Next-Generation Sequencing of the Chrysanthemum nankingense (Asteraceae) Transcriptome Permits Large-Scale Unigene Assembly and SSR Marker Discovery

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

PLoS ONE ◽

10.1371/journal.pone.0139868 ◽

2015 ◽

Vol 10 (10) ◽

pp. e0139868 ◽

Cited By ~ 18

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

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Speeding Up Large-Scale Next Generation Sequencing Data Analysis with pBWA

Journal of Applied Bioinformatics & Computational Biology ◽

10.4172/2329-9533.1000101 ◽

2017 ◽

Vol 01 (01) ◽

Cited By ~ 4

Author(s):

Darren Peters ◽

Xuemei Luo ◽

Ke Qiu ◽

Ping Liang

Keyword(s):

Data Analysis ◽

Next Generation Sequencing ◽

Large Scale ◽

Next Generation Sequencing Data ◽

Next Generation ◽

Sequencing Data ◽

Generation Sequencing ◽

Sequencing Data Analysis

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

Plant Disease ◽

10.1094/pdis-05-18-0905-re ◽

2019 ◽

Vol 103 (6) ◽

pp. 1075-1083 ◽

Cited By ~ 2

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.

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

Acta Botanica Croatica ◽

10.37427/botcro-2020-019 ◽

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.

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Sampling the Waterhemp (Amaranthus tuberculatus) Genome Using Pyrosequencing Technology

Weed Science ◽

10.1614/ws-09-021.1 ◽

2009 ◽

Vol 57 (5) ◽

pp. 463-469 ◽

Cited By ~ 37

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.

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Next-Generation Sequencing Technologies in Blood Group Typing

Transfusion Medicine and Hemotherapy ◽

10.1159/000504765 ◽

2019 ◽

Vol 47 (1) ◽

pp. 4-13 ◽

Cited By ~ 1

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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Large Scale Next Generation Sequencing and Newborn Screening: Are We Ready?

The Journal of Pediatrics ◽

10.1016/j.jpeds.2019.01.037 ◽

2019 ◽

Vol 209 ◽

pp. 9-10

Author(s):

Chanika Phornphutkul ◽

James Padbury

Keyword(s):

Next Generation Sequencing ◽

Newborn Screening ◽

Large Scale ◽

Next Generation ◽

Generation Sequencing

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Finding functional disease-associated non-coding variation using next-generation sequencing

10.1101/060285 ◽

2016 ◽

Author(s):

Paolo Devanna ◽

Xiaowei Sylvia Chen ◽

Joses Ho ◽

Dario Gajewski ◽

Alessandro Gialluisi ◽

...

Keyword(s):

Next Generation Sequencing ◽

Binding Sites ◽

Large Scale ◽

Sequence Data ◽

Whole Genome Sequence ◽

Next Generation Sequencing Data ◽

Whole Genome ◽

Next Generation ◽

Whole Exome ◽

Generation Sequencing

ABSTRACTNext generation sequencing has opened the way for the large scale interrogation of cohorts at the whole exome, or whole genome level. Currently, the field largely focuses on potential disease causing variants that fall within coding sequences and that are predicted to cause protein sequence changes, generally discarding non-coding variants. However non-coding DNA makes up ~98% of the genome and contains a range of sequences essential for controlling the expression of protein coding genes. Thus, potentially causative non-coding variation is currently being overlooked. To address this, we have designed an approach to assess variation in one class of non-coding regulatory DNA; the 3′UTRome. Variants in the 3'UTR region of genes are of particular interest because 3'UTRs are responsible for modulating protein expression levels via their interactions with microRNAs. Furthermore they are amenable to large scale analysis as 3′UTR-microRNA interactions are based on complementary base pairing and as such can be predicted in silico at the genome-wide level. We report a strategy for identifying and functionally testing variants in microRNA binding sites within the 3'UTRome and demonstrate the efficacy of this pipeline in a cohort of language impaired children. Using whole exome sequence data from 43 probands, we extracted variants that lay within 3'UTR microRNA binding sites. We identified a common variant (SNP) in a microRNA binding site and found this SNP to be associated with an endophenotype of language impairment (non-word repetition). We showed that this variant disrupted microRNA regulation in cells and was linked to altered gene expression in the brain, suggesting it may represent a risk factor contributing to SLI. This work demonstrates that biologically relevant variants are currently being under-investigated despite the wealth of next-generation sequencing data available and presents a simple strategy for interrogating non-coding regions of the genome. We propose that this strategy should be routinely applied to whole exome and whole genome sequence data in order to broaden our understanding of how non-coding genetic variation underlies complex phenotypes such as neurodevelopmental disorders.

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Next-generation sequencing in neuropathological diagnosis of infections of the nervous system

10.1101/039222 ◽

2016 ◽

Author(s):

Steven L. Salzberg ◽

Florian Breitwieser ◽

Anupama Kumar ◽

Haiping Hao ◽

Peter Burger ◽

...

Keyword(s):

Spinal Cord ◽

Nervous System ◽

Next Generation Sequencing ◽

Large Scale ◽

Infectious Agent ◽

Next Generation ◽

Dna And Rna ◽

Wide Range ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing

Objective: To determine the feasibility of next-generation sequencing (NGS) microbiome approaches in the diagnosis of infectious disorders in brain or spinal cord biopsies in patients with suspected central nervous system (CNS) infections. Methods: In a prospective-pilot study, we applied NGS in combination with a new computational analysis pipeline to detect the presence of pathogenic microbes in brain or spinal cord biopsies from ten patients with neurological problems indicating possible infection but for whom conventional clinical and microbiology studies yielded negative or inconclusive results. Results: Direct DNA and RNA sequencing of brain tissue biopsies generated 8.3 million to 29.1 million sequence reads per sample, which successfully identified with high confidence the infectious agent in three patients, identified possible pathogens in two more, and helped to understand neuropathological processes in three others, demonstrating the power of large-scale unbiased sequencing as a novel diagnostic tool. Validation techniques confirmed the pathogens identified by NGS in each of the three positive cases. Clinical outcomes were consistent with the findings yielded by NGS on the presence or absence of an infectious pathogenic process in eight of ten cases, and were non-contributory in the remaining two. Conclusions: NGS-guided metagenomic studies of brain, spinal cord or meningeal biopsies offer the possibility for dramatic improvements in our ability to detect (or rule out) a wide range of CNS pathogens, with potential benefits in speed, sensitivity, and cost. NGS-based microbiome approaches present a major new opportunity to investigate the potential role of infectious pathogens in the pathogenesis of neuroinflammatory disorders.

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