scholarly journals Time course Analysis of Gene expression patterns in ZebrafIsh Eye during Optic Nerve Regeneration

2010 ◽  
Vol 4 ◽  
pp. JEN.S5006 ◽  
Author(s):  
Amy T. Mccurley ◽  
Gloria V. Callard
Keyword(s):  
Gene Expression ◽  
Optic Nerve ◽  
Nerve Regeneration ◽  
Time Course ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Neural Cells ◽  
Nerve Crush ◽  
Optic Nerve Regeneration

It is well-established that neurons in the adult mammalian central nervous system (CNS) are terminally differentiated and, if injured, will be unable to regenerate their connections. In contrast to mammals, zebrafish and other teleosts display a robust neuroregenerative response. Following optic nerve crush (ONX), retinal ganglion cells (RGC) regrow their axons to synapse with topographically correct targets in the optic tectum, such that vision is restored in ~21 days. What accounts for these differences between teleostean and mammalian responses to neural injury is not fully understood. A time course analysis of global gene expression patterns in the zebrafish eye after ONX can help to elucidate cellular and molecular mechanisms that contribute to a successful neuroregeneration. To define different phases of regeneration after ONX, alpha tubulin 1 ( tuba1) and growth-associated protein 43 ( gap43), markers previously shown to correspond to morphophological events, were measured by real time quantitative PCR (qPCR). Microarray analysis was then performed at defined intervals (6 hours, 1, 4, 12, and 21 days) post-ONX and compared to SHAM. Results show that optic nerve damage induces multiple, phase-related transcriptional programs, with the maximum number of genes changed and highest fold-change occurring at 4 days. Several functional groups affected by optic nerve regeneration, including cell adhesion, apoptosis, cell cycle, energy metabolism, ion channel activity, and calcium signaling, were identified. Utilizing the whole eye allowed us to identify signaling contributions from the vitreous, immune and glial cells as well as the neural cells of the retina. Comparisons between our dataset and transcriptional profiles from other models of regeneration in zebrafish retina, heart and fin revealed a subset of commonly regulated transcripts, indicating shared mechanisms in different regenerating tissues. Knowledge of gene expression patterns in all components of the eye in a model of successful regeneration provides an entry point for functional analyses, and will help in devising hypotheses for testing normal and toxic regulatory factors.

scholarly journals Optic nerve crush induces spatial and temporal gene expression patterns in retina and optic nerve of BALB/cJ mice

2014 ◽  
Vol 9 (1) ◽  
pp. 14 ◽  
Author(s):  
Tasneem P Sharma ◽  
Colleen M McDowell ◽  
Yang Liu ◽  
Alex H Wagner ◽  
David Thole ◽  
...  
Keyword(s):  
Gene Expression ◽  
Optic Nerve ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Optic Nerve Crush ◽  
Nerve Crush ◽  
Temporal Gene Expression

scholarly journals Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

2017 ◽  
Vol 14 (2) ◽  
Author(s):  
Qihua Tan ◽  
Mads Thomassen ◽  
Mark Burton ◽  
Kristian Fredløv Mose ◽  
Klaus Ejner Andersen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Correlation Coefficient ◽  
Parametric Analysis ◽  
Time Course ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Microarray Time Course ◽  
Time Course Data ◽  
Generalized Correlation ◽  
Non Parametric

AbstractModeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

scholarly journals Gene Expression Patterns Underlying the Reinstatement of Plasticity in the Adult Visual System

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Ettore Tiraboschi ◽  
Ramon Guirado ◽  
Dario Greco ◽  
Petri Auvinen ◽  
Jose Fernando Maya-Vetencourt ◽  
...  
Keyword(s):  
Gene Expression ◽  
Visual Cortex ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Monocular Deprivation ◽  
Adult Brain ◽  
Gene Expression Patterns ◽  
Postnatal Life ◽  
Critical Periods

The nervous system is highly sensitive to experience during early postnatal life, but this phase of heightened plasticity decreases with age. Recent studies have demonstrated that developmental-like plasticity can be reactivated in the visual cortex of adult animals through environmental or pharmacological manipulations. These findings provide a unique opportunity to study the cellular and molecular mechanisms of adult plasticity. Here we used the monocular deprivation paradigm to investigate large-scale gene expression patterns underlying the reinstatement of plasticity produced by fluoxetine in the adult rat visual cortex. We found changes, confirmed with RT-PCRs, in gene expression in different biological themes, such as chromatin structure remodelling, transcription factors, molecules involved in synaptic plasticity, extracellular matrix, and excitatory and inhibitory neurotransmission. Our findings reveal a key role for several molecules such as the metalloproteases Mmp2 and Mmp9 or the glycoprotein Reelin and open up new insights into the mechanisms underlying the reopening of the critical periods in the adult brain.

scholarly journals Retinal Genomic Fabrics Remodeling after Optic Nerve Injury

2021 ◽  
Author(s):  
Pedro Henrique Victorino ◽  
Camila Marra ◽  
Dumitru Andrei Iacobas ◽  
Sanda Iacobas ◽  
David C Spray ◽  
...  
Keyword(s):  
Gene Expression ◽  
Optic Nerve ◽  
Notch Signaling ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Notch Signaling Pathway ◽  
Complement Cascade ◽  
Gene Expressions ◽  
Nerve Crush ◽  
Individual Gene

