Computational tools and Interoperability in Comparative ... - CBS

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Chapter 1 Introduction Introduction Since the publication of the first complete bacterial genome sequence in 1995 close to a thousand prokaryotes have been fully sequenced and made publicly available. These data represent large efforts by many scientists and technicians, closing gaps in the chromosomal sequences and providing detailed gene annotations. These genome projects constitute a valuable collection of prokaryotic diversity and they serve as an indispensable resource for comparative studies when novel features of newly discovered organisms are identified. We are however witnessing a transition phase as genome sequencing becomes a trivial step carried out by any researcher or company in the need of a better characterization of an organism. Sequencing equipment and the capability of assembling an entire genome will likely follow the same path as any other technological advance the world has seen. Telephones, cars, aeroplanes, and computers all have started as costly and clumsy attempts, and ended up as mainstream affordable and efficient products, taken for granted. Nothing will prevent sequencing technology to follow the same path and it will likely end up as a tiny desktop instrument on a doctor’s table next to the blood preasure measuring device. But the decreasing novelty of presenting a new genome sequence could cause a decline in the number of published genomes in the near future, causing less control and organization of these data, with fewer demands on data integrity, sequencing and annotation quality. Some major issues arrise as massive amounts of genomic data becomes a reality. There are signs that our ability to process and analyze genomic data is being overtaken by the technological developments of the sequencing equipment. For example, over the past twenty-five years, GenBank has grown roughly 100,000 fold, whereas the computer processing power, following Moore’s law has grown “only” a 1,000 times. The overwhelming data generated by modern sequencing machines constitite tough challenges for most biologist and although efforts are constantly being made to improve gene prediction and genome assembly software, these steps are not yet functioning in a scalable and unsupervised fashion. Further, post-annotation steps deriving knowledge from predicted genes remain one of the biggest challenges. How do we transform contigs of nucleotide sequences into knowledge to derive the phenotype of the organism? As more prokaryotic genomes are being sequenced, there are now a number of species for which multiple strains are sequenced. Roughly one fourth of all prokaryotic projects exist within species where 5 or more strains are available. As this coverage of diversity increases, we may begin to answer some key questions with better confidence. How do we define core sets of genes? Can we estimate the size of the pan genome? Which features are novel in selected strains and are these features regionally conserved within the chromosomes? To answer these questions, there is a fundamental need to visuzalize and overview the similarity and differences between larger number of genomes. Obtaining such an overview allows some questions concerning gene acquisition and chromosomal 1
organization to be answered. The development and refinement of the BLASTatlas method done during this Ph.D. project is an essential step forward enabling these types of analysis and the method is now offered as an online service by CBS. This work let to a publication in 2008, describing the BLASTatlas method. In chapter 2 a number of tools are described, which can assist rapid analysis of genomes, genomic contigs and larger collections of genomes to conclude the similarity. Enabling local and web based genome analysis tools for the novice user remains a critical point for the success of future sequencing projects. In chapter 3 the RNAmmer tool was used as a starting point to study the E. coli rrn tandem promotors. This work presents useful tools to model and visualize promotor conservation in genomes. The exchange of genomic data between users, sequencing centers, repositories, and tool providers currently lack standardizaion and interoperability. The lack of a formal way to exchange genomic data is a limiting factor as to how we in the future may exploit the wave of new genomic material being generated. Chapter 4 of this thesis describe a number of efforts made during this Ph.D. project to provide interoperabitlity and programmatic access to both prediction methods, genomic visualization methods as well as management of data standards. The outcome of this work has led CBS to adapt tools and server infrastructure thereby sharing its many tools in a way that allow programmers to insert sophistcated prediction methods directoy in their own programming environment. 2
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phylogenies based on alternative ho
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Figure 1 Phylogenetic tree of the 1
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25000 20000 15000 10000 5000 0 Pan
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Gap F 2M 2.5M Gap E 875k 750k 625k
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Table 2 A selection of genes locate
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4314 74 Tools Abstract: Of the plet
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4318 74 Tools Genome atlas Intrinsi
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4322 74 Tools for Comparison of Bac
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Chapter 3 rRNA operons and promoter
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Using HMMs also simplifies the use
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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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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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