Biology subjects

Fullwood, M. J.

Publications and source records attributed to Fullwood, M. J..

12 recordsLinked to original sources

bioRxiv2026

AI4Loop: an Artificial Intelligence Framework Reveals Increased 3D Chromatin Interactions and Therapeutic Vulnerabilities across 12,000 Cancer Samples

Three-dimensional chromatin interactions shape gene regulation, but their large-scale analysis remains limited by the cost and complexity of experimental assays. Here we present AI4Loop, a deep learning framework that infers genome-wide gene-centered chromatin interaction networks directly from RNA-seq data. Across multiple cell types, AI4Loop recovered interaction patterns consistent with clinical samples and orthogonal chromatin conformation datasets. Applied to 12,347 transcriptomes from 32 cancer types, AI4Loop revealed pervasive increases in gene-centered chromatin interactions in tumors, particularly at oncogene-associated loci. These inferred interaction networks outperformed gene expression alone in cancer classification. Integration with more than 50,000 drug-treated transcriptomes identified compounds predicted to reverse cancer-associated interaction gains. Hi-C experiments confirmed that the oxazolidinone antibiotics eperezolid and radezolid reduce breast cancer-gain chromatin interactions. Together, these results identify increased gene-centered chromatin interactions as a pan-cancer feature and provide a scalable strategy for linking 3D genome dysregulation to therapeutic vulnerabilities.

bioinformatics↗

bioRxiv2025

c-MYC can Form Phase Condensates via its DNA Binding Domain

The c-MYC oncogene is overexpressed in cancers. Phase condensates are membrane-less cellular compartments in cells. Using the optoDroplet system, which leverages optogenetics for condensate dynamics studies, here we showed c-MYC has the capability to form phase condensates. Moreover, the 3 terminus of c-MYC, which contains a DNA binding domain but no intrinsic disordered regions, is sufficient to form phase condensates. Our research contributes to a better understanding of c-MYC biology.

cancer biology↗

bioRxiv2023

Super-silencer perturbation by EZH2 and REST inhibition leads to large loss of chromatin interactions and reduction in cancer growth

Human silencers have been shown to exist and regulate developmental gene expression. However, the functional importance of human silencers needs to be elucidated, such as whether they can form "super-silencers" and whether they are linked to cancer progression. Here, through interrogating two putative silencer components of FGF18 gene, we found that two nearby silencers can cooperate via compensatory chromatin interactions to form a "super-silencer". Furthermore, double knockout of two silencers exhibited synergistic upregulation of FGF18 expression and changes of cell identity. To perturb the "super-silencers", we applied combinational treatment of an EZH2 inhibitor GSK343, and a REST inhibitor, X5050 ("GR"). We found that GR led to severe loss of TADs and loops, while the use of one inhibitor by itself only showed mild changes. Such changes in TADs and loops were associated with reduced CTCF and TOP2A mRNA levels. Moreover, GSK343 and X5050 synergistically upregulated super-silencer-controlled genes related to cell cycle, apoptosis and DNA damage, leading to anticancer effects both in vitro and in vivo. Overall, our data demonstrated the first example of a "super-silencer" and showed that combinational usage of GSK343 and X5050 to disrupt "super-silencers" could potentially lead to cancer ablation.

molecular biology↗

bioRxiv2022

MCIBox: A Toolkit for Single-molecule Multi-way Chromatin Interaction Visualization and Micro-Domains Identification

The emerging ligation-free three-dimensional (3D) genome mapping technologies can identify multiplex chromatin interactions with single-molecule precision. These technologies offer new insight into high-dimensional chromatin organization and gene regulation, but also introduce new challenges in data visualization and analysis. To overcome these challenges, we developed MCIBox, a toolkit for Multi-way Chromatin Interaction (MCI) analysis, including a visualization tool and a platform for identifying micro-domains with clustered single-molecule chromatin complexes. MCIBox is based on various clustering algorithms integrated with dimensionality reduction methods that can display multiplex chromatin interactions at single-molecule level, allowing users to explore chromatin extrusion patterns and super-enhancers regulation modes in transcription, and to identify single-molecule chromatin complexes that are clustered into micro-domains. Furthermore, MCIBox incorporates a two-dimensional kernel density estimation algorithm to identify micro-domains boundaries automatically. These micro-domains were stratified with distinctive signatures of transcription activity and contained different cell cycle associated genes. MCIBox could potentially distinguish the specificity of single-molecule chromatin interaction patterns in various phases of a cell cycle or cell types.

