Biology subjects

Li, C.

Publications and source records attributed to Li, C..

At least 325 records · Page 18Linked to original sources

bioRxiv2025

Large-scale skin metagenomics reveals extensive prevalence, coordination, and functional adaptation of skin microbiome dermotypes across body sites

While skin microbiome studies have increasingly highlighted its importance in health and disease, our understanding of inter-individual heterogeneity in structure and function remains limited, impacting the ability to develop microbiome-based stratification and therapeutics. Powered by comprehensive skin microbiome characterization in a multi-ethnic population-based cohort (>3,550 shotgun metagenomes across 18 sampling sites), we established significant undescribed inter-individual heterogeneity and the extensive prevalence of distinct microbial configurations (17 species-resolution dermotypes) in seven out of nine body sites. Combining functional in silico and in vitro studies revealed insights into how these dermotypes assemble as a function of niche-dependent microbial interactions (e.g. hypoxia-dependent inhibition of S. hominis by S. epidermidis/M. luteus) and metabolic resource utilization (e.g. differential galactose and histidine metabolism). Integration of demographic, skin physiological, and behavioral data further identified >30 significant associations with host attributes. Cross-site analysis revealed remarkable coordination across disparate skin regions (predictive AUC-ROC>0.8) and bilateral consistency (Pearson {pi}>0.95), emphasizing the role of specific microbial and host factors in shaping dermotypes. Finally, we provide multiple lines of evidence that dermotype states impact the risk for skin discomfort (e.g. irritation, itch) and diseases (e.g. eczema), that when combined with our highly accurate dermotype classifiers (AUC-ROC>0.98), provide a new paradigm for understanding skin microbiome function and stratifying patients in the context of skin and other diseases.

genomics↗

bioRxiv2025

Single cell omics extends metabolic regulon via orthologous transcription factors from a pair of medicinal plant species

Camptotheca acuminata Decne is a woody medicinal tree that produces over a hundred bioactive compounds, including camptothecin, which has been used as the starting material to semi-synthesize many leading anticancer drugs (Lorence and Nessler 2004). Camptothecin and its derivatives are potent inhibitors of DNA topoisomerase I and are widely used for the treatment of lung, cervical, ovarian, and colon cancers. Camptothecin biosynthesis in C. acuminata involves complex catalytic steps, most of which remain undeciphered. In this pathway, tryptamine and secologanic acid are coupled, leading to strictosidinic acid. The formation of strictosidinic acid is catalyzed by strictosidine/strictosidine acid syn-thase enzymes (STR) (Fig. 1A). While a biosynthetic route for the conversion of the indole ring to the quinoline ring has been proposed, most of the underlying biosynthetic genes have yet to be identified (Fig. 1A) (Sadre et al. 2016). In addition, the cell type specificity of this pathway also remains undescribed. Here, we generated a single cell multiome (RNA-seq and Assay for Transposase Accessible Chromatin by sequencing [ATAC-seq] from the same nuclei) to probe the cell type specificity of camptothecin biosyn-thetic genes. O_FIG O_LINKSMALLFIG WIDTH=149 HEIGHT=200 SRC="FIGDIR/small/650021v2_fig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@81dcf0org.highwire.dtl.DTLVardef@1d03ae1org.highwire.dtl.DTLVardef@1c9b0a9org.highwire.dtl.DTLVardef@6d5238_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 1.C_FLOATNO Single cell multi-ome of Camptotheca acuminata leaf. (A) The proposed biosynthetic pathway for camptotheci . Solid arrows indicate previously characterized enzymatic steps. Dashed arrows indicate proposed enzymatic steps (see Table S7 for gene name abbreviations). (B) Uniform Manifold Approximation and Projection (UMAP) of nuclei of the single nuclei RNA-seq dataset (n = 4,012), color coded by cell clusters. (C) Gene expression heatmap of MIA biosynthetic genes across cell clusters. Rows are expressed biosynthetic genes, which are ordered from upstream to downstream. Color scale shows the average scaled expression of each gene at each cell cluster. Cell clusters are sorted by cell types. Dot size indicates the percentage of cells where a given gene is detected. The predicted cell type for each cell cluster is annotated by the color strip below the x-axis. Box highlights expression of STR genes. (D) Heat map showing accessibility of cell type marker peaks across cell clusters. Each row is an ATAC-seq peak. Each column is a cell cluster. Color scale is maxed out at 90th percentile of normalized ATAC-seq signal. The predicted cell type for each cell cluster is annotated by the color strip below the x-axis, with the same color palette as (B). (E) Heatmap showing gene expression across cell clusters. Each row is a gene within 2-kb of a STR+ marker peak. Each column is a cell cluster. The predicted cell type for each cell cluster is annotated by the color strip below the x-axis, with the same color palette as (B). (F) DNA motif enriched in STR+ marker peaks, as well as a reference MYB motif. C_FIG

plant biology↗

bioRxiv2025

Theoretical origins of extreme cell differentiation irreversibility: a dynamic model of organismal size effects

