scholarly journals Next-Generation Sequencing for Binary Protein–Protein Interactions

2015 ◽  
Vol 6 ◽  
Author(s):  
Bernhard Suter ◽  
Xinmin Zhang ◽  
C. Gustavo Pesce ◽  
Andrew R. Mendelsohn ◽  
Savithramma P. Dinesh-Kumar ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Protein Interactions ◽  
Next Generation ◽  
Protein Protein Interactions ◽  
Generation Sequencing

scholarly journals Gene Expression Changes Associated with Nintedanib Treatment in Idiopathic Pulmonary Fibrosis Fibroblasts: A Next-Generation Sequencing and Bioinformatics Study

2019 ◽  
Vol 8 (3) ◽  
pp. 308 ◽  
Author(s):  
Chau-Chyun Sheu ◽  
Wei-An Chang ◽  
Ming-Ju Tsai ◽  
Ssu-Hui Liao ◽  
Inn-Wen Chong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Next Generation Sequencing ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Protein Interactions ◽  
Next Generation ◽  
Protein Protein Interactions ◽  
Bioinformatics Study ◽  
Generation Sequencing

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and fatal interstitial lung disease. Therapeutic options for IPF remain limited. Nintedanib, a tyrosine kinase inhibitor approved for IPF treatment, is known to inhibit fibroblasts proliferation, migration and transformation to myofibroblasts. However, how nintedanib changes gene regulations in IPF has never been systematically investigated. We conducted a next-generation sequencing and bioinformatics study to evaluate the changes of mRNA and miRNA profiles in IPF fibroblasts treated with 2 µM and 4 µM nintedanib, compared to those without treatment. We identified 157 upregulated and 151 downregulated genes and used STRING and DAVID databases for analysis of protein–protein interactions, biological pathways, and molecular functions. We found strong protein–protein interactions within these dysregulated genes, mostly involved in the pathways of cell cycle and mitotic cell cycle. We also discovered 13 potential miRNA–mRNA interactions associated with nintedanib treatment. After validation using miRDB, TargetScan, and RT-qPCR, we identified 4 downregulated genes (DDX11, E2F1, NPTX1, and PLXNA4) which might be repressed by the upregulated hsa-miR-486-3p. According to the proposed functions of DDX11, E2F1, and PLXNA4 reported in previous studies, these gene expression changes together might contribute to decreased proliferation of fibroblasts and decreased angiogenesis in the microenvironment of IPF. Our findings need further studies to confirm.

scholarly journals Next-Generation Sequencing Techniques for Eukaryotic Microorganisms: Sequencing-Based Solutions to Biological Problems

2010 ◽  
Vol 9 (9) ◽  
pp. 1300-1310 ◽  
Author(s):  
Minou Nowrousian
Keyword(s):  
Next Generation Sequencing ◽  
Protein Interactions ◽  
Large Scale ◽  
De Novo ◽  
Nucleotide Polymorphisms ◽  
Next Generation ◽  
Sequencing Data ◽  
Bioinformatics Analyses ◽  
Eukaryotic Microorganisms ◽  
Generation Sequencing

ABSTRACT Over the past 5 years, large-scale sequencing has been revolutionized by the development of several so-called next-generation sequencing (NGS) technologies. These have drastically increased the number of bases obtained per sequencing run while at the same time decreasing the costs per base. Compared to Sanger sequencing, NGS technologies yield shorter read lengths; however, despite this drawback, they have greatly facilitated genome sequencing, first for prokaryotic genomes and within the last year also for eukaryotic ones. This advance was possible due to a concomitant development of software that allows the de novo assembly of draft genomes from large numbers of short reads. In addition, NGS can be used for metagenomics studies as well as for the detection of sequence variations within individual genomes, e.g., single-nucleotide polymorphisms (SNPs), insertions/deletions (indels), or structural variants. Furthermore, NGS technologies have quickly been adopted for other high-throughput studies that were previously performed mostly by hybridization-based methods like microarrays. This includes the use of NGS for transcriptomics (RNA-seq) or the genome-wide analysis of DNA/protein interactions (ChIP-seq). This review provides an overview of NGS technologies that are currently available and the bioinformatics analyses that are necessary to obtain information from the flood of sequencing data as well as applications of NGS to address biological questions in eukaryotic microorganisms.

scholarly journals Aging, Bone Marrow and Next-Generation Sequencing (NGS): Recent Advances and Future Perspectives

2021 ◽  
Vol 22 (22) ◽  
pp. 12225
Author(s):  
Payal Ganguly ◽  
Bradley Toghill ◽  
Shelly Pathak
Keyword(s):  
Bone Marrow ◽  
Next Generation Sequencing ◽  
Protein Interactions ◽  
Genetic Alterations ◽  
Low Grade ◽  
Next Generation ◽  
High Throughput Analysis ◽  
Age Related ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

The aging of bone marrow (BM) remains a very imperative and alluring subject, with an ever-increasing interest among fellow scientists. A considerable amount of progress has been made in this field with the established ‘hallmarks of aging’ and continued efforts to investigate the age-related changes observed within the BM. Inflammaging is considered as a low-grade state of inflammation associated with aging, and whilst the possible mechanisms by which aging occurs are now largely understood, the processes leading to the underlying changes within aged BM remain elusive. The ability to identify these changes and detect such alterations at the genetic level are key to broadening the knowledgebase of aging BM. Next-generation sequencing (NGS) is an important molecular-level application presenting the ability to not only determine genomic base changes but provide transcriptional profiling (RNA-seq), as well as a high-throughput analysis of DNA–protein interactions (ChIP-seq). Utilising NGS to explore the genetic alterations occurring over the aging process within alterative cell types facilitates the comprehension of the molecular and cellular changes influencing the dynamics of aging BM. Thus, this review prospects the current landscape of BM aging and explores how NGS technology is currently being applied within this ever-expanding field of research.

Labordiagnostik bei gastrointestinalen Tumoren

2020 ◽  
Vol 11 (05) ◽  
pp. 232-238
Author(s):  
Marcus Kleber
Keyword(s):  
Next Generation Sequencing ◽  
Kolorektales Karzinom ◽  
Next Generation ◽  
Generation Sequencing

ZUSAMMENFASSUNGDas kolorektale Karzinom (KRK) ist einer der häufigsten malignen Tumoren in Deutschland. Einer frühzeitigen Diagnostik kommt große Bedeutung zu. Goldstandard ist hier die Koloskopie. Die aktuelle S3-Leitlinie Kolorektales Karzinom empfiehlt zum KRK-Screening den fäkalen okkulten Bluttest. Für das Monitoring von Patienten vor und nach Tumorresektion werden die Messung des Carcinoembryonalen Antigens (CEA) und der Mikrosatellitenstabilität empfohlen. Für die Auswahl der korrekten Chemotherapie scheint derzeit eine Überprüfung des Mutationsstatus, mindestens des KRAS-Gens und des BRAF-Gens, sinnvoll zu sein. Eine Reihe an neuartigen Tumormarkern befindet sich momentan in der Entwicklung, hat jedoch noch nicht die Reife für eine mögliche Anwendung in der Routinediagnostik erreicht. Den schnellsten Weg in die breite Anwendung können Next-Generation-Sequencing-basierte genetische Tests finden.

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