scholarly journals Long-range promoter-enhancer contacts are conserved during evolution and contribute to gene expression robustness

2021 ◽  
pp. gr.275901.121
Author(s):  
Alexandre Laverre ◽  
Eric Tannier ◽  
Anamaria Necsulea
Keyword(s):  
Gene Expression ◽  
Long Range ◽  
Large Scale ◽  
Target Genes ◽  
Expression Profiles ◽  
Regulatory Element ◽  
Gene Expression Profiles ◽  
Evolutionary Conservation ◽  
Regulatory Elements ◽  
Regulatory Landscapes

Gene expression is regulated through complex molecular interactions, involving cis-acting elements that can be situated far away from their target genes. Data on long-range contacts between promoters and regulatory elements is rapidly accumulating. However, it remains unclear how these regulatory relationships evolve and how they contribute to the establishment of robust gene expression profiles. Here, we address these questions by comparing genome-wide maps of promoter-centered chromatin contacts in mouse and human. We show that there is significant evolutionary conservation of cis-regulatory landscapes, indicating that selective pressures act to preserve not only regulatory element sequences but also their chromatin contacts with target genes. The extent of evolutionary conservation is remarkable for long-range promoter-enhancer contacts, illustrating how the structure of regulatory landscapes constrains large-scale genome evolution. We show that the evolution of cis-regulatory landscapes, measured in terms of distal element sequences, synteny or contacts with target genes, is significantly associated with gene expression evolution.

scholarly journals Long-range promoter-enhancer contacts are conserved during evolution and contribute to gene expression robustness

2021 ◽  
Author(s):  
Alexandre Laverré ◽  
Eric Tannier ◽  
Anamaria Necsulea
Keyword(s):  
Gene Expression ◽  
Long Range ◽  
Large Scale ◽  
Target Genes ◽  
Expression Profiles ◽  
Regulatory Element ◽  
Gene Expression Profiles ◽  
Evolutionary Conservation ◽  
Regulatory Elements ◽  
Regulatory Landscapes

AbstractGene expression is regulated through complex molecular interactions, involving cis-acting elements that can be situated far away from their target genes. Data on long-range contacts between promoters and regulatory elements is rapidly accumulating. However, it remains unclear how these regulatory relationships evolve and how they contribute to the establishment of robust gene expression profiles. Here, we address these questions by comparing genome-wide maps of promoter-centered chromatin contacts in mouse and human. We show that there is significant evolutionary conservation of cis-regulatory landscapes, indicating that selective pressures act to preserve regulatory element sequences and their interactions with target genes. The extent of evolutionary conservation is remarkable for long-range promoter-enhancer contacts, illustrating how the structure of regulatory interactions constrains large-scale genome evolution. Notably, we show that the evolution of cis-regulatory landscapes, measured in terms of distal element sequences, synteny or contacts with target genes, is tightly linked to gene expression evolution.

scholarly journals Chromatin occupancy analysis reveals genome-wide GATA factor switching during hematopoiesis

Blood ◽  
2012 ◽  
Vol 119 (16) ◽  
pp. 3724-3733 ◽  
Author(s):  
Louis C. Doré ◽  
Timothy M. Chlon ◽  
Christopher D. Brown ◽  
Kevin P. White ◽  
John D. Crispino
Keyword(s):  
Gene Expression ◽  
Transcriptional Activation ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Regulatory Elements ◽  
Gata Factor ◽  
Related Factors ◽  
Genome Wide ◽  
A Genome

