scholarly journals Assessing the Gene Regulatory Landscape in 1,188 Human Tumors

2017 ◽  
Author(s):  
C Calabrese ◽  
K Lehmann ◽  
L Urban ◽  
F Liu ◽  
S Erkek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Large Scale ◽  
Human Cancer ◽  
Expression Patterns ◽  
Regulatory Elements ◽  
Whole Genome ◽  
Somatic Variation ◽  
Specific Expression ◽  
Large Scale Assessment

AbstractCancer is characterised by somatic genetic variation, but the effect of the majority of non-coding somatic variants and the interface with the germline genome are still unknown. We analysed the whole genome and RNA-Seq data from 1,188 human cancer patients as provided by the Pan-cancer Analysis of Whole Genomes (PCAWG) project to map cis expression quantitative trait loci of somatic and germline variation and to uncover the causes of allele-specific expression patterns in human cancers. The availability of the first large-scale dataset with both whole genome and gene expression data enabled us to uncover the effects of the non-coding variation on cancer. In addition to confirming known regulatory effects, we identified novel associations between somatic variation and expression dysregulation, in particular in distal regulatory elements. Finally, we uncovered links between somatic mutational signatures and gene expression changes, including TERT and LMO2, and we explained the inherited risk factors in APOBEC-related mutational processes. This work represents the first large-scale assessment of the effects of both germline and somatic genetic variation on gene expression in cancer and creates a valuable resource cataloguing these effects.

scholarly journals Epigenomic profiling of primate lymphoblastoid cell lines reveals the evolutionary patterns of epigenetic activities in gene regulatory architectures

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Raquel García-Pérez ◽  
Paula Esteller-Cucala ◽  
Glòria Mas ◽  
Irene Lobón ◽  
Valerio Di Carlo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Regulatory Element ◽  
Regulation Of Gene Expression ◽  
Regulatory Elements ◽  
Lymphoblastoid Cell Lines ◽  
Whole Genome ◽  
Specific Expression ◽  
Gene Regulatory ◽  
Human Specific

AbstractChanges in the epigenetic regulation of gene expression have a central role in evolution. Here, we extensively profiled a panel of human, chimpanzee, gorilla, orangutan, and macaque lymphoblastoid cell lines (LCLs), using ChIP-seq for five histone marks, ATAC-seq and RNA-seq, further complemented with whole genome sequencing (WGS) and whole genome bisulfite sequencing (WGBS). We annotated regulatory elements (RE) and integrated chromatin contact maps to define gene regulatory architectures, creating the largest catalog of RE in primates to date. We report that epigenetic conservation and its correlation with sequence conservation in primates depends on the activity state of the regulatory element. Our gene regulatory architectures reveal the coordination of different types of components and highlight the role of promoters and intragenic enhancers (gE) in the regulation of gene expression. We observe that most regulatory changes occur in weakly active gE. Remarkably, novel human-specific gE with weak activities are enriched in human-specific nucleotide changes. These elements appear in genes with signals of positive selection and human acceleration, tissue-specific expression, and particular functional enrichments, suggesting that the regulatory evolution of these genes may have contributed to human adaptation.

Abstract 348: Multi-Species Genome-Wide Analyses of the Specification of Individual Cardiac Cell Fates

2014 ◽  
Vol 115 (suppl_1) ◽  
Author(s):  
Brian Busser ◽  
Julian Haimovich ◽  
Guokai Chen ◽  
Ivan Ovcharenko ◽  
Alan Michelson
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Patterns ◽  
Embryonic Stem ◽  
Regulatory Elements ◽  
Cardiac Cells ◽  
Specific Gene ◽  
Cardiac Cell ◽  
Cell Fates ◽  
Cell Fate Decisions

