scholarly journals Effect of Bortezomib on Global Gene Expression in PC12-Derived Nerve Cells

2020 ◽  
Vol 21 (3) ◽  
pp. 751 ◽  
Author(s):  
Karolina Łuczkowska ◽  
Dorota Rogińska ◽  
Zofia Ulańczyk ◽  
Bogusław Machaliński
Keyword(s):  
Gene Expression ◽  
Mirna Expression ◽  
Global Gene Expression ◽  
Nerve Cells ◽  
Microarray Expression Data ◽  
Neurotransmitter Secretion ◽  
Dna Replication And Repair ◽  
Gene Correlation ◽  
Regulation Of Cell Cycle ◽  
Microarray Expression

Peripheral neuropathy is one of the main side-effects of novel therapeutics used in oncohematological diseases, but the molecular basis underlying its development and progression as well as neurotoxicity mechanisms induced by the use of these therapeutics are still not fully elucidated. The aim of this study was to demonstrate the effect of bortezomib on global gene and miRNA expression on PC12-derived nerve cells. Microarray analysis showed that expression of 1383 genes was downregulated at least two fold and 671 genes were upregulated at least two fold in PC12-derived nerve cells treated with bortezomib compared to untreated/control cells. Analysis of functional annotations mainly identified downregulated processes (e.g., regulation of cell cycle, DNA replication and repair, regulation of cell migration, neuron projection morphogenesis and neurotransmitter secretion). The result of miRNA expression analysis demonstrated only 11 significantly downregulated miRNAs (at least two fold) in bortezomib-treated PC12-derived nerve cells vs. control cells. MiRNAs regulate gene expression, therefore we decided to conduct an analysis comparing the outcomes of miRNA microarray expression data to the obtained mRNA data. The most interesting miRNA–target gene correlation is downregulated expression of miR-130a-3p and miR-152-3p and as a result of this downregulation the expression of the Gadd45 increased. This gene is a member of a group of genes, the transcript expression of which is enhanced after stressful growth arrest conditions and treatment with DNA-damaging agents like drugs or mutagens.

scholarly journals Impact of gene annotation choice on the quantification of RNA-seq data

2021 ◽  
Author(s):  
David Chisanga ◽  
Yang Liao ◽  
Wei Shi
Keyword(s):  
Gene Expression ◽  
Gene Annotation ◽  
Expression Data ◽  
Rna Seq ◽  
Microarray Expression Data ◽  
Refseq Annotation ◽  
Sequencing Quality ◽  
Gene Expression Quantification ◽  
Microarray Expression ◽  
Expression Quantification

RNA sequencing is currently the method of choice for genome-wide profiling of gene expression. A popular approach to quantify expression levels of genes from RNA-seq data is to map reads to a reference genome and then count mapped reads to each gene. Gene annotation data, which include chromosomal coordinates of exons for tens of thousands of genes, are required for this quantification process. There are several major sources of gene annotations that can be used for quantification, such as Ensembl and RefSeq databases. However, there is very little understanding of the effect that the choice of annotation has on the accuracy of gene expression quantification in an RNA-seq analysis. In this paper, we present results from our comparison of Ensembl and RefSeq human annotations on their impact on gene expression quantification using a benchmark RNA-seq dataset generated by the SEquencing Quality Control (SEQC) consortium. We show that the use of RefSeq gene annotation models led to better quantification accuracy, based on the correlation with ground truths including expression data from $>$800 real-time PCR validated genes, known titration ratios of gene expression and microarray expression data. We also found that the recent expansion of the RefSeq annotation has led to a decrease in its annotation accuracy. Finally, we demonstrated that the RNA-seq quantification differences observed between different annotations were not affected by the use of different normalization methods.

scholarly journals Checkpoint activation drives global gene expression changes in Drosophila nuclear lamina mutants

2021 ◽  
Author(s):  
S Cole Kitzman ◽  
Tingting Duan ◽  
Miles A Pufall ◽  
Pamela K Geyer
Keyword(s):  
Gene Expression ◽  
Nuclear Lamina ◽  
Global Gene Expression ◽  
Regulation Of Transcription ◽  
Germline Stem Cells ◽  
General Role ◽  
Lamin B ◽  
Expression Of Genes ◽  
Dna Replication And Repair ◽  
Protein Barrier

