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PubMed2025

p53 Regulates Nuclear Architecture to Reduce Carcinogen Sensitivity and Mutagenic Potential.

The p53 tumor suppressor is an indispensable regulator of DNA damage responses that accelerates carcinogenesis when mutated. In this report, we uncover a new mechanism by which p53 maintains genomic integrity in the absence of canonical DNA damage response activation. Specifically, loss of p53 dramatically alters chromatin structure at the nuclear periphery, allowing increased transmission of an environmental carcinogen, ultraviolet (UV) radiation, into the nucleus. Genome-wide mapping of UV-induced DNA lesions in p53-deficient primary cells reveals elevated lesion abundance in regions corresponding to locations of high mutation burden in malignant melanomas. These findings uncover a novel role of p53 in the suppression of mutations that contribute to cancer and highlight the critical influence of nuclear architecture in regulating sensitivity to carcinogens.

Journal Article↗
PubMed2025

Serum, Cell-Free, HPV-Human DNA Junction Detection and HPV Typing for Predicting and Monitoring Cervical Cancer Recurrence.

Almost all cervical cancers are caused by human papillomaviruses (HPVs). In most cases, HPV DNA is integrated into the human genome. We found that tumor-specific, HPV-human DNA junctions are detectable in serum cell-free DNA of a fraction of cervical cancer patients at the time of initial treatment and/or at six months following treatment. Retrospective analysis revealed these junctions were more frequently detectable in women in whom the cancer later recurred. We also found that cervical cancers caused by HPV types outside of phylogenetic clade α9 had a higher recurrence frequency than those caused by α9 types in both our study and The Cancer Genome Atlas cervical cancer database, despite the higher prevalence of α9 types including HPV16 in cervical cancer. Thus, HPV-human DNA junction detection in serum cell-free DNA and HPV type determination in tumor tissue may help predict recurrence risk. Screening serum cell-free DNA for junctions may also offer an unambiguous, non-invasive means to monitor absence of recurrence following treatment.

DNA integration↗
PubMed2025

Prediction and functional interpretation of inter-chromosomal genome architecture from DNA sequence with TwinC.

Three-dimensional nuclear DNA architecture comprises well-studied intra-chromosomal (cis) folding and less characterized inter-chromosomal (trans) interfaces. Current predictive models of 3D genome folding can effectively infer pairwise cis-chromatin interactions from the primary DNA sequence but generally ignore trans contacts. There is an unmet need for robust models of trans-genome organization that provide insights into their underlying principles and functional relevance. We present TwinC, an interpretable convolutional neural network model that reliably predicts trans contacts measurable through proximity ligation-dependent (in situ and intact Hi-C) and independent (DNA SPRITE) genome-wide chromatin conformation assays. . TwinC uses a paired sequence design from replicate Hi-C experiments to learn single base pair relevance in trans interactions across two stretches of DNA. The method achieves high predictive accuracy (AUROC=0.80) on a cross-chromosomal test set from in situ and intact Hi-C experiments in heart tissue. Furthermore, we train TwinC using in situ Hi-C data from the widely used GM12878 cell line and validate its performance with orthogonal DNA SPRITE assay in the same cell type. Mechanistically, the neural network learns the importance of compartments, chromatin accessibility, clustered transcription factor binding and G-quadruplexes in forming trans contacts. In summary, TwinC models and interprets trans genome architecture, shedding light on this poorly understood aspect of gene regulation.

Journal Article↗
PubMed2024

The Human Cytomegalovirus vGPCR UL33 is Essential for Efficient Lytic Replication in Epithelial Cells.

Human cytomegalovirus (HCMV) is a β-herpesvirus which is ubiquitous in the human population. HCMV has the largest genome of all known human herpesviruses, and thus encodes a large array of proteins that affect pathogenesis in different cell types. Given the large genome and the ability of HCMV to replicate in a range of cells, investigators have begun to identify viral proteins required for cell type-specific replication. There are four proteins encoded in the HCMV genome that are homologous to human G protein-coupled receptors (GPCRs); these viral-encoded GPCRs (vGPCRs) are UL33, UL78, US27, and US28. In the current study, we find that deletion of all four vGPCR genes from a clinical isolate of HCMV severely attenuates lytic replication in both primary human salivary gland epithelial cells, as well as ARPE-19 retinal epithelial cells as evidenced by significant decreases in immediate early gene expression and virus production. Deletion of UL33 from the HCMV genome also results in a failure to efficiently replicate in epithelial cells, and this defect is manifested by decreased levels of immediate early, early, and late gene expression, as well as reduced viral production. We find that similar to US28, UL33 constitutively activates Gαq-dependent PLC-β signaling to high levels in these epithelial cells. We also find that UL33 transcription is more complicated than originally believed, and there is the potential for the virus to utilize various 5' UTRs to create novel UL33 proteins that are all capable of constitutive Gαq signaling. Taken together, these studies suggest that UL33 driven signaling is important for lytic HCMV replication in cells of epithelial origin.

