Biology subjects

Yoon, S.-H.

Publications and source records attributed to Yoon, S.-H..

6 recordsLinked to original sources

bioRxiv2025

Large-scale single-cell phylogenetic mapping of clonal evolution in the human aging esophagus

The human somatic genome evolves throughout our lifespan, producing mosaic individuals comprising clones harboring different mutations across tissues. While clonal expansions in the hematopoietic system have been extensively characterized and reported to be nearly ubiquitous, clonal mosaicism (CM) has more recently also been described across multiple solid tissues. However, outstanding questions remain about the parameters and processes of human somatic evolution in non-cancerous solid human tissues, including when clones arise, how they evolve over time, and what mechanisms lead to their expansion. Questions of timing and clonal dynamics can be addressed through phylogenetic reconstruction, which serves as a temporal microscope, while uncovering the mechanisms of expansion necessitates simultaneous phenotypic profiling. To address this gap, here we develop Single-cell Miniaturized Automated Reverse Transcription and Primary Template-directed Amplification (SMART-PTA) for joint single-cell whole-genome and whole-transcriptome sequencing for large scale and cost efficient interrogation of solid tissue CM. We established a workflow that generates hundreds of matched single-cell whole genome and transcriptome libraries within a week. We profiled phenotypically normal esophagus tissue from four aged donors and used somatic variants to build high-resolution single-cell lineages from >2,700 cells with accompanying transcriptomic information, reconstructing >70 years of somatic evolution. T cell expansions identified from T cell receptor (TCR) sequences validated the clonal structure of the single-nucleotide variant (SNV)-based phylogenies and phylogenetic cross-correlation analysis showed that epithelial cells had higher degrees of shared ancestry by spatial location compared to immune cells. Mapping mutation signatures to the phylogenetic tree revealed the emergence of tobacco/alcohol exposure-related signatures later in life, consistent with the donors exposure histories. We identified variants in driver genes that were previously reported in the phenotypically normal esophagus, detecting clonal expansions harboring mutations in genes including TP53 and FAT1. We mapped the evolution of clones with both monoallelic as well as biallelic TP53 loss, including a clone associated with high expression of cell cycling genes and higher chromosome instability. Leveraging the matched transcriptome data, we uncovered cell type biases in mutant clones, with a higher proportion of TP53 or FAT1-mutant cells in an earlier basal epithelial cell state compared to wild-type cells. We further observed copy-neutral loss of heterozygosity (CNLOH) events on chromosome 9q that spanned the NOTCH1 locus in up to [~]35% of epithelial cells. Mapping CNLOH events to the phylogenetic tree revealed a striking pattern in which CNLOH was separately acquired many times, reflecting convergent evolution. Cells with CNLOH events were biased towards the earlier basal epithelial state, suggestive of a selective advantage that leads to prevalent recurrence of chr9q CNLOH. Together, we demonstrate that SMART-PTA is an efficient, scalable approach for single-cell whole-genome and whole-transcriptome profiling to build phenotypically annotated single-cell phylogenies with enough throughput and power for application to normal tissue somatic evolution. Moreover, we reconstruct the evolutionary history of the esophageal epithelium at high scale and resolution, providing a window into the dynamics and processes that shape clonal expansions in phenotypically normal tissues throughout a lifespan.

genomics↗

bioRxiv2025

Single-cell mapping of regulatory DNA:Protein interactions

Gene expression is coordinated by a multitude of transcription factors (TFs), whose binding to the genome is directed through multiple interconnected epigenetic signals, including chromatin accessibility and histone modifications. These complex networks have been shown to be disrupted during aging, disease, and cancer. However, profiling these networks across diverse cell types and states has been limited due to the technical constraints of existing methods for mapping DNA:Protein interactions in single cells. As a result, a critical gap remains in understanding where TFs or other chromatin remodelers bind to DNA and how these interactions are perturbed in pathological contexts. To address this challenge, we developed a transformative single-cell immuno-tethering DNA:Protein mapping technology. By coupling a species-specific antibody-binding nanobody to a cytosine base editing enzyme, this approach enables profiling of even weak or transient factor binding to DNA, a task that was previously unachievable in single cells. Thus, our Docking & Deamination followed by sequencing (D&D-seq) technique induces cytosine-to-uracil edits in genomic regions bound by the target protein, offering a novel means to capture DNA:Protein interactions with unprecedented resolution. Importantly, this technique can be seamlessly incorporated into common single-cell multiomics workflows, enabling multimodal analysis of gene regulation in single cells. We tested the ability of D&D-seq to record TF binding both in bulk and at the single-cell level by profiling CTCF and GATA family members, obtaining high specificity and efficiency, with clear identification of TF footprint and signal retention in the targeted cell subpopulations. Furthermore, the deamination reaction showed minimal off-target activity, with high concordance to bulk ChIP-seq reference data. Applied to primary human peripheral blood mononuclear cells (PBMCs), D&D-seq successfully identified CTCF binding sites and enabled integration with advanced machine-learning algorithms for predicting 3D chromatin structure. Furthermore, we integrated D&D-seq with single-cell genotyping to assess the impact of IDH2 mutations on CTCF binding in a human clonal hematopoiesis sample, uncovering altered binding and chromatin co-accessibility patterns in mutant cells. Altogether, D&D-seq represents an important technological advance enabling the direct mapping of TF or chromatin remodeler binding to the DNA in primary human samples, opening new avenues for understanding chromatin and transcriptional regulation in health and disease.

