread on-target toxicity, revealing a narrow therapeutic index. Together, these findings define CDK11 as a core cancer dependency, uncover a chromosomal deletion that sensitizes tumors to CDK11 inhibition, and provide a generalizable strategy for deconvolving drug efficacy and toxicity in vivo for novel oncology targets.

cancer biology↗

bioRxiv2025

Deep Learning Prediction of Intact N-/O-Glycopeptide Tandem Mass Spectra Enhances Glycoproteomics

Protein glycosylation, a post-translational modification involving the attachment of glycans to proteins, plays critical roles in numerous physiological and pathological cellular functions. Characterization of protein glycosylation is among one of the most challenging problems in proteomics due to the high heterogeneity of glycosites and glycan structures. Recently, deep learning has been adopted to predict N-glycopeptide tandem mass (MS/MS) spectra and exhibited a promising effect in N-glycoproteomics. However, current deep learning frameworks struggle to accurately predict O-glycopeptide MS/MS spectra due to the complexity of O-glycopeptides and the limited availability of training data. In this study, we introduce DeepGPO, a deep learning framework for the prediction of both N- and O-glycopeptide MS/MS spectra. The DeepGPO incorporates a Transformer module alongside two graph neural network (GNN) modules specifically designed for handling branched glycans. To address the issue of data scarcity in O-glycoproteomics datasets, various training methods are adopted in DeepGPO, such as the introduction of training weights for different MS/MS spectra and the adoption of pre-training strategies. DeepGPO exhibits accurate prediction of N- and O-glycopeptides MS/MS spectra. With the predicted MS/MS, glycosylation sites can be localized even in the absence of site-determining ions, for instance using higher-energy collisional dissociation (HCD) for the localization of O-glycosylation. We also explored the possibility of differentiating O-glycosites and N-glycosites using the predicted MS/MS spectra. DeepGPO primarily addresses mono-glycosylated peptides and is capable of handling doubly glycosylated peptides, but it currently cannot process peptides with three or more glycan modifications due to limited training data and increased spectral complexity. We anticipate that DeepGPO will inspire future advancements in glycoproteomics research.

bioinformatics↗

bioRxiv2025

In silico design and validation of high-affinity RNA aptamers for SARS-CoV-2 comparable to neutralizing antibodies

Nucleic acid aptamers hold promise for clinical applications, yet understanding their molecular binding mechanisms to target proteins and efficiently optimizing their binding affinities remain challenging. Here, we present CAAMO (Computer-Aided Aptamer Modeling and Optimization), which integrates in silico aptamer design with experimental validation to accelerate the development of aptamer-based RNA therapeutics. Starting from the sequence information of a reported RNA aptamer, Ta, for the SARS-CoV-2 spike protein, our CAAMO method first determines its binding mode with the spike proteins receptor binding domain (RBD) through a multi-strategy computational approach. We then optimize its binding affinity via structure-based rational design. Among the six designed candidates, five were experimentally verified and exhibited enhanced binding affinities compared to the original Ta sequence. Furthermore, we directly compared the binding properties of the RNA aptamers to neutralizing antibodies, and found that the designed aptamer TaG34C demonstrated a comparable binding affinity to the RBD compared to the representative neutralizing antibodies analyzed in this study. This highlights its potential as an alternative to existing COVID-19 antibodies. Our work provides a robust approach for the efficient design of a relatively large number of high-affinity aptamers with complicated topologies. This approach paves the way for the development of aptamer-based RNA diagnostics and therapeutics.

biophysics↗

bioRxiv2025

FoldBench: An All-atom Benchmark for Biomolecular Structure Prediction

Accurate prediction of biomolecular complex structures is fundamental for understanding biological processes and rational therapeutic design. Recent advances in deep learning methods, particularly all-atom structure prediction models, have significantly expanded their capabilities to include diverse biomolecular entities, such as proteins, nucleic acids, ligands, and ions. However, comprehensive benchmarks covering multiple interaction types and molecular diversity remain scarce, limiting fair and rigorous assessment of model performance and generalizability. To address this gap, we introduce FoldBench, an extensive benchmark dataset consisting of 1,522 biological assemblies categorized into nine distinct prediction tasks. Our evaluations reveal critical performance dependencies, showing that ligand docking accuracy notably diminishes as ligand similarity to the training set decreases, a pattern similarly observed in protein-protein interaction modeling. Furthermore, antibody-antigen predictions remain particularly challenging, with current methods exhibiting failure rates exceeding 50%. Among evaluated models, AlphaFold 3 consistently demonstrates superior accuracy across the majority of tasks. In summary, our results highlight significant advancements yet reveal persistent limitations within the field, providing crucial insights and benchmarks to inform future model development and refinement.

