Biology subjects

Mao, Y.

Publications and source records attributed to Mao, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Mesoscale Soft Robotics for Mechanically Perturbing and Functionally Monitoring Responses in Human Organoids

Human organoids represent promising models for studies of significance to the biology and medical communities. Of the existing approaches for monitoring organoids, none offers the ability to apply programmable mechanical forces while simultaneously recording multi-modal physiological responses, of relevance to phenomena spanning from traumatic brain injuries to cardiac rhythm disorders. Here, we present a mesoscale soft robotic organoid interface that enables programmable delivery of forces to organoids of diverse shapes, and to map electrophysiological activity and mechanical responses. The platform combines actuation elements with integrated sensors for quantitative measurement and control. Studies using this technology reveal that spheroidal cortical organoids exhibit distinct responses to mechanical trauma, including silencing, recovery, and changes in neuronal firing patterns. Additional experiments on cardiac ring tissues demonstrate that sustained stretching induces beat-to-beat rhythm variability and altered conduction. The results establish a framework for investigating force-triggered transitions between physiological and disease-like states in human tissue models.

bioengineering↗

bioRxiv2026

Decoding super-enhancer regulatory grammar and pathogenic gain-of-function variants directly from DNA sequence

Super-enhancers (SEs) drive cell-identity gene expression, yet their identification relies on epigenomic profiling (e.g., H3K27ac ChIP-seq), precluding discovery in unprofiled cellular states and leaving their underlying sequence grammar unknown. Here, we present Borzoi-SE, a deep learning framework built upon the genomic transformer Borzoi that formulates SE discovery as hierarchical, cell-type-resolved genomic object detection directly from long-range sequence across 90 human lineages. Base-resolution attribution recovers lineage-defining master transcription factors across cell types. Within SEs shared across lineages, it reveals lineage-dependent motif usage, suggesting that the same regulatory regions can support distinct cell-type-specific programs. Using in silico ablation, Borzoi-SE decoded the functional hierarchy of the {beta}-globin super-enhancer, prioritizing hypersensitive site 2 (HS2) as the dominant constituent, which we experimentally verified via CRISPR interference. Trained without variant-effect labels, Borzoi-SE identified gain-of-super-enhancer variants in different tissues. At the CHRM2 locus, a single-nucleotide variant created a de novo glucocorticoid receptor (GR) motif that recruited activated GR and potentiated adjacent MEF2 regulatory syntax, nucleating a cardiac super-enhancer. Orthogonal multi-omics and population-genetic evidence linked this variant to increased CHRM2 expression and variation in resting heart rate and PR-interval duration. Borzoi-SE establishes a general framework for decoding SE regulatory grammar and prioritizing causal non-coding variants directly from sequence.

genomics↗

bioRxiv2026

Cross-species discovery of large structural variants reveals distinct evolutionary dynamics in primates

Large-scale structural variants (SVs) are major drivers of genome evolution and disease susceptibility, shaping lineage-specific gene content, genome architecture, and phenotypic diversity. Yet, their systematic detection across divergent species has been hindered by complex rearrangements and reference bias, limiting our understanding of their evolutionary impact. Here we present LGvar, a divergence-aware tool for identifying SVs in population-scale and cross-species genome assemblies, enabling up to a 7-fold increase in the detection of large deletions, insertions, inversions and complex rearrangements ([≥]10 kbp). Application of LGvar uncovers 112 previously undetected large SVs overlooked by conventional methods and quantifies the effect of evolutionary divergence on SV discovery across primate euchromatic genomes, revealing an approximately 30% overall decline in detection sensitivity with increasing phylogenetic distance. Mapping SVs from comparable syntenic regions onto the primate phylogeny shows that large deletions ([≥]10 kbp) accumulate approximately two-fold faster than insertions and eight-fold faster than inversions, in contrast to the dynamics of smaller SVs (<10 kbp). Integrating structurally divergent regions with the synteny region analysis reveals over 606 previously unreported gene gains and losses in great apes and refined the totals to 134 human-lineage-specific and 51 great-ape-lineage-specific protein coding genes. These results suggest that large SVs follow distinct evolutionary trajectories, with potential selective constraints shaping genome structure. Our study establishes a generalizable strategy for cross-species SV discovery and provides a high-resolution view of how large SVs contribute to genome evolution in primates.