genomics↗

bioRxiv2021

Dual targeting of salt inducible kinases and CSF1R uncouples bone formation and bone resorption

Bone formation and resorption are typically coupled, such that the efficacy of anabolic osteoporosis treatments may be limited by bone destruction. The multi-kinase inhibitor YKL-05-099 potently inhibits salt inducible kinases (SIKs) and may represent a promising new class of bone anabolic agents. Here we report that YKL-05-099 increases bone formation in hypogonadal female mice without increasing bone resorption. Postnatal mice with inducible, global deletion of SIK2 and SIK3 show increased bone mass, increased bone formation, and, distinct from the effects of YKL-05-099, increased bone resorption. No cell-intrinsic role of SIKs in osteoclasts was noted. In addition to blocking SIKs, YKL-05-099 also binds and inhibits CSF1R, the receptor for the osteoclastogenic cytokine M-CSF. Modeling reveals that YKL-05-099 binds to SIK2 and CSF1R in a similar manner. Dual targeting of SIK2/3 and CSF1R induces bone formation without concomitantly increasing bone resorption and thereby may overcome limitations of most current anabolic osteoporosis therapies.

physiology↗

bioRxiv2020

Single-cell transcriptome maps of myeloid blood cell lineages in Drosophila

Drosophila lymph gland, the larval hematopoietic organ comprised of prohemocytes and hemocytes, has been a valuable model for understanding mechanisms underlying hematopoiesis and immunity. Three types of mature hemocytes have been characterized in the lymph gland: plasmatocytes, lamellocytes, and crystal cells, which are analogous to vertebrate myeloid cells. Here, we used single-cell RNA sequencing to comprehensively analyze heterogeneity of developing hemocytes in the lymph gland, and discovered novel hemocyte types, stem-like prohemocytes, and intermediate prohemocytes. Additionally, we identified the emergence of the lamellocyte lineage following active cellular immunity caused by wasp infestation. We unraveled similarities and differences between embryonically derived- and larval lymph gland hemocytes. Finally, the comparison of Drosophila lymph gland hemocytes and human immune cells highlights similarities between prohemocytes and hematopoietic stem cell, and between mature hemocytes and myeloid cells across species. Altogether, our study provides detailed insights on the development and evolution of hematopoiesis at single-cell resolution.

developmental biology↗

bioRxiv2019

A single-cell survey of Drosophila blood

Drosophila blood cells, called hemocytes, are classified into plasmatocytes, crystal cells, and lamellocytes based on the expression of a few marker genes and cell morphologies, which are inadequate to classify the complete hemocyte repertoire. Here, we used single-cell RNA sequencing (scRNA-seq) to map hemocytes across different inflammatory conditions in larvae. We resolved plasmatocytes into different states based on the expression of genes involved in cell cycle, antimicrobial response, and metabolism together with the identification of intermediate states. Further, we discovered rare subsets within crystal cells and lamellocytes that express fibroblast growth factor (FGF) ligand branchless and receptor breathless, respectively. We demonstrate that these FGF components are required for mediating effective immune responses against parasitoid wasp eggs, highlighting a novel role for FGF signaling in inter-hemocyte crosstalk. Our scRNA-seq analysis reveals the diversity of hemocytes and provides a rich resource of gene expression profiles for a systems-level understanding of their functions. HighlightsO_LIscRNA-seq of Drosophila blood recovers plasmatocytes, crystal cells, and lamellocytes C_LIO_LIscRNA-seq identifies different plasmatocyte states based on the expression of genes involved in cell cycle regulation, antimicrobial response, and metabolism C_LIO_LIPseudotemporal ordering of single cells identifies crystal cell and lamellocyte intermediate states C_LIO_LIscRNA-seq uncovers a novel role for FGF signaling in inter-hemocyte crosstalk C_LI

immunology↗

bioRxiv2017

High-confidence Coding and Noncoding Transcriptome Maps

The advent of high-throughput RNA-sequencing (RNA-seq) has led to the discovery of unprecedentedly immense transcriptomes encoded by eukaryotic genomes. However, the transcriptome maps are still incomplete partly because they were mostly reconstructed based on RNA-seq reads that lack their orientations (known as unstranded reads) and certain boundary information. Methods to expand the usability of unstranded RNA-seq data by predetermining the orientation of the reads and precisely determining the boundaries of assembled transcripts could significantly benefit the quality of the resulting transcriptome maps. Here, we present a high-performing transcriptome assembly pipeline, called CAFE, that significantly improves the original assemblies, respectively assembled with stranded and/or unstranded RNA-seq data, by orienting unstranded reads using the maximum likelihood estimation and by integrating information about transcription start sites and cleavage and polyadenylation sites. Applying large-scale transcriptomic data comprising ninety-nine billion RNAs-seq reads from the ENCODE, human BodyMap projects, The Cancer Genome Atlas, and GTEx, CAFE enabled us to predict the directions of about eighty-nine billion unstranded reads, which led to the construction of more accurate transcriptome maps, comparable to the manually curated map, and a comprehensive lncRNA catalogue that includes thousands of novel lncRNAs. Our pipeline should not only help to build comprehensive, precise transcriptome maps from complex genomes but also to expand the universe of non-coding genomes.

bioinformatics↗