Biology subjects

Kim, S.

Publications and source records attributed to Kim, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Real-time electrochemical protein monitoring using molecular pendulum sensors

Continuous monitoring of proteins in complex biological fluids is essential for advancing personalized medicine, yet existing biosensors are often limited by instability, single-use designs, and insufficient sensitivity. Here, we describe a detailed protocol for the fabrication and operation of molecular pendulum (MP) electrochemical sensors integrated with an active-reset mechanism to enable real-time, reversible, and ultrasensitive protein detection. The protocol is described in two parts. First, we describe the microfabrication of gold microelectrodes and their nanostructured modification, followed by assembly of DNA-based pendulum probes with redox reporters and affinity receptors that translate binding into kinetic electron-transfer shifts. Second, we detail the sensing and active-reset approach, which detects the target analyte and applies tunable oscillatory potentials to accelerate its dissociation, regenerate sensor surfaces, and extend operational lifetime. The protocol includes detailed guidance on device fabrication, surface functionalization, sensing and reset cycles, and data analysis. When implemented, MP sensors with active-reset achieve pg/ml sensitivity, rapid equilibration, and robust performance across biofluids and in situ models, enabling continuous protein monitoring over extended periods. This combined technology represents a biosensing platform with significant potential, opening new avenues for wearable and implantable molecular monitoring, early disease detection, and personalized therapeutic guidance.

bioengineering↗

bioRxiv2026

Systematic modeling of phenotypic drug response profiles inpatient-derived organoids

Patient-derived tumor organoids provide a physiologically relevant 3D disease model for preclinical drug discovery, surpassing the limitations of conventional 2D cell lines. To better capture the dynamic nature of organoid drug responses, we developed a new systematic evaluation method called SCOPE (Systematic Classification of Organoids for Phenotypic Evaluation), harnessing phenotypic assessments from multi-timepoint 3D imaging data. By integrating artificial intelligence (AI)-based image analysis of organoid viability with tracking and mathematical modeling of organoid growth over time, we captured temporal-and dose-dependent dynamics of phenotypic changes, culminating in two novel metrics: a combined growth and viability (GV) score as well as a cytostatic-cytotoxic transition range (CCTR) that separates drug effects on organoid growth and viability. Our approach supports classification of specific drug responses into four distinct phenotypic groups: (1) cytotoxic, (2) cytostatic plus cytotoxic, (3) late cytotoxic, and (4) cytostatic. This novel drug evaluation system can identify previously unknown drug effects or new therapeutic use cases for existing drugs, facilitating the design of alternative therapeutic options to overcome efficacy or drug resistance challenges and improving the clinical applicability of organoid-based drug discovery results.

bioengineering↗

bioRxiv2026

Fast remote nucleotide sequence alignment with Riboseek

Structure prediction has reached RNA, where generating deep alignments is now the bottleneck. We developed Riboseek, a search and alignment tool for RNA and DNA that represents sequences as overlapping di-mers. Riboseek is more sensitive for homology detection than BLASTN and nhmmer, and generates alignments 250- and 376-fold faster than nhmmer and rMSA. With structure-aware realignment, it approaches rMSAs base-pair recovery, while remaining 29-fold faster. We provide a web server and 1.7 million precomputed alignments for putatively structured RNAs. Riboseek is freely available at https://github.com/steineggerlab/riboseek.

bioinformatics↗

bioRxiv2026

Cyclic-Phe-Pro Binds the ToxRS Interface to Promote Signal Transduction in Vibrio vulnificus

In Vibrio vulnificus, the quorum-sensing signal cyclo-(L-phenylalanine-L-proline) (cFP) binds the membrane receptor ToxRS to activate genes linked to oxidative-stress resistance and virulence. ToxR is a transmembrane transcription factor that pairs with ToxS to sense periplasmic signals, yet how V. vulnificus ToxRS recognizes cFP has remained undefined. AI-guided structure prediction revealed preferential ToxR/S heterodimer formation and a fold conserved with the V. cholerae crystal structure. Molecular docking placed cFP in a hydrophobic pocket at the ToxR-ToxS interface, where Phe279 stacked with its phenyl ring and Arg277 hydrogen-bonded its carbonyl oxygen. Introducing R277L and F279A substitutions lowered basal leuO expression and abolished cFP-dependent induction in a lacZ fusion assay. ChIP showed that cFP enhanced wild-type ToxR binding to the leuO promoter, whereas the mutant bound weakly and did not respond. Thus cFP bridges ToxR and ToxS to stabilize the heterodimer, facilitating ToxR recruitment to promoters and transcriptional activation in V. vulnificus.

