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Rao, S.

Publications and source records attributed to Rao, S..

At least 37 records · Page 2Linked to original sources

Monounsaturated fatty acid biosynthesis is critical for streptococcal envelope homeostasis and stress tolerance

AbstractThe genus Streptococcus contains some of the most important commensals and pathogens of the human microbiome. To obtain the fatty acids required for cell membranes, Streptococcus either produce fatty acids de novo through the fatty acid biosynthesis (fab) pathway or uptake host fatty acids through the fatty acid kinase (fak) pathway. Although both the fab and fak pathways represent potential therapeutic targets to prevent or treat infection, progress is limited because of an incomplete understanding of taxon-to-taxon variability in streptococcal lipid metabolism. Here, we examined the role of de novo monounsaturated fatty acid (MUFA) synthesis in physiology and virulence-associated traits in Streptococcus mutans, Streptococcus pyogenes, and Streptococcus pneumoniae, three major pathogens that cause disease at distinct body sites. In all three species, deletion of fabM abolished MUFA production and caused severe growth defects, decreased stress tolerance, increased antibiotic susceptibility, and defects in cell viability, morphology, and division. In S. mutans, loss of fabM also markedly reduced competence signaling and production of the mutacin IV bacteriocin. Deletion of fabM increased susceptibility to killing by human neutrophils in S. mutans and S. pneumoniae, but not S. pyogenes. Together, these findings illustrate that MUFA synthesis is broadly important for streptococcal physiology and cell membrane homeostasis, while its contribution to pathogenesis is strongly species- and context-dependent, providing leads to guide development of novel therapeutic and/or preventative strategies.

microbiology↗

Rescue from pyridostatin-stabilized telomeric G-quadruplexes by DNA cleavage and microhomology-mediated end joining

G-quadruplexes are four-stranded nucleic acid structures that are formed by guanine rich sequences. They have been implicated to interfere with telomere maintenance, but their effects are not well understood at a molecular level. Here, we treat human cells with the G-quadruplex stabilizer and anti-cancer drug-candidate pyridostatin and characterize its effects on telomere replication and maintenance. We demonstrate that pyridostatin interferes with lagging strand DNA synthesis during semiconservative replication of telomeres. Pyridostatin impedes replication fork progression and triggers telomere cleavage events involving the Flap-endonuclease FEN1 and the nuclease-helicase DNA2. Telomeric protein composition analysis reveals pyridostatin-induced association of LIG3 with telomeres. This enzyme is involved in repair of DNA double strand breaks by microhomology-mediated end joining (MMEJ). Depletion of MMEJ-factors or their chemical inhibition enhances telomere loss events in pyridostatin-treated cells. Altogether, our data reveal a three-step mechanism in which pyridostatin-stabilized G-quadruplexes inhibit replication of lagging strand telomeres, which is overcome by FEN1/DNA2-mediated DNA cleavage and MMEJ-mediated DNA repair. The synthetic effects of pyridostatin and MMEJ inhibition on telomere maintenance may become exploitable in future anti-cancer therapies.

molecular biology↗

Orchestrating Spatial Transcriptomics Analysis with Bioconductor

Spatial transcriptomics technologies provide spatially-resolved measurements of gene expression through assays that can either target selected genes or capture transcriptome-wide expression profiles. The complexity and variability of these technologies and their associated data necessitate multi-step workflows integrating diverse computational methods and software packages. We provide a freely accessible, open-source, continuously updated and tested online book containing reproducible code examples, datasets, and discussion about data analysis workflows for spatial omics data using Bioconductor in R, including interoperability with Python.

bioinformatics↗

Video-Based Cattle Behavior Detection for Digital Twin Development in Precision Dairy Systems

Digital twins in dairy systems require reliable behavioral inputs. We develop a video-based framework that detects and tracks individual cows and classifies seven behaviors under commercial barn conditions. From 4,964 annotated clips, expanded to 9,600 through targeted augmentation, we couple YOLOv11 detection with ByteTrack for identity persistence and evaluate SlowFast versus TimeSformer for behavior recognition. TimeSformer achieved 85.0% overall accuracy (macro-F1 0.84) and real-time throughput of 22.6 fps on RTX A100 hardware. Attention visualizations concentrated on anatomically relevant regions (head/muzzle for feeding and drinking; torso/limbs for postures), supporting biological interpretability. Structured outputs (cow ID, start-end times, durations, confidence) enable downstream use in nutritional modeling and 3D digital-twin visualization. The pipeline delivers continuous, per-animal activity streams suitable for individualized nutrition, predictive health, and automated management, providing a practical behavioral layer for scalable dairy digital twins.

