Phylogenomics and the diversity and diversification of microbes
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Talk by Jonathan Eisen for seminar series / class at UC Davis.
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Phylogenomics and the diversity and diversification of microbes
- 1. Phylogenomics and the Diversity and Diversification of Microbes Jonathan A. Eisen UC Davis UC Davis Talk February 11, 2011
- 2. Phylogenomics of Novelty Variation in Mechanisms of Mechanisms: Origin of New Patterns, Causes Functions and Effects Species Evolution
- 3. Why do this? • Discover causes and effects of differences in evolvability • Improve predictions from genome analysis • Guide interpretation of biological data
- 4. Outline • Introduction • Phylogenomic Stories – Within genome invention of novelty – Stealing novelty – Communities of microbes – Community service and knowing what we don’t know
- 6. rRNA Tree of Life FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 7. Limited Sampling of RRR Studies FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 8. Limited Sampling of RRR Studies Haloferax Methanococcus Chlorobium Deinococcus Thermotoga FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 9. UV Survival E.coli vs H.volcanii 1 Ecoli vs. Hvolcanii 0.1 0.01 Relative 0.001 Survival 0.0001 1E-05 1E-06 1E-07 0 50 100 150 200 250 300 350 400 UV J/m2 E.coli NR10121 mfd- E.coli NR10125 mfd+ TIGR H.volcanii WFD11
- 10. H. volcanii UV Repair Label 7 - 45J / m2) 0.6 Label5#2 0 J/m2 t0 45 J/m2 t0 45 J/m2 Photoreac. 45 J/m2 Dark 24 Hours 0.4 0.2 0 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 Avg. Mol. Wt.(Base Pairs)
- 12. Limited Sampling of RRR Studies Haloferax Methanococcus Chlorobium Deinococcus Thermotoga FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 17. Human commensals
- 19. Phylogenomics of Novelty I Origin of Functions from Within
- 20. Phylogenomics of Novelty • How does novelty originate? • Major categories of processes • From within • De novo invention • Simple substitutions • Duplication and divergence • Domain shuffling • Small & large rearrangements • Regulatory changes • From outside • Lateral gene transfer • Symbioses
- 21. Phylogenomics of Novelty • How does novelty originate? • Major categories of processes Mechanisms of • From within Origin of New • De novo invention Functions • Simple substitutions • Duplication and divergence • Domain shuffling • Small & large rearrangements • Regulatory changes • From outside • Lateral gene transfer • Symbioses
- 22. From Eisen et al. 1997 Nature Medicine 3: 1076-1078.
- 23. Blast Search of H. pylori “MutS” • Blast search pulls up Syn. sp MutS#2 with much higher p value than other MutS homologs • Based on this TIGR predicted this species had mismatch repair • Assumes functional constancy Based on Eisen et al. 1997 Nature Medicine 3: 1076-1078.
- 24. Predicting Function • Identification of motifs – Short regions of sequence similarity that are indicative of general activity – e.g., ATP binding • Homology/similarity based methods – Gene sequence is searched against a databases of other sequences – If significant similar genes are found, their functional information is used • Problem – Genes frequently have similarity to hundreds of motifs and multiple genes, not all with the same function
- 25. MutL?? Based on Eisen et al. 1997 Nature Medicine 3: 1076-1078.
- 26. Overlaying Functions onto Tree MutS2 Aquae MSH5 Strpy Bacsu Synsp Deira Helpy Yeast Human Borbu Metth Celeg MSH6 mSaco Yeast Human Mouse Arath Yeast MSH4 Celeg Human Arath Human MSH3 Mouse Fly Spombe Yeast Xenla Rat Mouse Yeast Human MSH1 Spombe Yeast MSH2 Neucr Arath Aquae Trepa Chltr DeiraTheaq BacsuBorbu Thema SynspStrpy Based on Eisen, Ecoli Neigo 1998 Nucl Acids MutS1 Res 26: 4291-4300.
