Phylogenomics Talk at UC Berkeley by J. A. Eisen

Phylogenomics and the Diversity
and Diversiﬁcation of Microbes

Jonathan A. Eisen
UC Davis

UC Berkeley Talk
February 3, 2011
Monday, February 14, 2011

My Obsessions

Jonathan A. Eisen
UC Davis

UC Berkeley Talk
February 3, 2011

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Sunday, April 1, 2007 Health
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FITNESS & NUTRITION HEALTH CARE POLICY MENTAL HEALTH & BEHAVIOR

Scientist Reveals Secret of the Ocean: It's Him
By NICHOLAS WADE
Published: April 1, 2007
PRINT nytimes.com/sports

Maverick scientist J. Craig Venter has done it again. It was just a few years SINGLE-PAGE
ago that Dr. Venter announced that the human genome sequenced by Celera
SAVE
Genomics was in fact, mostly his own. And now, Venter has revealed a second
SHARE
twist in his genomic self-examination. Venter was discussing his Global
SHARE
Ocean Voyage, in which he used his personal yacht to collect ocean water
samples from around the world. He then used large filtration units to collect How good is your bracket? Compare your tournament picks
to choices from members of The New York Times sports
microbes from the water samples which were then brought back to his high desk and other players.

tech lab in Rockville, MD where he used the same methods that were used to Also in Sports:
The Bracket Blog - all the news leading up to the Final
sequence the human genome to study the genomes of the 1000s of ocean Four
dwelling microbes found in each sample. In discussing the sampling methods, Venter let slip his Bats Blog: Spring training updates
Play Magazine: How to build a super athlete
latest attack on the standards of science – some of the samples were in fact not from the ocean, but
were from microbial habitats in and on his body.

“The human microbiome is the next frontier,” Dr. Venter said. “The ocean voyage was just a cover.
My main goal has always been to work on the microbes that live in and on people. And now that my
genome is nearly complete, why not use myself as the model for human microbiome studies as well.
”

It is certainly true that in the last few years, the microbes that live in and on people have become a
hot research topic. So hot that the same people who were involved in the race to sequence the human
genome have been involved in this race too. Francis Collins, Venter main competitor and still the
director of the National Human Genome Research Institute (NHGRI), recently testified before

Bacterial evolve


Phylogenomics of Novelty



Mechanisms of
Origin of New
Functions



Mechanisms of Variation in
Origin of New Mechanisms:
Functions Patterns, Causes
and Effects



Mechanisms of Variation in
Origin of New Mechanisms:
Functions Patterns, Causes
and Effects

Species Evolution



• How does novelty originate?
• Major categories of processes
• From within
• De novo invention
• Simple substitutions
• Duplication and divergence
• Domain shuffling
• Small & large rearrangements
• Regulatory changes
• From outside
• Lateral gene transfer
• Symbioses



• How does novelty originate?
• Major categories of processes
Mechanisms of • From within
Origin of New • De novo invention
Functions • Simple substitutions
• Duplication and divergence
• Domain shuffling
• Small & large rearrangements
• Regulatory changes
• From outside
• Lateral gene transfer
• Symbioses



• Patterns of variation
• Within species
• Between species
• Causes
• Variation in replication,
recombination and repair
• Effects
• Differences in evolvability
• Ecological niche
• Short and long term genome
evolution



• Patterns of variation
• Within species Variation in
• Between species Mechanisms:
• Causes Patterns, Causes
• Variation in replication, and Effects
recombination and repair
• Effects
• Differences in evolvability
• Ecological niche
• Short and long term genome
evolution



• Information needed to distinguish convergence from
homology
• Allows inference of rates and patterns of change
• Allows one to determine if something is a “one time” event
or a common theme in many lineages



• Information needed to distinguish convergence from
homology
• Allows inference of rates and patterns of change
• Allows one to determine if something is a “one time” event
or a common theme in many lineages

Species Evolution



Variation in
Mechanisms of
Mechanisms:
Origin of New
Patterns, Causes
Functions
and Effects

Species Evolution



Variation in
Mechanisms of
Mechanisms:
Origin of New
Patterns, Causes
Functions
and Effects

Focus Today on
Using Sequence
Information for All
of This
Species Evolution


Why do this?

