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TIGRTIGRTIGRTIGR
“Nothing in biology makes senseexcept in the light of evolution.”
T. H. Dobzhansky (1973)
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Talk Outline
• Complete Genome Projects - history and current status
• What have we learned about evolutionary history and processes from recent genome projects
• Two main themes - completeness and closeness• Coming attractions• Why we need more genomes
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The Institute for Genomic Research
• A not for profit institution, staff ~230• Departments:
– Eukaryotic Genomics– Microbial Genomics– Functional Genomics– Bioinformatics– Sequencing Core
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TIGRTIGR
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Whole Genome Shotgun Sequencing
shotgunshotgun
sequencesequenceWarner Brothers, Inc.Warner Brothers, Inc.
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Assemble Fragments
sequencer outputsequencer output
assemble assemble fragmentsfragments
Closure &Closure &
AnnotationAnnotation
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General Steps in Analysis of Complete Genomes
• Identification/prediction of genes• Characterization of gene features• Characterization of genome features• Prediction of gene function• Prediction of pathways• Integration with known biological data• Comparative genomics
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TIGRTIGR
Haemophilusinfluenzae
Mycoplasmagenitalium
Synechocystissp.
Methanococcusjannaschii
Mycoplasmapneumoniae
Saccharomyces cerevisiae
Helicobacterpylori
Escherichiacoli
Archaeoglobus fulgidus
Borrelia burgdorferi
Aquifexaeolicus
Pyrococcushorikoshii
Treponemapallidum
Rickettsia prowazekii
Aeropyrumpernix
Thermotoga maritima
Deinococcus
radiodurans
Helicobacterpylori
Neisseriameningitidis
Campylobacterjejuni Pseudomona
saeruginosa
Xylellafastidiosa
Vibrio cholerae
Bacillus subtilis
Methanobacteriumthermoautotrophicum
Mycobacterium
tuberculosis
Chlamydiatrachomatis
Chlamydia pneumoniae
Neisseriameningitidis
Chlamydiatrachomatis
Chlamydia pneumoniae
1996 2000199919981997
Microbial Genomes Sequenced
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Complete Genome/Chromosome Progress
0
10
20
30
40
50
Complete Genomes
1995 1996 1997 1998 1999 2000
Year
Eukaryote
Archaea
Bacteria
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rRNA Tree for Species with Complete Genomes (~August 2000)
Methanobacterium thermoautotrophicumArchaeoglobus fulgidusPyrococcus horikoshiiMethanococcus jannaschiiAeropyrum pernix0.05 changesArchaeaMycobacterium tuberculosisBacillus subtilisSynechocystis sp.Aquifex aeolicusThermotoga maritimaDeinococcus radioduransTreponema pallidumBorrelia burgdorferiHelicobacter pyloriCampylobacter jejuniNeisseria meningitidisEscherichia coliVibrio choleraeHaemophilus influenzaeRickettsia prowazekiiMycoplasma pneumoniaeMycoplasma genitaliumChlamydia trachomatisChlamydia pneumoniaeBacteriaCaenorhabditis elegansDrosophila melanogasterSaccharomyces cerevisiaeEukarya
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rRNA Tree - Complete/In ProgressEuryarchaeotaCrenarchaeotaAlphaProteobacteriaEpsilonProteobacteriaDeltaProteobacteriaSpirochetesGreen Sulfur bacteriaChlamydiaCyanobacteriaThermotogalesThermophilic O2 reducersDeinococcus/ThermusBetaProteobacteriaGammaProteobacteriaLow GC Gram-positive bacteriaHigh GCGram-positive bacteriaGreen Non-Sulfur bacteria
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Limitations of Genome Analysis• Functional predictions are PREDICTIONS• Need to follow up all predictions with
experimental work• Each genome sequence is a snapshots of one clone• Genome analysis is not able to identify novel
processes• Annotation needs to be updated• Assembly can be wrong• Some parts of genome may be missed (e.g., low
copy plasmids)
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TIGRTIGR