- 28. Evolutionary Functional Prediction EXAMPLE A METHOD EXAMPLE B 2A CHOOSE GENE(S) OF INTEREST 5 3A 1 3 4 2B 2 IDENTIFY HOMOLOGS 5 1A 2A 1B 3B 6 ALIGN SEQUENCES 1A 2A 3A 1B 2B 3B 1 2 3 4 5 6 CALCULATE GENE TREE Duplication? 1A 2A 3A 1B 2B 3B 1 2 3 4 5 6 OVERLAY KNOWN FUNCTIONS ONTO TREE Duplication? 1 2 3 4 5 6 1A 2A 3A 1B 2B 3B INFER LIKELY FUNCTION OF GENE(S) OF INTEREST Ambiguous Duplication? Species 1 Species 2 Species 3 1A 1B 2A 2B 3A 3B 1 2 3 4 5 6 ACTUAL EVOLUTION (ASSUMED TO BE UNKNOWN) Based on Eisen, 1998 Genome Duplication Res 8: 163-167.
- 29. Example 2: Recent Changes • Phylogenomic functional prediction NJ * ** V.cholerae VC V.cholerae VC 0512 A1034 V.cholerae VC V.cholerae VC V.cholerae VC A0974 A0068 V.cholerae VC0825 0282 may not work well for very newly V.cholerae VCA0906 V.cholerae VC A0979 V.cholerae VCA1056 V.cholerae VC1643 V.cholerae VC 2161 V.cholerae VCA0923 ** ** V.cholerae VC0514 V.cholerae VC1868 V.cholerae VCA0773 V.cholerae VC1313 evolved functions V.cholerae VC1859 V.cholerae VC 1413 V.cholerae VCA0268 V.cholerae VC A0658 ** V.cholerae VC1405 V.cholerae VC 1298 * V.cholerae V.cholerae VCA0864 VC 1248 V.cholerae VCA0176 V.cholerae VCA0220 ** V.cholerae VC1289 V.cholerae VC1069 A ** V.cholerae VC2439 • Can use understanding of origin of V.cholerae VC967 1 V.cholerae VCA0031 V.cholerae VC 1898 V.cholerae VCA0663 V.cholerae VC0988 A V.cholerae VC0216 V.cholerae VC0449 * V.cholerae VCA0008 V.cholerae VC1406 V.cholerae VC 1535 novelty to better interpret these cases? V.cholerae VC 0840 B.subtilis gi2633766 Synechocystis sp. gi1001299 Synechocystis sp.gi1001300 * Synechocystis sp. gi1652276 * Synechocystis * H.pylori sp. gi1652103 gi2313716 H.pylori 99 gi4155097 **C.jejuni ** C.jejuniCj1190c Cj1110c A.fulgidus gi2649560 A.fulgidus gi2649548 ** B.subtilis gi2634254 • Screen genomes for genes that have B.subtilis gi2632630 B.subtilis gi2635607 B.subtilis gi2635608 B.subtilis ** ** B.subtilis gi2635609 ** gi2635610 B.subtilis E.coli gi2635882 E.coligi1788195 gi2367378 * ** E.coligi1788194 E.coli A1092 gi1787690 V.cholerae VC changed recently V.cholerae VC0098 E.coli gi1789453 H.pylori gi2313186 H.pylori 99 gi4154603 C.jejuni ** C.jejuni Cj0144 Cj1564 C.jejuni ** C.jejuniCj0262c ** Cj1506c H.pylori gi2313163 * H.pylori 99 gi4154575 **H.pylori gi2313179 ** H.pylori 99 gi4154599 – Pseudogenes and gene loss ** C.jejuni Cj0019c C.jejuni C.jejuni Cj0951c Cj0246c B.subtilis gi2633374 T.maritima TM0014 V.cholerae VC V.cholerae VC 1403 A1088 T.pallidum gi3322777 T.pallidum ** T.pallidum gi3322939 gi3322938 ** B.burgdorferi gi2688522 – Contingency Loci T.pallidum gi3322296 B.burgdorferi * T.maritima gi2688521 TM0429 T.maritima **T.maritima TM0918 ** TM1428 T.maritima TM0023 * T.maritima TM1143 T.maritima TM1146 P.abyssi PAB1308 P.horikoshii gi3256846 ** P.horikoshii P.abyssi PAB1336 – Acquisition (e.g., LGT) ** gi3256896 ** **P.abyssi PAB2066 ** P.horikoshii gi3258290 * ** P.abyssi PAB1026 P.horikoshii gi3256884 ** D.radiodurans DRA00354 D.radiodurans DRA0353 ** D.radiodurans ** ** VC DRA0352 V.cholerae 1394 P.abyssi PAB1189 P.horikoshii gi3258414 – Unusual dS/dN ratios ** B.burgdorferi gi2688621 M.tuberculosis gi1666149 V.cholerae VC 0622 – Rapid evolutionary rates – Recent duplications
- 30. Tetrahymena Genome Processing • Probably exists as a defense mechanism • Analogous to RIPPING and heterochromatin silencing • Presence of repetitive DNA in MAC but not TEs suggests the mechanism involves targeting foreign DNA • Thus unlike RIPPING ciliate processing does not limit diversification by duplication Eisen et al. 2006. PLoS Biology.
