Computational tools and Interoperability in Comparative ... - CBS

More documents

Recommendations

Info

4314 74 Tools Abstract: Of the plethora of bioinformatical tools available, some useful tools that allow complete genome sequences to be compared are described here. Comparisons of genome length, base composition, gene density, numbers of tRNA and rRNA genes, and codon usage can provide useful biological insights. Examples are provided of a Genome Atlas plot, to summarize many features of a single genome, and a BLAST Atlas, in which multiple genomes can be combined. A table of web-services for useful tools is provided. 1 Introduction Presently, there are about 900 bacterial and archaeal genomes that have been fully sequenced and become publicly available 1 and their number more than doubled last year. Approximately 40% of the sequenced genomes are obtained from environmental (terrestrial and marine) organisms. In addition, metagenomic projects are now producing a vast amount of sequences. Here we provide a brief overview of methods to compare sequenced bacterial genomes. Of the many methods available to compare bacterial genomes (Binnewies et al., 2006) > Table 1 lists several that we find useful. It is beyond the scope of this review to provide a detailed analysis of these methods, and the list is far from complete. The tools discussed here provide some interesting information on fundamental biological features and can be used to compare a few or large numbers of genomes. The tools are easy to use and produce results that are easy to interpret and can be graphically represented. The latter is an important quality determinant of any sequence analysis tool when dealing with genomes, as the complexity of input data is so large. 2 Genomic DNA Sequence Comparisons A genome can be more than one DNA molecule. Approximately 10% of the bacterial genomes sequenced so far have more than one chromosome. By definition a genome includes all chromosomes (and plasmids) that constitute an organism’s total DNA. Chromosomes are essential, single-copy, independently replicating DNA molecules present in each member of the species. Some species contain plasmids; these are frequently strain-specific and sometimes (incorrectly, in our opinion) omitted from a genome sequence. At the time of writing, the largest bacterial genome sequenced is that of Solibacter usitatus (strain Ellin 6076), a soil bacterium belonging to the Acidobacteria. It consists of a single chromosome of 9.97 mega basepairs (Mbp). The smallest bacterial genome known is that of Carsonella ruddii (PV), an endosymbiont of a plant sap-feeding insect with a mere 159,662 bp. Genome size is a rough indicator of biological adaptive potential so it is no surprise that soil bacteria have bigger genomes, as they have to adapt to environmental variation, whereas the protective niche of an endosymbiont allows for a small genome. The genome size of an organism is easy to calculate and tabulate. > Figure 1a gives a graphical representation for genome size variation within bacterial phyla. A ‘‘box and whiskers’’ plot as shown in > Fig. 1 visualizes the distribution of a property that can be 1 Completed genome statistics obtained from the NCBI Genome Project web pages: http://www.ncbi.nlm.nih.gov/ genomes/lproks.cgi for Comparison of Bacterial Genomes
