Biology subjects

Won, S.

Publications and source records attributed to Won, S..

15 recordsLinked to original sources

bioRxiv2026

Sketching the SRA: experiment-wide similarity search across 4.8 million metagenomes

Recent efforts have demonstrated that systematic analysis of the millions of metagenomes in the Sequence Read Archive (SRA) enables groundbreaking biological discoveries. However, SRA-scale comparison of whole metagenomes has remained elusive. Here, we introduce the most comprehensive resource to date for experiment-to-experiment analysis of all SRA metagenomes, comprising FracMinHash sketches (470GB), hypergen sketches (19GB), and an all-pairs Jaccard similarity matrix (90GB), which we release online at https://github.com/RolandFaure/SRA-metagenome-sketches-databases. These resources enable a wide range of analyses, which we demonstrate with several applications. First, we use the FracMinHash sketches to uncover temporal trends, finding that the amount of newly discovered microbial sequence continues to grow, rather than saturate or shrink. Second, we use the hypergen sketches, which enable nearest-neighbor search, to identify co-assembly candidates and thereby improve assembly quality. Third, we use the similarity matrix to analyze all SRA metagenomes, identifying duplicated submissions and over 50K candidates for metadata correction. Together, our resources unlock systematic analysis of metagenomic data at unprecedented scale.

bioinformatics↗

bioRxiv2026

Genome-wide overexpression screen of Pseudomonas putida phage Emajogi

Bacteriophage genomes contain large fractions of uncharacterized genes, motivating high-throughput functional screens to illuminate their roles in host interaction and cytotoxicity. Here, we performed a genome wide overexpression assay for a Pseudomonas putida KT2440 infecting phage, Emajogi, and identified eight cytotoxic genes that reduce host growth under both basal and induced expression. We show that these proteins are conserved across phages that infect a diverse set of hosts. The most cytotoxic gene identified was a hypothetical protein (gp18) with no predicted functional domains. Transcriptomic profiling revealed that overexpression of gp18 caused a pronounced metabolic remodeling of the cell, likely shifting cell resources to phage production. Overall, this genome wide screen provides information about phage genes that were previously unannotated that can support biotechnology and novel antimicrobial development.

microbiology↗

bioRxiv2026

Phage proofing Pseudomonas putida uncovers novel broad-spectrum phage resistance protein Psh

Broad-spectrum phage resistance offers an important layer of protection against bacterial fermenter crashes during biomanufacturing processes, yet the underlying mechanisms are often poorly defined or come at a fitness cost. Using experimental evolution, we generated two Pseudomonas putida strains that were resistant to at least six phage genera. Genome sequencing revealed a single frameshift deletion in each strain that restored functionality of a Type I secretion system (T1SS) ATPase. We also found strong transcriptional upregulation of a nearby protein, PP_1794, which we coin Phage shielding helix rich protein (Psh). Overexpression experiments show that Psh protein is secreted by this restored T1SS to confer complete phage resistance. When compared to wild-type P. putida KT2440, no growth or expression defects were evident, but pyoverdine production was reduced. The Psh gene and T1SS are widely distributed across Gram-negative bacteria. These findings uncover a previously uncharacterized phage defense system in P. putida based on secretion-mediated receptor masking.

microbiology↗

bioRxiv2026

Large-scale meta-analysis of over one million individuals reveals the genetic architecture of 127 complex traits in East Asian populations

