Phylogenomics talk in 2000 at University of Maryland by J. Eisen

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Phylogenomics:
Combining Evolutionary
Reconstructions and Genome
Analysis into a Single
Composite Approach
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Subject Orf Position
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Query Orf Position
Mycobacterium tuberculosisBacillus subtilisSynechocystis sp.Caenorhabditis elegansDrosophila melanogasterSaccharomyces cerevisiaeMethanobacterium thermoautotrophicumArchaeoglobus fulgidusPyrococcus horikoshiiMethanococcus jannaschiiAeropyrum pernixAquifex aeolicusThermotoga maritimaDeinococcus radioduransTreponema pallidumBorrelia burgdorferiHelicobacter pyloriCampylobacter jejuniNeisseria meningitidisEscherichia coliVibrio choleraeHaemophilus influenzaeRickettsia prowazekiiMycoplasma pneumoniaeMycoplasma genitaliumChlamydia trachomatisChlamydia pneumoniae0.05 changes
ArchaeaBacteriaEukarya
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_CZeamays 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_CZeamays 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
BacteriaArchaeaBacteriaArchaeaA. rRNA tree of Bacterial and Archaeal Major GroupsB. Groups with Completed Genomes Highlighted
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E.coli
E. coli
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V. cholerae
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B1
A1
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A1 A2
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Inversion
Around
Terminus (*)
Inversion
Around
Terminus (*)
Inversion
Around
Origin(*)
Inversion
Around
Origin(*)
* *
* *
* *
* *
Figure 4
Common
Ancestorof
A and B
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Three V. cholerae
Photolyases
Phr.S thyp
PHR E. coli
ORFA00965*********
phr.neucr
Phr.Tricho
Phr.Yeast
Phr.B firm
phr.strpy
phr.haloba
PHR STRGR
pCRY1.huma
phr.mouse
phr2.human
phr2.mouse
phr.drosop
phr3.Synsp
ORF02295.Vibch********
phr.neigo
ORF01792.Vibch*******
Phr.Adiant
Phr2.Adian
Phr3.Adian
phr.tomato
CRY1 ARATH
phr.phycom
CRY2 ARATH
PHH1.arath
PHR1 SINAL
phr.chlamy
PHR ANANI
phr.Synsp
PHR SYNY3
phr.Theth
Rh.caps
MTHF type
Class I CPD
Photolyases
6-4
Photolyases
Blue
Light
Receptors
8-HDF type
CPD
Photolyases
Three Photolyase Homologs inV. cholerae
UvrA2
UvrA2 S. coelicolorDrrC S. peuceteusUvrA2 D. radioduransDuplication
in UvrA
family
UvrA1
UvrA H. influenzaeUvrA E. coliUvrA N. gonorrhoaeaUvrA R. prowazekiiUvrA S. mutansUvrA S. pyogenesUvrA S. pneumoniaeUvrA B. subtilisUvrA M. luteusUvrA M. tuberculosisUvrA M. hermoautotrophicumUvrA H. pyloriUvrA C. jejuniUvrA P. gingivalisUvrA C. tepidumuvra1 D. radioduransUvrA T. thermophilusUvrA T. pallidumUvrA B. burgdorefiUvrA T. maritimaUvrA A. aeolicusUvrA Synechocystis sp.
UvrA1UvrA2OppDFUUPNodILivFXylGNrtDCPstBMDRHlyBTAP1CFTR, SURA. ABC TransportersB. UvrA Subfamily
01020304050600510152005010015005101520
Number of Species With High Hits050100150200250
Frequency05101520
Papa BearMama BearBaby Bear
010020030040050005101520
E. coli

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Topics of Discussion
• Introduction to phylogenomics
• Phylogenomics Examples
– Functional prediction
– Not making functional predictions
– Gene duplication
– Genetic exchange within genomes
– Gene loss
– Specialization
– Horizontal gene transfer

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“Nothing in biology makes sense
except in the light of evolution.”
T. H. Dobzhansky (1973)

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Uses of Evolutionary Analysis in
Molecular Biology
• Identification of mutation patterns (e.g., ts/tv ratio)
• Amino-acid/nucleotide substitution patterns useful in
structural studies (e.g., rRNA)
• Sequence searching matrices (e.g., PAM, Blosum)
• Motif analysis (e.g., Blocks)
• Functional predictions
• Classifying multigene families
• Evolutionary history puts other information into
perspective (e.g., duplications, gene loss)
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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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Phylogenomic Analysis
• There are feedback loop between evolutionary and genome
analysis such that for many studies, genome and
evolutionary analyses are interdependent.
• Therefore, I have proposed that they actually be combined
into a single composite approach I refer to as
phylogenomics
• Phylogenomics involves combining evolutionary
reconstructions of genes, proteins, pathways, and species
with analysis of complete genome sequences.

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Outline of Phylogenomics
Gene Evolution EventsPhenotype PredictionsDatabaseSpecies treePresence/AbsenceGene treesCongruenceEvol. DistributionF(x) PredictionsPathway Evolution
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Uses of Phylogenomics I:
Functional Predictions

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Predicting Function
• Identification of motifs
• Homology/similarity based methods
– Highest hit
– Top hits
– Clusters of orthologous groups
– HMM models
– Structural threading and modeling
– Evolutionary reconstructions
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Types of Molecular Homology
• Homologs: genes that are descended from a common
ancestor (e.g., all globins)
• Orthologs: homologs that have diverged after speciation
events (e.g., human and chimp β-globins)
• Paralogs: homologs that have diverged after gene
duplication events (e.g., α and β globin).
• Xenologs: homologs that have diverged after lateral
transfer events
• Positional homology: common ancestry of specific amino
acid or nucleotide positions in different genes

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Phylogenomic Analysis of the
MutS Family of Proteins
• Published analysis
– Eisen JA et al. 1997. Nature Medicine
3(10):1076-1078.
– Eisen JA. 1998. Nucleic Acids Research 26(18):
4291-4300

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Blast Search of H. pylori “MutS”
Score E
Sequences producing significant alignments: (bits) Value
sp|P73625|MUTS_SYNY3 DNA MISMATCH REPAIR PROTEIN 117 3e-25
sp|P74926|MUTS_THEMA DNA MISMATCH REPAIR PROTEIN 69 1e-10
sp|P44834|MUTS_HAEIN DNA MISMATCH REPAIR PROTEIN 64 3e-09
sp|P10339|MUTS_SALTY DNA MISMATCH REPAIR PROTEIN 62 2e-08
sp|O66652|MUTS_AQUAE DNA MISMATCH REPAIR PROTEIN 57 4e-07
sp|P23909|MUTS_ECOLI DNA MISMATCH REPAIR PROTEIN 57 4e-07
• Blast search pulls up Syn. sp MutS#2 with
much higher p value than other MutS
homologs