genomics↗

bioRxiv2026

The extracellular matrix regulates tissue mechanics to enable cyclic lymph node remodelling and sustained immunity

Tissue shape and function are defined by the mechanical interactions of cellular and extracellular components. Lymph nodes cyclically remodel in response to immune challenges whilst preserving essential tissue architecture, comprised of a stromal fibroblastic reticular cell (FRC) network and extracellular matrix (ECM) it ensheaths. We experimentally quantified the contribution of ECM to the viscoelastic properties of the FRC network to parameterise an in silico model exploring factors affecting the FRC network's adaptation to lymph node expansion. The balance between tissue pressure, FRC contractility, and ECM stiffness permit robust tissue remodelling, while maintaining physiological geometries. Local perturbation of ECM stiffness or FRC contractility disrupts force distribution and impacts FRC proliferation and tissue expansion. Spatially dispersed perturbations exert higher impact on tissue remodelling than equivalent localised perturbations, with effects propagating across the network. The lymph node provides a system for studying the integration of cellular and extracellular mechanics during dramatic tissue remodelling.

biophysics↗

bioRxiv2026

Why is the purse string not enough?

Wound repair is an important mechanism to preserve tissue integrity in organisms after injury. However, why different tissues exhibit different mechanisms to repair wounds is a long-standing question that remains unanswered. In this work, we theoretically explore the role of the purse string, an actomyosin contractile cable used by tissues to close small wounds. Does the tissue 3D geometry influence the efficiency of the purse string in driving wound closure? Using a 3D biophysical model, we study in silico tissues with the same cell volumes but different aspect ratios, ranging from squamous to thick and tall tissues. The model predicts that taller cells are easily deformed by the purse string. In contrast, very squamous cells require a very strong purse string that might demand additional cellular mechanisms to close the gap. These findings establish a theoretical framework to predict the optimal biophysical mechanisms of wound healing in different tissues. Graphical abstractCells of different aspect ratios can be observed in a range of organisms with different function and mechanics. The wound healing efficiency of the purse string increases with the cell aspect ratio in our theoretical exploration. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/743165v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@874e22org.highwire.dtl.DTLVardef@11aabe3org.highwire.dtl.DTLVardef@af5e3org.highwire.dtl.DTLVardef@195197d_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

Heart rate dynamics embed a shared representation of individual brain organization and cognitive function

Idiosyncratic brain functional organization shapes intricate cardiac dynamics through central-peripheral autonomic interactions, yet a comprehensive mapping between multi-scale heart rate dynamics and whole-brain functional architecture remains lacking. Here, combining highly comparative time-series analysis with multi-modal neuroimaging and intracranial electrophysiology, we establish heart rate dynamics as a physiological fingerprint that maps onto whole-brain functional architecture. Partial least squares analysis revealed a generalizable latent axis linking reduced heart rate temporal complexity and elevated micro-scale predictability to heightened resting-state functional connectivity across default mode, salience, and sensorimotor networks. This covariance aligns spatially with serotonergic, noradrenergic, and cholinergic neuromodulatory gradients, persists across physiological confound controls and cross-session validations, derives support from human intracranial electrophysiological recordings, and extends to active cognitive states. Furthermore, brain-covarying heart rate signatures underpin the predictive capacity of heart rate dynamics for individual fluid and crystallized intelligence, demonstrating a shared representational substrate. Our findings demonstrate a robust neurovisceral coupling architecture, establishing well-characterized heart rate dynamics as a scalable, neurobiologically anchored window into human brain functional organization and cognitive traits.

neuroscience↗

bioRxiv2026

Immunometabolic Reprogramming by Thyroid-Stimulating Antibodies Drives Orbital Adipogenesis via Histone Lactylation in Thyroid Eye Disease

