Bioinformatics as a first-line approach for understanding bacteriophage transcription

Abstract

Current approach to understanding bacteriophage transcription strategies during infection includes a combination of experimental and bioinformatics approaches, which is often time and resource consuming. Given the exponentially growing number of sequenced bacteriophage genomes, it becomes sensible asking to what extent one can understand bacteriophage transcription by using bioinformatics methods alone. We here argue that a suitable choice of computational methods may provide a highly efficient first-line approach for underst-anding bacteriophage transcription.

Keywords: bacteriophage transcription; bioinformatics analysis; computational genomics; genome analysis; promoter predictions; transcription start-site prediction.

Figure 1.

Flow-chart of the underlying steps in the bioinformatics analysis of phage genomes. For promoter prediction, which is the most challenging part of the analysis, the bioinformatic methods that can be employed are specified (rectangle boxes in the upper left part of the figure). Note that MLSA stands for Multiple Local Sequence Alignment, while PSWM stands for Position Specific Weight Matrix – these bioinformatic methods will be further discussed in the text.