jonathan eisen talk for #scs2012 at #ismb "networks in genomics and bioinformatics: from...
DESCRIPTION
Talk as part of http://www.iscb.org/ismb2012-program/ismb2012-scs"Networks in genomics and bioinformatics: from phylogeny to Twitter"TRANSCRIPT
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Networks in genomics and bioinformatics: from phylogeny to Twitter
ISCB2012July 12, 2012
Jonathan A. EisenUniversity of California, Davis
@phylogenomics
Friday, July 13, 12
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Networks in genomics and bioinformatics: from phylogeny to Twitter
ISCB2012July 12, 2012
Jonathan A. EisenUniversity of California, Davis
@phylogenomics
Friday, July 13, 12
![Page 3: Jonathan Eisen talk for #SCS2012 at #ISMB "Networks in genomics and bioinformatics: from phylogeny to Twitter"](https://reader033.vdocuments.mx/reader033/viewer/2022060108/554e8f0ab4c905fc368b4b36/html5/thumbnails/3.jpg)
A meandering path and lessons “learned”
ISCB2012July 12, 2012
Jonathan A. EisenUniversity of California, Davis
@phylogenomics
Friday, July 13, 12
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Friday, July 13, 12
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Social Networking in Science
Friday, July 13, 12
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Bacterial evolve
Friday, July 13, 12
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Friday, July 13, 12
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Phylogenomics of Novelty
Friday, July 13, 12
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Phylogenomics of Novelty
Friday, July 13, 12
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Origin of New Functions and
Processes
Phylogenomics of Novelty
Friday, July 13, 12
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Origin of New Functions and
Processes
Phylogenomics of Novelty
•New genes•Changes in old genes•Changes in pathways
Friday, July 13, 12
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Origin of New Functions and
Processes
Phylogenomics of Novelty
•New genes•Changes in old genes•Changes in pathways
Friday, July 13, 12
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Origin of New Functions and
Processes
Genome Dynamics
Phylogenomics of Novelty
•New genes•Changes in old genes•Changes in pathways
Friday, July 13, 12
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Origin of New Functions and
Processes
Genome Dynamics
Phylogenomics of Novelty
•New genes•Changes in old genes•Changes in pathways
•Evolvability•Repair and recombination processes•Intragenomic variation
Friday, July 13, 12
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Origin of New Functions and
Processes
Genome Dynamics
Phylogenomics of Novelty
•New genes•Changes in old genes•Changes in pathways
•Evolvability•Repair and recombination processes•Intragenomic variation
Friday, July 13, 12
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Origin of New Functions and
Processes
Species Evolution
Genome Dynamics
Phylogenomics of Novelty
•New genes•Changes in old genes•Changes in pathways
•Evolvability•Repair and recombination processes•Intragenomic variation
Friday, July 13, 12
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Origin of New Functions and
Processes
Species Evolution
Genome Dynamics
Phylogenomics of Novelty
•New genes•Changes in old genes•Changes in pathways
•Phylogenetic history•Vertical vs. horizontal descent•Needed to track gain/loss of processes, infer convergence
•Evolvability•Repair and recombination processes•Intragenomic variation
Friday, July 13, 12
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Undergrad Lesson 1:Be prepared for random events
• Gould’s class b/c planned on not majoring in Biology
• RMBL via backpacking trip• Geology library job w/ Nabokov collection
b/c went to wrong building• Discovering Colleen Cavanaugh’s lab via
street encounter
Friday, July 13, 12
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Undergrad Lesson 2: Phylogeny Matters
• “MacClade”• Phylogenetic ecology• Phylotyping
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Phylogeny Matters
Eisen et al. 1992
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Grad school lesson I: find right people to work with
• Went to work on butterfly population biology and phylogeny
• Advisor and I did not see eye to eye• Despite great subject for me (combined
phylogeny, molecular evolution, RMBL, etc), chose not to join lab
• Did many rotations …• Picked final lab in part b/c advisor was right
match
Friday, July 13, 12
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Grad school lesson II:never too late to change
• Wanted to combine DNA repair studies and molecular evolution
• I: Thymineless death• II: Adaptive mutation• III: Repair in archaea
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Grad school lesson II:never too late to change
• Wanted to combine DNA repair studies and molecular evolution
• I: Thymineless death• II: Adaptive mutation• III: Repair in archaea• IV: Bioinformatics and genome analysis …
Friday, July 13, 12
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Grad school lesson III:Get others to do your work
• Interested in RecA structure function relationships
• Using phylogeny to look for correlated substitutions in RecA structure, like done with rRNA
• But not enough sequences …
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Shotgun Sequencing Allows Use of Alternative Anchors (e.g., RecA)
Venter et al., 2004Friday, July 13, 12
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Grad school lesson IV:Stealing is good
• Phylogenetic perspective in bioinformatics missing
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“Nothing in biology makes senseexcept in the light of evolution.”