Genome-wide association studies (GWASs) have disproportionately focused on European (EUR) populations, limiting the characterization of genetic architecture in other ancestries. To address this imbalance, we integrated large-scale biobanks from Japan, Korea, Taiwan, and China to perform the largest phenome-wide meta-analysis to date in East Asian (EAS) populations, encompassing over one million individuals across 127 complex traits. We identified 8,010 previously unreported associations and observed substantial genetic sharing across EAS subpopulations, while also detecting cohort-specific heterogeneity within the broader EAS context. Transethnic analyses revealed moderate genetic correlations between EAS and EUR populations, indicating both shared and ancestry-specific components of disease risk. Pleiotropy analyses highlighted prominent signals within the HLA region, supported by protein-protein interaction connectivity and immune-related pathway enrichment. Decomposition of genome-wide association matrices further uncovered structured cross-trait architectures, revealing a predominantly shared polygenic backbone driven by metabolic, biochemical, and anthropometric traits, together with two discrete latent components enriched for immune-related processes. Together, our findings refine the genetic architecture of complex traits in East Asian populations at unprecedented scale and clarify the balance between shared and population-specific determinants of human diseases.

genetics↗

bioRxiv2025

COBRA: Cell-type-specific Orthogonal Batch effect Removal Algorithm in single cell RNA-sequencing data

Single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling of cellular heterogeneity, yet batch effects remain a critical challenge in data integration. Existing batch correction methods often assume homogeneous batch effect across cell types, operate in reduced-dimensional space leading to potential loss of biological information, and require extensive computational resources. Here, we introduce COBRA (https://github.com/wonlab-healthstat/COBRA), a linear model-based batch correction method that explicitly adjusts cell-type-specific batch effect. By orthogonalizing batch-associated parameters with respect to biological variables, COBRA removes technical artifacts while preserving biologically meaningful transcriptional differences. When cell type annotations are unavailable, COBRA implements an iterative clustering algorithm to estimate pseudo-cell types while accounting for batch effects. COBRA retains the full gene expression matrix, ensuring seamless integration for downstream analyses. We evaluated COBRA across simulated and real-world datasets, including type 2 diabetes, and COVID-19 datasets. COBRA outperformed in terms of batch mixing efficiency, preservation of biological group structure, and accuracy of differentially expressed gene detection.

bioinformatics↗

bioRxiv2025

Integration of Nuclear Receptors into a Schwann cell Gene Regulatory Network

Peripheral nerve function depends on the proper formation and maintenance of Schwann cells. During development, large diameter axons are enveloped by single, myelinating Schwann cells whereas clusters of small diameter axons are surrounded by nonmyelinating Schwann cells in Remak bundles. The transcription factor SRY-box 10 (SOX10) is required for the development of Schwann cells, but its functions in different neural crest and glial lineages have shown that SOX10 commonly cooperates with other transcription factors to activate cell-specific gene programs. In a previous study, we compared SOX10-bound regulatory elements in Schwann cells and identified a specific enrichment for nuclear receptor motifs at SOX10 binding sites in Schwann cells. NR2F1 and NR2F2 (Coup-TFI/Coup-TFII) are expressed from neural crest through Schwann cell maturity, and knockdown of nuclear receptors Nr2f1 and Nr2f2 in primary Schwann cells downregulated several myelin genes. In this study, we have identified a NR2F-regulated target gene network in Schwann cells, which revealed enrichment for nonmyelinating Schwann cell genes. Cut&Run assays in S16 Schwann cells revealed novel, genome-wide binding sites of NR2F2 and two downstream transcription factors: 1) Retinoid X Receptor Gamma (RXRG), which is also expressed preferentially in nonmyelinating Schwann cells, and 2) TEA-Domain factor (TEAD1), which is an important HIPPO pathway component required for Remak bundle formation. Our study elucidates the transcriptional cooperation that programs the regulatory network in nonmyelinating Schwann cells.

neuroscience↗

bioRxiv2024

rRNA Operon Improves Species-Level Classification of Bacteria and Microbial Community Analysis Compared to 16S rRNA