. Table 1 Methods for comparison of bacterial genomes Method URL References Length, %GC http://www.ncbi.nlm.nih.gov/genomes/lproks.cgi Wheeler et al. (2007) Chromosome alignment (ACT) Chromosome alignment (MUMMER) http://www.sanger.ac.uk/Software/ACT/ Carver et al. (2005) http://www.webact.org/WebACT/home http://mummer.sourceforge.net Kurtz et al. (2004) Repeats – various http://www.cbs.dtu.dk/services/GenomeAtlas Ussery et al. (2004) Repeats – tetranucleotides Repeats – short, tandem Tools for Comparison of Bacterial Genomes 74 http://www.megx.net/tetra Teeling et al. (2004) http://minisatellites.u-psud.fr/GPMS/default.php Denoeud and Vergnaud (2004) Repeats – VNTRs http://vntr.csie.ntu.edu.tw Chang et al. (2007) Replication Origins http://www.cbs.dtu.dk/services/GenomeAtlas Worning et al. (2006) Noncoding RNAs http://rfam.sanger.ac.uk Griffiths-Jones, et al. (2005) rRNAs http://www.cbs.dtu.dk/services/RNAmmer Lagesen et al. (2007) Genome Atlas http://www.cbs.dtu.dk/services/GenomeAtlas Hallin and Ussery (2004) BLAST Atlas (zoomable) http://www.cbs.dtu.dk/services/gwBrowser UPDATE! ‘‘Genome Properties’’ http://cmr.tigr.org/tigr-scripts/CMR/shared/ GenomePropertiesHomePage.cgi Hallin and Ussery (2004) Selengut et al. (2007) 4315 expressed as a numerical value, such as length, %GC, number of genes, etc. Such plots show the spread of the data and are made as follows: the values are sorted and divided into two equal parts, separated by the median, which is marked as a bar in the middle of the distribution. A box is drawn to cover the range where the middle 50% of the data are (excluding the first 25% and the last 25% of the data). The ‘‘whiskers’’ are the hatched lines, connecting the lowest (left) and highest (right) values, with the exception of outlier points, which are shown as individual dots. Outliers are defined as data that are distant by more than 1.5 times the range of the box. The base composition of genomes, i.e., their %GC content (or %AT which together make 100%), can also be compared, as shown in > Fig. 1b. The GC content of a genome can range from 17% in C. ruddii to 75% GC in Anaeromyxobacter dehalogenans. The smallest genome is also the most AT rich, and many of the larger genomes are quite GC rich. It is not clear if there is a biological force in play behind this correlation, although it has been observed that the ecological niche an organism occupies roughly correlates to both genome size and GC content (Foerstner et al., 2005, Musto et al., 2006). In addition to the average GC content for a whole genome, local variation within a given genome can be examined, and this reveals two general trends for almost all bacterial genomes. First, on a more global, chromosomal level a large region flanking the origin of DNA
Page 1 and 2:
Peter Fischer Hallin | 2009 Peter F
Page 4:
Preface This Ph.D. thesis is writte
Page 7 and 8:
thesis, the work is just being publ
Page 9 and 10:
ved at blive publiceret i Standards
Page 11 and 12:
viii
Page 13 and 14:
Paper VI [Lagesen K, Hallin P] 1 ,
Page 15 and 16:
xii
Page 17 and 18:
3.3.3 Refining E. coli and Shigella
Page 19 and 20:
xvi
Page 21 and 22:
xviii 2.17 Pan- and core-genome plo
Page 24 and 25:
Chapter 1 Introduction Introduction
Page 26 and 27:
Chapter 2 Comparative Genomics 2.1
Page 28 and 29:
Comparative Genomics the publicly a
Page 30 and 31:
Comparative Genomics source CDS tot
Page 32 and 33:
Comparative Genomics 1 mysql -N -B
Page 34 and 35:
Listing 2.8: R code to generate a 2
Page 36 and 37:
1st U C A G U 2nd position C A G 3r
Page 38 and 39:
1st U C A G U 2nd position C A G 3r
Page 40 and 41:
Escherichia coli strain K-12, subst
Page 42 and 43:
Comparative Genomics
Page 44 and 45:
3M 2.5M 3.5M 2.5M 2M 0M 2M 0.5M B.
Page 46 and 47:
Streptococcus Escherichia Bacillus
Page 48 and 49:
2.4 Summary Comparative Genomics Th
Page 50 and 51:
Comparative Genomics 2.5 Instant in
Page 52 and 53:
‘ReSourCe is he best online submi
