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1 rRNA operons and promoter analysis 3.9 Paper VII: GeneWiz browser: An Interactive Tool for Visualizing Sequenced Chromosomes 131
Standards in Genomic Sciences (2009) 1: 204-215 DOI:10.4056/sigs.28177 GeneWiz browser: An Interactive Tool for Visualizing Sequenced Chromosomes Peter F. Hallin 1 , Hans-Henrik Stærfeldt 1 , Eva Rotenberg 1, 2 , Tim T. Binnewies 1, 3 , Craig J. Benham 4 , and David W. Ussery 1 1 Center for Biological Sequence Analysis, Department of Systems Biology, The Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. 2 Lersoe Parkalle 37, 2TV, 2100 Copenhagen, Denmark 3 Roche Diagnostics Ltd., CH-6343 Rotkreuz, Switzerland 4 UC Davis Genome Center, University of California, Davis, California, U.S.A. We present an interactive web application for visualizing genomic data of prokaryotic chromosomes. The tool (GeneWiz browser) allows users to carry out various analyses such as mapping alignments of homologous genes to other genomes, mapping of short sequencing reads to a reference chromosome, and calculating DNA properties such as curvature or stacking energy along the chromosome. The GeneWiz browser produces an interactive graphic that enables zooming from a global scale down to single nucleotides, without changing the size of the plot. Its ability to disproportionally zoom provides optimal readability and increased functionality compared to other browsers. The tool allows the user to select the display of various genomic features, color setting and data ranges. Custom numerical data can be added to the plot allowing, for example, visualization of gene expression and regulation data. Further, standard atlases are pre-generated for all prokaryotic genomes available in GenBank, providing a fast overview of all available genomes, including recently deposited genome sequences. The tool is available online from http://www.cbs.dtu.dk/services/gwBrowser. Supplemental material including interactive atlases is available online at http://www.cbs.dtu.dk/services/gwBrowser/suppl/. Introduction The development of fast and inexpensive genome sequencing technologies has led to the generation of vast amounts of genomic information. As ge-‐ nomic sequencing becomes both more powerful and affordable, the handling and analysis of the generated data produces novel challenges and shifts the focus away from the discovery process towards technical considerations of handling, storing and analyzing sequence data. An impor-‐ tant step when exploring a new genome is to com-‐ pare it to existing sequences, in order to identify both novel and conserved features. Many auto-‐ mated computational methods are available that attempt to derive protein function from sequence [1-3]. In a metagenomic study by Harrington and co-‐workers it was estimated that 76% of the ex-‐ amined protein coding genes could be assigned a function. However, to assess predictions for indi-‐ vidual genes the visualization remains critical to provide the biologist with an overview of the ge-‐ nomic context. Are genes of interest situated in clusters? In operons? How are they regulated? How does their DNA base composition compare with that of the rest of the genome? In order to display such features both on a genome scale and in close-‐up down to the level of nucleotides, we developed the GeneWiz browser which is based on the ‘Genome Atlas’ concept [4,5]. This tool can also display local DNA structural properties, so that regulatory or repeat regions can easily be identified and interpreted in a chromosomal con-‐ text. During development of the GeneWiz browser, it became apparent that novel sequencing technolo-‐ gy creates a further demand. The current genera-‐ tion of sequencing instruments utilizes primed The Genomic Standards Consortium
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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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xvi
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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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Comparative Genomics
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3M 2.5M 3.5M 2.5M 2M 0M 2M 0.5M B.
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Streptococcus Escherichia Bacillus
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2.4 Summary Comparative Genomics Th
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Comparative Genomics 2.5 Instant in
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‘ReSourCe is he best online submi
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up to a total of 41 different E. co
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Fig. 2 Genes (or segments) from eac
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Fig. 5 BLASTatlas of Clostridium bo
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different applications, such as ide
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1 Comparative Genomics 2.7 Paper II
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166 literally millions of bacterial
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168
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170 resistance genes on mobile gene
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172 involved in generating diversit
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174 recipient DNA. A feature observ
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176 Fig. 5 Genome length distributi
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178
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180 reasons why organisms remain un
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182 A final problem has to do with
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184 Middendorf B, Hochhut B, Leipol
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1 Comparative Genomics 2.8 Paper II
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2 O. N. Reva et al. Fig. 1. Genome
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1 2.9 Paper IV: The origins of Vibr
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phylogenies based on alternative ho
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Figure 1 Phylogenetic tree of the 1
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Page 108 and 109: Table 2 A selection of genes locate
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Page 114 and 115: 4314 74 Tools Abstract: Of the plet
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Page 164 and 165: ing platform-‐independent Java
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Page 178 and 179: Chapter 5 Conclusion and perspectiv
Page 180 and 181: Appendix A Appendix: Workshops, tea
Page 182 and 183: Appendix B Appendix: Ph.D. study pl
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Page 188 and 189: Appendix C Appendix: Courses C.1 Gl
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Page 196 and 197: Appendix: Software 25 [ ] A l t e r
Page 198 and 199: BIBLIOGRAPHY J. Rogers, P. F. Stadl
Page 200 and 201: BIBLIOGRAPHY Q. Jin, Z. Yuan, J. Xu
Page 202 and 203: BIBLIOGRAPHY Velicer, F.-J. Vorholt
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