scholarly journals Validation of Variant Assembly Using HAPHPIPE with Next-Generation Sequence Data from Viruses

Viruses ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 758 ◽  
Author(s):  
Keylie M. Gibson ◽  
Margaret C. Steiner ◽  
Uzma Rentia ◽  
Matthew L. Bendall ◽  
Marcos Pérez-Losada ◽  
...  
Keyword(s):  
De Novo ◽  
Sequence Data ◽  
Consensus Sequence ◽  
Sequence Assembly ◽  
Next Generation ◽  
Consensus Sequences ◽  
Bioinformatic Tools ◽  
Hiv Gp120 ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data

Next-generation sequencing (NGS) offers a powerful opportunity to identify low-abundance, intra-host viral sequence variants, yet the focus of many bioinformatic tools on consensus sequence construction has precluded a thorough analysis of intra-host diversity. To take full advantage of the resolution of NGS data, we developed HAplotype PHylodynamics PIPEline (HAPHPIPE), an open-source tool for the de novo and reference-based assembly of viral NGS data, with both consensus sequence assembly and a focus on the quantification of intra-host variation through haplotype reconstruction. We validate and compare the consensus sequence assembly methods of HAPHPIPE to those of two alternative software packages, HyDRA and Geneious, using simulated HIV and empirical HIV, HCV, and SARS-CoV-2 datasets. Our validation methods included read mapping, genetic distance, and genetic diversity metrics. In simulated NGS data, HAPHPIPE generated pol consensus sequences significantly closer to the true consensus sequence than those produced by HyDRA and Geneious and performed comparably to Geneious for HIV gp120 sequences. Furthermore, using empirical data from multiple viruses, we demonstrate that HAPHPIPE can analyze larger sequence datasets due to its greater computational speed. Therefore, we contend that HAPHPIPE provides a more user-friendly platform for users with and without bioinformatics experience to implement current best practices for viral NGS assembly than other currently available options.

scholarly journals HAPHPIPE: Haplotype Reconstruction and Phylodynamics for Deep Sequencing of Intra-Host Viral Populations

2020 ◽  
Author(s):  
Matthew L Bendall ◽  
Keylie M Gibson ◽  
Margaret C Steiner ◽  
Uzma Rentia ◽  
Marcos Pérez-Losada ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
De Novo ◽  
Consensus Sequence ◽  
Haplotype Reconstruction ◽  
Consensus Sequences ◽  
Genome Wide ◽  
Genomic Regions ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

Abstract Deep sequencing of viral populations using next generation sequencing (NGS) offers opportunities to understand and investigate evolution, transmission dynamics, and population genetics. Currently, the standard practice for processing NGS data to study viral populations is to summarize all the observed sequences from a sample as a single consensus sequence, thus discarding valuable information about the intra-host viral molecular epidemiology. Furthermore, existing analytical pipelines may only analyze genomic regions involved in drug resistance, thus are not suited for full viral genome analysis. Here we present HAPHPIPE, a HAplotype and PHylodynamics PIPEline for genome-wide assembly of viral consensus sequences and haplotypes. The HAPHPIPE protocol includes modules for quality trimming, error correction, de novo assembly, alignment, and haplotype reconstruction. The resulting consensus sequences, haplotypes, and alignments can be further analyzed using a variety of phylogenetic and population genetic software. HAPHPIPE is designed to provide users with a single pipeline to rapidly analyze sequences from viral populations generated from NGS platforms and provide quality output properly formatted for downstream evolutionary analyses.

scholarly journals SNP Mining in Functional Genes from Nonmodel Species by Next-Generation Sequencing: A Case of Flowering, Pre-Harvest Sprouting, and Dehydration Resistant Genes in Wheat

2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Zhong-Xu Chen ◽  
Mei Deng ◽  
Ji-Rui Wang
Keyword(s):  
Next Generation Sequencing ◽  
Sequence Data ◽  
Low Cost ◽  
Functional Genes ◽  
Accurate Information ◽  
Next Generation ◽  
Polynomial Fitting ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

