Biology subjects

Zang, C.

Publications and source records attributed to Zang, C..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Proximal immune-epithelial progenitor interactions drive chronic tissue sequelae post COVID-19

The long-term physiological consequences of SARS-CoV-2, termed Post-Acute Sequelae of COVID-19 (PASC), are rapidly evolving into a major public health concern. The underlying cellular and molecular etiology remain poorly defined but growing evidence links PASC to abnormal immune responses and/or poor organ recovery post-infection. Yet, the precise mechanisms driving non-resolving inflammation and impaired tissue repair in the context of PASC remain unclear. With insights from three independent clinical cohorts of PASC patients with abnormal lung function and/or viral infection-mediated pulmonary fibrosis, we established a clinically relevant mouse model of post-viral lung sequelae to investigate the pathophysiology of respiratory PASC. By employing a combination of spatial transcriptomics and imaging, we identified dysregulated proximal interactions between immune cells and epithelial progenitors unique to the fibroproliferation in respiratory PASC but not acute COVID-19 or idiopathic pulmonary fibrosis (IPF). Specifically, we found a central role for lung-resident CD8+ T cell-macrophage interactions in maintaining Krt8hi transitional and ectopic Krt5+ basal cell progenitors, thus impairing alveolar regeneration and driving fibrotic sequelae after acute viral pneumonia. Mechanistically, CD8+ T cell derived IFN-{gamma} and TNF stimulated lung macrophages to chronically release IL-1{beta}, resulting in the abnormal accumulation of dysplastic epithelial progenitors and fibrosis. Notably, therapeutic neutralization of IFN-{gamma} and TNF, or IL-1{beta} after the resolution of acute infection resulted in markedly improved alveolar regeneration and restoration of pulmonary function. Together, our findings implicate a dysregulated immune-epithelial progenitor niche in driving respiratory PASC. Moreover, in contrast to other approaches requiring early intervention, we highlight therapeutic strategies to rescue fibrotic disease in the aftermath of respiratory viral infections, addressing the current unmet need in the clinical management of PASC and post-viral disease.

immunology↗

bioRxiv2023

Integrative analysis of DNA replication origins and ORC binding sites in human cells reveals a lack of overlap between them

Based on experimentally determined average inter-origin distances of [~]100 kb, DNA replication initiates from [~]50,000 origins on human chromosomes in each cell cycle. The origins are believed to be specified by binding of factors like the Origin Recognition Complex (ORC) or CTCF or other features like G-quadruplexes. We have performed an integrative analysis of 113 genome-wide human origin profiles (from five different techniques) and 5 ORC-binding profiles to critically evaluate whether the most reproducible origins are specified by these features. Out of [~]7.5 million union origins identified by all datasets, only 0.27% were reproducibly obtained in at least 20 independent SNS-seq datasets and contained in initiation zones identified by each of three other techniques (20,250 shared origins), suggesting extensive variability in origin usage and identification. 21% of the shared origins overlap with transcriptional promoters, posing a conundrum. Although the shared origins overlap more than union origins with constitutive CTCF binding sites, G-quadruplex sites and activating histone marks, these overlaps are comparable or less than that of known Transcription Start Sites, so that these features could be enriched in origins because of the overlap of origins with epigenetically open, promoter-like sequences. Only 6.4% of the 20,250 shared origins were within 1 kb from any of the [~]13,000 reproducible ORC binding sites in human cancer cells, and only 4.5% were within 1 kb of the [~]11,000 union MCM2-7 binding sites in contrast to the nearly 100% overlap in the two comparisons in the yeast, S. cerevisiae. Thus, in human cancer cell lines, replication origins appear to be specified by highly variable stochastic events dependent on the high epigenetic accessibility around promoters, without extensive overlap between the most reproducible origins and currently known ORC- or MCM-binding sites.

genomics↗

bioRxiv2023

Spatially clustered pattern of transcription factor binding reveals phase-separated transcriptional condensates at super-enhancers

Many transcription factors (TFs) have been shown to bind at super-enhancers, forming transcriptional condensates to activate transcription in many cellular systems. Genomic and epigenomic determinants of phase-separated transcriptional condensates are not well understood. Here we systematically analyzed DNA sequence motifs and TF binding profiles across human cell types to identify the molecular features that contribute to the formation of transcriptional condensates. We found that most DNA sequence motifs are not distributed randomly in the genome, but exhibiting spatially clustered patterns associated with super-enhancers. TF binding sites are further clustered and enriched at cell-type-specific super-enhancers. TFs exhibiting clustered binding patterns also have high liquid-liquid phase separation abilities. Compared to regular TF binding, densely clustered TF binding sites are more enriched at cell-type-specific super-enhancers with higher chromatin accessibility, higher chromatin interaction, and higher association with cancer outcome. Our results indicate that the clustered pattern of genomic binding and the phase separation properties of TFs collectively contribute to the formation of transcriptional condensates.

