Biology subjects

Choi, H.

Publications and source records attributed to Choi, H..

At least 19 recordsLinked to original sources

bioRxiv2026

Signal Associa: hot tumors elicit field-spanning NK cell coordination linked to their recruitment

Cells coordinate through coupled dynamics, yet whether observed correlations reflect genuine coupling is rarely tested. Signal Associa is an open-source framework uniting six coupling methods with automated stationarization and surrogate testing. Benchmarking against six ground truth systems reveals a trichotomy of coupling regimes, each with a different best method: correlation for coupling carried by shared trends and cycles, Granger causality for linear stochastic coupling, and convergent cross-mapping for nonlinear coupling; agreement across methods identifies the regime from data. In 13 movies of natural killer (NK) cells across three colorectal tumor microenvironments, NK cells formed field-spanning coupling networks at a conserved rate; at matched exposure to tumor signal, NK cells around hot tumors were more globally integrated, and hot tumors with a more integrated NK network tended to attract more NK cells. In focal adhesions, stiffness strengthened vinculin-FAK coupling, most at protruding edges. Surrogates cut lagged-correlation false positives from 23-92% to about 5%.

systems biology↗

bioRxiv2026

fastACCORD enables ultrahigh-dimensional partial correlation modeling for multi-omic data integration

Gene co-expression networks reflect transcription factor-associated regulation together with epigenetic influences such as DNA methylation, chromatin states, and histone modifications. To distinguish gene-gene dependencies that persist after accounting for methylation covariation, large-scale statistical inference conditioning on hundreds of thousands of molecular features is necessary, but the task remains computationally intractable for conventional Gaussian graphical modelling approaches. Here we present fastACCORD, a scalable computational framework for ultrahigh-dimensional partial correlation modeling. fastACCORD combines row-separable optimization, {ell}2 stabilization, and a semismooth Newton solver in a PyTorch implementation for CPU and CUDA-enabled GPU hardware. We applied it to matched transcriptomic and methylomic profiles from 16 TCGA cancer types and obtained joint networks containing >300,000 molecular features per cancer. The resulting multi-omic networks revealed cancer-specific methylation-expression dependencies, including recurrent methylation-associated expression repression of metabolic genes. Methylation-adjusted gene co-expression networks were sparser than networks estimated from mRNA data alone, but more enriched for ChIP-seq-supported TF-target relationships and curated co-regulon annotations. TF-target subnetworks further revealed cancer-specific architectures consistent with lineage identity, oncofetal reactivation, and tumor microenvironment-associated programs. Together, these analyses establish fastACCORD as a practical framework for ultrahigh-dimensional multi-omic partial correlation modeling and demonstrate how joint modeling of transcriptomic and epigenomic measurements can refine the interpretation of gene co-expression networks.

bioinformatics↗

bioRxiv2026

Vritra: gene-specific reference construction for species-resolved functional profiling of metagenomic and metatranscriptomic data

Species-resolved profiling of microbial functional genes is important for linking microbial community composition to biological function, but existing functional profiling approaches are not designed to systematically define user-specified genes and resolve their contributing species. We developed Vritra (Versatile gene-guided Reads-identification with Impartial Taxonomic Refinement and Assignment), a framework for constructing gene-specific reference databases for metagenomic and metatranscriptomic data. Vritra expands and refines the UniRef-based sequence space for user-specified target genes using sequence-similarity network connectivity and functional annotations, retains related homologs as decoys to reduce assignment ambiguity, and links the resulting sequences to standardized microbial taxonomy. Across genes involved in oxalate, urate, and bile acid metabolism, Vritra recovered >97% of sequences represented by established annotation resources for most evaluated genes while substantially expanding the represented sequence space. In real microbiome datasets, the expanded references increased recovery of target-gene reads by up to threefold for poorly annotated genes while maintaining high sequence identity. Application to population-based and publicly available microbiome datasets enabled species-resolved profiling of functional genes and revealed gene-specific associations with microbial taxa, dietary factors, and disease-related phenotypes. Vritra provides a scalable framework for translating continuously expanding sequence resources into gene-specific, species-resolved references for microbiome studies.