• Discover causes and effects of differences in
evolvability
• Improve predictions from genome analysis
• Guide interpretation of biological data


Outline

• Introduction
• Phylogenomic Stories
– Within genome invention of novelty
– Stealing novelty
– Communities of microbes
– Community service and knowing what we don’t
know


Introduction

Genome Sequencing


rRNA Tree of Life

FIgure from Barton, Eisen et al.
“Evolution”, CSHL Press.
Based on tree from Pace NR, 2003.


Limited Sampling of RRR Studies



Limited Sampling of RRR Studies
Haloferax

Methanococcus
Chlorobium
Deinococcus
Thermotoga



UV Survival E.coli vs H.volcanii
1
Ecoli vs. Hvolcanii
0.1

0.01

Relative 0.001
Survival

0.0001

1E-05

1E-06

1E-07
0 50 100 150 200 250 300 350 400
UV J/m2
E.coli NR10121 mfd-

E.coli NR10125 mfd+

TIGR H.volcanii WFD11


H. volcanii UV Repair Label 7 - 45J / m2)

0.6
Label5#2
0 J/m2 t0
45 J/m2 t0
45 J/m2 Photoreac.
45 J/m2 Dark 24 Hours

0.4

0.2

0
0 2000 4000 6000 8000 10000 12000 14000 16000 18000

Avg. Mol. Wt.(Base Pairs)


Fleischmann et al.
1995

From http://genomesonline.org

Human commensals


Phylogenomics of Novelty I

Origin of Functions from Within


From Eisen et al.
1997 Nature
Medicine 3:
1076-1078.


Blast Search of H. pylori “MutS”

• Blast search pulls up Syn. sp MutS#2 with much higher p
value than other MutS homologs
• Based on this TIGR predicted this species had mismatch
repair
• Assumes functional constancy
Based on Eisen et al. 1997 Nature Medicine 3: 1076-1078.

Predicting Function
• Identification of motifs
– Short regions of sequence similarity that are indicative of
general activity
– e.g., ATP binding
• Homology/similarity based methods
– Gene sequence is searched against a databases of other
sequences
– If significant similar genes are found, their functional
information is used
• Problem
– Genes frequently have similarity to hundreds of motifs
and multiple genes, not all with the same function


MutL??

Based on Eisen et al. 1997 Nature Medicine 3: 1076-1078.

Overlaying Functions onto Tree
MutS2
Aquae
MSH5 Strpy
Bacsu
Synsp
Deira Helpy
Yeast
Human Borbu Metth
Celeg

MSH6 mSaco
Yeast
Human
Mouse
Arath
Yeast MSH4
Celeg
Human
Arath
Human
MSH3 Mouse
Fly
Spombe
Yeast Xenla
Rat
Mouse
Yeast Human
MSH1 Spombe Yeast MSH2
Neucr
Arath

Aquae Trepa
Chltr
DeiraTheaq
BacsuBorbu
Thema
SynspStrpy Based on Eisen,
Ecoli
Neigo
1998 Nucl Acids
MutS1 Res 26: 4291-4300.

Evolutionary Functional Prediction
EXAMPLE A METHOD EXAMPLE B

2A CHOOSE GENE(S) OF INTEREST 5

3A 1 3 4
2B 2
IDENTIFY HOMOLOGS 5
1A 2A 1B 3B 6

ALIGN SEQUENCES

1A 2A 3A 1B 2B 3B 1 2 3 4 5 6

CALCULATE GENE TREE

Duplication?

1A 2A 3A 1B 2B 3B 1 2 3 4 5 6

OVERLAY KNOWN
FUNCTIONS ONTO TREE

Duplication?

1 2 3 4 5 6
1A 2A 3A 1B 2B 3B

INFER LIKELY FUNCTION
OF GENE(S) OF INTEREST
Ambiguous
Duplication?

Species 1 Species 2 Species 3
1A 1B 2A 2B 3A 3B 1 2 3 4 5 6

ACTUAL EVOLUTION
(ASSUMED TO BE UNKNOWN)
Based on Eisen,
1998 Genome
Duplication
Res 8: 163-167.