biochemistry↗

bioRxiv2026

Representative vs. Load-bearing Layers: A Dissociation in Genomic Foundation Models

Downstream use of genomic foundation models follows one of three conventions: aggregating representations across all layers (Pearce et al., 2026), defaulting to the last hidden state as a fixed feature extractor (Dalla-Torre et al., 2024), or picking a single intermediate layer via mechanistic-interpretability tooling (Brixi et al., 2026). None of these examines which layer a joint classifier actually relies on. We probe this question with a minimal training-free scalar, ||{Delta}h{ell}||2, defined as the L2 norm of the per-layer hidden-state shift at the variant token. We evaluate it on 8,008 ClinVar (Landrum et al., 2018) single-nucleotide variants in NT-v2 500M (Dalla-Torre et al., 2024), a masked language model (MLM), and Evo 2 7B (Brixi et al., 2026), a causal language model (CLM) with a hyena/attention hybrid. In both models the layer with peak single-feature AUROC (the representative layer) is not the layer a joint multi-layer classifier most depends on (the load-bearing layer, identified by leave-one-layer-out ablation drop and concordant with |SHAP| (Lundberg & Lee, 2017)). Representative layers sit mid-network in both models, whereas load-bearing depth lies at opposite ends of the depth axis: mid-shallow in the MLM, and deep in the CLM hybrid. The dissociation has direct downstream consequences. In NT-v2, a 1-dimensional mid-layer scalar exceeds the canonical 1024-dimensional last-layer mean-pool base-line by +0.049 AUROC. In Evo 2, the 4096-dimensional mean-pool is competitive with the joint ||{Delta}h{ell}||2 feature, so standard last-layer pooling leaves variant-relevant signal untapped specifically in MLM-based pipelines.

bioinformatics↗

bioRxiv2026

GDTR: Layer-wise Settling Depth Reveals Biological Grammar in Genomic Foundation Models

Genomic foundation models capture sequence regularities, yet existing interpretability tools rarely ask where in the layer stack a biological grammar becomes stable. We introduce GDTR (Genomic Deep-Thinking Ratio), a training-free residual-stream lens that assigns each nucleotide token a settling depth c(t): the first layer at which its representation stabilises against the post-final-norm reference. On Evo 2 7B, splice donor and acceptor sites settle approximately two layers earlier than intronic contexts, enhancer-like cCREs show a smaller but measurable shift, and a chr22 calibration transfers to held-out chr17. Perturbing canonical splice donors shows that the signal is bidirectional: disrupting the central GT motif deepens settling, whereas shuffling the flanking grammar makes the preserved motif settle earlier. Differential GDTR further reveals consequence-associated peak-disruption depths across ClinVar variants, with synonymous substitutions peaking deepest but with broad class overlap. GDTR therefore provides a layer-wise interpretability axis for genomic foundation models, complementary to existing prediction and variant-scoring tools.

bioinformatics↗

bioRxiv2026

Structure-guided design of a CD81-binding mini-protein that blocks hepatitis C virus entry

Despite the success of direct-acting antivirals, preventing hepatitis C virus (HCV) reinfection remains a critical global challenge. To address this, we leveraged deep learning-based de novo protein design to engineer mini-proteins targeting the large extracellular loop (LEL) of the HCV co-receptor CD81. These mini-proteins are predicted to precisely dock into CD81-LEL, occluding the critical binding interface required for the HCV E2 glycoprotein. Through biophysical screening, we identified mini-19, a lead candidate with sub-nanomolar affinity (KD = 0.5 nM) and high thermostability up to 95{degrees}C. Flow cytometry and super-resolution imaging confirmed that mini-19 specifically recognizes the native topology of CD81 on cells and extracellular vesicles. Functionally, mini-19 neutralized HCVcc infection (IC50 = 1.2 nM). Molecular dynamics simulations demonstrated that mini-19 acts as a structural clamp, restricting the fusogenic conformational plasticity of the receptor. By targeting a conserved host factor rather than the rapidly mutating viral envelope, mini-19 provides a high genetic barrier to resistance. Beyond offering a prophylactic strategy against HCV, our findings establish a stable biologic platform for targeting tetraspanin-enriched microdomains and modulating host-pathogen interactions.