genomics↗

bioRxiv2022

DiSCs: Domains involving SETDB1 and Cohesin are critical regulators of genome topology and stem cell fate

SETDB1 is a key regulator of lineage-specific genes and endogenous retroviral elements (ERVs) through its deposition of repressive H3K9me3 mark. Apart from its H3K9me3 regulatory role, SETDB1 has seldom been studied in terms of its other potential regulatory roles. To investigate this, a genomic survey of SETDB1 binding in mouse embryonic stem cells across multiple libraries was conducted, leading to the unexpected discovery of regions bereft of common repressive histone marks (H3K9me3, H3K27me3). These regions were enriched with the CTCF motif that is often associated with the topological regulator Cohesin. Further profiling of these non-H3K9me3 regions led to the discovery of a cluster of non-repeat loci that were co-bound by SETDB1 and Cohesin. These regions, which we named DiSCs (Domains involving SETDB1 and Cohesin) were seen to be proximal to the gene promoters involved in embryonic stem cell pluripotency and lineage development. Importantly, it was found that SETDB1-Cohesin co-regulate target gene expression and genome topology at these DiSCs. Depletion of SETDB1 led to localized dysregulation of Cohesin binding thereby locally disrupting topological structures. Dysregulated gene expression trends revealed the importance of this cluster in ES cell maintenance as well as at gene islands that drive differentiation to other lineages. The unearthing of the DiSCs thus unravels a unique topological and transcriptional axis of control regulated chiefly by SETDB1.

genomics↗

bioRxiv2021

MYC overexpression leads to increased chromatin interactions at superenhancers and c-Myc binding sites

The MYC oncogene encodes for the c-Myc protein and is frequently dysregulated across multiple cancer cell types, making it an attractive target for cancer therapy. There have been many difficulties in targeting c-Myc, due to its complex network of regulators and the unstructured nature of its protein. Thus, we are interested in looking at the downstream cancer-specific functions of c-Myc. Overexpression of MYC leads to c-Myc binding at active enhancers, resulting in a global transcriptional amplification of active genes. However, the mechanism underlying this c-Myc enhancer invasion has not been well studied. To that end, we performed ChIP-seq, RNA-seq, 4C-seq and SIQHiC (Spike-in Quantitative Hi-C) on the U2OS osteosarcoma cell line with tetracycline-inducible MYC. MYC overexpression in U2OS cells modulated histone acetylation and increased c-Myc binding at superenhancers. SIQHiC analysis revealed increased global chromatin contact frequency, particularly at chromatin interactions connecting c-Myc binding sites. Our results suggest that c-Myc molecules are recruited to and accumulates within zones of high transcription activity, binding first at stable promoter binding sites at low expression levels, then at superenhancer binding sites when overexpressed. At the same time, the recruitment of c-Myc and other transcription factors may stabilize chromatin interactions to increase chromatin contact frequency. The accumulation of c-Myc at cancer-type specific superenhancers may then drive the expression of interacting oncogenes that each cancer is highly reliant on. By elucidating the chromatin landscape of c-Myc driven cancers, we can potentially target these chromatin interactions for cancer therapy, without affecting physiological c-Myc signaling.

genomics↗

bioRxiv2020

Three-dimensional Genome Organization Maps in Normal Haematopoietic Stem Cells and Acute Myeloid Leukemia