T. H. Dobzhansky (1973)
Friday, July 13, 12
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Evolutionary Perspective and Comparative Biology
• Comparative biology is the analysis of differences and similarities between species.
• An evolutionary perspective is useful in such studies because this allows one to focus not just on the levels and degrees of similarity or difference but on how and why similarities and differences came to be.
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Phylogenomics
• Lots of sequences being produced with no functions associated with them
• Much debate in community about how to predict functions
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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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Phylogeny Matters
Eisen et al. 1992
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Evolutionary Functional Prediction
1 2 3 4 5 6
3 5
3
1A 2A 3A 1B 2B 3B
2A 1B
1
1 2
2
2 31
1A 3A
1A 2A 3A
1A 2A 3A
4 6
4 5 6
4 5 6
2B 3B
1B 2B 3B
1B 2B 3B
1A3A
1B 2B3B
12 4
62A
2A
53
5
EXAMPLE BMETHOD
Duplication?
Duplication?
IDENTIFY HOMOLOGS
OVERLAY KNOWNFUNCTIONS ONTO TREE
INFER LIKELY FUNCTIONOF GENE(S) OF INTEREST
ALIGN SEQUENCES
CALCULATE GENE TREE
CHOOSE GENE(S) OF INTEREST
Species 3Species 1 Species 2
ACTUAL EVOLUTION(ASSUMED TO BE UNKNOWN)
EXAMPLE A
Duplication?
Duplication
Ambiguous
Based on Eisen, 1998 Genome Res 8: 163-167.
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Similarity ≠ Relatedness
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Evolutionary Rate Variation
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Phylogenetic Prediction of Function
• Many powerful and automated similarity based methods for assigning genes to protein families• COGs• PFAM HMM searches
• Some limitations of similarity based methods can be overcome by phylogenetic approaches
• Automated methods now available• Sean Eddy• Steven Brenner• Kimmen Sjölander
• But …
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Grad school lesson V:Teaching helps you learn
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Grad school lesson VI:There are no career rules
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Career Lesson I:Build on what you know
• Phylogenetic approaches to genomics• Genomics of endosymbionts• Genomic studies of communities• Analysis of DNA repair genes in genome
sequences• Phylogenomics of halophilic archaea• GEBA• Phylogenetic metagenomics• ...
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Career Lesson II: Don’t Only Use What You Know
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What We Don’t Know Can Hurt Us
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D. radiodurans genome
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DNA Repair Genes in D. radiodurans
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
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Problem ...
• List of DNA repair gene homologs in D. radiodurans genome is not significantly different from other bacterial genomes of the similar size
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Repair Studies in Different Species(via Medline searches as of 1998)
Humans 7028E. coli 3926S. cerevisiae 988Drosophila 387B. subtilits 284S. pombe 116Xenopus 56C. elegans 25A. thaliana 20Methanogens 16Haloferax 5Giardia 0
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0.1
Acidobacteria
Bacteroides
Fibrobacteres
Gemmimonas
Verrucomicrobia
Planctomycetes
Chloroflexi
Proteobacteria
Chlorobi
FirmicutesFusobacteria Actinobacteria
Cyanobacteria
Chlamydia
Spriochaetes
Deinococcus-Thermus
Aquificae
Thermotogae
TM6OS-K
Termite GroupOP8
Marine GroupAWS3
OP9
NKB19
OP3
OP10
TM7
OP1OP11
Nitrospira
SynergistesDeferribacteres
Thermudesulfobacteria
Chrysiogenetes
Thermomicrobia
Dictyoglomus
Coprothmermobacter
Tree based on Hugenholtz (2002) with some modifications.
~40 Phyla of Bacteria
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0.1
Acidobacteria
Bacteroides
Fibrobacteres
Gemmimonas
Verrucomicrobia
Planctomycetes
Chloroflexi
Proteobacteria
Chlorobi
FirmicutesFusobacteria Actinobacteria
Cyanobacteria
Chlamydia
Spriochaetes
Deinococcus-Thermus
Aquificae
Thermotogae
TM6OS-K
Termite GroupOP8
Marine GroupAWS3
OP9
NKB19
OP3
OP10
TM7
OP1OP11
Nitrospira
SynergistesDeferribacteres
Thermudesulfobacteria
Chrysiogenetes
Thermomicrobia
Dictyoglomus
Coprothmermobacter
Tree based on Hugenholtz (2002) with some modifications.