genomics↗

bioRxiv2022

Integrative single-cell meta-analysis reveals disease-relevant vascular cell states and markers in human atherosclerosis

Coronary artery disease (CAD) and atherosclerosis are characterized by plaque formation in the arteries wall. CAD progression involves complex interactions and phenotypic plasticity within and between distinct vascular and immune cell lineages. Single-cell RNA-seq (scRNA-seq) studies have highlighted lineage-specific transcriptomic signatures, but the reported cell phenotypes in humans remain controversial. Here, we meta-analyzed four scRNA-seq datasets, creating the first map of human cell diversity in atherosclerosis. We generated an atlas of 118,578 high-quality cells, characterized cell-type diversity and provided insights into smooth muscle cell (SMC) phenotypic modulation, transcription factor activity and cell-cell communication. We integrated genome-wide association study (GWAS) data and uncovered a critical role for modulated SMC phenotypes in CAD and coronary calcification. Finally, we identified candidate markers of fibromyocyte and fibrochondrogenic human SMCs (LTBP1 and CRTAC1) that may serve as proxies of atherosclerosis progression. Altogether, we created a unified cellular map of atherosclerosis informing cell state-specific mechanistic and translational studies of cardiovascular diseases.

genomics↗

bioRxiv2022

Adaptive duplication and functional diversification of Protein kinase R contribute to the uniqueness of bat-virus interactions

Several bat species act as asymptomatic reservoirs for many viruses that are instead highly pathogenic in other mammals. Here, we have characterized the functional diversification of the Protein kinase R (PKR), a major antiviral innate defense system. Our data indicate that PKR has evolved under positive selection and has undergone repeated genomic duplications in bats, in contrast to all studied mammals that possess a single copy of the gene. Functional testing of the relationship between PKR and poxvirus antagonists revealed how an evolutionary conflict with ancient pathogenic poxviruses has shaped a specific bat host-virus interface. More importantly, we determined that duplicated PKRs of the Myotis species have undergone functional diversification allowing them to collectively escape from and enhance control of DNA and RNA viruses. These findings suggest that viral-driven adaptations in PKR contribute to modern virus-bat interactions and may account for bat specific immunity.

evolutionary biology↗

bioRxiv2022

Fob1-dependent condensin recruitment and loop extrusion on yeast chromosome III

Despite recent advances in single-molecule and structural analysis of condensin activity in vitro, mechanisms of functional condensin loading and loop extrusion that lead to specific chromosomal organization remain unclear. In Saccharomyces cerevisiae, the most prominent condensin loading site is the rDNA locus on chromosome XII, but its repetitiveness deters rigorous analysis of individual genes. An equally prominent non-rDNA condensin site is located on chromosome III (chrIII). It lies in the promoter of a putative non-coding RNA gene called RDT1, which is in a segment of the recombination enhancer (RE) that dictates MATa-specific chrIII organization. Here, we unexpectedly find that condensin is recruited to RDT1 through interactions with Fob1, Tof2, and cohibin (Lrs4/Csm1), a set of nucleolar factors that also recruit condensin to the rDNA. Using Micro-C XL, we uncover evidence for condensin-driven loop extrusion anchored by Fob1 and cohibin at RDT1 that extends toward MATa on the right arm of chrIII, supporting donor preference during mating-type switching. S. cerevisiae chrIII therefore provides a new platform for the study of programmed condensin-mediated chromosome conformation.

molecular biology↗

bioRxiv2022

Extracting physical characteristics of higher-order chromatin structures from 3D image data

AO_SCPLOWBSTRACTC_SCPLOWHigher-order chromatin structures have functional impacts on gene regulation and cell identity determination. Using high-throughput sequencing (HTS)-based methods like Hi-C, active or inactive compartments and open or closed topologically associating domain (TAD) structures can be identified on a cell population level. Recently developed high-resolution three-dimensional (3D) molecular imaging techniques such as 3D electron microscopy with in situ hybridization (3D-EMSIH) and 3D structured illumination microscopy (3D-SIM) enable direct detection of physical representations of chromatin structures in a single cell. However, computational analysis of 3D image data with explainability and interpretability on functional characteristics of chromatin structures is still challenging. We developed Extracting Physical-Characteristics from Images of Chromatin Structures (EPICS), a machine-learning based computational method for processing high-resolution chromatin 3D image data. Using EPICS on images produced by 3D-EMISH or 3D-SIM techniques, we generated more direct 3D representations of higher-order chromatin structures, identified major chromatin domains, and determined the open or closed status of each domain. We identified several high-contributing features from the model as the major physical characteristics that define the open or closed chromatin domains, demonstrating the explainability and interpretability of EPICS. EPICS can be applied to the analysis of other high-resolution 3D molecular imaging data for spatial genomics studies. The R and Python codes of EPICS are available at https://github.com/zang-lab/epics.

