scholarly journals NGS-QCbox and Raspberry for Parallel, Automated and Rapid Quality Control Analysis of Large-Scale Next Generation Sequencing (Illumina) Data

PLoS ONE ◽  
2015 ◽  
Vol 10 (10) ◽  
pp. e0139868 ◽  
Author(s):  
Mohan A. V. S. K. Katta ◽  
Aamir W. Khan ◽  
Dadakhalandar Doddamani ◽  
Mahendar Thudi ◽  
Rajeev K. Varshney
Keyword(s):  
Quality Control ◽  
Next Generation Sequencing ◽  
Large Scale ◽  
Control Analysis ◽  
Next Generation ◽  
Quality Control Analysis ◽  
Illumina Data ◽  
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.

scholarly journals Applying Ancestry and Sex Computation as a Quality Control Tool in Targeted Next-Generation Sequencing

2016 ◽  
Vol 145 (3) ◽  
pp. 308-315 ◽  
Author(s):  
Patrick C. Mathias ◽  
Emily H. Turner ◽  
Sheena M. Scroggins ◽  
Stephen J. Salipante ◽  
Noah G. Hoffman ◽  
...  
Keyword(s):  
Quality Control ◽  
Next Generation Sequencing ◽  
Next Generation ◽  
Targeted Next Generation Sequencing ◽  
Quality Control Tool ◽  
Generation Sequencing ◽  
Control Tool

scholarly journals Applications of Next-Generation Sequencing for Large-Scale Pathogen Diagnoses in Soybean

Plant Disease ◽  
2019 ◽  
Vol 103 (6) ◽  
pp. 1075-1083 ◽  
Author(s):  
Gustavo A. Díaz-Cruz ◽  
Charlotte M. Smith ◽  
Kiana F. Wiebe ◽  
Sachi M. Villanueva ◽  
Adam R. Klonowski ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Pseudomonas Syringae ◽  
Large Scale ◽  
Fold Increase ◽  
Yellow Mosaic Virus ◽  
Growth Stages ◽  
Sequence Information ◽  
Next Generation ◽  
Leaf Sample ◽  
Generation Sequencing

Soybean (Glycine max) has become an important crop in Manitoba, Canada, with a 10-fold increase in dedicated acreage over the past decade. Given the rapid increase in production, scarce information about foliar diseases present in the province has been recorded. In order to describe the foliar pathogens affecting this legume, we harnessed next-generation sequencing (NGS) to carry out a comprehensive survey across Manitoba in 2016. Fields were sampled during the V2/3 (33 fields) and R6 (70 fields) growth stages, with at least three symptomatic leaves per field collected and subjected to RNA sequencing. We successfully detected several bacteria, fungi, and viruses known to infect soybean, including Pseudomonas savastanoi pv. glycinea, Septoria glycines, and Peronospora manshurica, as well as pathogens not previously identified in the province (e.g., Pseudomonas syringae pv. tabaci, Cercospora sojina, and Bean yellow mosaic virus). For some microorganisms, we were able to disentangle the different pathovars present and/or assemble their genome sequence. Since NGS generates data on the entire flora and fauna occupying a leaf sample, we also identified residual pathogens (i.e., pathogens of crops other than soybean) and multiple species of arthropod pests. Finally, the sequence information produced by NGS allowed for the development of polymerase chain reaction-based diagnostics for some of the most widespread and important pathogens. Although there are many benefits of using NGS for large-scale plant pathogen diagnoses, we also discuss some of the limitations of this technology.

scholarly journals Validation of variants using cost effective highresolution melting (HRM) analysis predicted from target re-sequencing in Eucalyptus

2020 ◽  
Vol 79 (2) ◽  
pp. 105-113
Author(s):  
Abdul Bari Muneera Parveen ◽  
Divya Lakshmanan ◽  
Modhumita Ghosh Dasgupta
Keyword(s):  
Next Generation Sequencing ◽  
Large Scale ◽  
Sequence Data ◽  
Cost Effective ◽  
Nucleotide Polymorphisms ◽  
Next Generation ◽  
Time Saving ◽  
Hrm Analysis ◽  
The Cost ◽  
Generation Sequencing