Journal Article↗
PubMed2025

Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair.

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, and Hi-C, and karyotyping. In future publications, these data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.

Journal Article↗
PubMed2025

scooby: Modeling multi-modal genomic profiles from DNA sequence at single-cell resolution.

Understanding how regulatory DNA elements shape gene expression across individual cells is a fundamental challenge in genomics. Joint RNA-seq and epigenomic profiling provides opportunities to build unifying models of gene regulation capturing sequence determinants across steps of gene expression. However, current models, developed primarily for bulk omics data, fail to capture the cellular heterogeneity and dynamic processes revealed by single-cell multi-modal technologies. Here, we introduce scooby, the first framework to model scRNA-seq coverage and scATAC-seq insertion profiles along the genome from sequence at single-cell resolution. For this, we leverage the pre-trained multi-omics profile predictor Borzoi as a foundation model, equip it with a cell-specific decoder, and fine-tune its sequence embeddings. Specifically, we condition the decoder on the cell position in a precomputed single-cell embedding resulting in strong generalization capability. Applied to a hematopoiesis dataset, scooby recapitulates cell-specific expression levels of held-out genes, and identifies regulators and their putative target genes through in silico motif deletion. Moreover, accurate variant effect prediction with scooby allows for breaking down bulk eQTL effects into single-cell effects and delineating their impact on chromatin accessibility and gene expression. We anticipate scooby to aid unraveling the complexities of gene regulation at the resolution of individual cells.

Journal Article↗
PubMed2025

Ancestry and somatic profile predict acral melanoma origin and prognosis.

Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

Journal Article↗
PubMed2025

Galvanin (TMEM154) is an electric-field sensor for directed cell migration.

Directed cell migration of immune and epithelial cells is critical for their rapid response to tissue injury or infection. Endogenous electric fields generated by disruption of the transepithelial potential across the skin have been postulated to play an important role in guiding cells to wound sites, though how individual cells sense these tissue-scale physical cues remains largely unknown. We have identified Galvanin (TMEM154), a previously uncharacterized single-pass transmembrane protein, as being required for electric-field-guided migration of individual rapidly moving cells. Galvanin functions in both immune and epithelial cell types. Upon exposure of cells to an electric field, Galvanin rapidly relocalizes to the anodal side of a cell, and the net charge on its extracellular domain is necessary and sufficient to drive this spatial relocalization. Furthermore, expression of Galvanin is sufficient to confer electric field-guided migration on otherwise non-responsive epithelial cells. In human neutrophils, we show that Galvanin relocalization is immediately followed by changes in the spatial pattern of cellular protrusion and retraction. The strong directional response of these cells is lost upon truncation of Galvanin's intracellular domain, suggesting that Galvanin acts as a direct sensor of the electric field, transducing spatial information about a cell's electrical environment to the intracellular migratory apparatus. This sensor relocalization mechanism of cell steering defines a new paradigm for directed cell migration.

Journal Article↗
PubMed2025

Decoding the biogenesis of HIV-induced CPSF6 puncta and their fusion with the nuclear speckle.