Example 2: Recent Changes
• Phylogenomic functional prediction NJ

* **
V.cholerae0512
VC
V.cholerae
VCA1034
V.cholerae
VC
V.cholerae
VC
V.cholerae
VC
A0974
A0068
V.cholerae
VC
0825
0282

may not work well for very newly
V.cholerae
VCA0906
V.cholerae
VC
A0979
V.cholerae
VCA1056
V.cholerae
VC1643
V.cholerae
VC2161
** V.cholerae
VCA0923
** V.cholerae
VC0514
V.cholerae
VC
1868
V.cholerae
VC
A0773
V.cholerae
VC1313

evolved functions
V.cholerae
VC
1859
V.cholerae
VC1413
V.cholerae
VCA0268
** V.cholerae
VC
A0658
V.cholerae
VC
1405
* V.cholerae
VC1298
V.cholerae
VC1248
V.cholerae
VCA0864
V.cholerae
VCA0176
** V.cholerae
VCA0220
V.cholerae
VC
1289
** V.cholerae
VC1069
A
V.cholerae
VC2439

• Can use understanding of origin of
V.cholerae
VC967
1
V.cholerae
VC
A0031
V.cholerae
VC1898
V.cholerae
VC
A0663
V.cholerae
VC0988
A
V.cholerae
VC0216
* V.cholerae
VC0449
V.cholerae
VCA0008
V.cholerae
VC1406
V.cholerae
VC
1535

novelty to better interpret these cases?
V.cholerae
VC0840
B.subtilis
gi2633766
Synechocystis
sp.
gi1001299
* Synechocystis
sp.gi1001300
* Synechocystis
sp.
gi1652276
* Synechocystis
sp.
gi1652103
H.pylori
gi2313716
** **H.pylori
99 gi4155097
C.jejuni
Cj1190c
C.jejuni
Cj1110c
A.fulgidus
gi2649560
A.fulgidus
gi2649548
** B.subtilis
gi2634254

• Screen genomes for genes that have
B.subtilis
gi2632630
B.subtilis
gi2635607
B.subtilis
gi2635608
** B.subtilis
gi2635609
** ** B.subtilisgi2635882
gi2635610
B.subtilis
E.coligi1788195
E.coli
gi2367378
* ** E.coligi1788194
E.coli A1092
gi1787690
V.cholerae
VC

changed recently
V.cholerae
VC
0098
E.coli
gi1789453
H.pylori
gi2313186
H.pylori
99 gi4154603
** C.jejuni Cj0144
C.jejuni
Cj1564
**C.jejuni
C.jejuni
Cj0262c
Cj1506c
** H.pylori
gi2313163
* ** H.pylori
99 gi4154575
** H.pylori
gi2313179
H.pylori
99 gi4154599

– Pseudogenes and gene loss
** C.jejuni Cj0019c
C.jejuni
Cj0951c
C.jejuni
Cj0246c
B.subtilis
gi2633374
T.maritima
TM0014
V.cholerae
VC1403
V.cholerae
VCA1088
T.pallidum
gi3322777
** T.pallidum
gi3322939
** T.pallidum
gi3322938
B.burgdorferi
gi2688522

– Contingency Loci
T.pallidum
gi3322296
B.burgdorferi
gi2688521
* T.maritima
TM0429
**T.maritima
TM0918
* **T.maritima
T.maritima
TM0023
TM1428
T.maritima
TM1143
T.maritima
TM1146
P.abyssi
PAB1308
P.horikoshii
gi3256846
** P.abyssiPAB1336

– Acquisition (e.g., LGT)
** P.horikoshii
gi3256896
** **P.abyssi
PAB2066
** P.horikoshii
** P.abyssi gi3258290
* PAB1026
** P.horikoshii DRA00354
gi3256884
D.radiodurans
D.radiodurans
** D.radioduransDRA0353
** DRA0352
** V.cholerae
VC
1394
P.abyssi
PAB1189
P.horikoshii
gi3258414

– Unusual dS/dN ratios
** B.burgdorferi
gi2688621
M.tuberculosis
gi1666149
V.cholerae
VC
0622

– Rapid evolutionary rates
– Recent duplications

Tetrahymena Genome Processing

• Probably exists as a defense mechanism
• Analogous to RIPPING and
heterochromatin silencing
• Presence of repetitive DNA in MAC but
not TEs suggests the mechanism involves
targeting foreign DNA
• Thus unlike RIPPING ciliate processing
does not limit diversiﬁcation by duplication
Eisen et al. 2006. PLoS Biology.

