Abstract

BackgroundClusters or runs of purines on the mRNA synonymous strand have been found in many different organisms including orthopoxviruses. The purine bias that is exhibited by these clusters can be observed using a purine skew and in the case of poxviruses, these skews can be used to help determine the coding strand of a particular segment of the genome. Combined with previous findings that minor ORFs have lower than average aspartate and glutamate composition and higher than average serine composition, purine content can be used to predict the likelihood of a poxvirus ORF being a "real gene".ResultsUsing purine skews and a "quality" measure designed to incorporate previous findings about minor ORFs, we have found that in our training case (vaccinia virus strain Copenhagen), 59 of 65 minor (small and unlikely to be a real genes) ORFs were correctly classified as being minor. Of the 201 major (large and likely to be real genes) vaccinia ORFs, 192 were correctly classified as being major. Performing a similar analysis with the entomopoxvirus amsacta moorei (AMEV), it was found that 4 major ORFs were incorrectly classified as minor and 9 minor ORFs were incorrectly classified as major. The purine abundance observed for major ORFs in vaccinia virus was found to stem primarily from the first codon position with both the second and third codon positions containing roughly equal amounts of purines and pyrimidines.ConclusionPurine skews and a "quality" measure can be used to predict functional ORFs and purine skews in particular can be used to determine which of two overlapping ORFs is most likely to be the real gene if neither of the two ORFs has orthologs in other poxviruses.

Highlights

  • Clusters or runs of purines on the mRNA synonymous strand have been found in many different organisms including orthopoxviruses

  • Chargaff's second parity rule states that for single-stranded DNA %A ≅ %T and %C ≅ %G [2,3] and implies that for regions with clusters of purines there must be local deviations from Chargaff's second parity rule favoring purines [4]. These local deviations from Chargaff's second parity rule known as Chargaff differences have been seen in a variety of organisms including vaccinia virus; Bell et al determined that Chargaff differences do correlate with direction of transcription and that the number of A nucleotides is greater than the number of T nucleotides in 83 of 92 vaccinia genes [4]

  • A characteristic "W" shaped plot can be seen for both graphs; in Figure 1b, this is the result of a trend for large blocks of genes to be transcribed in the same direction. These data indicate a good correlation between the purine content of the genomic DNA and the direction of transcription; for example, for genes that are transcribed in the leftward direction, the bottom/synonymous strand is purine rich and the opposite is true for genes that are transcribed to the right

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Summary

Introduction

Clusters or runs of purines on the mRNA synonymous strand have been found in many different organisms including orthopoxviruses. Chargaff's second parity rule states that for single-stranded DNA %A ≅ %T and %C ≅ %G [2,3] and implies that for regions with clusters of purines there must be local deviations from Chargaff's second parity rule favoring purines [4] These local deviations from Chargaff's second parity rule known as Chargaff differences have been seen in a variety of organisms including vaccinia virus; Bell et al determined that Chargaff differences do correlate with direction of transcription and that the number of A nucleotides is greater than the number of T nucleotides in 83 of 92 vaccinia genes [4]. Excluding ORFs that are smaller in size than the cut-off, risks missing genes that are unusually short; during annotation of vaccinia virus strain Copenhagen (VACV-COP) at least three recently verified genes (ranging from 162 bp – 231 bp) were not included in the initial annotation of the complete genome; these genes, VACV-COP A2.5L [5,6], A14.5L [7] and G5.5R [8] have been included in our Poxvirus Orthologous Clusters (POCs) database [9]

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