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The reach of the genome signature in prokaryotes.

ABSTRACT: BACKGROUND: With the increased availability of sequenced genomes there have been several initiatives to infer evolutionary relationships by whole genome characteristics. One of these studies suggested good congruence between genome synteny, shared gene content, 16S ribosomal DNA identity, codon usage and the genome signature in prokaryotes. Here we rigorously test the phylogenetic signal of the genome signature, which consists of the genome-specific relative frequencies of dinucleotides, on 334 sequenced prokaryotic genome sequences. RESULTS: Intrageneric comparisons show that in general the genomic dissimilarity scores are higher than in intraspecific comparisons, in accordance with the suggested phylogenetic signal of the genome signature. Exceptions to this trend, (Bartonella spp., Bordetella spp., Salmonella spp. and Yersinia spp.), which have low average intrageneric genomic dissimilarity scores, suggest that members of these genera might be considered the same species. On the other hand, high genomic dissimilarity values for intraspecific analyses suggest that in some cases (e.g. Prochlorococcus marinus, Pseudomonas fluorescens, Buchnera aphidicola and Rhodopseudomonas palustris) different strains from the same species may actually represent different species. Comparing 16S rDNA identity with genomic dissimilarity values corroborates the previously suggested trend in phylogenetic signal, albeit that the dissimilarity values only provide low resolution. CONCLUSION: The genome signature has a distinct phylogenetic signal, independent of individual genetic marker genes. A reliable phylogenetic clustering cannot be based on dissimilarity values alone, as bootstrapping is not possible for this parameter. It can however be used to support or refute a given phylogeny and resulting taxonomy.

SUBMITTER: van Passel MW

PROVIDER: S-EPMC1621082 | biostudies-other | 2006

REPOSITORIES: biostudies-other

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The reach of the genome signature in prokaryotes.

van Passel Mark W J MW Kuramae Eiko E EE Luyf Angela C M AC Bart Aldert A Boekhout Teun T

BMC evolutionary biology 20061013

<h4>Background</h4>With the increased availability of sequenced genomes there have been several initiatives to infer evolutionary relationships by whole genome characteristics. One of these studies suggested good congruence between genome synteny, shared gene content, 16S ribosomal DNA identity, codon usage and the genome signature in prokaryotes. Here we rigorously test the phylogenetic signal of the genome signature, which consists of the genome-specific relative frequencies of dinucleotides, ...[more]

PMID: 17040564

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Project description:BACKGROUND: Overlapping genes (OGs) are defined as adjacent genes whose coding sequences overlap partially or entirely. In fact, they are ubiquitous in microbial genomes and more conserved between species than non-overlapping genes. Based on this property, we have previously implemented a web server, named OGtree, that allows the user to reconstruct genome trees of some prokaryotes according to their pairwise OG distances. By analogy to the analyses of gene content and gene order, the OG distance between two genomes we defined was based on a measure of combining OG content (i.e., the normalized number of shared orthologous OG pairs) and OG order (i.e., the normalized OG breakpoint distance) in their whole genomes. A shortcoming of using the concept of breakpoints to define the OG distance is its inability to analyze the OG distance of multi-chromosomal genomes. In addition, the amount of overlapping coding sequences between some distantly related prokaryotic genomes may be limited so that it is hard to find enough OGs to properly evaluate their pairwise OG distances. RESULTS: In this study, we therefore define a new OG order distance that is based on more biologically accurate rearrangements (e.g., reversals, transpositions and translocations) rather than breakpoints and that is applicable to both uni-chromosomal and multi-chromosomal genomes. In addition, we expand the term "gene" to include both its coding sequence and regulatory regions so that two adjacent genes whose coding sequences or regulatory regions overlap with each other are considered as a pair of overlapping genes. This is because overlapping of regulatory regions of distinct genes suggests that the regulation of expression for these genes should be more or less interrelated. Based on these modifications, we have reimplemented our OGtree as a new web server, named OGtree2, and have also evaluated its accuracy of genome tree reconstruction on a testing dataset consisting of 21 Proteobacteria genomes. Our experimental results have finally shown that our current OGtree2 indeed outperforms its previous version OGtree, as well as another similar server, called BPhyOG, significantly in the quality of genome tree reconstruction, because the phylogenetic tree obtained by OGtree2 is greatly congruent with the reference tree that coincides with the taxonomy accepted by biologists for these Proteobacteria. CONCLUSIONS: In this study, we have introduced a new web server OGtree2 at http://bioalgorithm.life.nctu.edu.tw/OGtree2.0/ that can serve as a useful tool for reconstructing more precise and robust genome trees of prokaryotes according to their overlapping genes.

Project description:BackgroundDNA word frequencies, normalized for genomic AT content, are remarkably stable within prokaryotic genomes and are therefore said to reflect a "genomic signature." The genomic signatures can be used to phylogenetically classify organisms from arbitrary sampled DNA. Genomic signatures can also be used to search for horizontally transferred DNA or DNA regions subjected to special selection forces. Thus, the stability of the genomic signature can be used as a measure of genomic homogeneity. The factors associated with the stability of the genomic signatures are not known, and this motivated us to investigate further. We analyzed the intra-genomic variance of genomic signatures based on AT content normalization (0(th) order Markov model) as well as genomic signatures normalized by smaller DNA words (1(st) and 2(nd) order Markov models) for 636 sequenced prokaryotic genomes. Regression models were fitted, with intra-genomic signature variance as the response variable, to a set of factors representing genomic properties such as genomic AT content, genome size, habitat, phylum, oxygen requirement, optimal growth temperature and oligonucleotide usage variance (OUV, a measure of oligonucleotide usage bias), measured as the variance between genomic tetranucleotide frequencies and Markov chain approximated tetranucleotide frequencies, as predictors.Principal findingsRegression analysis revealed that OUV was the most important factor (p<0.001) determining intra-genomic homogeneity as measured using genomic signatures. This means that the less random the oligonucleotide usage is in the sense of higher OUV, the more homogeneous the genome is in terms of the genomic signature. The other factors influencing variance in the genomic signature (p<0.001) were genomic AT content, phylum and oxygen requirement.ConclusionsGenomic homogeneity in prokaryotes is intimately linked to genomic GC content, oligonucleotide usage bias (OUV) and aerobiosis, while oligonucleotide usage bias (OUV) is associated with genomic GC content, aerobiosis and habitat.

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The reach of the genome signature in prokaryotes.

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The reach of the genome signature in prokaryotes.

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