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8 O. N. Reva et al. compiled into a structural profile of all upstream regions of A. borkumensis (see section Experimental procedures). The profile uses z-scores to measure how the average value of the properties vary from minus 400 bp to 400 bp around the translation start (Fig. 7). A. borkumensis has only a coding density of 87% causing a wider spacer of the intergenic region and this appears to give rise to a larger and wider peak of curvature, stacking energy and AT content (Fig. 7A). For comparison we also analysed the promoter profile of another ocean bacterium, Candidatus Pelagibacter ubique HTCC1062 (Giovannoni et al., 2005), an example of a highly streamlined genome with a coding density of 96%. Here we observed a much weaker curvature signal, and the distribution of stacking energy and AT content was more narrow and had higher maxima (Fig. 7B). Next, the probability of opening during stress-induced DNA duplex destabilization was computed by using the program SIDD (Wang et al., 2004), covering five different values of the super-helical density s = {-0.025, -0.035, -0.045, -0.055, -0.065}. As super-coiling is being pushed, the probability of opening increases at lower super-helical densities in A. borkumensis (Fig. 7C). In contrast, a narrower SIDD profile that exhibits only minor dependence on super-helical density (Fig. 7D), was calculated for the Candidatus Pelagibacter ubique HTCC1062 genome. The structural profile for the promoter regions of A. borkumensis was compared with that of closely related species as found above (see Fig. 4). Generally, it looked more like the promoter profile of members of the Pseudomonadales than the general comparison organism, E. coli. Moreover, the promoter profile was very different compared with the promoter profile of X. fastidiosa strains, even though they where very similar with regard to their TU profile (see Fig. 4). The promoter profiles for the above mentioned organisms may be found at our website (http://www.cbs.dtu.dk/services/GenomeAtlas/). Amino acid and codon usage We have examined the codon and amino acid usage of A. borkumensis and compared this with both the usage of bacteria in general and of 16 oceanic bacteria (Entrez project IDs 230, 10 645, 12 530, 13 233, 13 239, 13 282, 13 642, 13 643, 13 654, 13 655, 13 902, 13 906, 13 910, 13 911, 13 989, 15 660) Willenbrock et al., 2006). In Fig. 8, the codon usage plot of A. borkumensis is superimposed on the cumulative plot of all completely sequenced bacteria in public databases (N = 518, Fig. 8A) or of that of 16 oceanic bacteria (Fig. 8B). A few codons are differentially utilized in A. borkumensis (GUC, CUG), but all values are within the range of three standard deviations. In other words, codon usage of A. borkumensis resides within the typical range of eubacteria. Interestingly, the sequenced oceanic bacteria share a very similar amino acid usage (Fig. 8D), whereas broad variations thereof were noted amongst all sequenced bacteria that represent the whole spectrum of habitats (Fig. 8C). A. borkumensis roughly follows the profile of the oceanic bacteria, although cysteine, tryptophan, leucine, proline, arginine, serine are under-utilized, and glutamic acid, lysine, phenylalanine, histidine, methionine, and tyrosine are over-utilized – all exceeding the threestandard deviation boundaries. Conclusion Fig. 7. Profile of structural properties of promoter regions (A and B) and probabilities of opening during stress-induced DNA duplex destabilization at various super-helical densities (C and D) in the A. borkumensis SK2 (A and C) and Candidatus Pelagibacter ubique HTCC1062 (B and D) chromosomes. Each annotated gene was aligned at the translation start site and the average values for the SIDD probabilities, AT-content, position preference, stacking energy, intrinsic curvature and DNase sensitivity were calculated at each position in the alignment. The values were subsequently converted into z-scores, using the average and standard deviation of the entire chromosome. Values are smoothed over a 5 bp window. Inspection of the collected phylogenetic connections revealed that the most closely related organisms are Acinetobacter sp. and Pseudomonas aeruginosa, ©2007TheAuthors Journal compilation © 2007 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology
although in trees where both Pseudomonas and Acinetobacter are present, A. borkumensis tends to cluster more often with the latter one. The major structural feature of the A. borkumensis chromosome is its symmetry and homogeneity. The genome contains only very few regions with extraordinarily low or high curvature, position preference or base stacking energy. The chromosomal frame is symmetric: The origin and the terminus of replication are located opposite to each other in the chromosome and are clearly discerned by maxima of oligonucleotide usage biases between leading and lagging strand. The genetic repertoire of A. borkumensis is most similar to that of Acinetobacter and P. aeruginosa. Moreover, Comparative genomics of Alcanivorax borkumensis 9 Fig. 8. Codon usage (A and B) and amino acid usage (C and D) of A. borkumensis SK2 compared with