Most DNA metabolism studies in two Phyla
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0.1
Acidobacteria
Bacteroides
Fibrobacteres
Gemmimonas
Verrucomicrobia
Planctomycetes
Chloroflexi
Proteobacteria
Chlorobi
FirmicutesFusobacteria Actinobacteria
Cyanobacteria
Chlamydia
Spriochaetes
Deinococcus-Thermus Aquificae
Thermotogae
TM6OS-K
Termite GroupOP8
Marine GroupAWS3
OP9
NKB19
OP3
OP10
TM7
OP1OP11
Nitrospira
SynergistesDeferribacteres
Thermudesulfobacteria
Chrysiogenetes
Thermomicrobia
Dictyoglomus
Coprothmermobacter
Tree based on Hugenholtz (2002) with some modifications.
Deinococcus is very distant from well studied groups
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-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 He
lpy
Bacs
u
Strpy
Myc
ge
Myc
pn
Borbu Trep
a
Syns
p
Met
jn
Arcfu
Met
th
Human
Yeas
t
BACTERIA ARCHAEA EUKARYOTES
from mitochondria
+Ada+MutH+SbcB
dPhr
+TagI?+Fpg
+UvrABCD+Mfd
+RecFJNOR+RuvABC
+RecG+LigI
+LexA+SSB
+PriA+Dut?
+Rus+UmuD+Nei?
+RecEtRecT?
+Vsr+RecBCD?
+RFAs+TFIIH
+Rad4,10,14,16,23,26+CSA
+Rad52,53,54+DNA-PK, Ku
dSNF2dMutSdMutLdRecA
+Rad1+Rad2
+Rad25?+Ogg+LigII
+Ung?+SSB,
+Dut?
+PhrI, PhrII+Ogt
+Ung, AlkA, MutY-Nth+AlkA
+Xth, Nfo?+MutLS?
+SbcCD+RecA
+UmuC+MutT
+LondMutSI/MutSII
dRecA/SMSdPhrI/PhrII
+Sprt3MG
+Rad7+CCE1
+P53dRecQ
dRad23+MAG?
-PhrII-RuvC
tRad25
+TagI?
+RecT
tUvrABCD
tTagI ?
Gain and Loss of Repair Genes
Eisen and Hanawalt, 1999 Mut Res 435: 171-213
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Solution - Experiments
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What We Don’t Know Can Hurt Us
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Acidobacteria
Bacteroides
Fibrobacteres
Gemmimonas
Verrucomicrobia
Planctomycetes
Chloroflexi
Proteobacteria
Chlorobi
FirmicutesFusobacteria Actinobacteria
Cyanobacteria
Chlamydia
Spriochaetes
Deinococcus-Thermus
Aquificae
Thermotogae
TM6OS-K
Termite GroupOP8
Marine GroupAWS3
OP9
NKB19
OP3
OP10
TM7
OP1OP11
Nitrospira
SynergistesDeferribacteres
Thermudesulfobacteria
Chrysiogenetes
Thermomicrobia
Dictyoglomus
Coprothmermobacter
• At least 40 phyla of bacteria
As of 2002
Based on Hugenholtz, 2002
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Acidobacteria
Bacteroides
Fibrobacteres
Gemmimonas
Verrucomicrobia
Planctomycetes
Chloroflexi
Proteobacteria
Chlorobi
FirmicutesFusobacteria Actinobacteria
Cyanobacteria
Chlamydia
Spriochaetes
Deinococcus-Thermus
Aquificae
Thermotogae
TM6OS-K
Termite GroupOP8
Marine GroupAWS3
OP9
NKB19
OP3
OP10
TM7
OP1OP11
Nitrospira
SynergistesDeferribacteres
Thermudesulfobacteria
Chrysiogenetes
Thermomicrobia
Dictyoglomus
Coprothmermobacter
• At least 40 phyla of bacteria
• Most genomes from three phyla
As of 2002
Based on Hugenholtz, 2002
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Acidobacteria
Bacteroides
Fibrobacteres
Gemmimonas
Verrucomicrobia
Planctomycetes
Chloroflexi
Proteobacteria
Chlorobi
FirmicutesFusobacteria Actinobacteria
Cyanobacteria
Chlamydia
Spriochaetes
Deinococcus-Thermus
Aquificae
Thermotogae
TM6OS-K
Termite GroupOP8
Marine GroupAWS3
OP9
NKB19
OP3
OP10
TM7
OP1OP11
Nitrospira
SynergistesDeferribacteres
Thermudesulfobacteria
Chrysiogenetes
Thermomicrobia
Dictyoglomus
Coprothmermobacter
• At least 40 phyla of bacteria
• Most genomes from three phyla
• Some studies in other phyla
As of 2002
Based on Hugenholtz, 2002
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Acidobacteria
Bacteroides
Fibrobacteres
Gemmimonas
Verrucomicrobia
Planctomycetes
Chloroflexi
Proteobacteria
Chlorobi
FirmicutesFusobacteria Actinobacteria
Cyanobacteria
Chlamydia
Spriochaetes
Deinococcus-Thermus
Aquificae
Thermotogae
TM6OS-K
Termite GroupOP8
Marine GroupAWS3
OP9
NKB19
OP3
OP10
TM7
OP1OP11
Nitrospira
SynergistesDeferribacteres
Thermudesulfobacteria
Chrysiogenetes
Thermomicrobia
Dictyoglomus
Coprothmermobacter
• At least 40 phyla of bacteria
• Most genomes from three phyla
• Some other phyla are only sparsely sampled
• Same trend in Eukaryotes
As of 2002
Based on Hugenholtz, 2002
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Acidobacteria
Bacteroides
Fibrobacteres
Gemmimonas
Verrucomicrobia
Planctomycetes
Chloroflexi
Proteobacteria
Chlorobi
FirmicutesFusobacteria Actinobacteria
Cyanobacteria
Chlamydia
Spriochaetes
Deinococcus-Thermus
Aquificae
Thermotogae
TM6OS-K
Termite GroupOP8
Marine GroupAWS3
OP9
NKB19
OP3
