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Genome Detective: An Automated System for Virus Identification from High-throughput sequencing data
Bioinformatics (Oxford, England), 2018
Genome Detective is an easy to use web-based software application that assembles the genomes of viruses quickly and accurately. The application uses a novel alignment method that constructs genomes by reference-based linking of de-novo contigs by combining amino-acids and nucleotide scores. The software was optimized using synthetic datasets to represent the great diversity of virus genomes. The application was then validated with next generation sequencing data of hundreds of viruses. User time is minimal and it is limited to the time required to upload the data. Available online: http://www.genomedetective.com/app/typingtool/virus/. Supplementary data are available at Bioinformatics online.
viruSITE—integrated database for viral genomics
Database, 2016
Viruses are the most abundant biological entities and the reservoir of most of the genetic diversity in the Earth's biosphere. Viral genomes are very diverse, generally short in length and compared to other organisms carry only few genes. viruSITE is a novel database which brings together high-value information compiled from various resources. viruSITE covers the whole universe of viruses and focuses on viral genomes, genes and proteins. The database contains information on virus taxonomy, host range, genome features, sequential relatedness as well as the properties and functions of viral genes and proteins. All entries in the database are linked to numerous information resources. The above-mentioned features make viruSITE a comprehensive knowledge hub in the field of viral genomics. The web interface of the database was designed so as to offer an easy-to-navigate, intuitive and user-friendly environment. It provides sophisticated text searching and a taxonomy-based browsing system. viruSITE also allows for an alternative approach based on sequence search. A proprietary genome browser generates a graphical representation of viral genomes. In addition to retrieving and visualising data, users can perform comparative genomics analyses using a variety of tools.
Base-By-Base Version 3: New Comparative Tools for Large Virus Genomes
Viruses, 2018
Base-By-Base is a comprehensive tool for the creation and editing of multiple sequence alignments that is coded in Java and runs on multiple platforms. It can be used with gene and protein sequences as well as with large viral genomes, which themselves can contain gene annotations. This report describes new features added to Base-By-Base over the last 7 years. The two most significant additions are: (1) The recoding and inclusion of “consensus-degenerate hybrid oligonucleotide primers” (CODEHOP), a popular tool for the design of degenerate primers from a multiple sequence alignment of proteins; and (2) the ability to perform fuzzy searches within the columns of sequence data in multiple sequence alignments to determine the distribution of sequence variants among the sequences. The intuitive interface focuses on the presentation of results in easily understood visualizations and providing the ability to annotate the sequences in a multiple alignment with analytic and user data.
Identification of Novel Viruses Using VirusHunter -- an Automated Data Analysis Pipeline
PLoS ONE, 2013
Quick and accurate identification of microbial pathogens is essential for both diagnosis and response to emerging infectious diseases. The advent of next-generation sequencing technology offers an unprecedented platform for rapid sequencing-based identification of novel viruses. We have developed a customized bioinformatics data analysis pipeline, VirusHunter, for the analysis of Roche/454 and other long read Next generation sequencing platform data. To illustrate the utility of VirusHunter, we performed Roche/454 GS FLX titanium sequencing on two unclassified virus isolates from the World Reference Center for Emerging Viruses and Arboviruses (WRCEVA). VirusHunter identified sequences derived from a novel bunyavirus and a novel reovirus in the two samples respectively. Further sequence analysis demonstrated that the viruses were novel members of the Phlebovirus and Orbivirus genera. Both Phlebovirus and Orbivirus genera include many economic important viruses or serious human pathogens.
VIGOR extended to annotate genomes for additional 12 different viruses
Nucleic Acids Research, 2012
A gene prediction program, VIGOR (Viral Genome ORF Reader), was developed at J. Craig Venter Institute in 2010 and has been successfully performing gene calling in coronavirus, influenza, rhinovirus and rotavirus for projects at the Genome Sequencing Center for Infectious Diseases. VIGOR uses sequence similarity search against custom protein databases to identify protein coding regions, start and stop codons and other gene features. Ribonucleicacid editing and other features are accurately identified based on sequence similarity and signature residues. VIGOR produces four output files: a gene prediction file, a complementary DNA file, an alignment file, and a gene feature table file. The gene feature table can be used to create GenBank submission. VIGOR takes a single input: viral genomic sequences in FASTA format. VIGOR has been extended to predict genes for 12 viruses: measles virus, mumps virus, rubella virus, respiratory syncytial virus, alphavirus and Venezuelan equine encephal...
GLUE: a flexible software system for virus sequence data
BMC Bioinformatics
Background: Virus genome sequences, generated in ever-higher volumes, can provide new scientific insights and inform our responses to epidemics and outbreaks. To facilitate interpretation, such data must be organised and processed within scalable computing resources that encapsulate virology expertise. GLUE (Genes Linked by Underlying Evolution) is a data-centric bioinformatics environment for building such resources. The GLUE core data schema organises sequence data along evolutionary lines, capturing not only nucleotide data but associated items such as alignments, genotype definitions, genome annotations and motifs. Its flexible design emphasises applicability to different viruses and to diverse needs within research, clinical or public health contexts. Results: HCV-GLUE is a case study GLUE resource for hepatitis C virus (HCV). It includes an interactive public web application providing sequence analysis in the form of a maximum-likelihood-based genotyping method, antiviral resistance detection and graphical sequence visualisation. HCV sequence data from GenBank is categorised and stored in a large-scale sequence alignment which is accessible via web-based queries. Whereas this web resource provides a range of basic functionality, the underlying GLUE project can also be downloaded and extended by bioinformaticians addressing more advanced questions. Conclusion: GLUE can be used to rapidly develop virus sequence data resources with public health, research and clinical applications. This streamlined approach, with its focus on reuse, will help realise the full value of virus sequence data.