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H. pylori and MutS
• Prior to this genome, all species that
encoded a MutS homolog also encoded a
MutL homolog
• Experimental studies have shown MutS and
MutL always work together in mismatch
repair
• Problem: what do we conclude about H.
pylori mismatch repair

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Phylogenetic Tree of MutS Family
AquaeTrepaFlyXenlaRatMouseHumanYeastNeucrArathBorbuStrpyBacsuSynspEcoliNeigoThemaTheaqDeiraChltrSpombeYeastYeastSpombeMouseHumanArathYeastHumanMouseArathStrpyBacsuCelegHumanYeastMetthBorbuAquaeSynspDeiraHelpymSacoYeastCelegHuman

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MutS SubfamiliesAquaeTrepaFlyXenlaRatMouseHumanYeastNeucrArathBorbuStrpyBacsuSynspEcoliNeigoThemaTheaqDeiraChltrSpombeYeastYeastSpombeMouseHumanArathYeastHumanMouseArathStrpyBacsuCelegHumanYeastMetthBorbuAquaeSynspDeiraHelpymSacoYeastCelegHumanMSH4MSH5MutS2MutS1MSH1MSH3MSH6MSH2

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MutS Subfamilies
• MutS1 Bacterial MMR
• MSH1 Euk - mitochondrial MMR
• MSH2 Euk - all MMR in nucleus
• MSH3 Euk - loop MMR in nucleus
• MSH6 Euk - base:base MMR in nucleus
• MutS2 Bacterial - function unknown
• MSH4 Euk - meiotic crossing-over
• MSH5 Euk - meiotic crossing-over

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Overlaying Functions onto Tree
AquaeTrepaRatFlyXenlaMouseHumanYeastNeucrArathBorbuSynspNeigoThemaStrpyBacsuEcoliTheaqDeiraChltrSpombeYeastYeastSpombeMouseHumanArathYeastHumanMouseArathStrpyBacsuHumanCelegYeastMetthBorbuAquaeSynspDeiraHelpymSacoYeastCelegHumanMSH4MSH5MutS2MutS1MSH1MSH3MSH6MSH2

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Functional Prediction Using Tree
AquaeTrepaFlyXenlaRatMouseHumanYeastNeucrArathBorbuStrpyBacsuSynspEcoliNeigoThemaTheaqDeiraChltrSpombeYeastYeastSpombeMouseHumanArathYeastHumanMouseArathMSH1
Repair
in Mictochondria
MSH3
Repair of Loops
in Nucleus
MSH6
Repair of Mismatches
in Nucleus
MutS1
Repair of Loops and Mismatches
StrpyBacsuCelegHumanYeastMetthBorbuAquaeSynspDeiraHelpymSacoYeastCelegHumanMSH4
Meiotic Crossing-Over
MSH5
Meiotic Crossing-Over
MutS2 Unknown FunctionsMSH2
Repair of Loops and Mismatches
in Nucleus

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Table 3. Presence of MutS Homologs in Complete Genomes Sequences
Species # of MutS
Homologs
Which
Subfamilies?
MutL
Homologs
Bacteria
Escherichia coli K12 1 MutS1 1
Haemophilus influenzae Rd KW20 1 MutS1 1
Neisseria gonorrhoeae 1 MutS1 1
Helicobacter pylori 26695 1 MutS2 -
Mycoplasma genitalium G-37 - - -
Mycoplasma pneumoniae M129 - - -
Bacillus subtilis 169 2 MutS1,MutS2 1
Streptococcus pyogenes 2 MutS1,MutS2 1
Mycobacterium tuberculosis - - -
Synechocystis sp. PCC6803 2 MutS1,MutS2 1
Treponema pallidum Nichols 1 MutS1 1
Borrelia burgdorferi B31 2 MutS1,MutS2 1
Aquifex aeolicus 2 MutS1,MutS2 1
Deinococcus radiodurans R1 2 MutS1,MutS2 1
Archaea
Archaeoglobus fulgidus VC-16, DSM4304 - - -
Methanococcus janasscii DSM 2661 - - -
Methanobacterium thermoautotrophicum ∆Η 1 ΜυτΣ2 −
Ευκαρψοτεσ
Σαχχηαροµψχεσχερεϖισιαε 6 ΜΣΗ1−6 3+
Ηοµο σαπιενσ 5 ΜΣΗ2−6 3+

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Why was the MutS2 Family Missed?
Blast Search of Syn. sp. MutS#2
Sequences producing significant alignments: (bits) Value
sp|Q56239|MUTS_THETH DNA MISMATCH REPAIR PROTEIN MUT 91 3e-17
sp|P26359|SWI4_SCHPO MATING-TYPE SWITCHING PROTEIN 87 4e-16
sp|P27345|MUTS_AZOVI DNA MISMATCH REPAIR PROTEIN MUTS 83 1e-14
sp|P74926|MUTS_THEMA DNA MISMATCH REPAIR PROTEIN MUTS 81 3e-14
sp|Q56215|MUTS_THEAQ DNA MISMATCH REPAIR PROTEIN MUTS 81 4e-14
sp|P10564|HEXA_STRPN DNA MISMATCH REPAIR PROTEIN HEXA 80 5e-14
• Blast search pulls up standard MutS genes
but with only a moderate p value (10-17
)

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Problems with Similarity Based
Functional Prediction
• Prone to database error propagation.
• Cannot identify orthologous groups reliably.
• Perform poorly in cases of evolutionary rate
variation and non-hierarchical trees (similarity will
not reflect evolutionary relationships in these cases)
• May be misled by modular proteins or large
insertion/deletion events.
• Are not set up to deal with expanding data sets.
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Evolutionary Rate Variation
231456

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Rate Variation and Duplication
Species 3Species 1Species 21A2A3A1B2B3BDuplication