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Genome sequences and evolution
• Origin of new gene function• Gene loss• Genome degradation• Gene and genome duplication• Rates and patterns of mutation,
recombination• Gene transfer• Species evolution
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Evolution and Complete Genomes I:Gene Loss
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EuksArchBacteriaLossEvolutionary Origin of GeneMTMJSCHSAADRTABSMGMPBBTPHPHIECSSMTPresence ( ) or Absence of GeneSpecies AbbreviationKingdom
Example of Tracing Gene Loss
TIGRTIGR
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Why Identify Gene Loss
• Indicates that gene is not absolutely required for survival
• Parallel loss of same gene in different species may indicate selective advantage of loss of that gene
• Correlated loss of genes in a pathway indicates a conserved association among those genes (important for phylogenetic profiles)
• Loss in organellar genomes frequently accompanied by gain in nuclear genome
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TIGRTIGR
Duplication and Loss of Mismatch Repair Genes
51234*E. coliH. influenzaeN. gonorrhoaeaH. pyloriSyn. spB. subtilisS. pyogenesM. pneumoniaeM. genitaliumA. aeolicusD. radioduransT.pallidumB.burgdorferiSyn. spB. subtilisS. pyogenesA. aeolicusD. radioduransB. burgdorferiMutS1MutS-I lineageMutS-II lineageSpecies TreeGene loss*Gene Duplications1-5Gene LossA.B.A. aeolicusS pyogenesB. subtilisSyn. spD. radioduransMutS2B.burgdorferi
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Buchnera
• Extensive gene loss relative to E. coli
• Surprising loss of some genes– UvrABCD– RecA– Very different than many pathogens (frequently
loss MutS, MutL)
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Evolution and Complete Genomes II:Gene and Genome Duplication
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Why Duplications Are Useful to Identify
• Allows division into orthologs and paralogs
• Improves functional predictions
• Helps identify mechanisms of duplication
• Can be used to study mutation processes in different parts of a genome
• Lineage specific duplications may be indicative of species’ specific adaptations
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TIGRTIGR
Expansion of MCP Family in V. choleraeE.coli gi1787690B.subtilis gi2633766Synechocystis sp. gi1001299Synechocystis sp. gi1001300Synechocystis sp. gi1652276Synechocystis sp. gi1652103H.pylori gi2313716H.pylori99 gi4155097C.jejuni Cj1190cC.jejuni Cj1110cA.fulgidus gi2649560A.fulgidus gi2649548B.subtilis gi2634254B.subtilis gi2632630B.subtilis gi2635607B.subtilis gi2635608B.subtilis gi2635609B.subtilis gi2635610B.subtilis gi2635882E.coli gi1788195E.coli gi2367378E.coli gi1788194E.coli gi1789453C.jejuni Cj0144C.jejuni Cj0262cH.pylori gi2313186H.pylori99 gi4154603C.jejuni Cj1564C.jejuni Cj1506cH.pylori gi2313163H.pylori99 gi4154575H.pylori gi2313179H.pylori99 gi4154599C.jejuni Cj0019cC.jejuni Cj0951cC.jejuni Cj0246cB.subtilis gi2633374T.maritima TM0014T.pallidum gi3322777T.pallidum gi3322939T.pallidum gi3322938B.burgdorferi gi2688522T.pallidum gi3322296B.burgdorferi gi2688521T.maritima TM0429T.maritima TM0918T.maritima TM0023T.maritima TM1428T.maritima TM1143T.maritima TM1146P.abyssi PAB1308P.horikoshii gi3256846P.abyssi PAB1336P.horikoshii gi3256896P.abyssi PAB2066P.horikoshii gi3258290P.abyssi PAB1026P.horikoshii gi3256884D.radiodurans DRA00354D.radiodurans DRA0353D.radiodurans DRA0352P.abyssi PAB1189P.horikoshii gi3258414B.burgdorferi gi2688621M.tuberculosis gi1666149V.cholerae VC0512V.cholerae VCA1034V.cholerae VCA0974V.cholerae VCA0068V.cholerae VC0825V.cholerae VC0282V.cholerae VCA0906V.cholerae VCA0979V.cholerae VCA1056V.cholerae VC1643V.cholerae VC2161V.cholerae VCA0923V.cholerae VC0514V.cholerae VC1868V.cholerae VCA0773V.cholerae VC1313V.cholerae VC1859V.cholerae VC1413V.cholerae VCA0268V.cholerae VCA0658V.cholerae VC1405V.cholerae VC1298V.cholerae VC1248V.cholerae VCA0864V.cholerae VCA0176V.cholerae VCA0220V.cholerae VC1289V.cholerae VCA1069V.cholerae VC2439V.cholerae VC1967V.cholerae VCA0031V.cholerae VC1898V.cholerae VCA0663V.cholerae VCA0988V.cholerae VC0216V.cholerae VC0449V.cholerae VCA0008V.cholerae VC1406V.cholerae VC1535V.cholerae VC0840V.cholerae VC0098V.cholerae VCA1092V.cholerae VC1403V.cholerae VCA1088V.cholerae VC1394V.cholerae VC0622NJ*******************************************************************************