Acute Myeloid Leukemia (AML) is a highly lethal blood cancer arising due to aberrant differentiation of haematopoietic stem cells. Here we obtained 3D genome organization maps by Hi-C in the CD34+ haematopoietic stem cells from three healthy individuals and eight individuals with AML, and found that AML have increased loops to oncogenes compared with normal CD34+ cells. The MEIS1 oncogenic transcription factor is regulated by a Frequently Interacting Region (FIRE). This FIRE is only present in normal bone marrow samples, and four of eight AML sample. FIRE presence is associated with MEIS1 expression. CRISPR excision of a FIRE boundary led to loss of MEIS1 and reduced cell growth. Moreover, MEIS1 can bind to the promoter of HOXA9, and HOXA9 shows gain of Acute Myeloid Leukemia-specific super-enhancers that loop to the HOXA9 promoter. SignificanceWe found that Acute Myeloid Leukemias have more chromatin loops to oncogenes compared with normal blood stem cells. We identified heterogeneity in chromatin interactions at oncogenes, and heterogeneity in super-enhancers that loop to oncogenes, as two key epigenetic mechanisms that underlie MEIS1 and HOXA9 oncogene expression respectively.

cancer biology↗

bioRxiv2019

Defining Essential Enhancer for Pluripotent stem cells using Features Oriented CRISPR-Cas9 Screen

Cis Regulatory Elements (CREs) regulate the expression of the genes in their genomic neighborhoods and influence cellular processes such as cell-fate maintenance and differentiation. To date, there remain major gaps in the functional characterization of CREs and the identification of its target genes in the cellular native environment. In this study, we performed a Features Oriented CRISPR Utilized Systematic (FOCUS) screen of OCT4-bound CREs using CRISPR/Cas9 to identify functional enhancers important for pluripotency maintenance in mouse ES cells. From the initial 235 candidates tested, 16 CREs were identified to be essential stem cell enhancers. Using RNA-seq and genomic 4C-seq, we further uncovered a complex network of candidate CREs and their downstream target genes, which supports the growth and self-renewal of mESCs. Notably, an essential enhancer, CRE111, and its target, Lrrc31, form the important switch to modulate the LIF-JAK1-STAT3 signaling pathway.

genomics↗

bioRxiv2019

TP63, SOX2 and KLF5 Establish Core Regulatory Circuitry and Construct Cancer Specific Epigenome in Esophageal Squamous Cell Carcinoma

Transcriptional network is controlled by master transcription factors (TFs) and cis-regulatory elements through interacting with target sequences and recruiting epigenetic regulators. By integration of enhancer profiling and chromatin accessibility, we establish super-enhancer (SE) mediated core regulatory circuitry (CRC) for esophageal squamous cell carcinoma (ESCC) and identify tumor cells-dependent CRC TFs-TP63, SOX2 and KLF5. They preferentially co-occupy SE loci and form a positive interconnected auto-regulatory loop through SEs to orchestrate chromatin and transcriptional programming. SE-associated oncogene-ALDH3A1 is identified as a novel CRC target contributing to ESCC viability. Using circular chromosome conformation capture sequencing (4C-seq) and CRISPR/Cas9 genome editing, the direct interaction between TP63 promoter and functional enhancers which is mediated by CRC TFs is identified. Deletion of each enhancer decreases expression of CRC TFs and impairs cell viability, phenocopying the knockdown of each CRC TF. Targeting epigenetic regulation by inhibition of either the BET bromodomain or HDAC disrupts the CRC program and its dependent global epigenetic modification, consequently suppressing ESCC tumor growth. Importantly, combination of both compounds result in synergistic anti-tumor effect.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=162 SRC=\"FIGDIR/small/825372v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (58K):\norg.highwire.dtl.DTLVardef@1a9f923org.highwire.dtl.DTLVardef@238c90org.highwire.dtl.DTLVardef@1e14f58org.highwire.dtl.DTLVardef@120249a_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LISuper-enhancers mediated transcriptional regulatory circuitry is established for ESCC\nC_LIO_LITP63, SOX2 and KLF5 as CRC TFs co-localize super-enhancer loci to orchestrate chromatin accessibility and transcriptional dysregulation\nC_LIO_LIComplex interaction between functional enhancers and TP63 promoter is mediated by CRC TFs\nC_LIO_LIALDH3A1 is a key downstream target of ESCC CRC and is essential for ESCC cell survival\nC_LIO_LIBET degrader-ARV-771 and HDAC inhibitor-Romidepsin synergistically inhibit ESCC tumor growth\nC_LI

