Biology subjects

Chun, S.

Publications and source records attributed to Chun, S..

12 recordsLinked to original sources

bioRxiv2026

Cas12a-Targeted Multiplexed Nanopore Sequencing

Targeted long read sequencing (LRS) of native genomic DNA (gDNA) using Oxford Nanopore Technologies (ONT) is an economically and computationally accessible method for sequencing selected genomic regions without the limitations associated with amplification-based approaches. At present, efficiency, multiplexing, and scalability remain key challenges for existing targeted LRS. We have developed Cas12a-Targeted Multiplexed Nanopore Sequencing (CTM-nSeq), which combines Cas12a-targeting, DNA fragment enrichment, and optimized adapter ligation using T7 DNA ligase. Unlike previously established protocols, CTM-nSeq is compatible with the latest ONT flow cell chemistry. Performing CTM-nSeq on a single sample with an R10.4 MinION flow cell routinely yields hundreds of on-target reads. Furthermore, CTM-nSeq enables targeting of multiple loci and is the first targeted ONT sequencing method, allowing reliable, barcode-assisted multiplexing. CTM-nSeq is an efficient and accessible method for sequencing native gDNA and analysing DNA methylation, repeat expansions, and sequence integrity. As such, CTM-nSeq has a wide range of analytical and diagnostic applications. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/736710v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@1c7c9a1org.highwire.dtl.DTLVardef@1867539org.highwire.dtl.DTLVardef@7a10bdorg.highwire.dtl.DTLVardef@1e10c70_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical abstract illustrating CTM-nSeq workflow and advantages, showing the key steps for sample preparation: Cas12a cleavage, DNA fragment size enrichment, T7 DNA ligase mediated ligation and ONT-based sequencing. Key advantages include increased specificity, optimized cohesive end ligation, barcode-based multiplexing, and over 50-fold coverage.

molecular biology↗

bioRxiv2026

A self-limiting orexin-habenula circuit for stress resilience

Resilience requires neural systems that mobilise active coping during stress while limiting its persistence to preserve homeostasis under sustained challenge1-4. Here we identify a self-limiting orexin-habenula circuit in which lateral hypothalamic orexin neurons engage aromatic L-amino acid decarboxylase-expressing D-neurons (encoded by Ddc) in the lateral habenula via orexin receptor type 2 (OX2R)5-7. Activation of this pathway increased nucleus accumbens dopamine and promoted active coping and positive valence. Optotagging revealed rapid stress-evoked recruitment followed by post-stress suppression. In lateral habenula neurons, orexin peptides exerted dissociable effects: orexin-A engaged an OX2R-dependent inhibitory programme superimposed on a parallel inward current, whereas orexin-B did not reproduce this inhibitory profile and instead exerted a distinct membrane effect. Chronic stress disrupted this buffering system through coordinated inflammatory activation, promoter methylation and erosion of D-neuron identity and orexin responsiveness. Restoring orexin-A reversed behavioural and molecular deficits through OX2R-dependent suppression of nuclear factor kappa B signalling, preservation of Tet2 expression, and demethylation-linked maintenance of the Ddc programme. Together, these findings define a self-limiting orexin-habenula resilience circuit that enables adaptive coping while constraining stress-induced vulnerability.

neuroscience↗

bioRxiv2025

A single-cell genetic colocalization test improves power and resolves disease-mediating cell types

Statistical colocalization testing methods can determine if the same single-nucleotide polymorphism (SNP) underlies both a genome-wide association study (GWAS) locus as well as an expression quantitative trait (eQTL) locus. This can nominate potential mechanistic pathways from SNPs to genes to traits, while providing cell type or tissue context. Surprisingly, systematic colocalization testing with bulk-tissue eQTLs fails to link the majority of GWAS loci with gene expression changes. Mapping eQTLs with single-cell expression data has the potential to reveal the missing regulatory effects of GWAS variants. However, current pseudobulk cluster-based approaches may be underpowered when clustering accuracy is imperfect or with an incorrectly selected cluster resolution. To improve power of single-cell colocalization tests, we developed a cluster-free method, scJLIM. By modeling eQTL interactions with continuous cell states (e.g., principal components), scJLIM estimates eQTL significance and colocalization in individual cells. We benchmarked our method with simulated data, demonstrating improvements in power over pseudobulk methods. In our main applications, we used scJLIM to analyze blood and brain scRNA-seq datasets paired with autoimmune and neurological disease GWAS, respectively. We identified nearly twice as many total colocalizations compared with traditional pseudobulk analyses carried out within the major cell populations of these tissues. Aligning with a recent experimental study, we highlighted an example of the ETS2 gene colocalizing with an inflammatory bowel disease GWAS locus in a subset of myeloid cells. For Parkinsons disease (PD), our results pointed to TRPV2 as a potential gene of interest, corroborated by transcriptional changes in both post-mortem PD brains and iPSC-derived neuronal models of alpha-synucleinopathy.