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TIGRTIGR
C. pneumoniae Paralogs by Position
0
250000
500000
750000
1000000
1250000
Subject Orf Position
0 250000 500000 750000 1000000 1250000
Query Orf Position
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C. pneumoniae Paralogs - Lineage Specific
0
250000
500000
750000
1000000
1250000
Subject Orf Position
0 250000 500000 750000 1000000 1250000
Query Orf Position
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Evolution and Complete Genomes III:Genome Rearrangements
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TIGRTIGR
X-files
Eisen et al. 2000. Genome Biology 1(6): 11.1-11.9
Also see Tillier and Collins. 2000. Nature Genetics 26(2):195-7.
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V. cholerae vs. E. coliBest Matching Proteins by Location
0
1000000
2000000
3000000
4000000
5000000
E. coli
ORF Coordinates
0 500000 1000000 1500000 2000000 2500000 3000000
V. cholerae ORF Coordinates
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TIGRTIGR
M. leprae vs. M. tuberculosis Whole Genome Alignment
0
1000000
2000000
3000000
4000000
Mycobacterium tuberculosis
0 1000000 2000000 3000000
Mycobacterium leprae
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TIGRTIGR
Duplication and Gene Loss Model
A
B
CD
E
F
A
B
CD
E
F
A
B
CD
E
F
A
B
C
D
EF
A’
B’
C’
D’
E’F’
A
B
C
D
EF
A’
B’
C’
D’
E’F’
A
C
D
F
A’
B’
E’
E. coliE. coli
B
C
D
F
A’
B’
D’
E’
V. cholerae
A
B
C
D
EF
A’
B’
C’
D’
E’F’
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TIGRTIGR C. trachomatis MoPn
C. p
neum
onia
e A
R39
Origin
Terminus
C. trachomatis vs C. pneumoniae Dot Plot
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TIGRTIGR
B1A1B2A2B3A3B3B22423222120191817161514131211109672582627282930123453132 B131326789101112131415161718192021222324252627282930123453132 B32423222120191817161514131211109672582627282933231304521 A131326789101112131415161718192021222324252627282930123453132 A231326789101112131918171615142021222324252627282930123453132 A32678910111213191817161514202122232425262754331302928132B2Inversion Around Terminus (*)
Inversion Around Terminus (*)
Inversion AroundOrigin (*)
Inversion AroundOrigin (*)
******** Common Ancestor of
A and B
31326789101112131415161718192021222324252627282930123453132A2A1A2A3B2B1
Symmetric Inversion Model
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TIGRTIGR
Why are Inversions Symmetrical Around Origin
• Genetic studies in Salmonella and E. coli suggest that there may be strong selection against other inversions
– Mahan, Segall, Schmid and Roth– Liu and Sanderson– Rebollo, Francois, and, Louarn
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TIGRTIGR
Evolution and Complete Genomes IV:Gene Transfer
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TIGRTIGR
Examples of Horizontal Transfers
• Antibiotic and toxin resistance genes on plasmids
• Pathogenicity islands• Agrobacterium Ti plasmid• Viruses• Organelle to nucleus transfers
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TIGRTIGR
Why Gene Transfers Are Useful to Identify
• Laterally transferred genes frequently involved in environmental adaptations and/or pathogenicity
• Helps identify transposons, integrons, and other vectors of gene transfer
• Helps identify species associations in the environment
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TIGRTIGR
Tree of Life or Web of Life?
