scholarly journals CIDER: a pipeline for detecting waves of coordinated transcriptional regulation in gene expression time-course data

2015 ◽  
Author(s):  
Marco Mina ◽  
Giuseppe Jurman ◽  
Cesare Furlanello
Keyword(s):  
Gene Expression ◽  
Transcriptional Regulation ◽  
Gene Transcription ◽  
Environmental Changes ◽  
Expression Patterns ◽  
Transcriptional Networks ◽  
Motif Enrichment ◽  
Time Courses ◽  
External Stimuli ◽  
Expression Time

Cell adaptability to environmental changes is conferred by complex transcriptional regulatory networks, which respond to external stimuli by modulating the expression dynamics of each gene. Hence, deciphering the network of transcriptional regulation is remarkably important, but proves to be extremely challenging, mainly due to the unfavorable ratio between the number of available observations and the number of parameters to estimate. Most of the existing computational methods for the inference of transcriptional networks consider steady-state gene expression datasets, and produce models of transcriptional regulation best explaining the observed static gene expression. Gene expression time-courses are an emergent typology of gene expression data, paving the way to the characterization of the time-dependent dynamics of transcriptional regulation. In this work we introduce the Complexity Invariant Dynamic Time Warping motif EnRichment (CIDER) analysis, a novel computational pipeline to identify the prominent waves of coordinated gene transcription induced in cells by external stimuli, and determine which TFs are involved in the coordination of gene transcription. The CIDER pipeline combines unsupervised time series clustering and motif enrichment analysis to first detect transcriptional expression patterns, and then identify the TFs over-represented in the promoter regions of gene sets with similar expression dynamics. The ability of CIDER to correctly identify regulatory interactions is assessed on a realistic synthetic dataset of gene expression time-courses, generated by simulating the effects of knock-out perturbations on the E. coli regulatory network. The CIDER source code and the validation datasets are available on request from the corresponding author.

scholarly journals Systems Biology Analysis of the Antagonizing Effects of HIV-1 Tat Expression in the Brain over Transcriptional Changes Caused by Methamphetamine Sensitization

Viruses ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 426 ◽  
Author(s):  
Liana V. Basova ◽  
James P. Kesby ◽  
Marcus Kaul ◽  
Svetlana Semenova ◽  
Maria Cecilia Garibaldi Marcondes
Keyword(s):  
Gene Expression ◽  
Systems Biology ◽  
Gene Transcription ◽  
Gene Networks ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Global Gene Expression ◽  
Sirtuin 1 ◽  
The Brain ◽  
Hiv 1

Methamphetamine (Meth) abuse is common among humans with immunodeficiency virus (HIV). The HIV-1 regulatory protein, trans-activator of transcription (Tat), has been described to induce changes in brain gene transcription that can result in impaired reward circuitry, as well as in inflammatory processes. In transgenic mice with doxycycline-induced Tat protein expression in the brain, i.e., a mouse model of neuroHIV, we tested global gene expression patterns induced by Meth sensitization. Meth-induced locomotor sensitization included repeated daily Meth or saline injections for seven days and Meth challenge after a seven-day abstinence period. Brain samples were collected 30 min after the Meth challenge. We investigated global gene expression changes in the caudate putamen, an area with relevance in behavior and HIV pathogenesis, and performed pathway and transcriptional factor usage predictions using systems biology strategies. We found that Tat expression alone had a very limited impact in gene transcription after the Meth challenge. In contrast, Meth-induced sensitization in the absence of Tat induced a global suppression of gene transcription. Interestingly, the interaction between Tat and Meth broadly prevented the Meth-induced global transcriptional suppression, by maintaining regulation pathways, and resulting in gene expression profiles that were more similar to the controls. Pathways associated with mitochondrial health, initiation of transcription and translation, as well as with epigenetic control, were heavily affected by Meth, and by its interaction with Tat in anti-directional ways. A series of systems strategies have predicted several components impacted by these interactions, including mitochondrial pathways, mTOR/RICTOR, AP-1 transcription factor, and eukaryotic initiation factors involved in transcription and translation. In spite of the antagonizing effects of Tat, a few genes identified in relevant gene networks remained downregulated, such as sirtuin 1, and the amyloid precursor protein (APP). In conclusion, Tat expression in the brain had a low acute transcriptional impact but strongly interacted with Meth sensitization, to modify effects in the global transcriptome.

scholarly journals Analyzing Gene Expression Time-Courses

2005 ◽  
Vol 2 (3) ◽  
pp. 179-193 ◽  
Author(s):  
A. Schliep ◽  
I.G. Costa ◽  
C. Steinhoff ◽  
A. Schonhuth
Keyword(s):  
Gene Expression ◽  
Time Courses ◽  
Expression Time

scholarly journals Prognostic Prediction through Biclustering-Based Classification of Clinical Gene Expression Time Series

2011 ◽  
Vol 8 (3) ◽  
pp. 73-89 ◽  
Author(s):  
André V. Carreiro ◽  
Orlando Anunciação ◽  
João A. Carriço ◽  
Sara C. Madeira
Keyword(s):  
Gene Expression ◽  
Time Series ◽  
Expression Patterns ◽  
Classification Problems ◽  
Temporal Perspective ◽  
Temporal Gene Expression ◽  
Gene Expression Time Series ◽  
Prognostic Prediction ◽  
Multiple Sclerosis Patients ◽  
Expression Time