- 31. Phylogenomics of Novelty II Sometimes, it is easier to steal, borrow, or coopt functions rather than evolve them anew
- 32. Stealing DNA
- 33. rRNA Tree of Life Bacteria Archaea Eukaryotes FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 34. Perna et al. 2003
- 35. Network of Life Bacteria Archaea Eukaryotes Figure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 36. Correlated gain/loss of genes • Microbial genes are lost rapidly when not maintained by selection • Genes can be acquired by lateral transfer • Frequently gain and loss occurs for entire pathways/processes • Thus might be able to use correlated presence/absence information to identify genes with similar functions
- 37. Non-Homology Predictions: Phylogenetic Profiling • Step 1: Search all genes in organisms of interest against all other genomes • Ask: Yes or No, is each gene found in each other species • Cluster genes by distribution patterns (profiles)
- 38. Carboxydothermus hydrogenoformans • Isolated from a Russian hotspring • Thermophile (grows at 80°C) • Anaerobic • Grows very efficiently on CO (Carbon Monoxide) • Produces hydrogen gas • Low GC Gram positive (Firmicute) • Genome Determined (Wu et al. 2005 PLoS Genetics 1: e65. )
- 39. Homologs of Sporulation Genes Wu et al. 2005 PLoS Genetics 1: e65.
- 40. Carboxydothermus sporulates Wu et al. 2005 PLoS Genetics 1: e65.
- 41. Wu et al. 2005 PLoS Genetics 1: e65.
- 43. Mutualistic Genome Evolution • Compare and contrast different types of mutualistic symbioses • Diverse hosts, symbionts, biology, ages • Organelles, chemosymbioses, photosynthetic symbioses, nutritional symbioses • What are the rules & patterns?
- 44. Glassy Winged Sharpshooter • Feeds on xylem sap • Vector for Pierce’s Disease • Potential bioterror agent
- 45. Sharpshooter Shotgun Sequencing shotgun Collaboration with Nancy Wu et al. 2006 PLoS Biology 4: e188. Moran’s lab
- 49. Higher Evolutionary Rates in Endosymbionts Wu et al. 2006 PLoS Biology 4: e188. Collaboration with Nancy Moran’ s Lab
- 50. Variation in Evolution Rates MutS MutL + + + + + + + + _ _ _ _ Wu et al. 2006 PLoS Biology 4: e188. Collaboration with Nancy Moran’ s Lab
- 51. Polymorphisms in Metapopulation • Data from ~200 hosts – 104 SNPs – 2 indels • PCR surveys show that this is between host variation • Much lower ratio of transitions:transversions than in Blochmannia • Consistent with absence of MMR from Blochmannia
- 52. Baumannia is a Vitamin and Cofactor Producing Machine Wu et al. 2006 PLoS Biology 4: e188.