bioengineering↗

bioRxiv2026

UVfinder: a tool to extract bryophyte sex-linked gene copies from the GoFlag408 probe set

PremiseTarget enrichment sequencing using probe sets like GoFlag 408 has revolutionized phylogenetics, yet recent genomic data indicate that some probes may be sex-linked, potentially introducing topological conflict but also allowing studies of sex-specific evolutionary processes. To test for sex-linkage across the bryophytes, we developed UVfinder, a pipeline designed to identify sex-linked GoFlag loci across published moss genomes and enable sex-aware downstream analyses. Methods and ResultsApplying UVfinder to 50 dioicous moss genomes,we identified 93 probes that exhibit sex-linkage in one or more lineages. Our results provide genomic evidence for neo-sex chromosome formation via autosome-sex chromosome fusion and gene translocation. By comparing species trees derived from sex-linked versus autosomal loci in Hypnales and Dicranidae, we demonstrate that sex-linked loci harbor phylogenetic information that is distinct from that in autosomes. We also discovered a pervasive female sampling bias perhaps reflecting a preference among collectors for plants with sporophytes. ConclusionsOur findings highlight the dynamism in sex linkage across bryophytes and suggest that sex-aware phylogenomics can be used to reconstruct ancestral karyotypes and potentially resolve topological conflict. We also expect that UVfinder will facilitate study of sex specific evolutionary processes, particularly with improved genome assemblies and increased sampling in males.

bioinformatics↗

bioRxiv2026

Desktop-Scale Hit-Point Discovery for Intrinsically Disordered α-Synuclein Using State-Space Compression and a Discrete Phase-Interference Search Operator

The accessible chemical space dwarfs any tractable screening budget, and most artificial intelligence drug discovery pipelines respond by docking and ranking a small sublibrary. The resulting hit list is agnostic to selectivity, brain penetration, toxicity, synthetic accessibility, and chemical novelty. We present ISTP-DPISO DrugEngine, an end-to-end engine developed by ISTP Tech that integrates the Local Information Criticality Principle (LICP) with a Discrete Phase-Interference Search Operator (DPISO). We demonstrate the engine on the intrinsically disordered protein (IDP) -synuclein, whose non-amyloid-component (NAC, residues 61-95) drives Parkinson-associated aggregation. The resulting LICP active set focuses the expensive LICP-DPISO scoring: in a production-scale run, the engine compressed a ~8.46x108-molecule mirror to a 10,000,000-molecule active set (~85-fold) before scoring, then converged to a compact, safety-gated shortlist plus de novo designs. The entire campaign ran on a single desktop workstation, without any high-performance-computing cluster. Three engine-prioritized, commercially available candidates (2-D08, Uralenol, Herbacetin) and an (-)-epigallocatechin gallate (EGCG) positive control were then tested in a thioflavin-T (ThT) aggregation assay at 100 {micro}M: all three engine-nominated candidates suppressed -synuclein aggregation, giving perfect prospective inhibitor-call concordance (3/3 nominated); together with the EGCG positive control, all four assayed compounds inhibited aggregation (4/4 total), two by [≤]80% plateau reduction. ISTP-DPISO DrugEngine reframes virtual screening from post-hoc score fusion to a single, state-space-compressed, safety-gated, experimentally validated discovery pipeline.