Viruses rely on host cellular machinery for replication. After entering the nucleus, the HIV genome accumulates in nuclear niches where it undergoes reverse transcription and integrates into neighboring chromatin, promoting high transcription rates and new virus progeny. Despite antiretroviral treatment, viral genomes can persist in these nuclear niches and reactivate upon treatment interruption, raising the possibility that they could play a role in the establishment of viral reservoirs. The post-nuclear entry dynamics of HIV remain unclear, and understanding these steps is critical for revealing how viral reservoirs are established. In this study, we elucidate the formation of HIV-induced CPSF6 puncta and the domains of CPSF6 essential for this process. We also explore the roles of nuclear speckle scaffold factors, SON and SRRM2, in the biogenesis of these puncta. Through genetic manipulation and depletion experiments, we demonstrate the key role of the intrinsically disordered region of SRRM2 in enlarging nuclear speckles in the presence of the HIV capsid. We identify the FG domain of CPSF6 as essential for both puncta formation and binding to the viral core, which serves as the scaffold for CPSF6 puncta. While the low-complexity regions (LCRs) modulate CPSF6 binding to the viral capsid, they do not contribute to puncta formation, nor do the disordered mixed charge domains (MCDs) of CPSF6. Interestingly, the FG peptide facilitates viral replication. These results demonstrate how HIV evolved to hijack host nuclear factors, enabling its persistence in the host. Of note, this study provides new insights into the underlying interactions between host factors and viral components, advancing our understanding of HIV nuclear dynamics and offering potential therapeutic targets for preventing viral persistence.

Journal Article↗
PubMed2025

rbfox1 LoF mutants show disrupted bdnf/trkb2 and crhb/nr3c2 expression and increased cortisol levels during development coupled with signs of allostatic overload in adulthood.

Mutations in the RBFOX1 gene are associated with psychiatric disorders but how RBFOX1 influences psychiatric disorder vulnerability remains unclear. Recent studies showed that RBFOX proteins mediate the alternative splicing of PAC1, a critical HPA axis activator. Further, RBFOX1 dysfunction is linked to dysregulation of BDNF/TRKB, a pathway promoting neuroplasticity, neuronal survival, and stress resilience. Hence, RBFOX1 dysfunction may increase psychiatric disorder vulnerability via HPA axis dysregulation, leading to disrupted development and allostatic overload. To test this hypothesis, we generated a zebrafish rbfox1 loss of function (LoF) line and examined behavioural and molecular effects during development. We found that rbfox1 LoF mutants exhibited hyperactivity, impulsivity and heightened arousal, alongside alterations in proliferation - traits associated with neurodevelopmental and stress-related disorders. In adults, loss of rbfox1 function led to decreased fertility and survival, consistent with allostatic overload. At the molecular level, at larval stages rbfox1 mutants showed increased cortisol levels and disrupted expression of key stress-related genes (bdnf, trkb2, pac1a-hop, crhb, nr3c2). Pharmacological intervention targeting TRKB restored crhb and nr3c2 gene expression and hyperactive and hyperarousal behaviours. In adults, dysregulation of crhb, nr3c2 and bdnf/trkb2 genes was only seen following acute stress exposure. Our findings reveal a fundamental role for RBFOX1 in integrating stress responses through its regulation of BDNF/TRKB and neuroendocrine signalling.

Journal Article↗
PubMed2025

Tunable, proteolytic dosage control of CRISPR-Cas systems enables precise gene therapy for dosage sensitive disorders.

The ability to modulate gene expression through modular and universal genetic tools like CRISPR-Cas has greatly advanced gene therapy for therapeutics and basic science. Yet, the inherent stochasticity of delivery methods cause variation in target gene expression at the single-cell level, limiting their applicability in systems that require more precise expression. Thus, we implement a modular incoherent feedforward loop based on proteolytic cleavage of Cas to reduce gene expression variability against the variability of vector delivery. We target a genome-integrated marker and demonstrate dosage control of gene activation and repression, post-delivery tuning, and RNA-based compatibility of the system. To illustrate therapeutic relevance, we target the gene RAI1, the haploinsufficiency and triplosensitivity of which cause two autism-related syndromes. We demonstrate dosage-controlled gene activation for both human and mouse Rai1 via viral delivery to patient-derived cell lines and mouse cortical neurons. Overall, we established a robust dosage control circuit for uniform gene expression, beneficial for basic and translational research.

Journal Article↗
PubMed2025

Orthrus: Towards Evolutionary and Functional RNA Foundation Models.

