scholarly journals Time-dependent changes in ARE-driven gene expression by use of a noise-filtering process for microarray data

2002 ◽  
Vol 9 (3) ◽  
pp. 137-144 ◽  
Author(s):  
Jiang Li ◽  
Jeffrey A. Johnson
Keyword(s):  
Gene Expression ◽  
Signal Transduction ◽  
Microarray Data ◽  
Transcriptional Activation ◽  
Expression Profiles ◽  
Time Dependent ◽  
Gene Clustering ◽  
Noise Filtering ◽  
Human Neuroblastoma ◽  
Rank Analysis

The current study was designed to identify the time-dependent gene expression profiles of antioxidant responsive element (ARE)-driven genes induced by tert-butylhydroquinone (tBHQ). A set of simple noise-filtering methods was introduced to evaluate and minimize the variance of microarray datasets. Gene expression induced by tBHQ (10 μM) in IMR-32 human neuroblastoma cells was analyzed by means of large-scale oligonucleotide microarray. Rank analysis was used to determine the acceptable number of independent samples necessary to eliminate false positives from the dataset. A dramatic reduction in the number of genes passing the rank analysis was achieved by using a 3 × 3 matrix comparison. Reproducibility was evaluated based on the coefficient of variation for average difference change. Completion of these analyses revealed that 101 of the 9,670 genes examined showed dynamic changes with treatment ranging from 4 h to 48 h. Since certain ARE-driven genes have been already identified, gene clustering would presumably group them together based on similar regulation. Self-organizing map grouped the genes induced by tBHQ into 12 (4×3) distinct clusters. Those previously identified ARE-driven genes were shown to group into different clusters. Since all potential ARE-driven genes did not cluster together, we speculate that multiple transcription factors and/or multiple signal transduction pathways contribute to transcriptional activation of the ARE. In conclusion, many novel potential ARE-driven genes were identified in this study. They function in detoxification and antioxidant defense, neuronal proliferation and differentiation, and signal transduction. The noise-filtering process applied to these microarray data, therefore, has proven to be very useful in identification of the time-dependent changes in ARE-drive gene expression.

scholarly journals Leiomyoma and Myometrial Gene Expression Profiles and Their Responses to Gonadotropin-Releasing Hormone Analog Therapy

Endocrinology ◽  
2005 ◽  
Vol 146 (3) ◽  
pp. 1074-1096 ◽  
Author(s):  
Xiaoping Luo ◽  
Li Ding ◽  
Jingxia Xu ◽  
R. Stan Williams ◽  
Nasser Chegini
Keyword(s):  
Gene Expression ◽  
Signal Transduction ◽  
Binding Protein ◽  
Expression Profiles ◽  
Primary Cultures ◽  
Time Dependent ◽  
Early Gene ◽  
Dependent Manner ◽  
Cell Cycle Regulators ◽  
Gnrh Analog

Gene microarray was used to characterize the molecular environment of leiomyoma and matched myometrium during growth and in response to GnRH analog (GnRHa) therapy as well as GnRHa direct action on primary cultures of leiomyoma and myometrial smooth muscle cells (LSMC and MSMC). Unsupervised and supervised analysis of gene expression values and statistical analysis in R programming with a false discovery rate of P ≤ 0.02 resulted in identification of 153 and 122 differentially expressed genes in leiomyoma and myometrium in untreated and GnRHa-treated cohorts, respectively. The expression of 170 and 164 genes was affected by GnRHa therapy in these tissues compared with their respective untreated group. GnRHa (0.1 μm), in a time-dependent manner (2, 6, and 12 h), targeted the expression of 281 genes (P ≤ 0.005) in LSMC and MSMC, 48 of which genes were found in common with GnRHa-treated tissues. Functional annotations assigned these genes as key regulators of processes involving transcription, translational, signal transduction, structural activities, and apoptosis. We validated the expression of IL-11, early growth response 3, TGF-β-induced factor, TGF-β-inducible early gene response, CITED2 (cAMP response element binding protein-binding protein/p300-interacting transactivator with ED-rich tail), Nur77, growth arrest-specific 1, p27, p57, and G protein-coupled receptor kinase 5, representing cytokine, common transcription factors, cell cycle regulators, and signal transduction, at tissue levels and in LSMC and MSMC in response to GnRHa time-dependent action using real-time PCR, Western blotting, and immunohistochemistry. In conclusion, using different, complementary approaches, we characterized leiomyoma and myometrium molecular fingerprints and identified several previously unrecognized genes as targets of GnRHa action, implying that local expression and activation of these genes may represent features differentiating leiomyoma and myometrial environments during growth and GnRHa-induced regression.