- 56. Great Plate Count Anomaly Culturing Microscope Count Count
- 57. Great Plate Count Anomaly Culturing Microscope Count <<<< Count
- 58. Great Plate Count Anomaly DNA Culturing Microscope Count <<<< Count
- 59. rRNA PCR The Hidden Majority Richness estimates Hugenholtz 2002 Bohannan and Hughes 2003
- 61. rRNA data increasing exponentially too
- 62. Perna et al. 2003
- 63. Metagenomics shotgun clone
- 65. How can we best use metagenomic data? • Many possible uses including: – Improvements on rRNA based phylotyping and species diversity measurements – Adding functional information on top of phylogenetic/species diversity information • Most/all possible uses either require or are improved with phylogenetic analysis
- 66. Example I: Phylotyping with rRNA and other genes
- 67. Functional Diversity of Proteorhodopsins? Venter et al., 2004
- 68. Weighted % of Clones 0 0.1250 0.2500 0.3750 0.5000 Al ph ap ro te Be ob ta ac pr te ot ria G eo am ba m ct ap er ro ia Ep te si ob lo ac np te ro ria D te el ob ta ac pr te ot ria eo C ba ya ct no er b ia ac te Fi ria rm ic ut Ac e s tin ob ac te C ria hl o ro bi C FB Major Phylogenetic Group Sargasso Phylotypes C hl o ro fle Sp xi iro ch ae Fu te so s D ba ei ct no er c oc ia cu s- Eu Th ry erm ar ch us C ae re ot na a rc ha eo ta Shotgun Sequencing Allows Use of Other Markers EFG Venter et al., Science 304: 66-74. 2004 EFTu rRNA RecA RpoB HSP70
- 71. Binning challenge A T B U C V D W E X F Y G Z
- 72. Binning challenge A T B U C V D W E X F Y G Best binning method: reference genomes Z
- 73. Binning challenge A T B U C V D W E X F Y G Best binning method: reference genomes Z
- 74. Binning challenge A T B U C V D W E X F Y G No reference genome? What do you do? Z
- 75. Binning challenge A T B U C V D W E X F Y G No reference genome? What do you do? Z Phylogeny ....
- 79. ???????
- 80. CFB Phyla
- 81. Sulcia makes amino acids Baumannia makes vitamins and cofactors Wu et al. 2006 PLoS Biology 4: e188.
- 82. Phylogenomics of Novelty III Knowing What We Don’t Know
- 83. Research Topics Variation in Mechanisms of Mechanisms: Origin of New Patterns, Causes Functions and Effects Species Evolution
- 84. Research Topics Variation in Mechanisms of Mechanisms: Origin of New Patterns, Causes Functions and Effects Species Evolution
- 85. As of 2002
- 86. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA WS3 Gemmimonas Firmicutes Fusobacteria Actinobacteria OP9 Cyanobacteria Synergistes Deferribacteres Chrysiogenetes NKB19 Verrucomicrobia Chlamydia OP3 Planctomycetes Spriochaetes Coprothmermobacter OP10 Thermomicrobia Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 87. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA • Genome WS3 Gemmimonas Firmicutes sequences are Fusobacteria Actinobacteria mostly from OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 Verrucomicrobia Chlamydia OP3 Planctomycetes Spriochaetes Coprothmermobacter OP10 Thermomicrobia Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 88. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA • Genome WS3 Gemmimonas Firmicutes sequences are Fusobacteria Actinobacteria mostly from OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 • Some other Verrucomicrobia Chlamydia OP3 phyla are Planctomycetes Spriochaetes only sparsely Coprothmermobacter OP10 Thermomicrobia sampled Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 89. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA • Genome WS3 Gemmimonas Firmicutes sequences are Fusobacteria Actinobacteria mostly from OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 • Some other Verrucomicrobia Chlamydia OP3 phyla are Planctomycetes Spriochaetes only sparsely Coprothmermobacter OP10 Thermomicrobia sampled Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 90. Proteobacteria • NSF-funded TM6 OS-K • At least 40 Tree of Life Acidobacteria Termite Group phyla of OP8 Project Nitrospira Bacteroides bacteria Chlorobi • A genome Fibrobacteres Marine GroupA • Genome WS3 from each of Gemmimonas sequences are Firmicutes eight phyla Fusobacteria mostly from Actinobacteria OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 • Some other Verrucomicrobia Chlamydia OP3 phyla are only Planctomycetes Spriochaetes sparsely Coprothmermobacter OP10 Thermomicrobia sampled Chloroflexi TM7 Deinococcus-Thermus • Solution I: Dictyoglomus Eisen, Ward, Aquificae Thermudesulfobacteria sequence more Robb, Nelson, et Thermotogae phyla OP1 al OP11