Cell differentiation is a pivotal evolutionary transition underlying multicellular complexity. Irreversible differentiation - a process in which cells permanently lose plasticity to become specialized types - is hypothesized to emerge predominantly in large, cell-rich organisms. However, the causal relationship between organismal size and the evolutionary origins of this extreme developmental commitment remains unclear. By integrating developmental dynamics into a mathematical model, we demonstrate that extreme irreversible differentiation (where all cell types exhibit irreversibility) most robustly evolves in intermediately sized multicellularity. This reveals a non-monotonic dependence of cell fate determinism on an organismal scale. Specifically, increasing organismal size initially promotes extreme irreversible differentiation by enhancing the selective advantages of cellular division of labor. Beyond a critical size threshold, however, further expansion destabilizes this extreme irreversibility due to its decreasing differentiation advantages compared with reversible differentiation. Counterintuitively, smaller organisms establish cellular irreversibility at earlier developmental stages rather than larger organisms. Our framework identifies an evolutionary double-edged sword: while body size expansion initially facilitates extreme differentiation irreversibility, it ultimately leads to its collapse. These results establish quantitative links between organismal dimensions and cell fate determinism, explaining the size-dependent evolution of developmental strategies in simple multicellular systems.

evolutionary biology↗

bioRxiv2025

Therapeutic Effect of Anti-FABP4 mAb (6H2) on Systemic Inflammation in Sepsis: Insights from Abdominal Organ Analysis

Sepsis is a life-threatening condition driven by dysregulated immune responses and multi-organ dysfunction, with limited treatments targeting its underlying pathophysiology. Growing evidence highlights fatty acid-binding protein 4 (FABP4) as a key mediator of inflammation and organ injury in sepsis. In this study, we investigated the therapeutic potential of an anti-FABP4 monoclonal antibody (6H2) in a murine endotoxemia model induced by lipopolysaccharide (LPS). Treatment with 6H2 significantly attenuated systemic inflammation, as evidenced by modulated leukocyte responses, and provided substantial tissue protection in the liver, lungs, kidneys, and heart, reducing histopathological damage. Our findings identify 6H2 as a promising novel therapeutic intervention for sepsis. Author SummaryTitleTherapeutic Potential of Anti-FABP4 Antibody (6H2) in Sepsis: Protection Against Systemic Inflammation and Organ Damage Key Findings- Sepsis, a life-threatening inflammatory condition, lacks targeted therapies. We investigated 6H2, a monoclonal antibody against fatty acid-binding protein 4 (FABP4), in a mouse model of sepsis. - 6H2 treatment significantly reduced sepsis severity, improved survival, and attenuated organ damage in the liver, lungs, kidneys, and heart. - Histopathological analysis revealed restored tissue integrity in 6H2-treated mice, with reduced inflammation and cell death compared to controls. - Complete Blood Count showed modulated immune responses, including altered leukocyte counts, suggesting 6H2s role in rebalancing inflammation. SignificanceFABP4 is a key driver of sepsis-related inflammation and organ dysfunction. Our study demonstrates that 6H2 not only mitigates systemic inflammation but also provides multi-organ protection, offering a promising therapeutic strategy for sepsis. These findings support further preclinical and clinical development of FABP4-targeted therapies.

immunology↗

bioRxiv2025

Prevalent cross-cell type QTL trans-regulatory genetic effects impacting innate lymphoid cells in the small intestine

