Genome-wide Chromatin Localization Research Articles

Abstract B012: Defining the role of the BAF complex in primary liver cancers

Abstract Incidence and mortality from primary liver cancer are increasing and few effective therapies exist for this deadly disease. Mutations in genes important for chromatin mediated gene regulation commonly occur in both hepatocellular carcinoma and cholangiocarcinoma, the two most common primary liver cancers. Chromatin regulators have been shown to be key modulators of both sensitivity and resistance to therapy response, and therapeutic targeting of chromatin regulators is under development for a wide range of cancers. To uncover chromatin genes that modulate therapy response, we performed epigenome-focused CRISPR screening in the presence of multiple kinases inhibitors (sorafenib, donafenib, cabozantinib). We found that disruption of a specific form of the SWI/SNF chromatin remodeling complex, called BAF, led to therapy resistance. The BAF complex is frequently mutated in both hepatocellular carcinoma and cholangiocarcinoma. Recent studies show that loss of ARID1A and ARID1B, members of the BAF complex, gives rise to liver tumors with morphologies of both hepatocellular carcinoma and cholangiocarcinoma. Critically, because multikinase inhibitors are the most common treatments for advanced hepatocellular carcinoma, our findings suggest patients with BAF mutations would not respond well to these drugs. Using gene expression analysis, genome-wide chromatin localization, and chromatin accessibility assays we are uncovering how altered chromatin state underlies multikinase inhibitor response in BAF mutant tumors. Using high-throughput epigenome focused CRISPR screens we will identify novel modulators of therapy response in liver cancer. Citation Format: Margarita M. Dzama, Deena M. Scoville, Emma D. Bucklan, Jesse R. Raab. Defining the role of the BAF complex in primary liver cancers. [abstract]. In: Proceedings of the AACR Special Conference: Cancer Epigenomics; 2022 Oct 6-8; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_2):Abstract nr B012.

A Hyper-IgM Syndrome Mutation in Activation-Induced Cytidine Deaminase Disrupts G-Quadruplex Binding and Genome-wide Chromatin Localization

Precise targeting of activation-induced cytidine deaminase (AID) to immunoglobulin (Ig) loci promotes antibody class switch recombination (CSR) and somatic hypermutation (SHM), whereas AID targeting of non-Ig loci can generate oncogenic DNA lesions. Here, we examined the contribution of G-quadruplex (G4) nucleic acid structures to AID targeting invivo. Mice bearing a mutation in Aicda (AIDG133V) that disrupts AID-G4 binding modeled the pathology of hyper-IgM syndrome patients with an orthologous mutation, lacked CSR and SHM, and had broad defects in genome-wide AIDG133V chromatin localization. Genome-wide analyses also revealed that wild-type AID localized to MHCII genes, and AID expression correlated with decreased MHCII expression in germinal center B cells and diffuse large B cell lymphoma. Our findings indicate a crucial role for G4 binding in AID targeting and suggest that AID activity may extend beyond Ig loci to regulate the expression of genes relevant to the physiology and pathology of activated B cells.

Replication stress induces accumulation of FANCD2 at central region of large fragile genes.

During mild replication stress provoked by low dose aphidicolin (APH) treatment, the key Fanconi anemia protein FANCD2 accumulates on common fragile sites, observed as sister foci, and protects genome stability. To gain further insights into FANCD2 function and its regulatory mechanisms, we examined the genome-wide chromatin localization of FANCD2 in this setting by ChIP-seq analysis. We found that FANCD2 mostly accumulates in the central regions of a set of large transcribed genes that were extensively overlapped with known CFS. Consistent with previous studies, we found that this FANCD2 retention is R-loop-dependent. However, FANCD2 monoubiquitination and RPA foci formation were still induced in cells depleted of R-loops. Interestingly, we detected increased Proximal Ligation Assay dots between FANCD2 and R-loops following APH treatment, which was suppressed by transcriptional inhibition. Collectively, our data suggested that R-loops are required to retain FANCD2 in chromatin at the middle intronic region of large genes, while the replication stress-induced upstream events leading to the FA pathway activation are not triggered by R-loops.