Abstract The nuclear lamina (NL) lines the inner nuclear membrane. This extensive protein network organizes chromatin and contributes to the regulation of transcription, DNA replication and repair. Lap2-emerin-MAN1 domain (LEM-D) proteins are key members of the NL, representing proteins that connect the NL to the genome through shared interactions with the chromatin binding protein Barrier-to-autointegration factor (BAF). Functions of the LEM-D protein emerin and BAF are essential during Drosophila melanogaster oogenesis. Indeed, loss of either emerin or BAF blocks germ cell development and causes loss of germline stem cells, defects linked to deformation of NL structure and non-canonical activation of Checkpoint kinase 2 (Chk2). Here, we investigate contributions of emerin and BAF to gene expression in the ovary. Profiling RNAs from emerin and baf mutant ovaries revealed that nearly all baf mis-regulated genes were shared with emerin mutants, defining a set of NL-regulated genes. Strikingly, loss of Chk2 restored expression of most NL-regulated genes, identifying a large class of Chk2-dependent genes (CDGs). Nonetheless, some genes remained mis-expressed upon Chk2 loss, identifying a smaller class of emerin-dependent genes (EDGs). Properties of EDGs suggest a shared role for emerin and BAF in repression of developmental genes. Properties of CDGs demonstrate that Chk2 activation drives global mis-expression of genes in the emerin and baf mutant backgrounds. Notably, CDGs were found up-regulated in lamin-B mutant backgrounds. These observations predict that Chk2 activation might have a general role in gene expression changes found in NL-associated diseases, such as laminopathies.

scholarly journals ETMM-07. HYPOXIC REGULATION OF METABOLIC AND STRUCTURAL GENES IN T98 GLIOBLASTOMA MULTIFORME CELLS BY RNA SEQUENCING

2021 ◽  
Vol 3 (Supplement_1) ◽  
pp. i15-i15
Author(s):  
Brian E White ◽  
Edward Liu ◽  
Hakon Hakonarson ◽  
Russell J Buono
Keyword(s):  
Gene Expression ◽  
Glioblastoma Multiforme ◽  
Rna Sequencing ◽  
Therapeutic Potential ◽  
Global Gene Expression ◽  
Total Rna ◽  
Kegg Pathways ◽  
Unfolded Protein ◽  
Dna Replication And Repair ◽  
Significant Enrichment

Abstract Glioblastoma multiforme (GBM) is the most common primary brain cancer and carries a very poor prognosis. The GBM tumor microenvironment is characterized by regions of profound hypoxia, which are associated with a variety of alterations in gene expression that confer survival, proliferation, and resistance to therapy. Multiple mechanisms have been implicated in hypoxia-associated GBM behavior including upregulation of pathways involved in angiogenesis, immunosuppression, and glucose metabolism. Our study aimed to identify changes in gene expression induced by hypoxia among T98G cells via total RNA sequencing. Human T98 GBM cell lines were cultured in a humidified incubator at 37° C and 5% CO2 and were grown in normoxia (21% O2) or hypoxia (95% N2, 5% C02) for 72 hours. Total RNA was harvested, and global gene expression was evaluated via total RNA sequencing. Standard bioinformatics analysis was performed to identify changes in expression associated with hypoxia. Hypoxia in T98 cells led to significant upregulation of genes implicated in canonical glycolysis, focal adhesion, extracellular matrix reorganization, and endoplasmic reticulum-associated protein processing. We document 690 genes and 11 associated KEGG pathways that demonstrated significant enrichment (p ≤0.01 with Bonferroni, Benjamini, and False Discovery Rate corrections) induced by hypoxia. Notably, upregulation of the IRE1-mediated unfolded protein response was observed. DrugBank database analysis identified four molecules targeting genes upregulated in hypoxic T98G cells: tenecteplase (p = 0.013, 5 gene targets), succinic acid (p = 0.02, 7 targets), artenimol (p = 0.013, 13 targets), and copper (p = 0.0015, 22 targets). We document 733 genes and 6 associated KEGG pathways significantly downregulated (p ≤0.01) in hypoxia, including genes associated with DNA replication and repair, mitotic processes, and spliceosome function. Total RNA sequencing showed hypoxic upregulation of genes involved in various pathways associated with neoplastic GBM behavior and identified multiple candidate molecules which may hold therapeutic potential.

scholarly journals Data-Driven Analysis of Age, Sex, and Tissue Effects on Gene Expression Variability in Alzheimer’s Disease

2018 ◽  
Author(s):  
Lavida R.K. Brooks ◽  
George I. Mias
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Meta Analysis ◽  
Tissue Type ◽  
Healthy Controls ◽  
Expression Data ◽  
Mitochondrial Translation ◽  
Microarray Expression Data ◽  
Microarray Expression