In the face of rapidly accumulating genomic data, our ability to accurately predict key mature RNA properties that underlie transcript function and regulation remains limited. Pre-trained genomic foundation models offer an avenue to adapt learned RNA representations to biological prediction tasks. However, existing genomic foundation models are trained using strategies borrowed from textual domains that do not leverage biological domain knowledge. Here, we introduce Orthrus, a Mamba-based mature RNA foundation model pre-trained using a novel self-supervised contrastive learning objective with biological augmentations. Orthrus is trained by maximizing embedding similarity between curated pairs of RNA transcripts, where pairs are formed from splice isoforms of 10 model organisms and transcripts from orthologous genes in 400+ mammalian species from the Zoonomia Project. This training objective results in a latent representation that clusters RNA sequences with functional and evolutionary similarities. We find that the generalized mature RNA isoform representations learned by Orthrus significantly outperform genomic foundation models on mRNA property prediction tasks, and requires only a fraction of fine-tuning data to do so. Finally, we show that Orthrus is capable of capturing divergent biological function of individual transcript isoforms.

Journal Article↗
PubMed2025

Extensive longevity and DNA virus-driven adaptation in nearctic Myotis bats.

The genus Myotis is one of the largest clades of bats, and exhibits some of the most extreme variation in lifespans among mammals alongside unique adaptations to viral tolerance and immune defense. To study the evolution of longevity-associated traits and infectious disease, we generated cell lines and near-complete genome assemblies for 8 closely related species of Myotis. Using genome-wide screens of positive selection, analyses of structural variation, and functional experiments in primary cells, we identify new patterns of adaptation contributing to longevity, cancer resistance, and viral interactions in bats. We show that the recurrent evolution of longevity seen in Myotis leads to some of the highest predicted increases in cancer risk across mammals and demonstrate a unique DNA damage response in primary cells of the long-lived M. lucifugus. We also find evidence of abundant adaptation in response to DNA viruses - but not RNA viruses - in Myotis and other bats in sharp contrast with other mammals, potentially contributing to the role of bats as reservoirs of zoonoses. Together, our results demonstrate how genomics and primary cells derived from diverse taxa uncover the molecular bases of extreme adaptations in non-model organisms.

Aging↗
PubMed2024

Cryo-electron tomography reveals coupled flavivirus replication, budding and maturation.

Flaviviruses replicate their genomes in replication organelles (ROs) formed as bud-like invaginations on the endoplasmic reticulum (ER) membrane, which also functions as the site for virion assembly. While this localization is well established, it is not known to what extent viral membrane remodeling, genome replication, virion assembly, and maturation are coordinated. Here, we imaged tick-borne flavivirus replication in human cells using cryo-electron tomography. We find that the RO membrane bud is shaped by a combination of a curvature-establishing coat and the pressure from intraluminal template RNA. A protein complex at the RO base extends to an adjacent membrane, where immature virions bud. Naturally occurring furin site variants determine whether virions mature in the immediate vicinity of ROs. We further visualize replication in mouse brain tissue by cryo-electron tomography. Taken together, these findings reveal a close spatial coupling of flavivirus genome replication, budding, and maturation.

Journal Article↗
PubMed2025

Carafe enables high quality in silico spectral library generation for data-independent acquisition proteomics.

Data-independent acquisition (DIA)-based mass spectrometry is becoming an increasingly popular mass spectrometry acquisition strategy for carrying out quantitative proteomics experiments. Most of the popular DIA search engines make use of in silico generated spectral libraries. However, the generation of high-quality spectral libraries for DIA data analysis remains a challenge, particularly because most such libraries are generated directly from data-dependent acquisition (DDA) data or are from in silico prediction using models trained on DDA data. In this study, we developed Carafe, a tool that generates high-quality experiment-specific in silico spectral libraries by training deep learning models directly on DIA data. We demonstrate the performance of Carafe on a wide range of DIA datasets, where we observe improved fragment ion intensity prediction and peptide detection relative to existing pretrained DDA models. To make Carafe more accessible to the community, we have integrated Carafe into the widely used Skyline tool.

Journal Article↗
PubMed2025

Automated Deep Learning-Based Detection of Early Atherosclerotic Plaques in Carotid Ultrasound Imaging.

