Biology subjects

Jensen, M.

Publications and source records attributed to Jensen, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Transcriptomic analysis reveals differential regulation of synaptic components in pediatric and adult brain tumors

Neuronal-cancer cell interactions are a key component of brain tumor pathophysiology, yet many fundamental questions remain unanswered, with even more remaining unasked. Here, we present a comprehensive brain tumor reference map generated from bulk RNA-seq data of ~4,300 adult and pediatric brain tumors, including various glioma subtypes, medulloblastomas, ependymomas, and meningiomas, alongside ~1,400 healthy brain samples. By analyzing synaptic processes and synaptic gene expression across tumor types, we reveal the complexity of neuron-tumor crosstalk and its potential impact on patient survival. Our findings identify key synaptic signaling pathways and dysregulated patterns in brain tumors, including HNRNPH2 upregulation, a key factor in RNA processing and metabolism, in gliomas and medulloblastomas. Additionally, we highlight the role of cholinergic signaling, particularly CHRNA9, as a driver of glioma progression, which is also upregulated in WNT and Group 4 medulloblastomas, ependymomas, and meningiomas. Furthermore, P2 purinergic signaling emerges as a key player in glioma progression. These insights lay the groundwork for future studies exploring whether targeting these pathways could reprogram the tumor microenvironment toward an anti-tumor state, ultimately leading to novel therapeutic strategies and improved patient outcomes.

cancer biology↗

bioRxiv2026

A pan-cohort transcriptional landscape of breast cancer maps subtype and microenvironmental programs

Breast cancer comprises heterogeneous transcriptional states that are incompletely captured by discrete clinical or molecular subtype labels. To visualize this heterogeneity in a unified framework, we integrated bulk RNA-seq data from 2,284 patient samples across 13 studies using 18,089 protein coding genes, a harmonized processing pipeline, batch correction, consensus clustering and PaCMAP dimensionality reduction to construct an interactive breast cancer transcriptional landscape. Consensus clustering identified five major regions, which were annotated using PAM50 scores calculated for each sample: Luminal A, Luminal B, HER2 enriched, and two basal associated clusters. The basal clusters separated into an immune rich region marked by T cell-inflamed, tumor-associated macrophages (TAM), and low-purity signatures, and a cell-cycle driven region enriched for proliferation and DNA replication programs. Overlay of marker genes, pathways, kinases, neuronal like signaling programs, cancer associated fibroblasts (CAF) states, and TAM programs revealed spatially organized subtype biology and microenvironmental heterogeneity. Finally, projection of therapy associated resistance signatures identified landscape regions linked to predicted resistance to HER2-targeted therapy and hormone receptor directed endocrine therapies. By enabling interactive exploration of transcriptional states, marker genes, pathways, and therapeutic response programs, this resource provides a community framework for biomarker discovery in breast cancer.

bioinformatics↗

bioRxiv2026

Population-scale Y chromosome assemblies reveal recurrent remodeling within constrained architectures

The human Y chromosome is among the most structurally dynamic chromosomes in the human genome, yet much of its diversity remains unresolved because of extensive palindromes, ampliconic gene families, satellite-rich heterochromatin and large segmental duplications. What remained unclear was how these diverse forms of variation fit together across the full chromosome, how often similar structures recur in different lineages, and which aspects of organization remain constrained despite rapid sequence turnover. Here, we generated and analyzed 142 nearly complete human Y chromosome assemblies from 17 major haplogroups spanning approximately 180,000 years of evolution, creating a population-scale resource for studying Y chromosome biology and diversity. These assemblies show that structural change on the Y chromosome is recurrent but constrained, even in its most repetitive regions. In the fertility-associated azoospermia factor c (AZFc) region, recurrent inversions, deletions, and complex rearrangements generate a limited repertoire of structural haplotypes. Multicopy ampliconic gene families follow distinct evolutionary paths: DAZ paralogues differ in structural constraint, RBMY evolves within a modular array, and TSPY copy number varies mainly through local expansion and contraction. The centromere and Yq12 heterochromatin vary greatly in size but retain a stable higher-order organization, including a single hypomethylated centromeric core and conserved Yq12 repeat composition and orientation. Methylation across palindromic and ampliconic regions is likewise structured by repeat class, copy order and local architecture. Together, these results provide a population-scale resource for the human Y chromosome and show that its rapid structural evolution is repeatedly funneled into a limited set of architectural outcomes.