As plenty of nonmodel plants are without genomic sequences, the combination of molecular technologies and the next generation sequencing (NGS) platform has led to a new approach to study the genetic variations of these plants. Software GATK, SOAPsnp, samtools, and others are often used to deal with the NGS data. In this study, BLAST was applied to call SNPs from 16 mixed functional gene’s sequence data of polyploidy wheat. In total 1.2 million reads were obtained with the average of 7500 reads per genes. To get accurate information, 390,992 pair reads were successfully assembled before aligning to those functional genes. Standalone BLAST tools were used to map assembled sequence to functional genes, respectively. Polynomial fitting was applied to find the suitable minor allele frequency (MAF) threshold at 6% for assembled reads of each functional gene. SNPs accuracy form assembled reads, pretrimmed reads, and original reads were compared, which declared that SNPs mined from the assembled reads were more reliable than others. It was also demonstrated that mixed samples’ NGS sequences and then analysis by BLAST were an effective, low-cost, and accurate way to mine SNPs for nonmodel species. Assembled reads and polynomial fitting threshold were recommended for more accurate SNPs target.

scholarly journals Sequencing of animal viruses: quality data assurance for NGS bioinformatics

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Gianpiero Zamperin ◽  
Pierrick Lucas ◽  
Irene Cano ◽  
David Ryder ◽  
Miriam Abbadi ◽  
...  
Keyword(s):  
Sequence Data ◽  
Consensus Sequence ◽  
Quality Data ◽  
Library Preparation ◽  
Bioinformatics Pipeline ◽  
Manual Curation ◽  
Genome Termini ◽  
Intergenic Regions ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data

Abstract Background Next generation sequencing (NGS) is becoming widely used among diagnostics and research laboratories, and nowadays it is applied to a variety of disciplines, including veterinary virology. The NGS workflow comprises several steps, namely sample processing, library preparation, sequencing and primary/secondary/tertiary bioinformatics (BI) analyses. The latter is constituted by a complex process extremely difficult to standardize, due to the variety of tools and metrics available. Thus, it is of the utmost importance to assess the comparability of results obtained through different methods and in different laboratories. To achieve this goal, we have organized a proficiency test focused on the bioinformatics components for the generation of complete genome sequences of salmonid rhabdoviruses. Methods Three partners, that performed virus sequencing using different commercial library preparation kits and NGS platforms, gathered together and shared with each other 75 raw datasets which were analyzed separately by the participants to produce a consensus sequence according to their own bioinformatics pipeline. Results were then compared to highlight discrepancies, and a subset of inconsistencies were investigated more in detail. Results In total, we observed 526 discrepancies, of which 39.5% were located at genome termini, 14.1% at intergenic regions and 46.4% at coding regions. Among these, 10 SNPs and 99 indels caused changes in the protein products. Overall reproducibility was 99.94%. Based on the analysis of a subset of inconsistencies investigated more in-depth, manual curation appeared the most critical step affecting sequence comparability, suggesting that the harmonization of this phase is crucial to obtain comparable results. The analysis of a calibrator sample allowed assessing BI accuracy, being 99.983%. Conclusions We demonstrated the applicability and the usefulness of BI proficiency testing to assure the quality of NGS data, and recommend a wider implementation of such exercises to guarantee sequence data uniformity among different virology laboratories.

scholarly journals Histoimmunogenetics Markup Language 1.0: Reporting Next Generation Sequencing-based HLA and KIR Genotyping

2015 ◽  
Author(s):  
Robert P Milius ◽  
Michael Heuer ◽  
Daniel Valiga ◽  
Kathryn J Doroschak ◽  
Caleb J. Kennedy ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Data Exchange ◽  
Consensus Sequence ◽  
Markup Language ◽  
Next Generation ◽  
Multiple Group ◽  
Specific Priming ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

We present an electronic format for exchanging data for HLA and KIR genotyping with extensions for next-generation sequencing (NGS). This format addresses NGS data exchange by refining the Histoimmunogenetics Markup Language (HML) to conform to the proposed Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) reporting guidelines (miring.immunogenomics.org). Our refinements of HML include two major additions. First, NGS is supported by new XML structures to capture additional NGS data and metadata required to produce a genotyping result, including analysis-dependent (dynamic) and method-dependent (static) components. A full genotype, consensus sequence, and the surrounding metadata are included directly, while the raw sequence reads and platform documentation are externally referenced. Second, genotype ambiguity is fully represented by integrating Genotype List Strings, which use a hierarchical set of delimiters to represent allele and genotype ambiguity in a complete and accurate fashion. HML also continues to enable the transmission of legacy methods (e.g. site-specific oligonucleotide, sequence-specific priming, and sequence based typing (SBT)), adding features such as allowing multiple group-specific sequencing primers, and fully leveraging techniques that combine multiple methods to obtain a single result, such as SBT integrated with NGS.