Tissue function in homeostasis and disease arise from coordinated interactions between different cell types and can vary between individuals in a population, in part due to the impact of genetic variants. In barrier tissues such as the gut, innate lymphoid cells (ILCs) play critical roles in maintaining tissue homeostasis and immunity, but the genetic basis and associated regulatory circuitry affecting tissue ILCs remain largely unknown. Here, we systematically mapped the regulatory functions of genetic variants across 273,370 gut ILCs profiled by single cell RNA-seq from 274 diversity outbred (DO) mice. Computational analysis identified quantitative trait loci (QTL) impacting ILCs at three levels: cell subtype-specific mRNA expression (local and distal), cell subset proportions, and ILC gene expression programs (in trans), of which we experimentally validated a pivotal role for the transcription factor Rbpj in regulating ILC3s. All three classes of ILC QTL display polygenic inheritance signatures and broadly overlap with QTL affecting peripheral cytokine levels that we measured in another 261 DO mice. Strikingly, nearly half of trans-QTL affecting ILC traits did not overlap (within a 50-kb window) genes expressed in ILCs, and such loci were enriched for genes expressed by non-ILCs especially enteric neurons and intestinal glia. This suggests that such loci may act instead across cell type boundaries and allowed us to recover causal trans-cell type regulatory circuits in the tissue, including loci encoding multiple neuron-expressed peptides, epithelial-cell expressed Sox9, and phagocyte-expressed Ccl17. Finally, human orthologs of genes in QTL impacting gene expression and cell proportions are enriched for autoimmune disease risk heritability, suggesting their relevance to human disease. Our findings highlight how the impact of genetic variants may propagate to maintain tissue homeostasis and show a path to understand causality in tissue biology using quantitative genetics.

genetics↗

bioRxiv2025

Research on Crop Phenotype Prediction Methods Based on SNP-context and Whole-genome Features Embedding

Modern agriculture demands precise genomic prediction to accelerate elite crop breeding, yet traditional genomic prediction approaches, such as genomic best linear unbiased prediction (GBLUP) and Bayesian methods, focus primarily on the cumulative effect of individual SNPs, thus neglecting the concerted influence that the surrounding sequence context has on the phenotype. To overcome these limitations, we propose two novel feature embedding modes (SNP-context and whole-genome) based on DNABERT-2, a cross-species genomic foundation model that uses self-attention mechanisms and transfer learning to automatically identify conserved sequence features across diverse evolutionary lineages without prior biological assumptions. The whole-genome feature embedding aggregates genomic information at a global scale by pooling vectors from chunked sequences processed by DNABERT-2, whereas the context feature embedding captures local information by directly encoding variable-length (500--3000 bp) sequences centered on target SNPs. To reduce noise in the high-dimensional feature embeddings, we employed principal component analysis (PCA) and partial least squares (PLS) to project the features into a lower-dimensional space. We generated two kinds of feature embedding for three crop datasets (rice413, rice395, and maize301), investigated the impact of 500--3000 bp flanking SNP contexts on phenotypic prediction, and compared prediction accuracy variations across algorithms at 4--768 feature dimensions among the PCA, PLS, and no dimensionality reduction strategies. The results demonstrate that machine learning (ML) algorithms operating under the SNP-context embedding mode achieve greater accuracy and lower mean absolute errors (MAEs) than traditional SNP features do at specific context lengths, particularly for traits with low-to-moderate heritability (h2[isin](0.2, 0.7]). In contrast, using whole-genome embeddings as input for ML can further improve the prediction accuracy for highly heritable traits (h2[isin](0.7, 1.0]), even outperforming state-of-the-art deep learning models (such as DNNGP and ResGS) that rely on SNP markers. Our code is available on https://github.com/oliveSpring/Crop_DNA_Embedding.git

genetics↗

bioRxiv2025

Dissecting organoid-bacteria interaction highlights decreased contractile force as a key factor for heart infection

Bacterial endocarditis is a fatal cardiovascular disease exacerbated by weakened heart contraction, yet the direct impact of cardiac contractility on bacterial adhesion remains elusive. Here, we present a novel quantitative physics model integrating finite element analysis and live-cell imaging to uncover their strong correlation. Using this model, we quantified the real-time force magnitude generated by organoid-type cardiac microtissue derived from healthy donors and dilated cardiomyopathy patients - mimicking normal and suppressed heart contractility, respectively - to the approaching bacteria in a real fluidic system. The data revealed that weakened cardiac contractility facilitated bacterial invasion of the myocardium. Verifying this finding in a mouse transverse aortic constriction model demonstrated that increasing heart contraction efficiently mitigated bacterial invasion, with a 25% increase in heart contractility reducing endocarditis risk by 80%. Our findings demonstrate that patient-derived cardiac organoids provide a physiologically relevant platform for studying bacterial infections in vitro, offering high clinical fidelity. This platform establishes a valuable tool for drug screening and the development of novel therapeutic strategies.