genomics↗

bioRxiv2026

Beyond Histology: A Unified Transcriptomic Atlas Defines Lung Cancer Biologic States and Subtypes

Lung cancer encompasses multiple histological entities with substantial molecular heterogeneity that remain incompletely resolved at population scale. Here, we constructed a unified reference landscape of lung cancer by analyzing raw RNA sequencing data from 1,824 tumors spanning adenocarcinoma (n=966), squamous cell carcinoma (n=628), small cell lung cancer (n=150), and unclassified non small cell lung cancer (n=80). Following batch correction, samples were analyzed using consensus clustering and visualized with PaCMAP to generate a molecular atlas annotated with clinical and biological metadata. Rather than segregating by pathological diagnosis, tumors organized along conserved transcriptional axes defined by tumor-intrinsic biology including proliferative or metabolic programs and immune-infiltrated states. Consensus clustering resolved nine robust molecular clusters, including an adenocarcinoma-associated subgroup, a neuroendocrine-like adenocarcinoma marked by ASCL1 activation, immune-associated regions, and bifurcation of both small cell and squamous carcinomas into biologically distinct states. Spatially restricted expression of selected clinically relevant transcripts nominated state-specific therapeutic hypotheses requiring future functional and clinical validation. Projection of patient tumors and patient-derived xenografts onto the atlas demonstrated preservation of transcriptional identity and enabled quantitative assessment of model fidelity. This integrated framework organizes lung cancer as a structured continuum of transcriptional states and provides a reference resource for biological interpretation and future translational studies.

bioinformatics↗

bioRxiv2025

Open Raman Microscopy (ORM): A Modular Hardware and Software Framework for Accessible Raman Imaging

Raman microscopy is a label-free, non-destructive imaging tool for spatially resolved chemical fingerprinting. Its powerful ability to reveal molecular information has driven rapid growth in applications across fields as varied as materials science, environmental analysis, and biomedical research. Despite its versatility, the accessibility of Raman microscopy is limited by expensive commercial setups and the technical barriers faced by researchers attempting to build custom systems. Here, we introduce an Open Raman Microscopy (ORM) framework based on a readily accessible modular microscopy platform. The ORM platform provides configurations for both high-throughput imaging and confocal imaging. We developed a dedicated python-based control and acquisition software, the ORM-Integrated Raman and Imaging Software (ORM-IRIS) designed to accommodate modular integration and control of components, including the laser source, spectrometer, and translational stages. Implemented across three institutions we demonstrate the ORM platform for high-throughput imaging of articular cartilage tissue, confocal three-dimensional imaging of a zebrafish embryo, and imaging of gold colloid decorated surfaces for surface enhanced Raman spectroscopy. Together, this open-source hardware and software framework enhances the accessibility of Raman microscopy across an expanding range of scientific applications.

biophysics↗

bioRxiv2025

Quantifying the impact of genetic mutations on enhancer dynamics

Transcriptional regulation is mediated by enhancers, yet how genetic perturbations alter enhancer activity and gene expression remains poorly understood. We developed UDI-UMI-STARR-seq, which integrates dual indexes and unique molecular identifiers, and combined it with RNA-seq to profile the effects of perturbations on enhancer activity and target gene expression. We applied this approach to a library of 253,632 fragments representing 46,142 cell type-specific candidate enhancers and assessed the impact of CRISPR/Cas9-mediated deletion of six transcription factors (or TFs; ATF2, CTCF, FOXA1, LEF1, TCF7L2, and SCRT1) with diverse regulatory roles. Across knockout lines, we identified responsive enhancers that were either repressed or induced, often through motifs such as the p53 family of TFs. Enhancer-gene mapping revealed TF-specific programs, including repression of Wnt/p53 targets with ATF2 or LEF1 loss, downregulation of the FIRRE locus with CTCF loss, and compensatory upregulation of RNA polymerase II regulators following FOXA1 depletion. A deep learning model trained on enhancer sequences recapitulated core principles of enhancer grammar, including cooperative motif syntax and the influence of flanking sequence context. Applying this framework to the neurodevelopmental disorder-associated 16p12.1 deletion identified responsive enhancers linked to genes involved in axon guidance, synaptic plasticity, and translational control, providing a scalable readout of enhancer dynamics generalizable to genetic mutations.