scholarly journals Time Dependent Gene Expression Changes in the Liver of Mice Treated with Benzene

2008 ◽  
Vol 3 ◽  
pp. BMI.S590 ◽  
Author(s):  
Han-Jin Park ◽  
Jung Hwa Oh ◽  
Seokjoo Yoon ◽  
S.V.S. Rana
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
General Purpose ◽  
Time Dependent ◽  
Expression Data ◽  
Benzene Exposure ◽  
Microarray Analyses ◽  
First Time ◽  
Affymetrix Gene Chip

Benzene is used as a general purpose solvent. Benzene metabolism starts from phenol and ends with p-benzoquinone and o-benzoquinone. Liver injury inducted by benzene still remains a toxicologic problem. Tumor related genes and immune responsive genes have been studied in patients suffering from benzene exposure. However, gene expression profiles and pathways related to its hepatotoxicity are not known. This study reports the results obtained in the liver of BALB/C mice (SLC, Inc., Japan) administered 0.05 ml/100 g body weight of 2% benzene for six days. Serum, ALT, AST and ALP were determined using automated analyzer (Fuji., Japan). Histopathological observations were made to support gene expression data. c-DNA microarray analyses were performed using Affymetrix Gene-chip system. After six days of benzene exposure, twenty five genes were down regulated whereas nineteen genes were up-regulated. These gene expression changes were found to be related to pathways of biotransformation, detoxification, apoptosis, oxidative stress and cell cycle. It has been shown for the first time that genes corresponding to circadian rhythms are affected by benzene. Results suggest that gene expression profile might serve as potential biomarkers of hepatotoxicity during benzene exposure.

scholarly journals Genome-Wide Gene Expression Profiles Analysis Reveal Novel Insights into Drought Stress in Foxtail Millet (Setaria italica L.)

2020 ◽  
Vol 21 (22) ◽  
pp. 8520
Author(s):  
Ling Qin ◽  
Erying Chen ◽  
Feifei Li ◽  
Xiao Yu ◽  
Zhenyu Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signal Transduction ◽  
Drought Stress ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Foxtail Millet ◽  
Gene Expression Profiles ◽  
Sugar Metabolism ◽  
Setaria Italica ◽  
Phenylpropanoid Biosynthesis

Foxtail millet (Setaria italica (L.) P. Beauv) is an important food and forage crop because of its health benefits and adaptation to drought stress; however, reports of transcriptomic analysis of genes responding to re-watering after drought stress in foxtail millet are rare. The present study evaluated physiological parameters, such as proline content, p5cs enzyme activity, anti-oxidation enzyme activities, and investigated gene expression patterns using RNA sequencing of the drought-tolerant foxtail millet variety (Jigu 16) treated with drought stress and rehydration. The results indicated that drought stress-responsive genes were related to many multiple metabolic processes, such as photosynthesis, signal transduction, phenylpropanoid biosynthesis, starch and sucrose metabolism, and osmotic adjustment. Furthermore, the Δ1-pyrroline-5-carboxylate synthetase genes, SiP5CS1 and SiP5CS2, were remarkably upregulated in foxtail millet under drought stress conditions. Foxtail millet can also recover well on rehydration after drought stress through gene regulation. Our data demonstrate that recovery on rehydration primarily involves proline metabolism, sugar metabolism, hormone signal transduction, water transport, and detoxification, plus reversal of the expression direction of most drought-responsive genes. Our results provided a detailed description of the comparative transcriptome response of foxtail millet variety Jigu 16 under drought and rehydration environments. Furthermore, we identify SiP5CS2 as an important gene likely involved in the drought tolerance of foxtail millet.