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TIGRTIGR
Most ‘Evidence’ for Gene Transfer has Alternative Explanations
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How to Infer Gene Transfers
• Unusual distribution patterns
• Unusual nucleotide composition
• High sequence similarity to supposedly distantly related species
• Unusual gene trees
• Observe transfer events
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TIGRTIGR
100s of DNA Islands in O157:H7 vs. K12: Gene Loss or Transfer?
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TIGRTIGR
Lateral Transfer Inference Based on Complete Genome Analysis I:
Organellar to Nuclear Transfers in A. thaliana
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TIGRTIGR
Mitochondrial Genome Integration into A. thaliana chrII
3.2E+063.3E+063.4E+063.5E+063.6E+06D’1 A. thalianaMitochondrial
AlternativeGenome
PossibleInsertionPoint
3 D’1A’3C1B3B.C.D.Chromosome II1E+052E+053E+054E+05Alternative Mitochondrial Form03CBA’
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TIGRTIGR
A. thaliana Nuclear Proteins:Best Matches to Complete Genomes
0
1000
2000
3000
4000
Bes
t M
atch
es
CH
LT
E
PO
RG
IB
AC
SUM
CY
TU
BB
UR
TR
EP
AC
HL
PN
EC
OL
IN
EIM
ER
ICP
RC
AU
CR
HE
LP
YSY
NSP
AQ
UA
ED
EIR
AT
HE
MA
AE
RP
EA
RC
FU
ME
TJA
ME
TT
HP
YR
AB
CE
LE
GY
EA
STD
RO
ME
B A E
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TIGRTIGR
SYNSP0100200300400500600700800900Number of Best Matches to This Species050010001500200025003000350040004500Number of ORFs in Complete GenomeBest Matches vs. Prokaryotes
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TIGRTIGR
Organellar HSP60sDROMECG12101DROMECG7235DROMECG2830DROMECG16954ARATH At2g33210ARATH F14O13.19ARATH MCP4.7YEAST SWCAUCR ORF03639RICPR gi|3861167ECOLI gi|1790586NEIMEb gi|7227233.AQUAE gi|2984379CHLPN gi|4376399|DEIRA ORF02245BACSU gi|2632916SYNSP gi|1652489SYNSP gi|1001103ARATH At2g28000ARATH MRP15.11MCYTU gi|2909515MCYTU gi|1449370THEMA TM0506BBUR gi|2688576TREPA gi|3322286PORGI ORF00933CHLTE ORF00173HELPY gi|2313084MitochondrialFormsα−ΠροτεοΧψανοβαχτεριαΠλαστιδ Φορµσ
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TIGRTIGR
Best Matches Per ORF
B A
0
0.05
0.1
0.15
0.2
0.25
0.3
CH
LT
E P
OR
GI
BA
CSU
MC
YT
UB
BU
R
TR
EP
AC
HL
PN
EC
OL
IN
EIM
ER
ICP
RC
AU
CR
HE
LP
YSY
NSP
AQ
UA
ED
EIR
AT
HE
MA
AE
RP
EA
RC
FU
ME
TJA
ME
TT
HP
YR
AB
CE
LE
GY
EA
STD
RO
ME
E
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Lateral Transfer Inference Based on Complete Genome Analysis II:
Bacterial to Vertebrate Transfers Based on Analysis of the Human
Genome
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Lander et al. ‘Evidence’
• Genes match bacteria not non-vertebrate eukaryotes
• Or, genes have stronger match to bacteria than non-vertebrates
• A set of ~120 of these genes found in many bacterial species
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Alternative explanations
• Gene loss from non-vertebrate eukaryotes• Rapid divergence in non-vertebrate
eukaryotes• Incomplete genomes (e.g., D.
