Viral Bioinformatics

Viral Bioinformatics enables analysis, annotation, comparison, and visualization of viral genomes to support gene discovery, comparative genomics, and evolutionary studies.

Key Features:

• Genome Annotation Transfer Utility (GATU): GATU transfers annotations from reference viral genomes to target genomes, detects open reading frames (ORFs) unique to the target, and outputs annotated sequences in GenBank, EMBL, or XML formats.
• Base-By-Base: Base-By-Base performs nucleotide-level comparisons of viral genomes, identifies and corrects alignment errors in large genome alignments, generates tabular and graphical outputs highlighting differences, and can connect to Virus Orthologous Clusters (VOCs) or accept text files for annotation data.
• Java-Dotter (JDotter): Java-Dotter generates dotplots of large DNA or protein sequences, operates as a client–server application for submission of sequences for alignment and retrieval of preprocessed dotplots, and accesses supplementary feature data from sequence databases or file systems.
• Viral Genome Organizer (VGO): VGO automates characterization and annotation of complete viral genomes, particularly large genomes such as poxviruses, integrates database search routines including FASTA, BLASTP, PSI-BLAST, and TBLASTN with a multiple-alignment viewer, generates self-dotplots to identify repeated genes and sequences, and produces restriction maps and PCR primer analyses.
• ReHAB (Recent Hits Acquired from BLAST): ReHAB compares PSI-BLAST search results across different versions of a protein sequence database to identify newly acquired protein hits and highlights those hits in tabular outputs.

Scientific Applications:

• Annotation Transfer: Reducing time to annotate new viral genomes by leveraging existing annotations from related reference genomes.
• Comparative Genomics: Identifying nucleotide-level variations that may influence phenotypic traits such as virulence through detailed genome comparisons.
• Genome Visualization: Visualizing alignments, dotplots, and self-dotplots to detect repeated sequences and alignment errors.
• Gene Discovery and Annotation: Discovering novel genes and supporting annotation through integrated database searches (FASTA, BLASTP, PSI-BLAST, TBLASTN) and ORF detection.
• Evolutionary Analysis: Identifying conserved gene families and orthologous clusters across viral species using VOCs and comparative alignments.

Methodology:

Methods include annotation transfer from reference genomes, ORF detection, nucleotide-level alignment and correction, database searches using FASTA, BLASTP, PSI-BLAST and TBLASTN, multiple-alignment viewing, dotplot and self-dotplot generation, restriction map and PCR primer analysis, and comparative PSI-BLAST result comparison across database versions.