There are remarkable molecular and embryological similarities in cardiogenesis between Drosophila and vertebrates. Cells comprising the Drosophila heart can be subdivided into individual identities based on differences in morphology, function and gene expression patterns. Recent studies have shown that differential modifications of histone proteins, in vivo transcription factor (TF) binding, and the presence of particular TF binding motifs can be used as predictive signatures of the enhancers that govern cell-specific gene expression. Here we used discriminative training methods within an integrative, multi-species framework to uncover the motifs, enhancers and genes underlying cardiac cell fate decisions. As an initial step, we undertook a large-scale validation of Drosophila heart enhancers, which revealed enhancer activities in distinct subpopulations of cardiac cells. To identify related cell-specific regulatory elements, we used the validated enhancers as a training set in a machine learning approach that integrated TF motifs with ChIP data for both TF binding and histone modifications. Empirical validation of candidate enhancers predicted by this method confirmed activity in the appropriate cardiac cells. By clustering the motifs derived from the individual cardiac classifiers, we identified and validated sequence features which discriminate specific cellular identities. Next, we asked if similar predictive signatures underlie mouse and human cardiomyocyte (CM) differentiation from embryonic stem cells (ESCs). We show that the distribution of histone marks found within differentiating human and mouse ESCs indeed predict genes potentially critical for CM differentiation, with the best predictions provided by the overlapping mouse and human candidates. We evaluated this result in a large-scale RNAi-based screen of Drosophila orthologs of the mammalian genes, which uncovered dozens of novel cardiogenic regulators whose function is being tested in differentiating human ESCs. In total, these results document the utility of computational modeling combined with empirical testing to uncover the enhancers, TF motifs and genes which characterize individual cardiac cell fates in both invertebrate and mammalian species.

scholarly journals Passive and active DNA methylation and the interplay with genetic variation in gene regulation

eLife ◽  
2013 ◽  
Vol 2 ◽  
Author(s):  
Maria Gutierrez-Arcelus ◽  
Tuuli Lappalainen ◽  
Stephen B Montgomery ◽  
Alfonso Buil ◽  
Halit Ongen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Gene Regulation ◽  
Genetic Variation ◽  
Genomic Sequence ◽  
Expression Patterns ◽  
Active Role ◽  
Epigenetic Mark ◽  
Sequencing Data ◽  
Specific Expression

DNA methylation is an essential epigenetic mark whose role in gene regulation and its dependency on genomic sequence and environment are not fully understood. In this study we provide novel insights into the mechanistic relationships between genetic variation, DNA methylation and transcriptome sequencing data in three different cell-types of the GenCord human population cohort. We find that the association between DNA methylation and gene expression variation among individuals are likely due to different mechanisms from those establishing methylation-expression patterns during differentiation. Furthermore, cell-type differential DNA methylation may delineate a platform in which local inter-individual changes may respond to or act in gene regulation. We show that unlike genetic regulatory variation, DNA methylation alone does not significantly drive allele specific expression. Finally, inferred mechanistic relationships using genetic variation as well as correlations with TF abundance reveal both a passive and active role of DNA methylation to regulatory interactions influencing gene expression.

scholarly journals ARBic: An All-Round Biclustering Algorithm for Analyzing Gene Expression Data

2021 ◽  
Author(s):  
Xiangyu Liu ◽  
Zhengchang Su ◽  
Guojun Li
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Large Scale ◽  
Expression Patterns ◽  
Data Matrix ◽  
Expression Data ◽  
Specific Expression ◽  
Longest Path ◽  
Background Data ◽  
Effectiveness And Efficiency

Abstract Background: Identifying significant biclusters of genes with specific expression patterns is an effective approach to reveal functionally correlated genes in gene expression data. However, existing algorithms are limited to finding either broad or narrow biclusters but both due to failure of balancing between effectiveness and efficiency. Methods: We developed a new algorithm ARBic which can accurately identify any meaningful biclusters of shape no matter broad or narrow in a large scale gene expression data matrix, even when the values in the biclusters to be identified have the same distribution as that the background data has. ARBic is developed by integrating column-based and row-based strategies into biclustering procedure. The column-based strategy borrowed from ReBic, a recently published biclustering tool, prefers to narrow bicluters. The row-based strategy newly designed in this article by repeatedly finding a longest path in a specific directed graph prefers to broader ones. Result and Conclusion: When tested and compared to other seven salient biclustering algorithms on simulated datasets, ARBic achieved recovery, relevance and f1-scores 29% higher than the second best algorithm. Furthermore, ARBic substantially outperforms all of them on real datasets and robusts to noises, shapes of biclusters and types of datasets.Code: https://github.com/holyzews/ARBicData: https://doi.org/10.5281/zenodo.5121018

scholarly journals The combined detection of Amphiregulin, Cyclin A1 and DDX20/Gemin3 expression predicts aggressive forms of oral squamous cell carcinoma