- 92. Proteobacteria • NSF-funded TM6 OS-K • At least 40 Tree of Life Acidobacteria Termite Group phyla of bacteria OP8 Project Nitrospira • Genome Bacteroides • A genome Chlorobi Fibrobacteres sequences are Marine GroupA from each of WS3 Gemmimonas mostly from eight phyla Firmicutes Fusobacteria three phyla Actinobacteria OP9 Cyanobacteria • Some other Synergistes Deferribacteres Chrysiogenetes phyla are only NKB19 Verrucomicrobia sparsely Chlamydia OP3 Planctomycetes sampled Spriochaetes Coprothmermobacter • Still highly OP10 Thermomicrobia Chloroflexi biased in terms TM7 Deinococcus-Thermus Dictyoglomus of the tree Aquificae Eisen & Ward, PIs Thermudesulfobacteria Thermotogae OP1 OP11
- 93. Proteobacteria • GEBA TM6 OS-K • At least 40 Acidobacteria • A genomic Termite Group OP8 phyla of bacteria encyclopedia Nitrospira Bacteroides • Genome Chlorobi of bacteria Fibrobacteres Marine GroupA sequences are and archaea WS3 Gemmimonas mostly from Firmicutes Fusobacteria three phyla Actinobacteria OP9 Cyanobacteria • Some other Synergistes Deferribacteres Chrysiogenetes phyla are only NKB19 Verrucomicrobia sparsely Chlamydia OP3 Planctomycetes sampled Spriochaetes Coprothmermobacter OP10 • Solution: Really Thermomicrobia Chloroflexi Fill in the Tree TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Eisen & Ward, PIs Thermotogae OP1 OP11
- 95. GEBA Pilot Project: Components • Project overview (Phil Hugenholtz, Nikos Kyrpides, Jonathan Eisen, Eddy Rubin, Jim Bristow) • Project management (David Bruce, Eileen Dalin, Lynne Goodwin) • Culture collection and DNA prep (DSMZ, Hans-Peter Klenk) • Sequencing and closure (Eileen Dalin, Susan Lucas, Alla Lapidus, Mat Nolan, Alex Copeland, Cliff Han, Feng Chen, Jan-Fang Cheng) • Annotation and data release (Nikos Kyrpides, Victor Markowitz, et al) • Analysis (Dongying Wu, Kostas Mavrommatis, Martin Wu, Victor Kunin, Neil Rawlings, Ian Paulsen, Patrick Chain, Patrik D’Haeseleer, Sean Hooper, Iain Anderson, Amrita Pati, Natalia N. Ivanova, Athanasios Lykidis, Adam Zemla) • Adopt a microbe education project (Cheryl Kerfeld) • Outreach (David Gilbert) • $$$ (DOE, Eddy Rubin, Jim Bristow)
- 96. GEBA Pilot Project Overview • Identify major branches in rRNA tree for which no genomes are available • Identify those with a cultured representative in DSMZ • DSMZ grew > 200 of these and prepped DNA • Sequence and finish 100+ (covering breadth of bacterial/archaea diversity) • Annotate, analyze, release data • Assess benefits of tree guided sequencing • 1st paper Wu et al in Nature Dec 2009
- 97. GEBA Phylogenomic Lesson 1 The rRNA Tree of Life is a Useful Tool for Identifying Phylogenetically Novel Genomes
- 98. Compare PD in Trees From Wu et al. 2009 Nature 462, 1056-1060
- 99. GEBA Phylogenomic Lesson 2 The rRNA Tree of Life is not perfect ...
- 100. 16s Says Hyphomonas is in Rhodobacteriales Badger et al. 2005 Int J System Evol Microbiol 55: 1021-1026.
- 101. WGT and individual gene trees: Its Related to Caulobacterales Badger et al. 2005 Int J System Evol Microbiol 55: 1021-1026.
- 103. GEBA Phylogenomic Lesson 3 Phylogeny-driven genome selection helps discover new genetic diversity
- 104. Network of Life Bacteria Archaea Eukaryotes FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 105. Protein Family Rarefaction Curves • Take data set of multiple complete genomes • Identify all protein families using MCL • Plot # of genomes vs. # of protein families
- 106. Wu et al. 2009 Nature 462, 1056-1060
- 107. Wu et al. 2009 Nature 462, 1056-1060
- 108. Wu et al. 2009 Nature 462, 1056-1060
- 109. Wu et al. 2009 Nature 462, 1056-1060
- 110. Wu et al. 2009 Nature 462, 1056-1060
- 111. Synapomorphies exist Wu et al. 2009 Nature 462, 1056-1060
- 112. +,%-./&#(%)"* !"#$%"&'(%)"* ! !