Thyroid eye disease (TED) is conventionally viewed as an autoimmune inflammatory disorder. However, the metabolic determinants driving orbital tissue remodeling remain largely undefined. Here, we uncover a paradigm-shifting mechanism whereby thyroid-stimulating antibodies (TSAbs) instigate profound metabolic reprogramming in orbital fibroblasts (OFs), driving a switch toward glycolysis and markedly elevating lactate production via the CREB/LDHA axis. Critically, we demonstrate that this TSAbs-induced metabolic perturbation is not a mere byproduct but the principal driver of pathology. Mechanistically, lactate functions as a signaling metabolite that directly potentiates adipogenesis via histone lactylation-dependent transcriptional activation of the master adipogenic regulators PPAR{gamma} and C/EBP. Collectively, our findings underscore metabolic reprogramming as a central pathogenic mechanism in TED, whereby autoimmune cues drive disease progression through metabolic-epigenetic crosstalk. This work substantiates the paradigm of TED as an immune- metabolic disorder.

immunology↗

bioRxiv2026

Multidimensional variation and population stratification across 8000 complete human centromeres

Human centromeres are indispensable for the faithful segregation of chromosomes during cell division, yet their highly repetitive nature has historically precluded comprehensive characterization, leaving fundamental questions about their sequence diversity, evolution trajectories and function dynamics unresolved. Here, we generated 6,312 complete human centromere sequences from 320 phased genome assemblies in Asian Pan-Genome project phase 1. By integrating the assemblies from the Human Pangenome Reference Consortium (HPRC) and Human Genome Structural Variation Consortium (HGSVC), we constructed a multidimensional genetic variation map encompassing over 8,000 gapless centromeres. Centromeric satellite arrays account for 4.19% to 6.01% of the whole genome, with substantial variations in size and architecture across chromosomes. Using a refined alpha satellite clustering approach that captures global diversity, we identified 195 higher-order repeat (HOR) arrays, 56.4% of which are absent from the T2T-CHM13 reference genome. Extensive structural variations across multiple dimensions exhibit population stratification, including centromeric haplotypes (CenHaps), ultra-large pericentric inversions spanning up to 36.6 Mbp, and inter-chromosomal HOR sharing that reflects sequence exchange among chromosomes. Integrating CENP-A CUT&Tag experiments and long-read-based DNA methylation profiles, we demonstrate that 16.8% of centromeres harbor multiple potential kinetochore assembly sites, and CenHap-specific local HOR homogenization is associated with kinetochore positioning. Despite global suppression of recombination at centromeres, we observed asymmetric linkage disequilibrium flanking centromeres and an ancient recombination event within the centromere of chromosome 19. Furthermore, contrary to the prevailing assumption of high mutation rates in centromeres, our estimates based on stringent orthology reveal no significantly higher single-base substitution rates for centromeres relative to flanking pericentromeric regions with substantial variations across chromosomes, despite extraordinary structural plasticity. Collectively, these multi-scale centromeric variations provide a global view of human centromere diversity and population stratification, fundamentally redefine centromere evolution through a dual-track model balancing structural innovation with mutational constraint, and establish an essential resource for investigating centromere biology and a baseline reference for diagnosing centromere-associated disorders.

genomics↗

bioRxiv2026

Phase-tuned interfacial condensates drive transcellular access

Nanocondensates occupy mesoscopic scale in both spatial scale and thermodynamic state, and the mesoscopic scale is central to structure-function conversion in living systems. However, how the dual mesoscopic properties of nanocondensates support biological function remains unclear because their small size and rapid dynamics hinder direct observation in living cells. Here we construct nanocondensates in situ at the cell-membrane interface and observe them permeating membranes within seconds, diffusing freely, exiting cells within minutes, re-entering neighbouring cells and traversing multilayered barriers. We report the first observation of this phenomenon and term it nanocondensate tunnelling. We find that nanocondensates cross membranes without membrane enclosure, preserving their wetting characteristics after passage. Theoretical and ultrastructural analyses support a transient-pore model linking this behaviour. We exploit nanocondensate tunnelling to transport small molecules, siRNA and antibodies across cellular barriers, and small molecules and siRNA across a multilayered corneal barrier, demonstrating its functional capacity for intercellular transfer. Our results suggest that nanocondensate tunnelling represents a previously undescribed mode of intercellular transfer. Nanocondensate tunnelling provides a physical basis for biologics delivery and a testable framework for investigating unresolved biological phenomena such as viral permeation.