Glaucoma is a multifactorial neurodegenerative disease, characterized by degeneration of the retinal ganglion cells (RGCs). There has been little progress in developing efficient strategies for neuroprotection in glaucoma. We profiled the retina transcriptome of Lister Hooded rats at 2 weeks after optic nerve crush (ONC) and analyzed the data from the Genomic Fabric Paradigm (GFP) to bring additional insights into the molecular mechanisms of the retinal remodeling after induction of RGC degeneration. GFP considers for the expression of each gene 3 independent characteristics: level, variability and correlation with each other gene. Thus, the 17,657 quantified genes our study generated a total of 155,911,310 values to analyze. This represents 8,830x more data per condition than a traditional transcriptomic analysis. ONC led to a 57% reduction in RGC numbers as detected by retrograde labeling with DiI. We observed a higher Relative Expression Variability after ONC. Gene expression stability was used as a measure of transcription control and disclosed a robust reduction in the number of very stably expressed genes. Predicted Protein-Protein interaction (PPI) analysis with STRING revealed axon and neuron projection as mostly decreased processes, consistent with RGC degeneration. Conversely, immune response PPIs were found among up-regulated genes. Enrichment analysis showed that Complement Cascade and Notch Signaling Pathway, as well as Oxidative Stress and Kit Receptor Pathway were affected after ONC. To expand our studies of altered molecular pathways, we examined the pair-wise coordination of gene expressions within each pathway and within the entire transcriptome using Pearson correlations. ONC increased the number of synergistically coordinated pairs of genes and the number of similar profiles mainly in Complement Cascade and Notch Signaling Pathway. This deep bioinformatic study provides novel insights beyond the regulation of individual gene expression and discloses changes in the control of expression of Complement Cascade and Notch Signaling functional pathways that may be relevant for both RGC degeneration and remodeling of the retinal tissue after ONC.

scholarly journals Discovering gene expression patterns in time course microarray experiments by ANOVA–SCA

2007 ◽  
Vol 23 (14) ◽  
pp. 1792-1800 ◽  
Author(s):  
María José Nueda ◽  
Ana Conesa ◽  
Johan A. Westerhuis ◽  
Huub C. J. Hoefsloot ◽  
Age K. Smilde ◽  
...  
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Microarray Experiments

scholarly journals Unraveling the molecular heterogeneity in type 2 diabetes: A potential subtype discovery study followed by metabolic modeling

2020 ◽  
Author(s):  
Maryam Khoshnejat ◽  
Kaveh Kavousi ◽  
Ali Mohammad Banaei-Moghaddam ◽  
Ali Akbar Moosavi-Movahedi
Keyword(s):  
Gene Expression ◽  
Type 2 Diabetes ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Critical Role ◽  
Gene Expression Pattern ◽  
Gene Expression Patterns ◽  
Diabetic Patients ◽  
Molecular Heterogeneity

Abstract BackgroundType 2 diabetes mellitus (T2DM) is a complex multifactorial disease with a high prevalence in the world. Insulin resistance and impaired insulin secretion are the two major abnormalities in the pathogenesis of T2DM. Skeletal muscle is responsible for over 75% of the glucose uptake, thus plays a critical role in T2DM. Here, we attempted to provide a better understanding of abnormalities in this tissue. MethodsThe muscle gene expression patterns in healthy and newly diagnosed T2DM individuals were explored using supervised and unsupervised classification approach. Moreover, the potential of sub-typing T2DM patients based on the gene expression patterns was evaluated.ResultsA machine-learning technique was applied to identify a gene expression pattern that could discriminate between normoglycemic and diabetic groups. A gene set comprises of 26 genes was found that was able to discriminate healthy from diabetic individuals with 94% accuracy. In addition, three distinct clusters of diabetic patients with different dysregulated genes and metabolic pathways were identified. Conclusions This study implies that it seems the disease has triggered through different cellular/molecular mechanisms, and it has the potential to be categorized in different sub-types. Possibly, subtyping of T2DM patients in combination with their real clinical profiles will provide a better understanding of abnormalities in each group. Thus, this approach will help to recommend the appropriate treatment for each subtype in the future.

scholarly journals Unraveling the molecular heterogeneity in type 2 diabetes: A potential subtype discovery followed by metabolic modeling

2020 ◽  
Author(s):  
Maryam Khoshnejat ◽  
Kaveh Kavousi ◽  
Ali Mohammad Banaei-Moghaddam ◽  
Ali Akbar Moosavi-Movahedi
Keyword(s):  
Gene Expression ◽  
Type 2 Diabetes ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Critical Role ◽  
Unsupervised Classification ◽  
Gene Expression Patterns ◽  
Diabetic Patients ◽  
Molecular Heterogeneity

Abstract BackgroundType 2 diabetes mellitus (T2DM) is a complex multifactorial disease with a high prevalence worldwide. Insulin resistance and impaired insulin secretion are the two major abnormalities in the pathogenesis of T2DM. Skeletal muscle is responsible for over 75% of the glucose uptake and plays a critical role in T2DM. Here, we sought to provide a better understanding of the abnormalities in this tissue. MethodsThe muscle gene expression patterns were explored in healthy and newly diagnosed T2DM individuals using supervised and unsupervised classification approaches. Moreover, the potential of subtyping T2DM patients was evaluated based on the gene expression patterns.ResultsA machine-learning technique was applied to identify a set of genes whose expression patterns could discriminate diabetic subjects from healthy ones. A gene set comprising of 26 genes was found that was able to distinguish healthy from diabetic individuals with 94% accuracy. In addition, three distinct clusters of diabetic patients with different dysregulated genes and metabolic pathways were identified. Conclusions This study indicates that T2DM is triggered by different cellular/molecular mechanisms, and it can be categorized into different subtypes. Subtyping of T2DM patients in combination with their real clinical profiles will provide a better understanding of the abnormalities in each group and more effective therapeutic approaches in the future.

Sign in / Sign up

Export Citation Format

Share Document