Biology subjects

Lee, D.-I.

Publications and source records attributed to Lee, D.-I..

3 recordsLinked to original sources

bioRxiv2023

Examining dynamics of three-dimensional genome organization with multi-task matrix factorization

Three-dimensional (3D) genome organization, which determines how the DNA is packaged inside the nucleus, has emerged as a key component of the gene regulation machinery. High-throughput chromosome conformation datasets, such as Hi-C, have become available across multiple conditions and timepoints, offering a unique opportunity to examine changes in 3D genome organization and link them to phenotypic changes in normal and diseases processes. However, systematic detection of higher-order structural changes across multiple Hi-C datasets remains a major challenge. Existing computational methods either do not model higher-order structural units or cannot model dynamics across more than two conditions of interest. We address these limitations with Tree-Guided Integrated Factorization (TGIF), a generalizable multi-task Non-negative Matrix Factorization (NMF) approach that can be applied to time series or hierarchically related biological conditions. TGIF can identify large-scale changes at compartment or subcompartment levels, as well as local changes at boundaries of topologically associated domains (TADs). Compared to existing methods, TGIF boundaries are more enriched in CTCF and reproducible across biological replicates, normalization methods, depths, and resolutions. Application to three multi-sample mammalian datasets shows TGIF can detect differential regions at compartment, subcompartment, and boundary levels that are associated with significant changes in regulatory signals and gene expression enriched in tissue-specific processes. Finally, we leverage TGIF boundaries to prioritize sequence variants for multiple phenotypes from the NHGRI GWAS catalog. Taken together, TGIF is a flexible tool to examine 3D genome organization dynamics across disease and developmental processes.

bioinformatics↗

bioRxiv2020

Graph-regularized matrix factorization for reliable detection of topological units from high-throughput chromosome conformation capture datasets

The three-dimensional (3D) organization of the genome plays a critical role in gene regulation for diverse normal and disease processes. High-throughput chromosome conformation capture (3C) assays, such as Hi-C, SPRITE, GAM, and HiChIP, have revealed higher-order organizational units such as topologically associating domains (TADs), which can shape the regulatory landscape governing downstream phenotypes. Analysis of high-throughput 3C data depends on the sequencing depth, which directly affects the resolution and the sparsity of the generated 3D contact count map. Identification of TADs remains a significant challenge due to the sensitivity of existing methods to resolution and sparsity. Here we present GRiNCH, a novel matrix-factorization-based approach for simultaneous TAD discovery and smoothing of contact count matrices from high-throughput 3C data. GRiNCH TADs are enriched in known architectural proteins and chromatin modification signals and are stable to the resolution, and sparsity of the input data. GRiNCH smoothing improves the recovery of structure and significant interactions from low-depth datasets. Furthermore, enrichment analysis of 746 transcription factor motifs in GRiNCH TADs from developmental time-course and cell-line Hi-C datasets predicted transcription factors with potentially novel genome organization roles. GRiNCH is a broadly applicable tool for the analysis of high throughput 3C datasets from a variety of platforms including SPRITE and HiChIP to understand 3D genome organization in diverse biological contexts.

bioinformatics↗

bioRxiv2020

PGC1/PPAR Drive Cardiomyocyte Maturation through Regulation of Yap1 and SF3B2

Cardiomyocytes undergo significant levels of structural and functional changes after birth--fundamental processes essential for the heart to produce the volume and contractility to pump blood to the growing body. However, due to the challenges in isolating single postnatal/adult myocytes, how individual newborn cardiomyocytes acquire multiple aspects of mature phenotypes remains poorly understood. Here we implemented large-particle sorting and analyzed single myocytes from neonatal to adult hearts. Early myocytes exhibited a wide-ranging transcriptomic and size heterogeneity, maintained until adulthood with a continuous transcriptomic shift. Gene regulatory network analysis followed by mosaic gene deletion revealed that peroxisome proliferator-activated receptor coactivator-1 signaling--activated in vivo but inactive in pluripotent stem cell-derived cardiomyocytes--mediates the shift. The signaling regulated key aspects of cardiomyocyte maturation simultaneously through previously unrecognized regulators, including Yap1 and SF3B2. Our study provides a single-cell roadmap of heterogeneous transitions coupled to cellular features and unveils a multifaceted regulator controlling cardiomyocyte maturation. Significance StatementHow the individual single myocytes achieve full maturity remains a black box, largely due to the challenges with the isolation of single mature myocytes. Understanding this process is particularly important as the immaturity and early developmental arrest of pluripotent stem cell-derived myocytes has emerged a major concern in the field. Here we present the first study of high-quality single-cell transcriptomic analysis of cardiac muscle cells from neonatal to adult hearts. We identify a central transcription factor and its novel targets that control key aspects of myocyte maturation, including cellular hypertrophy, contractility, and mitochondrial activity.

developmental biology↗