bioengineering↗

bioRxiv2025

Single-Cell Multiomic Analysis of Circadian Rhythmicity in Mouse Liver

Circadian rhythms are remarkably widespread across most organisms, regulating hormonal, metabolic, physiological, and behavioral oscillations through molecular clocks that orchestrate the rhythmic expression of thousands of genes. Here, we generate single-nucleus RNA and ATAC multiomics data to simultaneously characterize gene expression and chromatin accessibility of mouse liver cells across the 24-hour day. We interrogate multimodal circadian rhythmicity in both discretized cell types and transient sub-lobule cell states, capturing space-time omics profiles. We delve beyond mean cyclic patterns to characterize stochastic transcriptional bursting and infer spatiotemporal gene regulatory networks that control circadian rhythmicity and liver physiology. Our findings apply to existing single-cell data of mouse and Drosophila brains and are validated by time-series single-molecule fluorescence in situ hybridization and vast amounts of orthogonal omics data. Altogether, our study constructs a comprehensive map of the time-series transcriptomic and epigenomic landscapes that elucidate the function and mechanism of the liver peripheral clocks.

bioinformatics↗

bioRxiv2025

Imputation Disparities Driven by Recent Selectionand Their Impact on Disease Risk Estimation in East and Southeast Asian Populations

Using genotype data consisting of 8,316 individuals, we systematically evaluated imputation performance across six state-of-the-art reference panels for Chinese and Thai populations. A substantial proportion of variants identified through whole-genome sequencing, especially low-frequency variants, remained undetected by existing reference panels. In the Chinese population, the TOPMed panel required an R2 threshold of 0.60-0.70 to achieve comparable imputation accuracy of the ChinaMAP panel without R2 filtering, challenging the standard practice of applying a fixed R2 threshold for downstream analyses. Regional analysis highlighted the role of recent selection in imputation discrepancies and revealed an enrichment of immune-related genes in poorly imputed regions. In addition, we showed that the selection of reference panels and R2 thresholds could significantly influence estimation of polygenic risk score for disease prediction. These findings underscore the importance of developing ancestrally diverse reference panels and provide valuable guidelines for improving genotype imputation in East and Southeast Asian populations.

genomics↗

bioRxiv2025

Restoration of Susceptibility of blaNDM-bearing Escherichia. coli to Carbapenem Antibiotics by Exogenous N-acetylcysteine

The global spread of the New Delhi metallo-{beta}-lactamase (NDM) -producing carbapenem-resistant Enterobacteriaceae pose a serious threat to public health, as NDM and its variants enzymes efficiently hydrolyze almost {beta}-lactam antibiotics. The development of novel antibiotics or antibiotic adjuvants capable of eradicating antibiotic-resistance bacteria through multiple mechanisms represents a promising strategy for reversing antibiotic resistance and preventing the emergence of new resistance. In this study, we utilized high-performance liquid chromatography (HPLC) to demonstrate that N-acetylcysteine (NAC) is a prominent reducing metabolite in bacteria harboring NDM-5. Notably, NAC was able to restore carbapenem susceptibility in NDM-producing bacteria in vitro. Subsequently, we further investigated the underlying mechanisms involved. Our findings revealed that NAC exerts its effect through multiple mechanisms that collectively contribute to reversing meropenem resistance. Firstly, NAC may inhibit biofilm formation and reduces polysaccharide production in NDM-positive Escherichia coli. and this potential mechanism was verified by transcriptomic analysis, reverse transcription PCR (RT-PCR) and a biofilm restoration experiment involving the addition of citrate cycle intermediate metabolites. Secondly, RT-PCR analysis demonstrated that NAC significantly downregulates the expression of blaNDM-5. Additionally, NAC exhibited competitive inhibition of NDM activity in vitro. Thirdly, NAC was found to enhance the intracellular accumulation of meropenem, therapy increasing its bactericidal efficacy. These three independent mechanisms offer valuable insights for developing adjuvants. The discovery offers a promising prospect for combating the antibiotic resistance concern. This study paves the way for further exploration and potential clinical applications in the fight against antibiotic-resistant bacterial infections.

pharmacology and toxicology↗

bioRxiv2025

TRUHiC: A TRansformer-embedded U-2 Net to enhance Hi-C data for 3D chromatin structure characterization

