Cooperative signaling between cytokine receptors and the glucocorticoid receptor in the expansion of erythroid progenitors: molecular analysis by expression profiling

Blood ◽  
2003 ◽  
Vol 102 (9) ◽  
pp. 3136-3146 ◽  
Author(s):  
Andrea Kolbus ◽  
Montserrat Blázquez-Domingo ◽  
Sebastian Carotta ◽  
Walbert Bakker ◽  
Susanna Luedemann ◽  
...  
Keyword(s):  
Gene Expression ◽  
Glucocorticoid Receptor ◽  
Large Scale ◽  
Target Genes ◽  
Expression Patterns ◽  
Regulation Of Gene Expression ◽  
Gene Profiling ◽  
Erythroid Progenitors ◽  
Erythroid Progenitor ◽  
Synergistic Interactions

AbstractErythroid progenitors undergo renewal (proliferation without apparent differentiation) in response to erythropoietin (Epo), stem cell factor (SCF), and glucocorticoids (dexamethasone) (Dex). SCF and Dex cooperate with Epo to promote proliferation and inhibit differentiation of erythroid progenitors, while Epo alone is required to protect erythroid cells from apoptosis during terminal red cell maturation. To examine the mechanism of the synergistic interactions of Epo, SCF, and Dex, we analyzed gene expression patterns using DNA chip–based large-scale comparative gene profiling using microarrays enriched in hematopoietic transcripts or containing randomly selected genes. Differentially regulated genes were validated by real-time reverse transcription–polymerase chain reaction (RT-PCR). The results reveal cooperative regulation of gene expression by glucocorticoids and Epo/SCF on a number of genes, such as CIS, BTG1, VDUP1, CXCR4, GILZ, and RIKEN29300106B05. While Epo and SCF never showed opposite effects on gene expression, Dex either enhanced or attenuated the effect of Epo and/or SCF. Several glucocorticoid receptor (GR)–target genes were regulated by Dex only in the presence of Epo and/or SCF, suggesting that the GR functions in the context of a larger transactivation complex to regulate these genes. The data also suggest that modulation of cytokine-induced signals by the GR is an important mechanism in erythroid progenitor renewal.

microRNAs in seeds: modified detection techniques and potential applications

2006 ◽  
Vol 84 (2) ◽  
pp. 189-198 ◽  
Author(s):  
Ruth C. Martin ◽  
Po-Pu Liu ◽  
Hiroyuki Nonogaki
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Expression Patterns ◽  
Regulation Of Gene Expression ◽  
Environmental Signals ◽  
Detection Techniques ◽  
Potential Applications ◽  
Technical Advances ◽  
Spatio Temporal ◽  
Germinating Seeds

microRNAs (miRNAs) are small (21–24 nucleotides), single-stranded RNAs that regulate target gene expression at transcriptional and posttranscriptional levels. miRNAs play crucial roles in plant development, maintenance of homeostasis, and responses to environmental signals. miRNAs and their target genes, which can be computationally predicted in plants, are expressed in developing and germinating seeds as in other plant tissues, suggesting that miRNAs may be involved in the regulation of gene expression in seeds. Profiling multiple miRNAs expressed in developing and germinating seeds, characterizing their expression patterns in a spatio-temporal manner, and elucidating their biological functions will provide information essential for understanding the mechanisms of seed development and germination. In this review, an overview of the recent technical advances in seed miRNA research and their potential applications for plant, specifically seed, research are presented.

scholarly journals Maternal small RNAs mediate spatial-temporal regulation of gene expression, imprinting, and seed development in Arabidopsis

2019 ◽  
Vol 116 (7) ◽  
pp. 2761-2766 ◽  
Author(s):  
Ryan C. Kirkbride ◽  
Jie Lu ◽  
Changqing Zhang ◽  
Rebecca A. Mosher ◽  
David C. Baulcombe ◽  
...  
Keyword(s):  
Gene Expression ◽  
Seed Development ◽  
Seed Coat ◽  
Target Genes ◽  
Expression Patterns ◽  
Regulation Of Gene Expression ◽  
Small Interfering Rnas ◽  
Altered Expression ◽  
Temporal Regulation ◽  
Laser Capture