scholarly journals Visual Comparison of Multiple Gene Expression Datasets in a Genomic Context

2008 ◽  
Vol 5 (2) ◽  
Author(s):  
Krzysztof Borowski ◽  
Jung Soh ◽  
Christoph W. Sensen
Keyword(s):  
Gene Expression ◽  
Microarray Data ◽  
Gene Function ◽  
Graphical Representation ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Expression Data ◽  
Genomic Context ◽  
Multiple Gene ◽  
Microarray Datasets

SummaryThe need for novel methods of visualizing microarray data is growing. New perspectives are beneficial to finding patterns in expression data. The Bluejay genome browser provides an integrative way of visualizing gene expression datasets in a genomic context. We have now developed the functionality to display multiple microarray datasets simultaneously in Bluejay, in order to provide researchers with a comprehensive view of their datasets linked to a graphical representation of gene function. This will enable biologists to obtain valuable insights on expression patterns, by allowing them to analyze the expression values in relation to the gene locations as well as to compare expression profiles of related genomes or of di erent experiments for the same genome.

scholarly journals Application of Gene Shaving and Mixture Models to Cluster Microarray Gene Expression Data

2007 ◽  
Vol 5 ◽  
pp. 117693510700500
Author(s):  
K-A. Do ◽  
G.J. McLachlan ◽  
R. Bean ◽  
S. Wen
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Lymphoblastic Leukemia ◽  
Gene Clusters ◽  
Gene Clustering ◽  
Expression Data ◽  
Colon Tissue ◽  
Data Set ◽  
Tissue Samples ◽  
Gene Shaving

Researchers are frequently faced with the analysis of microarray data of a relatively large number of genes using a small number of tissue samples. We examine the application of two statistical methods for clustering such microarray expression data: EMMIX-GENE and GeneClust. EMMIX-GENE is a mixture-model based clustering approach, designed primarily to cluster tissue samples on the basis of the genes. GeneClust is an implementation of the gene shaving methodology, motivated by research to identify distinct sets of genes for which variation in expression could be related to a biological property of the tissue samples. We illustrate the use of these two methods in the analysis of Affymetrix oligonucleotide arrays of well-known data sets from colon tissue samples with and without tumors, and of tumor tissue samples from patients with leukemia. Although the two approaches have been developed from different perspectives, the results demonstrate a clear correspondence between gene clusters produced by GeneClust and EMMIX-GENE for the colon tissue data. It is demonstrated, for the case of ribosomal proteins and smooth muscle genes in the colon data set, that both methods can classify genes into co-regulated families. It is further demonstrated that tissue types (tumor and normal) can be separated on the basis of subtle distributed patterns of genes. Application to the leukemia tissue data produces a division of tissues corresponding closely to the external classification, acute myeloid meukemia (AML) and acute lymphoblastic leukemia (ALL), for both methods. In addition, we also identify genes specific for the subgroup of ALL-Tcell samples. Overall, we find that the gene shaving method produces gene clusters at great speed; allows variable cluster sizes and can incorporate partial or full supervision; and finds clusters of genes in which the gene expression varies greatly over the tissue samples while maintaining a high level of coherence between the gene expression profiles. The intent of the EMMIX-GENE method is to cluster the tissue samples. It performs a filtering step that results in a subset of relevant genes, followed by gene clustering, and then tissue clustering, and is favorable in its accuracy of ranking the clusters produced.

