Detecting overlapping coding sequences in virus genomes

Abstract

BACKGROUND: Detecting new coding sequences (CDSs) in viral genomes can be difficult for several reasons. The typically compact genomes often contain a number of overlapping coding and non-coding functional elements, which can result in unusual patterns of codon usage; conservation between related sequences can be difficult to interpret – especially within overlapping genes; and viruses often employ non-canonical translational mechanisms – e.g. frameshifting, stop codon read-through, leaky-scanning and internal ribosome entry sites – which can conceal potentially coding open reading frames (ORFs). RESULTS: In a previous paper we introduced a new statistic – MLOGD (Maximum Likelihood Overlapping Gene Detector) – for detecting and analysing overlapping CDSs. Here we present (a) an improved MLOGD statistic, (b) a greatly extended suite of software using MLOGD, (c) a database of results for 640 virus sequence alignments, and (d) a web-interface to the software and database. Tests show that, from an alignment with just 20 mutations, MLOGD can discriminate non-overlapping CDSs from non-coding ORFs with a typical accuracy of up to 98%, and can detect CDSs overlapping known CDSs with a typical accuracy of 90%. In addition, the software produces a variety of statistics and graphics, useful for analysing an input multiple sequence alignment. CONCLUSION: MLOGD is an easy-to-use tool for virus genome annotation, detecting new CDSs – in particular overlapping or short CDSs – and for analysing overlapping CDSs following frameshift sites. The software, web-server, database and supplementary material are available at