bioinformatics↗

bioRxiv2026

A genetic toolkit to reduce wheat immunogenicity and incidence of celiac disease

Celiac disease (CeD) is an immune-mediated condition triggered by wheat gluten in genetically predisposed individuals. The immune reaction in people with CeD is driven by particular gluten amino acid sequences, or immunogenic epitopes. Some of these epitopes elicit strong immune responses in the majority of CeD patients and are designated as immunodominant epitopes. Previous research has shown correlations between the amount of immunogenic wheat epitopes consumed and the onset of CeD, suggesting that reducing wheat immunogenic epitopes may reduce CeD incidence at the population level. Gluten consists of gliadins and glutenins, with gliadins having the majority of the immunodominant epitopes and glutenins playing a major role in dough strength and breadmaking quality (BMQ). This study used radiation-induced deletions, chemical mutagenesis, and natural variation in wheat (Triticum aestivum) to generate genetic stocks with reduced immunogenic epitope content. Most lines were developed in the wheat cultivar Summit, for which we produced a full genome assembly and annotation. We used exome capture to characterize these deletions and identify prolamins located within and outside the deletions. We combined different deletions and developed molecular markers to facilitate their deployment. For chromosome arms 1BS and 1DS, we generated two alternative lines: one lacking immunogenic epitopes for the development of CeD-safe genetic stocks for research purposes, and another retaining selected glutenins for breeding commercial lines with reduced immunogenicity and adequate BMQ. By making these non-transgenic genetic stocks publicly available, we aim to accelerate the development of wheat varieties with reduced immunogenicity and, eventually, a fully CeD-safe wheat.

plant biology↗

bioRxiv2026

DNA Polymerase Beta Catalytic and Fidelity Mutations Drive Platinum Specific Drug Sensitivity

With the advent of genome sequencing and its widespread use in the clinic, there is a great need to identify mutational biomarkers that predict therapeutic responses. DNA polymerase Beta (Pol{beta}) and the base excision repair (BER) pathway have been previously implicated as modulators of response to platinum-based chemotherapies and are mutated in as high as 30% of cancers. Here, we show in a triple-negative breast cancer (TNBC) model that two classes of mutations in Pol{beta}, reduced catalytic activity (E295K and D256A mutation) and reduced fidelity (I260M), are sufficient to drive cisplatin and carboplatin-specific sensitivity. Cellular response to oxaliplatin in these Pol{beta} mutant models is minimal relative to cisplatin and carboplatin. Additionally, we show that sensitivity is associated with reduced repair of both platinum-induced DNA intrastrand adducts and interstrand crosslinks (ICLs). Downregulation of the upstream BER factor uracil DNA glycosylase (UNG) reverses drug sensitivity consistent with these Pol{beta} mutations negatively impacting ICL DNA repair to drive drug sensitivity. In addition, intrastrand adduct repair readout indicates these lesions also play a role in the sensitivity observed in Pol{beta} mutant models. In vivo studies demonstrate a significant effect on tumor growth delay with cisplatin treatment in tumor xenografts harboring Pol{beta} mutations. These results support the potential for using Pol{beta} mutations as predictive biomarkers for cisplatin and carboplatin therapies in the clinical setting.

Cancer Biology↗

bioRxiv2026

Pore-Resolved High-Throughput Quantification of Amyloid Aggregation and Amplification

Amyloid fibrils are implicated in a wide spectrum of neurodegenerative and systemic disorders, yet their biological consequences are governed not only by total fibril content but also by how fibrillar species are organized, clustered, and amplified within heterogeneous populations. Conventional thioflavin T (ThT)-based assays provide sensitive sample-level readouts of {beta}-sheet-rich material but offer limited access to the local population structure underlying amyloid aggregation and amplification. Here, we introduce the Amyloid Pore Quantification (APQ) chip, a pore-resolved geometric partitioning platform that converts heterogeneous amyloid assembly states into fluorescence intensity distributions across thousands of defined pore-level units. Using hen egg-white lysozyme as a model amyloid-forming protein, we combine length-controlled truncated amyloid nanofibrils with vacuum-assisted ThT infiltration to establish a reproducible pore fluorescence intensity reference. APQ provided quantitative concentration-dependent calibration across a 50-fold concentration range, enabling bulk-comparable quantification while preserving pore-level distribution information. Deviations from this reference resolved pH-dependent fibril clustering near the isoelectric point as pore-signal suppression and accessibility loss, captured pepsin-associated fibrillar amplification as a population-wide increase in pore intensity, and distinguished monomer- and oligomer-driven fibril processing through coupled amplification-aggregation fingerprints. When benchmarked against ensemble fluorescence measurements and AFM morphological analysis, APQ revealed assembly-state changes that were not fully represented by sample-level ThT intensity alone. These results establish APQ as a high-throughput, distribution-aware analytical framework for translating amyloid aggregation and amplification into quantitative pore-resolved fingerprints.