Conclusions

• Enormous variation in processes underlying
origin of novelty
• See within genomes -> between species
• Knowledge about mechanisms and variation
helps predictions of function and biology
from analysis of sequence data


Phylogenomics of Novelty II

Sometimes, it is easier to steal, borrow, or
coopt functions rather than evolve them
anew


Stealing DNA


rRNA Tree of Life
Bacteria

Archaea

Eukaryotes



Perna et al. 2003

Network of Life
Bacteria

Archaea

Eukaryotes

Figure from Barton, Eisen et al.


A. thaliana T1E2.8 is a
Chloroplast Derived HSP60


Phylogenetic Distribution Novelty:
Bacterial Actin Related Protein
2"#3)&4&*&& !"#*)$*),+%
5"#$-.-6&0&1- !"#$%,$-%)(
7"#0(1.8-9& !"#$''+-+,',!
5"#:1,)*&$/0 !"#&$,%+)+-+ !"#$%
!"#$%&'()*&& !"#$%&'(%()
(( +"#,-.(/01 !"#*+,**'+(
;"#01,&-*0 !"#%*+$--(
<"#$-.-3.1%&0 !"#%',&'-+)
') 2"#$&*-.-1 !"#$'(-%%+&$
="#$.1001 !"#-*$+$(&( !&'(
$++ >"#0$1,/%1.&0 !"#&$**+),)-!
*$ $++ ;"#01,&-*0 !"#*+,$*'(
'* 5"#:1,)*&$/0 !"#&$,%+%-%%
$++ 5"#$-.-6&0&1- !"#',&+$)*
!&')
?"#@-%1*)A10(-. !"#&%'%&*%*
$++ B"#A1%%/0# "#%*,-&*'(
)* 2"#*-)').@1*0 !"#*-&'''(+
5"#$-.-6&0&1- !"#',&&*&* !&'*
$++ ?"#@-%1*)A10(-. !"#$)),)*%,
$++ ;"#01,&-*0 !"#*+,$*),!
;"#)$C.1$-/@ !"#&&),(*((- +!&'
5"#$-.-6&0&1- !"#$++-&%%!
), ."#,1(-*0 !"#$'-+*$((&! !&',
(( !"#(C1%&1*1 !"#$-,(%'+-!
(% 5"#$-.-6&0&1- !"#$,+$(,&
$++ 5"#:1,)*&$/0 !"#&$,%+-,(,! !&'-
-) ?"#4&0$)&4-/@ !"#''-+&%$-
)% ?"#@-%1*)A10(-. !"#$)),),%)
() 5"#$-.-6&0&1- !"#',&,$$%
$++ ?"#C1*0-*&&!"#&$-*$ $(&$ !&'.
$++ D"#01(&61 !"#$-&'*)%&+!
!"#(C1%&1*1!"#$-%$ $),) !&'/
?"#@-%1*)A1(-. !"#$((&+,*-
$++ <"#@/0$/%/0 !"#&&'&%'*(, !&'(0

+/*!

Haliangium ochraceum DSM 14365 Patrik D’haeseleer, Adam Zemla, Victor Kunin

Wu et al. 2009 Nature 462, 1056-1060 See also Guljamow et al. 2007 Current Biology.

Correlated gain/loss of genes

• Microbial genes are lost rapidly when not
maintained by selection
• Genes can be acquired by lateral transfer
• Frequently gain and loss occurs for entire
pathways/processes
• Thus might be able to use correlated
presence/absence information to identify
genes with similar functions


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)


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. )


Homologs of Sporulation Genes

Wu et al. 2005
PLoS Genetics 1:
e65.

Carboxydothermus sporulates

Wu et al. 2005 PLoS Genetics 1: e65.

Wu et al. 2005 PLoS Genetics 1: e65.

Stealing Organisms (Symbioses)


Mutualistic Genome Evolution

• Compare and contrast different types of
mutualistic symbioses
• Diverse hosts, symbionts, biology, ages
• Organelles, chemosymbioses,
photosynthetic symbioses, nutritional
symbioses
• What are the rules & patterns?