ABSTRACTAlzheimer’s disease (AD) has been categorized by the Centers for Disease Control and Prevention (CDC) as the 6thleading cause of death in the United States. AD is a significant health-care burden because of its increased occurrence (specifically in the elderly population) and the lack of effective treatments and preventive methods. With an increase in life expectancy, the CDC expects AD cases to rise to 15 million by 2060. Aging has been previously associated with susceptibility to AD, and there are ongoing efforts to effectively differentiate between normal and AD age-related brain degeneration and memory loss. AD targets neuronal function and can cause neuronal loss due to the buildup of amyloid-beta plaques and intracellular neurofibrillary tangles.Our study aims to identify temporal changes within gene expression profiles of healthy controls and AD subjects. We conducted a meta-analysis using publicly available microarray expression data from AD and healthy cohorts. For our meta-analysis, we selected datasets that reported donor age and gender, and used Affymetrix and Illumina microarray platforms (8 datasets, 2,088 samples). Raw microarray expression data were re-analyzed, and normalized across arrays. We then performed an analysis of variance, using a linear model that incorporated age, tissue type, sex, and disease state as effects, as well as study to account for batch effects, and including binary interaction between factors. Our results identified 3,735 statistically significant (Bonferroni adjusted p<0.05) gene expression differences between AD and healthy controls, which we filtered for biological effect (10% two-tailed quantiles of mean differences between groups) to obtain 352 genes. Interesting pathways identified as enriched comprised of neurodegenerative diseases pathways (including AD), and also mitochondrial translation and dysfunction, synaptic vesicle cycle and GABAergic synapse, and gene ontology terms enrichment in neuronal system, transmission across chemical synapses and mitochondrial translation.Overall our approach allowed us to effectively combine multiple available microarray datasets and identify gene expression differences between AD and healthy individuals including full age and tissue type considerations. Our findings provide potential gene and pathway associations that can be targeted to improve AD diagnostics and potentially treatment or prevention. (US).

scholarly journals Error Distribution for Gene Expression Data

2005 ◽  
Vol 4 (1) ◽  
Author(s):  
Elizabeth Purdom ◽  
Susan P Holmes
Keyword(s):  
Gene Expression ◽  
Pareto Distribution ◽  
Parametric Bootstrap ◽  
Error Distribution ◽  
Second Law ◽  
Expression Data ◽  
Microarray Experiments ◽  
Microarray Expression Data ◽  
Microarray Expression ◽  
Better Than

We present a new instance of Laplace's second Law of Errors and show how it can be used in the analysis of data from microarray experiments. This error distribution is shown to fit microarray expression data much better than a normal distribution. The use of this distribution in a parametric bootstrap leads to more powerful tests as we show that the t-test is conservative in this setting. We propose a biological explanations for this distribution based on the Pareto distribution of the variables used to compute the log ratios.

Transcriptional profiling of iPSC-derived neurons with reciprocal monogenic CNV in 3p26.3 region

2020 ◽  
pp. 10-11
Author(s):  
М.Е. Лопаткина ◽  
В.С. Фишман ◽  
М.М. Гридина ◽  
Н.А. Скрябин ◽  
Т.В. Никитина ◽  
...  
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
System Development ◽  
Transcriptional Profiling ◽  
Global Gene Expression ◽  
Nervous System Development ◽  
Number Variation ◽  
The Central Nervous System ◽  
Cntn6 Gene ◽  
Copy Number Changes

Проведен анализ генной экспрессии в нейронах, дифференцированных из индуцированных плюрипотентных стволовых клеток пациентов с идиопатическими интеллектуальными нарушениями и реципрокными хромосомными мутациями в регионе 3p26.3, затрагивающими единственный ген CNTN6. Для нейронов с различным типом хромосомных аберраций была показана глобальная дисрегуляция генной экспрессии. В нейронах с вариациями числа копий гена CNTN6 была снижена экспрессия генов, продукты которых вовлечены в процессы развития центральной нервной системы. The gene expression analysis of iPSC-derived neurons, obtained from patients with idiopathic intellectual disability and reciprocal microdeletion and microduplication in 3p26.3 region affecting the single CNTN6 gene was performed. The global gene expression dysregulation was demonstrated for cells with CNTN6 copy number variation. Gene expression in neurons with CNTN6 copy number changes was downregulated for genes, whose products are involved in the central nervous system development.

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