Genomic signatures in microbes -- properties and applications

The ratio of genomic oligonucleotide frequencies relative to the mean genomic AT/GC content has been shown to be similar for closely related species and, therefore, said to reflect a "genomic signature". The genomic signature has been found to be more similar within genomes than between closely related genomes. Furthermore, genomic signatures of closely related organisms are, in turn, more similar than more distantly related organisms. Since the genomic signature is remarkably stable within a genome, it can be extracted from only a fraction of the genomic DNA sequence. Genomic signatures, therefore, have many applications. The most notable examples include recognition of pathogenicity islands in microbial genomes and identification of hosts from arbitrary DNA sequences, the latter being of great importance in metagenomics. What shapes the genomic signature in microbial DNA has been readily discussed, but difficult to pinpoint exactly. Most attempts so far have mainly focused on correlations from in silico data. This mini-review seeks to summarize possible influences shaping the genomic signature and to survey a set of applications. KEYWORDS: genomics signatures, microbes, pathogenicity islands, nonhomologous DNA sequence comparisons BACKGROUND Biochemical experiments conducted in the early 1960s revealed remarkable species-specific patterns as measured using dinucleotide frequencies divided by corresponding mononucleotide frequencies, i.e., f(XY)/f(X)f(Y), X,Y={A,G,C,T(U)}, in genomic DNA METHODS TO EXTRACT THE GENOMIC SIGNATURE The genomic signature was originally computed by calculating all dinucleotide frequencies (16 in total) of a genomic DNA sequence divided by the corresponding nucleotide frequencies constituting the dinucleotide for RNA), from DNA sequence A, the genomic signature is found by calculating the ratios ρ = f A (XY)/f A (X)f A (Y) for every possible combination of dinucleotides XY. To compute the signature difference between two DNA sequences, A and B, a difference measure is typically used. Karlin et al. where n is the number of possible dinucleotide combinations (n = 16 for dinucleotides, n = 256 for tetranucleotides, etc.). It is sufficient to carry out analyses on one strand 717 information. There is only one example known to the author where the measure has been altogether dropped and cluster analysis been carried out directly on the computed ratios for all DNA sequences to assess phylogeny in the notation used above, other more advanced methods have been applied. Most notable of these is the second-order Markov chain model WHAT CAUSES THE GENOMIC SIGNATURE? Although the genomic signature was first revealed more than 40 years ago, its cause is difficult to understand, most likely due to many contributing factors APPLICATIONS A species-specific signal in microbial DNA sequences offers many applications. Originally, it was suggested that genomic signatures could be used for phylogenetic classifications and nonhomologous sequence comparisons Using genomic signatures, van Passel and coworkers were able to extract information about the nature of horizontal transfer in a strain of Vibrio vulnificus Although signature similarity is low between phages, plasmids, and host genomes the findings of Pride et al. indicate that viruses (both bacteriophages and eukaryotic viruses) coevolve with their Bohlin: Genomic Signatures in Microbes TheScientificWorldJOURNAL (2011) 11, 715-725 719 hosts The search for foreign genetic regions is often carried out by comparing the signature from a fraction of the genome, typically 5-to 20-kbp sliding windows, to the whole genome signature where n = 256 is the total number of tetranucleotide combinations. High OUV means bias in oligonucleotide usage, and low OUV means similarity between estimated and computed oligonucleotide frequencies. Low OUV is interpreted as increased genomic mutation rates, or lower bias in the oligonucleotide usage since the genomic oligonucleotide frequencies deviate less from the estimated oligonucleotide frequencies Bohlin: Genomic Signatures in Microbes TheScientificWorldJOURNAL (2011) 11, 715-725 721 Elhai found that the maximal-order Markov chain model approximated oligonucleotide frequencies in Escherichia coli poorly GENOMIC SIGNATURES: ADVANTAGES AND DRAWBACKS The signatures from genomic DNA sequences make possible comparison of nonhomologous DNA sequences and determine the phylogenetic relationship of the host to arbitrary DNA sequences. In addition, signature variations within microbial genomes are associated with pathogenicity islands and horizontally transferred DNA since it is believed that such genes have been subjected to different evolutionary pressures PROSPECTS The methods discussed here show that there are species-specific signals in genomic DNA sequences. The increasing number of sequenced genomes contains huge quantities of information that will require considerable computational power to analyze. Computational methods that can extract relevant information from only a fraction of a genome's DNA sequence are therefore of great importance. This ability is of great importance in metagenomics, which is becoming progressively more common and requires efficient tools to analyze the vast amounts of emerging data. The oligonucleotide frequencybased genomic signatures discussed here require relatively large amounts of genomic DNA, but it is conceivable that more advanced mathematical methods may be required, such as wavelet analysis and Bohlin: Genomic Signatures in Microbes TheScientificWorldJOURNAL (2011) 11, 715-725 722 FIGURE 2. Cluster analysis of 50 microbes based on genomic signatures of arbitrary pieces of 30-kbp DNA. The bacteria are clustered with respect to the genomic signatures from 30 kbp of arbitrary DNA sequences taken randomly from each genome (horizontal axis). The signature of each dinucleotide can be found on the vertical axis. The degree of shading from dark to light color indicates low and high frequency of occurrence, respectively, of the dinucleotide in question compared to what is expected from genomic AT/GC content. In other words, 30 kbp of genomic DNA was randomly picked from 50 predetermined prokaryotes ranging from AT-rich mycoplasmas to the GC-rich mycobacteria. It can be seen that closely related species and strains, with the notable exception of species from genera Mycoplasma and Bacillus, tend to cluster together, while the clustering of more distantly related microbes is more arbitrary. It can also be noticed that each dinucleotide clusters together with its reverse complement, indicating similar signatures even for small (i.e., 30 kbp) contigs. Bohlin: Genomic Signatures in Microbes TheScientificWorldJOURNAL (2011) 11, 715-725 723 fractal-based method