animal behavior and cognition↗

A late cytoplasmic surveillance pathway ensures ribosome integrity

Errors in ribosome assembly can produce defective subunits that can lead to aberrant translation events. How faulty ribosomes are recognized and whether they are recognized during assembly or translation remains poorly understood. We utilized a mutation in the ribosomal protein uL16 to track defective 60S subunits through the biogenesis and translation pathways. This mutation deletes a critical loop in the P site and arrests pre- 60S particles during late cytoplasmic maturation. However, simultaneous mutations in the late biogenesis factors Nmd3 and Tif6 bypass this block, releasing defective ribosomes into the translational pool. Cryo-EM and selective ribosome profiling reveal that these ribosomes can form peptide bonds, but stall predominantly at the first few codons. We show that the uL16 mutant ribosomes are detected and targeted for degradation during biogenesis and that they escape degradation if they enter translation. We identify Reh1 as a non-canonical ribosome assembly factor that is required for this surveillance pathway.

molecular biology↗

IS110 transposon utilizes two mechanistically distinct RNA-guided transposition pathways

The recently discovered IS110 elements employ RNA-guided transposases that use bridge-RNA to coordinate donor and target DNA recognition and integration via donor- and target-binding loops, offering promise for precise, DSB-free genome editing. However, their transposition mechanism remains unclear, with prior inconsistent observations. Using a IS110 element from Caloranaerobacter azorensis, we show that IS110 transposons utilize two independent transposition pathways. The first depends on bridge-RNA and excises the element via copy-out to form a circular intermediate, revisiting the earlier cut-out model. Integration occurs predominantly through top-strand insertion, suggesting an alternative to the earlier Holliday junction-mediated dual-strand mechanism. The second involves cooperation between a truncated target-binding loop RNA and bridge-RNA, enabling direct top-strand transfer to a new target via two sequential reactions, bypassing circular intermediates. Both pathways preserve the original transposon copy. These findings redefine the mechanistic understanding of IS110 transposition and reconcile prior discrepancies, offering insight into programmable, RNA-guided genome modification.

molecular biology↗

Laplacian Dynamics and Kron Reduction in Species-Reaction Graphs of Chemical Reaction Networks

We present a new method for deriving the dynamics of chemical reaction networks using the Laplacian matrix of the corresponding species-reaction graph, in contrast to previous works that use the Laplacian of the graph of complexes. Species-reaction graphs are bipartite graphs that contain two sets of vertices, one representing species and the other representing reactions, connected by directed edges that indicate relationships between them. Our approach starts by assigning appropriate edge weights to this bipartite graph, which are then used to compute the weighted graph Laplacian. This Laplacian reformulation of the system of differential equations governing the network dynamics emphasizes the flow of information throughout the chemical reaction network considered as causal network. As an application of this framework, we introduce a novel model reduction technique based on the Kron reduction of the weighted Laplacian matrix associated with the species-reaction graphs. Our systematic approach involves identifying nodes for deletion while preserving the bipartite structure, followed by constructing the Kron-reduced model. To demonstrate the effectiveness of our method, we apply it to a complex biochemical network, showing how model simplification facilitates analysis and interpretation of these systems.

systems biology↗

Moving Beyond Binary Biomarkers: Machine Learning Model Resolves Concurrent and Molecularly Heterogeneous Mismatch Repair and Homologous Recombination Deficiencies in Prostate Cancer

Current DNA damage repair (DDR) biomarkers employ binary classifications that fail to capture the molecular complexity of tumors with concurrent repair deficiencies. We used genomics analysis to stratify 672 metastatic prostate cancer patients into 11 DDR subgroups, identifying 51 molecular signatures with weighted roles in class identity. We identified a tumor-mutational-burden very-high subset, characterized by 19 mutations/Mb or more, as a molecularly distinct group characterized by preserved genomic integrity and enhanced immunogenicity. Critically, 2.3 percent of tumors exhibited concurrent TMB-High and HRR mutant phenotypes, while 1.5 percent harbored MMR bi-allelic loss without MMRd (mismatch-repair-deficiency) signatures. Clinical validation in 130 patients demonstrated superior immunotherapy responses in tumors with very high TMB levels. We developed CHIMERA DDR, a probabilistic machine learning tool that integrates these 51 genomic features using a nested Random Forest architecture to infer seven clinically relevant DDR subgroups. After negating model overfit concerns, CHIMERA-DDR showed exceptional classification performance (AUCs 0.919-0.999) to accurately detect MMRd and HRR mutant molecular subtypes with or without concurrent DDR deficiencies, resolving admixed phenotypes to enable precision therapeutic stratification beyond binary methods.