bioinformatics↗

bioRxiv2021

Accurate estimation of intrinsic biases for improved analysis of chromatin accessibility sequencing data using SELMA

Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. However, enzymatic DNA cleavage exhibits intrinsic sequence biases that confound chromatin accessibility profiling data analysis. Existing computational tools are limited in their ability to account for such intrinsic biases and not designed for analyzing single-cell data. Here, we present Simplex Encoded Linear Model for Accessible Chromatin (SELMA), a computational method for systematic estimation of intrinsic cleavage biases from genomic chromatin accessibility profiling data. We demonstrate that SELMA yields accurate and robust bias estimation from both bulk and single-cell DNase-seq and ATAC-seq data. SELMA can utilize internal mitochondrial DNA data to improve bias estimation. We show that transcription factor binding inference from DNase footprints can be improved by incorporating estimated biases using SELMA. Furthermore, we show strong effects of intrinsic biases in single-cell ATAC-seq data, and develop the first single-cell ATAC-seq intrinsic bias correction model to improve cell clustering. SELMA can enhance the performance of existing bioinformatics tools and improve the analysis of both bulk and single-cell chromatin accessibility sequencing data.

bioinformatics↗

bioRxiv2021

Nonparametric Interrogation of Transcriptional Regulation in Single-Cell RNA and Chromatin Accessibility Multiomic Data

Epigenetic control of gene expression is highly cell-type- and context-specific. Yet, despite its complexity, gene regulatory logic can be broken down into modular components consisting of a transcription factor (TF) activating or repressing the expression of a target gene through its binding to a cis-regulatory region. Recent advances in joint profiling of transcription and chromatin accessibility with single-cell resolution offer unprecedented opportunities to interrogate such regulatory logic. Here, we propose a nonparametric approach, TRIPOD, to detect and characterize three-way relationships between a TF, its target gene, and the accessibility of the TFs binding site, using single-cell RNA and ATAC multiomic data. We apply TRIPOD to interrogate cell-type-specific regulatory logic in peripheral blood mononuclear cells and contrast our results to detections from enhancer databases, cis-eQTL studies, ChIP-seq experiments, and TF knockdown/knockout studies. We then apply TRIPOD to mouse embryonic brain data during neurogenesis and gliogenesis and identified known and novel putative regulatory relationships, validated by ChIP-seq and PLAC-seq. Finally, we demonstrate TRIPOD on SHARE-seq data of differentiating mouse hair follicle cells and identify lineage-specific regulation supported by histone marks for gene activation and super-enhancer annotations.

bioinformatics↗

bioRxiv2021

Cell-specific chromatin landscape of human coronary artery resolves regulatory mechanisms of disease risk

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. We identified a number of candidate mechanisms for smooth muscle cell transition states and identified putative binding sites for risk variants. We further employed CRE to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. This single cell atlas provides a critical step towards interpreting cis-regulatory mechanisms in the vessel wall across the continuum of CAD risk.

genomics↗

bioRxiv2020

BART Cancer: a web resource for transcriptional regulators in cancer genomes

Dysregulation of gene expression plays an important role in cancer development. Identifying transcriptional regulators, including transcription factors and chromatin regulators, that drive the oncogenic gene expression program is a critical task in cancer research. Genomic profiles of active transcriptional regulators from primary cancer samples are limited in the public domain. Here we present BART Cancer (bartcancer.org), an interactive web resource database to display the putative transcriptional regulators that are responsible for differentially regulated genes in 15 different cancer types in The Cancer Genome Atlas (TCGA). BART Cancer integrates over 10,000 gene expression profiling RNA-seq datasets from TCGA with over 7,000 ChIP-seq datasets from the Cistrome Data Browser database and the Gene Expression Omnibus (GEO). BART Cancer uses Binding Analysis for Regulation of Transcription (BART) for predicting the transcriptional regulators from the differentially expressed genes in cancer samples compared to normal samples. BART Cancer also displays the activities of over 900 transcriptional regulators across cancer types, by integrating computational prediction results from BART and the Cistrome Cancer database. Focusing on transcriptional regulator activities in human cancers, BART Cancer can provide unique insights into epigenetics and transcriptional regulation in cancer, and is a useful data resource for genomics and cancer research communities.