bioengineering↗

bioRxiv2026

Generalisable tissue-wide molecular reconstruction from histology

Spatial transcriptomics technologies measure gene expression within intact tissues but remain difficult to scale across large tissue sections and patient cohorts. Consequently, many studies rely on tissue microarrays (TMAs) or sparse spatial profiling designs, where molecular measurements are available for only limited tissue regions and are often generated using heterogeneous gene panels. Existing H&E to spatial gene expression prediction methods remain challenged by sparse molecular measurements, partially overlapping gene panels and tissue-wide reconstruction across heterogeneous spatial datasets. Here, we present GHIST+, a framework for tissue-wide reconstruction of single-cell molecular states from H&E histology. GHIST+ integrates cellular morphology, local tissue context and shared tissue representations to extend sparse molecular measurements into tissue-wide molecular maps across heterogeneous spatial datasets. Across multiple cancer types and GTEx breast tissues, GHIST+ reconstructs biologically meaningful tissue-wide molecular organisation from sparse TMA-derived measurements while preserving spatial tissue structure, cell-type organisation and age-associated tissue states across cancer and non-cancer settings. GHIST+ establishes a scalable framework for transforming sparse spatial profiling experiments into tissue-wide molecular maps, enabling cohort-scale molecular reconstruction from routine histology under heterogeneous spatial transcriptomic settings.

bioinformatics↗

bioRxiv2026

The widely used eGFP sequence produces an unintended protein product

Plasmids are widely used for gene expression, yet their coding potential beyond the intended coding sequence (CDS) is often poorly characterized. Here, we explored putative hidden open reading frames (hidden ORFs) embedded within non-canonical reading frames of plasmid sequences through a computational workflow for their identification. Using enhanced green fluorescent protein (eGFP) as a target gene, we observed unexpectedly uninterrupted ORFs in both the +2 coding frame and the reverse frame. Immunoblotting detected stable expression of the +2 frame-derived protein, but not the reverse-frame ORF. Motivated by these observations, we developed a computational pipeline and analyzed 6,308 eGFP-containing plasmids, identifying putative hidden ORFs in approximately 6% of constructs. Approximately 94% of hidden ORFs occurred in the +2 frame, with the remainder occurring in the reverse frame. The same analytical pipeline, if utilized for plasmids beyond eGFP plasmids, can contribute to avoiding unintended outcomes, in applications such as gene replacement therapy.

molecular biology↗

bioRxiv2026

Transcriptomic, Specific Marker, and Pathway Analysis of Smooth Muscle Cell Foam Cells Compared to Macrophage Foam Cells in Human Atherosclerosis

