The Next Generation Sequencing Techniques and Application in Drug Discovery and Development

2019 ◽  
pp. 240-259
Author(s):  
Afzal Hussain
Keyword(s):  
Next Generation Sequencing ◽  
Rna Sequencing ◽  
Expression Profiling ◽  
Massively Parallel Sequencing ◽  
Life Sciences ◽  
Rna Seq ◽  
Next Generation ◽  
Parallel Sequencing ◽  
Short Period ◽  
Generation Sequencing

Next-generation sequencing or massively parallel sequencing describe DNA sequencing, RNA sequencing, or methylation sequencing, which shows its great impact on the life sciences. The recent advances of these parallel sequencing for the generation of huge amounts of data in a very short period of time as well as reducing the computing cost for the same. It plays a major role in the gene expression profiling, chromosome counting, finding out the epigenetic changes, and enabling the future of personalized medicine. Here the authors describe the NGS technologies and its application as well as applying different tools such as TopHat, Bowtie, Cufflinks, Cuffmerge, Cuffdiff for analyzing the high throughput RNA sequencing (RNA-Seq) data.

scholarly journals Genetic approaches to study plant responses to environmental stresses

2018 ◽  
Author(s):  
Khaled Moustafa ◽  
Joanna M. Cross
Keyword(s):  
Gene Expression ◽  
Next Generation Sequencing ◽  
Systems Biology ◽  
Massively Parallel Sequencing ◽  
Environmental Stresses ◽  
Plant Responses ◽  
Rna Seq ◽  
Next Generation ◽  
Rnase Protection ◽  
Generation Sequencing

The assessment of gene expression levels is an important step toward elucidating gene functions temporally and spatially. Decades ago, typical studies were focusing on a few genes individually, whereas now researchers are able to examine whole genomes at once. The upgrade of throughput levels aided the introduction of systems biology approaches whereby cell functional networks can be scrutinized in their entireties to unravel potential functional interacting components. The birth of systems biology goes hand-in-hand with huge technological advancements and enables a fairly rapid detection of all transcripts in studied biological samples. Even so, earlier technologies that were restricted to probing single genes or a subset of genes still have their place in research laboratories. The objective here is to highlight key approaches used in gene expression analysis in plant responses to environmental stresses, or, more generally, any other condition of interest. Northern blots, RNase protection assays, and qPCR are described for their targeted detection of one or a few transcripts at a once. Differential display and serial analysis of gene expression represent non-targeted methods to evaluate expression changes of a significant number of gene transcripts. Finally, microarrays and RNA-seq (next-generation sequencing) contribute to the ultimate goal of identifying and quantifying all transcripts in a cell under conditions or stages of study. Recent examples of applications as well as principles, advantages, and drawbacks of each method are contrasted. We also suggest replacing the term "Next-Generation Sequencing (NGS)" with another less confusing synonym such as "RNA-seq", "high throughput sequencing", or "massively parallel sequencing" to avoid confusion with any future sequencing technologies.

scholarly journals Genetic approaches to study plant responses to environmental stresses

2018 ◽  
Author(s):  
Khaled Moustafa
Keyword(s):  
Gene Expression ◽  
Next Generation Sequencing ◽  
Systems Biology ◽  
Massively Parallel Sequencing ◽  
Environmental Stresses ◽  
Plant Responses ◽  
Rna Seq ◽  
Next Generation ◽  
Rnase Protection ◽  
Generation Sequencing

The assessment of gene expression levels is an important step toward elucidating gene functions temporally and spatially. Decades ago, typical studies were focusing on a few genes individually, whereas now researchers are able to examine whole genomes at once. The upgrade of throughput levels aided the introduction of systems biology approaches whereby cell functional networks can be scrutinized in their entireties to unravel potential functional interacting components. The birth of systems biology goes hand-in-hand with huge technological advancements and enables a fairly rapid detection of all transcripts in studied biological samples. Even so, earlier technologies that were restricted to probing single genes or a subset of genes still have their place in research laboratories. The objective here is to highlight key approaches used in gene expression analysis in plant responses to environmental stresses, or, more generally, any other condition of interest. Northern blots, RNase protection assays, and qPCR are described for their targeted detection of one or a few transcripts at a once. Differential display and serial analysis of gene expression represent non-targeted methods to evaluate expression changes of a significant number of gene transcripts. Finally, microarrays and RNA-seq (next-generation sequencing) contribute to the ultimate goal of identifying and quantifying all transcripts in a cell under conditions or stages of study. Recent examples of applications as well as principles, advantages, and drawbacks of each method are contrasted. We also suggest replacing the term "Next-Generation Sequencing (NGS)" with another less confusing synonym such as "RNA-seq", "high throughput sequencing", or "massively parallel sequencing" to avoid confusion with any future sequencing technologies.

scholarly journals The Impact of Next Generation Sequencing in Cancer Research

Cancers ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2928
Author(s):  
Katia Nones ◽  
Ann-Marie Patch
Keyword(s):  
Cancer Research ◽  
Next Generation Sequencing ◽  
Massively Parallel Sequencing ◽  
Massively Parallel ◽  
Next Generation ◽  
Parallel Sequencing ◽  
Next Generation Sequencing Ngs ◽  
The Impact ◽  
Generation Sequencing ◽  
Technical Revolution

Next generation sequencing (NGS) describes the technical revolution that enabled massively parallel sequencing of fragmented nucleic acids, thus making possible our current genomic understanding of cancers [...]