Glassy Winged Sharpshooter

• Feeds on xylem
sap
• Vector for
Pierce’s Disease
• Potential
bioterror agent


Sharpshooter Shotgun Sequencing

shotgun

Collaboration with Nancy
Wu et al. 2006 PLoS Biology 4: e188.
Moran’s lab

Higher Evolutionary Rates in
Endosymbionts

Wu et al. 2006 PLoS Biology 4: e188. Collaboration with Nancy Moran’ s Lab

Variation in Evolution Rates

MutS MutL
+ +
+ +
+ +
+ +
_ _
_ _

Wu et al. 2006 PLoS Biology 4: e188. Collaboration with Nancy Moran’ s Lab

Polymorphisms in Metapopulation

• Data from ~200 hosts
– 104 SNPs
– 2 indels
• PCR surveys show that
this is between host
variation
• Much lower ratio of
transitions:transversions
than in Blochmannia
• Consistent with absence
of MMR from
Blochmannia

Baumannia is a Vitamin and
Cofactor Producing Machine

Wu et al.
2006
PLoS
Biology 4:
e188.

No Amino-Acid Synthesis


The Uncultured Majority


Great Plate Count Anomaly

Culturing Microscope

Count Count




Count <<<< Count



DNA


Count <<<< Count


rRNA PCR

The Hidden Majority Richness estimates

Hugenholtz 2002 Bohannan and Hughes 2003


rRNA data increasing exponentially too

Metagenomics

shotgun

clone


How can we best use
metagenomic data?
• Many possible uses including:
– Improvements on rRNA based phylotyping and
species diversity measurements
– Adding functional information on top of
phylogenetic/species diversity information
• Most/all possible uses either require or are
improved with phylogenetic analysis


Example I: Phylotyping with
rRNA and other genes


Functional Diversity of Proteorhodopsins?

Venter et al., 2004

Weighted % of Clones

0
0.1250
0.2500
0.3750
0.5000
Al
ph
ap
ro
t eo
Be b ac
ta
pr t er
ot
e ia
G ob
am ac
m t er
ap ia

ro
Ep te
si ob
lo ac
np t er
ro ia
De t eo
lta b ac
pr te
ot ria
eo
b
C ac
ya ter
n ob ia
ac
t er
Fi ia
rm
ic
u te
Ac s
tin
ob
ac
t er
C ia
hl
or
ob
i
C
FB

Major Phylogenetic Group
Sargasso Phylotypes

C
hl
or
of
le
Sp xi
iro
ch
ae
te
Fu
so s
De ba
in ct
er
oc ia
oc
cu
s-
Eu The
ry r
ar mu
ch s
ae
C ot
re a
na
rc
ha
eo
ta
Shotgun Sequencing Allows Use of Other Markers

EFG

Venter et al., Science 304: 66-74. 2004
EFTu

rRNA
RecA
RpoB
HSP70

Example II: Binning


Metagenomics Challenge


Binning challenge

A T
B U
C V
D W
E X
F Y
G Z

Binning challenge

A T
B U
C V
D W
E X
F Y
G Best binning method: reference genomes Z

Binning challenge

A T
B U
C V
D W
E X
F Y
G No reference genome? What do you do? Z

Binning challenge

A T
B U
C V
D W
E X
F Y
G No reference genome? What do you do? Z
Phylogeny ....

???????


CFB Phyla


Sulcia makes amino acids

Baumannia makes vitamins and cofactors

Wu et al. 2006 PLoS Biology 4: e188.

Phylogenomics of Novelty III

Knowing What We Don’t Know


Research Topics

Variation in
Mechanisms of
Mechanisms:
Origin of New
Patterns, Causes
Functions
and Effects

Species Evolution


As of 2002


As of 2002 Proteobacteria
TM6
OS-K • At least 40
Acidobacteria
Termite Group
OP8
phyla of
Nitrospira
Bacteroides bacteria
Chlorobi
Fibrobacteres
Marine GroupA
WS3
Gemmimonas
Firmicutes
Fusobacteria
Actinobacteria
OP9
Cyanobacteria
Synergistes
Deferribacteres
Chrysiogenetes
NKB19
Verrucomicrobia
Chlamydia
OP3
Planctomycetes
Spriochaetes
Coprothmermobacter
OP10
Thermomicrobia
Chloroﬂexi
TM7
Deinococcus-Thermus
Dictyoglomus
Aquiﬁcae
Thermudesulfobacteria
Thermotogae
OP1 Based on
OP11 Hugenholtz, 2002

TM6
OS-K
• At least 40
Acidobacteria
Termite Group
OP8
phyla of
Nitrospira
Chlorobi
Fibrobacteres
Marine GroupA • Genome
WS3
Gemmimonas
Firmicutes
sequences are
Fusobacteria
Actinobacteria
mostly from
OP9
Cyanobacteria
Synergistes
three phyla
Deferribacteres
Chrysiogenetes
NKB19
Verrucomicrobia
Chlamydia
OP3
Planctomycetes
Spriochaetes
Coprothmermobacter
OP10
Thermomicrobia
Chloroﬂexi
TM7
Deinococcus-Thermus
Dictyoglomus
Aquiﬁcae
Thermotogae
OP1 Based on