BACKGROUNDSmooth muscle cells (SMCs) are reported to contribute the majority of cholesterol-overloaded foam cells in human and mouse atheromas. However, the transcriptome, specific markers, and biologic itinerary of SMC foam cells relative to macrophage foam cells have not been determined. METHODSTranscriptomic analysis by single cell RNA sequencing (scRNA-seq) was performed on fresh coronary segments from heart transplant recipients with early to intermediate stage atherosclerosis. The gene expression pattern of a putative cluster of SMC foam cells was compared to those of cultured SMCs loaded with either aggregated low density lipoprotein (agLDL) or cholesterol bound to methyl-{beta}-cyclodextrin (Chol-M{beta}CD). Candidate markers of SMC foam cells not expressed by macrophage foam cells were validated in ours and publicly available datasets, by spatial transcriptomics and by immunofluorescence microscopy of human atheromas. Pathway analysis was performed using Gene Set Enrichment Analysis Hallmark gene sets. RESULTSSMC foam cells derived from fibromyocytes were tentatively identified using a panel of markers upregulated with in vitro cholesterol loading of SMCs. agLDL loading reproduced the same transcriptional profile, whereas Chol-M{beta}CD did not reproduce any in vivo SMC state. Top genes highly represented in SMC foam cells included SERPINE1, encoding plasminogen activator inhibitor 1 (PAI-1) and CFH, complement factor H, which were validated in further human coronary scRNA-seq datasets, by Xenium spatial transcriptomics, and by immunofluorescence microscopy. Relative to macrophage foam cells, SMC foam cells exhibit a distinct biologic itinerary, including activation of extracellular matrix, coagulation and angiogenesis pathways. CONCLUSIONSSMC foam cells, which are derived from fibromyocytes ("lipomyocytes"), exhibit unique markers and biologic programs that differ markedly from macrophage foam cells in atherosclerotic plaque development. Further understanding of the role of lipomyocytes and their expression of CFH and PAI-1 expression in plaque biology may offer novel therapeutic options to reduce ischemic cardiovascular disease. Novelty and SignificanceO_ST_ABSWhat is Known?C_ST_ABSO_LISingle-cell transcriptomic studies have demonstrated vascular SMCs undergo extensive phenotypic modulation during atherosclerosis, giving rise to fibromyocytes and other intermediate cell states. C_LIO_LISMC-derived foam cells constitute a major proportion of plaque foam cells. C_LIO_LIPrevious studies have shown that SMC-derived foam cells differ from macrophage-derived foam cells in cholesterol handling and lipid metabolism, making their identification using conventional macrophage-associated foam-cell markers challenging, and highlighting the need for SMC foam cell-specific molecular markers. C_LI What New Information Does This Article ContributeO_LIBy integrating published transcriptomic datasets with bulk RNA-sequencing of agLDL-loaded human SMCs, we identify the transcriptional program of human SMC-derived foam cells and demonstrate that these cells are embedded within the fibromyocyte population rather than forming a distinct cell cluster. C_LIO_LIagLDL loading in vitro reproduces the in vivo SMC foam-cell phenotype, whereas loading with cholesterol bound to cyclodextrin induces an inflammatory state not found in any in vivo SMC state in human atherosclerosis. C_LIO_LICFH and SERPINE1 were identified as specific markers of SMC-derived foam cells and validated by immunostaining and Xenium spatial transcriptomics, providing robust markers for identification of these cells in human atherosclerotic plaques. C_LIO_LIThe top transcriptional programs activated in SMC foam cells differ completely from macrophage foam cells and include extracellular matrix remodeling, complement regulation, coagulation and angiogenesis. C_LI In this study, we mapped smooth muscle foam cells to the fibromyocyte cluster of arterial SMC subtypes in human coronary artery atheromas. In vitro loading of smooth muscle cells with aggregated low-density lipoprotein, the presumed physiologic substrate for foam cell formation during plaque development, induced a gene expression pattern that localized to the same fibromyocyte cluster. The proposed sequence of SMC foam cell formation is that fibromyocytes present in human pre-atherosclerotic intima generate the proteoglycans that bind lipoproteins and allow their uptake by fibromyocytes to generate cholesterol-loaded "lipomyocytes". Lipid loading of fibromyocytes drives expression of specific markers and transcriptional programs, but with an overall gene expression pattern that continues to resemble fibromyocytes. We demonstrate here that lipomyocytes express the specific markers CFH and SERPINE1, and exhibit activation of a completely different set of pathways relative to macrophage foam cells in the plaque. These findings provide evidence for the unique phenotype and specific markers of lipomyocytes relative to macrophage foam cells in human atherosclerosis, which will be critical in evaluating the response of these different types of foam cell to novel therapies.

genomics↗

bioRxiv2026

Selective Elimination of TP53 Mutant Cells by Transcript-Activated Chromatin Shredding