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Evolutionary
Method
PHYLOGENENETIC PREDICTION OF GENE FUNCTIONIDENTIFY HOMOLOGSOVERLAY KNOWN
FUNCTIONS ONTO TREE
INFER LIKELY FUNCTION
OF GENE(S) OF INTEREST
1234563531A2A3A1B2B3B2A1B1A3A1B2B3BALIGN SEQUENCESCALCULATE GENE TREE1246CHOOSE GENE(S) OF INTEREST2A2A53Species 3Species 1Species 211222311A3A1A2A3A1A2A3A464564562B3B1B2B3B1B2B3B ACTUAL EVOLUTION
(ASSUMED TO BE UNKNOWN)
Duplication?EXAMPLE AEXAMPLE BDuplication?Duplication?Duplication5 METHODAmbiguous

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MutS.Aquaeorf.TrepaSPE1.DromeMSH2.XenlaMSH2.RatMSH2.MouseMSH2.HumanMSH2.YeastMSH2.NeucratMSH2.ArathMutS.Borbuorf.StrpyMutS.BacsuMutS
Synsp
MutS
Ecoli
orf
Neigo
MutS
Thema
MutS
Theaq
orf.Deiraorf.ChltrMSH1.SpombeMSH1.YeastMSH3.YeastSwi4.SpombeRep3.MousehMSH3.Humanorf.ArathMSH6.YeastGTBP.HumanGTBP.MouseMSH6.Arathorf
Strpy
yshD
Bacsu
MSH5
Caeel
hMHS5
human
MSH5
Yeast
MutS.Metthorf
Borbu
MutS2
Aquae
MutS
Synsp
orf
Deira
MutS.HelpysgMutS.SauglMSH4.YeastMSH4.CaeelhMSH4.Human
A.AquaeTrepaFlyXenlaRatMouseHumanYeastNeucrArathBorbuStrpyBacsuSynspEcoliNeigoThemaTheaqDeiraChltrSpombeYeastYeastSpombeMouseHumanArathYeastHumanMouseArathMutS2.MetthMutS2.SauglStrpyBacsuCaeelHumanYeastBorbuAquaeSynspDeiraHelpyYeastCaeelHumanMSH4MSH5MutS2MutS1MSH1MSH3MSH6MSH2B.AquaeTrepaXenlaNeucrArathBorbuSynspNeigoThemaDeiraChltrSpombeSpombeArathMouseMouseFlyRatMouseHumanYeastStrpyBacsuEcoliTheaqYeastYeastHumanYeastHumanArathStrpyBacsuHumanMutS2-MetthBorbuAquaeSynspDeiraHelpyMutS2-SauglCaeelYeastYeastCaeelHumanMSH4MSH5MutS2MutS1MSH1MSH3MSH6MSH2C.MutS2StrpyBacsuMutS2.MetthBorbuAquaeSynspDeiraHelpyMutS2.SauglCaeelYeastYeastCaeelHumanHumanMSH4
Segregation &
Crossover
MSH5
Segregation &
Crossover
FlyMouseHumanYeastAquaeTrepaXenlaNeucrArathBorbuSynspNeigoThemaDeiraChltrSpombeSpombeArathArathMutS1
All MMR
(Bacteria)
RatStrpyBacsuEcoliTheaqYeastYeastMouseHumanYeastHumanMouseMSH1
MMR in
Mitochondria
MSH3
MMR of
Large Loops
in Nucleus
MSH6
MMR of
Mismatches and
Small Loops
in Nucleus
MSH2
All MMR
in Nucleus
D.

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ETL1_M.mYA19_S.cCHD1_M.mSYGP4_S.cMOT1_S.cERCC6_H.sRAD26_S.cNUCP_H.sNUCP_M.mYB53_S.cRAD54_S.cDNRPPX_S.pRAD5_S.cRAD8_S.pHIP116A_H.sRAD16_S.cLODE._D.mNPHCG_42HEPA._E.cYB95_S.cF37A4_C.eISWI_D.mSNF2L_H.sBRM_D.mBRM_H.sBRG1_H.sBRG1_M.mSTH1_S.cSNF2_S.c
SNF2SNF2LCHD1ETL1CSBRAD54RAD16LODEEvolution of the SNF2 Family of Proteins

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4 F17L22 170 Arabidopsis thali
4455279 Arabidopsis thaliana
1049068 Lycopersicon esculentu
Homo sapiens
5514652 Drosophila melanogaste
Drosophila melanogaster2
123725 Caenorhabditis elegans
6606113 Capronia mansonii
RpoII.Yeast.YOR151C
107346 Schizosaccharomyces pom
151348 Euplotes octocarinatus
3845258 Plasmodium falciparum
RpoIII.Drome
RpoIII.Drome.7303535
EGAD 114464 Caenorhabditis ele
RpoIII.Yeast.172383
EGAD 145012 Schizosaccharomyce
RpoIII.Neucr.7800864
ARATH5 K18C1 1
Aeropyrum pernix
EGAD 8025 Sulfolobus acidocald
5458046 Pyrococcus abyssi
PH1546 Pyrococcus horikoshii
Thermococcus celer
EGAD 14667 Methanococcus vanni
MJ1040 Methanococcus jannaschi
AF1886 Archaeoglobus fulgidus
Halobacterium halobium
Thermoplasma acidophilum
RPB2 Methanobacterium thermoau
atmystery.BAB02021
ARATH3 MRC8.7
ARATH3 MYM9.12
6723961 Schizosaccharomyces po
RpoI.Yeast.YPR010C
RpoI.Neucr.3668171
RPA2 Rattus norvegicus
Mus musculus
RpoI.Drome.7296211
Caenorhabditis elegans
ARATH1 T1P2.15
ARATH1 F1N18.2
1492072Molluscum contagiosum v
439046 Variola major virus
1143635 Variola virus
2772787 Vaccinia virus
323395 Cowpox virus
6578643 Rabbit fibroma virus
6523969 Myxoma virus
6682809 Yaba monkey tumor viru
7271687 Fowlpox virus
4049822 Melanoplus sanguinipes
2887 Kluyveromyces lactis
EGAD 151364 Sacch kluyveri
1369760 Borrelia burgdorferi
BB0389 Borrelia burgdorferi
TP0241 Treponema pallidum
6652714 Rickettsia massiliae
6652723 Rickettsia sp. Bar29
6652720 Rickettsia conorii
RP140 Rickettsia prowazekii
6960339 Salmonella typhimurium
EGAD 1084 Salmonella choleraes
EC3987 Escherichia coli
EGAD 23892 Buchnera aphidicola
HI0515 Haemophilus influenzae
EGAD 6020 Pseudomonas putida
RPOB Coxiella burnetii
3549149 Legionella pneumophila
RPOB Neisseria meningitidis
HP1198 Helicobacter pylori
6967949 Campylobacter jejuni
AA1339 Aquifex aeolicus
BS0107 Bacillus subtilis
4512396 Bacillus halodurans
6002201 Listeria monocytogenes
EGAD 32012 Staphylococcus aure
EGAD 32011 Spiroplasma citri
MG341 Mycoplasma genitalium
MP326 Mycoplasma pneumoniae
6899151 Ureaplasma urealyticum
Rv0667 Mycobacterium tuberculo
Mycobacterium leprae
7144498 Mycobacterium smegmati
EGAD 39063 Mycobacterium smegm
GP 7331268 Amycolatopsis medit
7248348 Streptomyces coelicolo
7573273 Thermus aquaticus
DR0912 Deinococcus radiodurans
TM0458 Thermotoga maritima
EGAD 74970 80693 Heterosigma c
EGAD Odontella sinensis
EGAD 60306 Spinacia oleracea
EGAD Nicotiana tabacum
6723742 Oenothera elata
5457427 Sinapis alba
5881686 Arabidopsis thaliana
4958867 Triticum aestivum
EGAD 76270 Zea mays
RPOB Oryza sativa
EGAD Pinus thunbergii
EGAD Marchantia polymorpha
7259525 Mesostigma viride
5880717 Nephroselmis olivacea
RPOB Guillardia theta
sll1787 Synechocystis PCC6803
EGAD 75526 Porphyra purpurea
6466433 Cyanidium caldarium
EGAD 76712 Cyanophora paradoxa
RPOB Chlorella vulgaris
EGAD 76424 Euglena gracilis
5231258 Toxoplasma gondii
6492294 Neospora caninum
EGAD 83446 Plasmodium falcipar
100
78
100
85
93
83
100
79
100
100
100
100 100
100
94100
100
74
99
100
99
100
100
99
9480
100
100
100
100
59
100
100
99
56100
100
100
100
58 95
100
97
63
95
100
100
100
81
100
100
100
59
60
99
100
100
94
100
100
69
100
77
100
97
100
71
100
99
58
83
100100
100
99
100
98
100
100
61
99
75
100
73
100
100
59
100
100
72
72
98
52
98
59
100
100
a
Novel RNA Polymerase in A. thaliana
Archaeal
IV
II
III
I
Viral
Bacterial - RpoB
Plastid- RpoBs