OP10
TM7
OP1OP11
Nitrospira
SynergistesDeferribacteres
Thermudesulfobacteria
Chrysiogenetes
Thermomicrobia
Dictyoglomus
Coprothmermobacter
• At least 40 phyla of bacteria
• Most genomes from three phyla
• Some other phyla are only sparsely sampled
• Same trend in Viruses
As of 2002
Based on Hugenholtz, 2002
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GEBA
http://www.jgi.doe.gov/programs/GEBA/pilot.html
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rRNA Tree of Life
Figure from Barton, Eisen et al. “Evolution”, CSHL Press. 2007.
Based on tree from Pace 1997 Science 276:734-740
Archaea
Eukaryotes
Bacteria
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PD: Genomes
From Wu et al. 2009 Nature 462, 1056-1060
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From Wu et al. 2009 Nature 462, 1056-1060
PD: Genomes + GEBA
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PD: Isolates
From Wu et al. 2009 Nature 462, 1056-1060Friday, July 13, 12
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rRNA Tree of Life
Figure from Barton, Eisen et al. “Evolution”, CSHL Press. 2007.
Based on tree from Pace 1997 Science 276:734-740
Archaea
Eukaryotes
Bacteria
??????
Wu et al. (2011) PLoS ONE 6(3): e18011. doi:10.1371/journal.pone.0018011
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????
Phage
Phage
????
Thaumarchaeot
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56
Number of SAGs from Candidate Phyla
OD
1
OP
11
OP
3
SA
R4
06
Site A: Hydrothermal vent 4 1 - -Site B: Gold Mine 6 13 2 -Site C: Tropical gyres (Mesopelagic) - - - 2Site D: Tropical gyres (Photic zone) 1 - - -
Sample collections at 4 additional sites are underway.
Phil Hugenholtz
GEBA uncultured
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Uncharacterized genes
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Non homology functional
• Many genes have homologs in other species but no homologs have ever been studied experimentally
• Non-homology methods can make functional predictions for these
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Phylogenetic profiling basis
• 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
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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)
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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. )
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Homologs of Sporulation Genes
Wu et al. 2005 PLoS Genetics 1: e65.
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Carboxydothermus sporulates
Wu et al. 2005 PLoS Genetics 1: e65.
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Wu et al. 2005 PLoS Genetics 1: e65.
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PG Profiling Works Better Using Orthology
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PG Profiling Works Better Using Independent Contrasts
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Career Lesson III: Networks Matter
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Protein Family Rarefaction Curves
• Take data set of multiple complete genomes
• Identify all protein families using MCL• Plot # of genomes vs. # of protein families
Friday, July 13, 12
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Wu et al. 2009 Nature 462, 1056-1060
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Wu et al. 2009 Nature 462, 1056-1060
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Wu et al. 2009 Nature 462, 1056-1060
Friday, July 13, 12
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Wu et al. 2009 Nature 462, 1056-1060
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Wu et al. 2009 Nature 462, 1056-1060
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Synapomorphies exist
Wu et al. 2009 Nature 462, 1056-1060
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Metagenomics
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Binning challenge
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Sharpton et al. submitted
Friday, July 13, 12
![Page 88: Jonathan Eisen talk for #SCS2012 at #ISMB "Networks in genomics and bioinformatics: from phylogeny to Twitter"](https://reader033.vdocuments.mx/reader033/viewer/2022060108/554e8f0ab4c905fc368b4b36/html5/thumbnails/88.jpg)
Career Lesson IV: Openness Helps
Friday, July 13, 12