Precise identification of species is fundamental in microbial genomics, crucial for understanding the microbial communities. While the 16S rRNA gene, particularly its V3-V4 regions, has been extensively employed for microbial identification, however has limitations in achieving species-level resolution. Advancements in long-read sequencing technologies have highlighted the rRNA operon as a more accurate marker for microbial classification and analysis than the 16S rRNA gene. This study aims to compare the accuracy of species classification and microbial community analysis using the rRNA operon versus the 16S rRNA gene. We evaluated the species classification accuracy of the rRNA operon,16S rRNA gene, and 16S rRNA V3-V4 region using a BLAST based method and a k-mer matching based method with public data available from NCBI. We further preformed simulations to model microbial community analysis. We accessed the performance using each marker in community composition estimation and differential abundance analysis. Our findings demonstrate that the rRNA operon offers an advantage over the 16S rRNA gene and its V3-V4 region for species-level classification within genus. When applied to microbial community analysis, the rRNA operon enables a more accurate determination of composition. Using the rRNA operon yielded more reliable results in differential abundance analysis as well. IMPORTANCEWe quantitatively demonstrated that the rRNA operon outperformed the 16S rRNA and its V3-V4 regions in accuracy, for both individual species identification and species-level microbial community analysis. Our findings can provide guidelines for selecting appropriate markers in the field of microbial research.

microbiology↗

bioRxiv2023

PaGeSearch: A Tool for Identifying Genes within Pathways in Unannotated Genomes

In biological research, the identification and comparison of genes within specific pathways across the genomes of various species are invaluable. However, annotating the entire genome is resource-intensive and sequence similarity searches often yield results that are not actually genes. To address these limitations, we introduce PaGeSearch (Pathway Gene Search), a tool designed to identify genes from predefined lists, especially those in specific pathways, within genomes. The tool employs an initial sequence similarity search to identify relevant genomic regions, followed by targeted gene prediction and neural network-based result filtering. PaGeSearch suggests the regions that are most likely the orthologs of the genes in the query and is designed to be applicable for species within five classes: mammals, fish, birds, eudicotyledons, and liliopsida. When compared with GeMoMa, PaGeSearch consistently outperformed in terms of sensitivity and positive predictive value. Although its performance showed increased variability when applied to actual biological pathways, it nonetheless maintained an acceptable level of accuracy.

bioinformatics↗

bioRxiv2023

Robust Phylogenetic Tree-based Microbiome Association Test using Repeatedly Measured Data for Composition Bias

MotivationThe effects of microbiota on the host phenotypes can substantially differ depending on his/her age. Longitudinally measured microbiome data allows us to detect the age modification effect and are useful for the detection of microorganisms related to the progression of disease which change identification over time. Moreover, longitudinal analysis enables the estimation of within-subject covariate effect, is robust against the between-subject confounders, and provides better evidence for the causal relationship than cross-sectional studies. However, they suffer from compositional bias, and few statistical methods can estimate their effect on host diseases with repeatedly measured 16S rRNA gene data. In this article, we proposed mTMAT which can be applied to longitudinal microbiome data and is robust against compositional bias. ResultsmTMAT normalized the microbial abundance and utilized the ratio of the pooled abundances for association analysis. mTMAT is based on generalized estimating equations with a robust variance estimator and can be applied to repeatedly measured microbiome data. With extensive simulation studies, we showed that mTMAT is statistically more powerful and is robust against compositional bias. mTMAT enables detection of microbial taxa associated with host diseases using repeatedly measured 16S rRNA gene data and can provide deeper insight into bacterial pathology. AvailabilityThe 16S rRNA amplicon sequencing metagenomics datasets for Korea Association REsource cohort is available from the NCBI Sequence Read Archive database under project accession number PRJNA716550. mTMAT was implemented in the R package. Detailed information is available at https://healthstat.snu.ac.kr/software/mtmat. Contactwon1@snu.ac.kr Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2023