BACKGROUND: Carotid plaque presence is associated with cardiovascular risk, even among asymptomatic individuals. While deep learning has shown promise for carotid plaque phenotyping in patients with advanced atherosclerosis, its application in population-based settings of asymptomatic individuals remains unexplored. METHODS: We developed a YOLOv8-based model for plaque detection using carotid ultrasound images from 19,499 participants of the population-based UK Biobank (UKB) and fine-tuned it for external validation in the BiDirect study (N = 2,105). Cox regression was used to estimate the impact of plaque presence and count on major cardiovascular events. To explore the genetic architecture of carotid atherosclerosis, we conducted a genome-wide association study (GWAS) meta-analysis of the UKB and CHARGE cohorts. Mendelian randomization (MR) assessed the effect of genetic predisposition to vascular risk factors on carotid atherosclerosis. RESULTS: Our model demonstrated high performance with accuracy, sensitivity, and specificity exceeding 85%, enabling identification of carotid plaques in 45% of the UKB population (aged 47-83 years). In the external BiDirect cohort, a fine-tuned model achieved 86% accuracy, 78% sensitivity, and 90% specificity. Plaque presence and count were associated with risk of major adverse cardiovascular events (MACE) over a follow-up of up to seven years, improving risk reclassification beyond the Pooled Cohort Equations. A GWAS meta-analysis of carotid plaques uncovered two novel genomic loci, with downstream analyses implicating targets of investigational drugs in advanced clinical development. Observational and MR analyses showed associations between smoking, LDL cholesterol, hypertension, and odds of carotid atherosclerosis. CONCLUSIONS: Our model offers a scalable solution for early carotid plaque detection, potentially enabling automated screening in asymptomatic individuals and improving plaque phenotyping in population-based cohorts. This approach could advance large-scale atherosclerosis research.

atherosclerosis↗
PubMed2025

Large future genetic diversity losses are predicted even with habitat protection.

Genetic diversity within species is the basis for evolutionary adaptive capacity and has recently been included as a target for protection in the United Nations' Global Biodiversity Framework (GBF). However, we lack large-scale mathematical frameworks to quantify how much genetic diversity has already been lost, let alone to predict future losses under 21st century conservation scenarios. To fill this gap, we developed an area-based spatio-temporal predictive framework of genetic diversity calibrated with population-scale genomic data of 29 plant and animal species. To estimate present genetic diversity loss with our framework, we used species' habitat area and population sizes losses reported in the Living Planet Index, the Red List, and new GBF indicators across 13,808 species for the last 5 decades. Applying our evolutionary framework across these species, we estimate genetic diversity loss lags behind population and habitat area declines, with an estimated current 13-22% π genetic diversity loss. However, we forecast future genetic diversity losses will reach 41-76% even if populations are not further contracted. These results highlight that safeguarding existing habitats is insufficient to maintain the genetic health of species and relying solely on continuous genetic monitoring underestimates lagging long term impacts.

Genetic diversity↗
PubMed2024

A Transcriptional Signature of Induced Neurons Differentiates Virologically Suppressed People Living With HIV from People Without HIV.

Neurocognitive impairment is a prevalent and important co-morbidity in virologically suppressed people living with HIV (PLWH), yet the underlying mechanisms remain elusive and treatments lacking. Here, we explored for the first time, use of participant-derived directly induced neurons (iNs) to model neuronal biology and injury in PLWH. iNs retain age- and disease-related features of the donors, providing unique opportunities to reveal novel aspects of neurological disorders. We obtained primary dermal fibroblasts from six virologically suppressed PLWH (range: 27 - 64 years, median: 53); 83% Male; 50% White) and seven matched people without HIV (PWOH) (range: 27 - 66, median: 55); 71% Male; 57% White). iNs were generated using transcription factors NGN2 and ASCL1, and validated by immunocytochemistry and single-cell-RNAseq. Transcriptomic analysis using bulk-RNAseq identified 29 significantly differentially expressed genes between iNs from PLWH and PWOH. Of these, 16 genes were downregulated and 13 upregulated in PLWH iNs. Protein-protein interaction network mapping indicates that iNs from PLWH exhibit differences in extracellular matrix organization and synaptic transmission. IFI27 was upregulated in iNs from PLWH, which complements independent post-mortem studies demonstrating elevated IFI27 expression in PLWH-derived brain tissue, indicating that iN generation reconstitutes this pathway. Finally, we observed that expression of the FOXL2NB-FOXL2-LINC01391 genome locus is reduced in iNs from PLWH and negatively correlates with neurocognitive impairment. Thus, we have identified an iN gene signature of HIV through direct reprogramming of skin fibroblasts into neurons revealing novel mechanisms of neurocognitive impairment in PLWH.

HAND↗