scholarly journals CREAM: Clustering of genomic REgions Analysis Method

2017 ◽  
Author(s):  
Seyed Ali Madani Tonekaboni ◽  
Parisa Mazrooei ◽  
Victor Kofia ◽  
Benjamin Haibe-Kains ◽  
Mathieu Lupien
Keyword(s):  
Expression Profiles ◽  
Gene Expression Profiles ◽  
R Package ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Analysis Method ◽  
Chromatin Interactions ◽  
Super Enhancer ◽  
Highly Expressed Genes ◽  
Genomic Regions

ABSTRACTCellular identity relies on cell type-specific gene expression profiles controlled by cis-regulatory elements (CREs), such as promoters, enhancers and anchors of chromatin interactions. CREs are unevenly distributed across the genome, giving rise to distinct subsets such as individual CREs and Clusters Of cis-Regulatory Elements (COREs), also known as super-enhancers. Identifying COREs is a challenge due to technical and biological features that entail variability in the distribution of distances between CREs within a given dataset. To address this issue, we developed a new unsupervised machine learning approach termed Clustering of genomic REgions Analysis Method (CREAM) that outperforms the Ranking Of Super Enhancer (ROSE) approach. Specifically CREAM identified COREs are enriched in CREs strongly bound by master transcription factors according to ChIP-seq signal intensity, are proximal to highly expressed genes, are preferentially found near genes essential for cell growth and are more predictive of cell identity. Moreover, we show that CREAM enables subtyping primary prostate tumor samples according to their CORE distribution across the genome. We further show that COREs are enriched compared to individual CREs at TAD boundaries and these are preferentially bound by CTCF and factors of the cohesin complex (e.g.: RAD21 and SMC3). Finally, using CREAM against transcription factor ChIP-seq reveals CTCF and cohesin-specific COREs preferentially at TAD boundaries compared to intra-TADs. CREAM is available as an open source R package (https://CRAN.R-project.org/package=CREAM) to identify COREs from cis-regulatory annotation datasets from any biological samples.

scholarly journals Identifying Transcription Regulatory Elements in the Human and Mouse Genomes Using Tissue-specific Gene Expression Profiles

2007 ◽  
Vol 4 (2) ◽  
pp. 1-23
Author(s):  
Amitava Karmaker ◽  
Kihoon Yoon ◽  
Mark Doderer ◽  
Russell Kruzelock ◽  
Stephen Kwek
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Binding Sites ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Tissue Specific Gene ◽  
Human And Mouse

Summary Revealing the complex interaction between trans- and cis-regulatory elements and identifying these potential binding sites are fundamental problems in understanding gene expression. The progresses in ChIP-chip technology facilitate identifying DNA sequences that are recognized by a specific transcription factor. However, protein-DNA binding is a necessary, but not sufficient, condition for transcription regulation. We need to demonstrate that their gene expression levels are correlated to further confirm regulatory relationship. Here, instead of using a linear correlation coefficient, we used a non-linear function that seems to better capture possible regulatory relationships. By analyzing tissue-specific gene expression profiles of human and mouse, we delineate a list of pairs of transcription factor and gene with highly correlated expression levels, which may have regulatory relationships. Using two closely-related species (human and mouse), we perform comparative genome analysis to cross-validate the quality of our prediction. Our findings are confirmed by matching publicly available TFBS databases (like TRANFAC and ConSite) and by reviewing biological literature. For example, according to our analysis, 80% and 85.71% of the targets genes associated with E2F5 and RELB transcription factors have the corresponding known binding sites. We also substantiated our results on some oncogenes with the biomedical literature. Moreover, we performed further analysis on them and found that BCR and DEK may be regulated by some common transcription factors. Similar results for BTG1, FCGR2B and LCK genes were also reported.

scholarly journals Mechanisms of YAP/TAZ transcriptional control

Cell Stress ◽  
2021 ◽  
Vol 5 (11) ◽  
pp. 167-172
Author(s):  
Giusy Battilana ◽  
Francesca Zanconato ◽  
Stefano Piccolo
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Transcriptional Control ◽  
Cell Transformation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Chromatin Regulators ◽  
Small Set