genomics↗

bioRxiv2025

Low Dose GLP-1 Therapy Attenuates Pathological Cardiac and Hepatic Remodelling in HFpEF Independent of Weight Loss

BACKGROUND AND AIMSHeart failure with preserved ejection fraction (HFpEF) remains a therapeutic challenge. GLP-1 receptor agonists (GLP-1RAs) show clinical promise, and the prevailing hypothesis is that their benefits are primarily driven by weight loss and the downstream benefits of improved functional status. We investigated the weight loss-independent effects of low-dose GLP-1RA therapy in a clinically relevant rodent model of severe cardiometabolic HFpEF. METHODSTen-week-old male ZSF1 obese rats with spontaneous HFpEF were treated with low-dose semaglutide (30 nmol/kg twice weekly, n=6) or vehicle for 16 weeks. Comprehensive assessments included body weight, 2-D echocardiography, invasive hemodynamics, exercise capacity as well as cardiac and hepatic fibrosis and lipid deposition. The study utilized advanced multi-omics approaches, including single-cell RNA sequencing of the heart and liver, as well as cardiac, hepatic and plasma proteomics, to explore underlying mechanisms. RESULTSIn ZSF1 obese rats, low-dose semaglutide in the absence of weight loss, significantly improved cardiac function, exercise tolerance, and attenuated fibrosis in the heart and liver. Interestingly, semaglutide therapy reduced cardiac and hepatic lipid content as well as lipid droplets in cardiac myocytes and hepatocytes. Mechanistically, multi-omics analyses of cardiac and hepatic tissues revealed that semaglutide exerted these benefits by improving cardiac metabolism, interfering with pro-fibrotic and pro-hypertrophic signals, and by reducing systemic inflammation. CONCLUSIONSLow-dose semaglutide provides significant cardioprotective, hepatoprotective, and metabolic benefits in HFpEF independent of weight loss. Our findings support the investigation of lower GLP-1RA dosing in HFpEF and other cardiovascular conditions, including in non-obese patients, to expand the clinical utility of these potent drugs. Translational PerspectiveWe demonstrate that low-dose semaglutide attenuates HFpEF-mediated pathological cardiac and hepatic remodelling in HFpEF independently of the weight loss effects of GLP-1 receptor activation. Primary mechanisms are attenuated cardiac and hepatic fibrosis and reverse lipid transport. These findings provide a mechanistic basis for the direct cardiovascular actions of GLP-1RAs, revealing their potential to modulate key disease drivers like fibrosis and lipotoxicity. These data support the use of lower, better-tolerated doses of GLP-1RAs to treat HFpEF, potentially benefiting a wider range of patients, including those who are not obese or who suffer from side effects with current GLP-1 regimens.

pharmacology and toxicology↗

bioRxiv2025

Generalized brain-state modeling with KenazLBM

The large-scale functional state of a human brain remains difficult to characterize, much less predict. Regardless, techniques have been engineered to electrically neuromodulate the brain to treat a subset of neurologic and psychiatric disorders with moderate efficacy. Accurate characterization of a brains instantaneous functional state has stymied the development of more effective neuromodulation paradigms. Advanced computational methods are required to address this gap and enable large-scale neuroscience. Here we define the concept of generalized brain-state modeling across humans as Large Brain-State Modeling (LBM) and present KenazLBM as the worlds first example. KenazLBM can instantaneously characterize the functional state of a persons brain with raw iEEG data, and predict future brain-states. KenazLBM was trained on over 17.9 billion unique multichannel tokens from people undergoing intracranial electroencephalography (iEEG) recordings, and has learned to interrelate brain-states between people into a common interpretable topology. Most importantly, the model generalizes to unseen subject data with significant recording channel heterogeneity from the training set. We offer KenazLBM as a first generalized brain-state model to serve as a new paradigm of basic neuroscience inquiry and potential translation into neuromodulation therapeutics.