Arabidopsis seed development involves maternal small interfering RNAs (siRNAs) that induce RNA-directed DNA methylation (RdDM) through the NRPD1-mediated pathway. To investigate their biological functions, we characterized siRNAs in the endosperm and seed coat that were separated by laser-capture microdissection (LCM) in reciprocal genetic crosses with an nrpd1 mutant. We also monitored the spatial-temporal activity of the NRPD1-mediated pathway on seed development using the AGO4:GFP::AGO4 (promoter:GFP::protein) reporter and promoter:GUS sensors of siRNA-mediated silencing. From these approaches, we identified four distinct groups of siRNA loci dependent on or independent of the maternal NRPD1 allele in the endosperm or seed coat. A group of maternally expressed NRPD1-siRNA loci targets endosperm-preferred genes, including those encoding AGAMOUS-LIKE (AGL) transcription factors. Using translational promoter:AGL::GUS constructs as sensors, we demonstrate that spatial and temporal expression patterns of these genes in the endosperm are regulated by the NRPD1-mediated pathway irrespective of complete silencing (AGL91) or incomplete silencing (AGL40) of these target genes. Moreover, altered expression of these siRNA-targeted genes affects seed size. We propose that the corresponding maternal siRNAs could account for parent-of-origin effects on the endosperm in interploidy and hybrid crosses. These analyses reconcile previous studies on siRNAs and imprinted gene expression during seed development.

scholarly journals Characterization of Differentially Expressed miRNAs and Their Predicted Target Transcripts during Smoltification and Adaptation to Seawater in Head Kidney of Atlantic Salmon

Genes ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 1059
Author(s):  
Alice Shwe ◽  
Tone-Kari Knutsdatter Østbye ◽  
Aleksei Krasnov ◽  
Sigmund Ramberg ◽  
Rune Andreassen
Keyword(s):  
Gene Expression ◽  
Atlantic Salmon ◽  
Target Genes ◽  
Sea Water ◽  
Expression Patterns ◽  
Regulation Of Gene Expression ◽  
Head Kidney ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Small Rna Sequencing

Smoltification and early seawater phase are critical developmental periods with physiological and biochemical changes in Atlantic salmon that facilitates survival in saltwater. MicroRNAs (miRNAs) are known to have important roles in development, but whether any miRNAs are involved in regulation of gene expression during smoltification and the adaption to seawater is largely unknown. Here, small RNA sequencing of materials from head kidney before, during smoltification and post seawater transfer were used to study expression dynamics of miRNAs, while microarray analysis was applied to study mRNA expression dynamics. Comparing all timepoints, 71 miRNAs and 2709 mRNAs were identified as differentially expressed (DE). Hierarchical clustering analysis of the DE miRNAs showed three major clusters with characteristic expression changes. Eighty-one DE mRNAs revealed negatively correlated expression patterns to DE miRNAs in Cluster I and III. Furthermore, 42 of these mRNAs were predicted as DE miRNA targets. Gene enrichment analysis of negatively correlated target genes showed they were enriched in gene ontology groups hormone biosynthesis, stress management, immune response, and ion transport. The results strongly indicate that post-transcriptional regulation of gene expression by miRNAs is important in smoltification and sea water adaption, and this study identifies several putative miRNA-target pairs for further functional studies.

scholarly journals Large-scale mapping of positional changes of hypoxia-responsive genes upon activation

2021 ◽  
Author(s):  
Koh Nakayama ◽  
Sigal Shachar ◽  
Elizabeth H Finn ◽  
Hiroyuki Sato ◽  
Akihiro Hirakawa ◽  
...  
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Radial Distance ◽  
Spatial Location ◽  
Distance Analysis ◽  
Large Scale Analysis ◽  
Activity State ◽  
Hypoxic Treatment

Chromosome structure and nuclear organization are important factors in the regulation of gene expression. Transcription of a gene is influenced by local and global chromosome features such as condensation status and histone modifications. The relationship between the position of a gene in the cell nucleus and its activity is less clear. Here, we used high-throughput imaging to perform a large-scale analysis of the spatial location of a set of nearly 100 hypoxia-inducible genes to determine whether their location within the nucleus is correlated with their activity state upon stimulation. Radial distance analysis demonstrated that the majority of HIF- and CREB-inducible hypoxia responsive genes are located in the intermediate region of the nucleus. Radial position of numerous responsive genes changed upon hypoxic treatment. Analysis of the relative distances amongst a subset of HIF target gene groups revealed that some gene pairs also altered their relative location to each other upon hypoxic treatment, suggesting higher order chromatin rearrangements. While these changes in location occurred in response to hypoxic activation of the target genes, they did not correlate with the extent of their activation. These results suggest that induction of the hypoxia-responsive gene expression program is accompanied by spatial alterations of the genome, but that radial and relative gene positions are not directly related to gene activity.

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.

