EVE 161 Lecture 4

Lecture 4

EVE 161: 
Microbial Phylogenomics
!

Lecture #4:
Era I: Modern View of the Tree of Life
!
UC Davis, Winter 2014
Instructor: Jonathan Eisen

Slides for UC Davis EVE161 Course Taught by Jonathan Eisen Winter 2014

Where we are going and where we have been

• Previous lecture:
! 3. Woese and the Tree of Life
• Current Lecture:
! 4. Modern view of Tree of Life
• Next Lecture:
! 5. Era II: rRNA from environment


!2

Two papers for today
Syst. Biol. 59(5):518–533, 2010
c
⃝ The Author(s) 2010. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved.
For Permissions, please email: journals.permissions@oxfordjournals.org
DOI:10.1093/sysbio/syq037
Advance Access publication on July 23, 2010

Broadly Sampled Multigene Analyses Yield a Well-Resolved Eukaryotic Tree of Life
Downloaded from rspb.royalsocietypublishing.org on January 16, 2014
1
2
2,6

L AURA W EGENER PARFREY , J ESSICA G RANT , Y ONAS I. T EKLE , E RICA L ASEK -N ESSELQUIST 3,4 ,
H ILARY G. M ORRISON 3 , M ITCHELL L. S OGIN3 , D AVID J. PATTERSON 5 , AND L AURA A. K ATZ1,2,∗
1 Program

in Organismic and Evolutionary Biology, University of Massachusetts, 611 North Pleasant Street, Amherst,
of Biological Sciences, Smith College, 44 College Lane, Northampton, MA 01063, USA; 3 Bay Paul Center for
MA 01003, USA;
Comparative Molecular Biology and Evolution, Marine Biological Laboratory, 7 MBL Street, Woods Hole, MA 02543, USA; 4 Department of Ecology and
Evolutionary Biology, Brown University, 80 Waterman Street, Providence, RI 02912, USA; 5 Biodiversity Informatics Group, Marine Biological
Laboratory, 7 MBL Street, Woods Hole, MA 02543, USA; 6 Present address: Department of Epidemiology and Public Health, Yale University School of
Medicine, New Haven, CT 06520, USA;
∗ Correspondence to be sent to: Laura A. Katz, 44 College Lane, Northampton, MA 01003, USA; E-mail: lkatz@smith.edu.
2 Department

A congruent phylogenomic signalDecember 2009; accepted 25 May 2010
places eukaryotes within
Received 30 September 2009; reviews returned 1
the Archaea
Associate Editor: C´cile An´
e
e
Abstract.—An Peter G. Foster, of the M. W. Nye, Cymon J. Cox identify Martin Embley
Tom A. Williams,accurate reconstruction Tom eukaryotic tree of life is essential to and T. the innovations underlying the

diversity of microbial and macroscopic (e.g., plants and animals) eukaryotes. Previous work has divided eukaryotic diversity into a small number
Proc. R. Soc. the2012 279of doi:in phylogenomic analyses can which receive strong support online 24 Octoberdue
B abundance of high-level “supergroups,” many of lead to highly supported but incorrect relationships 2012
, data 10.1098/rspb.2012.1795 first published in phylogenomic analyses.
However,
to systematic phylogenetic error. Furthermore, the paucity of major eukaryotic lineages (19 or fewer) included in these
genomic studies may exaggerate systematic error and reduce power to evaluate hypotheses. Here, we use a taxon-rich
strategy to assess eukaryotic relationships. We show that analyses emphasizing broad taxonomic sampling (up to 451 taxa
Supplementary data lineages) "Data Supplement"
representing 72 major
combined with a moderate number of genes yield a well-resolved eukaryotic tree of life.
The consistency across analyses http://rspb.royalsocietypublishing.org/content/suppl/2012/10/18/rspb.2012.1795.DC1.h
with varying numbers of taxa (88–451) and levels of missing data (17–69%) supports the
tml
accuracy of the resulting topologies. The resulting stable topology emerges without the removal of rapidly evolving genes
or taxa, a practice common to phylogenomic analyses. Several35 of which can be accessed
This article cites 56 articles, major groups are stable and strongly supported in these
References(e.g., SAR, Rhizaria, Excavata), whereas the proposed supergroup “Chromalveolata” isfree
analyses
rejected. Furthermore, exhttp://rspb.royalsocietypublishing.org/content/279/1749/4870.full.html#ref-list-1
tensive instability among photosynthetic lineages suggests the presence of systematic biases including endosymbiotic gene
transfer from symbiont (nucleus Article cited host. Our analyses demonstrate that stable topologies of ancient evolutionary
or plastid) to in:
relationships can be achieved with broad taxonomic sampling and a moderate number of genes. Finally, taxon-rich analyhttp://rspb.royalsocietypublishing.org/content/279/1749/4870.full.html#related-urls
ses such as presented Slides for UC Davis for testing the accuracy of relationships that Eisen Winter 2014 support
here provide a method EVE161 Course Taught by Jonathan receive high bootstrap

Downloaded from http://sysbio.oxfordjournals.org/ at University

Laura Wegener Parfrey and Jessica Grant have contributed equally to this work.