High-throughput chromosome conformation capture sequencing (Hi-C) is a key technology for studying the three-dimensional (3D) structure of genomes and chromatin folding. Hi-C data reveals underlying patterns of genome organization, such as topologically associating domains (TADs) and chromatin loops, with critical roles in transcriptional regulation and disease etiology and progression. However, the sparsity of existing Hi-C data often hinders robust and reliable inference of 3D structures. Hence, we propose TRUHiC, a new computational method that leverages recent state-of-the-art deep generative modeling to augment low-resolution Hi-C data for the characterization of 3D chromatin structures. By applying TRUHiC to real low-resolution Hi-C data from the GM12329 cell line and across other publicly available Hi-C data for human and mice, we demonstrate that the augmented data significantly improve the characterization of TADs and loops across diverse cell lines and species. We further present a pre-trained TRUHiC on human lymphoblastoid cell lines that can be adaptable and transferable to improve chromatin characterization of various cell lines, tissues, and species.

bioinformatics↗

bioRxiv2025

A TRPV4-dependent calcium signaling axis governs lamellipodial actin architecture to promote cell migration

Cell migration is crucial for development and tissue homeostasis, while its dysregulation leads to severe pathologies. Cell migration is driven by the extension of actin-based lamellipodia protrusions, powered by actin polymerization, which is tightly regulated by signaling pathways, including Rho GTPases and Ca2+ signaling. While the importance of Ca2+ signaling in lamellipodia protrusions has been established, the molecular mechanisms linking Ca2+ to lamellipodia assembly are unknown. Here, we identify a novel Ca2+ signaling axis involving the mechano-gated channel TRPV4, which regulates lamellipodia protrusions in various cell types. Using Ca2+ and FRET imaging, we demonstrate that TRPV4-mediated Ca2+ influx upregulates RhoA activity within lamellipodia, which then facilitates formin-mediated actin assembly. Mechanistically, we identify CaMKII and TEM4 as key mediators relaying the TRPV4-mediated Ca2+ signal to RhoA. These data define a molecular pathway by which Ca2+ influx regulates small GTPase activity within a specific cellular domain - lamellipodia - and demonstrate the critical role in organizing the actin machinery and promoting cell migration in diverse biological contexts.

cell biology↗

bioRxiv2025

Highly heterozygous Citrus changshan-huyou Y. B. Chang originated from ancient hybridization between mandarin and pummelo and displayed distinct tissue-specific allelic imbalance

The genus Citrus is characterized by a reticulate evolutionary history with frequent hybridization, making it an intriguing subject for genome evolution investigation. Citrus changshan Y. B. Chang (Huyou) is a unique landrace first discovered in Zhejiang Province, China with premium fruit quality. The evolutionary origin of Huyou has puzzled local botanists and growers. Here, we sequenced a 120-years-old "ancestral tree" of Huyou using PacBio long read and Hi-C sequencing and assembled 2 high-quality haplotype-resolved genomes HY1 and HY2. Huyou displayed a genome heterozygosity level at 3.07%, among the highest in published citrus genomes. Using a k-mer-based tracing approach, we explicitly resolved that HY1 genome contained 87.8% mandarin, 7.3% pummelo, 0.2% citron origin, whereas HY2 had 85.0% pummelo, 2.9% mandarin, 0.3% citron, implying a hybridization event between mandarin and pummelo. Phylogeny dating showed that HY1 (2.0 Mya) and HY2 (2.18 Mya) had diverged earlier than the split of Citrus clementina and Citrus reticulata, and the split of Citrus grandis and Citrus maxima, respectively. We observed clear chromosomal recombination on chr8 and chr9 in HY1, which may have occurred after the ancestral hybridization. Further transcriptome analyses in 6 tissues revealed a strong allelic dominance of HY2 over HY1 in root tissue and moderately in stem, leaf, flower, and fruits. KEGG enrichment analyses revealed that genes related to antioxidants biosynthesis and lipid metabolisms were most significantly affected by allelic imbalance. This first report of allelic imbalance in citrus species support Huyou as an interesting model to investigate genome evolution following distant hybridization.

evolutionary biology↗

bioRxiv2025

Lognormal distributions capture site-specific variability in enteric virus concentrations in wastewater

