Hyobin Jeong

Genome-wide association studies (GWAS) have identified numerous single-nucleotide polymorphisms (SNPs) associated with various diseases, including cancer. However, the mechanisms by which these SNPs contribute to disease susceptibility remain largely unclear. While recent studies have explored the transcriptional impact of disease-associated SNPs, their role in post-transcriptional regulation has been less extensively investigated. In this study, we investigated whether cancer-associated SNPs influence gene expression by altering N6 -methyladenosine (m ⁶ A) RNA methylation. We collected GWAS-identified SNPs across nine cancer types and integrated these with matched tumor and normal m ⁶ A RNA immunoprecipitation sequencing (m ⁶ A-seq) and RNA sequencing (RNA-seq) datasets. We first identified differentially methylated m ⁶ A sites and assessed whether cancer-associated SNPs were enriched within these regions. These analyses revealed that cancer-associated SNPs were significantly enriched within hypermethylated m ⁶ A regions in colon cancer. Integrative analysis revealed that SNPs enriched in m ⁶ A-modified regions are associated with altered gene expression and RNA splicing, suggesting that m ⁶ A methylation mediates the post-transcriptional impact of genetic variants. Experimental validation further confirmed altered gene expression following ALKBH5 knockdown, consistent with patient-derived data. Collectively, our findings support a novel mechanistic connection between genetic variants and RNA methylation-driven transcriptomic regulation in colorectal cancer, underscoring the epitranscriptome as a potential axis of oncogenic control.

Seung Kyun Noh, Minhyeok Lee & Hyobin Jeong. BMB Reports -0001;0:. https://doi.org/10.5483/BMBRep.2025-0015

Naïve CD4 T cells are traditionally viewed as a quiescent, homogeneous, resting population, but emerging evidence reveals their heterogeneity, which can be crucial for understanding disease contexts and therapeutic outcomes. In this study, we identify distinct subpopulations within both murine and human naïve CD4 T cells by single cell-RNA-sequencing (scRNA-seq), particularly focusing on a subpopulation that expresses super-high levels of interleukin-7 receptor (IL-7R^sup-hi), along with CD97, IL-18R, and Ly6C. This subpopulation, absent in the thymus and peripherally induced, exhibits type 1 helper T cell (Th1)-poised characteristics and contributes to the inhibition of cancer progression in B16F10 tumor-bearing mice. In humans, this IL-7R^sup-hi subpopulation expressing CD97 correlates with the responsiveness to anti-PD-1 therapy in cancer patients and the disease state of multiple sclerosis. By elucidating the heterogeneity of naive CD4 T cells and identifying a Th1-poised subpopulation capable of robust type 1 responses, we highlight the importance of this heterogeneity in inflammatory conditions for defining the disease states and predicting drug responsiveness.

The most common chemotherapeutics induce DNA damage to eradicate cancer cells, yet defective DNA repair can propagate mutations, instigating therapy resistance and secondary malignancies. Structural variants (SVs), arising from copy-number-imbalanced and -balanced DNA rearrangements, are a major driver of tumor evolution, yet understudied posttherapy. Here, we adapted single-cell template-strand sequencing (Strand-seq) to a HER2+ breast cancer model to investigate the formation of doxorubicin-induced de novo SVs. We coupled this approach with nucleosome occupancy (NO) measurements obtained from the same single cell to enable simultaneous SV detection and cell-type classification. Using organoids from TetO-CMYC/TetO-Neu/MMTV-rtTA mice modeling HER2+ breast cancer, we generated 459 Strand-seq libraries spanning various tumorigenesis stages, identifying a 7.4-fold increase in large chromosomal alterations post-doxorubicin. Complex DNA rearrangements, deletions, and duplications were prevalent across basal, luminal progenitor (LP), and mature luminal (ML) cells, indicating uniform susceptibility of these cell types to SV formation. Doxorubicin further elevated sister chromatid exchanges (SCEs), indicative of genomic stress persisting posttreatment. Altered nucleosome occupancy levels on distinct cancer-related genes further underscore the broad genomic impact of doxorubicin. The organoid-based system for single-cell multiomics established in this study paves the way for unraveling the most important therapy-associated SV mutational signatures, enabling systematic studies of the effect of therapy on cancer evolution.

Chromosomal instability is a major driver of intratumoral heterogeneity (ITH), promoting tumor progression. In the present study, we combined structural variant discovery and nucleosome occupancy profiling with transcriptomic and immunophenotypic changes in single cells to study ITH in complex karyotype acute myeloid leukemia (CK-AML). We observed complex structural variant landscapes within individual cells of patients with CK-AML characterized by linear and circular breakage–fusion–bridge cycles and chromothripsis. We identified three clonal evolution patterns in diagnosis or salvage CK-AML (monoclonal, linear and branched polyclonal), with 75% harboring multiple subclones that frequently displayed ongoing karyotype remodeling. Using patient-derived xenografts, we demonstrated varied clonal evolution of leukemic stem cells (LSCs) and further dissected subclone-specific drug–response profiles to identify LSC-targeting therapies, including BCL-xL inhibition. In paired longitudinal patient samples, we further revealed genetic evolution and cell-type plasticity as mechanisms of disease progression. By dissecting dynamic genomic, phenotypic and functional complexity of CK-AML, our findings offer clinically relevant avenues for characterizing and targeting disease-driving LSCs.