Summary The constant drive towards a more personalized medicine led to an increasing interest in temporal gene expression analyzes. It is now broadly accepted that considering a temporal perspective represents a great advantage to better understand disease progression and treatment results at a molecular level. In this context, biclustering algorithms emerged as an important tool to discover local expression patterns in biomedical applications, and CCC-Biclustering arose as an efficient algorithm relying on the temporal nature of data to identify all maximal temporal patterns in gene expression time series. In this work, CCC-Biclustering was integrated in new biclustering-based classifiers for prognostic prediction. As case study we analyzed multiple gene expression time series in order to classify the response of Multiple Sclerosis patients to the standard treatment with Interferon-β, to which nearly half of the patients reveal a negative response. In this scenario, using an effective predictive model of a patient’s response would avoid useless and possibly harmful therapies for the non-responder group. The results revealed interesting potentialities to be further explored in classification problems involving other (clinical) time series.

scholarly journals Gene expression patterns in synchronized islet populations

2018 ◽  
Author(s):  
Nikita Mukhitov ◽  
Michael G. Roper
Keyword(s):  
Gene Expression ◽  
Environmental Changes ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Protein Translation ◽  
Gene Set Enrichment Analysis ◽  
Gene Expression Patterns ◽  
Insulin Synthesis

AbstractIn vivo levels of insulin are oscillatory with a period of ~5-10 minutes, implying that the numerous islets of Langerhans within the pancreas are synchronized. While the synchronizing factors are still under investigation, one result of this behavior is expected to be coordinated intracellular [Ca2+] ([Ca2+]i) oscillations throughout the islet population. The role that coordinated [Ca2+]i oscillations have on controlling gene expression within pancreatic islets was examined by comparing gene expression levels in islets that were synchronized using a low amplitude glucose wave and an unsynchronized population. The [Ca2+]i oscillations in the synchronized population were homogeneous and had a significantly lower drift in their oscillation period as compared to unsynchronized islets. This reduced drift in the synchronized population was verified by comparing the drift of in vivo and in vitro profiles from published reports. Microarray profiling indicated a number of Ca2+-dependent genes were differentially regulated between the two islet populations. Gene set enrichment analysis revealed that the synchronized population had reduced expression of gene sets related to protein translation, protein turnover, energy expenditure, and insulin synthesis, while those that were related to maintenance of cell morphology were increased. It is speculated that these gene expression patterns in the synchronized islets results in a more efficient utilization of intra-cellular resources and response to environmental changes.

Gene expression investigations on plant-pathogen interactions between Xanthomonas campestris pv. vesicatoria and pepper ( Capsicum annuum L.) using the cDNA-AFLP technology

2009 ◽  
Vol 57 (2) ◽  
pp. 127-136
Author(s):  
E. Szabó ◽  
G. Bárdos ◽  
I. Nagy
Keyword(s):  
Gene Expression ◽  
Capsicum Annuum ◽  
Plant Pathogen ◽  
Xanthomonas Campestris ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Bacterial Pathogen ◽  
Sequence Comparisons ◽  
Time Courses ◽  
Plant Pathogen Interactions

In order to target factors involved in plant-pathogen interactions, gene expression differences were investigated on pepper ( Capsicum annuum L.) plants after artificial infection with the bacterial pathogen Xanthomonas campestris pv. vesicatoria . Amplified Fragment Length Polymorphism investigations on reverse transcribed DNA fragments (cDNA-AFLP) were used to compare the expression profiles of parental lines and of resistant and susceptible individuals from pepper populations segregating for the gds gene, which confers a general defence system in pepper. In total, 73 transcript-derived fragments (TDFs) displaying differential expression patterns could be identified (presence-absence and/or different time courses in resistant and susceptible genotypes). Of these, 67 fragments were cloned and sequenced. In the case of several TDFs, sequence comparisons revealed close homologies to genes known to be responsible for abiotic stress or biotic elicitors, presenting potentially interesting targets for more detailed studies on gene expression and signal transduction.

scholarly journals Dynamic mRNP Remodeling in Response to Internal and External Stimuli

Biomolecules ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1310 ◽  
Author(s):  
Kathi Zarnack ◽  
Sureshkumar Balasubramanian ◽  
Michael P. Gantier ◽  
Vladislav Kunetsky ◽  
Michael Kracht ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signal Transduction ◽  
Rna Binding ◽  
Environmental Changes ◽  
Rna Binding Proteins ◽  
Regulation Of Gene Expression ◽  
Cellular Processes ◽  
Messenger Ribonucleoprotein ◽  
Transcriptional Modulation ◽  
External Stimuli

Signal transduction and the regulation of gene expression are fundamental processes in every cell. RNA-binding proteins (RBPs) play a key role in the post-transcriptional modulation of gene expression in response to both internal and external stimuli. However, how signaling pathways regulate the assembly of RBPs with mRNAs remains largely unknown. Here, we summarize observations showing that the formation and composition of messenger ribonucleoprotein particles (mRNPs) is dynamically remodeled in space and time by specific signaling cascades and the resulting post-translational modifications. The integration of signaling events with gene expression is key to the rapid adaptation of cells to environmental changes and stress. Only a combined approach analyzing the signal transduction pathways and the changes in post-transcriptional gene expression they cause will unravel the mechanisms coordinating these important cellular processes.

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