- 113. Phylogenetic Distribution Novelty: Bacterial Actin Related Protein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aliangium ochraceum DSM 14365 Patrik D’haeseleer, Adam Zemla, Victor Kunin Wu et al. 2009 Nature 462, 1056-1060 See also Guljamow et al. 2007 Current Biology.
- 114. GEBA Phylogenomic Lesson 4 Phylogeny driven genome selection (and phylogenetics in general) improves genome annotation
- 115. Most/All Functional Prediction Improves w/ Better Phylogenetic Sampling • Took 56 GEBA genomes and compared results vs. 56 randomly sampled new genomes • Better definition of protein family sequence “patterns” • Greatly improves “comparative” and “evolutionary” based predictions • Conversion of hypothetical into conserved hypotheticals • Linking distantly related members of protein families • Improved non-homology prediction Kostas Natalia Thanos Nikos Iain Mavrommatis Ivanova Lykidis Kyrpides Anderson
- 116. GEBA Phylogenomic Lesson 5 Improves analysis of genome data from uncultured organisms
- 117. Weighted % of Clones 0 0.1250 0.2500 0.3750 0.5000 Al ph ap ro te Be ob ta ac pr te ot ria G eo am ba m ct ap er ro ia Ep te si ob lo ac np te ro ria D te el ob ta ac pr te ot ria eo C ba ya ct no er b ia ac te Fi ria rm ic ut Ac e s tin ob ac te C ria hl o ro bi C FB Major Phylogenetic Group Sargasso Phylotypes C hl o ro fle Sp xi iro ch ae Fu te so s D ba ei ct no er c oc ia cu s- Eu Th ry erm ar ch us C ae re ot na a rc ha eo ta Shotgun Sequencing Allows Use of Other Markers EFG Venter et al., Science 304: 66-74. 2004 EFTu rRNA RecA RpoB HSP70
- 118. Weighted % of Clones 0 0.1250 0.2500 0.3750 0.5000 Al ph ap ro te Be ob ta ac pr te ot ria G eo am ba m ct ap er ro ia Ep te si ob lo ac np te ro ria D te el ob ta ac pr te ot ria eo C ba ya ct no er b ia ac te Fi ria rm ic ut Ac e s tin ob ac te C ria hl o ro bi without good C FB Major Phylogenetic Group Sargasso Phylotypes C Cannot be done hl o ro fle Sp xi iro ch ae Fu te so s D ba ei ct no er c ia sampling of genomes oc cu s- Eu Th ry erm ar ch us C ae re ot na a rc ha eo ta Shotgun Sequencing Allows Use of Other Markers EFG Venter et al., Science 304: 66-74. 2004 EFTu rRNA RecA RpoB HSP70
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- It has been less than 10 years since the first genome was determined\n
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- Functional prediction using a gene tree is just like predicting the biology of a species using a species tree\n
- Extension of rRNA analysis to uncultured organisms using PCR\n
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- Functional prediction using a gene tree is just like predicting the biology of a species using a species tree\n
- Functional prediction using a gene tree is just like predicting the biology of a species using a species tree\n
- Functional prediction using a gene tree is just like predicting the biology of a species using a species tree\n
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- This is a tree of a rRNA gene that was found on a large DNA fragment isolated from the Monterey Bay. This rRNA gene groups in a tree with genes from members of the gamma Proteobacteria a group that includes E. coli as well as many environmental bacteria. This rRNA phylotype has been found to be a dominant species in many ocean ecosystems.\n
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- Phylogenetic analysis of rRNAs led to the discovery of archaea\n
- This is a tree of a rRNA gene that was found on a large DNA fragment isolated from the Monterey Bay. This rRNA gene groups in a tree with genes from members of the gamma Proteobacteria a group that includes E. coli as well as many environmental bacteria. This rRNA phylotype has been found to be a dominant species in many ocean ecosystems.\n\n clone from the Sargasso Sea. This shows that this \n
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- It has been less than 10 years since the first genome was determined\n