melanogaster)
• Bad annotation/gene finding• Contamination
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Evolutionary Rate Variation
231456
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Trees Don’t Support TransferParamecium bursaria Chlorella virus 1Homo sapiens HAS1Mus musculus HAS1Xenopus laevisXenopus laevis Danio rerio Homo sapiens Mus musculus Danio rerio Xenopus laevis Gallus gallus Bos taurus Homo sapiens Mus musculus Rattus norvegicus Bradyrhizobium sp SNU001Rhizobium leguminosarumRhizobium spRhizobium lotiRhizobium tropiciRhizobium sp. NodCMesorhizobium sp 7653RSinorhizobium melilotiRhizobium melilotiRhizobium leguminosarumRhizobium galegaeAzorhizobium caulinodansStigmatella aurantiacaStreptomyces coelicolorStreptococcus uberisStreptococcus equisimilisStreptococcus pyogenes HASAStreptococcus pneumoniae0.2BacteriaVertebratesVirusIIIIII
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Number of pBVTs is Dependent on # of Genomes Analyzed
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Birney et al, same issue of Nature as complete genome
“The unfinished human genomic DNA may contain contamination, particularly from bacteria but also from other sources. Contaminating DNA is routinely removed from finished sequence, but some is still present in unfinished sequence. If the predicted gene matches a bacterial gene more closely than any vertebrate gene then it will almost always be a contaminant.”
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Evolution and Complete Genomes V:Species Evolution
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Whole Genome “Phylogeny”
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Whole Genome vs. rRNA
Methanobacterium thermoautotrophicumArchaeoglobus fulgidusPyrococcus horikoshiiMethanococcus jannaschiiAeropyrum pernix0.05 changesArchaeaMycobacterium tuberculosisBacillus subtilisSynechocystis sp.Aquifex aeolicusThermotoga maritimaDeinococcus radioduransTreponema pallidumBorrelia burgdorferiHelicobacter pyloriCampylobacter jejuniNeisseria meningitidisEscherichia coliVibrio choleraeHaemophilus influenzaeRickettsia prowazekiiMycoplasma pneumoniaeMycoplasma genitaliumChlamydia trachomatisChlamydia pneumoniaeBacteriaCaenorhabditis elegansDrosophila melanogasterSaccharomyces cerevisiaeEukarya
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Deinococcus radiodurans2a) RecA2b) SS-rRNAErwinia carotovaraEscherichia coliShigella flexneriEnterobacter agglomeransYersinia pestisSerratia marcescensProteus vulgarisProteus mirabilisVibrio anguilarrumVibrio choleraeHaemophilus influenzaeArabidopsis thaliana CPSTAcetobacter polyoxogenesMethylobacillus flagellatumMethylomonas claraMethylophilus methylotrophusMagnetispirillum magnetotacticumRhizobium phaseoliRhizobium viciaeCorynebacterium glutamicumStreptomyces violaceusMycobacterium lepraeMycobacterium tuberculosisStreptomyces ambofaciensStreptomyces lividansBorrelia burgdorferiBacteroides fragilisChlamydia trachomatisThermus aquaticusThermus thermophilusAquifex pyrophilusThermotoga maritimaLactococcus lactisStreptococcus pneumoniaeBacillus subtilisStaphylococcus aureusAcholeplasma laidlawiiSynechococcus sp. PCC7002Synechococcus sp. PCC7942Anabaena variabilisCampylobacter jejuniHelicobacter pyloriAgrobacterium tumefaciensRhizobium melilotiRhodobacter sphaeroidesRhodobacter capsulatusRickettsia prowazekiiMyxococcus xanthus2Myxococcus xanthus1Xanthomonas oryzaeThiobacillus ferrooxidansAcidiphilium facilisBrucella abortusNeisseria gonorrhoeaePseudomonas fluorescencsPseudomonas aeruginosaAzotobacter vinelandiiPseudomonas putidaAcinetobacter calcoaceticusLegionella pneumophilaBurkholderia cepaciaBordetella pertussisMycoplasma mycoidesMycoplasma pulmonisErwinia carotovaraEscherichia coliEnterobacter agglomeransYersinia pestisSerratia marcescensProteus vulgarisArsenophonus nasoniaeVibrio anguilarrumVibrio choleraeHaemophilus