TM6
OS-K
• At least 40
Acidobacteria
Termite Group
OP8
phyla of
Nitrospira
Chlorobi
Fibrobacteres
WS3
Gemmimonas
Firmicutes
sequences are
Fusobacteria
Actinobacteria
mostly from
OP9
Cyanobacteria
Synergistes
three phyla
Deferribacteres
Chrysiogenetes
NKB19
• Some other
Verrucomicrobia
Chlamydia
OP3
phyla are
Planctomycetes
Spriochaetes only sparsely
Coprothmermobacter
OP10
Thermomicrobia
sampled
Chloroﬂexi
TM7
Deinococcus-Thermus
Dictyoglomus
Aquiﬁcae
Thermotogae
OP1 Based on

Proteobacteria
• NSF-funded TM6
OS-K
• At least 40
Tree of Life Acidobacteria
Termite Group phyla of
OP8
Project Nitrospira
Chlorobi
• A genome Fibrobacteres
WS3
from each of Gemmimonas sequences are
Firmicutes
eight phyla Fusobacteria
mostly from
Actinobacteria
OP9
Cyanobacteria
Synergistes
three phyla
Deferribacteres
Chrysiogenetes
NKB19
• Some other
Verrucomicrobia
Chlamydia
OP3
phyla are only
Planctomycetes
Spriochaetes sparsely
Coprothmermobacter
OP10
Thermomicrobia
sampled
Chloroﬂexi
TM7
Deinococcus-Thermus
• Solution I:
Dictyoglomus
Eisen, Ward, Aquiﬁcae
sequence more
Robb, Nelson, et Thermotogae
phyla
OP1
al OP11


Proteobacteria
• NSF-funded TM6
OS-K
• At least 40
Termite Group phyla of bacteria
OP8
Project Nitrospira
• Genome
Bacteroides

• A genome Chlorobi
Fibrobacteres sequences are
Marine GroupA
from each of WS3
Gemmimonas mostly from
eight phyla Firmicutes
Fusobacteria three phyla
Actinobacteria
OP9
Cyanobacteria
• Some other
Synergistes
Deferribacteres
Chrysiogenetes
phyla are only
NKB19
Verrucomicrobia sparsely
Chlamydia
OP3
Planctomycetes
sampled
Spriochaetes
Coprothmermobacter • Still highly
OP10
Thermomicrobia
Chloroﬂexi
biased in terms
TM7
Deinococcus-Thermus
Dictyoglomus
of the tree
Aquiﬁcae
Eisen & Ward, PIs Thermudesulfobacteria
Thermotogae
OP1
OP11


Proteobacteria
• NSF-funded TM6
OS-K
• At least 40
OP8
Project Nitrospira
• Genome
Bacteroides

Marine GroupA
from each of WS3
Actinobacteria
OP9
Cyanobacteria
• Some other
Synergistes
Deferribacteres
Chrysiogenetes
phyla are only
NKB19
Chlamydia
OP3
Planctomycetes
sampled
Spriochaetes
Coprothmermobacter • Same trend in
OP10
Thermomicrobia
Chloroﬂexi
Archaea
TM7
Deinococcus-Thermus
Dictyoglomus
Aquiﬁcae
Thermotogae
OP1
OP11


Proteobacteria
• NSF-funded TM6
OS-K
• At least 40
OP8
Project Nitrospira
• Genome
Bacteroides

Marine GroupA
from each of WS3
Actinobacteria
OP9
Cyanobacteria
• Some other
Synergistes
Deferribacteres
Chrysiogenetes
phyla are only
NKB19
Chlamydia
OP3
Planctomycetes
sampled
Spriochaetes
Coprothmermobacter • Same trend in
OP10
Thermomicrobia
Chloroﬂexi
Eukaryotes
TM7
Deinococcus-Thermus
Dictyoglomus
Aquiﬁcae
Thermotogae
OP1
OP11


Phylogenomics Talk at UC Berkeley by J. A. Eisen

Phylogenomics Talk at UC Berkeley by J. A. Eisen

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