Dataset Information

Cenote-Taker 2 democratizes virus discovery and sequence annotation.

ABSTRACT: Viruses, despite their great abundance and significance in biological systems, remain largely mysterious. Indeed, the vast majority of the perhaps hundreds of millions of viral species on the planet remain undiscovered. Additionally, many viruses deposited in central databases like GenBank and RefSeq are littered with genes annotated as 'hypothetical protein' or the equivalent. Cenote-Taker 2, a virus discovery and annotation tool available on command line and with a graphical user interface with free high-performance computation access, utilizes highly sensitive models of hallmark virus genes to discover familiar or divergent viral sequences from user-input contigs. Additionally, Cenote-Taker 2 uses a flexible set of modules to automatically annotate the sequence features of contigs, providing more gene information than comparable tools. The outputs include readable and interactive genome maps, virome summary tables, and files that can be directly submitted to GenBank. We expect Cenote-Taker 2 to facilitate virus discovery, annotation, and expansion of the known virome.

SUBMITTER: Tisza MJ

PROVIDER: S-EPMC7816666 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Cenote-Taker 2 democratizes virus discovery and sequence annotation.

Tisza Michael J MJ Belford Anna K AK Domínguez-Huerta Guillermo G Bolduc Benjamin B Buck Christopher B CB

Virus evolution 20201230 1

Viruses, despite their great abundance and significance in biological systems, remain largely mysterious. Indeed, the vast majority of the perhaps hundreds of millions of viral species on the planet remain undiscovered. Additionally, many viruses deposited in central databases like GenBank and RefSeq are littered with genes annotated as 'hypothetical protein' or the equivalent. Cenote-Taker 2, a virus discovery and annotation tool available on command line and with a graphical user interface wit ...[more]

PMID: 33505708

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Project description:BackgroundGenBank contains over 3 million viral sequences. The National Center for Biotechnology Information (NCBI) previously made available a tool for validating and annotating influenza virus sequences that is used to check submissions to GenBank. Before this project, there was no analogous tool in use for non-influenza viral sequence submissions.ResultsWe developed a system called VADR (Viral Annotation DefineR) that validates and annotates viral sequences in GenBank submissions. The annotation system is based on the analysis of the input nucleotide sequence using models built from curated RefSeqs. Hidden Markov models are used to classify sequences by determining the RefSeq they are most similar to, and feature annotation from the RefSeq is mapped based on a nucleotide alignment of the full sequence to a covariance model. Predicted proteins encoded by the sequence are validated with nucleotide-to-protein alignments using BLAST. The system identifies 43 types of "alerts" that (unlike the previous BLAST-based system) provide deterministic and rigorous feedback to researchers who submit sequences with unexpected characteristics. VADR has been integrated into GenBank's submission processing pipeline allowing for viral submissions passing all tests to be accepted and annotated automatically, without the need for any human (GenBank indexer) intervention. Unlike the previous submission-checking system, VADR is freely available (https://github.com/nawrockie/vadr) for local installation and use. VADR has been used for Norovirus submissions since May 2018 and for Dengue virus submissions since January 2019. Since March 2020, VADR has also been used to check SARS-CoV-2 sequence submissions. Other viruses with high numbers of submissions will be added incrementally.ConclusionVADR improves the speed with which non-flu virus submissions to GenBank can be checked and improves the content and quality of the GenBank annotations. The availability and portability of the software allow researchers to run the GenBank checks prior to submitting their viral sequences, and thereby gain confidence that their submissions will be accepted immediately without the need to correspond with GenBank staff. Reciprocally, the adoption of VADR frees GenBank staff to spend more time on services other than checking routine viral sequence submissions.

Project description:Drug resistance resulting from reverse transcriptase (RT) mutations is one of the main obstacles to successful hepatitis B virus (HBV) therapy. Indeed, HBV treatment guidelines recommend HBV genotypic resistance testing for patients receiving nucleos(t)ide RT inhibitors (N(t)RTIs) who develop virological failure. N(t)RTI-resistance mutations at 10 RT positions have been well characterized in phenotypic studies, however, data are lacking on the relative frequency of these mutations in N(t)RTI-treated and untreated individuals. There are also few published data on the extent of amino acid variation at most of the 344 positions of HBV RT and the extent to which this variation is influenced by N(t)RTI treatment. We retrieved 23,871 HBV RT sequences from GenBank and reviewed the published reports of these sequences to ascertain the number of individuals from whom the sequences were obtained, the N(t)RTI treatments of these individuals, and the year and region of virus sampling. We then used these data to populate a relational database we named HBVrtDB. As of July 2010, HBVrtDB contained 6811 sequences from 3869 individuals reported in 281 references. Among these 3869 individuals, 73% were N(t)RTI-naïve and 27% received one or more N(t)RTIs. Among the 10 well-characterized N(t)RTI-resistance mutations, L80I/V, V173L, L180M, A181T, T184S, S202G and M204I/V were significantly associated with treatment with lamivudine, an l-nucleoside analog, and A181S/T/V and N236T were significantly associated with treatment with adefovir, an acyclic nucleoside phosphonate. A similar analysis of ten additional less well-characterized resistance mutations demonstrated a significant association with N(t)RTI treatment for four of the mutations: L82M, S85A, A200V, and Q215S. We also created an interactive program, HBVseq, to enable users to identify mutations in submitted sequences and retrieve the prevalence of these mutations in HBVrtDB according to genotype and N(t)RTI treatment. HBVrtDB and HBVseq are available at http://hivdb.stanford.edu/HBV/releaseNotes/.

Dataset Information

Cenote-Taker 2 democratizes virus discovery and sequence annotation.

Publications

Cenote-Taker 2 democratizes virus discovery and sequence annotation.

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