Biology subjects

Wong, E. S.

Publications and source records attributed to Wong, E. S..

9 recordsLinked to original sources

bioRxiv2026

Aging activates latent enhancers that can be reversed withexercise

Aging profoundly alters the genome's regulatory landscape, but the properties of age-acquired enhancers, including how they are selected and sustained in aged animals are unclear. We used single-cell multiomics in the mouse heart to identify age-responsive cis-regulatory elements and endurance exercise to understand which of these elements can be attenuated. Aging increased AP-1 engagement at more than 100,000 regulatory loci across cardiac cell types. Exercise opposed most of these gains. Despite low endogenous accessibility, age-gained enhancer sequences drove reporter activity comparable to stable elements, revealing substantial latent transcriptional potential. Local sequence features distinguished responsiveness to aging and exercise. Reporter perturbations implicated sequence outside the AP-1 core, and mutagenesis localized informative positions to dispersed segments of dynamic enhancers. These enhancers were IL-1-sensitive and were preferentially responsive to neutralization of the cytokine in vivo. AP-1 inhibition further opposed age-associated transcription. Together, these findings support a model in which aging engages latent cell-type specific enhancers that are sustained in an active state by ongoing trans signaling. Aging therefore changes the deployment of existing regulatory information, while the acquired activity remains responsive to changes in signaling even in old age.

molecular biology↗

bioRxiv2025

Studying cis-regulatory heterogeneity in single-cells at allelic resolution

Single-cell RNA-seq data from F1 hybrids provides a unique framework for dissecting complex regulatory phenomena, but allelic measurements are limited by technical noise. Here, we present ASPEN, a statistical method for modeling allelic mean and variance in single-cell transcriptomic data from F1 hybrids. ASPEN uses a sensitive mapping pipeline and adaptive shrinkage to distinguish allelic imbalance and variance in single cells. Through extensive simulation based on sparse droplet-based single-cell data, ASPEN demonstrates improved sensitivity and control of false discoveries compared to existing approaches. Applied to mouse brain organoids and T cells, ASPEN identifies genes with incomplete X inactivation, stochastic monoallelic expression, and significant deviations in allelic variance. This reveals reduced variance in essential cellular pathways, and increased variance in neurodevelopmental and immune-specific genes.

bioinformatics↗

bioRxiv2024

A mouse organoid platform for modeling cerebral cortex development and cis-regulatory evolution in vitro

Natural selection has shaped the gene regulatory networks that orchestrate the development of the neocortex, leading to diverse neocortical structure and function across mammals, but the molecular and cellular mechanisms driving phenotypic changes have proven difficult to characterize. Here, we develop a reproducible protocol to generate neocortical organoids from mouse epiblast stem cells (EpiSCs) that gives rise to diverse cortical cell types, including distinct classes of excitatory neurons (pre-plate, deep-layer, and upper-layer) and glia (oligodendrocyte precursor cells, myelinating oligodendrocytes, astrocytes, ependymal cells). Cortical organoids develop with similar kinetics to the mouse cortex in vivo and begin to exhibit features of maturation in glia and neuronal cell types relatively rapidly compared to human brain organoids. Using this new protocol, we generated cortical organoids from F1 hybrid EpiSCs derived from crosses between standard laboratory mice (C57BL/6J) and four wild-derived mouse strains from distinct sub-species spanning [~]1M years of evolutionary divergence. This allowed us to comprehensively map cis-acting transcriptional regulatory variation across developing cortical cell types using scRNA-seq. We identify hundreds of genes that exhibit dynamic allelic imbalances during cortical neurogenesis, providing the first insight into the developmental mechanisms underpinning changes in cortical structure and function between mouse strains. These experimental methods and cellular resources represent a powerful new platform for investigating mechanisms of gene regulation in the developing cerebral cortex.

developmental biology↗

bioRxiv2024

DNA-Diffusion: Leveraging Generative Models for Controlling Chromatin Accessibility and Gene Expression via Synthetic Regulatory Elements

The challenge of systematically modifying and optimizing regulatory elements for precise gene expression control is central to modern genomics and synthetic biology. Advancements in generative AI have paved the way for designing synthetic sequences with the aim of safely and accurately modulating gene expression. We leverage diffusion models to design context-specific DNA regulatory sequences, which hold significant potential toward enabling novel therapeutic applications requiring precise modulation of gene expression. Our framework uses a cell type-specific diffusion model to generate synthetic 200 bp regulatory elements based on chromatin accessibility across different cell types. We evaluate the generated sequences based on key metrics to ensure they retain properties of endogenous sequences: transcription factor binding site composition, potential for cell type-specific chromatin accessibility, and capacity for sequences generated by DNA diffusion to activate gene expression in different cell contexts using state-of-the-art prediction models. Our results demonstrate the ability to robustly generate DNA sequences with cell type-specific regulatory potential. DNA-Diffusion paves the way for revolutionizing a regulatory modulation approach to mammalian synthetic biology and precision gene therapy.