SDT: A Virus Classification Tool Based on Pairwise Sequence Alignment and Identity Calculation
PLoS ONE, 2014
The perpetually increasing rate at which viral full-genome sequences are being determined is creating a pressing demand for computational tools that will aid the objective classification of these genome sequences. Taxonomic classification approaches that are based on pairwise genetic identity measures are potentially highly automatable and are progressively gaining favour with the International Committee on Taxonomy of Viruses (ICTV). There are, however, various issues with the calculation of such measures that could potentially undermine the accuracy and consistency with which they can be applied to virus classification. Firstly, pairwise sequence identities computed based on multiple sequence alignments rather than on multiple independent pairwise alignments can lead to the deflation of identity scores with increasing dataset sizes. Also, when gap-characters need to be introduced during sequence alignments to account for insertions and deletions, methodological variations in the way that these characters are introduced and handled during pairwise genetic identity calculations can cause high degrees of inconsistency in the way that different methods classify the same sets of sequences. Here we present Sequence Demarcation Tool (SDT), a free user-friendly computer program that aims to provide a robust and highly reproducible means of objectively using pairwise genetic identity calculations to classify any set of nucleotide or amino acid sequences. SDT can produce publication quality pairwise identity plots and colour-coded distance matrices to further aid the classification of sequences according to ICTV approved taxonomic demarcation criteria. Besides a graphical interface version of the program for Windows computers, command-line versions of the program are available for a variety of different operating systems (including a parallel version for cluster computing platforms).
The International Virus Bioinformatics Meeting 2022
Viruses
The International Virus Bioinformatics Meeting 2022 took place online, on 23–25 March 2022, and has attracted about 380 participants from all over the world. The goal of the meeting was to provide a meaningful and interactive scientific environment to promote discussion and collaboration and to inspire and suggest new research directions and questions. The participants created a highly interactive scientific environment even without physical face-to-face interactions. This meeting is a focal point to gain an insight into the state-of-the-art of the virus bioinformatics research landscape and to interact with researchers in the forefront as well as aspiring young scientists. The meeting featured eight invited and 18 contributed talks in eight sessions on three days, as well as 52 posters, which were presented during three virtual poster sessions. The main topics were: SARS-CoV-2, viral emergence and surveillance, virus–host interactions, viral sequence analysis, virus identification ...
NucAmino: a nucleotide to amino acid alignment optimized for virus gene sequences
BMC Bioinformatics
Background: Current nucleotide-to-amino acid alignment software programs were developed primarily for detecting gene exons within eukaryotic genomes and were therefore optimized for speed across long genetic sequences. We developed a nucleotide-to-amino acid alignment program NucAmino optimized for virus sequencing. Results: NucAmino is an open source program written in the high-level language Go. NucAmino is more likely to align codons flush with a reference sequence's amino acids and can be modified to facilitate the placement of insertions and deletions at specific positions. We compared NucAmino to the nucleotide to amino acid alignment program Local Alignment Program (LAP) using 115,118 human immunodeficiency virus type 1 (HIV-1) protease, reverse transcriptase, and integrase sequences-three genes that are commonly sequenced in clinical laboratories. Discordances between NucAmino and LAP occurred in 512 (16.9%) of the 3,029 sequences containing gaps but in none of 112,910 sequences without gaps. For 242 of the sequences with discordances, NucAmino produced an alignment that was preferable to that found by LAP in that it was more likely to codon align insertions and deletions and to facilitate the placement of an important drug-resistance associated insertion at the position at which most laboratories expect it to occur. Conclusions: NucAmino is a nucleotide-to-amino acid alignment program with several advantages for clinical laboratories performing virus sequencing compared with older programs designed for gene finding.
Virology Journal, 2023
Background The genome of the largest known animal virus, the white spot syndrome virus (WSSV) responsible for huge economic losses and loss of employment in aquaculture, suffers from inconsistent annotation nomenclature. Novel genome sequence, circular genome and variable genome length led to nomenclature inconsistencies. Since vast knowledge has already accumulated in the past two decades with inconsistent nomenclature, the insights gained on a genome could not be easily extendable to other genomes. Therefore, the present study aims to perform comparative genomics studies in WSSV on uniform nomenclature. Methods We have combined the standard mummer tool with custom scripts to develop missing regions finder (MRF) that documents the missing genome regions and coding sequences in virus genomes in comparison to a reference genome and in its annotation nomenclature. The procedure was implemented as web tool and in commandline interface. Using MRF, we have documented the missing coding sequences in WSSV and explored their role in virulence through application of phylogenomics, machine learning models and homologous genes. Results We have tabulated and depicted the missing genome regions, missing coding sequences and deletion hotspots in WSSV on a common annotation nomenclature and attempted to link them to virus virulence. It was observed that the ubiquitination, transcription regulation and nucleotide metabolism might be essentially required for WSSV pathogenesis; and the structural proteins, VP19, VP26 and VP28 are essential for virus assembly. Few minor structural proteins in WSSV would act as envelope glycoproteins. We have also demonstrated the advantage of MRF in providing detailed graphic/tabular output in less time and also in handling of low-complexity, repeat-rich and highly similar regions of the genomes using other virus cases. Conclusions Pathogenic virus research benefits from tools that could directly indicate the missing genomic regions and coding sequences between isolates/strains. In virus research, the analyses performed in this study provides an †