bioinformatics↗

bioRxiv2026

Developmental Dynamics of Naturalistic Social Behavior Revealed by Longitudinal Multi-Animal Tracking

Early-life social experiences with parents and littermates are critical for the development of social behavior and cognition in social species. Yet, how naturalistic social interactions evolve across development remains poorly understood, because reliable tracking of multiple freely interacting animals is challenged by frequent occlusion and body overlap. To address this challenge, we developed Move-Altogether (MovAl), a multi-animal pose estimation pipeline integrating video object segmentation and contour-guided preprocessing that improved identity stability and pose accuracy compared with widely used methods. Using MovAl-derived pose sequences, we established a denoising autoencoder (DAE)-based framework to map longitudinal home-cage behavior within a common three-dimensional space defined by inter-animal spacing, social orientation, and interaction dynamics. Within this space, control mice showed progressive reorganization of group behavior from 3 to 8 weeks of age, establishing a developmental reference for naturalistic social organization. Against this reference, prenatal valproic acid (VPA) exposure produced prominent alterations in social behavior organization at 3-5 weeks of age, demonstrating that the consequences of neurodevelopmental perturbation can be detected through changes in naturalistic group behavior among littermates. Extending the analysis to preweaning mother-pup interactions revealed increased maternal movement and reduced mother-pup proximity in the VPA condition, indicating alterations in the early social environment that preceded postweaning behavioral differences. These findings suggest that quantitative characterization of early social interactions may provide a means to identify early behavioral alterations associated with atypical neurodevelopment. Together, the MovAl-DAE framework enables longitudinal quantification of naturalistic social behavior, defining its developmental organization and revealing alterations associated with neurodevelopmental perturbation.

neuroscience↗

bioRxiv2026

De novo design of allosterically controlled enzymes

The ability of enzymes to sense signals and respond by changing their structure and activity underlies cellular processes from signaling to metabolic control. While there have been recent advances in the de novo design of enzymes and conformationally switching proteins, combining these to achieve allosteric regulation of enzymatic activity in a fully designed system remains an outstanding challenge. Here, we show that denoising diffusion models enable the design of compact de novo enzymes whose activity can be allosterically activated or repressed by designed protein effectors. Our results establish a general route to allosteric control over a wide range of catalytic and other protein functions.

biochemistry↗

bioRxiv2026

Evaluation of the Translational Readiness of Pluripotent Stem Cell-Derived Vascular Cell Therapy for Limb Ischemia: A Systematic Review and Meta-analysis

Background: For the first time, pluripotent stem cell (PSC)-derived endothelial cells were administered to a human for peripheral artery disease (PAD), in August 2026. This translation is based on a large preclinical literature claiming that donor cells build blood vessels in animal models of limb ischemia, but whether it supports that claim has not been assessed systematically. Methods: In this systematic review and meta-analysis, we searched MEDLINE, Web of Science, Europe PMC, and Embase to August 2026 for studies of PSC-derived vascular cells in animal models of limb ischemia with an acellular control. Limb perfusion at each experiment's primary timepoint was pooled as Hedges' g in a three-level random-effects model with cluster-robust variance. Donor-cell fate and a seven-level ordinal of vascular contribution were graded for every study. This meta-analysis was registered on PROSPERO (CRD420261465308). Results: Sixty-eight studies in 69 reports met the criteria; 51 contributed 114 comparisons at primary timepoints. Cell therapy increased perfusion (Hedges' g 2.26, 95% CI 1.72-2.79; P=4.1x10-11; I2=87.5%; 95% prediction interval -1.47 to 5.98). No prespecified moderator survived Holm-Bonferroni adjustment, including the donor-cell fate grade (P=0.30). A donor cell was resolved in a vessel wall in 35 studies, and flow through such a vessel in 7. Small-study effects were strong (Egger t=6.25, P=9x10-8) but were not reproduced by a sample-size-based test (P=0.80); trim-and-fill moved the estimate to 1.15. On the natural scale, treated limbs recovered about twice the control perfusion (ratio of means 1.96, 95% CI 1.66-2.33). Limb preservation favored cell therapy in 11 studies with countable events (risk ratio 4.88, 95% CI 2.28-10.45), but 43 of 68 studies reported no functional outcome, and only 22 comparisons from 8 studies were both randomized and blindly assessed. In a post hoc analysis that did not survive multiplicity adjustment, effects were largest in studies whose images could not resolve their incorporation claims (g 3.23) versus those that resolved incorporation (g 2.33). Conclusions: PSC-derived vascular cell therapy improved limb perfusion in animal models, consistently across every sensitivity analysis, although the magnitude is uncertain given heterogeneity and small-study effects. Benefit was not associated with the degree of donor-cell incorporation across studies and was largest where incorporation was least resolvable, a pattern more consistent with reporting and measurement bias than with a true mechanistic effect. The first rigorous, blinded test of that benefit may come not from animals but from the patients now receiving these cells.