those of 518 completely sequenced bacteria (A and C) or compared with those of 16 sequenced oceanic bacteria. Frequencies of amino acids and codons were counted for each genome and normalized. Mean value (grey line) and three standard deviations (grey solid area) represent the global usage of individual codons (A and B) and amino acids (C and D) in the 518 (A and C) or 16 (B and D) reference genomes. The red line (A and B) shows the codon usage and the blue line (C and D) shows the amino acid usage of A. borkumensis. A. borkumensis shares a similar oligonucleotide usage with the Xanthomonadales and Pseudomonadales indicating close phylogenetic relationships with these orders in accordance with 16S rDNA sequence relatedness (Schneiker et al., 2006). Amongst this subgroup of completely sequenced genomes, the A. borkumensis chromosome harbours the relatively lowest number of genome islands with atypical tetranucleotide usage. P. putida KT2440, for example, carries threefold more islands per Megabase in its chromosome (Weinel et al., 2002). Interestingly, one of the three enzyme systems that are upregulated in alkane-grown cells (Sabirova et al., 2006), the well-known alkB1 cluster, is encoded by genome islands. The molecular evolution of the alk genes that are ©2007TheAuthors Journal compilation © 2007 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology
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Peter Fischer Hallin | 2009 Peter F
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Preface This Ph.D. thesis is writte
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thesis, the work is just being publ
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ved at blive publiceret i Standards
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Paper VI [Lagesen K, Hallin P] 1 ,
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3.3.3 Refining E. coli and Shigella
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xviii 2.17 Pan- and core-genome plo
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Chapter 1 Introduction Introduction
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Chapter 2 Comparative Genomics 2.1
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Comparative Genomics the publicly a
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Comparative Genomics source CDS tot
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Comparative Genomics 1 mysql -N -B
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Listing 2.8: R code to generate a 2
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1st U C A G U 2nd position C A G 3r
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1st U C A G U 2nd position C A G 3r
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Escherichia coli strain K-12, subst
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1 rRNA operons and promoter analysi
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Using HMMs also simplifies the use
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Information content Information con
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of the annotation. Some of the majo
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where match states stop around 10 c
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1 rRNA operons and promoter analysi
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synthesis in flow cells to simultan
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Read absence. A boolean where ‘on
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Hallin, et al. Figure 4 | The dataf
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Genome homology: Comparing multiple
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ing platform-‐independent Java
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34. Wang H, Noordewier M, Benham CJ
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Chapter 4 Web Services and Interope
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Web Services and Interoperability i
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Chapter 5 Conclusion and perspectiv
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Appendix A Appendix: Workshops, tea
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Appendix B Appendix: Ph.D. study pl
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Danmarks Tekniske Universitet AFI,
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Danmarks Tekniske Universitet AFI,
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Appendix C Appendix: Courses C.1 Gl
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D.2 Sample output from queryGenomes
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Appendix: Software 13 w a r n " $ o
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Appendix: Software 109 m y ( $ m i
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Appendix: Software 25 [ ] A l t e r
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BIBLIOGRAPHY J. Rogers, P. F. Stadl
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BIBLIOGRAPHY Q. Jin, Z. Yuan, J. Xu
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BIBLIOGRAPHY Velicer, F.-J. Vorholt
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