TIGRTIGR
Novel Large Subunit Rubisco in
Chlorobium tepidumAgathis.gi3982533
Agathis.gi3982549
Araucaria.gi3982517
Agathis.gi3982535
Agathis.gi3982541
Venturiella.gi4009420
Leucobryum.gi6230571
Mougeotia.gi1145415
Anabaena.gi68158
Thife.gi2411435
Thiin.gi4105518
Metja.gi2129276
Pyrho.gi|3257353
Pyrab.gi|5458634
Pyr karaensis.gi3769302
Arcfu.gi2648911
Arcfu.gi2648975
Bacsu.gi2633730
Chlte.ORF02314
100
100
96
54
99
58
66
59
100
100
82
67
100
100
100
93
Type X
Type I
Rubisco
Large
Subunit
Phylogeny

TIGRTIGR
Uses of Phylogenomics II:
Knowing when to Not Predict
Functions

TIGRTIGR
Deinococcus radiodurans

TIGRTIGR
DNA Repair Genes in D.
radiodurans Complete Genome
Process Genes in D. radiodurans
Nucleotide Excision Repair UvrABCD, UvrA2
Base Excision Repair AlkA, Ung, Ung2, GT, MutM, MutY-Nths,
MPG
AP Endonuclease Xth
Mismatch Excision Repair MutS, MutL
Recombination
Initiation
Recombinase
Migration and resolution
RecFJNRQ, SbcCD, RecD
RecA
RuvABC, RecG
Replication PolA, PolC, PolX, phage Pol
Ligation DnlJ
dNTP pools, cleanup MutTs, RRase
Other LexA, RadA, HepA, UVDE, MutS2

TIGRTIGR
Recombination Genes in Genomes
Pathway |------------------------------Bacteria---------------------------| |---Archaea---| Euks
Protein Name(s)
Initiation
RecBCD pathway
RecB + + - - - - - - + + - + - - - - - - - -
RecC + + - - - - - - + ±+ - ± - - - - - - - -
RecD + + - - ± - - - + ±+ - ++ - ± ±+ - - - - -
RecF pathway
RecF + + + - + - - + + - + ± - - + - - ± ± ±
RecJ + + + + + - - + - + + + + + + - - - - -
RecO + + - - + - - + + - - - - - ± - - - - -
RecR + + + ±+ + - - + + - + + - + + - - - - -
RecN + + + + + - - + + - + - ± + + - - ± ± -
RecQ + + - - + - - + - - + - - - + - - - - + ++
RecE pathway
RecE/ExoVIII + - - - - - - - - - - - - - - - - - - -
RecT + - - - + - - - - - - - - - - - - - - -
SbcBCD pathway
SbcB/ExoI + + - - - - - - - - - - - - - - - - - -
SbcC + - - - + - - + - + + - + + + ± ± ± ± ± ±
SbcD + - - - + - - + - + + - + + + ± ± ± ± ± ±
AddAB Pathway
AddA/RexA - - + - + - - - - - + + - ± - - - - - -
AddB/RexB - - - - + - - - - - - - - - - - - - - -
Rad52 pathway
Rad52, Rad59 - - - - - - - - - - - - - - - - - - - ++ +
Mre11/Rad32 ± - - - ± - - ± - ± ± - ± ± ± + + + + + +
Rad50 ± - - - ± - - ± - ± ± - ± ± ± + + + ± + +
Recombinase
RecA, Rad51 + + + + + + + + + + + + + + + + + + + ++ ++
Branch migration
RuvA + + + + + + + + + + + + + - + - - - - -
RuvB + + + + + + + + + + + + + - + - - - - -
RecG + + + + + - - + + + + - + + + - - - - -
Resolvases
RuvC + + + + - - - + + - + + + - + - - - - -
RecG + + + + + - - + + + + - + + + - - - - -
Rus + - - - - - - - ±+ - - - - ±+ - - - - - -
CCE1 - - - - - - - - - - - - - - - - - - - +
Other recombination proteins
Rad54 - - - - - - - - - - - - - - - - - - - + +
Rad55 - - - - - - - - - - - - - - - - - - - + +
Rad57 - - - - - - - - - - - - - - - - - - - + +
Xrs2 - - - - - - - - - - - - - - - - - - - +