Translational Bioinformatics and Computational Systems Medicine

This special issue is dedicated to Translational bioinformatics and Computational Systems Medicine. Translational biomedical informatics is a rapidly emerging discipline to integrate data from medical research, biotechnologies, and electronic medical records, and computational systems medicine is to apply computational and systems biology approaches to solve complex problems in medical research, aiming to improve the diagnosis, prognosis, and treatment of complex diseases. It is also well known that their development needs an integration of mathematical models, statistical methods, and computer algorithms. Complex diseases such as cancers are coursed by a combination of genetic, environmental, and lifestyle factors, and thus the research of complex diseases at a system level like gene sets, pathway level, or static/dynamic network is a necessity. T. Holden et al. present an exploratory bioinformatics study of long noncoding RNA in Alzheimer's disease. The authors also discuss the model for drug development based on fractal dimension and entropy correlation in this study consistent with a zebrafish model and a mouse model. M. Ding et al. explore the genome-wide chromatin localization of Estrogen receptor-DNA binding regions by analyzing ChIP-Seq data from MCF-7 breast cancer cell line. It reveals novel Estrogen receptor-regulated genes pathways for further experimental validation. Y.-w. Lv et al. perform gene ontology category and pathways analysis for relationships among statistically significant genes in Kawasaki disease. The importance of compelling immune pathway of NF-AT signal and leukocyte interactions combined with another transcription factor NF-κB in the pathogenesis of KD is investigated by network analysis. J. Chen et al. perform two case studies on colorectal and prostate cancer microarray datasets to proof two hypotheses that (1) the expression signatures of different cancer microarray datasets are more similar at pathway level than at gene level; (2) the comparability of the cancer molecular mechanisms of different individuals is related to their genetic similarities. The concept of entropy suggests that systems naturally progress from order to disorder. Entropy-based methods provide a novel insight into understanding many phenomena in biological systems. V. Oswal et al. present an automated entropy-based thresholding system for segmentation and quantification of cell nuclei from histologically stained images. The contributions to the application of this entropy-based system to detect cancerous cell nuclei and observe overlapping cellular events occurring during wound healing process in the human body are also presented. H.-T. Wu et al. investigate the feasibility and sensitivity of a novel multiscale entropy index in detecting subtle vascular abnormalities in healthy and diabetic subjects. The authors further focus on four groups of subjects to discuss the application of multiscale entropy index. The role of protein structures in understanding diseases becomes more and more important, due to the following two reasons. One is that there are a lot of disease-associated proteins that were discovered, while the other fact is that many diseases are believed to result from misfolded proteins. Moreover, protein structures can be considered as complex systems, and thus network theory can be used to characterize and to analyze protein structures. J. Sun et al. present a contribution which focuses on the effect of edge definition of complex networks on protein structure identification. After the performance on 2847 proteins, the authors argue that the optimal cutoff value for constructing the protein structure networks is 5.0 A. X. Jiao et al. improve the amino acid network for proteins by introducing similar weight and dissimilar weight. This work demonstrates that highly central residues of the amino acid network are highly correlated with the hot spots in disease-associated proteins. Finally, two bioinformatics tools were also involved in this issue. H. Wu et al. contribute a bioinformatics tool called patGPCR, to predict the 3D structures of transmembrane helices of G-protein-coupled receptors. patGPCR, a parallelized multitemplate approach, extends a bundle-packing related energy function to RosettaMem energy, which improves the TM RMSD (root mean square deviation of the transmembrane helices) of the predicted models. N. Deng et al. contribute another platform, called crcTRP, for colorectal cancer. This server provides the translational research of colorectal cancer by providing various types of biomedical information, including clinical data, epidemiology data, individual omics data, and public omics data. Bairong Shen Hong-Bin Shen Tianhai Tian Qiang Lu Guang Hu