cell biology↗

bioRxiv2026

AnnFlux: object-conditioned neural stochastic differential equations for single-cell perturbation dynamics

Single-cell perturbation profiling measures responses to genetic and chemical interventions, yet most models learn a static map, ignoring how populations move over time and how perturbations combine. AnnFlux, an object-conditioned stochastic differential equation, learns a drift field in latent cell-state space. Conditioning on the perturbing object makes the field queryable one object at a time, yielding per-object drifts comparable across genes and drugs. By learning a drift field tailored to each perturbation context, it interpolates a held-out timepoint in an epithelial-mesenchymal transition time course and predicts unseen perturbations. Beyond point estimates, AnnFlux improves distributional fidelity and predicts responses to held-out perturbation combinations. An IFN-response signature predicted by AnnFlux was associated with TLS proximity in an independent pan-cancer spatial atlas. This framework maps perturbation-driven cell-state evolution as continuous trajectories and represents unseen perturbations using prior-knowledge embeddings.

bioinformatics↗

bioRxiv2026

EcoXAI: Autonomous Agentic Ecosystem for Explainable Artificial Intelligence and Biomedical Discovery

Motivation: As biomedical datasets and knowledge graphs continue to grow in size, complexity, and heterogeneity, navigating and extracting actionable insights from them presents a major bottleneck for researchers. There is a clear need for autonomous analytical solutions that can utilize recent advancements in agentic AI such as agent harnessing and loop engineering without introducing hallucination or workflow fragmentation. Researchers, regardless of technical expertise, need tools that streamline complex data analysis and deliver meaningful, actionable insights grounded in both data and established biomedical knowledge. EcoXAI addresses this by introducing a modular, customizable, containerized multi-agent system that structures analysis into explicit pipeline execution stages, lowering the computational barrier for clinical and translational researchers. Result: EcoXAI replaces monolithic AI text interfaces with an autonomous execution-driven framework with specialized bioinformatics agents for delivering proactive, data-driven insights grounded in established biological knowledge. Unlike purely LLM-driven or less integrated AI solutions prone to hallucinations or biologically implausible outcomes, EcoXAI's multi-agent framework, which leverages modern agentic management and explicit knowledge graph integration, provides greater transparency and verifiability in its reasoning. In our use case in drug repurposing for Alzheimer's Disease, EcoXAI evaluated 103 drug candidates and identified 79 novel candidates whose predictive models exceeded a randomized baseline, including the CCR5 antagonist Maraviroc, whose generated hypothesis was subsequently supported by the literature. These results demonstrate the potential of knowledge graph-grounded AI agents to accelerate hypothesis-driven biomedical research.