bioengineering↗

bioRxiv2026

Human meningiomas arise from developmental meningeal mosaicism

Meningioma is the most common primary intracranial tumour, yet its genetic origin and the temporal sequence of mutational events remain poorly defined. Here, we analysed 80 triple-matched tumour, histologically normal meninges, and blood samples from 22 patients. NF2 or TRAF7 driver mutations are detectable in phenotypically normal meninges in 81.8% of cases (95% CI: 59.7-94.8%; VAF [~]0.02%), corroborated by high-depth sequencing, single-cell cloning, and phylogenetic analysis. By distinguishing developmental mosaic mutations from postnatal tumour-private mutations, we revealed distinct mutational signatures and resolved the temporal sequence of meningioma evolution. The developmental origin was further underscored in patients with multiple meningiomas, where identical driver mutations were shared across genomically distinct tumours and meninges, and in intraventricular meningiomas (IVM), where driver mutations were detected in distant cranial dura. Reconstruction of mutational timing revealed lineage-specific trajectories, linking mosaicism to diverse disease presentations including solitary meningioma, IVM, meningiomatosis, and NF2-related schwannomatosis. Together, these findings reveal an early origin of human meningioma, in which developmental mosaicism establishes a pre-neoplastic field within the meninges, providing a developmental framework for adult tumourigenesis.

Cancer Biology↗

bioRxiv2026

Mtf2 Safeguards Naïve Pluripotency by Restricting Trophectoderm Competence

The first fate decision in mammalian embryos segregates embryonic and extraembryonic lineages, establishing a largely irreversible transition from totipotency to pluripotency. The mechanisms that enforce this unidirectionality remain incompletely understood. Here, we identify the PRC2.1 subunit Mtf2 as a key epigenetic barrier that safeguards lineage fidelity in naive embryonic stem cells (ESCs). Despite globally elevated H3K27me3 levels in naive ESCs, loss of Mtf2 derepresses trophectoderm (TE) regulators, enhances cellular plasticity, generating both ICM- and TE-like populations. Mtf2-deficient cells readily acquire expanded potential with extraembryonic competence and form blastoids without trophoblast stem cell supplementation, whereas loss of the PRC2.2 subunit Jarid2 has minimal effects. Integrated CUT&Tag and transcriptomic analyses reveal that Mtf2 directly represses TE-associated genes in naive ESCs. Thus, reduced Mtf2 occupancy permits their activation in expanded potential states. Collectively, our findings establish Mtf2 as a central epigenetic barrier that stabilizes naive pluripotency and restricts inappropriate acquisition of extraembryonic fate.

Developmental Biology↗

bioRxiv2026

CAREPath: Semantic Context-Aware Reasoning Paths with Mechanism-Augmented Embeddings for Drug Repurposing

Biomedical knowledge graphs (BKGs) that include drugs, genes, and diseases support drug repurposing by connecting drugs to diseases through gene-mediated multi-hop paths, thereby enabling mechanism-of-action reasoning. However, deeper traversal does not necessarily improve mechanistic reasoning: long paths grow combinatorially and frequently pass through hub genes, producing irrelevant gene regulatory signals, whereas overly constrained or sparse paths may miss broader biological context. We propose CAREPath, a KG-LLM framework inspired by depth-first search (DFS)-like and breadth-first search (BFS)-like reasoning to balance mechanistic specificity, scalability, and context recovery. The DFS-like module constrains traversal to short disease-gene-drug paths, converts each path into a structured prompt, and encodes it with a biomedical language model to generate semantic path embeddings. Complementarily, the BFS-like module constructs entity-level mechanism-context embeddings from one-hop gene neighborhoods and enriches them through similarity-guided augmentation using pharmacologically related drugs and gene-signature-similar diseases. Across five biomedical KGs, CAREPath achieves the best overall AUPRC among 18 baselines, improving performance by up to 3.8%. Additional analyses show that semantic short-path encoding contributes most to performance, while mechanism-context augmentation improves robustness under sparse evidence and strengthens Gene Ontology functional agreement. Case studies and recently FDA-approved indications further demonstrate its practical relevance, positioning CAREPath as an interpretable framework for scalable and mechanism-aware drug repurposing. Source code is available at https://github.com/hamppy-song/CAREPath.