The advent of next-generation sequencing has facilitated large-scale discovery and mapping of genomic variants for high-throughput genotyping. Several research groups working in tree species are presently employing next generation sequencing (NGS) platforms for marker discovery, since it is a cost effective and time saving strategy. However, most trees lack a chromosome level genome map and validation of variants for downstream application becomes obligatory. The cost associated with identifying potential variants from the enormous amount of sequence data is a major limitation. In the present study, high resolution melting (HRM) analysis was optimized for rapid validation of single nucleotide polymorphisms (SNPs), insertions or deletions (InDels) and simple sequence repeats (SSRs) predicted from exome sequencing of parents and hybrids of Eucalyptus tereticornis Sm. ? Eucalyptus grandis Hill ex Maiden generated from controlled hybridization. The cost per data point was less than 0.5 USD, providing great flexibility in terms of cost and sensitivity, when compared to other validation methods. The sensitivity of this technology in variant detection can be extended to other applications including Bar-HRM for species authentication and TILLING for detection of mutants.

Sampling the Waterhemp (Amaranthus tuberculatus) Genome Using Pyrosequencing Technology

Weed Science ◽  
2009 ◽  
Vol 57 (5) ◽  
pp. 463-469 ◽  
Author(s):  
Ryan M. Lee ◽  
Jyothi Thimmapuram ◽  
Kate A. Thinglum ◽  
George Gong ◽  
Alvaro G. Hernandez ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Large Scale ◽  
Ecological Model ◽  
Average Length ◽  
Science Research ◽  
Complete Sequence ◽  
Next Generation ◽  
Next Generation Sequencing Technology ◽  
Sequencing Technologies ◽  
Generation Sequencing

Recent advances in sequencing technologies (next-generation sequencing) offer dramatically increased sequencing throughput at a lower cost than traditional Sanger sequencing. This technology is changing genomics research by allowing large scale sequencing experiments in nonmodel systems. Waterhemp is an important weed in the midwestern United States with characteristics that makes it an interesting ecological model. However, very few genomic resources are available for this species. One half of a 70 by 75 picotiter plate of 454-pyrosequencing was performed on total DNA isolated from waterhemp, generating 158,015 reads of an average length of 271 bp, or a total of nearly 43 Mbp of sequence. Included in this sequence was a nearly complete sequence of the chloroplast genome, sequences of several important herbicide resistance genes, leads for simple sequence repeat (SSR) markers, and a sampling of the repeated elements (e.g., transposons) present in this species. Here we present the waterhemp genomic data gleaned from this sequencing experiment and illustrate the value of next-generation sequencing technology to weed science research.

scholarly journals Next-Generation Sequencing Technologies in Blood Group Typing

2019 ◽  
Vol 47 (1) ◽  
pp. 4-13 ◽  
Author(s):  
Daniel Fürst ◽  
Chrysanthi Tsamadou ◽  
Christine Neuchel ◽  
Hubert Schrezenmeier ◽  
Joannis Mytilineos ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Blood Group ◽  
Large Scale ◽  
Cost Effective ◽  
Molecular Testing ◽  
Blood Group Antigens ◽  
Next Generation ◽  
Sequencing Technologies ◽  
Blood Group Typing ◽  
Generation Sequencing

Sequencing of the human genome has led to the definition of the genes for most of the relevant blood group systems, and the polymorphisms responsible for most of the clinically relevant blood group antigens are characterized. Molecular blood group typing is used in situations where erythrocytes are not available or where serological testing was inconclusive or not possible due to the lack of antisera. Also, molecular testing may be more cost-effective in certain situations. Molecular typing approaches are mostly based on either PCR with specific primers, DNA hybridization, or DNA sequencing. Particularly the transition of sequencing techniques from Sanger-based sequencing to next-generation sequencing (NGS) technologies has led to exciting new possibilities in blood group genotyping. We describe briefly the currently available NGS platforms and their specifications, depict the genetic background of blood group polymorphisms, and discuss applications for NGS approaches in immunohematology. As an example, we delineate a protocol for large-scale donor blood group screening established and in use at our institution. Furthermore, we discuss technical challenges and limitations as well as the prospect for future developments, including long-read sequencing technologies.

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