bioinformatics↗

bioRxiv2026

Screening Lipid Nanoparticles through Structure-Ratio Alignment

Lipid Nanoparticles (LNPs) are widely used as delivery systems for nucleic acid therapeutics, where transfection efficiency is determined by both the identities of constituent lipid components and their composition ratios. While prior studies have focused on learning molecular representations for individual components, modeling how multiple components and their ratios jointly influence LNP performance remains underexplored. In this work, we propose STRATA, a framework that models molecule interaction between LNP components, which is known to contribute to LNP transfection efficiency. Our approach is built on two complementary views: (1) a ratio-centric view that captures interaction patterns induced by composition ratios through a transformer with a Ratio-induced Positional Embedding, and (2) a molecule-centric view that incorporates interaction-induced effects into structure-based molecule embeddings. By jointly training and aligning these views, our model integrates molecular structure and composition ratio within a unified framework that captures interaction-driven effects. Experiments demonstrate that our method improves prediction accuracy and generalization to unseen molecules and ratios, highlighting the effectiveness of our approach. Implementation code will be available after acceptance.

biochemistry↗

bioRxiv2026

L-5--glutamine PET of Breast Cancer: Kinetic Analysis in Mouse Models to Evaluate Glutamine Metabolism

BackgroundGlutamine addiction is a hallmark of aggressive tumors, yet glutaminase (GLS1) inhibitor CB-839 showed disappointing anti-tumor efficacy in clinical trials. L-5-[{superscript 1}{superscript 1}C]-glutamine ([{superscript 1}{superscript 1}C]glutamine) PET enables non-invasive assessment of glutamine metabolism in vivo, providing a tool to test mechanistic hypotheses, and identify tumors likely to respond to GLS1 inhibition: focusing on compartmentation of GLS1-derived glutamate, CB-839 impact on flux, and reciprocal glutamine synthesis. MethodsGlutaminolytic TNBC (HCC1806) and poorly glutaminolytic ER+ (MCF-7) xenograft mice with or without CB-839, underwent dynamic [11C]glutamine PET. HPLC quantified fractional radioactivity of [11C]glutamine, soluble metabolites ([11C]glutamate, [11C]CO2), and macromolecule-incorporated metabolites from blood and tumor. A four-tissue compartment model characterized GLS1 activity (kGLS) and flux, glutamine synthetase activity (kGS), and subcellular glutamate distribution by comparing single vs. dual glutamate pool models. Averaged tumor curves and HPLC-derived tumor metabolites were fit. Monte Carlo simulations assessed parameter estimation performance. ResultsThe single glutamate pool model showed high correlations between kGLS and other parameters, yielding inflated kGLS estimates. The dual glutamate pool model reduced correlations, improved kGLS recovery, and yielded subcellular glutamate distributions consistent with in vitro measurements. In TNBC, kGLS was 3-fold higher than ER+ tumors (non-overlapping 95% CI) with glutamate concentrated in the mitochondrial compartment. CB-839 reduced kGLS in TNBC and depleted mitochondrial glutamate (non-overlapping 95% CI), though glutaminolytic flux showed no distinguishable change. ER+ tumors showed higher kGS compared to TNBC. Conclusion[11C]glutamine PET kinetic analysis reveals distinct glutamine metabolic phenotypes in breast cancer subtypes. Preserved glutaminolytic flux and cytosolic glutamate in TNBC provide mechanistic hypotheses for clinical failure of GLS1 inhibitors, informing ongoing studies.

bioengineering↗

bioRxiv2026

Spatial Transcriptomics Reveals a Conserved Border Niche and Etiology-Associated Immune Rewiring in Hepatocellular Carcinoma

