NucAmino: a nucleotide to amino acid alignment optimized for virus gene sequences

Tzou, Philip L.; Huang, Xiaoqiu; Shafer, Robert W.

doi:10.1186/s12859-017-1555-6

Cited by 12 publications

(8 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The alignments used here act as an initial starting point for evaluating RNA sequence conservation in SARS-related viruses and in SARS-CoV-2 strains. Further conservation analysis may benefit from exploring the use of codon-correct viral genome alignments (Libin, et al 2019) or reference-guided alignments (Tzou, et al 2017). Additionally, alignments capturing Cold Spring Harbor Laboratory Press on June 9, 2020 -Published by rnajournal.cshlp.org Downloaded from Rangan 16 a broader range of betacoronavirus sequences may enable the use of covariation signals for secondary structure prediction with tools like R-scape (Rivas, et al 2017).…”

Section: Discussionmentioning

confidence: 99%

RNA genome conservation and secondary structure in SARS-CoV-2 and SARS-related viruses: a first look

Rangan

Zheludev

Hagey

et al. 2020

RNA

242

401

View full text Add to dashboard Cite

As the COVID-19 outbreak spreads, there is a growing need for a compilation of conserved RNA genome regions in the SARS-CoV-2 virus along with their structural propensities to guide development of antivirals and diagnostics. Here we present a first look at RNA sequence conservation and structural propensities in the SARS-CoV-2 genome. Using sequence alignments spanning a range of betacoronaviruses, we rank genomic regions by RNA sequence conservation, identifying 79 regions of length at least 15 nucleotides as exactly conserved over SARS-related complete genome sequences available near the beginning of the COVID-19 outbreak. We then confirm the conservation of the majority of these genome regions across 739 SARS-CoV-2 sequences subsequently reported from the COVID-19 outbreak, and we present a curated list of 30 'SARS-related-conserved' regions. We find that known RNA structured elements curated as Rfam families and in prior literature are enriched in these conserved genome regions, and we predict additional conserved, stable secondary structures across the viral genome. We provide 106 'SARS-CoV-2-conserved-structured' regions as potential targets for antivirals that bind to structured RNA. We further provide detailed secondary structure models for the extended 5´ UTR, frame-shifting element, and 3´ UTR. Last, we predict regions of the SARS-CoV-2 viral genome that have low propensity for RNA secondary structure and are conserved within SARS-CoV-2 strains. These 59 'SARS-CoV-2-conserved-unstructured' genomic regions may be most easily targeted in primer-based diagnostic and oligonucleotidebased therapeutic strategies.Cold Spring Harbor Laboratory Press on June 9, 2020 -Published by rnajournal.cshlp.org Downloaded from , Connelly, et al. 2016, Spurgers, et al. 2008).Conserved structured RNA regions have already been shown to play critical functional roles in the life cycles of coronaviruses. Most coronavirus 5´ UTR's harbor at least four stem loops, with many showing heightened sequence conservation across betacoronaviruses, and various stems demonstrating functional roles in viral replication (Yang and Leibowitz 2015). Furthermore, RNA secondary structure in the 5´ UTR exposes a critical sequence motif, the transcriptional regulatory sequence (TRS), that forms long-range RNA interactions necessary for facilitating the discontinuous transcription characteristic to coronaviruses (van den Born, et al. 2005). Beyond the 5´ UTR, the frame-shifting element (FSE) in the first protein-coding ORF (ORF1ab) includes a pseudoknot structure that is necessary for the production of ORF1a and ORF1b from two Cold Spring Harbor Laboratory Press on June 9, 2020 -Published by rnajournal.cshlp.org Downloaded from Results RNA sequence conservation in SARS-related betacoronaviruses and SARS-CoV-2 Cold Spring Harbor Laboratory Press on June 9, 2020 -Published by rnajournal.cshlp.org Downloaded from 1. The first multiple sequence alignment (SARSr-MSA-1) was computed by aligning sequences curated by Ceraolo and Giorgi (Ceraolo and Giorgi 2...

show abstract

Section: Discussionmentioning

confidence: 99%

RNA genome conservation and secondary structure in SARS-CoV-2 and SARS-related viruses: a first look

Rangan

Zheludev

Hagey

et al. 2020

RNA

242

401

View full text Add to dashboard Cite

show abstract

“…Of particular importance in these steps is sequence alignment. HIVdb utilizes NucAmino [12] to initially align and identify amino acid mutations in each query sequence.…”

Section: Methodsmentioning

confidence: 99%

sierra-local: A lightweight standalone application for secure HIV-1 drug resistance prediction