Contrasting synaptic roles of MDGA1 and MDGA2

Neurodevelopmental disorders are frequently linked to mutations in synaptic organizing molecules. MAM domain containing glycosylphosphatidylinositol anchor 1 and 2 (MDGA1 and MDGA2) are a family of synaptic organizers suggested to play an unusual role as synaptic repressors, but studies offer conflicting evidence for their localization. Using epitope-tagged MDGA1 and MDGA2 knock-in mice, we found that native MDGAs are expressed throughout the brain, peaking early in postnatal development. Surprisingly, endogenous MDGA1 was enriched at excitatory, but not inhibitory, synapses. Both shRNA knockdown and CRISPR/Cas9 knockout of MDGA1 resulted in cell-autonomous, specific impairment of AMPA receptor- mediated synaptic transmission, without affecting GABAergic transmission. Conversely, MDGA2 knockdown/knockout selectively depressed NMDA receptor-mediated transmission but enhanced inhibitory transmission. Our results establish that MDGA2 acts as a synaptic repressor, but only at inhibitory synapses, whereas both MDGAs are required for excitatory transmission. This nonoverlapping division of labor between two highly conserved synaptic proteins is unprecedented. TeaserMDGAs 1 and 2 independently localize to and modulate excitatory and inhibitory hippocampal synapses by different mechanisms.

neuroscience↗

bioRxiv2022

Predicting Lung Cancer in Korean Never-Smokers with Polygenic Risk Scores

In the last few decades, genome-wide association studies (GWAS) with more than 10,000 subjects have identified several loci associated with lung cancer. Hence, recently, genetic data have been used to develop novel risk prediction tools for cancer. The present study aimed to establish a lung cancer prediction model for Korean never-smokers using polygenic risk scores (PRSs). PRSs were calculated using a thresholding-pruning-based approach based on 11 genome-wide significant single nucleotide polymorphisms (SNPs). Overall, the odds ratios tended to increase as PRSs were larger, with the odds ratio of the top 5% PRSs being 1.71 (95% confidence interval: 1.31-2.23), and the area under the curve (AUC) of the prediction model being of 0.76 (95% confidence interval: 0.747-0.774). The receiver operating characteristic (ROC) curves of the prediction model with and without PRSs as covariates were compared using DeLongs test, and a significant difference was observed. Our results suggest that PRSs can be valuable tools for predicting the risk of lung cancer.

bioinformatics↗

bioRxiv2022

JUN Regulation of Injury-induced Enhancers in Schwann Cells

Schwann cells play a critical role after peripheral nerve injury by clearing myelin debris, forming axon-guiding Bands of Bungner, and re-myelinating regenerating axons. Schwann cells undergo epigenomic remodeling to differentiate into a repair state that expresses unique genes, some of which are not expressed at other stages of Schwann cell development. We previously identified a set of enhancers that are activated in Schwann cells after nerve injury, and we determined if these enhancers are pre-programmed into the Schwann cell epigenome as poised enhancers prior to injury. Poised enhancers share many attributes of active enhancers, such as open chromatin, but are marked by repressive H3K27 trimethylation (H3K27me3) rather than H3K27ac. We find that most injury-induced enhancers are not marked as poised enhancers prior to injury indicating that injury-induced enhancers are not pre-programmed in the Schwann cell epigenome. Injury-induced enhancers are enriched with AP-1 binding motifs, and the c-JUN subunit of AP-1 had been shown to be critical to drive the transcriptional response of Schwann cells after injury. Using in vivo ChIP-seq analysis we find that c-JUN binds to a subset of injury-induced enhancers. To test the role of specific injury-induced enhancers, we focused on c-JUN-binding enhancers upstream of the Sonic Hedgehog (Shh) gene, which is only upregulated in repair Schwann cells compared to other stages of Schwann cell development. We confirm that c-JUN regulates these enhancers and also show that the enhancers are required for robust induction of the Shh gene after injury. Significance StatementThe pro-regenerative actions of Schwann cells after nerve injury depends on upon profound reprogramming of the epigenome. The repair state is directed by injury-induced transcription factors, like JUN, which is uniquely required after nerve injury. In this study, we test whether the injury program is pre-programmed into the epigenome as poised enhancers and define which enhancers bind JUN. Finally, we test the roles of these enhancers by performing CRISPR-mediated deletion of JUN-bound injury enhancers in the Sonic hedgehog gene. While many long range enhancers drive expression of Sonic hedgehog at different developmental stages of specific tissues, these studies identify an entirely new set of enhancers that are required for Sonic hedgehog induction in Schwann cells after injury.