Background and AimsThe tumor-stroma interface in hepatocellular carcinoma (HCC) harbors critical intercellular interactions that shape immune evasion and treatment response, yet its spatial architecture remains poorly characterized across etiologies. Whether hepatitis B virus (HBV)-related and non-B non-C (NBNC) HCC share conserved border niche features or exhibit etiology-specific microenvironment programs is unknown. We aimed to spatially resolve the tumor boundary ecosystem and identify etiology-associated signaling networks with translational relevance. Approach and ResultsWe performed 10x Visium spatial transcriptomics on 11 HCC specimens (7 HBV, 4 NBNC) and applied a machine-learning pipeline integrating CancerFinder and SpaceFlow to define tumor, boundary, and stromal domains. Across etiologies, the boundary zone showed a recurrent desmoplastic niche characterized by cancer-associated fibroblast, tumor-associated macrophage, and tumor endothelial cell accumulation with collagen-integrin extracellular matrix remodeling, including COL1A1-ITGA11 and COL4A1-ITGAV. Etiology-associated differences were observed in the organization of border-zone signaling programs. In representative HBV-related sections, CCL19-CCR7 signaling showed a comparatively restricted, endothelial-skewed topology, whereas representative NBNC sections showed broader inflammatory ligand-receptor networks with elevated NF-kB-associated pathway activity. ConclusionsThe HCC tumor-stroma border harbors a recurrent desmoplastic niche upon which etiology-associated immune regulatory programs may be superimposed. These findings generate spatial hypotheses relevant to etiology-informed biomarker development and future therapeutic stratification.

cancer biology↗

bioRxiv2026

Spatial tumor microenvironmental architecture of chemoradiotherapy-resistant residual esophageal squamous cell carcinoma

PurposeResidual ESCC after neoadjuvant CCRT reflects incomplete treatment response and carries a high risk of recurrence. We sought to define the spatial tumor microenvironmental features of CCRT-resistant residual ESCC -- using tumor regression grade (TRG) 2-3 tumors as a model of poor pathologic response -- with mechanistic refinement at single-cell resolution and outcome assessment in internal and external cohorts. Experimental DesignWe profiled post-CCRT ESCC tissue microarray (TMA) cores by Visium FFPE whole-transcriptome spatial transcriptomics and orthogonal Xenium single-cell-resolution in situ profiling on serial sections from the same TMA blocks. Spot-level cell-type composition was inferred by CellDART deconvolution against a published ESCC single-cell RNA sequencing (scRNAseq). Local malignant-cell-enriched regions were defined by CancerFinder. We additionally re-analyzed the scRNAseq dataset to characterize SPP1 and CXCL5 macrophage states and their ligand-receptor signaling using CellChat. Outcome associations were evaluated in the SNUH cohort and externally tested in the TCGA ESCC cohort. ResultsTRG 2-3 residual tumors exhibited effector immune-cell exclusion from malignant-cell-enriched regions, SPP1/CXCL5 macrophage accumulation, microvascular rarefaction, and proliferative-metabolic reprogramming. Single-cell re-analysis confirmed that CXCL5 macrophages constitute a transcriptional subset of the broader SPP1 macrophage population. CellChat showed that SPP1 macrophages dominantly signal through SPP1-CD44 and SPP1-integrin axes to stromal and epithelial targets, and additionally engage immunosuppressive NECTIN2-TIGIT, CD86-CTLA4, and LGALS9-HAVCR2 programs with CD8 T cells, providing a mechanistic context for local immune exclusion. Visium LIANA and Xenium distance-gradient profiling localized SPP1-associated signaling preferentially to tumor cells and CAFs. Higher SPP1 expression and lower endothelial abundance were associated with shorter disease-free survival in the SNUH cohort. Higher SPP1 expression was also associated with shorter disease-free survival in the independent TCGA ESCC cohort. ConclusionsCCRT-resistant residual ESCC is characterized by a spatially organized tumor microenvironmental niche centered on SPP1-associated macrophage programs and microvascular rarefaction. These spatially resolved findings identify candidate macrophage- and vasculature-targeted axes for overcoming treatment resistance. Translational RelevancePatients with esophageal squamous cell carcinoma (ESCC) who harbor residual disease after neoadjuvant chemoradiotherapy (CCRT) remain at high risk of recurrence, yet the spatial biology of this resistant residual state has been poorly defined. Here, we combine Visium whole-transcriptome and Xenium single-cell-resolution spatial transcriptomics with single-cell RNA-seq re-analysis and external TCGA context to define the tumor microenvironmental architecture of CCRT-resistant residual ESCC. The resistant niche is characterized by effector immune-cell exclusion from malignant-cell-enriched regions, accumulation of SPP1/CXCL5 macrophage programs that signal to tumor cells and cancer-associated fibroblasts through SPP1-CD44 and SPP1-integrin axes, microvascular rarefaction, and proliferative-metabolic reprogramming. These findings define a coordinated spatial tumor microenvironmental signature of CCRT-resistant residual ESCC and nominate macrophage-tumor/stromal interactions and vascular injury as biologic axes that may help guide future strategies to overcome treatment resistance.