Abstract There are many examples of transcription factor families whose members control gene expression profiles of diverse cell types. However, the mechanism by which closely related factors occupy distinct regulatory elements and impart lineage specificity is largely undefined. Here we demonstrate on a genome wide scale that the hematopoietic GATA factors GATA-1 and GATA-2 bind overlapping sets of genes, often at distinct sites, as a means to differentially regulate target gene expression and to regulate the balance between proliferation and differentiation. We also reveal that the GATA switch, which entails a chromatin occupancy exchange between GATA2 and GATA1 in the course of differentiation, operates on more than one-third of GATA1 bound genes. The switch is equally likely to lead to transcriptional activation or repression; and in general, GATA1 and GATA2 act oppositely on switch target genes. In addition, we show that genomic regions co-occupied by GATA2 and the ETS factor ETS1 are strongly enriched for regions marked by H3K4me3 and occupied by Pol II. Finally, by comparing GATA1 occupancy in erythroid cells and megakaryocytes, we find that the presence of ETS factor motifs is a major discriminator of megakaryocyte versus red cell specification.

scholarly journals LncGSEA: a versatile tool to infer lncRNA associated pathways from large-scale cancer transcriptome sequencing data

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanan Ren ◽  
Ting-You Wang ◽  
Leah C. Anderton ◽  
Qi Cao ◽  
Rendong Yang
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Multiple Cancer ◽  
Regulatory Pathways ◽  
Cancer Transcriptome ◽  
Versatile Tool

Abstract Background Long non-coding RNAs (lncRNAs) are a growing focus in cancer research. Deciphering pathways influenced by lncRNAs is important to understand their role in cancer. Although knock-down or overexpression of lncRNAs followed by gene expression profiling in cancer cell lines are established approaches to address this problem, these experimental data are not available for a majority of the annotated lncRNAs. Results As a surrogate, we present lncGSEA, a convenient tool to predict the lncRNA associated pathways through Gene Set Enrichment Analysis of gene expression profiles from large-scale cancer patient samples. We demonstrate that lncGSEA is able to recapitulate lncRNA associated pathways supported by literature and experimental validations in multiple cancer types. Conclusions LncGSEA allows researchers to infer lncRNA regulatory pathways directly from clinical samples in oncology. LncGSEA is written in R, and is freely accessible at https://github.com/ylab-hi/lncGSEA.

scholarly journals Analysis of blood-based gene expression in idiopathic Parkinson disease

Neurology ◽  
2017 ◽  
Vol 89 (16) ◽  
pp. 1676-1683 ◽  
Author(s):  
Ron Shamir ◽  
Christine Klein ◽  
David Amar ◽  
Eva-Juliane Vollstedt ◽  
Michael Bonin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson Disease ◽  
Gene Networks ◽  
Large Scale ◽  
Expression Profiles ◽  
Area Under The Curve ◽  
Gene Expression Profiles ◽  
Gene Signature ◽  
Gene Profiles ◽  
Independent Test

Objective:To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220 samples).Methods:Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks.Results:A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was identified with the training cohort and successfully replicated in both an independent validation cohort (area under the curve [AUC] = 0.79, p = 7.13E–6) and a subsequent independent test cohort (AUC = 0.74, p = 4.2E–4). Network analysis of the signature revealed gene enrichment in pathways, including metabolism, oxidation, and ubiquitination/proteasomal activity, and misregulation of mitochondria-localized genes, including downregulation of COX4I1, ATP5A1, and VDAC3.Conclusions:We present a large-scale study of PD gene expression profiling. This work identifies a reliable blood-based PD signature and highlights the importance of large-scale patient cohorts in developing potential PD biomarkers.

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.

Isolation stress for 30 days alters hepatic gene expression profiles, especially with reference to lipid metabolism in mice

2009 ◽  
Vol 37 (2) ◽  
pp. 79-87 ◽  
Author(s):  
Keiko Motoyama ◽  
Yuji Nakai ◽  
Tomoya Miyashita ◽  
Yuichiro Fukui ◽  
Maki Morita ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lipid Metabolism ◽  
Dna Microarray ◽  
Social Stress ◽  
Secretory Pathway ◽  
Expression Profiles ◽  
Regulatory Element ◽  
Gene Expression Profiles ◽  
Hepatic Gene Expression ◽  
Isolation Stress