genomics↗

SMTrackR: a R/Bioconductor package for mapping protein binding at individual DNA molecules

Single-molecule assays like NOMe-seq, dSMF and Nanopore are superior to DNase-seq and ATAC-seq as they do not nibble down DNA. Thus, they enable quantification of all three i.e., protein-free, Transcription Factor-bound and histone-complex-bound states. But a user-friendly tool to visualize and quantify such states is lacking. Here, we present, SMTrackR, a Bioconductor package to visualize protein-DNA binding states on individual sequenced DNA molecules. SMTrackR queries the single-molecule footprint database we built and hosted at Galaxy Server. It comprises of BigBed files generated from NOMe-seq, dSMF, and Nanopore (SMAC-seq) datasets. SMTrackR exploits UCSC REST API to query a BigBed file and plot footprint heatmap categorized in different binding states as well as report their occupancies. Additionally, this package generates a Gviz-enabled script to visualize these single-molecules on gene tracks. Availability and implementationThe SMTrackR tool is implemented the statistical programming language R and is available at the GitHub developer site, https://github.com/satyanarayan-rao/SMTrackR. The tool is also available in a web version https://smtrackr.iitr.ac.in. A function is provided to use local BigBed file for users who wish to use unpublished data. A fully automated pipeline to generate such BigBed files is available at https://github.com/satyanarayan-rao/SMF_for_SMThub and https://github.com/satyanarayan-rao/dSMF_for_SMThub.

bioinformatics↗

dioscRi enables transferable prediction of clinical outcomes in multi-parameter cytometry data

Multi-parameter cytometry technologies enable high-dimensional analysis of immune cell populations at single-cell resolution. Deep learning has emerged as a transformative tool for analyzing these datasets, but existing methods often struggle with transferability across datasets due to technical variability, batch effects and identification of biologically relevant cell populations, limiting their utility in clinical research. We present dioscRi, a transferable deep learning framework that integrates a maximum mean discrepancy variational autoencoder for normalization and de-noising, enhancing cross-dataset compatibility. Changes in cell type proportions and marker expression are identified by structuring these features within biologically or empirically derived cell type hierarchies. These hierarchies are incorporated directly into an overlapping group LASSO model, improving the prediction of clinical outcomes. When applied to a coronary artery disease study, dioscRi recapitulated several known immune associations. Benchmarking across multiple datasets demonstrated dioscRis ability to generalize and outperform existing methods, establishing it as a versatile and interpretable tool for cytometry data analysis.

bioinformatics↗

Arg80 Orchestrates a Metabolic-Translational Proteostasis Network in S. cerevisiae

Proteostasis or protein homeostasis is essential for cellular function and organismal health. While many models of cytosolic proteostasis emphasize heat shock response as critical for regulating cellular protein folding, a comprehensive understanding of transcriptional modules that may regulate cytosolic protein folding is lacking. Through a focused screening for transcription factors, we provide evidence that a number of transcriptional programs unlinked to canonical proteotoxic response are involved in maintaining cellular homeostasis of protein folding. Among these, Arg80, a regulator of arginine metabolism, was activated during proteotoxic stress and found essential for mitigating it. We show that proteostasis imbalance in arg80{Delta} cells is caused by excess arginine accumulation, which is sufficient to impair protein folding. We reveal a complex interplay between arginine repression (Arg80), trehalose biosynthesis (Tps2), and the integrated stress response (Gcn2) in combating proteotoxic insults. We posit that multiple metabolic pathways integrate with classical protein quality control networks to regulate the protein folding environment. Harnessing these metabolic circuits may offer new avenues to modulate proteostasis when needed.

systems biology↗

Liver Kinome Profiling Identifies PS1145 as a Potential Therapeutic molecule for amelioration of Systemic Inflammation in Alcohol-related Liver Disease