TIGRTIGR
Unusual Features of D. radiodurans
DNA Repair Genes
Process Genes
Nucleotide excision repair Two UvrAs
Base excision repair Four MutY-Nths
Recombination RecD but not RecBC
Replication Four Pol genes
dNTP pools Many MutTs, two RRases
Other UVDE

TIGRTIGR
Problem:
List of DNA repair gene homologs
in D. radiodurans genome is not
significantly different from other
bacterial genomes of the similar size

TIGRTIGR
-Ogt
-RecFRQN
-RuvC
-Dut
-SMS
-PhrI
-AlkA
-Nfo
-Vsr
-SbcCD
-LexA
-UmuC
-PhrI
-PhrII
-AlkA
-Fpg
-Nfo
-MutLS
-RecFORQ
-SbcCD
-LexA
-UmuC
-TagI
-PhrI
-Ogt
-AlkA
-Xth
-MutLS
-RecFJORQN
-Mfd
-SbcCD
-RecG
-Dut
-PriA
-LexA
-SMS
-MutT
-PhrI
-PhrII?
-AlkA
-Fpg
-Nfo
-RecO
-LexA
-UmuC
-PhrI
-Ung?
-MutLS
-RecQ?
-Dut
-UmuC
-PhrII
-Ogg
-Ogt
-AlkA
-TagI
-Nfo
-Rec
-SbcCD
-LexA
-Ogt
-AlkA
-Nfo
-RecQ
-SbcD?
-Lon
-LexA
-AlkA
-Xth
-Rad25?
-AlkA
-Rad25
-Nfo
-Ogt
-Ung
-Nfo
-Dut
-Lon
-Ung
-PhrII
-PhrI
Ecoli
Haein
Neigo
Helpy
Bacsu
Strpy
Mycge
Mycpn
Borbu
Trepa
Synsp
Metjn
Arcfu
Metth
Human
Yeast
BACTERIA ARCHAEA EUKARYOTES
from mitochondria
+Ada
+MutH
+SbcB
dPhr
+TagI?
+Fpg
+UvrABCD
+Mfd
+RecFJNOR
+RuvABC
+RecG
+LigI
+LexA
+SSB
+PriA
+Dut?
+Rus
+UmuD
+Nei?
+RecE
tRecT?
+Vsr
+RecBCD?
+RFAs
+TFIIH
+Rad4,10,14,16,23,26
+CSA
+Rad52,53,54
+DNA-PK, Ku
dSNF2
dMutS
dMutL
dRecA
+Rad1
+Rad2
+Rad25?
+Ogg
+LigII
+Ung?
+SSB,
+Dut?
+PhrI, PhrII
+Ogt
+Ung, AlkA, MutY-Nth
+AlkA
+Xth, Nfo?
+MutLS?
+SbcCD
+RecA
+UmuC
+MutT
+Lon
dMutSI/MutSII
dRecA/SMS
dPhrI/PhrII
+Spr
t3MG
+Rad7
+CCE1
+P53
dRecQ
dRad23
+MAG?
-PhrII
-RuvC
tRad25
+TagI?
+RecT
tUvrABCD
tTagI ?
Gain and Loss of Repair Genes
TIGRTIGR

TIGRTIGR
Repair Studies in Different Species
(determined by Medline searches as of 1998)
Humans 7028
E. coli 3926
S. cerevisiae 988
Drosophila 387
B. subtilits 284
S. pombe 116
Xenopus 56
C. elegans 25
A. thaliana 20
Methanogens 16
Haloferax 5
Giardia 0

TIGRTIGR
Uses of Phylogenomics III:
Gene Duplication

TIGRTIGR
Why Duplications Are Useful to Identify
• Allows division into orthologs and paralogs
• Aids functional predictions
• Recent duplications may be indicative of species’
specific adaptations
• Helps identify mechanisms of duplication
• Can be used to study mutation processes in
different parts of genome

TIGRTIGR
MutY-NthDEIRA ORF00829DEIRA ORF02784DEIRAAQUAEMETJAMETTHTHEMACHLTRHAEINMCYTUTHEMAMETTHPYRHOAQUAEMETJAARCFUCELEGVIBCHECOLIHAEINTREPARICPRAQUAEBACSUCAMJEHELPYMCYTUSYNSPCHLPNCHLTRBBUR

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*******************************************************************************

TIGRTIGR
Phosphate Transporters
ARCFUSYNSPTHEMAAQUAEMETJAMCYTUMCYTUVIBCHECOLIDEIRA_ORF00198DEIRA_ORFA00139DEIRA_ORF00510

TIGRTIGR
Levels of Paralogy Within A Genome
• All
– All members of a gene family are linked together
• Top matches
– Only top matching pairs are linked together.
Therefore, if in a large gene family, only the pair
from the most recent duplication event is included
• Recent
– Operational definition based on comparison to other
species. Only pairs which are more similar to each
other than to selected other species are included.

TIGRTIGR
C. pneumoniae Paralogs - All
0
250000
500000
750000
1000000
1250000
0 250000 500000 750000 1000000 1250000
Query Orf Position

TIGRTIGR
C. pneumoniae Paralogs - Top
0
250000
500000
750000
1000000
1250000
0 250000 500000 750000 1000000 1250000
Query Orf Position

TIGRTIGR
C. pneumoniae Paralogs – Recent
0
250000
500000
750000
1000000
1250000
0 250000 500000 750000 1000000 1250000
Query Orf Position

TIGRTIGR
Uses of Phylogenomics IV:
Genetic Exchange within Genomes

TIGRTIGR
Uses of Phylogenomics V:
Gene Loss

TIGRTIGR
Why Gene Loss is Useful to Identify
• Indicates that gene is not absolutely required for
survival
• Helps distinguish likelihood of gene transfers
• Correlated 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

TIGRTIGR
EuksArchBacteriaLossEvolutionary Origin of GeneMTMJSCHSAADRTABSMGMPBBTPHPHIECSSMTPresence ( ) or Absence of GeneSpecies AbbreviationKingdom
Example of Tracing Gene Loss
TIGRTIGR