The functional impact and cellular context of mosaic structural variants (mSVs) in normal tissues is understudied. Utilizing Strand-seq, we sequenced 1,133 single-cell genomes from 19 human donors of increasing age, and discovered the heterogeneous mSV landscapes of hematopoietic stem and progenitor cells. While mSVs are continuously acquired throughout life, expanded subclones in our cohort are confined to individuals >60. Cells already harboring mSVs are more likely to acquire additional somatic structural variants, including megabase-scale segmental aneuploidies. Capitalizing on comprehensive single-cell micrococcal nuclease digestion with sequencing reference data, we conducted high-resolution cell-typing for eight hematopoietic stem and progenitor cells. Clonally expanded mSVs disrupt normal cellular function by dysregulating diverse cellular pathways, and enriching for myeloid progenitors. Our findings underscore the contribution of mSVs to the cellular and molecular phenotypes associated with the aging hematopoietic system, and establish a foundation for deciphering the molecular links between mSVs, aging and disease susceptibility in normal tissues.

Structural variants (SVs) are genomic rearrangements that can take many different forms such as copy number alterations, inversions and translocations. During cell development and aging, somatic SVs accumulate in the genome with potentially neutral, deleterious or pathological effects. Generation of somatic SVs is a key mutational process in cancer development and progression. Despite their importance, the detection of somatic SVs is challenging, making them less studied than somatic single-nucleotide variants. In this review, we summarize recent advances in whole-genome sequencing (WGS)-based approaches for detecting somatic SVs at the tissue and single-cell levels and discuss their advantages and limitations. First, we describe the state-of-the-art computational algorithms for somatic SV calling using bulk WGS data and compare the performance of somatic SV detectors in the presence or absence of a matched-normal control. We then discuss the unique features of cutting-edge single-cell-based techniques for analyzing somatic SVs. The advantages and disadvantages of bulk and single-cell approaches are highlighted, along with a discussion of their sensitivity to copy-neutral SVs, usefulness for functional inferences and experimental and computational costs. Finally, computational approaches for linking somatic SVs to their functional readouts, such as those obtained from single-cell transcriptome and epigenome analyses, are illustrated, with a discussion of the promise of these approaches in health and diseases.

Leaf senescence, the last stage of leaf development, is essential for whole-plant fitness as it marks the relocation of nutrients from senescing leaves to reproductive or other developing organs. Temporally coordinated physiological and functional changes along leaf aging are fine-tuned by a highly regulated genetic program involving multi-layered regulatory mechanisms. Long noncoding RNAs (lncRNAs) are newly emerging as hidden players in many biological processes; however, their contribution to leaf senescence has been largely unknown. Here, we performed comprehensive analyses of RNA-seq data representing all developmental stages of leaves to determine the genome-wide lncRNA landscape along leaf aging. A total of 771 lncRNAs, including 232 unannotated lncRNAs, were identified. Time-course analysis revealed 446 among 771 developmental age-related lncRNAs (AR-lncRNAs). Intriguingly, the expression of AR-lncRNAs was regulated more dynamically in senescing leaves than in growing leaves, revealing the relevant contribution of these lncRNAs to leaf senescence. Further analyses enabled us to infer the function of lncRNAs, based on their interacting miRNA or mRNA partners. We considered functionally diverse lncRNAs including antisense lncRNAs (which regulate overlapping protein-coding genes), competitive endogenous RNAs (ceRNAs; which regulate paired mRNAs using miRNAs as anchors), and mRNA-interacting lncRNAs (which affect the stability of mRNAs). Furthermore, we experimentally validated the senescence regulatory function of three novel AR-lncRNAs including one antisense lncRNA and two mRNA-interacting lncRNAs through molecular and phenotypic analyses. Our study provides a valuable resource of AR-lncRNAs and potential regulatory networks that link the function of coding mRNA and AR-lncRNAs. Together, our results reveal AR-lncRNAs as important elements in the leaf senescence process.

Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their functional consequences. We present a computational method, scNOVA, which uses Strand-seq to perform haplotype-aware integration of SV discovery and molecular phenotyping in single cells by using nucleosome occupancy to infer gene expression as a readout. Application to leukemias and cell lines identifies local effects of copy-balanced rearrangements on gene deregulation, and consequences of SVs on aberrant signaling pathways in subclones. We discovered distinct SV subclones with dysregulated Wnt signaling in a chronic lymphocytic leukemia patient. We further uncovered the consequences of subclonal chromothripsis in T cell acute lymphoblastic leukemia, which revealed c-Myb activation, enrichment of a primitive cell state and informed successful targeting of the subclone in cell culture, using a Notch inhibitor. By directly linking SVs to their functional effects, scNOVA enables systematic single-cell multiomic studies of structural variation in heterogeneous cell populations.