scholarly journals “System 48” High-Throughput Cloning and Protein Expression Analysis

2009 ◽  
pp. 117-127 ◽  
Author(s):  
James M. Abdullah ◽  
Andrzej Joachimiak ◽  
Frank R. Collart
Keyword(s):  
Protein Expression ◽  
Expression Analysis ◽  
High Throughput

Structural genomics for Caenorhabditis elegans: high throughput protein expression analysis

2004 ◽  
Vol 34 (1) ◽  
pp. 49-55 ◽  
Author(s):  
James B Finley ◽  
Shi-Hong Qiu ◽  
Chi-Hao Luan ◽  
Ming Luo
Keyword(s):  
Caenorhabditis Elegans ◽  
Protein Expression ◽  
Expression Analysis ◽  
High Throughput ◽  
Structural Genomics

scholarly journals High Throughput Screen Identifies the DNMT1 (DNA Methyltransferase-1) Inhibitor, 5-Azacytidine, as a Potent Inducer of PTEN (Phosphatase and Tensin Homolog)

2020 ◽  
Vol 40 (8) ◽  
pp. 1854-1869
Author(s):  
Keith A. Strand ◽  
Sizhao Lu ◽  
Marie F. Mutryn ◽  
Linfeng Li ◽  
Qiong Zhou ◽  
...  
Keyword(s):  
Protein Expression ◽  
High Throughput ◽  
Knockout Mice ◽  
Vascular Remodeling ◽  
Dna Methyltransferase ◽  
Dna Methyltransferase 1 ◽  
Protective Effects ◽  
High Throughput Screen ◽  
Phosphatase And Tensin Homolog ◽  
Tensin Homolog

Objective: Our recent work demonstrates that PTEN (phosphatase and tensin homolog) is an important regulator of smooth muscle cell (SMC) phenotype. SMC-specific PTEN deletion promotes spontaneous vascular remodeling and PTEN loss correlates with increased atherosclerotic lesion severity in human coronary arteries. In mice, PTEN overexpression reduces plaque area and preserves SMC contractile protein expression in atherosclerosis and blunts Ang II (angiotensin II)-induced pathological vascular remodeling, suggesting that pharmacological PTEN upregulation could be a novel therapeutic approach to treat vascular disease. Approach and Results: To identify novel PTEN activators, we conducted a high-throughput screen using a fluorescence based PTEN promoter-reporter assay. After screening ≈3400 compounds, 11 hit compounds were chosen based on level of activity and mechanism of action. Following in vitro confirmation, we focused on 5-azacytidine, a DNMT1 (DNA methyltransferase-1) inhibitor, for further analysis. In addition to PTEN upregulation, 5-azacytidine treatment increased expression of genes associated with a differentiated SMC phenotype. 5-Azacytidine treatment also maintained contractile gene expression and reduced inflammatory cytokine expression after PDGF (platelet-derived growth factor) stimulation, suggesting 5-azacytidine blocks PDGF-induced SMC de-differentiation. However, these protective effects were lost in PTEN-deficient SMCs. These findings were confirmed in vivo using carotid ligation in SMC-specific PTEN knockout mice treated with 5-azacytidine. In wild type controls, 5-azacytidine reduced neointimal formation and inflammation while maintaining contractile protein expression. In contrast, 5-azacytidine was ineffective in PTEN knockout mice, indicating that the protective effects of 5-azacytidine are mediated through SMC PTEN upregulation. Conclusions: Our data indicates 5-azacytidine upregulates PTEN expression in SMCs, promoting maintenance of SMC differentiation and reducing pathological vascular remodeling in a PTEN-dependent manner.

scholarly journals Advancing clinical genomics and precision medicine with GVViZ: FAIR bioinformatics platform for variable gene-disease annotation, visualization, and expression analysis

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Zeeshan Ahmed ◽  
Eduard Gibert Renart ◽  
Saman Zeeshan ◽  
XinQi Dong
Keyword(s):  
Data Analysis ◽  
Patient Care ◽  
Expression Analysis ◽  
High Throughput ◽  
Gene Annotation ◽  
Next Generation Sequencing Data ◽  
Rna Seq ◽  
Sequencing Data ◽  
Complex Disorders ◽  
Transcriptomics Data

Abstract Background Genetic disposition is considered critical for identifying subjects at high risk for disease development. Investigating disease-causing and high and low expressed genes can support finding the root causes of uncertainties in patient care. However, independent and timely high-throughput next-generation sequencing data analysis is still a challenge for non-computational biologists and geneticists. Results In this manuscript, we present a findable, accessible, interactive, and reusable (FAIR) bioinformatics platform, i.e., GVViZ (visualizing genes with disease-causing variants). GVViZ is a user-friendly, cross-platform, and database application for RNA-seq-driven variable and complex gene-disease data annotation and expression analysis with a dynamic heat map visualization. GVViZ has the potential to find patterns across millions of features and extract actionable information, which can support the early detection of complex disorders and the development of new therapies for personalized patient care. The execution of GVViZ is based on a set of simple instructions that users without a computational background can follow to design and perform customized data analysis. It can assimilate patients’ transcriptomics data with the public, proprietary, and our in-house developed gene-disease databases to query, easily explore, and access information on gene annotation and classified disease phenotypes with greater visibility and customization. To test its performance and understand the clinical and scientific impact of GVViZ, we present GVViZ analysis for different chronic diseases and conditions, including Alzheimer’s disease, arthritis, asthma, diabetes mellitus, heart failure, hypertension, obesity, osteoporosis, and multiple cancer disorders. The results are visualized using GVViZ and can be exported as image (PNF/TIFF) and text (CSV) files that include gene names, Ensembl (ENSG) IDs, quantified abundances, expressed transcript lengths, and annotated oncology and non-oncology diseases. Conclusions We emphasize that automated and interactive visualization should be an indispensable component of modern RNA-seq analysis, which is currently not the case. However, experts in clinics and researchers in life sciences can use GVViZ to visualize and interpret the transcriptomics data, making it a powerful tool to study the dynamics of gene expression and regulation. Furthermore, with successful deployment in clinical settings, GVViZ has the potential to enable high-throughput correlations between patient diagnoses based on clinical and transcriptomics data.

MicroRNA expression analysis of rosette and folding leaves in Chinese cabbage using high-throughput Solexa sequencing

Gene ◽  
2013 ◽  
Vol 532 (2) ◽  
pp. 222-229 ◽  
Author(s):  
Fengde Wang ◽  
Huayin Li ◽  
Yihui Zhang ◽  
Jingjuan Li ◽  
Libin Li ◽  
...  
Keyword(s):  
Expression Analysis ◽  
High Throughput ◽  
Chinese Cabbage ◽  
Solexa Sequencing ◽  
Microrna Expression
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