TIGRTIGR
51234
E. coliH. influenzaeN. gonorrhoeaeH. pyloriSyn. spB. subtilisS. pyogenesM. pneumoniaeM. genitaliumA. aeolicusD. radioduransT. pallidumB.burgdorferiA. aeolicusS pyogenesB. subtilisSyn. spD. radioduransB. burgdorferiSyn. spB. subtilisS. pyogenesA. aeolicusD. radioduransB. burgdorferiMutS2MutS1A.B.Gene
Duplication
Gene
Duplication
Ancient Duplication in MutS Family

TIGRTIGR
Loss of MMR
• Lost in many pathogen species
• Mechanism of loss
– gene deletion (e.g., M. tuberculosis, H. pylori)
– frameshifts (e.g., N. meningitidis, S.
pneumoniae)
– some species have evolved systems to turn
MMR on and off depending on conditions (e.g.,
E. coli)

TIGRTIGR
Need for Phylogenomics Example:
Gene Duplication and Loss
• Genome analysis required to determine number of
homologs in different species
• Evolutionary analysis required to divide into
orthology groups and identify gene duplications
• Genome analysis is then required to determine
presence and absence of orthologs
• Then loss of orthologs can be traced onto
evolutionary tree of species

TIGRTIGR
Uses of Phylogenomics VI:
Specialization

TIGRTIGR
Species Distribution of Homologs of
D. radiodurans Genes
01020304050600510152005010015005101520
Number of Species With High Hits050100150200250
Frequency05101520
Papa BearMama BearBaby Bear010020030040050005101520
E. coli

TIGRTIGR
Specialized Genetic Elements
(Chromosome II and Megaplasmid)
• Many two component systems
• Nitrogen metabolism
• LexA
• Ribonucleotide reductase
• UvrA2
• Many transcription factors (e.g., HepA)
• Iron metabolism

TIGRTIGR
Uses of Phylogenomics VII:
Genome Rearrangements

TIGRTIGR
V. cholerae vs. E. coli All Hits
0
1000000
2000000
3000000
4000000
5000000
E. coli
Coordinates
0 1000000 2000000 3000000
V. cholerae Coordinates

TIGRTIGR
V. cholerae vs. E. coli Top Hits
0
1000000
2000000
3000000
4000000
5000000
E. coli
Coordinates
0 1000000 2000000 3000000

TIGRTIGR
V. cholerae vs. E. coli
Only if EC-Orf is Closest in All Genomes
0
1000000
2000000
3000000
4000000
5000000
E. coli
Coordinates
0 1000000 2000000 3000000

TIGRTIGR
V. cholerae vs. E. coli Proteins
Top
0
1000000
2000000
3000000
4000000
V. cholerae ORF Coordinates

TIGRTIGR
S. pneumoniae vs. S. pyogenes DNA F+R
0500000100000015000002000000BSP vs Spyo

TIGRTIGR
M. tuberculosis vs. M. leprae DNA
0
1000000
2000000
3000000
4000000
M1

TIGRTIGR
Duplication and Gene Loss Model
A
B
CD
E
F
A
B
CD
E
F
A
B
C
D
E
F
A
B
C
D
E
F
A’
B’
C’
D’
E’
F’
A
B
C
D
E
F
A’
B’
C’
D’
E’
F’
A
C
D
F
A’
B’
E’
E. coli
E. coli
B
C
D
F
A’
B’
D’
E’
V. cholerae
A
B
C
D
E
F
A’
B’
C’
D’
E’
F’

TIGRTIGR C. trachomatis MoPn
C.pneumoniaeAR39
Origin
Termination
C. trachomatis vs C. pneumoniae Dot Plot

TIGRTIGR
B1
A1
B2
A2
B3
A3
A2
A1 A2
A3
B2
B1
B3
B2
24
23
22
21
20
19
18171615
14
13
12
11
10
9
6
7
258
26
27
28
29
30
1 2
3
4
5
3132
B1
3132
6
7
8
9
10
11
12
13
14
15161718
19
20
21
22
23
24
25
26
27
28
29
30
1 2
3
4
5
3132
B3 24
23
22
21
20
19
18171615
14
13
12
11
10
9
6
7
258
26
27
28
29
3
3231
30
4
5
2 1
A1
3132
6
7
8
9
10
11
12
13
14
15161718
19
20
21
22
23
24
25
26
27
28
29
30
1 2
3
4
5
3132
A2
3132
6
7
8
9
10
11
12
13
19
18171615
14
20
21
22
23
24
25
26
27
28
29
30
1 2
3
4
5
3132
A3
2
6
7
8
9
10
11
12
13
19
18171615
14
20
21
22
23
24
25
26
27
5
4
3
31
30
29
28
1 32
B2
Inversion
Around
Terminus (*)
Inversion
Around
Terminus (*)
Inversion
Around
Origin (*)
Inversion
Around
Origin (*)
* *
* *
* *
* *
Figure 4
Common
Ancestor of
A and B
3132
6
7
8
9
10
11
12
13
14
15161718
19
20
21
22
23
24
25
26
27
28
29
30
1 2 3
4
5
3132

TIGRTIGR
Uses of Phylogenomics VIII:
Horizontal Gene Transfer and
Species Evolution

TIGRTIGR
Examples of Horizontal Transfers
• Antibiotic resistance genes on plasmids
• Insertion sequences
• Pathogenicity islands
• Toxin resistance genes on plasmids
• Agrobacterium Ti plasmid
• Viruses and viroids
• Organelle to nucleus transfers

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

TIGRTIGR
Steps in Lateral Gene Transfer
1
2
3-5
6
A B C D

TIGRTIGR
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

TIGRTIGR
E. coli and S. typhimurium Transfer
E. coliS. typhimuriumOld ModelE. coliS. typhimuriumNew Model

TIGRTIGR
Archaeal genes in bacterial genomesArchaeal genes in bacterial genomes**
Bacterial speciesBacterial species Best hits to ArchaealBest hits to Archaeal
Thermotoga maritimaThermotoga maritima 451 (24%)451 (24%)
Aquifex aeolicusAquifex aeolicus 246 (16%)246 (16%)
SynechocystisSynechocystis sp.sp. 126 (4%)126 (4%)
Borrelia burgdorferiBorrelia burgdorferi 45 (3.6%)45 (3.6%)
Escherichia coliEscherichia coli 99 (2.3%)99 (2.3%)
** 1010-5-5
over 60% of sequenceover 60% of sequence

TIGRTIGR
Evidence for lateral gene transfer inEvidence for lateral gene transfer in
ThermotogaThermotoga
1. 81 archaeal-like genes are clustered in 15 regions which
range in size from ~ 4 to 20 kb; many share conserved gene
order with their archaeal counterparts.
2. Many of the archaeal-like genes correspond to regions with
a significantly different base composition than the rest of
the chromosome.
3. Some of these regions are associated with a 30 bp repeat
structure found only in thermophiles.
4. Initial phylogenetic analyses of some of these genes lends
support to lateral gene transfer.