neuroscience↗

bioRxiv2025

Wilms tumor 1 impairs apoptotic clearance of fibroblasts in distal fibrotic lung lesions

Idiopathic pulmonary fibrosis (IPF) is a fatal fibrotic lung disease characterized by impaired fibroblast clearance and excessive extracellular matrix (ECM) protein production. Wilms Tumor 1 (WT1), a transcription factor, is selectively upregulated in IPF fibroblasts. However, the mechanisms by which WT1 contributes to fibroblast accumulation and ECM production remain unknown. Here, we investigated the heterogeneity of WT1-expressing mesenchymal cells using single-nucleus RNA sequencing of distal lung tissues from IPF patients and control donors. WT1 was selectively upregulated in a subset of IPF fibroblasts that co-expressed several pro- survival and ECM genes. The results of both loss-of-function and gain-of-function studies are consistent with a role for WT1 as a positive regulator of pro-survival genes to impair apoptotic clearance and promote ECM production. Fibroblast-specific overexpression of WT1 augmented fibroproliferation, myofibroblast accumulation, and ECM production during bleomycin-induced pulmonary fibrosis in young and aged mice. Together, these findings suggest that targeting WT1 is a promising strategy for attenuating fibroblast expansion and ECM production during fibrogenesis.

pathology↗

bioRxiv2025

A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity

Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow defined cellular trajectories across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cellular trajectory regionalises tumours into distinct tissue niches and manifests in a molecularly conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to map cancer cell states jointly with clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

cancer biology↗

bioRxiv2025

SPAC: a scalable, integrated enterprise platform for end-to-end single cell spatial analysis of multiplexed tissue imaging

BackgroundMultiplexed tissue imaging enables the simultaneous detection of dozens of proteins at single-cell resolution, providing unprecedented insights into tissue organization and disease microenvironments. However, the resulting high-dimensional, gigabyte-scale datasets pose significant computational and methodological challenges. Existing analytical workflows, often fragmented between bespoke scripts and static visualizations, lack the scalability and user-friendly interfaces required for efficient, reproducible analysis. To overcome these limitations, we developed SPAC (analysis of SPAtial single-Cell datasets), a scalable, web-based ecosystem that integrates modular pipelines, high-performance computing (HPC) connectivity, and interactive visualization to democratize end-to-end single-cell spatial analysis applied to cellular positional data and protein expression levels. ResultsSPAC is built on a modular, layered architecture that leverages community-based and newly developed tools for single-cell and spatial proteomics analysis. A specialized Python package extends these functionalities with custom analysis routines and established software engineering practices. An Interactive Analysis Layer provides web-hosted pipelines for configuring and executing complex workflows, and scalability enhancements that support distributed or parallel execution on GPU-enabled clusters. A Real-Time Visualization Layer delivers dynamic dashboards for immediate data exploration and sharing. As a showcase of its capabilities, SPAC was applied to a 4T1 breast cancer model, analyzing a multiplex imaging dataset comprising 2.6 million cells. GPU acceleration reduced unsupervised clustering runtimes from several hours to under ten minutes, and real-time visualization enabled detailed spatial characterization of tumor subregions. ConclusionsSPAC effectively overcomes key challenges in spatial single-cell analysis by streamlining high-throughput data processing and spatial profiling within an accessible and scalable framework. Its robust architecture, interactive interface and ease of access have the potential to accelerate biomedical research and clinical applications by converting complex imaging data into actionable biological and clinical insights.

bioinformatics↗

bioRxiv2025

Approximating Signal Sources in Stereo-EEG Single Pulse Electrical Stimulation using Re-referencing and Spectral Analysis