genomics↗

bioRxiv2025

The eutherian-specific histone H3.4 promotes germ cell development and reproductive fitness

Many genes encoding chromatin proteins are subject to evolutionary selection driving reproductive fitness. In mice and men, the histone H3.4 variant is essential to spermatogenesis. Here we define the evolutionary origin and molecular-physiological roles of sequence variation in H3f4 for male germ cell development in mice. Our phylogenetic analyses indicate that eutherian H3f4 orthologs originate from an ancestral H3.2 gene existing prior to the divergence of eutherian and marsupial mammals over 100 million years ago. Positioned in truncated histone gene clusters, eutherian H3f4 orthologs show increased non-synonymous and synonymous substitution rates compared to orthologous marsupial H3.2 loci located in typically large histone clusters. To determine the impact of sequence divergence on reproductive fitness, we reverted non-synonymously substituted residues in H3f4 to those present in canonical H3.1 (H3f4V24A, H3f4H42R, H3f4S98A). Hemizygous expression of such triply reverted H3f4H3.1 allele on a H3f4-deficiency background caused an >40% reduction in testis weight associated with impaired meiotic DNA double strand break repair, death of pachytene spermatocytes, impaired differentiation of spermatids and aberrant expression of thousands of genes during spermatid elongation. Hemizygous expression of individual residue substitution alleles revealed residues V24 and H42 of H3.4 to promote spermatogenesis, while residue S98 is neutral. Together, our study shows that H3f4 has been subject to positive evolutionary selection, promoting male reproductive fitness.

genetics↗

bioRxiv2024

Neural bidomain model for multidimensional ephaptic coupling of neural spike propagation along myelinated fiber bundles with the nodes of Ranvier

A novel mathematical model is proposed to investigate the distributions and functions of ephaptic coupling in generally-shaped neural fiber bundles in a multidimensional space, corresponding to the spatiotemporal interactions between propagating fiber bundles via the extracellular space. The proposed macroscopic model is derived from the classic Frankenhaeuser-Huxley model for neural spike propagation along the general neural fiber bundles in two domains (bidomain) of the nonoverlapping intracellular and extracellular space, except the common nodes of Ranvier. A high-order continuous Galerkin scheme provides an efficient two-dimensional (2D) computational simulation with moving frames (orthonormal basis vectors) representing intracellular and extracellular conductivity and nonoverlapping domains. The governing equation is mathematically and computationally validated against the existing 1D models of propagations along neural fiber bundles with the aligned nodes of Ranvier. The proposed model reveals the critical role of neural fiber bundle configurations by simulating their 2D propagations. For sufficiently large fiber bundles, synchronizing neural spike propagation along two fiber bundles with misaligned nodes of Ranvier is almost impossible. Moreover, the magnitude of interference of propagations passing-by along the fiber bundles depends on the fiber-bundle configuration, significantly depending on the location of the closest distance of two propagations, either in the myelin sheath or nodes of Ranvier. Finally, the curved fiber bundles demonstrate drastically different ephaptic coupling compared to straight fiber bundles due to the unique extracellular potential distribution by the curved fiber bundles. The new simulations highlight the importance of intrinsic fiber-bundle structures in neural spike propagation and brain functions. Author summaryFiber bundles communicate via chemical interactions across synaptic junctions and electrical interactions across gap junctions. Ephaptic coupling is another communication method between fiber bundles, which is of a small magnitude compared with other communication methods. The effect of ephaptic coupling is known on a relatively large scale and is mostly affected by the intrinsic structure of neural fiber bundles. The study of ephaptic coupling has attracted considerable attention since the 1940s, when the term ephaptic coupling was first coined. However, the lack of a multidimensional model of neural spike propagation with various configurations of myelinated fiber bundles has prohibited further investigations of ephaptic coupling in brain subregions. This paper proposes a multidimensional model of neural spike simulation in the context of partial differential equations. The proposed model aims to simulate neural spike propagations in complex configurations of fiber bundles to study the functions of ephaptic coupling in such brain structures. In this paper, the new simulations of the misaligned nodes of Ranvier, interfering opposite-traveling fiber bundles, and curved fiber bundles demonstrate the critical roles of intrinsic fiber-bundle structures, including the location and alignment of the nodes of Ranvier, in neural spike propagation and brain functions.

neuroscience↗

bioRxiv2024

Anatomical Region-Specific Transcriptomic Signatures and the Role of Epithelial Cells in Pterygium Inflammation: A Multi-Omics Analysis