A TRIPARTITE CLUSTERING ANALYSIS ON MICRORNA, GENE AND DISEASE MODEL

2012 ◽  
Vol 10 (01) ◽  
pp. 1240007 ◽  
Author(s):  
CHENGCHENG SHEN ◽  
YING LIU
Keyword(s):  
Gene Expression ◽  
Clustering Algorithm ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Disease Model ◽  
Relational Information ◽  
Microrna Gene ◽  
Research Findings ◽  
Family Based

Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings.

scholarly journals SOMDE: A scalable method for identifying spatially variable genes with self-organizing map

2020 ◽  
Author(s):  
Minsheng Hao ◽  
Kui Hua ◽  
Xuegong Zhang
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Patterns ◽  
Self Organizing Map ◽  
Expression Data ◽  
Spatial Expression ◽  
Variable Expression ◽  
Sequencing Technologies ◽  
Physical Context ◽  
Variable Genes

AbstractRecent developments of spatial transcriptomic sequencing technologies provide powerful tools for understanding cells in the physical context of tissue micro-environments. A fundamental task in spatial gene expression analysis is to identify genes with spatially variable expression patterns, or spatially variable genes (SVgenes). Several computational methods have been developed for this task. Their high computational complexity limited their scalability to the latest and future large-scale spatial expression data.We present SOMDE, an efficient method for identifying SVgenes in large-scale spatial expression data. SOMDE uses selforganizing map (SOM) to cluster neighboring cells into nodes, and then uses a Gaussian Process to fit the node-level spatial gene expression to identify SVgenes. Experiments show that SOMDE is about 5-50 times faster than existing methods with comparable results. The adjustable resolution of SOMDE makes it the only method that can give results in ~5 minutes in large datasets of more than 20,000 sequencing sites. SOMDE is available as a python package on PyPI at https://pypi.org/project/somde.

scholarly journals Alterations of Growth and Focal Adhesion Molecules in Human Breast Cancer Cells Exposed to the Random Positioning Machine

2021 ◽  
Vol 9 ◽  
Author(s):  
Jayashree Sahana ◽  
Thomas J. Corydon ◽  
Markus Wehland ◽  
Marcus Krüger ◽  
Sascha Kopp ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Target Genes ◽  
Interaction Analysis ◽  
Expression Patterns ◽  
Focal Adhesions ◽  
Multicellular Spheroids ◽  
Down Regulation ◽  
Random Positioning Machine ◽  
Mcf 7

In this study, we evaluated changes in focal adhesions (FAs) in two types of breast cancer cell (BCC) lines (differentiated MCF-7 and the triple-negative MDA-MB-231 cell line) exposed to simulated microgravity (s-μg) created by a random positioning machine (RPM) for 24 h. After exposure, the BCC changed their growth behavior and exhibited two phenotypes in RPM samples: one portion of the cells grew as a normal two-dimensional monolayer [adherent (AD) BCC], while the other portion formed three-dimensional (3D) multicellular spheroids (MCS). After 1 h and 30 min (MDA-MB-231) and 1 h 40 min (MCF-7), the MCS adhered completely to the slide flask bottom. After 2 h, MDA-MB-231 MCS cells started to migrate, and after 6 h, a large number of the cells had left the MCS and continued to grow in a scattered pattern, whereas MCF-7 cells were growing as a confluent monolayer after 6 h and 24 h. We investigated the genes associated with the cytoskeleton, the extracellular matrix and FAs. ACTB, TUBB, FN1, FAK1, and PXN gene expression patterns were not significantly changed in MDA-MB-231 cells, but we observed a down-regulation of LAMA3, ITGB1 mRNAs in AD cells and of ITGB1, TLN1 and VCL mRNAs in MDA-MB-231 MCS. RPM-exposed MCF-7 cells revealed a down-regulation in the gene expression of FAK1, PXN, TLN1, VCL and CDH1 in AD cells and PXN, TLN and CDH1 in MCS. An interaction analysis of the examined genes involved in 3D growth and adhesion indicated a central role of fibronectin, vinculin, and E-cadherin. Live cell imaging of eGFP-vinculin in MCF-7 cells confirmed these findings. β-catenin-transfected MCF-7 cells revealed a nuclear expression in 1g and RPM-AD cells. The target genes BCL9, MYC and JUN of the Wnt/β-catenin signaling pathway were differentially expressed in RPM-exposed MCF-7 cells. These findings suggest that vinculin and β-catenin are key mediators of BCC to form MCS during 24 h of RPM-exposure.

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