Renaud

et al. 2018

Preprint

View full text Add to dashboard Cite

1Genotypic resistance interpretation systems for the prediction and interpretation of HIV-1 2 antiretroviral resistance are an important part of the clinical management of HIV-1 infection.3 Current interpretation systems are generally hosted on remote webservers that enable clinical 4 laboratories to generate resistance predictions easily and quickly from patient HIV-1 sequences 5 encoding the primary targets of modern antiretroviral therapy. However they also potentially 6 compromise a health provider's ethical, professional, and legal obligations to data security, 7 patient information confidentiality, and data provenance. Furthermore, reliance on web-based 8 algorithms makes the clinical management of HIV-1 dependent on a network connection. Here, 9 we describe the development and validation of sierra-local, an open-source implementation of 10 the Stanford HIVdb genotypic resistance interpretation system for local execution, which aims 11 to resolve the ethical, legal, and infrastructure issues associated with remote computing. This 12 package reproduces the HIV-1 resistance scoring by the web-based Stanford HIVdb algorithm 13 with a high degree of concordance (99.997%) and a higher level of performance than current 14 methods of accessing HIVdb programmatically. 15 INTRODUCTIONGenotype-based prediction of human immunodeficiency virus type 1 (HIV-1) drug resistance is an 16 important component for the routine clinical management of HIV-1 infection [1, 2]. Detecting the 17 presence of viruses carrying mutations that confer drug resistance enables physicians to select an 18 optimal drug combination for that patient's treatment regimen. Furthermore, genotyping by bulk # Corresponding author, apoon42@uwo.ca sequencing is a cost-effective alternative to the direct measurement of drug resistance from cultur-20 ing virus isolates in a laboratory [3]. Provided access to affordable bulk sequencing at an accredited 21 laboratory for clinical microbiology, the interpretation of HIV-1 sequence variation is the primary 22 obstacle to utilizing resistance genotyping for HIV-1 care. Fortunately, there are several HIV-1 23 drug resistance interpretation algorithms that can be accessed at no cost through web applications 24 or services hosted by remote network servers, such as the Standard University HIV Drug Resis-25 tance Database (HIVdb) [4], Agence Nationale de Recherche sur le SIDA (ANRS) AC11 [5], and 26 Rega Institute [6] algorithms. The Stanford HIVdb interpretation system can be accessed either 27 through a web browser at http://hivdb.stanford.edu/hivdb or programmatically through its Sierra 28 Web Service [7], which requires the transmission of an HIV-1 sequence from a local computer 29 over the network to the remote server. This is a convenient arrangement for clinical laboratories 30 because there is no need to install any specialized software, web browsers are ubiquitous and most 31 users are familiar with submitting web forms. 32 On the other hand, there are a number of disadvantages to accessing interpretatio...

show abstract

“…This purpose is best served by tools that utilize the information in putative exon boundary (i.e., donor/acceptor) sites like GeneWise (Birney, Clamp, & Durbin, 2004), sim4cc (Zhou, Pertea, Delcher, & Florea, 2009), NucAmino (Tzou, Huang, & Shafer, 2017), and others. Hence, for blastx and tblastn, the expected frequency for a match to occur with a given score on a purely random basis is six times higher than in blastp.…”

Section: Translated Blast Searchesmentioning

confidence: 99%

Finding Homologs in Amino Acid Sequences Using Network BLAST Searches

Ladunga

2017

CP in Bioinformatics

View full text Add to dashboard Cite

BLAST, the Basic Local Alignment Search Tool, is used more frequently than any other biosequence database search program. We show how to run searches on the Web, and demonstrate how to increase performance by fine-tuning arguments for a specific research project. We offer guidance for interpreting results, statistical significance and biological relevance issues, and suggest complementary analyses. This unit covers both protein-to-protein (blastp) searches and translated searches (blastx, tblastn, tfastx). blastx conceptually translates the query sequence and tblastn translates all nucleotide sequences in a database, while tblastx translates both the query and the database sequences into amino acid sequences. © 2017 by John Wiley & Sons, Inc.

show abstract

NucAmino: a nucleotide to amino acid alignment optimized for virus gene sequences

Cited by 12 publications

References 10 publications

RNA genome conservation and secondary structure in SARS-CoV-2 and SARS-related viruses: a first look

RNA genome conservation and secondary structure in SARS-CoV-2 and SARS-related viruses: a first look

sierra-local: A lightweight standalone application for secure HIV-1 drug resistance prediction

Finding Homologs in Amino Acid Sequences Using Network BLAST Searches

Contact Info

Product

Resources

About