To elucidate the physiological responses to a social stressor, we exposed mice to an isolation stress and analyzed their hepatic gene expression profiles using a DNA microarray. Male BALB/c mice were exposed to isolation stress for 30 days, and then hepatic RNA was sampled and subjected to DNA microarray analysis. The isolation stress altered the expression of 420 genes (after considering the false discovery rate). Gene Ontology analysis of these differentially expressed genes indicated that the stress remarkably downregulated the lipid metabolism-related pathway through peroxisome proliferator-activated receptor-α, while the lipid biosynthesis pathway controlled by sterol regulatory element binding factor 1, Golgi vesicle transport, and secretory pathway-related genes were significantly upregulated. These results suggest that isolation for 30 days with a mild and consecutive social stress regulates the systems for lipid metabolism and also causes endoplasmic reticulum stress in mouse liver.

scholarly journals Dynamical consequences of regional heterogeneity in the brain’s transcriptional landscape

2020 ◽  
Author(s):  
Gustavo Deco ◽  
Kevin Aquino ◽  
Aurina Arnatkevičiūtė ◽  
Stuart Oldham ◽  
Kristina Sabaroedin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Global Gene Expression ◽  
Brain Regions ◽  
Biophysical Model ◽  
Neuronal Dynamics ◽  
Regional Heterogeneity ◽  
Magnetic Resonance Imaging Mri

AbstractBrain regions vary in their molecular and cellular composition, but how this heterogeneity shapes neuronal dynamics is unclear. Here, we investigate the dynamical consequences of regional heterogeneity using a biophysical model of whole-brain functional magnetic resonance imaging (MRI) dynamics in humans. We show that models in which transcriptional variations in excitatory and inhibitory receptor (E:I) gene expression constrain regional heterogeneity more accurately reproduce the spatiotemporal structure of empirical functional connectivity estimates than do models constrained by global gene expression profiles and MRI-derived estimates of myeloarchitecture. We further show that regional heterogeneity is essential for yielding both ignition-like dynamics, which are thought to support conscious processing, and a wide variance of regional activity timescales, which supports a broad dynamical range. We thus identify a key role for E:I heterogeneity in generating complex neuronal dynamics and demonstrate the viability of using transcriptional data to constrain models of large-scale brain function.

Sex differences in viral entry protein expression and host transcript responses to SARS-CoV-2

2020 ◽  
Author(s):  
Mengying Sun ◽  
Rama Shankar ◽  
Meehyun Ko ◽  
Christopher Daniel Chang ◽  
Shan-Ju Yeh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Sex Differences ◽  
Viral Entry ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Scale Analysis ◽  
Transcriptional Responses ◽  
Deconvolution Analysis ◽  
Large Scale Analysis

Abstract Epidemiological studies suggest that men exhibit a higher mortality rate to COVID-19 than women, yet the underlying biology is largely unknown. Here, we seek to delineate sex differences in the gene expression of viral entry proteins ACE2 and TMPRSS2, and host transcriptional responses to SARS-CoV-2 through large-scale analysis of genomic and clinical data. We first compiled 220,000 human gene expression profiles from three databases and completed the meta-information through machine learning and manual annotation. Large scale analysis of these profiles indicated that male samples show higher expression levels of ACE2 and TMPRSS2 than female samples, especially in the older group (>60 years) and in the kidney. Subsequent analysis of 6,031 COVID-19 patients at Mount Sinai Health System revealed that men have significantly higher creatinine levels, an indicator of impaired kidney function. Further analysis of 782 COVID-19 patient gene expression profiles taken from upper airway and blood suggested men and women present distinct expression changes. Computational deconvolution analysis of these profiles revealed male COVID-19 patients have enriched kidney-specific mesangial cells in blood compared to healthy patients. Together, this study suggests biological differences in the kidney between sexes may contribute to sex disparity in COVID-19.

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