Dysregulated gene expression is intrinsic to cell transformation, tumorigenesis and metastasis. Cancer-specific gene-expression profiles stem from gene regulatory networks fueled by genetic and epigenetic defects, and by abnormal signals of the tumor microenvironment. These oncogenic signals ultimately engage the transcriptional machinery on the cis -regulatory elements of a host of effector genes, through recruitment of transcription factors (TFs), co-activators and chromatin regulators. That said, whether gene -expression in cancer cells is the chaotic product of myriad regulations or rather a relatively ordered process orchestrated by few TFs (master regulators) has long remained enigmatic. Recent work on the YAP/TAZ co-activators has been instrumental to break new ground into this outstanding issue, revealing that tumor cells hijack growth programs that are active during development and regeneration through engagement of a small set of interconnected TFs and their nuclear partners.

scholarly journals Non-Coding RNAs as Biomarkers of Tumor Progression and Metastatic Spread in Epithelial Ovarian Cancer

Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1839
Author(s):  
Karolina Seborova ◽  
Radka Vaclavikova ◽  
Lukas Rob ◽  
Pavel Soucek ◽  
Pavel Vodicka
Keyword(s):  
Ovarian Cancer ◽  
Tumor Progression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Distant Metastases ◽  
Regulatory Elements ◽  
Metastatic Spread ◽  
Response To Treatment ◽  
Primary Tumors ◽  
Non Coding Rnas

Ovarian cancer is one of the most common causes of death among gynecological malignancies. Molecular changes occurring in the primary tumor lead to metastatic spread into the peritoneum and the formation of distant metastases. Identification of these changes helps to reveal the nature of metastases development and decipher early biomarkers of prognosis and disease progression. Comparing differences in gene expression profiles between primary tumors and metastases, together with disclosing their epigenetic regulation, provides interesting associations with progression and metastasizing. Regulatory elements from the non-coding RNA families such as microRNAs and long non-coding RNAs seem to participate in these processes and represent potential molecular biomarkers of patient prognosis. Progress in therapy individualization and its proper targeting also rely upon a better understanding of interactions among the above-listed factors. This review aims to summarize currently available findings of microRNAs and long non-coding RNAs linked with tumor progression and metastatic process in ovarian cancer. These biomolecules provide promising tools for monitoring the patient’s response to treatment, and further they serve as potential therapeutic targets of this deadly disease.

scholarly journals Glucocorticoid receptor wields chromatin interactions to tune transcription for cytoskeleton stabilization in podocytes

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Hong Wang ◽  
Aiping Duan ◽  
Jing Zhang ◽  
Qi Wang ◽  
Yuexian Xing ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Glucocorticoid Receptor ◽  
Protective Effect ◽  
Histone Modification ◽  
Regulatory Networks ◽  
Target Gene ◽  
Regulatory Elements ◽  
Chromatin Interactions ◽  
Super Enhancer

AbstractElucidating transcription mediated by the glucocorticoid receptor (GR) is crucial for understanding the role of glucocorticoids (GCs) in the treatment of diseases. Podocyte is a useful model for studying GR regulation because GCs are the primary medication for podocytopathy. In this study, we integrated data from transcriptome, transcription factor binding, histone modification, and genome topology. Our data reveals that the GR binds and activates selective regulatory elements in podocyte. The 3D interactome captured by HiChIP facilitates the identification of remote targets of GR. We found that GR in podocyte is enriched at transcriptional interaction hubs and super-enhancers. We further demonstrate that the target gene of the top GR-associated super-enhancer is indispensable to the effective functioning of GC in podocyte. Our findings provided insights into the mechanisms underlying the protective effect of GCs on podocyte, and demonstrate the importance of considering transcriptional interactions in order to fine-map regulatory networks of GR.

scholarly journals Large organized chromatin lysine domains help distinguish primitive from differentiated cell populations