cancer biology↗

bioRxiv2020

BART3D: Inferring transcriptional regulators associated with differential chromatin interactions from Hi-C data

SummaryIdentification of functional transcriptional regulators associated with chromatin interactions is an important problem in studies of 3-dimensional genome organization and gene regulation. Direct inference of TR binding has been limited by the resolution of Hi-C data. Here, we present BART3D, a computational method for inferring TRs associated with genome-wide differential chromatin interactions by comparing Hi-C maps from two states, leveraging public ChIP-seq data for human and mouse. We demonstrate that BART3D can detect relevant TRs from dynamic Hi-C profiles with TR perturbation or cell differentiation. BART3D can be a useful tool in 3D genome data analysis and functional genomics research. Availability and ImplementationImplemented in Python, source code freely available at https://github.com/zanglab/bart3d Contactzang@virginia.edu Supplementary InformationSupplementary data are available.

bioinformatics↗

bioRxiv2020

BARTweb: a web server for transcription factor association analysis

Identifying active transcription factors (TFs) that bind to cis-regulatory regions in the genome to regulate differential gene expression is a key task in gene regulation research. TF binding profiles from numerous existing ChIP-seq data can be utilized for association analysis with query data for TF identification, as alternative to DNA sequence motif analysis. Here, we present BARTweb, an interactive webserver for identifying TFs whose genomic binding patterns associate with input genomic features, by leveraging over 13,000 public ChIP-seq datasets for human and mouse. Using an updated Binding Analysis for Regulation of Transcription (BART) algorithm, BARTweb can identify functional TFs that regulate a gene set, or have a binding profile correlated with a ChIP-seq profile or enriched in a genomic region set, without a priori information of the cell type. Compared with the original BART package, BARTweb substantially reduces the execution time of a typical job by two orders of magnitude. We also show that BARTweb outperforms other existing tools in identifying true TFs from collected experimental data. BARTweb is a useful webserver for performing functional analysis of gene regulation. BARTweb is freely available at http://bartweb.org.

bioinformatics↗

bioRxiv2020

Cancer-specific CTCF binding facilitates oncogenic transcriptional dysregulation

BackgroundThe three-dimensional genome organization is critical for gene regulation and can malfunction in diseases like cancer. As a key regulator of genome organization, CCCTC-binding factor (CTCF) has been characterized as a DNA-binding protein with important functions in maintaining the topological structure of chromatin and inducing DNA looping. Among the prolific binding sites in the genome, several events with altered CTCF occupancy have been reported as associated with effects in physiology or disease. However, there is no hitherto a comprehensive survey of genome-wide CTCF binding patterns across different human cancers. ResultsTo dissect functions of CTCF binding, we systematically analyze over 700 CTCF ChIP-seq profiles across human tissues and cancers and identify cancer-specific CTCF binding patterns in six cancer types. We show that cancer-specific lost and gained CTCF binding events are associated with altered chromatin interactions in patient samples, but not always with DNA methylation changes or sequence mutations. While lost bindings primarily occur near gene promoters, most gained CTCF binding events are induced by oncogenic transcription factors and exhibit enhancer activities. We validate these findings in T-cell acute lymphoblastic leukemia and show that oncogenic NOTCH1 induces specific CTCF binding and they cooperatively activate expression of target genes, indicating transcriptional condensation phenomena. ConclusionsCancer-specific CTCF binding events are not always associated with DNA methylation changes or mutations, but can be induced by other transcription factors to regulate oncogenic gene expression. Our results substantiate CTCF binding alteration as a functional epigenomic signature of cancer.

genomics↗

bioRxiv2019

Nickel induced transcriptional changes persist post exposure through epigenetic reprograming

Nickel is an occupational and environmental toxicant associated with a number of diseases in humans including pulmonary fibrosis, bronchitis and lung and nasal cancers. Our earlier studies showed that the nickel-exposure-induced genome-wide transcriptional changes, which persist even after the termination of exposure may underlie nickel pathogenesis. However, the mechanisms that drive nickel-induced persistent changes to the transcriptome remain elusive. To elucidate the mechanisms that underlie nickel induced long-term transcriptional changes, in this study, we examined the transcriptome and the epigenome of human lung epithelial cells during nickel exposure and after the termination of exposure. We identified two categories of persistently differentially expressed genes based on the timing of expression changes: i) the genes that were differentially expressed during nickel exposure; and ii) the genes that were differentially expressed only after the termination of nickel exposure. Interestingly, the majority of nickel-induced transcriptional changes occurred only after the termination of exposure. We found robust genome-wide alterations to the activating histone modification, H3K4me3, after the termination of nickel exposure, which coincided with the post-exposure gene expression changes. In addition, we found significant post-exposure alterations to the repressive histone modification, H3K27me3. By uncovering a new category of transcriptional and epigenetic changes, which occur only after the termination of exposure, this study sheds new light on the post-exposure effects of nickel and provides a novel understanding of the long-term deleterious consequences of nickel exposure on human health.

