PhiSiGns: an online tool to identify signature genes in phages and design PCR primers for examining phage diversity
1 College of Marine Science, University of South Florida, St. Petersburg FL 33701, USA
2 Department of Computer Sciences and Biology, San Diego State University, San Diego CA 92182, USA
3 Computational Science Research Center, San Diego State University, San Diego CA 92182, USA
4 Mathematics and Computer Science Division, Argonne National Laboratory, Argonne IL 60439, USA
BMC Bioinformatics 2012, 13:37 doi:10.1186/1471-2105-13-37Published: 4 March 2012
Phages (viruses that infect bacteria) have gained significant attention because of their abundance, diversity and important ecological roles. However, the lack of a universal gene shared by all phages presents a challenge for phage identification and characterization, especially in environmental samples where it is difficult to culture phage-host systems. Homologous conserved genes (or "signature genes") present in groups of closely-related phages can be used to explore phage diversity and define evolutionary relationships amongst these phages. Bioinformatic approaches are needed to identify candidate signature genes and design PCR primers to amplify those genes from environmental samples; however, there is currently no existing computational tool that biologists can use for this purpose.
Here we present PhiSiGns, a web-based and standalone application that performs a pairwise comparison of each gene present in user-selected phage genomes, identifies signature genes, generates alignments of these genes, and designs potential PCR primer pairs. PhiSiGns is available at (http://www.phantome.org/phisigns/ webcite; http://phisigns.sourceforge.net/ webcite) with a link to the source code. Here we describe the specifications of PhiSiGns and demonstrate its application with a case study.
PhiSiGns provides phage biologists with a user-friendly tool to identify signature genes and design PCR primers to amplify related genes from uncultured phages in environmental samples. This bioinformatics tool will facilitate the development of novel signature genes for use as molecular markers in studies of phage diversity, phylogeny, and evolution.