2021 ◽  
Author(s):  
Ekaterina Bourova-Flin ◽  
Samira Derakhshan ◽  
Afsaneh Goudarzi ◽  
Tao Wang ◽  
Anne-Laure Vitte ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell ◽  
Large Scale ◽  
Biomarker Discovery ◽  
Gene Expression Signature ◽  
Predictive Biomarkers ◽  
Specific Gene ◽  
Specific Expression ◽  
Intrinsic Nature ◽  
Independent Cohort

Abstract Background Large-scale genetic and epigenetic deregulations enable cancer cells to ectopically activate tissue-specific expression programmes. A specifically designed strategy was applied to oral squamous cell carcinomas (OSCC) in order to detect ectopic gene activations and develop a prognostic stratification test. Methods A dedicated original prognosis biomarker discovery approach was implemented using genome-wide transcriptomic data of OSCC, including training and validation cohorts. Abnormal expressions of silent genes were systematically detected, correlated with survival probabilities and evaluated as predictive biomarkers. The resulting stratification test was confirmed in an independent cohort using immunohistochemistry. Results A specific gene expression signature, including a combination of three genes, AREG, CCNA1 and DDX20, was found associated with high-risk OSCC in univariate and multivariate analyses. It was translated into an immunohistochemistry-based test, which successfully stratified patients of our own independent cohort. Discussion The exploration of the whole gene expression profile characterising aggressive OSCC tumours highlights their enhanced proliferative and poorly differentiated intrinsic nature. Experimental targeting of CCNA1 in OSCC cells is associated with a shift of transcriptomic signature towards the less aggressive form of OSCC, suggesting that CCNA1 could be a good target for therapeutic approaches.

A Global Vista of the Epigenomic State of the Mouse Submandibular Gland

2021 ◽  
pp. 002203452110120
Author(s):  
C. Gluck ◽  
S. Min ◽  
A. Oyelakin ◽  
M. Che ◽  
E. Horeth ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptional Control ◽  
Expression Patterns ◽  
Global Gene Expression ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Submandibular Salivary Gland ◽  
Data Sets ◽  
Control Mechanisms ◽  
Chromatin Immunoprecipitation Sequencing

The parotid, submandibular, and sublingual glands represent a trio of oral secretory glands whose primary function is to produce saliva, facilitate digestion of food, provide protection against microbes, and maintain oral health. While recent studies have begun to shed light on the global gene expression patterns and profiles of salivary glands, particularly those of mice, relatively little is known about the location and identity of transcriptional control elements. Here we have established the epigenomic landscape of the mouse submandibular salivary gland (SMG) by performing chromatin immunoprecipitation sequencing experiments for 4 key histone marks. Our analysis of the comprehensive SMG data sets and comparisons with those from other adult organs have identified critical enhancers and super-enhancers of the mouse SMG. By further integrating these findings with complementary RNA-sequencing based gene expression data, we have unearthed a number of molecular regulators such as members of the Fox family of transcription factors that are enriched and likely to be functionally relevant for SMG biology. Overall, our studies provide a powerful atlas of cis-regulatory elements that can be leveraged for better understanding the transcriptional control mechanisms of the mouse SMG, discovery of novel genetic switches, and modulating tissue-specific gene expression in a targeted fashion.

scholarly journals The CD11b promoter directs high-level expression of reporter genes in macrophages in transgenic mice [published erratum appears in Blood 1995 Apr 1;85(7):1983]

Blood ◽  
1995 ◽  
Vol 85 (2) ◽  
pp. 319-329 ◽  
Author(s):  
S Dziennis ◽  
RA Van Etten ◽  
HL Pahl ◽  
DL Morris ◽  
TL Rothstein ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transgenic Mice ◽  
Transgene Expression ◽  
Heterologous Gene Expression ◽  
Myeloid Cells ◽  
Reporter Genes ◽  
Regulatory Elements ◽  
Specific Expression ◽  
High Level