TIGRTIGR
0987 09900989ThermotogaThermotoga ORFORF
Archaea homologArchaea homolog
Bacterial homologBacterial homolog
Eukaryote homologEukaryote homolog
ThermotogaThermotoga ORFORF
Archaea homologArchaea homolog
Bacterial homologBacterial homolog
Eukaryote homologEukaryote homolog
0988 0991 0992 0993 0994
0995 0996 0997 0998 0999 1000 10021001 1003
Region TM00987 - TM1003 ( 21kb Archaea-like stretch)Region TM00987 - TM1003 ( 21kb Archaea-like stretch)
79% 69% 69% 72%
72% 69% 65%61% 78%
72%
TransposonTransposon
54%
48%
68% 51%
73%
73%
Regulatory proteinRegulatory protein

TIGRTIGR
0
100
200
300
400
500
600
700
500 1000 1500 2000 2500 3000 3500 4000 4500
Orfs in Target Genome
Best
Matches
Best Matches to Prokaryotes
CAUCR BACSU
ECOLI
MYCTU
SYNSP

TIGRTIGR
A. thaliana T1E2.8 is a
Chloroplast Derived HSP60ARATH -T1E2.8**********ECOLHAEINVIBCHVIBCHRICPRYEASTCHLPNCHLTRAQUAECAMJEHELPYBBURTREPATHEMABACSUDEIRAMCYTUMCYTUSYNSPSYNSPODONT CPSTMYCGEMYCPNCHLPNCHLTRCHLPNCHLTRARCFUARCFUMETJAPYRHOMETTHMETTHYEASTYEASTYEASTYEASTCELEGYEASTYEASTYEASTCELEGYEASTYEASTCELEGYEASTCELEGCELEG
EukaryaArchaeaBacteriaCyano/Cpst

TIGRTIGR
ParA Phylogeny
pOMB25.Bor
BBl32.Borb
Borbu3
Borbu.2
BBM32.Borb
CP32-6.Bor
BBA20.Borb
Cp18.Borbu
pOMB10.Bor
pLp7E.Borb
BBE19.Borb
BBB12.Borb
BBN32.Borb
BBF13.Borb
BBH28.Borb
BBK21.Borb
BBU05.Borb
BBJ17.Borb
BBQ08.Borb
BBF24.Borb
OrfC.Borbu
BBG08.Borb
Pyrab
Pyrho
YZ24 METJA
IncC1.Enta
IncC2.Enta
INC1 ECOLI
INC2 ECOLI
Orf.pRK2
IncC.pRK2
pM3.ParA
ORF3.Pseae
ORFB.Psepu
2603.Vibch*****
ParA.Strco
Strco2
Strco3
Myctu4
Mycle3
Deira.Chro
Soj.Trepa
SOJ BACSU
Ricpr
YGI1 PSEPU
ParA.Caucr
pAG1.Corgl
Mycle
Mycle2
Rv1708.Myc
Strco
Rv3213.Myc
Helpy99
Helpy26695
A00900.Vib*****
ParB.pR27.
ParA.pMT1.
parA.pMT1
parA.phage
ParA phage
ORFA00900
SOPA ECOLI
F-Plasmid
PhageN13
pCD1.Yerpe
pCD1#2.Yer
pYVe227.Ye
pNL1.Sphar
pQPH1.Coxb
p42d.Rhile
p42d.Rhiet
REPA AGRRA
pRiA4b.Agr
pTiB6S3.Ag
pTi-SAKURA
pRL8JI.Rhi
Y4CK Plasm
ParA.Raleu
pL6.5.Psef
Chr2.Deira
MP1#2.Deir
MP1.Deira
PX02.Bacan
ORF298.Clo
SojC.Halsp
Borbu4
sojD.Halsp
plasmid.St
SojB.Halsp
ParA.Rhoer
SOJ MYCPN
SOJ MYCGE
MinD2.Pyra
Pyrho2
pK214.Lacl
PatA.synsp
Deira.ParA
pCHL1.Chlt2
GP5D CHLTR
pCHL1.Chlt
Chltr
Chlps
Chlps2
Chlpn
Chltr2
Chlpn2
Chromosomal
Plasmid
and
Phage
BBQ08.Borb
Chlamydial
Inc
Borrelia
Plasmids
Archaea
Misc
Evolution of Chromosome Partitioning Proteins (ParA)

TIGRTIGR
Horizontal Gene Transfer II

TIGRTIGR
Reconciling a Tree of Life in the
Context of Lateral Gene Transfer

TIGRTIGR
rRNA Tree of Complete Genomes

TIGRTIGR
Whole Genome Phylogeny

TIGRTIGR
rRNA vs. Whole Genome Trees

TIGRTIGR
Evolutionary Genome Scanning
• Distribution patterns/phylogenetic profiles
• Patterns of evolution (ds/dn, correlations, constraints)
• Lateral gene transfers (organellar genes, Pathogenicity islands)
• Subdividing gene families
• Functional predictions (gene trees, PG profiles)
• Gene duplications
• Gene loss
• Specialization
• Comparing close relatives
• Species evolution

TIGRTIGR
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
BacteriaArchaeaBacteriaArchaeaA. rRNA tree of Bacterial and Archaeal Major GroupsB. Groups with Completed Genomes Highlighted

TIGRTIGR
True Phylogenetic Methods
Work Best
MutS2.SynsMutS2.BacsMutS2.HelpMutS2.DeirMutsl.MettMSH4.CelegMSH4.YeastMSH4.humanmMutS.SacoMSH3.yeastC23C11.SpoMSH1.YeastMSH3.HumanREP1.MouseGTBP.MouseGTBP.HumanMSH6.YeastMSH5.HumanMSH5.CelegMSH5.YeastMSH2.HumanMSH2.MouseMSH2.YeastMutS.EcoliMutS.SynspMutS.DeiraMutS.Bacsu
MutS.EcoliMutS.SynspMutS.BacsuMutS.DeiraMSH2.HumanMSH2.MouseMSH2.YeastMSH3.HumanREP1.MouseGTBP.MouseGTBP.HumanMSH6.YeastC23C11.SpoMSH1.YeastMSH3.yeastMSH4.CelegMSH4.humanMSH5.CelegMSH5.YeastmMutS.SacoMSH5.HumanMSH4.YeastMutS2.SynsMutS2.BacsMutS2.DeirMutS2.HelpMutsl.Mett
UPGMANeighbor-Joining

