SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:[email protected].

A suffix tree is a fundamental data structure for string searching algorithms. Unfortunately, when it comes to the use of suffix trees in real-life applications, the current methods for constructing suffix trees do not scale for large inputs. All the existing practical algorithms perform random access to the input string, thus requiring that the input be small enough to be kept in main memory.

We propose a new method to build persistent suffix trees for indexing the genomic data. Our algorithm DiGeST (Disk-Based Genomic Suffix Tree) improves significantly over previous work in reducing the random access to the input string and performing only two passes over disk data. DiGeST is based on the two-phase multi-way merge sort paradigm using a concise binary representation of the DNA alphabet. Furthermore, our method scales to larger genomic data than managed before.

We investigate the k-LCS problem that is finding a longest common subsequence (LCS) for k given input strings. The problem is known to have practical solutions for k = 2, but for higher dimensions it is not very well explored. We consider the algorithms by Miller and Myers as well as Wu et al. which solve the 2-LCS problem, and shed a new light on their generalization to higher dimensions. First, we redesign both algorithms such that the generalization to higher dimensions becomes natural. Then we present our algorithms for solving the k-LCS problem. We further propose a new approach to reduce the algorithms' space complexity. We demonstrate that our algorithms are practical as they significantly outperform the dynamic programming approaches. Our results stand in contrast to observations made in previous work by Irving and Fraser.

BACKGROUND: Under conditions of no strand bias the number of Gs is equal to that of Cs for each DNA strand; similarly, the total number of Ts is equal to that of As. However, within each strand there are considerable local deviations from the A = T and G = C equality. These asymmetries in nucleotide composition have been extensively analyzed in prokaryotic and eukaryotic genomes and related to chromosome organization, transcription orientation and other processes in certain organisms. To carry out analysis of intra-strand nucleotide distribution several graphical methods have been developed. RESULTS: GraphDNA is a new Java application that provides a simple, user-friendly interface for the visualization of DNA nucleotide composition. The program accepts GenBank, EMBL and FASTA files as an input, and it displays multiple DNA nucleotide composition graphs (skews and walks) in a single window to allow direct comparisons between the sequences. We illustrate the use of DNA skews for characterization of poxvirus and coronavirus genomes. CONCLUSION: GraphDNA is a platform-independent, Open Source, tool for the analysis of nucleotide trends in DNA sequences. Multiple sequence formats can be read and multiple sequences may be plotted in a single results window.

MOTIVATION: Of the approximately 200 proteins that have been identified for the vaccinia virus (VACV) genome, many are currently listed as having an unknown function, and seven of these are also found in all other poxvirus genomes that have been sequenced. The G5R protein of VACV is included in this list, and to date, very little is known about this essential and highly conserved protein. Conventional similarity searches of protein databases do not identify significantly similar proteins, and experimental approaches have been unsuccessful at determining protein function. RESULTS: Using HHsearch, a hidden Markov model (HMM) comparison search tool, the G5R protein was found to be similar to both human and archaeal flap endonucleases (FEN-1) with 96% probability. The G5R protein structure was subsequently successfully modeled using the Robetta protein structure prediction server with an archaeal FEN-1 as the template. The G5R model was then compared to the human FEN-1 crystal structure and was found to be structurally similar to human FEN-1 in both active site residues and DNA substrate binding regions.

BACKGROUND: Recent, rapid growth in the quantity of available genomic data has generated many protein sequences that are not yet biochemically classified. Thus, the prediction of biochemical function based on structural motifs is an important task in post-genomic analysis. The InterPro databases are a major resource for protein function information. For optimal results, these databases should be searched at regular intervals, since they are frequently updated. RESULTS: We describe here a new program JIPS (Java GUI for InterProScan), a tool for tracking and viewing results obtained from repeated InterProScan searches. JIPS stores matches (in a local database) obtained from InterProScan searches performed with multiple versions of the InterPro database and highlights hits that have been added since the last search of the InterPro database. Results are displayed in an easy-to-use tabular format. JIPS also contains tools to assist with ortholog-based comparative studies of protein signatures. CONCLUSION: JIPS is an efficient tool for performing repeated InterProScans on large batches of protein sequences, tracking and viewing search results, and mining the collected data.

BACKGROUND: Sequence similarity searching is a powerful tool to help develop hypotheses in the quest to assign functional, structural and evolutionary information to DNA and protein sequences. As sequence databases continue to grow exponentially, it becomes increasingly important to repeat searches at frequent intervals, and similarity searches retrieve larger and larger sets of results. New and potentially significant results may be buried in a long list of previously obtained sequence hits from past searches. RESULTS: ReHAB (Recent Hits Acquired from BLAST) is a tool for finding new protein hits in repeated PSI-BLAST searches. ReHAB compares results from PSI-BLAST searches performed with two versions of a protein sequence database and highlights hits that are present only in the updated database. Results are presented in an easily comprehended table, or in a BLAST-like report, using colors to highlight the new hits. ReHAB is designed to handle large numbers of query sequences, such as whole genomes or sets of genomes. Advanced computer skills are not needed to use ReHAB; the graphics interface is simple to use and was designed with the bench biologist in mind. CONCLUSIONS: This software greatly simplifies the problem of evaluating the output of large numbers of protein database searches.