High concordance for MammaPrint 70 genes by RNA next generation sequencing.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 3065-3065
Author(s):  
Lorenza Mittempergher ◽  
Iris de Rink ◽  
Marja Nieuwland ◽  
Ron M Kerkhoven ◽  
Annuska Glas ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Rna Sequencing ◽  
Pearson Correlation ◽  
Microarray Gene Expression Data ◽  
Good Prognosis ◽  
Rna Seq ◽  
Next Generation ◽  
Illumina Hiseq ◽  
Microarray Gene Expression ◽  
Generation Sequencing

3065 Background: The development of new biomarkers often requires fresh frozen (FF) samples. Recently we showed that microarray gene expression data generated from FFPE material are comparable to data extracted from the FF counterpart, including known signatures such as the 70-gene prognosis signature (Mittempergher L et al., 2011). As described by Luo et al (2010) RNA profiling using next generation sequencing (RNA-Seq) is now applicable to archival FFPE specimens. Methods: Technical performance and the comparison between the RNA-Seq 70-gene read-out and the MammaPrint test (Glas et al., 2006) is evaluated in a series of 15 patients (11/15 with matched FFPE/FF material). RNA-Seq was carried out using minor adjustments of the Illumina TruSeq RNA preparation method. RNA sequencing libraries were prepared starting from 100ng of total RNA. Next, the DSN (Duplex-Specific Nuclease) normalization process was used to remove ribosomal RNA and other abundant transcripts (Luo et al, 2010). The libraries were paired-end sequenced on the Illumina HiSeq 2000 instrument with multiplexing of 4 libraries per lane. The resulting sequences were mapped to the human reference genome (build 37) using TopHat 1.3.1(Trapnell et al., 2009). The HTSeq-count tool was used to generate the total number of uniquely mapped reads for each gene. Results: Between 14% and 45% of the total number of reads were assigned to protein-coding genes. The minimum coverage per 1000bp of CDS was 38 reads. The 70 MammaPrint genes were successfully mapped to the RNA-Seq transcripts. We calculated the Pearson correlation coefficient between the centroids of the original good prognosis template (van’t Veer et al., 2002) and the 70-gene read count determined by RNA-Seq of each sample. Predictions based on the 70-gene RNA-Seq data showed a high agreement with the actual MammaPrint test predictions (>90%), irrespective of whether the RNA-seq was performed on FF or FFPE tissue. Conclusions: New generation RNA-sequencing is a feasible technology to assess diagnostic signatures.

scholarly journals RNA-Seq Atlas—a reference database for gene expression profiling in normal tissue by next-generation sequencing

2012 ◽  
Vol 28 (8) ◽  
pp. 1184-1185 ◽  
Author(s):  
Markus Krupp ◽  
Jens U. Marquardt ◽  
Ugur Sahin ◽  
Peter R. Galle ◽  
John Castle ◽  
...  
Keyword(s):  
Gene Expression ◽  
Next Generation Sequencing ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Normal Tissue ◽  
Reference Database ◽  
Rna Seq ◽  
Next Generation ◽  
Generation Sequencing

Next-Generation Sequencing: An Emerging Tool for Drug Designing

2019 ◽  
Vol 25 (31) ◽  
pp. 3350-3357 ◽  
Author(s):  
Pooja Tripathi ◽  
Jyotsna Singh ◽  
Jonathan A. Lal ◽  
Vijay Tripathi
Keyword(s):  
Next Generation Sequencing ◽  
High Throughput ◽  
Large Scale ◽  
Massively Parallel Sequencing ◽  
Genomic Research ◽  
Biological Research ◽  
Next Generation ◽  
Human Welfare ◽  
Drug Designing ◽  
Generation Sequencing

Background: With the outbreak of high throughput next-generation sequencing (NGS), the biological research of drug discovery has been directed towards the oncology and infectious disease therapeutic areas, with extensive use in biopharmaceutical development and vaccine production. Method: In this review, an effort was made to address the basic background of NGS technologies, potential applications of NGS in drug designing. Our purpose is also to provide a brief introduction of various Nextgeneration sequencing techniques. Discussions: The high-throughput methods execute Large-scale Unbiased Sequencing (LUS) which comprises of Massively Parallel Sequencing (MPS) or NGS technologies. The Next geneinvolved necessarily executes Largescale Unbiased Sequencing (LUS) which comprises of MPS or NGS technologies. These are related terms that describe a DNA sequencing technology which has revolutionized genomic research. Using NGS, an entire human genome can be sequenced within a single day. Conclusion: Analysis of NGS data unravels important clues in the quest for the treatment of various lifethreatening diseases and other related scientific problems related to human welfare.

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