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Seyed Ali Madani Tonekaboni ◽  
Benjamin Haibe-Kains ◽  
Mathieu Lupien
Keyword(s):  
Transposable Elements ◽  
Histone Modifications ◽  
Cell Types ◽  
Regulatory Elements ◽  
Cell Populations ◽  
Genomic Features ◽  
Differentiated Cells ◽  
Chromatin Interactions ◽  
Topologically Associating Domains ◽  
Highly Expressed Genes

AbstractThe human genome is partitioned into a collection of genomic features, inclusive of genes, transposable elements, lamina interacting regions, early replicating control elements and cis-regulatory elements, such as promoters, enhancers, and anchors of chromatin interactions. Uneven distribution of these features within chromosomes gives rise to clusters, such as topologically associating domains (TADs), lamina-associated domains, clusters of cis-regulatory elements or large organized chromatin lysine (K) domains (LOCKs). Here we show that LOCKs from diverse histone modifications discriminate primitive from differentiated cell types. Active LOCKs (H3K4me1, H3K4me3 and H3K27ac) cover a higher fraction of the genome in primitive compared to differentiated cell types while repressive LOCKs (H3K9me3, H3K27me3 and H3K36me3) do not. Active LOCKs in differentiated cells lie proximal to highly expressed genes while active LOCKs in primitive cells tend to be bivalent. Genes proximal to bivalent LOCKs are minimally expressed in primitive cells. Furthermore, bivalent LOCKs populate TAD boundaries and are preferentially bound by regulators of chromatin interactions, including CTCF, RAD21 and ZNF143. Together, our results argue that LOCKs discriminate primitive from differentiated cell populations.

scholarly journals Using 3D epigenomic maps of primary olfactory neuronal cells from living individuals to understand gene regulation

2018 ◽  
Vol 4 (12) ◽  
pp. eaav8550 ◽  
Author(s):  
Suhn K. Rhie ◽  
Shannon Schreiner ◽  
Heather Witt ◽  
Chris Armoskus ◽  
Fides D. Lay ◽  
...  
Keyword(s):  
Cell Model ◽  
Expression Profiles ◽  
Neuronal Cells ◽  
Three Dimensional ◽  
Gene Expression Profiles ◽  
Regulatory Elements ◽  
A Genome ◽  
Wide Scale ◽  
Cell Model System ◽  
Distal Regulatory Elements

As part of PsychENCODE, we developed a three-dimensional (3D) epigenomic map of primary cultured neuronal cells derived from olfactory neuroepithelium (CNON). We mapped topologically associating domains and high-resolution chromatin interactions using Hi-C and identified regulatory elements using chromatin immunoprecipitation and nucleosome positioning assays. Using epigenomic datasets from biopsies of 63 living individuals, we found that epigenetic marks at distal regulatory elements are more variable than marks at proximal regulatory elements. By integrating genotype and metadata, we identified enhancers that have different levels corresponding to differences in genetic variation, gender, smoking, and schizophrenia. Motif searches revealed that many CNON enhancers are bound by neuronal-related transcription factors. Last, we combined 3D epigenomic maps and gene expression profiles to predict enhancer-target gene interactions on a genome-wide scale. This study not only provides a framework for understanding individual epigenetic variation using a primary cell model system but also contributes valuable data resources for epigenomic studies of neuronal epithelium.

scholarly journals Convergent evolution of venom gland transcriptomes across Metazoa

2021 ◽  
Author(s):  
Giulia Zancolli ◽  
Maarten Reijnders ◽  
Robert Waterhouse ◽  
Marc Robinson-Rechavi
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Venom Gland ◽  
Bioactive Molecules ◽  
Specific Gene ◽  
Animal Kingdom ◽  
Venom Glands