scholarly journals Minimum Information for Reporting Next Generation Sequence Genotyping (MIRING): Guidelines for Reporting HLA and KIR Genotyping via Next Generation Sequencing

2015 ◽  
Author(s):  
Steven J. Mack ◽  
Robert P Milius ◽  
Benjamin D Gifford ◽  
Jürgen Sauter ◽  
Jan Hofmann ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Consensus Sequence ◽  
Primary Data ◽  
Genotype Data ◽  
Next Generation ◽  
Minimum Information ◽  
Structured Information ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

The development of next-generation sequencing (NGS) technologies for HLA and KIR genotyping is rapidly advancing knowledge of genetic variation of these highly polymorphic loci. NGS genotyping is poised to replace older methods for clinical use, but standard methods for reporting and exchanging these new, high quality genotype data are needed. The Immunogenomic NGS Consortium, a broad collaboration of histocompatibility and immunogenetics clinicians, researchers, instrument manufacturers and software developers, has developed the Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) reporting guidelines. MIRING is a checklist that specifies the content of NGS genotyping results as well as a set of messaging guidelines for reporting the results. A MIRING message includes five categories of structured information – message annotation, reference context, full genotype, consensus sequence and novel polymorphism – and references to three categories of accessory information – NGS platform documentation, read processing documentation and primary data. These eight categories of information ensure the long-term portability and broad application of this NGS data for all current histocompatibility and immunogenetics use cases. In addition, MIRING can be extended to allow the reporting of genotype data generated using pre-NGS technologies. Because genotyping results reported using MIRING are easily updated in accordance with reference and nomenclature databases, MIRING represents a bold departure from previous methods of reporting HLA and KIR genotyping results, which have provided static and less-portable data. More information about MIRING can be found online at miring.immunogenomics.org.

scholarly journals Mining and Development of Novel SSR Markers Using Next Generation Sequencing (NGS) Data in Plants

Molecules ◽  
2018 ◽  
Vol 23 (2) ◽  
pp. 399 ◽  
Author(s):  
Sima Taheri ◽  
Thohirah Lee Abdullah ◽  
Mohd Yusop ◽  
Mohamed Hanafi ◽  
Mahbod Sahebi ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Ssr Markers ◽  
Next Generation ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

scholarly journals ViennaNGS: A toolbox for building efficient next- generation sequencing analysis pipelines

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 50 ◽  
Author(s):  
Michael T. Wolfinger ◽  
Jörg Fallmann ◽  
Florian Eggenhofer ◽  
Fabian Amman
Keyword(s):  
Next Generation Sequencing ◽  
Sequence Motif ◽  
Software Components ◽  
Sequencing Analysis ◽  
Next Generation ◽  
File Formats ◽  
Next Generation Sequencing Analysis ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

Recent achievements in next-generation sequencing (NGS) technologies lead to a high demand for reuseable software components to easily compile customized analysis workflows for big genomics data. We present ViennaNGS, an integrated collection of Perl modules focused on building efficient pipelines for NGS data processing. It comes with functionality for extracting and converting features from common NGS file formats, computation and evaluation of read mapping statistics, as well as normalization of RNA abundance. Moreover, ViennaNGS provides software components for identification and characterization of splice junctions from RNA-seq data, parsing and condensing sequence motif data, automated construction of Assembly and Track Hubs for the UCSC genome browser, as well as wrapper routines for a set of commonly used NGS command line tools.

scholarly journals Whole genome sequencing suggests transmission of Corynebacterium diphtheriae-caused cutaneous diphtheria in two siblings, Germany, 2018

2019 ◽  
Vol 24 (2) ◽  
Author(s):  
Anja Berger ◽  
Alexandra Dangel ◽  
Tilmann Schober ◽  
Birgit Schmidbauer ◽  
Regina Konrad ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Corynebacterium Diphtheriae ◽  
Whole Genome ◽  
Next Generation ◽  
Insect Bites ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

In September 2018, a child who had returned from Somalia to Germany presented with cutaneous diphtheria by toxigenic Corynebacterium diphtheriae biovar mitis. The child’s sibling had superinfected insect bites harbouring also toxigenic C. diphtheriae. Next generation sequencing (NGS) revealed the same strain in both patients suggesting very recent human-to-human transmission. Epidemiological and NGS data suggest that the two cutaneous diphtheria cases constitute the first outbreak by toxigenic C. diphtheriae in Germany since the 1980s.

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