BackgroundThe anatomy of pterygium consists of the head, neck, and body. Prior studies have examined the three parts collectively, yet the treatment methods and their success rates differ based on the anatomical characteristics. In this study, we divide the pterygium tissue into Main (head and neck) and Acc (body) to investigate its pathogenesis across regions. PurposesThis study aims to understand the pathogenesis and identify potential therapeutic targets of pterygium. Through a robust multi-omics analysis of bulk and single-cell RNA sequencing (RNA-seq) data from pterygium patients, we focus on the expression of inflammatory and mitochondrial energy pathways and identify potential genes responsible for the upregulated pathways in pterygium. MethodsWe collected bulk RNA-seq data from six pterygium patients and single-cell RNA-seq data from two pterygium patients. We then investigated the pathway enrichment, pathway correlation, differential gene expressions, protein-protein interactions, and cell-cell communications of pterygium. ResultsFrom the analysis of bulk RNA-seq data, the distribution of sample points from the principal component analysis plot and the pathways enriched from the Gene Ontology analysis showed distinct expression patterns in the Acc group compared to the Main and control groups. This suggested the need to separate the Main and Acc regions within pterygium samples and utilize single-cell RNA-seq data to understand the differences between the Main and control groups that the bulk data could not capture. The annotation of integrated single-cell data revealed a cluster of epithelial cells containing only pterygium samples. Cells from this cluster exhibited significant contributions to the ANGPTL, IL1, and KLK signaling networks in the cell-cell communication analysis. We also observed significant upregulation of the cells in the inflammatory pathways related to integrated stress response and the renin-angiotensin-aldosterone system, both of which showed high correlations with energy metabolism pathways. Significant changes in the expression of multiple pro-inflammatory, antioxidant, and immune-related genes were also identified. ConclusionThe different expression patterns between the Main and Acc groups suggest the need to consider different anatomical regions separately in future studies of pterygium. Additionally, the significant role epithelial cells from the Main group play in the inflammation of pterygium presents a potential clinical approach to the disease.

bioinformatics↗

bioRxiv2022

Neural mechanism of acute stress management by trace aminergic signalling in the lateral habenula

Stress management is a prerequisite for the survival of vertebrates because chronic stress may cause depression and is known to negatively modulate the dopaminergic reward system1. Enhanced excitability of neurons in the lateral habenula (LHb) induced by chronic stress is essential for silencing dopaminergic neurons in the ventral tegmental area (VTA) via GABAergic neurons in the rostromedial tegmental nucleus (RMTg)2-10. However, the effect of acute stress on the LHb-RMTg-VTA pathway is unknown11-14. Here, we show that both aromatic L-amino acid decarboxylase (AADC)-expressing neurons (D-neurons)15 in the LHb and dopaminergic neurons in the VTA are activated by acute stress, whereas GABAergic neurons in the RMTg are not. Selective stimulation of LHb D-neurons and AADC knockdown of these neurons reverse-regulate the RMTg-VTA pathway. Circuit tracing and electrophysiology data demonstrate that trace aminergic signalling by LHb D-neurons directly suppresses RMTg GABAergic neurons. Furthermore, local activation of trace amine-associated receptor 1 (TAAR1; a trace amine receptor) in the RMTg is sufficient to rescue the despair-like behaviour produced by the loss of AADC expression. Our results identify a novel efferent pathway from the LHb to the RMTg whereby trace aminergic signalling allows the brain to manage acute stress by preventing VTA dopaminergic neuron hypoactivity. The TAAR1-mediated trace aminergic signalling in the LHb-RMTg pathway may hold promise as a therapeutic target for stress-mediated psychological diseases.

neuroscience↗

bioRxiv2021

The three-dimensional chromatin structure of the major human pancreatic cell types reveals lineage-specific regulatory architecture of T2D risk

Three-dimensional (3D) chromatin organization maps help to dissect cell type-specific gene regulatory programs. Furthermore, 3D chromatin maps have contributed to elucidating the pathogenesis of complex genetic diseases by connecting distal regulatory regions and genetic risk variants to their respective target genes. To understand the cell type-specific regulatory architecture of diabetes risk, we generated transcriptomic and 3D epigenomic profiles of human pancreatic acinar, alpha, and beta cells using single-cell RNA-seq, single-cell ATAC-seq, and high-resolution Hi-C of sorted cells. Comparisons of these profiles revealed differential A/B (open/closed) chromatin compartmentalization, chromatin looping, and transcriptional factor mediated control of cell type-specific gene regulatory programs. We identified a total of 4,750 putative causal-variant-target-gene pairs at 194 type 2 diabetes GWAS signals using pancreatic 3D chromatin maps. We found that the connections between candidate causal variants and their putative target effector genes are cell-type stratified and emphasize previously underappreciated roles for alpha and acinar cells in diabetes pathogenesis.