Identification and Functional Annotation of Genome-Wide ER-Regulated Genes in Breast Cancer Based on ChIP-Seq Data

Estrogen receptor (ER) is a crucial molecule symbol of breast cancer. Molecular interactions between ER complexes and DNA regulate the expression of genes responsible for cancer cell phenotypes. However, the positions and mechanisms of the ER binding with downstream gene targets are far from being fully understood. ChIP-Seq is an important assay for the genome-wide study of protein-DNA interactions. In this paper, we explored the genome-wide chromatin localization of ER-DNA binding regions by analyzing ChIP-Seq data from MCF-7 breast cancer cell line. By integrating three peak detection algorithms and two datasets, we localized 933 ER binding sites, 92% among which were located far away from promoters, suggesting long-range control by ER. Moreover, 489 genes in the vicinity of ER binding sites were identified as estrogen response elements by comparison with expression data. In addition, 836 single nucleotide polymorphisms (SNPs) in or near 157 ER-regulated genes were found in the vicinity of ER binding sites. Furthermore, we annotated the function of the nearest-neighbor genes of these binding sites using Gene Ontology (GO), KEGG, and GeneGo pathway databases. The results revealed novel ER-regulated genes pathways for further experimental validation. ER was found to affect every developed stage of breast cancer by regulating genes related to the development, progression, and metastasis. This study provides a deeper understanding of the regulatory mechanisms of ER and its associated genes.

Genome-Wide Analysis of Estrogen Receptor α DNA Binding and Tethering Mechanisms Identifies Runx1 as a Novel Tethering Factor in Receptor-Mediated Transcriptional Activation

Nuclear receptor estrogen receptor alpha (ER alpha) controls the expression of hundreds of genes responsible for target cell phenotypic properties, but the relative importance of direct versus tethering mechanisms of DNA binding has not been established. In this first report, we examine the genome-wide chromatin localization of an altered-specificity mutant ER with a DNA binding domain deficient in binding to estrogen response element (ERE)-containing DNA (DBDmut ER) versus wild-type ER alpha. Using high-throughput sequencing of ER chromatin immunoprecipitations (ChIP-Seq) and mRNA transcriptional profiling, we show that direct ERE binding is required for most of (75%) estrogen-dependent gene regulation and 90% of hormone-dependent recruitment of ER to genomic binding sites. De novo motif analysis of the chromatin binding regions in MDA-MB-231 human breast cancer cells defined unique transcription factor profiles responsible for genes regulated through tethering versus direct ERE binding, with Runx motifs enriched in ER-tethered sites. We confirmed a role for Runx1 in mediating ER alpha genomic recruitment and regulation of tethering genes. Our findings delineate the contributions of direct receptor ERE binding versus binding through response elements for other transcription factors in chromatin localization and ER-dependent gene regulation, paradigms likely to underlie the gene regulatory actions of other nuclear receptors as well.

Transcriptional responses to fatty acid are coordinated by combinatorial control

In transcriptional regulatory networks, the coincident binding of a combination of factors to regulate a gene implies the existence of complex mechanisms to control both the gene expression profile and specificity of the response. Unraveling this complexity is a major challenge to biologists. Here, a novel network topology-based clustering approach was applied to condition-specific genome-wide chromatin localization and expression data to characterize a dynamic transcriptional regulatory network responsive to the fatty acid oleate. A network of four (predicted) regulators of the response (Oaf1p, Pip2p, Adr1p and Oaf3p) was investigated. By analyzing trends in the network structure, we found that two groups of multi-input motifs form in response to oleate, each controlling distinct functional classes of genes. This functionality is contributed in part by Oaf1p, which is a component of both types of multi-input motifs and has two different regulatory activities depending on its binding context. The dynamic cooperation between Oaf1p and Pip2p appears to temporally synchronize the two different responses. Together, these data suggest a network mechanism involving dynamic combinatorial control for coordinating transcriptional responses.