Page 54 and 55:
up to a total of 41 different E. co
Page 56 and 57:
Fig. 2 Genes (or segments) from eac
Page 58 and 59:
Fig. 5 BLASTatlas of Clostridium bo
Page 60 and 61:
different applications, such as ide
Page 62 and 63:
1 Comparative Genomics 2.7 Paper II
Page 64 and 65: 166 literally millions of bacterial
Page 66 and 67: 168
Page 68 and 69: 170 resistance genes on mobile gene
Page 70 and 71: 172 involved in generating diversit
Page 72 and 73: 174 recipient DNA. A feature observ
Page 74 and 75: 176 Fig. 5 Genome length distributi
Page 76 and 77: 178
Page 78 and 79: 180 reasons why organisms remain un
Page 80 and 81: 182 A final problem has to do with
Page 82 and 83: 184 Middendorf B, Hochhut B, Leipol
Page 84 and 85: 1 Comparative Genomics 2.8 Paper II
Page 86 and 87: 2 O. N. Reva et al. Fig. 1. Genome
Page 88 and 89: 4 O. N. Reva et al. decrease of the
Page 90 and 91: 6 O. N. Reva et al. of which are kn
Page 92 and 93: 8 O. N. Reva et al. compiled into a
Page 94 and 95: 10 O. N. Reva et al. encoded by a c
Page 96 and 97: 12 O. N. Reva et al. systems and ef
Page 98 and 99: 1 2.9 Paper IV: The origins of Vibr
Page 100 and 101: phylogenies based on alternative ho
Page 102 and 103: Figure 1 Phylogenetic tree of the 1
Page 104 and 105: 25000 20000 15000 10000 5000 0 Pan
Page 106 and 107: Gap F 2M 2.5M Gap E 875k 750k 625k
Page 108 and 109: Table 2 A selection of genes locate
Page 110 and 111: Open Access This article is distrib
Page 112 and 113: 1 Comparative Genomics 2.10 Paper V
Page 116 and 117: 4316 74 Tools Size distribution of
Page 118 and 119: 4318 74 Tools Genome atlas Intrinsi
Page 120 and 121: 4320 74 Tools Genome atlas Intrinsi
Page 122 and 123: 4322 74 Tools for Comparison of Bac
Page 124 and 125: 4324 74 Tools for Comparison of Bac
Page 126 and 127: 4326 74 Tools information, as genet
Page 128 and 129: Chapter 3 rRNA operons and promoter
Page 130 and 131: tuB murI Fis III Fis II Fis I UP -3
Page 132 and 133: Bits 2.0 1.5 1.0 0.5 0.0 Bits 2.0 1
Page 134 and 135: RNA operons and promoter analysis O
Page 136 and 137: Bits 2.0 1.5 1.0 0.5 0.0 Bits T A T
Page 138 and 139: Code Meaning Example C Coding CCCCC
Page 140 and 141: RNA operons and promoter analysis 3
Page 142 and 143: P2 -10 -35 UP P1 -10 -35 UP FIS FIS
Page 144 and 145: 1 rRNA operons and promoter analysi
Page 146 and 147: Using HMMs also simplifies the use
Page 148 and 149: Information content Information con
Page 150 and 151: of the annotation. Some of the majo
Page 152 and 153: where match states stop around 10 c
Page 154 and 155: 1 rRNA operons and promoter analysi
Page 156 and 157: synthesis in flow cells to simultan
Page 158 and 159: Read absence. A boolean where ‘on
Page 160 and 161: Hallin, et al. Figure 4 | The dataf
Page 162 and 163: Genome homology: Comparing multiple
Page 164 and 165:
ing platform-‐independent Java
Page 166 and 167:
34. Wang H, Noordewier M, Benham CJ
Page 168 and 169:
Chapter 4 Web Services and Interope
Page 170 and 171:
Web Services and Interoperability i
Page 172 and 173:
Page 174 and 175:
Page 176 and 177:
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
Page 184 and 185:
Danmarks Tekniske Universitet AFI,
Page 186 and 187:
Danmarks Tekniske Universitet AFI,
Page 188 and 189:
Appendix C Appendix: Courses C.1 Gl
Page 190 and 191:
D.2 Sample output from queryGenomes
Page 192 and 193:
Appendix: Software 13 w a r n " $ o
Page 194 and 195:
Appendix: Software 109 m y ( $ m i
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
show all

Computational tools and Interoperability in Comparative ... - CBS

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?