Genetic mutations that drive cancer often occur in tumor suppressor proteins, including the p53 transcription factor which is altered in [~]40-50% of cases1,2. However, current therapies fail to target most such mutations because the mutant proteins typically lack defined drug-binding pockets, and restoring the endogenous function has proven challenging. Here, we programmed CRISPR-Cas12a2, an RNA-guided nuclease with trans-nucleolytic cleavage activities3,4, to selectively kill cancer cells by targeting cancer-specific transcripts. This approach eliminates cells by inducing trans chromatin cleavage, triggering DNA damage and cell death. Unlike existing methods, RNA-guided Cas12a2 senses cellular RNA signatures to shred chromatin, enabling precise targeting of undruggable mutations. Transcript-activated chromatin shredding provides an innovative paradigm to develop precision disease treatments for undruggable targets.

cell biology↗

bioRxiv2026

Basement membrane sets the timescale of tissue mechanical memory

The basement membrane (BM) is a specialised extracellular matrix tightly tethered to epithelial tissues. While the viscoelastic response of epithelial cells to external deformation has been widely studied, the dynamic mechanical role of its underlying BM remains poorly understood. This is mainly due to its thin, dense, non-fibrillar structure and limited number of model systems that allow live fluorescent imaging of the BM components. Using the Drosophila wing disc, we investigate the BMs response to sustained deformation and find that the tissue retains memory of its shape for up to four hours, enabled by the BMs initial elasticity. However, prolonged deformation leads to BM network rearrangement and loss of mechanical memory, resulting in permanent shape change. Our findings reveal that the BM sets the long-term viscoelastic timescale of epithelial tissues which plays a critical role in maintaining tissue architecture under mechanical stress.

biophysics↗

bioRxiv2026

TAR syndrome causal gene RBM8A is critical for embryonic bone development and proper Hedgehog signaling

RNA-Binding Motif Protein 8A (RBM8A) is a core component of the exon junction complex (EJC), which plays a fundamental role in post-transcriptional RNA regulation. Mutations in the RBM8A gene cause thrombocytopenia-absent radius (TAR) syndrome, characterized by reduced platelet number and radial defects. However, how its function contributes to bone development remains poorly understood. We found that RBM8A is highly expressed in human bone marrow-derived mesenchymal stem cells (MSCs) and mouse embryonic limb buds. To further investigate the role of RBM8A in bone development, we generated an Rbm8a conditional knockout mouse (cKO) model in the early limb bud and craniofacial mesenchyme using the Prx1-cre line, which recapitulates key features of TAR syndrome. Rbm8a deficiency in this mouse model resulted in significant defects in limb and craniofacial development, including shorter limb bones across developmental timepoints, delayed ossification, altered cranial morphogenesis, along with impairments in motor function and reduced brain size. To elucidate the molecular basis of these phenotypes, we performed RNA immunoprecipitation sequencing (RIP-seq) in embryonic limb tissue. Our analysis revealed that RBM8A preferentially associates with long, exon-rich transcripts with high isoform complexity. These transcripts are enriched in pathways related to primary cilia, RNA processing, and developmental signaling. Consistent with this, transcriptomic and enrichment analyses identified strong associations with ciliopathy-related and congenital skeletal disease gene sets. At the cellular level, Rbm8a deficiency resulted in altered expression of key chondrogenic and ossification markers in embryonic limb bone tissue, such as reduced SOX9 and increased IHH in the primary ossification center, suggesting impaired progression of endochondral ossification and disrupted Hedgehog pathway activity. Quantitative Reverse Transcription-PCR (qRT-PCR) analysis further validated selective downregulation of Hedgehog pathway targets, including Gli3 and Hhip, while other developmental genes remained unchanged, indicating pathway-specific attenuation. Together, these findings support a model in which Rbm8a regulates structurally complex transcripts that are enriched in ciliary and developmental signaling pathways, and that disruption of this process leads to selective impairment of Hedgehog signaling and skeletal development. These results provide a novel mechanistic link between RNA processing and developmental signaling and offer new insight into how defects in RNA regulation contribute to congenital skeletal abnormalities.

developmental biology↗

bioRxiv2026

Relative Index of Chimeric Expression (RICE) Analysis: A Quantitative Approach for Chimeric RNAs Using FusionBlaster