!3

Phylogeny Review


!4

Parts of a phylogenetic tree
terminal (or tip) taxa

a

b

c

d

e

f

g

h

u

z

Terminal
branches

y

v

x
w

internal nodes
t

internal
branches

root, root node

Internal nodes represent hypothetical ancestral taxa

!5

Characters
• A heritable feature of an organism is known as a character
(also character trait or trait).

!
• The form that a character takes is known as its state (also
known as character state).
! Note: Presence/absence can be a state
!
• Example:
! Character = heart
! Character state = present/absent
! Character state = # of chambers

!6

Characters ancestry is critical to understand
• Characters that are inherited from a common ancestor
are homologous.
• Species change over time
! Known (generally) as divergence, or divergent
evolution.
! Species change over time due to the combined
processes of mutation, recombination, drift, selection,
etc


!7

Data matrices


!8

Sequence Alignment


!9

Tree reconstruction methods


!10

Some other bells and whistles


!11

Long branch attraction


!12

Homoplasy


!13

Bootstrapping


!14

Jackniﬁng


!15

Congruence


!16

Rooting


!17

Masking


!18

Concatenation


!19

Syst. Biol. 59(5):518–533, 2010
c
⃝ The Author(s) 2010. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved.
For Permissions, please email: journals.permissions@oxfordjournals.org
DOI:10.1093/sysbio/syq037
Advance Access publication on July 23, 2010

Broadly Sampled Multigene Analyses Yield a Well-Resolved Eukaryotic Tree of Life
L AURA W EGENER PARFREY1 , J ESSICA G RANT2 , Y ONAS I. T EKLE2,6 , E RICA L ASEK -N ESSELQUIST 3,4 ,
H ILARY G. M ORRISON 3 , M ITCHELL L. S OGIN3 , D AVID J. PATTERSON 5 , AND L AURA A. K ATZ1,2,∗
1 Program

in Organismic and Evolutionary Biology, University of Massachusetts, 611 North Pleasant Street, Amherst,
of Biological Sciences, Smith College, 44 College Lane, Northampton, MA 01063, USA; 3 Bay Paul Center for
MA 01003, USA;
Comparative Molecular Biology and Evolution, Marine Biological Laboratory, 7 MBL Street, Woods Hole, MA 02543, USA; 4 Department of Ecology and
Evolutionary Biology, Brown University, 80 Waterman Street, Providence, RI 02912, USA; 5 Biodiversity Informatics Group, Marine Biological
Laboratory, 7 MBL Street, Woods Hole, MA 02543, USA; 6 Present address: Department of Epidemiology and Public Health, Yale University School of
Medicine, New Haven, CT 06520, USA;
∗ Correspondence to be sent to: Laura A. Katz, 44 College Lane, Northampton, MA 01003, USA; E-mail: lkatz@smith.edu.
Laura Wegener Parfrey and Jessica Grant have contributed equally to this work.
2 Department

Received 30 September 2009; reviews returned 1 December 2009; accepted 25 May 2010
Associate Editor: C´cile An´
e
e
Abstract.—An accurate reconstruction of the eukaryotic tree of life is essential to identify the innovations underlying the
diversity of microbial and macroscopic (e.g., plants and animals) eukaryotes. Previous work has divided eukaryotic diversity into a small number of high-level “supergroups,” many of which receive strong support in phylogenomic analyses.
However, the abundance of data in phylogenomic analyses can lead to highly supported but incorrect relationships due
to systematic phylogenetic error. Furthermore, the paucity of major eukaryotic lineages (19 or fewer) included in these
genomic studies may exaggerate systematic error and reduce power to evaluate hypotheses. Here, we use a taxon-rich
strategy to assess eukaryotic relationships. We show that analyses emphasizing broad taxonomic sampling (up to 451 taxa
representing 72 major lineages) combined with a moderate number of genes yield a well-resolved eukaryotic tree of life.
The consistency across analyses with varying numbers of taxa (88–451) and levels of missing data (17–69%) supports the
accuracy of the resulting topologies. The resulting stable topology emerges without the removal of rapidly evolving genes
or taxa, a practice common to phylogenomic analyses. Several major groups are stable and strongly supported in these
analyses (e.g., SAR, Rhizaria, Excavata), whereas the proposed supergroup “Chromalveolata” is rejected. Furthermore, extensive instability among photosynthetic lineages suggests the Taught by Jonathan Eisen including endosymbiotic gene
Slides for UC Davis EVE161 Course presence of systematic biases Winter 2014
transfer from symbiont (nucleus or plastid) to host. Our analyses demonstrate that stable topologies of ancient evolutionary