influenzae"Flavobacterium" lutescensNicotiana tabacum CPSTAcetobacter pasterianusMethylobacillus flagellatumMethylomonas methylovoraMethylophilus methylotrophusMagnetispirillum magnetotacticumRhizobium phaseoliRhizobium viciaeCorynebacterium glutamicumStreptomyces coelicolorMycobacterium lepraeMycobacterium tuberculosisStreptomyces ambofaciensStreptomyces lividansBorrelia burgdorferiBacteroides fragilisChlamydia trachomatisThermus aquaticusThermus thermophilusDeinococcus radioduransAquifex pyrophilusThermotoga maritimaLactococcus lactisStreptococcus salivariusBacillus subtilisStaphylococcus aureusAcholeplasma laidlawiiSynechococcus sp. PCC6301Phormidium minutumAnabaena sp . PCC7120Campylobacter jejuniHelicobacter pyloriAgrobacterium tumefaciensRhizobium melilotiRhodobacter sphaeroidesRhodobacter capsulatusRickettsia prowazekiiMyxococcus xanthusXanthomonas oryzaeThiobacillus caldusAcidiphilium facilisBrucella abortusNeisseria gonorrhoeaePseudomonas flavescensPseudomonas aeruginosaPseudomonas putidaAcinetobacter calcoaceticusLegionella pneumophilaBurkholderia cepaciaBordetella pertussisMycoplasma mycoidesMycoplasma pulmonisγ1γ2βαΛοωΓΧΗιγηΓΧδεΧψανο∆/Τ
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Coming Attractions I: Phylogenetic Profiles
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Phylogenetic Profile - E.coliFlagellar Genes
fhiAfliMfliPfliGflgGfliFflgIflhAflhBgcpE
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PG Profile. C. tepidum Chlorophyll Synthesis
CbiGCbiPDsrNCbiACbiJHCobNBchH1BchH2CobN2BchH3ChlIChlI2ChlI3
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Coming Attractions II:Uncultured Environmental Species
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Genomics does not require initial culturing step.
• Isolate, by filtration, all bacteria in a water sample• Extract total DNA in very large pieces• Clone those pieces as BACs into E.coli to get enough.• Sequence the BACs like a bacterial genome.
Natural Water
Filterconcentrate
ExtractDNA
CloneInto BACs
SequenceGeneList
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Bacterial Rhodopsin: a new photosynthesis system in the oceans
SAR86, anuncultured
bacteria
BAC Sequenced and
Analyzed
Beja O, et.al., Science 2000 289:1902-6
Bacterial rhodopsin: evidence for a new type of phototrophy in the sea.
Rhodopsinfound
H+
light
H+ ADP ATP
Cloned into E. coli E. coli pumps
protons in thelight
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0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
0.045
0.05
0 m
80 m750 m
γ
α
βε
Proteobacteria
Archaea
Best Matches of Bac Ends
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RecA-Bacteroides/Cytophaga in Monterey Bay BACs
Chlorobium tepidum
Cytophaga hutchinsonii
Prevotella ruminocola
Bacteroides fragilis
Porphyromonas gingivalis
MBBAD68TR
MBBAD65TR
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Wither Genomics? Not yet.
• Despite limitations, a great deal can still be learned from genome sequence analysis.
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Evolutionary Diversity Still Poorly Represented in Complete Genomes
Tmf-pendenR-rubrum3Azs-brasi2Rm-vannielRhb-legum8Bdr-japoniSpg-capsulRic-prowazSte-maltopSpr-volutaRub-gelat2Rcy-purpurNis-gonor1Hrh-halch2Alm-vinosmPs-aerugi3E-coliMyx-xanthuBde-stolpiDsv-desulfDsb-postgaC-leptumC-butyric4C-pasteuriEub-barkerC-quercicoHel-chlor2Acp-laidlaM-capricolC-ramosumB-stearothEco-faecalLis-monoc3B-cereus4B-subtilisStc-therm3L-delbruckL-caseiFus-nucleaGlb-violacOlst-lut_CZea mays