Background and aimsAlcohol-related liver disease (ALD) has high mortality due to systemic inflammation. We analysed liver and monocyte kinome profiles in a chronic ethanol-fed pre-clinical rat model to identify therapeutic targets that could mitigate inflammation in ALD. MethodKinome profile was performed in liver and circulating monocytes at baseline, and after 8,12,16,20 and 24-weeks of 40% ethanol administration. Pathway-specific inhibitors, including PS1145 (IKK-phosphorylation inhibitor), PH-797804 (MAPK14 inhibitor), resveratrol and prednisolone were tested for their anti-inflammatory effects in ALD-rats, PBMC from patients and NIAAA mouse model. ResultsKinome profiling identified 497 liver and 345 monocyte kinases in ALD rats (FDR<0.01). A time-dependent increase in MAPK14-associated kinases was observed in both tissues (FC>1.5, p<0.05). By 24 weeks, 172 liver and 48 monocyte kinases were significantly upregulated, particularly those linked to MyD88-TLR4, PI3K-Akt, TNF, TGF{beta}, and cellular senescence pathways. Key contributors included TGF{beta}R1, ROS-generating kinases, and IL-1-driven MAPK14 and IKK phosphorylation. Targeting this axis, PS1145 (an IKK inhibitor) suppressed NF{kappa}B activation and inflammation in THP1 and HepG2 cells, as well as PBMCs from healthy and SAH patients, outperforming PH797804, resveratrol, and prednisolone (p<0.05, FC>1.5). PS1145 significantly reduced IL-6, TNF, and NF{kappa}B, while increasing IL-10. In vivo, PS1145 treatment in the NIAAA mouse model markedly reduced hepatic steatosis, cellular stress and inflammatory pathways (cytokine signalling, IL-36 signalling and others) more effectively than standard therapies, Notably, it also downregulated IL36R, impairing TLR receptor dimerization, suggesting a dual mechanism of action (p<0.05) highlighting its therapeutic potential in ameliorating systemic inflammation in ALD. ConclusionOur study highlights the key role of MAPK14 and MYD88-TLR4 pathway kinases in driving systemic inflammation in SAH. The IKK inhibitor PS1145, by blocking both IKK phosphorylation and TLR dimerization, effectively suppresses inflammatory signalling and improves liver pathology, positioning it as a promising targeted therapy for ALD.

pharmacology and toxicology↗

Phytoene synthase modulates seed longevity via the action of β-carotene derived metabolites

Seed longevity, the seeds ability to stay viable over time, is an important trait in agriculture. Despite extensive research, seed longevity remains one of the fundamental topics in plant biology. Here, we discovered the novel role of carotenoid metabolites in prolonging seed lifespan. We found that phytoene synthase (PSY), the gene encoding a major rate-limiting enzyme in carotenoid biosynthesis, modulated seed storability in Arabidopsis under both natural and artificial aging conditions. Seeds from the PSY overexpression (OE) lines exhibited significantly enhanced lifespan with low levels of reactive oxygen species (ROS), a major factor affecting longevity, whereas those from the psy mutants had decreased viability with high ROS levels. While lutein and {beta}-carotene were detected in seeds, only {beta}-carotene and its derived apocarotenoids, i.e. {beta}-cyclocitral and {beta}-ionone, were found to improve seed lifespan. Notably, the carotenoid cleavage dioxygenase 1 and 4 (ccd1 ccd4) double mutant and PSY ccd1 ccd4 seeds showed significantly reduced seed longevity, indicating that {beta}-carotene cleavage is necessary for or it is apocarotenoids playing the role in preserving seed lifespan. Comparative proteomic analysis identified TIP2;2, an aquaporin protein, which showed differential abundances in seeds of PSY OE and psy mutant vs wild type. The mutant tip2;2 had reduced seed longevity, and its promoter was transactivated by apocarotenoids. Collectively, this study uncovers a novel role of apocarotenoids in protecting seed longevity and highlights the importance of seed carotenoid production in strengthening agriculture. One Sentence SummaryPhytoene synthase, the gene encoding a major rate-limiting enzyme in carotenoid biosynthesis, modulates seed longevity via {beta}-carotene derived apocarotenoids and an aquaporin protein TIP2;2 identified is a new player that responds to apocarotenoid signaling and influences seed longevity.