synthetic biology↗

bioRxiv2024

A Bag-Of-Motif Model Captures Cell States at Distal Regulatory Sequences

Deciphering the intricate regulatory code governing cell-type-specific gene expression is a fundamental goal in genetics. Current methods struggle to capture the complex interplay between gene distal regulatory sequences and cell context. We developed a computational approach, BOM (Bag-of-Motifs), which represents cis-regulatory sequences by the type and number of TF binding motifs it contains, irrespective of motif order, orientation, and spacing. This simple yet powerful representation allows BOM to efficiently capture the complexity of cell-type-specific information encoded within these sequences. We apply BOM to mouse, human, and zebrafish distal regulatory regions, demonstrating remarkable accuracy. Notably, the method outperforms more complex deep learning models at the same task using fewer parameters. BOM can also uncover cross-species sequence similarities unrecognized by genome alignments. We experimentally validate our in silico predictions using enhancer reporter assay, showing that motifs with the most significant explanatory power are sequence determinants of cell-type specific enhancer activity. BOM offers a novel systematic framework for studying cell-type or condition-specific cis-regulatory sequences. Using BOM, we demonstrate the existence of a highly predictive sequence code at distal regulatory regions in mammals driven by TF binding motifs.

bioinformatics↗

bioRxiv2022

Quantitative trait and transcriptome analysis of genetic complexity underpinning cardiac interatrial septation in mice using an advanced intercross line

Unlike single-gene mutations leading to Mendelian conditions, common human diseases are likely emergent phenomena arising from multilayer, multiscale and highly interconnected interactions. Atrial and ventricular septal defects are the most common forms of cardiac congenital anomalies in humans. Atrial septal defects (ASD) show an open communication between left and right atria postnatally, potentially resulting in serious hemodynamic consequences if untreated. A milder form of atrial septal defect, patent foramen ovale (PFO), exists in about one quarter of the human population, strongly associated with ischaemic stroke and migraine. The anatomic liabilities and genetic and molecular basis of atrial septal defects remain unclear. Here, we advance our previous analysis of atrial septal variation through quantitative trait locus (QTL) mapping of an advanced intercross line (AIL) established between the inbred QSi5 and 129T2/SvEms mouse strains, that show extremes of septal phenotypes. Analysis resolved 37 unique septal QTL with high overlap between QTL for distinct septal traits. Whole genome sequencing of parental strains identified high confidence candidate deleterious variants, including in known human congenital heart disease genes, whereas transcriptome analysis of developing septa revealed networks involving ribosome, nucleosome, mitochondrial and extracellular matrix biosynthesis underlying septal variation. Analysis of variant architecture across different gene features, including enhancers and promoters, provided evidence for involvement of non-coding as well as protein coding variants. Our study provides the first high resolution picture of genetic complexity and network liability underlying common congenital heart disease, with relevance to human ASD and PFO.

genetics↗

bioRxiv2022

Synergistic Combined-proteomics Guided Mapping strategy identifies mTOR mediated phosphorylation of LARP1 in nutrient responsiveness and dilated cardiomyopathy

Increased activity of the mammalian target of rapamycin (mTOR) signalling pathway, a crucial nutrient sensor, exacerbates ageing and ageing-related diseases, including cancer and heart failure. To further elucidate the physiological role of the serine/threonine kinase mTOR, we devised a novel tractable proteomics strategy that combines interaction proteomics, proximity-based proteomics and quantitative phosphoproteomics to identify interactors with and potential substrates of mTOR. We identified 58 candidate mTOR substrates, several of which were further validated. Interestingly, several of these candidate mTOR substrates are involved in various aspects of RNA biology, including regulating stability and processing. We characterized in-depth one of the validated mTOR substrates, LARP1, an RNA binding protein. mTOR-dependent phosphorylation of LARP1 is nutrient-sensitive and controls the RNA-binding ability of LARP1. We show that mTOR activity and LARP1 and LARP1 phosphorylation levels are increased in a congenital mouse model of dilated cardiomyopathy (DCM) caused by a mutation in the Lamin A gene. This implicates LARP1 in the development of DCM.

molecular biology↗

bioRxiv2019

Early origin and deep conservation of enhancers in animals

Transcription factors (TFs) bind DNA enhancer sequences to regulate gene transcription in animals. Unlike TFs, the evolution of enhancers has been difficult to trace because of their rapid evolution. Here, we show enhancers from the sponge Amphimedon queenslandica can drive cell type-specific reporter gene expression in zebrafish and mouse, despite sponge and vertebrate lineages diverging over 700 million years ago. Although sponge enhancers, which are present in both highly conserved syntenic gene regions (Islet-Scaper, Ccne1-Uri and Tdrd3-Diaph3) and sponge-specific intergenic regions, have no significant sequence identity with vertebrate genomic sequences, the type and frequency of TF binding motifs in the sponge enhancer allow for the identification of homologous enhancers in bilaterians. Islet enhancers identified in human and mouse Scaper genes drive zebrafish reporter expression patterns that are almost identical to the sponge Islet enhancer. The existence of homologous enhancers in these disparate metazoans suggests animal development is controlled by TF-enhancer DNA interactions that were present in the first multicellular animals.\n\nOne-sentence summaryEnhancer activity is conserved across 700 million years of trans-phyletic divergence.

evolutionary biology↗

bioRxiv2016

Genetic variation and gene expression across multiple tissues and developmental stages in a non-human primate

By analyzing multi-tissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalogue of expression quantitative trait loci (eQTLs) in a non-human primate model. This catalogue contains more genome-wide significant eQTLs, per sample, than comparable human resources, and reveals sex and age-related expression patterns. Findings include a master regulatory locus that likely plays a role in immune function, and a locus regulating hippocampal long non-coding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders.

genetics↗