CNost-muscrSyn-6301Tnm-lapsumFlx-litoraCy-lyticaEmb-brevi2Bac-fragilPrv-rumcolPrb-diffluCy-hutchinFlx-canadaSap-grandiChl-limicoWln-succi2Hlb-pylor6Cam-jejun5Stm-ambofaArb-globifCor-xerosiBif-bifiduCfx-aurantTmc-roseumAqu-pyrophenv-SBAR12env-SBAR16Msr-barkerTpl-acidopMsp-hungatHf-volcaniMb-formiciMt-fervid1Tc-celerArg-fulgidMpy-kandl1Mc-vannielMc-jannascenv-pJP27Sul-acaldaThp-tenaxenv-pJP89Tt-maritimFer-islandMei-ruber4D-radiodurChd-psittaAcbt-capslenv-MC18Pir-staleyLpn-illiniLps-interKSpi-stenosTrp-pallidBor-burgdoSpi-halophBrs-hyodysFib-sucS85Tmf-pendenR-rubrum3Azs-brasi2Rm-vannielRhb-legum8Bdr-japoniSpg-capsulRic-prowazSte-maltopSpr-volutaRub-gelat2Rcy-purpurNis-gonor1Hrh-halch2Alm-vinosmPs-aerugi3E-coliMyx-xanthuBde-stolpiDsv-desulfDsb-postgaC-leptumC-butyric4C-pasteuriEub-barkerC-quercicoHel-chlor2Acp-laidlaM-capricolC-ramosumB-stearothEco-faecalLis-monoc3B-cereus4B-subtilisStc-therm3L-delbruckL-caseiFus-nucleaGlb-violacOlst-lut_CZea mays CNost-muscrSyn-6301Tnm-lapsumFlx-litoraCy-lyticaEmb-brevi2Bac-fragilPrv-rumcolPrb-diffluCy-hutchinFlx-canadaSap-grandiChl-limicoWln-succi2Hlb-pylor6Cam-jejun5Stm-ambofaArb-globifCor-xerosiBif-bifiduCfx-aurantTmc-roseumAqu-pyrophenv-SBAR12env-SBAR16Msr-barkerTpl-acidopMsp-hungatHf-volcaniMb-formiciMt-fervid1Tc-celerArg-fulgidMpy-kandl1Mc-vannielMc-jannascenv-pJP27Sul-acaldaThp-tenaxenv-pJP89Tt-maritimFer-islandMei-ruber4D-radiodurChd-psittaAcbt-capslenv-MC18Pir-staleyLpn-illiniLps-interKSpi-stenosTrp-pallidBor-burgdoSpi-halophBrs-hyodysFib-sucS85
Bacteria Archaea Bacteria Archaea A. rRNA tree of Bacterial and Archaeal Major Groups B. Groups with Completed Genomes Highlighted
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Limited Ecological and Physiological Diversity
• All genomes from cultured species or pathogens/symbionts
• Limited ecological diversity– most are from pathogens or thermophiles
• Limited physiological diversity– need whole range for particular physiologies,
not just extremes
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Why Completeness is Important
• Improves characterization of genome features– Gene order, replication origins
• Better comparative genomics– Genome duplications, inversions
• Presence and absence of particular genes can be very important (e.g., gene loss)
• Missing sequence might be important (e.g., centromere)
• Allows researchers to focus on biology not sequencing• Facilitates large scale correlation studies
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Acknowledgements
• Genome inversions: S. Salzberg, J. Heidelberg, O. White, A. Stoltzfus, J. Peterson, H. Ochman
• Genome sequences and analysis: J. Heidelberg, T. Read, H. Tettelin, K. Nelson, J. Peterson, R. Fleischmann, D. Bryant
• Horizontal transfers: K. Nelson, W. F. Doolittle
• TIGR: C. Fraser, J. Venter, M-I. Benito, S. Kaul, Seqcore
• $$$: NSF, NIH, ONR, DOE
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Close Relatives vs Year0510152025303540199519961997199819992000Solo generaMultiple species
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Evolutionary Studies Improve Most Aspects of Genome Analysis• Phylogeny of species places comparative data in perspective• Evolution of genes and gene families
– Functional predictions– Identification of orthologs and paralogs– Species specific mutation patterns
• Evolution of pathways– Convergence– Prediction of function
• Evolution of gene order/genome rearrangements• Phylogenetic distribution patterns• Identification of novel features
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Genome Information and Analysis Improves Studies of Evolution
• Complete genome information particularly useful • Unbiased sampling• More sequences of genes• Presence/absence information needed to infer certain
events (e.g., gene loss, duplication)• Genome wide mutation and substitution patterns (e.g.,
strand bias)• Diversification and duplication
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Tracing Gene Loss
• Need presence and absence information of orthologous genes from different species
• Determining absence requires a complete genome• May still miss some homologs (e.g., due to rapid
divergence)• Helps to have closely related species• Use standard character state reconstruction methods to
infer gene gain and loss