scholarly journals SNP Discovery through Next-Generation Sequencing and Its Applications

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Santosh Kumar ◽  
Travis W. Banks ◽  
Sylvie Cloutier
Keyword(s):  
Next Generation Sequencing ◽  
Large Scale ◽  
Easy Access ◽  
Next Generation ◽  
Snp Discovery ◽  
Genetic Studies ◽  
Research Areas ◽  
Wide Availability ◽  
Sequencing Platforms ◽  
Generation Sequencing

The decreasing cost along with rapid progress in next-generation sequencing and related bioinformatics computing resources has facilitated large-scale discovery of SNPs in various model and nonmodel plant species. Large numbers and genome-wide availability of SNPs make them the marker of choice in partially or completely sequenced genomes. Although excellent reviews have been published on next-generation sequencing, its associated bioinformatics challenges, and the applications of SNPs in genetic studies, a comprehensive review connecting these three intertwined research areas is needed. This paper touches upon various aspects of SNP discovery, highlighting key points in availability and selection of appropriate sequencing platforms, bioinformatics pipelines, SNP filtering criteria, and applications of SNPs in genetic analyses. The use of next-generation sequencing methodologies in many non-model crops leading to discovery and implementation of SNPs in various genetic studies is discussed. Development and improvement of bioinformatics software that are open source and freely available have accelerated the SNP discovery while reducing the associated cost. Key considerations for SNP filtering and associated pipelines are discussed in specific topics. A list of commonly used software and their sources is compiled for easy access and reference.

DNA sequencing

2018 ◽  
Author(s):  
Pierre Taberlet ◽  
Aurélie Bonin ◽  
Lucie Zinger ◽  
Eric Coissac
Keyword(s):  
Next Generation Sequencing ◽  
Dna Sequencing ◽  
Large Scale ◽  
Scale Analysis ◽  
Next Generation ◽  
Illumina Platform ◽  
Large Scale Analysis ◽  
Sequencing Platforms ◽  
Generation Sequencing ◽  
Illumina Library

The emergence of eDNA analysis is tightly linked to the development of next-generation sequencing. Chapter 7 “DNA sequencing” gives an overview of the characteristics and limitations of the main next-generation sequencing platforms. It focuses particularly on the Illumina platform, which is the only technology currently suitable for large-scale analysis with hundreds to thousands of samples. More specifically, Chapter 7 describes the Illumina library preparation process, the generation of sequencing clusters by bridge PCR on the flow cell, and the sequencing reaction itself, based on sequencing by synthesis. Finally, detailed information is provided on the meaning and coding of quality scores of the sequencing reads.

scholarly journals Multi-Platform Assessment of DNA Sequencing Performance using Human and Bacterial Reference Genomes in the ABRF Next-Generation Sequencing Study

2020 ◽  
Author(s):  
Jonathan Foox ◽  
Scott W. Tighe ◽  
Charles M. Nicolet ◽  
Justin M. Zook ◽  
Marta Byrska-Bishop ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Dna Sequencing ◽  
Large Scale ◽  
Error Rates ◽  
Clinical Diagnostics ◽  
Small Scale ◽  
Next Generation ◽  
Oxford Nanopore ◽  
Sequencing Platforms ◽  
Generation Sequencing

AbstractMassively parallel DNA sequencing is a critical tool for genomics research and clinical diagnostics. Here, we describe the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Phase II Study to measure quality and reproducibility of DNA sequencing. Replicates of human and bacterial reference DNA samples were generated across multiple sequencing platforms, including well-established technologies such as Illumina, ThermoFisher Ion Torrent, and Pacific Biosciences, as well as emerging technologies such as BGI, Genapsys, and Oxford Nanopore. A total of 202 datasets were generated to investigate the performance of a total of 16 sequencing platforms, including mappability of reads, coverage and error rates in difficult genomic regions, and detection of small-scale polymorphisms and large-scale structural variants. This study provides a comprehensive baseline resource for continual benchmarking as chemistries, methods, and platforms evolve for DNA 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 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

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 Hi-C chromosome conformation capture sequencing of avian genomes using the BGISEQ-500 platform

GigaScience ◽  
2020 ◽  
Vol 9 (8) ◽  
Author(s):  
Marcela Sandoval-Velasco ◽  
Juan Antonio Rodríguez ◽  
Cynthia Perez Estrada ◽  
Guojie Zhang ◽  
Erez Lieberman Aiden ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
High Throughput Sequencing ◽  
Data Generation ◽  
Next Generation ◽  
Sequencing Data ◽  
Yield Data ◽  
Chromosome Conformation ◽  
Sequencing Platform ◽  
Sequencing Platforms ◽  
Generation Sequencing

Abstract Background Hi-C experiments couple DNA-DNA proximity with next-generation sequencing to yield an unbiased description of genome-wide interactions. Previous methods describing Hi-C experiments have focused on the industry-standard Illumina sequencing. With new next-generation sequencing platforms such as BGISEQ-500 becoming more widely available, protocol adaptations to fit platform-specific requirements are useful to give increased choice to researchers who routinely generate sequencing data. Results We describe an in situ Hi-C protocol adapted to be compatible with the BGISEQ-500 high-throughput sequencing platform. Using zebra finch (Taeniopygia guttata) as a biological sample, we demonstrate how Hi-C libraries can be constructed to generate informative data using the BGISEQ-500 platform, following circularization and DNA nanoball generation. Our protocol is a modification of an Illumina-compatible method, based around blunt-end ligations in library construction, using un-barcoded, distally overhanging double-stranded adapters, followed by amplification using indexed primers. The resulting libraries are ready for circularization and subsequent sequencing on the BGISEQ series of platforms and yield data similar to what can be expected using Illumina-compatible approaches. Conclusions Our straightforward modification to an Illumina-compatible in situHi-C protocol enables data generation on the BGISEQ series of platforms, thus expanding the options available for researchers who wish to utilize the powerful Hi-C techniques in their research.

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