Stereoelectroencephalography (sEEG) is a method of epilepsy monitoring that uses stereotactically placed depth electrodes. Connectivity between brain regions may be assessed by delivering a current pulse from sEEG electrode(s) and monitoring all other electrodes for Brain Stimulation-Evoked Potentials (BSEPs). However, the shape, magnitude, and spectral content of BSEPs are sensitive to the analysis approaches used to study them. In order to understand the nuance between analysis and interpretation of BSEP data, we carefully apply and contrast modified common average & bipolar re-referencing techniques, combined with wavelet-based spectral analysis on measured data from 4 human subjects. Comparison between analysis approaches allows us to identify recording sites within, near, or far from the tissue source of the BSEPs they record. We further explore the interaction between re-referencing techniques and dipole source orientation, providing methods to estimate source location and upper bound of far field recordings. This systematic application and comparison of different analysis tools can enable those who study BSEPs to localize potential sources within, near, or far from measurement sites, and more accurately constrain how brain connectivity is understood from stimulation experiments.

neuroscience↗

bioRxiv2025

Uptake of fucosylated type I human milk oligosaccharide blocks by Bifidobacterium longum subsp. infantis

Human milk oligosaccharides (HMOs) are uniquely rich in the type 1 building block disaccharide lacto-N-biose I (LNB, Gal{beta}1,3GlcNAc), as compared to other mammals. Most HMOs are fucosylated, e.g., 1,2 and 1,4 fucosylations on LNB blocks, resulting in H type 1 (H1) and Lewis a (Lea) epitopes, respectively. The dominance of Bifidobacterium in breastfed infant guts hinges on efficient uptake of HMOs by specific ATP-binding cassette (ABC) importers. However, molecular insight into uptake of fucosylated LNB blocks is lacking. Here, we analyzed the uptake of LNB and its fucosylated H1 and Lea trisaccharides, as well as the mucin-derived disaccharide galacto-N-biose (GNB, Gal{beta}1,3GalNAc) by an ABC importer form the HMO-utilization specialist Bifidobacterium longum subsp. infantis. Structural analyses and molecular dynamics simulations explained how fucosylated and non-fucosylated LNB forms are recognized with similar affinities by the binding protein of this importer. Strikingly, we showed that two ABC importers confer to the uptake of LNB, while the Lea trisaccharide is efficiently internalized by a single importer in B. infantis. Phylogenetic and structural analyses of bifidobacterial ABC-associated binding proteins showed that the Lea clade harbors homologues possessing internal cavities, which allows for the accommodation of branched oligosaccharides. Our work provides unique insight into the evolution and molecular basis of capture and uptake of key HMO and host-derived saccharide blocks, highlighting these compounds as hitherto unexplored candidates for fortification of infant formula. ImportanceThe assembly of the gut microbiota in early life is critical to the health trajectory of human hosts. Breast feeding selects for a Bifidobacterium-rich community, adapted to efficiently utilize HMOs from mothers milk. Industrial scale production of HMOs for infant formula fortification has mainly considered fucosyllactoses, whereas fucosylated type 1 HMO blocks have hitherto not been explored. Our work sheds light on the uptake facet, central to the utilization of fucosylated HMOs with type 1 LNB building blocks. These type I blocks are efficiently internalized and assimilated by B. infantis, which has been recently shown to secrete immune-modulatory aromatic-lactate metabolites that mediate immune-priming of hosts in early life. This study contributes to our understanding of the utilization of HMOs and highlights fucosylated LNB blocks, as hitherto unexplored prebiotic candidates that support the growth of B. infantis and other beneficial bacteria in early life.

microbiology↗

bioRxiv2025

Parameterization of intraoperative human microelectroderecordings: Linking action potential morphology to brainanatomy

Deep brain stimulation (DBS) is a targeted manipulation of brain circuitry to treat neurological and neuropsychiatric conditions. Optimal DBS lead placement is essential for treatment efficacy. Current targeting practice is based on preoperative and intraoperative brain imaging, intraoperative electrophysiology, and stimulation mapping. Electrophysiological mapping using extracellular microelectrode recordings aids in identifying functional subdomains, anatomical boundaries, and disease-correlated physiology. The shape of single-unit action potentials may differ due to different biophysical properties between cell-types and brain regions. Here, we describe a technique to parameterize the structure and duration of sorted spike units using a novel algorithmic approach based on canonical response parameterization, and illustrate how it may be used on DBS microelectrode recordings. Isolated spike shapes are parameterized then compared using a spike similarity metric and grouped by hierarchical clustering. When spike morphology is associated with anatomy, we find regional clustering in the human globus pallidus. This method is widely applicable for spike removal and single-unit characterization and could be integrated into intraoperative array-based technologies to enhance targeting and clinical outcomes in DBS lead placement. Author summaryWe developed a new algorithmic approach to capture the structure of single neuron electrophysiology from microelectrode recordings during deep brain stimulation surgery. This method has broad applications for spike characterization, clustering, removal from the background field potential, and comparison across recording sites. Using this technique, we illustrate regional clustering of spike morphologies in the human globus pallidus.

