Distributional profiles of homologous open reading frames among bacterial phyla: implications for vertical and lateral transmission. Free

Abstract

If open reading frames (ORFs) have been transmitted primarily by vertical descent, the distributional profile of orthologues of each ORF should be congruent with the organismal tree or a subtree thereof. Distributional patterns not reconciled parsimoniously with tree-like descent and loss are prima facie evidence of lateral gene transfer. Herein, a rigorous criterion for recognizing ORF distributions is described and implemented; it does not require the inference of phylogenetic trees, nor does it assume any specific tree. Because lineage-specific differences in rates of sequence change can also generate unexpected distributional patterns, rate artefacts were controlled for by requiring pairwise matches between ORFs to exceed a rigorous inclusion threshold, but absence of a match was assessed against a more-permissive exclusion threshold. Applying this dual-threshold criterion to cross-domain and cross-phylum distributional patterns for ORFs in 23 bacterial genomes, a relative abundance of ORFs was observed that find a match in exactly seven other bacterial phyla; 94-99% of these ORFs also find matches among the Archaea and/or Eukarya. In the larger (and some smaller) bacterial genomes, ORFs that find matches in exactly one other bacterial phylum are also relatively abundant, but fewer of these have non-bacterial homologues; most of their matches within the Bacteria are to the Proteobacteria and/or Firmicutes, which cannot be sister lineages to all bacteria. ORFs that are neither distributed universally among the Bacteria, nor necessarily shared with topologically adjacent lineages, are preferentially enriched in large bacterial genomes.

Loading

Article metrics loading...

/content/journal/ijsem/10.1099/00207713-52-3-777
2002-05-01
2024-03-29
Loading full text...

Full text loading...

http://instance.metastore.ingenta.com/content/journal/ijsem/10.1099/00207713-52-3-777
Loading

Most cited Most Cited RSS feed