plant biology↗

Translational buffering tunes gene expression in mouse and human

BackgroundTranslational buffering refers to the regulation of ribosome occupancy to offset the effects of transcriptional variation. While previous studies have primarily investigated translational buffering in yeast under genetic variation or environmental stress, it remains unclear how widespread this is across mammalian genes in various cellular contexts. ResultsWe performed a uniform analysis of 1,515 matched ribosome profiling and RNA-seq datasets from humans and mice. This resource enabled us to assess translational buffering through comparative analysis of variation in ribosome occupancy and RNA expression, and by examining the relationship between mRNA abundance and translation efficiency. We found that translational buffering is partly conserved between humans and mice; homologous genes showed moderate cross-species correlation in mRNA-translation efficiency relationships and strong enrichment of shared buffered genes, particularly those encoding ribosomal, RNA-binding, and proteasomal proteins. Although identified buffered genes associate with specific sequence features, these alone are insufficient to predict translational buffering, highlighting the importance of cellular context. Genes exhibiting translational buffering show lower variation in protein abundance in cancer cell lines and tissues. We also observed that translationally buffered genes are more likely to be haploinsufficient and triplosensitive, suggesting a demand for stringent dosage limits. ConclusionsWe hypothesize two models of translational buffering, namely the "differential accessibility model" and the "translation initiation rate model", suggesting that different transcripts align with one or the other. Our study explores the translational buffering potential of genes across diverse conditions, elucidates their distinctive features, and provides insights into the mechanisms driving this effect.

bioinformatics↗

Neural sensitivity to the heartbeat is modulated by spontaneous fluctuations in subjective arousal during wakeful rest

Spontaneous thoughts, occupying much of ones awake time in daily life, are often colored by emotional qualities. While spontaneous thoughts have been associated with various neural correlates, the relationship between subjective qualities of ongoing experiences and the brains sensitivity to bodily signals (i.e., interoception) remains largely unexplored. Given the well-established role of interoception in emotion, clarifying this relationship may elucidate how processes relevant to mental health, such as arousal and anxiety, are regulated. We used EEG and ECG to measure the heartbeat evoked potential (HEP), an index of interoceptive processing, while 51 adult participants (34 male, 20 female) visually fixated on a cross image and let their minds wander freely. At pseudo-random intervals, participants reported their momentary level of arousal. This measure of affective arousal was highly variable within and between individuals but was statistically unrelated to several markers of physiological arousal, including heart rate, heart rate variability, time on task, and EEG alpha power at posterior electrodes. A cluster-based permutation analysis revealed that the HEP amplitude was increased during low relative to high affective arousal in a set of frontal electrodes during the 340 - 356 millisecond window after heartbeat onset. This HEP effect was more pronounced in individuals who reported high, relative to low, levels of trait anxiety. Together, our results offer novel evidence that at varying levels of trait anxiety, the brain differentially modulates sensitivity to bodily signals in coordination with the momentary, spontaneous experience of affective arousal--a mechanism that may operate independently of physiological arousal. Significance StatementOur findings highlight the relationships between spontaneous fluctuations in affective arousal, brain-body interactions, and anxiety, offering new insights into how interoception fluctuates with changes in internal states. By showing that interoceptive processing is heightened during lower affective arousal and that this effect is amplified in individuals with higher trait anxiety, our study suggests the brain adaptively downregulates interoceptive sensitivity in response to fluctuating internal states. These results have implications for understanding how spontaneous thoughts shape interoception and emotion, particularly in clinical contexts where dysregulated interoception is linked to anxiety and mood disorders. More broadly, our work underscores the need to distinguish between different forms of arousal, advancing understanding of the taxonomy and ways of measuring arousal.

neuroscience↗

Intranasal Human NSC-derived EVs Therapy in Late Middle Age Can Restrain the Activation of NLRP3 Inflammasome and cGAS-STING Signaling in the Aged Hippocampus