bioinformatics↗

bioRxiv2026

ProMiSE: Protein Multi-State Evaluation Benchmark in Biological Contexts

Proteins are inherently dynamic, with biological functions often emerging from transitions between multiple conformational states. While recent breakthroughs have largely addressed the static structure prediction problem, no systematic benchmark exists to demonstrate how well current models capture functionally relevant dynamics. We introduce ProMiSE, the first benchmark that provides both a dataset and an evaluation scheme, based on native biological assemblies and integrating major conformational change mechanisms--intrinsic, ligand-induced, and protein-induced--within a single curated dataset. We conducted a comprehensive evaluation of state-of-the-art structure prediction models, including Al-phaFold3 and recent generative approaches. Our findings reveal that current models exhibit a limited ability to sample intrinsic multi-states and are often insensitive to biological context in induced scenarios. Internal representation analysis suggests that training-data exposure can shift predictions toward dominant conformational states over alternative biologically relevant states, primarily at the structure module. In contrast, results from BioEmu indicate that reducing decoding-stage bias can substantially improve multi-state sampling without major changes to upstream pair representations.

bioinformatics↗

bioRxiv2026

Capsinoids (non-pungent TRPV1 agonists) promote mild hypothermia and improved outcome following stroke in aged mice

Background and PurposeMild hypothermia provides potent neuroprotection in experimental ischemic stroke, however, its implementation in awake stroke patients is hampered by the induction of intense shivering and inconsistent body temperature control. Pharmacological activation of peripheral/peritoneal TRPV1 channels with non-pungent capsinoids offers a means to induce hypothermia while minimizing TRPV1 activation in the injury region. We tested whether capsinoid-mediated mild hypothermia, initiated within the post-stroke period, reduces brain injury and improves functional outcomes in aged mice. MethodsAged (18-20 months) male and female C57BL/6 mice underwent either permanent distal middle cerebral artery (MCA) occlusion (pdMCAO) or 60-minute MCA occlusion/reperfusion (MCAO/R). At 2 or 4 hours after stroke, mice received intraperitoneal injections of vehicle or capsinoids (>97% purity; 40 mg/kg) every 90 minutes to induce mild hypothermia for 4.5-6 hours. Core temperature was monitored by wireless probe. After pdMCAO, infarct volume was quantified at post-stroke day 3 (PSD3) by TTC and brain atrophy at PSD30 by iodine-enhanced microCT; sensorimotor function (DigiGait, forelimb grip strength, foot fault) was assessed at PSD7 and PSD30. Survival was the primary measured outcome for MCAO/R. ResultsCapsinoids induced a rapid and sustained reduction in core temperature of 2-4{degrees}C, independent of sex. In the pdMCAO model, capsinoid-induced hypothermia reduced infarct volume by 48% at PSD3 and decreased chronic cortical tissue loss by 44% at PSD30. Capsinoid-treated mice showed significant improvements in gait, grip strength, and contralateral foot fault performance at PSD7 and PSD30. In the MCAO/R model, survival was significantly higher in capsinoid-treated mice (80%) versus vehicle controls (33%) through PSD3. ConclusionsIntraperitoneal capsinoid administration after stroke induces mild hypothermia in aged mice and confers robust acute neuroprotection and improved chronic functional outcome and survival. These preclinical findings add support for the use of capsinoids as a means to target peripheral thermoeffectors for promoting neuroprotective hypothermia in conscious stroke subjects.

neuroscience↗

bioRxiv2026

eQTM (expression quantitative trait methylation) Atlas: a comprehensive resource of over 11 million DNA methylation-gene expression associations through across 11 tissues and 4 diseases

MotivationEpigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. ResultsWe developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG-searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. Availability and implementationThe eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/. The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas.

genetics↗