systems biology↗

bioRxiv2019

Polyadenylation of Histone H3.1 mRNA Promotes Cell Transformation by Displacing H3.3 from Gene Regulatory Elements

Replication-dependent canonical histone messenger RNAs (mRNAs) do not terminate with a poly(A) tail at the 3 end. We previously demonstrated that exposure to arsenic, an environmental carcinogen, induces polyadenylation of canonical histone H3.1 mRNA. The addition of a poly(A) tail to the H3.1 mRNA caused transformation of human cells in vitro, but the underlying mechanisms are unknown. Here we report that polyadenylation of H3.1 mRNA increases H3.1 protein level, resulting in depletion of histone variant H3.3 at active promoters, enhancers, and insulator regions through its displacement. Cells underwent transcriptional deregulation, G2/M cell cycle arrest, chromosome aneuploidy and aberrations. Furthermore, knocking down the expression of H3.3 induced cell transformation, whereas ectopic expression of H3.3 attenuated arsenic-induced cell transformation, suggesting that H3.3 displacement might be central to tumorigenic effects of polyadenylated H3.1 mRNA. Our study provides novel insights into the importance of proper histone stoichiometry in maintaining genome integrity.\n\nHighlightsO_LIPolyadenylation of canonical histone H3.1 mRNA promotes tumor formation in nude mice\nC_LIO_LIHistone variant H3.3 is displaced from critical gene regulatory elements by overexpression of polyadenylated H3.1 mRNA\nC_LIO_LIIncreased polyadenylated H3.1 mRNA causes abnormal transcription, cell cycle arrest, and chromosomal instability\nC_LIO_LIArsenic induces polyadenylation of H3.1 mRNA in vivo\nC_LI

molecular biology↗

bioRxiv2019

Pitfalls in estimating the global carbon removal via forest expansion - a comment on Bastin et al. (2019)

We believe the carbon removal potential of 205 Gt C reported by Bastin et al. (2019) to be overestimated. The authors did not consider the carbon already stored on the land with identified tree restoration potential. For instance, grasslands and degraded forests have similar soil carbon stocks as old-growth forests. Accounting for these inconsistencies in the calculation, we estimate a carbon removal potential of 81 Gt C, i.e. only 39% of the Bastin et al. estimate. In addition, some of the assumptions about potential restoration area seem questionable and an essential question remains unanswered: why do areas identified as suitable for tree growth currently lack tree cover?

ecology↗

bioRxiv2019

An integrative ENCODE resource for cancer genomics

ENCODE comprises thousands of functional genomics datasets, and the encyclopedia covers hundreds of cell types, providing a universal annotation for genome interpretation. However, for particular applications, it may be advantageous to use a customized annotation. Here, we develop such a custom annotation by leveraging advanced assays, such as eCLIP, Hi-C, and whole-genome STARR-seq on a number of data-rich ENCODE cell types. A key aspect of this annotation is comprehensive and experimentally derived networks of both transcription factors and RNA-binding proteins (TFs and RBPs). Cancer, a disease of system-wide dysregulation, is an ideal application for such a network-based annotation. Specifically, for cancer-associated cell types, we put regulators into hierarchies and measure their network change (rewiring) during oncogenesis. We also extensively survey TF-RBP crosstalk, highlighting how SUB1, a previously uncharacterized RBP, drives aberrant tumor expression and amplifies the effect of MYC, a well-known oncogenic TF. Furthermore, we show how our annotation allows us to place oncogenic transformations in the context of a broad cell space; here, many normal-to-tumor transitions move towards a stem-like state, while oncogene knockdowns show an opposing trend. Finally, we organize the resource into a coherent workflow to prioritize key elements and variants, in addition to regulators. We showcase the application of this prioritization to somatic burdening, cancer differential expression and GWAS. Targeted validations of the prioritized regulators, elements and variants using siRNA knockdowns, CRISPR-based editing, and luciferase assays demonstrate the value of the ENCODE resource.

genomics↗