As more data on virus concentrations in influent water from wastewater treatment plants (WWTPs) becomes available, establishing best practices for virus measurements, monitoring, and statistical modelling can improve the understanding of virus concentration distributions in wastewater. To support this, we assessed the temporal variability of norovirus, adenovirus, enterovirus, and rotavirus concentrations in influent water across multiple WWTPs in Switzerland, the USA, and Japan. Our findings demonstrate that the lognormal distribution accurately predicts temporal variations in concentrations for all viruses at all sites, outperforming the gamma and Weibull distributions that do not capture high variability. However, important differences in variability and uncertainty were observed across systems, underscoring the need for site-specific assessments. Using lognormal parameters, we identified optimal monitoring frequencies to balance cost-effectiveness and precision. For most sites, weekly monitoring would be sufficient to estimate the annual average concentration of enteric viruses within a 95% confidence interval of 0.5-log10. We examined the mechanistic basis of the lognormal distribution, highlighting processes that drive its prevalence and shape the behavior of its upper tail. By integrating these insights, this study provides a novel statistical foundation for optimizing virus monitoring frameworks and informing public health interventions targeting wastewater systems.

microbiology↗

bioRxiv2025

High-resolution NMR spectroscopy of proteins in intact mitochondria

Understanding protein structure and function within mitochondria is essential for unraveling the molecular mechanisms underlying cellular energy production, stress response, and disease. Here, we present a novel approach for NMR observation of proteins within intact mitochondria by delivering proteins directly into isolated mitochondria via electroporation. Using this method, we investigate the interaction of -synuclein (-syn) with the mitochondria membrane and examine how post-translational modifications regulate this interaction. Additionally, we assessed the stability of GB1 and the dimerization of its variant within mitochondria, achieving quantitative insights into mitochondrial environmental impact on protein function. This approach offers a valuable framework for exploring mitochondrial related biomolecular events at atomic-resolution within intact mitochondria, paving the way for a more comprehensive understanding of the molecular events governing mitochondrial health and dysfunction.

biochemistry↗

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↗

bioRxiv2025

Lamin A/C safeguards replication initiation by orchestrating chromatin accessibility and PCNA recruitment

Lamin A/C, a nuclear lamina protein, is essential for maintaining nuclear architecture, organizing chromatin and preserving genomic stability. However, its role in regulating DNA replication remains unclear. This study investigates how Lamin A/C regulates proper activation of replication origins by orchestrating the chromatin structure and recruitment of proliferating cell nuclear antigen (PCNA). We demonstrate that Lamin A/C stabilizes replication domains (RDs) by restricting chromatin mobility, preserving spatial organization, and maintaining accessibility. Furthermore, Lamin A/C interacts with PCNA and sequesters a pool of PCNA, to regulate its recruitment to replication machinery. The loss of Lamin A/C leads to an increase in chromatin dynamics, RD accessibility, and PCNA availability at RDs, which together trigger excessive activation of replication origins, leading to replication stress and DNA damage. These disruptions prolong the S phase and compromise genome stability, highlighting Lamin A/C as a critical gatekeeper of balanced replication initiation. Our findings reveal Lamin A/Cs dual role in chromatin organization and replication machinery regulation, offering valuable insights into its involvement in replication-associated diseases and potential therapeutic opportunities through targeting replication dynamics.

biophysics↗

bioRxiv2025

Context-dependent effects of mutations on complex splicing decisions

Alternative pre-mRNA splicing is an essential step in human gene regulation, and mutation-induced aberrant splicing is frequently found in diseases and therapy resistance. Splicing regulation is highly dependent on sequence and cellular context, posing a challenge to predict outcomes of splicing-related disease mutations. Here, we use kinetic modeling to derive the underlying quantitative principles, describing splice site competition and downstream effects on a wide spectrum of splice isoforms. Employing statistical learning on a large-scale mutagenesis dataset for CD19 mRNA splicing, our model quantitatively describes the generation of 93 RNA isoforms. It takes into account various splicing events such as cassette exon skipping, intron retention, and extensive alternative 3 and 5 splice site usage, which are implicated in CART therapy resistance in leukemia. Beyond CD19, by analyzing genome-wide RNA sequencing data and large-scale screening of synthetic splicing decisions, we find that splice site distance is an important parameter controlling the switch from canonical to alternative/cryptic splice site usage, as mutations located in between two nearby splice sites show a pronounced directionality, regulating up- and downstream effectors in opposite direction. Taken together, our work demonstrates that a quantitative description of splice site competition provides insights into context-dependent, complex isoform changes and cryptic splice site activation in health and disease.

systems biology↗