High-Throughput Approaches for miRNA Expression Analysis

2009 ◽  
pp. 107-125 ◽  
Author(s):  
Cheng Lu ◽  
Frédéric Souret
Keyword(s):  
Expression Analysis ◽  
High Throughput ◽  
Mirna Expression

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.

Evaluation of reference genes for miRNA expression analysis in Galeruca daurica (Coleoptera: Chrysomelidae) using qRT‐PCR

2021 ◽  
Author(s):  
Hai‐Chao Wang ◽  
Ling Li ◽  
Yan‐Yan Li ◽  
Yao Tan ◽  
Bao‐Ping Pang
Keyword(s):  
Expression Analysis ◽  
Mirna Expression ◽  
Reference Genes ◽  
Qrt Pcr

scholarly journals Optimizing a Massive Parallel Sequencing Workflow for Quantitative miRNA Expression Analysis

PLoS ONE ◽  
2012 ◽  
Vol 7 (2) ◽  
pp. e31630 ◽  
Author(s):  
Francesca Cordero ◽  
Marco Beccuti ◽  
Maddalena Arigoni ◽  
Susanna Donatelli ◽  
Raffaele A. Calogero
Keyword(s):  
Expression Analysis ◽  
Mirna Expression ◽  
Massive Parallel Sequencing ◽  
Parallel Sequencing

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

MiRNA expression analysis during normal zebrafish development and following inhibition of the Hedgehog and Notch signaling pathways

2007 ◽  
Vol 236 (8) ◽  
pp. 2172-2180 ◽  
Author(s):  
Elizabeth J. Thatcher ◽  
Alex S. Flynt ◽  
Nan Li ◽  
Jonathan R. Patton ◽  
James G. Patton
Keyword(s):  
Notch Signaling ◽  
Signaling Pathways ◽  
Expression Analysis ◽  
Mirna Expression ◽  
Zebrafish Development

scholarly journals miRNA-mRNA integrative analysis in primary myelofibrosis CD34+ cells: role of miR-155/JARID2 axis in abnormal megakaryopoiesis

Blood ◽  
2014 ◽  
Vol 124 (13) ◽  
pp. e21-e32 ◽  
Author(s):  
Ruggiero Norfo ◽  
Roberta Zini ◽  
Valentina Pennucci ◽  
Elisa Bianchi ◽  
Simona Salati ◽  
...  
Keyword(s):  
Expression Analysis ◽  
Mirna Expression ◽  
Therapeutic Targets ◽  
Primary Myelofibrosis ◽  
Integrative Analysis ◽  
Cd34 Cells ◽  
Key Points ◽  
Differential Gene ◽  
New Biomarkers

Key Points Differential gene and miRNA expression analysis in PMF granulocytes identifies new biomarkers and putative therapeutic targets. Activation of the miR-155/JARID2 axis in PMF CD34+ cells results in overproduction of MK precursors.

scholarly journals miRNA expression analysis in AD human brain

2018 ◽  
Author(s):  
Perla Zambrano Prado ◽  
Dolores J. Siedlecki Wullich ◽  
Alfredo Jes�s Mi�ano Molina ◽  
Jos� Rodr�guez �lvarez
Keyword(s):  
Human Brain ◽  
Expression Analysis ◽  
Mirna Expression

scholarly journals Bioinformatics in otolaryngology research. Part one: concepts in DNA sequencing and gene expression analysis

2014 ◽  
Vol 128 (10) ◽  
pp. 848-858 ◽  
Author(s):  
T J Ow ◽  
K Upadhyay ◽  
T J Belbin ◽  
M B Prystowsky ◽  
H Ostrer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Storage ◽  
Expression Analysis ◽  
High Throughput ◽  
Gene Expression Analysis ◽  
Biological Data ◽  
Biological Research ◽  
Nucleotide Sequencing ◽  
New Era ◽  
Crucial Component

AbstractBackground:Advances in high-throughput molecular biology, genomics and epigenetics, coupled with exponential increases in computing power and data storage, have led to a new era in biological research and information. Bioinformatics, the discipline devoted to storing, analysing and interpreting large volumes of biological data, has become a crucial component of modern biomedical research. Research in otolaryngology has evolved along with these advances.Objectives:This review highlights several modern high-throughput research methods, and focuses on the bioinformatics principles necessary to carry out such studies. Several examples from recent literature pertinent to otolaryngology are provided. The review is divided into two parts; this first part discusses the bioinformatics approaches applied in nucleotide sequencing and gene expression analysis.Conclusion:This paper demonstrates how high-throughput nucleotide sequencing and transcriptomics are changing biology and medicine, and describes how these changes are affecting otorhinolaryngology. Sound bioinformatics approaches are required to obtain useful information from the vast new sources of data.

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