Comparison of the genome sequences of non-pathogenic and pathogenic African swine fever virus isolates.

The genomic coding sequences, apart from the inverted terminal repeats and cross-links, have been determined for two African swine fever virus (ASFV) isolates from the same virus genotype, a non-pathogenic isolate from Portugal, OURT88/3, and a highly pathogenic isolate from West Africa, Benin 97/1. These genome sequences were annotated and compared with that of a tissue culture-adapted isolate, BA71V. The genomes range in length between 170 and 182 kbp and encode between 151 and 157 open reading frames (ORFs). Compared to the Benin 97/1 isolate, the OURT88/3 and BA71V isolates have deletions of 8-10 kbp that encode six copies of the multigene family (MGF) 360 and either one MGF 505/530 copy in the BA71V or two copies in the OURT88/3 isolate. The BA71V isolate has a deletion, close to the right end of the genome, of 3 kbp compared with the other isolates. The five ORFs in this region include an additional copy of an ORF similar to that encoding the p22 virus structural protein. The OURT88/3 isolate has interruptions in ORFs that encode a CD2-like and a C-type lectin protein. Variation between the genomes is observed in the number of copies of five different MGFs. The 109 non-duplicated ORFs conserved in the three genomes encode proteins involved in virus replication, virus assembly and modulation of the host's defences. These results provide information concerning the genetic variability of African swine fever virus isolates that differ in pathogenicity.

Comparative genomic analysis of the family Iridoviridae: re-annotating and defining the core set of iridovirus genes.

BACKGROUND: Members of the family Iridoviridae can cause severe diseases resulting in significant economic and environmental losses. Very little is known about how iridoviruses cause disease in their host. In the present study, we describe the re-analysis of the Iridoviridae family of complex DNA viruses using a variety of comparative genomic tools to yield a greater consensus among the annotated sequences of its members. RESULTS: A series of genomic sequence comparisons were made among, and between the Ranavirus and Megalocytivirus genera in order to identify novel conserved ORFs. Of these two genera, the Megalocytivirus genomes required the greatest number of altered annotations. Prior to our re-analysis, the Megalocytivirus species orange-spotted grouper iridovirus and rock bream iridovirus shared 99% sequence identity, but only 82 out of 118 potential ORFs were annotated; in contrast, we predict that these species share an identical complement of genes. These annotation changes allowed the redefinition of the group of core genes shared by all iridoviruses. Seven new core genes were identified, bringing the total number to 26. CONCLUSION: Our re-analysis of genomes within the Iridoviridae family provides a unifying framework to understand the biology of these viruses. Further re-defining the core set of iridovirus genes will continue to lead us to a better understanding of the phylogenetic relationships between individual iridoviruses as well as giving us a much deeper understanding of iridovirus replication. In addition, this analysis will provide a better framework for characterizing and annotating currently unclassified iridoviruses.

GraphDNA: a Java program for graphical display of DNA composition analyses.

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.

Predicted function of the vaccinia virus G5R protein.

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.

Genome Annotation Transfer Utility (GATU): rapid annotation of viral genomes using a closely related reference genome.

BACKGROUND: Since DNA sequencing has become easier and cheaper, an increasing number of closely related viral genomes have been sequenced. However, many of these have been deposited in GenBank without annotations, severely limiting their value to researchers. While maintaining comprehensive genomic databases for a set of virus families at the Viral Bioinformatics Resource Center http://www.biovirus.org and Viral Bioinformatics - Canada http://www.virology.ca, we found that researchers were unnecessarily spending time annotating viral genomes that were close relatives of already annotated viruses. We have therefore designed and implemented a novel tool, Genome Annotation Transfer Utility (GATU), to transfer annotations from a previously annotated reference genome to a new target genome, thereby greatly reducing this laborious task. RESULTS: GATU transfers annotations from a reference genome to a closely related target genome, while still giving the user final control over which annotations should be included. GATU also detects open reading frames present in the target but not the reference genome and provides the user with a variety of bioinformatics tools to quickly determine if these ORFs should also be included in the annotation. After this process is complete, GATU saves the newly annotated genome as a GenBank, EMBL or XML-format file. The software is coded in Java and runs on a variety of computer platforms. Its user-friendly Graphical User Interface is specifically designed for users trained in the biological sciences. CONCLUSION: GATU greatly simplifies the initial stages of genome annotation by using a closely related genome as a reference. It is not intended to be a gene prediction tool or a "complete" annotation system, but we have found that it significantly reduces the time required for annotation of genes and mature peptides as well as helping to standardize gene names between related organisms by transferring reference genome annotations to the target genome. The program is freely available under the General Public License and can be accessed along with documentation and tutorial from http://www.virology.ca/gatu.

Base-By-Base: single nucleotide-level analysis of whole viral genome alignments.

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.