Abstract CD11b is the alpha chain of the Mac-1 integrin and is preferentially expressed in myeloid cells (neutrophils, monocytes, and macrophages). We have previously shown that the CD11b promoter directs cell-type- specific expression in myeloid lines using transient transfection assays. To confirm that these promoter sequences contain the proper regulatory elements for correct myeloid expression of CD11b in vivo, we have used the -1.7-kb human CD11b promoter to direct reporter gene expression in transgenic mice. Stable founder lines were generated with two different reporter genes, a Thy 1.1 surface marker and the Escherichia coli lacZ (beta-galactosidase) gene. Analysis of founders generated with each reporter demonstrated that the CD11b promoter was capable of driving high levels of transgene expression in murine macrophages for the lifetime of the animals. Similar to the endogenous gene, transgene expression was preferentially found in mature monocytes, macrophages, and neutrophils and not in myeloid precursors. These experiments indicate that the -1.7 CD11b promoter contains the regulatory elements sufficient for high-level macrophage expression. This promoter should be useful for targeting heterologous gene expression to mature myeloid cells.

scholarly journals Discovering Distinct Patterns in Gene Expression Profiles

2008 ◽  
Vol 5 (2) ◽  
Author(s):  
Li Teng ◽  
Laiwan Chan
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Clustering Methods ◽  
Gene Expressions ◽  
Real Gene ◽  
Large Scale Dataset ◽  
Coexpressed Genes

SummaryTraditional analysis of gene expression profiles use clustering to find groups of coexpressed genes which have similar expression patterns. However clustering is time consuming and could be diffcult for very large scale dataset. We proposed the idea of Discovering Distinct Patterns (DDP) in gene expression profiles. Since patterns showing by the gene expressions reveal their regulate mechanisms. It is significant to find all different patterns existing in the dataset when there is little prior knowledge. It is also a helpful start before taking on further analysis. We propose an algorithm for DDP by iteratively picking out pairs of gene expression patterns which have the largest dissimilarities. This method can also be used as preprocessing to initialize centers for clustering methods, like K-means. Experiments on both synthetic dataset and real gene expression datasets show our method is very effective in finding distinct patterns which have gene functional significance and is also effcient.

CFTR ΔF508 mutation has minimal effect on the gene expression profile of differentiated human airway epithelia

2005 ◽  
Vol 289 (4) ◽  
pp. L545-L553 ◽  
Author(s):  
Joseph Zabner ◽  
Todd E. Scheetz ◽  
Hakeem G. Almabrazi ◽  
Thomas L. Casavant ◽  
Jian Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cystic Fibrosis ◽  
Large Scale ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Primary Cultures ◽  
Gene Expression Profiles ◽  
Filter Method ◽  
Tissue Destruction ◽  
Airway Epithelia

Cystic fibrosis (CF) is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR), an epithelial chloride channel regulated by phosphorylation. Most of the disease-associated morbidity is the consequence of chronic lung infection with progressive tissue destruction. As an approach to investigate the cellular effects of CFTR mutations, we used large-scale microarray hybridization to contrast the gene expression profiles of well-differentiated primary cultures of human CF and non-CF airway epithelia grown under resting culture conditions. We surveyed the expression profiles for 10 non-CF and 10 ΔF508 homozygote samples. Of the 22,283 genes represented on the Affymetrix U133A GeneChip, we found evidence of significant changes in expression in 24 genes by two-sample t-test ( P < 0.00001). A second, three-filter method of comparative analysis found no significant differences between the groups. The levels of CFTR mRNA were comparable in both groups. There were no significant differences in the gene expression patterns between male and female CF specimens. There were 18 genes with significant increases and 6 genes with decreases in CF relative to non-CF samples. Although the function of many of the differentially expressed genes is unknown, one transcript that was elevated in CF, the KCl cotransporter (KCC4), is a candidate for further study. Overall, the results indicate that CFTR dysfunction has little direct impact on airway epithelial gene expression in samples grown under these conditions.

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