neuroscience↗

bioRxiv2024

Dysregulation of Nitrosylation Dynamics Promotes Nitrosative Stress and Contributes to Cardiometabolic Heart Failure with Preserved Ejection Fraction

BackgroundRecent reports suggest increased myocardial iNOS expression leads to excessive protein s-nitrosylation, contributing to the pathophysiology of HFpEF. However, the relationship between NO bioavailability, dynamic regulation of protein s-nitrosylation by trans- and de-nitrosylases, and HFpEF pathophysiology has not been elucidated. Here, we provide novel insights into the delicate interplay between NO bioavailability and protein s-nitrosylation in HFpEF. MethodsPlasma nitrite, nitrosothiols (RsNO), and 3-nitrotyrosine (3-NT) were measured in HFpEF patients and in controls. Studies in WKY or ZSF1 obese rats were performed to evaluate HFpEF severity, NO signaling, and total nitroso-species (Rx(s)NO) levels. snRNA sequencing was performed to identify key genes involved in NO signaling and s-nitrosylation regulation. ResultsIn HFpEF patients, circulating RsNO and 3-NT were significantly elevated while nitrite, a biomarker for NO bioavailability, remained unchanged. In ZSF1 obese rats, NO bioavailability was significantly reduced while Rx(s)NO levels exhibited an age-dependent increase as HFpEF progressed. snRNA seq highlighted significant upregulation of a trans-nitrosylase, hemoglobin-beta subunit (HBb), which was corroborated in human HFpEF hearts1. Subsequent experiments confirmed HBb upregulation and revealed significant reductions in enzyme activity of two major de-nitrosylases, Trx2 and GSNOR in ZSF1 obese hearts. Further, elevated RxNO levels, increased HBb expression, and reduced activity of Trx2 and GSNOR were identified in the kidney and liver of the ZSF1 obese rats. ConclusionsOur data reveal circulating markers of nitrosative stress (RsNO and 3-NT) are significantly elevated in HFpEF patients. Data from the ZSF1 obese rat model mirror the results from HFpEF patients and reveal that pathological accumulation of RxNO/nitrosative stress in HFpEF may be in part, due to the upregulation of the trans-nitrosylase, HBb, and impaired activity of the de-nitrosylases, Trx2 and GSNOR. Our data suggest that dysregulated protein nitrosylation dynamics in the heart, liver, and kidney contribute to the pathogenesis of cardiometabolic HFpEF. Translational PerspectiveOur findings describe for the first time that circulating RsNO and 3-NT are significantly upregulated in HFpEF patients suggesting systemic nitrosative stress in HFpEF, and demonstrate a profound disconnect between insufficient physiological NO signaling and pathological nitrosative stress in HFpEF, which is in stark contrast to HFrEF in which both NO bioavailability and protein s-nitrosylation are attenuated. Further, this study provides novel mechanistic insights into a critical molecular feature of HFpEF in humans and animal models: nitrosative stress arises predominantly from imbalance of trans-nitrosylases and de-nitrosylases, thereby leading to impaired NO bioavailability concomitant with increased protein s-nitrosylation. Importantly, these perturbations extend beyond the heart to the kidney and liver, suggesting HFpEF is characterized by a systemic derangement in trans- and de-nitrosylase activity and providing a unifying molecular lesion for the systemic presentation of HFpEF pathophysiology. These findings have direct clinical implications for the modulation of NO levels in the HFpEF patient, and indicate that restoring the balance between trans- and denitrosylases may be novel therapeutic targets to ameliorate disease symptoms in HFpEF patients.