Chimeric RNA molecules, which contain nucleotide sequences originating from multiple genes, are generated by chromosomal rearrangements, transcriptional read-throughs, or trans-splicing between separate parental transcripts. Chimeric RNAs have been functionally validated in both pathological and normal healthy physiological contexts indicating the biological significance of chimeric RNA expression. There is, however, currently no standard for computationally quantifying chimeric RNA expression and only limited benchmarking data available for the few chimeric RNA detection software that attempt to measure the abundance of the predicted chimeras. Here, we develop the relative index of chimeric expression, RICE, that is calculated based on the relative expression of chimeric transcripts compared to the respective parental WT transcripts. We evaluate three different methods for generating this measurement from simulated RNA sequencing data with known transcript abundances. Our BLAST-based approach outperforms STAR and Kallisto based approaches when considering both accuracy and consistency between simulated data of different read lengths and sequencing depths. We further demonstrate that RICE values can be validated using qPCR and are sensitive to dynamic conditions using siRNA targeting chimeric RNA expression. Finally, we apply our RICE analysis pipeline to clinical prostate cancer data. We quantify over 1200 chimeric RNAs in primary prostate cancer, metastatic prostate cancer, and non-cancer tissue samples from GTEx. Our differential RICE analysis revealed a clustering of prostate cancer tissue samples from three different sequencing cohorts distinct from their associated tissue type noncancer GTEx clusters. Our pipeline is publicly available on github and can be run on a personal laptop with computational resources and processing time dependent on the number of quantified chimeras.

bioinformatics↗

bioRxiv2026

ProAR: Probabilistic Autoregressive Modeling for Molecular Dynamics

Understanding the structural dynamics of biomolecules is crucial for uncovering biological functions. As molecular dynamics (MD) simulation data becomes more available, deep generative models have been developed to synthesize realistic MD trajectories. However, existing methods produce fixed-length trajectories by jointly denoising high-dimensional spatiotemporal representations, which conflicts with MDs frame-by-frame integration process and fails to capture time-dependent conformational diversity. Inspired by MDs sequential nature, we introduce a new probabilistic autoregressive (ProAR) framework for trajectory generation. ProAR uses a dual-network system that models each frame as a multivariate Gaussian distribution and employs an anti-drifting sampling strategy to reduce cumulative errors. This approach captures conformational uncertainty and time-coupled structural changes while allowing flexible generation of trajectories of arbitrary length. Experiments on ATLAS, a large-scale protein MD dataset, demonstrate that for long trajectory generation, our model achieves a 7.5% reduction in reconstruction RMSE and an average 25.8% improvement in conformation change accuracy compared to previous state-of-the-art methods. For conformation sampling task, it performs comparably to specialized time-independent models, providing a flexible and dependable alternative to standard MD simulations.

molecular biology↗

bioRxiv2026

Minimal biophysical rules are sufficient for the emergence of computational intelligence at the neuronal scale

How intelligence emerges from the brains complex microscopic physical system is a central question for neuroscience and artificial intelligence. Constrained by the genomic bottleneck that precludes synapse-by-synapse specification, we propose and validate a microscopic structure-function concise-constraint sufficiency hypothesis. We develop the Neuro-Informed Generative Connectome (NIGC) framework, and show that connectomes generated under a concise set of biophysical constraints (geometric embedding, node propensity modulation, a global energy budget and maximum-entropy selection) closely match the structural statistics of a measured mouse V1 microcircuit (similarities, 0.997). In parallel, using the generated connectome as the fixed reservoir of an echo state network (ESN), training only a linear readout achieves 90% accuracy on an auditory multi-classification task. Moreover, multidimensional biologically consistent functional phenotypes, such as hierarchical transmission delays and low-dimensional spatiotemporal trajectories, are obtained without fitting functional matrices or time courses. Further, by combining single-constraint ablations, pathological perturbations and cross-modal validation, we clarify how specific structural constraints map onto functional consequences. Together, these results delineate sufficient conditions for computational intelligence emergence at the microscopic scale, and provide an auditable benchmark for first-principles understanding of brain construction.

neuroscience↗