UNLABELLED: Java-Dotter (JDotter) is a platform-independent Java interactive interface for the Linux version of Dotter, a widely used program for generating dotplots of large DNA or protein sequences. JDotter runs as a client-server application and can send new sequences to the Dotter program for alignment as well as rapidly access a repository of preprocessed dotplots. JDotter also interfaces with a sequence database or file system to display supplementary feature data. Thus, JDotter greatly simplifies access to dotplot data in laboratories that deal with large numbers of genomes and have a multi-platform organization. AVAILABILITY: Currently, JDotter is used via Java Web Start by the Poxvirus Bioinformatics Resource for examining dotplots of complete poxvirus genomes; http://athena.bioc.uvic.ca/pbr/jdotter/. The software is available for download from the same location. SUPPLEMENTARY INFORMATION: Installation instructions, the User's Manual, screenshots and examples are available at the JDotter home page http://athena.bioc.uvic.ca/pbr/jdotter/. The software and source code is free for non-commercial applications.

BACKGROUND: With ever increasing numbers of closely related virus genomes being sequenced, it has become desirable to be able to compare two genomes at a level more detailed than gene content because two strains of an organism may share the same set of predicted genes but still differ in their pathogenicity profiles. For example, detailed comparison of multiple isolates of the smallpox virus genome (each approximately 200 kb, with 200 genes) is not feasible without new bioinformatics tools. RESULTS: A software package, Base-By-Base, has been developed that provides visualization tools to enable researchers to 1) rapidly identify and correct alignment errors in large, multiple genome alignments; and 2) generate tabular and graphical output of differences between the genomes at the nucleotide level. Base-By-Base uses detailed annotation information about the aligned genomes and can list each predicted gene with nucleotide differences, display whether variations occur within promoter regions or coding regions and whether these changes result in amino acid substitutions. Base-By-Base can connect to our mySQL database (Virus Orthologous Clusters; VOCs) to retrieve detailed annotation information about the aligned genomes or use information from text files. CONCLUSION: Base-By-Base enables users to quickly and easily compare large viral genomes; it highlights small differences that may be responsible for important phenotypic differences such as virulence. It is available via the Internet using Java Web Start and runs on Macintosh, PC and Linux operating systems with the Java 1.4 virtual machine.

Abstract Summary: Poxvirus Orthologous Clusters (POCs) is a JAVA client–server application which accesses an updated database containing all complete poxvirus genomes; it automatically groups orthologous genes into families based on BLASTP scores for assessment by a human database curator. POCs has a user-friendly interface permitting complex SQL queries to retrieve interesting groups of DNA and protein sequences as well as gene families for subsequent interrogation by a variety of integrated tools: BLASTP, BLASTX, TBLASTN, Jalview (multiple alignment), Dotlet (Dotplot), Laj (local alignment), and NAP (nucleotide to amino acid alignment). Availability: Direct access to the POCs database via the GENOME ANALYSIS link at the Poxvirus Bioinformatics Resource: http://www.poxvirus.org. The Software is available for download via HTTP at: http://athena.bioc.uvic.ca/pbr/POCs/pocs.html. Contact: [email protected] Supplementary Information: Installation instructions, the User's Manual, screenshots, and examples are available at the POCs home page http://athena.bioc.uvic.ca/pbr/POCs/pocs.html. The software is free for non-commercial applications. For information on poxviruses see http://www.poxvirus.org. * To whom correspondence should be addressed.

UNLABELLED: BLAST Search Updater (BSU) can help molecular biologists perform large numbers of BLAST searches routinely and screen the results for novel matches. The search result files (HTML format) and delta files (novel matches) are WWW viewable and BSU also emails users alignments of new matches. AVAILABILITY: BSU runs on UNIX machines and is freely available to academic users at http://athena.bioc.uvic.ca/genomes/. Additional figures and description are also available. CONTACT: [email protected]

SUMMARY: The Viral Genome DataBase (VGDB) contains detailed information of the genes and predicted protein sequences from 15 completely sequenced genomes of large (&100 kb) viruses (2847 genes). The data that is stored includes DNA sequence, protein sequence, GenBank and user-entered notes, molecular weight (MW), isoelectric point (pI), amino acid content, A + T%, nucleotide frequency, dinucleotide frequency and codon use. The VGDB is a mySQL database with a user-friendly JAVA GUI. Results of queries can be easily sorted by any of the individual parameters. AVAILABILITY: The software and additional figures and information are available at http://athena.bioc.uvic.ca/genomes/index.html .