cancer biology↗

bioRxiv2019

Predicting chromatin interactions between open chromatin regions from DNA sequences

Chromatin interactions play important roles in regulating gene expression. However, the availability of genome-wide chromatin interaction data is very limited. Various computational methods have been developed to predict chromatin interactions. Most of these methods rely on large collections of ChIP-Seq/RNA-Seq/DNase-Seq datasets and predict only enhancer-promoter interactions. Some of the state-of-the-art methods have poor experimental designs, leading to over-exaggerated performances and misleading conclusions. Here we developed a computational method, Chromatin Interaction Neural Network (CHINN), to predict chromatin interactions between open chromatin regions by using only DNA sequences of the interacting open chromatin regions. CHINN is able to predict CTCF- and RNA polymerase II-associated chromatin interactions between open chromatin regions. CHINN also shows good across-sample performances and captures various sequence features that are predictive of chromatin interactions. We applied CHINN to 84 chronic lymphocytic leukemia (CLL) samples and detected systematic differences in the chromatin interactome between IGVH-mutated and IGVH-unmutated CLL samples.

bioinformatics↗

bioRxiv2019

H3K27me3-rich genomic regions can function as silencers to repress gene expression via chromatin interactions

Gene repression and silencers are poorly understood. We reasoned that H3K27me3-rich regions (MRRs) of the genome defined from clusters of H3K27me3 peaks may be used to identify silencers that can regulate gene expression via proximity or looping. MRRs were associated with chromatin interactions and interact preferentially with each other. MRR component removal at interaction anchors by CRISPR led to upregulation of interacting target genes, altered H3K27me3 and H3K27ac levels at interacting regions, and altered chromatin interactions. Chromatin interactions did not change at regions with high H3K27me3, but regions with low H3K27me3 and high H3K27ac levels showed changes in chromatin interactions. The MRR knockout cells also showed changes in phenotype associated with cell identity, and altered xenograft tumor growth. MRR-associated genes and long-range chromatin interactions were susceptible to H3K27me3 depletion. Our results characterized H3K27me3-rich regions and their mechanisms of functioning via looping.

genomics↗

bioRxiv2019

NanoVar: Accurate Characterization of Patients’ Genomic Structural Variants Using Low-Depth Nanopore Sequencing

Despite the increasing relevance of structural variants (SV) in the development of many human diseases, progress in novel pathological SV discovery remains impeded, partly due to the challenges of accurate and routine SV characterization in patients. The recent advent of third-generation sequencing (3GS) technologies brings promise for better characterization of genomic aberrations by virtue of having longer reads. However, the applications of 3GS are restricted by their high sequencing error rates and low sequencing throughput. To overcome these limitations, we present NanoVar, an accurate, rapid and low-depth (4X) 3GS SV caller utilizing long-reads generated by Oxford Nanopore Technologies. NanoVar employs split-reads and hard-clipped reads for SV detection and utilizes a neural network classifier for true SV enrichment. In simulated data, NanoVar demonstrated the highest SV detection accuracy (F1 score = 0.91) amongst other long-read SV callers using 12 gigabases (4X) of sequencing data. In patient samples, besides the detection of genomic aberrations, NanoVar also uncovered many normal alternative sequences or alleles which were present in healthy individuals. The low sequencing depth requirements of NanoVar enable the use of Nanopore sequencing for accurate SV characterization at a lower sequencing cost, an approach compatible with clinical studies and large-scale SV-association research.

bioinformatics↗