bioinformatics↗

bioRxiv2025

Dynamics of the formation of flat clathrin lattices in response to growth factor stimulus

Clathrin assemblies on the cell membrane are critical for endocytosis and signal transduction in cells. Specifically, {Omega}-shaped clathrin assemblies function as the coat of endocytic vesicles, while flat clathrin assemblies, also known as flat clathrin lattices, serve as signaling hubs for various signaling pathways. Multiple flat clathrin lattices exist on the cell membrane, and these lattices grow after epidermal growth factor stimulation (EGF) and then return to baseline. In this work, we used a particle-based model to simulate the assembly and disassembly of flat clathrin lattices to capture these dynamics. We found that the formation of flat clathrin lattices is highly dynamic, that is, cluster number, size and dwelling time often change even in the absence of any stimulus. Moreover, these key features are affected by adaptor protein 2 (AP-2) number, clathrin-clathrin binding rate, and clathrin diffusion coefficient. Specifically, an increase in AP-2 number leads to the transition from no cluster, short-lasting multiple small clusters, to a long-lasting single giant cluster. An increased clathrin-clathrin binding rate or decreased clathrin diffusion coefficient both result in an increased cluster number, reduced cluster size, and shortened dwelling time. Furthermore, we also predicted that under EGF stimulation, simultaneous changes in the AP-2 number, the clathrin-clathrin binding rate, and the clathrin diffusion coefficient can reproduce the experimentally observed trend of FCLs: an increase in cluster number and size in the first 30 minutes, followed by a decrease after 30 minutes. These findings reveal kinetic mechanisms underlying the formation of multiple FCLs and how EGF regulates FCL dynamics.

biophysics↗

bioRxiv2025

A rapid and efficient red-light-activated Cre recombinase system for genome engineering in mammalian cells and transgenic mice

The Cre-loxP recombination system enables precise genome engineering; however, existing photoactivatable Cre tools suffer from several limitations, including low DNA recombination efficiency, background activation, slow activation kinetics, and poor tissue penetration. Here, we present REDMAPCre, a red-light-controlled split-Cre system based on the {Delta}PhyA/FHY1 interaction. REDMAPCre enables rapid activation (1-second illumination) and achieves an 85-fold increase in recombination efficiency. We demonstrate its efficient regulation of DNA recombination in mammalian cells and mice, as well as its compatibility with other inducible recombinase systems for Boolean logic-gated DNA recombination. Using a single-vector adeno-associated virus (AAV) delivery system, we successfully induced REDMAPCre-mediated DNA recombination in mice. Furthermore, we generated a REDMAPCre transgenic mouse line and validated its efficient, light-dependent recombination across multiple organs. To explore its functional applications, REDMAPCre transgenic mice were crossed with the relative Cre-dependent reporter mice, enabling optogenetic induction of insulin resistance and hepatic lipid accumulation via Cre-dependent overexpression of ubiquitin-like with PHD and ring finger domains 1 (UHRF1), as well as targeted cell ablation through diphtheria toxin fragment A (DTA) expression. Collectively, REDMAPCre provides a powerful tool for achieving remote control of recombination and facilitating functional genetic studies in living systems.

synthetic biology↗

bioRxiv2025

Multimodal brain cell atlas across the adult macaque lifespan

High-throughput single-cell omics of non-human primate tissues present a remarkable opportunity to study primate brain aging. Here, we introduce a transcriptomic and chromatin accessibility landscape of 1,985,317 cells from eight brain regions of 13 cynomolgus female monkeys spanning adult lifespan including exceptionally old individuals up to 29-years old. This dataset uncovers dynamic molecular changes in critical brain functions such as synaptic communication and axon myelination, exhibiting a high degree of cell type and brain region specificity. We identify the multicellular networks of the pons and medulla as a previously unrecognized hotspot for aging. Furthermore, comparative analyses with human neurodegeneration datasets highlight both shared and distinct mechanisms contributing to aging and disease. In addition, we uncover transcription factors implicated in monkey brain aging and pinpoint aging-regulated loci linked to longevity and neurodegeneration. This spatiotemporal atlas will advance our understanding of primate brain aging and its broader implications for health and disease.

neuroscience↗