TIGRTIGR
Acknowledgements
• Genome duplications: S. Salzberg, J. Heidelberg, O. White,
A. Stoltzfus, J. Peterson
• 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
• $$$: DOE, NSF, NIH, ONR

TIGRTIGR
TIGTIG
RR
OtherOther
peoplepeople
Mom and DadMom and Dad
S. KarlinS. Karlin
M. FeldmanM. Feldman
A. M. CampbellA. M. Campbell
R. FernaldR. Fernald
R. ShaferR. Shafer
D. AckerlyD. Ackerly
D. GoldsteinD. Goldstein
M. EisenM. Eisen
J. CourcelleJ. Courcelle
R. MyersR. Myers
C. M. CavanaughC. M. Cavanaugh
P. HanawaltP. Hanawalt
NSFNSF
J. HeidelberJ. Heidelber
T.ReadT.Read
S. KaulS. Kaul
M-I BenitoM-I Benito
J. C. VenterJ. C. VenterC. FraseC. Fraser
S. SalzbergS. Salzberg
O. WhiteO. White
K. NelsonK. Nelson
$$$$$$
ONRONR
DOEDOE
NIHNIH
H. TettelinH. Tettelin

TIGRTIGR
Uses of Phylogenomics IX:
Evolution Within Species

TIGRTIGR
M. tuberculosis strain phylogeny (Indels)

TIGRTIGR
Musser-Type Evolution (Indel Phylogeny)
98a
107a
43a
73a
105a
133a
114a
169a
218a
290a
160a
159a
13a
18a
26a
30a
32a
53a
58a
70a
96a
97a
100a
124a
204a
208a
236a
239a
249a
286a
99a
279a
205a
304a
54a
155a
165a
CDC1551a
223a
110a
122a
245a
313a
36a
40a
71a
79a
168a
254a
283a
312a
4a
12a
41a
42a
52a
77a
187a
214a
81a
129a
274a
220a
64a
48a
55a
60a
72a
80a
83a
85a
89a
91a
95a
111a
170a
171a
182a
212a
219a
225a
244a
278a
301a
195a
2a
123a
207a
306a
69a
94a
101a
102a
112a
113a
121a
132a
211a
222a
235a
250a
284a
285a
N1a
87a
117a
120a
136a
191a
237a
261a
37a
131a
269a
240a
63a
197a
206a
75a
108a
263a
128a
172a
162a
86a
38a
109a
119a
248a
6a
65a
68a
189a
66a
106a
227a
31a
78a
202a
213a
62a
163a
224a
256a
276a
287a
173a
291a
252a
281a
295a
310a
251a
151a
188a
292a
140a
141a
103a
174a
229a
259a
H37Rv
88a
44a
74a
76a
126a
282a
166a
210a
84a

TIGRTIGR
Consistency Indices (Indel Phylogeny)
Calculated over stored trees
CI
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
maximum
average
minimum
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 201
Character

TIGRTIGR
Phylogenomics I:
Presence/Absence of Homologs
• Important to have complete genomes
• Similarity searches with high “homology
threshold” (to prevent false positives)
• Iterative searches (to prevent false negatives)
• Multiple sequence alignments to confirm
assignment of homology and to divide up
multi-domain proteins

TIGRTIGR
Phylogenomics II:
Phylogenetic Analysis of Homologs
• Multiple sequence alignment
• Mask alignment (exclude certain regions)
– ambiguous regions of alignment
– hypervariable regions and regions with large gaps
• Phylogenetic tree with method of choice
• Robustness checks
– bootstrapping
– compare trees with different alignments
– compare trees with different tree-building methods

TIGRTIGR
Phylogenomics III:
Inferring Evolutionary Events
• Infer evolutionary distribution patterns (overlay
presence/absence onto species tree)
• Compare gene tree vs. species tree
• Compare gene tree vs. evolutionary distribution
• Infer gene duplication and transfer events
• Combine gene transfer and duplication information with
evolutionary distribution analysis to infer gene loss, gene
origin, and timing of gene duplications and transfers

TIGRTIGR
Phylogenomics IV:
Functional Predictions and Evolution
• Overlay experimentally determined functions
onto gene tree
• Infer changes in function
– many changes suggests caution should be used in
making new predictions
• Predict functions based on position in tree
relative to genes with known functions and
based on orthology groups

TIGRTIGR
Phylogenomics V:
Pathway Analysis
• Correlated presence/absence of all genes in pathway in different
species?
– If not, maybe non-orthologous gene displacement
– Alternatively, pathway may be different between species
• Correlated evolutionary events for genes in pathway
– loss of all genes at once
– correlated duplications?
• Compare evolution of function between pathways
– The number of times an activity has evolved helps in making
predictions of function/phenotype

TIGRTIGR
Steps in Phylogenomic Analysis
• Create database of genes of interest
• Presence/absence of homologs in complete genomes
• Phylogenetic trees of each gene family
• Infer evolutionary events (gene origin, duplication, loss and transfer)
• Refine presence/absence (orthologs, paralogs, subfamilies)
• Functional predictions and functional evolution
• Analysis of pathways

TIGRTIGR
Evolution as a Screening
Method
• Gene loss
• Lateral gene transfers
• Organellar genes
• Structurally constrained genes
• Correlated evolutionary changes

TIGRTIGR
Evolutionary Genome Scanning
• Distribution patterns/phylogenetic profiles
• Patterns of evolution
– (ds/dn)
– Structurally constrained genes
– Correlated evolutionary changes
• Lateral gene transfers
– Organellar genes
– Pathogenicity islands
• Subdividing gene families
– Orthologs vs paralogs
– Functional predictions
– Subfamilies
– Motif identification
• Gene loss

TIGRTIGR
Genome Sequences Allow
“Hypothesisless Research”
• DNA microarrays
• Proteomics
• GC skew and other nucleotide composition
analyses
• Parallel genome wide genetic experiments
• Evolutionary genome scanning
• Phylogenetic profiles

Phylogenomics talk in 2000 at University of Maryland by J. Eisen

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