cancer biology↗

bioRxiv2026

Rank dependency of rescaled pruning in recurrent neural networks

Throughout development and maturity, neural circuits undergo massive synaptic pruning, yielding highly sparse connectivity while preserving robust population-level computations. These population dynamics are often low-dimensional, allowing task-related computations to be formalized as trajectories within latent subspaces. How such low-dimensional dynamics are preserved amid widespread network sparsification remains unclear. Here, we investigate how different synaptic pruning rules shape low-dimensional dynamics and task performance in recurrent neural networks (RNNs). Moving beyond previous approaches focused on random sparsification of low-rank networks or networks with strictly constrained structures, we systematically evaluate how biologically motivated pruning rules interact with a networks underlying rank. We show that post-pruning dynamics and task performance depend critically on the networks initial rank due to distinct eigenspectral characteristics across rank regimes. Combining mathematical analysis with simulations, we demonstrate that pruning with synaptic rescaling preserves low-dimensional dynamics with minimal distortion in low-rank RNNs, but degrades in the high-rank regime. Our findings suggest that low-rank structure, combined with homeostatic synaptic rescaling, is essential for maintaining stable, low-dimensional dynamics in sparse networks. Author summaryIn biological neural networks, population activity is fundamentally shaped by synaptic connection strengths. During development, many of these connections are eliminated through synaptic pruning--a process thought to minimize metabolic costs and optimize computational efficiency by promoting network sparsity. However, how networks preserve their core functionalities after losing a vast numbers of connections remains an open question. Here, we combine mathematical analysis and simulations to examine how various pruning strategies affect network dynamics and computation in both low- and high-rank recurrent neural networks (RNNs). We show that uncompensated connection removal drastically alters network activity. However, implementing a homeostatic rescaling that strengthens remaining connections preserves original dynamics exclusively in low-rank networks, where connectivity is governed by a few dominant structural patterns. In contrast, pruning with homeostatic rescaling fails to maintain dynamics in high-rank networks. Our findings suggest that low-rank connectivity coupled with network homeostasis is crucial for maintaining brain function throughout significant developmental pruning.

neuroscience↗

bioRxiv2026

Third Trimester-Equivalent Alcohol Exposure Reduces Neurons in Males and Increases Vglut2⁺ Neurons with Reduced Intrinsic Bursting in Females in The Murine Dorsal Subiculum

Individuals with Fetal Alcohol Spectrum Disorders (FASDs) show reduced subicular volume, and preclinical studies compliment this by demonstrating that third-trimester-equivalent ethanol exposure induced apoptosis in corticolimbic regions, including the subiculum. The subiculum mediates hippocampal-cortical communication critical for long-term memory consolidation. Within the distal dorsal subiculum, a population of bursting neurons uniquely express VGLUT2 and they play a key role in memory processing. We hypothesized that third-trimester-equivalent ethanol exposure would reduce neuronal and VGLUT2+ cell density in the dorsal subiculum and reduce the excitability of bursting neurons, providing a mechanism for long-term memory impairments observed in FASD. To test this, postnatal day (P)7 mice received a subcutaneous injection of ethanol and long-term effects were assessed in adolescence (P35-62). Using transgenic mice with fluorescently labeled VGLUT2+ neurons, and immunohistochemistry we observed a significant reduction in neuronal density in males and an increase in VGLUT2+ cell density in females. Using whole-cell patch clamp electrophysiology, we observed a reduction in action potentials per burst in both sexes. Additionally, females showed reduced overall excitability, and a subset of neurons exhibited a shift to regular spiking. These findings suggest that development ethanol exposure disrupts subicular output by impairing burst firing, potentially weaking hippocampal-cortical communication and contributing to the cognitive deficits associated with FASD. HighlightsO_LIThird-trimester ethanol targets VGLUT2+ neurons in the dorsal subiculum C_LIO_LIEthanol reduced neuronal density in male dorsal subiculum C_LIO_LIEthanol increases VGLUT2+ cell density in females C_LIO_LIEthanol reduces action potential per burst in both sexes C_LIO_LIFemales show reduced excitability and loss of bursting in some cells C_LI