genetics↗

bioRxiv2020

Shared associations identify causal relationships between gene expression and immune cell phenotypes

Genetic mapping studies have identified thousands of associations between common variants and hundreds of human traits. Translating these associations into mechanisms is complicated by two factors: they fall into gene regulatory regions; and they are rarely mapped to one causal variant. One way around these limitations is to find groups of traits that share associations, using this genetic link to infer a biological connection. Here, we assess how many trait associations in the same locus are due to the same genetic variant, and thus shared; and if these shared associations are due to causal relationships between traits. We find that only a subset of traits share associations, with most due to causal relationships rather than pleiotropy. We therefore suggest that simply observing overlapping associations at a genetic locus is insufficient to infer causality; direct evidence of shared associations is required to support mechanistic hypotheses in genetic studies of complex traits.

genetics↗

bioRxiv2019

Leveraging pleiotropy to discover and interpret GWAS results for sleep-associated traits

Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations in underpowered validation cohorts and leads to higher interpretability. Here, as an exemplar, we use Obstructive Sleep Apnea (OSA), a common disorder diagnosed using overnight multi-channel physiological testing. We leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS. We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example, we identify and replicate the pleiotropy across the plateletcrit, OSA and an eQTL of DNA primase subunit 1 (PRIM1) in immune cells. We find suggestive links between OSA, a measure of lung function (FEV1/FVC), and an eQTL of matrix metallopeptidase 15 (MMP15) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase 1 (HK1) locus to hematocrit and other red blood cell related traits. Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases. Author SummaryLarge genetic studies with hundreds of thousands of patients have been successful at finding genetic variants that associate with disease traits in humans. However, smaller-scale studies can often have inadequate power to discover new genetic associations. Here, we use a small genetic study of Obstructive Sleep Apnea (OSA), to introduce a strategy that both helps find genetic associations and proposes biological hypotheses for the mechanisms behind those associations. To achieve this, we use large genetic studies carried out on traits that are related to OSA, and look for genetic variants that affect both OSA in our small study and the trait in question in the large study. By linking two or more traits at select loci, we were able to, among other results, find a locus that affects the expression of a gene in immune cells (DNA primase subunit 1), a marker of thrombotic and inflammatory processes (plateletcrit) and OSA. This results in a novel genetic association to OSA and a corresponding biological hypothesis behind its effect on OSA.

genetics↗

bioRxiv2018

Non-parametric polygenic risk prediction using partitioned GWAS summary statistics

In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the traits heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for Breast Cancer, Type 2 Diabetes, Inflammatory Bowel Disease and Coronary Heart Disease, all of which have available early intervention or prevention treatments.

bioinformatics↗

bioRxiv2018

Metabolomics profile of umbilical cord blood is associated with maternal pre-pregnant obesity in a prospective multi-ethnic cohort displaying health disparities

Maternal obesity has become a growing global health concern that may predispose the offspring to medical conditions later in life. However, the metabolic link between maternal pre-pregnant obesity and healthy offspring has not yet been fully elucidated. In this study, we conducted a case-control study using coupled untargeted and targeted metabolomics approach, from the newborn cord blood metabolomes associated with a matched maternal pre-pregnant obesity cohort of 28 cases and 29 controls. The subjects were recruited from multi-ethnic populations in Hawaii, including rarely reported Native Hawaiian and other Pacific Islanders (NHPI). We found that maternal obesity was the most important factor contributing to differences in cord blood metabolomics. Using elastic net regularization based logistic regression model, we identified 29 metabolites as potential early-life biomarkers manifesting intrauterine effect of maternal obesity, with accuracy as high as 0.947 after adjusting for clinical confounding (maternal and paternal age and ethnicity, parity and gravidity). We validated the model results in a subsequent set of samples (N=30) with an accuracy of 0.822. Among the metabolites, six metabolites (galactonic acid, butenylcarnitine, 2-hydroxy-3-methylbutyric acid, phosphatidylcholine diacyl C40:3, 1,5-anhydrosorbitol, and phosphatidylcholine acyl-alkyl 40:3) were individually and significantly different between the maternal obese vs. norm-weight groups. Interestingly, Hydroxy-3-methylbutyric acid showed significnatly higher levels in cord blood from the NHPI group, compared to asian and caucasian groups. In summary, significant associations were observed between maternal pre-pregnant obesity and offspring metabolomics alternation at birth, revealing the inter-generational impact of maternal obesity.

bioinformatics↗