Animals have repeatedly evolved specialized organs and anatomical structures to produce and deliver a cocktail of potent bioactive molecules to subdue prey or predators: venom. This makes it one of the most widespread convergent functions in the animal kingdom. Whether animals have adopted the same genetic toolkit to evolved venom systems is a fascinating question that still eludes us. Here, we performed the first comparative analysis of venom gland transcriptomes from 20 venomous species spanning the main Metazoan lineages, to test whether different animals have independently adopted similar molecular mechanisms to perform the same function. We found a strong convergence in gene expression profiles, with venom glands being more similar to each other than to any other tissue from the same species, and their differences closely mirroring the species phylogeny. Although venom glands secrete some of the fastest evolving molecules (toxins), their gene expression does not evolve faster than evolutionarily older tissues. We found 15 venom gland specific gene modules enriched in endoplasmic reticulum stress and unfolded protein response pathways, indicating that animals have independently adopted stress response mechanisms to cope with mass production of toxins. This, in turns, activates regulatory networks for epithelial development, cell turnover and maintenance which seem composed of both convergent and lineage-specific factors, possibly reflecting the different developmental origins of venom glands. This study represents the first step towards an understanding of the molecular mechanisms underlying the repeated evolution of one of the most successful adaptive traits in the animal kingdom.

Dimethyl fumarate induces ferroptosis and impairs NF-κB/STAT3 signaling in DLBCL

Blood ◽  
2021 ◽  
Author(s):  
Anja Schmitt ◽  
Wendan Xu ◽  
Philip Bucher ◽  
Melanie Grimm ◽  
Martina Konantz ◽  
...  
Keyword(s):  
Cell Death ◽  
B Cell ◽  
Expression Profiles ◽  
Therapeutic Option ◽  
Gene Expression Profiles ◽  
B Cell Lymphoma ◽  
Dimethyl Fumarate ◽  
Specific Gene ◽  
Molecular Heterogeneity ◽  
Stat3 Signaling

Despite the development of novel targeted drugs, the molecular heterogeneity of diffuse large B-cell lymphoma (DLBCL) still poses a major therapeutic challenge. DLBCL can be classified into at least two major subtypes, i.e. germinal center B-cell-like (GCB) and the aggressive activated B-cell-like (ABC) DLBCL, each characterized by specific gene expression profiles and mutation patterns. Here we demonstrate a broad anti-tumor effect of dimethyl fumarate (DMF) on both DLBCL subtypes, which is mediated by the induction of ferroptosis, a form of cell death driven by the peroxidation of phospholipids. Due to high expression of arachidonate 5-lipoxygenase in concert with low glutathione and glutathione peroxidase 4 levels, DMF induces lipid peroxidation and thus ferroptosis particularly in GCB DLBCL. In ABC DLBCL cells, which are addicted to NF-κB and STAT3 survival signaling, DMF treatment efficiently inhibits the activity of the IKK complex and JAK kinases. Interestingly, the BCL-2 specific BH3 mimetic ABT-199 and an inhibitor of ferroptosis suppressor protein 1 synergize with DMF in inducing cell death in DLBCL. Collectively, our findings identify the clinically approved drug DMF as a promising novel therapeutic option in the treatment of both GCB and ABC DLBCL.

scholarly journals Biophysical Techniques for Target Validation and Drug Discovery in Transcription-Targeted Therapy

2020 ◽  
Vol 21 (7) ◽  
pp. 2301 ◽  
Author(s):  
Mehdi Moustaqil ◽  
Yann Gambin ◽  
Emma Sierecki
Keyword(s):  
Drug Discovery ◽  
Therapeutic Strategy ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Attractive Alternative ◽  
Specific Gene ◽  
Pharmaceutical Companies ◽  
Biochemical Activity ◽  
Biophysical Techniques ◽  
And Personalized Medicine

In the post-genome era, pathologies become associated with specific gene expression profiles and defined molecular lesions can be identified. The traditional therapeutic strategy is to block the identified aberrant biochemical activity. However, an attractive alternative could aim at antagonizing key transcriptional events underlying the pathogenesis, thereby blocking the consequences of a disorder, irrespective of the original biochemical nature. This approach, called transcription therapy, is now rendered possible by major advances in biophysical technologies. In the last two decades, techniques have evolved to become key components of drug discovery platforms, within pharmaceutical companies as well as academic laboratories. This review outlines the current biophysical strategies for transcription manipulation and provides examples of successful applications. It also provides insights into the future development of biophysical methods in drug discovery and personalized medicine.

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