neuroscience↗

bioRxiv2026

Telomere-to-telomere, accurate, and gapless genome assembly (TTAGGA) of the Korean Jindo dog with a single-contig Y chromosome

Complete canine reference genomes are essential for studies of structural variation, sex-chromosome evolution, and breed-specific architecture, yet existing references remain incomplete on the Y chromosome and retain internal gaps across multiple chromosomes. Here, we introduce TTAGGA (Telomere-to-Telomere, Accurate, Gapless Genome Assembly), a stricter completeness standard requiring chromosomes assembled end-to-end with zero internal gaps and Merqury consensus QV [≥] 50, and present Jindo1-G-TTAGGA, the first canine assembly to meet this standard, achieved under a stringent QV [≥] 60 threshold. From 813 Gb ([~]340x coverage) of multi-platform data (PacBio HiFi [~]150x, ONT ultra-long [~]103x, parental Illumina [~]40x per parent) generated from a male Korean Jindo dog, trio binning with hifiasm produced two haplotype-resolved assemblies of 2,441.6 Mb (Hap1, maternal, chrX-carrying) and 2,340.5 Mb (Hap2, paternal, chrY-carrying). Both haplotypes are gap-free at every internal position, with canonical telomeric repeats verified at both ends of all 39 chromosomes (tidk), Merqury consensus QV of 78.0 (Hap1) and 76.8 (Hap2), trio switch-error rates below 0.13%, BUSCO completeness of 99.3% (Hap1) and 96.4% (Hap2; the lower value reflects absent X-linked orthologues in the Y-bearing haplotype), and Genome Continuity Index values of 98.2 (Hap1) and 94.7 (Hap2). Hap2 carries a single 21,255,890 bp gap-free Y chromosome with TTAGGG telomeric repeats at the q-arm terminus and an acrocentric satellite-rich p-arm, representing a 5.4-fold increase over the 3.94 Mb chrY of ROS_Cfam_1.0 and adding approximately 14 Mb of newly resolved Y-linked sequence; this corresponds to roughly 79% of the cytogenetically estimated 27 Mb full-length canine chrY. Jindo1-G-TTAGGA provides a chromosome-scale, haplotype-resolved, gap-free canine reference for studies of canine structural variation, sex-chromosome evolution, and canid phylogenomics.

genomics↗

bioRxiv2026

TIR-like NADases act in bacterial immunity and the RNA vault

Across all domains of life, organisms exploit NAD+ metabolism as a central line of defense against invading pathogens. Here, we show that domain of unknown function 4062 (DUF4062) is a widespread family of TIR-like NADases that hydrolyze NAD+ to ADP-ribose and nicotinamide. In bacteria, DUF4062 homologs form a previously unrecognized antiphage defense system, which we name Swaro[z]yc, that assembles with the phage portal into a supramolecular NADase complex to induce abortive infection. In eukaryotes, DUF4062 is found in TEP1, which we demonstrate functions as an active NADase within the RNA vault, an enigmatic organelle-like structure. Single-particle cryo-electron microscopy reveals ADP-ribose bound within the shoulder of both reconstituted and human brain vaults, while cryo-electron tomography positions TEP1 along the central axis at the shoulder. Thus, TEP1, like bacterial Swaro[z]yc, functions by depleting NAD+, providing new insight into the long-standing mystery of vault function.