neuroscience↗

bioRxiv2021

False gene and chromosome losses affected by assembly and sequence errors

Many genome assemblies have been found to be incomplete and contain misassemblies. The Vertebrate Genomes Project (VGP) has been producing assemblies with an emphasis on being as complete and error-free as possible, utilizing long reads, long-range scaffolding data, new assembly algorithms, and manual curation. Here we evaluate these new vertebrate genome assemblies relative to the previous references for the same species, including a mammal (platypus), two birds (zebra finch, Annas hummingbird), and a fish (climbing perch). We found that 3 to 11% of genomic sequence was entirely missing in the previous reference assemblies, which included nearly entire GC-rich and repeat-rich microchromosomes with high gene density. Genome-wide, between 25 to 60% of the genes were either completely or partially missing in the previous assemblies, and this was in part due to a bias in GC-rich 5-proximal promoters and 5 exon regions. Our findings reveal novel regulatory landscapes and protein coding sequences that have been greatly underestimated in previous assemblies and are now present in the VGP assemblies.

genomics↗

bioRxiv2019

Retrograde mitochondrial transport is essential for mitochondrial homeostasis in neurons

Mitochondrial transport in neurons is essential for forming and maintaining axonal projections. While much is known about anterograde mitochondrial movement, the function of retrograde mitochondrial motility in neurons was unknown. We investigated the dynamics and utility of retrograde mitochondrial transport. Using long-term tracking of mitochondria in vivo, we found mitochondria in axon terminals turnover within hours via retrograde transport. Mitochondria do not return to the cell body solely for degradation; rather, mitochondria use bidirectional transport to redistribute themselves throughout the neuron. Disruption of retrograde mitochondrial transport severely depletes the cell body of mitochondria and impacts mitochondrial health throughout the cell. Altered mitochondrial health correlates with decreased synaptic activity. Using proteomics, we provide evidence that retrograde mitochondrial movement functions to maintain the organelles proteome. Together, our work demonstrates that mitochondrial retrograde transport is essential for the maintenance of a homeostatic population of mitochondria in neurons and consequently effective synaptic activity through promoting mitochondrial protein turnover.

neuroscience↗

bioRxiv2018

BALLI: Bartlett-Adjusted Likelihood-based LInear Model Approach for Identifying Differentially Expressed Gene with RNA-seq Data

MotivationTranscriptomic profiles can improve our understanding of the phenotypic molecular basis of biological research, and many statistical methods have been proposed to identify differentially expressed genes under two or more conditions with RNA-seq data. However, statistical analyses with RNA-seq data often suffer from small sample sizes, and global variance estimates of RNA expression levels have been utilized as prior distributions for gene-specific variance estimates, making it difficult to generalize the methods to more complicated settings. We herein proposed a Bartlett-Adjusted Likelihood based LInear mixed model approach (BALLI) to analyze more complicated RNA-seq data. The proposed method estimates the technical and biological variances with a linear mixed effect model, with and without adjusting small sample bias using Bartletts corrections.\n\nResultsWe conducted extensive simulations to compare the performance of BALLI with those of existing approaches (edgeR, DESeq2, and voom). Results from the simulation studies showed that BALLI correctly controlled the type-1 error rates at the various nominal significance levels, and produced better statistical power and precision estimates than those of other competing methods in various scenarios. Furthermore, BALLI was robust to variation of library size. It was also successfully applied to Holstein milk yield data, illustrating its practical value.\n\nAvailability and ImplementationBALLI is implemented as R package and freely available at http://healthstat.snu.ac.kr/software/balli/.\n\nContactwon1@snu.ac.kr\n\nSupplementary InformationSupplementary data are available at Bioinformatics online

bioinformatics↗