physiology↗

bioRxiv2024

Transcriptomic landscape identifies two unrecognized ependymoma subtypes and novel pathways in medulloblastoma

Medulloblastoma and ependymoma are common pediatric central nervous system tumors with significant molecular and clinical heterogeneity. We collected bulk RNA sequencing data from 888 medulloblastoma and 370 ependymoma tumors to establish a comprehensive reference landscape. Following rigorous batch effect correction, normalization, and dimensionality reduction, we constructed a unified landscape to explore gene expression, signaling pathways, RNA fusions, and copy number variations. Our analysis revealed distinct clustering patterns, including two primary ependymoma compartments, EPN-E1 and EPN-E2, each with specific RNA fusions and molecular signatures. In medulloblastoma, we observed precise stratification of Group 3/4 tumors by subtype and in SHH tumors by patient age. This landscape serves as a vital resource for identifying biomarkers, refining diagnoses, and enables the mapping of new patients bulk RNA-seq data onto the reference framework to predict biology and outcome from nearest neighbor analysis facilitate accurate disease subtype identification. The landscape is accessible via Oncoscape, an interactive platform, empowering global exploration and application. One Sentence SummaryA landscape built using only Transcriptomic analysis for medulloblastoma and ependymoma reveals novel insights about subtype-specific biology.

bioinformatics↗

bioRxiv2024

Spatial and Spectral Changes in Cortical Surface Potentials during Pinching versus Thumb and Index Finger Flexion

Electrocorticographic (ECoG) signals provide high-fidelity representations of sensorimotor cortex activation during contralateral hand movements. Understanding the relationship between independent and coordinated finger movements along with their corresponding ECoG signals is crucial for precise brain mapping and neural prosthetic development. We analyzed subdural ECoG signals from three adult epilepsy patients with subdural electrode arrays implanted for seizure foci identification. Patients performed a cue-based task consisting of thumb flexion, index finger flexion or a pinching movement of both fingers together. Broadband power changes were estimated using principal component analysis of the power spectrum. All patients showed significant increases in broadband power during each movement compared to rest. We created topological maps for each movement type on brain renderings and quantified spatial overlap between movement types using a resampling metric. Pinching exhibited the highest spatial overlap with index flexion, followed by superimposed index and thumb flexion, with the least overlap observed for thumb flexion alone. This analysis provides practical insights into the complex overlap of finger representations in the motor cortex during various movement types, and may help guide more nuanced approaches to brain-computer interfaces and neural prosthetics. SIGNIFICANCE STATEMENTThis study measured brain activity actively during finger movement and found that pinching movements show higher cortical overlap with index finger flexion and uniquely engage parietal regions, advancing our understanding of motor control hierarchy and sensorimotor integration, while suggesting improvements for more naturalistic brain-computer interfaces through prioritized index finger decoding and integration of parietal lobe measurements.

neuroscience↗

bioRxiv2024

Complex genetic variation in nearly complete human genomes

Diverse sets of complete human genomes are required to construct a pangenome reference and to understand the extent of complex structural variation. Here, we sequence 65 diverse human genomes and build 130 haplotype-resolved assemblies (130 Mbp median continuity), closing 92% of all previous assembly gaps1,2 and reaching telomere-to-telomere (T2T) status for 39% of the chromosomes. We highlight complete sequence continuity of complex loci, including the major histocompatibility complex (MHC), SMN1/SMN2, NBPF8, and AMY1/AMY2, and fully resolve 1,852 complex structural variants (SVs). In addition, we completely assemble and validate 1,246 human centromeres. We find up to 30-fold variation in -satellite high-order repeat (HOR) array length and characterize the pattern of mobile element insertions into -satellite HOR arrays. While most centromeres predict a single site of kinetochore attachment, epigenetic analysis suggests the presence of two hypomethylated regions for 7% of centromeres. Combining our data with the draft pangenome reference1 significantly enhances genotyping accuracy from short-read data, enabling whole-genome inference3 to a median quality value (QV) of 45. Using this approach, 26,115 SVs per sample are detected, substantially increasing the number of SVs now amenable to downstream disease association studies.

genomics↗