biochemistry↗

bioRxiv2026

High throughput single-cell RNA sequencing of intact adult cardiomyocytes and non-myocytes using a split-pool approach

MOTIVATIONAdult cardiomyocytes are difficult to profile by whole-cell single-cell RNA sequencing because of their large size and fragility, which make them poorly compatible with standard workflows. Current approaches for adult cardiomyocyte transcriptomics often require a trade-off between data quality and throughput, thus, studies instead rely heavily on sequencing of nuclei alone. Therefore, we set out to develop a high-quality and scalable workflow for adult heart cells using in-cell ligation and split-pool barcoding strategies to address this methodological gap. This workflow may be further generalisable to other large cell types or samples containing cell populations with highly unequal RNA content. SUMMARYAdult cardiomyocytes are difficult to profile by whole-cell single-cell RNA sequencing (scRNA-seq). Here, we developed a high-quality and scalable workflow for adult heart cells using in-cell ligation and split-pool barcoding. We identified per-cell RNA content as a significant variable that must be accounted for. Separation of cardiomyocytes (large cells) and non-cardiomyocytes (small cells) before library construction, and allocation of deeper sequencing to cardiomyocytes, produced high-quality whole-cell datasets for both compartments. Compared with single-nucleus RNA sequencing, whole-cell cardiomyocyte profiling better recovered metabolic, mitochondrial, cytoplasmic translational, and contractile gene programs. This workflow provides a practical method for scalable, high-quality cardiomyocyte whole-cell scRNA-seq and offers general strategies for other large cell types or samples containing cell populations with highly unequal RNA content.

cell biology↗

bioRxiv2026

Distinct Spatial Programs of Response versus Resistance in Non-Small Cell Lung Cancer after Neoadjuvant Chemoimmunotherapy

BackgroundNeoadjuvant chemoimmunotherapy (nCIT) has become a standard treatment for locally advanced resectable non-small cell lung cancer (NSCLC), yet the spatial biology underlying treatment resistance remains poorly understood. We used spatial transcriptomics to define the microenvironmental architecture of residual cancers in patients who did not achieve major pathologic response (non-MPR) compared with those who did (MPR). MethodsSpatial transcriptomics was performed on 10 formalin-fixed paraffin-embedded (FFPE) tumor blocks (5 MPR, 5 non-MPR) obtained from 8 patients treated with nCIT. A deep learning algorithm was applied to detect viable residual cancer spots from treatment-induced fibrosis and necrosis. Spatial deconvolution, distance modeling, ligand-receptor analysis, and functional pathway scoring were integrated to characterize niche-specific programs. ResultsMPR cancer core displayed an immune-permissive remodeling environment with deep infiltration of cytotoxic CD8+ T cells, mature dendritic cells (LAMP3+, CCR7+), and active efferocytosis signaling (APOE-TREM2), alongside robust MHC class II expression. Non-MPR cancer core, by contrast, exhibited spatial immune exclusion: a dense fibroblast barrier reinforced by TIMP1-CD63 signaling and Treg-enriched boundaries physically restricted effector T cell access to the cancer core. Residual cancer cells in non-MPR samples maintained active cell cycling and independently upregulated cytochrome P450-mediated drug detoxification and DNA damage response pathways without inducing MHC class II expression -- effectively decoupling intrinsic survival from immune recognition. The non-MPR core also showed a hyper-metabolic profile, including elevated glutathione metabolism consistent with antioxidant buffering against chemotherapy-induced oxidative stress. TROP2 was broadly expressed across the non-MPR cancer core and co-localized with DNA damage response and nuclear factor erythroid 2-related factor 2 resistance signatures. ConclusionsResidual cancer cores in non-MPR tumors appear to represent evolved resistant niches sustained by structural immune exclusion, metabolic rewiring, and DNA repair proficiency. These findings highlight the spatial co-localization of epithelial anchors, such as TROP2, with intrinsic resistance pathways, providing a structural rationale for developing novel precision therapeutic strategies to bypass stromal barriers and overcome the cancer cores intrinsic repair capacity.

cancer biology↗