Photo-caged agonists of the nuclear receptors RARγ and TRβ provide unique time-dependent gene expression profiles for light-activated gene patterning

2004 ◽  
Vol 12 (22) ◽  
pp. 5949-5959 ◽  
Author(s):  
Kristian H. Link ◽  
Federico G. Cruz ◽  
Hai-Fen Ye ◽  
Kathryn E. O’Reilly ◽  
Sarah Dowdell ◽  
...  
Keyword(s):  
Gene Expression ◽  
Nuclear Receptors ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Time Dependent ◽  
Gene Patterning

scholarly journals The control of transcriptional memory by stable mitotic bookmarking

2021 ◽  
Author(s):  
Maelle Bellec ◽  
Jeremy Dufourt ◽  
George Hunt ◽  
Helene Lenden-Hasse ◽  
Antonio Trullo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptional Activation ◽  
Expression Profiles ◽  
Large Fraction ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Mitotic Exit ◽  
Regulatory Sequences ◽  
Transcriptional Memory ◽  
Genome Activation

To maintain cellular identities during development, gene expression profiles must be faithfully propagated through cell generations. The reestablishment of gene expression patterns upon mitotic exit is thought to be mediated, in part, by mitotic bookmarking by transcription factors (TF). However, the mechanisms and functions of TF mitotic bookmarking during early embryogenesis remain poorly understood. In this study, taking advantage of the naturally synchronized mitoses of Drosophila early embryos, we provide evidence that the pioneer-like transcription factor GAF acts as stable mitotic bookmarker during zygotic genome activation. We report that GAF remains associated to a large fraction of its interphase targets including at cis-regulatory sequences of key developmental genes, with both active and repressive chromatin signatures. GAF mitotic targets are globally accessible during mitosis and are bookmarked via histone acetylation (H4K8ac). By monitoring the kinetics of transcriptional activation in living embryos, we provide evidence that GAF binding establishes competence for rapid activation upon mitotic exit.

Abstract P744: Gene Transcript Clusters Distinguish Time-Dependent Expression Patterns in Monocytes, Neutrophils and Whole Blood After Ischemic Stroke Injury

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Paulina Carmona-Mora ◽  
Glen C Jickling ◽  
Xinhua Zhan ◽  
Marisa Hakoupian ◽  
Heather Hull ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ischemic Stroke ◽  
Whole Blood ◽  
Temporal Dynamics ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Time Dependent ◽  
Gene Transcript ◽  
Time Points

Introduction: After ischemic stroke (IS), peripheral leukocytes infiltrate the damaged region and modulate the response to injury. We previously showed that peripheral blood cells display different gene expression profiles after IS and these transcriptional programs reflect the changes in immune processes in response to IS. Dissecting the temporal dynamics of gene expression after IS improves our understanding of the changes of molecular and cellular pathways involved in acute brain injury. Methods: We analyzed the transcriptomic profiles of 33 IS patients in isolated monocytes, neutrophils and whole blood. RNA-sequencing was performed on all the stroke samples as well as 12 controls with vascular risk factors (diabetes and/or hypertension and/or hypercholesterolemia). To identify differentially expressed genes, subjects were split into time points (TPs) from stroke onset (TP1= 0-24 h; TP2= 24-48 h; and TP3= > 48 h), and controls were assigned TP0. A linear regression model including time and the interaction of diagnosis x TP with cutoff of p<0.02 and fold-change>|1.2| was used. Time dependent changes were analyzed using artificial neural networks to identify clusters of genes that behave in a similar way across TPs. Results: Unique patterns of temporal expression were distinguished for the three sample types. These include genes not expressed in TP0 that peak only within the first 24 h, others that peak or decrease in TP2 and TP3, and more complex patterns. Genes that peak at TP1 in monocytes and neutrophils are related to cell adhesion and leukocyte differentiation/migration, respectively. Early peaks in whole blood occur in genes related to transcriptional regulation. In monocytes, interleukin pathways are enriched across all TPs, whereas there is a trend of suppression after 24 h in neutrophils. The inflammasome pathway is enriched in the earlier TPs in neutrophils, while not enriched in monocytes until over 48 hours. Conclusion: Our analyses on gene expression dynamics and cluster patterns allow identification of key genes and pathways at different time points following ischemic injury that are valuable as IS biomarkers and may be possible treatment targets.

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