Neuroinflammaging, a moderate, chronic, and sterile inflammation in the hippocampus, contributes to age-related cognitive decline. Neuroinflammaging comprises the activation of the nucleotide-binding domain, leucine-rich repeat family, and pyrin domain-containing 3 (NLRP3) inflammasomes, and the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway that triggers type 1 interferon (IFN-1) signaling. Studies have shown that extracellular vesicles from human induced pluripotent stem cell-derived neural stem cells (hiPSC-NSC-EVs) contain therapeutic miRNAs that can alleviate neuroinflammation. Therefore, this study examined the effects of late middle-aged (18-month-old) male and female C57BL6/J mice receiving two intranasal doses of hiPSC-NSC-EVs on neuroinflammaging in the hippocampus at 20.5 months of age. Compared with animals receiving vehicle treatment, the hippocampus of animals receiving hiPSC-NSC-EVs exhibited reductions in astrocyte hypertrophy, microglial clusters, and oxidative stress, along with elevated expression of antioxidant proteins and genes that maintain mitochondrial respiratory chain integrity. Moreover, hiPSC-NSC-EVs therapy decreased the levels of various proteins involved in the activation of the NLRP3 inflammasome, p38/mitogen-activated protein kinase, cGAS-STING-IFN-1, and Janus kinase and signal transducer and activator of transcription signaling pathways. Furthermore, in vitro assays using genetically engineered RAW cells and hiPSC-NSC-EVs, with or without targeted depletion of specific miRNAs, demonstrated that miRNA-30e-3p and miRNA-181a-5p, both present in hiPSC-NSC-EVs, can significantly inhibit the activation of the NLRP3 inflammasome and the STING pathway, respectively. Additionally, single-cell RNA sequencing conducted 7 days post-treatment revealed that hiPSC-NSC-EVs induce widespread transcriptomic changes in microglia, including increased expression of numerous genes that enhance oxidative phosphorylation and reduced expression of abundant genes that drive multiple proinflammatory signaling pathways. These changes mediated by hiPSC-NSC-EVs were also associated with improved cognitive and memory function. Thus, intranasal hiPSC-NSC-EVs therapy in late middle age can effectively diminish proinflammatory microglial transcriptome and signaling cascades that drive neuroinflammaging in the hippocampus, contributing to better brain function in old age.

neuroscience↗

Integrated Cross-Disease Atlas of Human And Mouse Astrocytes Reveals Heterogeneity and Conservation of Astrocyte Subtypes in Neurodegeneration

Astrocytes play a pivotal role in central nervous system homeostasis and neuroinflammation. Despite advancements in single-cell analyses, the heterogeneity of reactive astrocytes in neurodegenerative diseases, particularly across species, remains understudied. Here, we present an integrated atlas of 187,000 astrocytes from mouse models of Alzheimers (AD) and multiple sclerosis (MS) alongside 438,000 astrocytes from AD, MS, and Parkinsons (PD) patients. Our analysis identified four distinct mouse astrocyte clusters, including two disease-associated astrocyte (DAA) clusters, DAA1 and DAA2. DAA1 displayed reactivity resembling responses to acute stimuli, including endotoxemia, while DAA2 expressed well-known AD risk genes. In an AD model, DAA1 and DAA2 exhibited distinct spatial relationships to amyloid plaques. In humans, we identified eight distinct astrocyte clusters, encompassing homeostatic and disease-associated subtypes. Cross-species analysis linked disease-associated clusters while also highlighting divergent expression in others. Our astrocyte atlas is available through a user-friendly, searchable website: http://research-pub.gene.com/AstroAtlas/.

neuroscience↗

Global and genetic regulation of gene expression in human endothelial and vascular smooth muscle cells

BackgroundThe understanding of genetic and epigenetic regulation of gene expression in endothelial and vascular smooth muscle cells remains fragmented with limited experimental validation. MethodsChromatin conformation (Micro-C), DNA methylation (RRBS), chromatin accessibility (ATAC-seq), and transcriptome profiles (RNA-seq) were mapped in human induced pluripotent stem cell (hiPSC)-derived, isogenic endothelial and vascular smooth muscle cells (iECs and iVSMCs). CTCF and RAD21 were depleted to assess the functional relevance of chromatin architecture, and genome editing was used to evaluate the allelic effect of a blood pressure-associated single nucleotide polymorphism (SNP). ResultsSignificant correlations were identified between gene expression levels and chromatin interactions, chromatin accessibility, and DNA methylation in iECs and iVSMCs, with chromatin interactions showing the strongest association. Chromatin contact regions displayed distinct epigenetic landscapes depending on the types of regulatory element interactions involved. Perturbation of CTCF and RAD21 revealed their differential regulatory effects, particularly on the expression of genes overlapping chromatin contacts, with RAD21 exhibiting a broader regulatory impact. SNPs associated with several vascular traits were enriched in chromatin loops or accessible regions in iECs or iVSMCs. Precise genome editing demonstrated allele-dependent effects of SNP rs9833313 on the expression of SHOX2 located 247.4 kbp away but within the same chromatin loops as the SNP. ConclusionThis study provides an extensive epigenetic landscape of vascular cells that may drive novel research on the role of genetic and epigenetic mechanisms of vascular function and disease as demonstrated by our targeted experiments.

genomics↗