!20

Abstract.—An accurate reconstruction of the eukaryotic tree of life is essential to identify the
innovations underlying the diversity of microbial and macroscopic (e.g., plants and animals)
eukaryotes. Previous work has divided eukaryotic diversity into a small number of high-level
“supergroups,” many of which receive strong support in phylogenomic analyses. However, the
abundance of data in phylogenomic analyses can lead to highly supported but incorrect
relationships due to systematic phylogenetic error. Furthermore, the paucity of major eukaryotic
lineages (19 or fewer) included in these genomic studies may exaggerate systematic error and
reduce power to evaluate hypotheses. Here, we use a taxon-rich strategy to assess eukaryotic
relationships. We show that analyses emphasizing broad taxonomic sampling (up to 451 taxa
representing 72 major lineages) combined with a moderate number of genes yield a wellresolved eukaryotic tree of life. The consistency across analyses with varying numbers of taxa
(88–451) and levels of missing data (17–69%) supports the accuracy of the resulting topologies.
The resulting stable topology emerges without the removal of rapidly evolving genes or taxa, a
practice common to phylogenomic analyses. Several major groups are stable and strongly
supported in these analyses (e.g., SAR, Rhizaria, Excavata), whereas the proposed supergroup
“Chromalveolata” is rejected. Furthermore, extensive instability among photosynthetic lineages
suggests the presence of systematic biases including endosymbiotic gene transfer from
symbiont (nucleus or plastid) to host. Our analyses demonstrate that stable topologies of
ancient evolutionary relationships can be achieved with broad taxonomic sampling and a
moderate number of genes. Finally, taxon-rich analyses such as presented here provide a
method for testing the accuracy of relationships that receive high bootstrap support (BS) in
phylogenomic analyses and enable placement of the multitude of lineages that lack genome
scale data. [Excavata; microbial eukaryotes; Rhizaria; supergroups; systematic error; taxon
sampling.]

!21


!22


!23


!24


!25


!26


!27


!28

451 Taxa


!29

88 Taxa


!30


!31


!32

Just Rhizaria


!33

Just Excavata


!34


!35


!36

A congruent phylogenomic signal places eukaryotes within
the Archaea
Tom A. Williams, Peter G. Foster, Tom M. W. Nye, Cymon J. Cox and T. Martin Embley
Proc. R. Soc. B 2012 279, doi: 10.1098/rspb.2012.1795 first published online 24 October 2012
Supplementary data

"Data Supplement"
http://rspb.royalsocietypublishing.org/content/suppl/2012/10/18/rspb.2012.1795.DC1.h
tml

References

This article cites 56 articles, 35 of which can be accessed free

http://rspb.royalsocietypublishing.org/content/279/1749/4870.full.html#ref-list-1
Article cited in:
http://rspb.royalsocietypublishing.org/content/279/1749/4870.full.html#related-urls

This article is free to access

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!37

Determining the relationships among the major groups of cellular life is
important for understanding the evolution of biological diversity, but is difficult
given the enormous time spans involved. In the textbook ‘three domains’ tree
based on informational genes, eukaryotes and Archaea share a common
ancestor to the exclusion of Bacteria. However, some phylogenetic analyses
of the same data have placed eukaryotes within the Archaea, as the nearest
relatives of different archaeal lineages. We compared the support for these
competing hypotheses using sophisticated phylogenetic methods and an
improved sampling of archaeal biodiversity. We also employed both new and
existing tests of phylogenetic congruence to explore the level of uncertainty
and conflict in the data. Our analyses suggested that much of the observed
incongruence is weakly supported or associated with poorly fitting
evolutionary models. All of our phylogenetic analyses, whether on small
subunit and large subunit ribosomal RNA or concatenated protein-coding
genes, recovered a monophyletic group containing eukaryotes and the TACK
archaeal superphylum comprising the Thaumarchaeota, Aigarchaeota,
Crenarchaeota and Korarchaeota. Hence, while our results provide no
support for the iconic three-domain tree of life, they are consistent with an
extended eocyte hypothesis whereby vital components of the eukaryotic
nuclear lineage originated from within the archaeal radiation

!38


!39


!40


!41


!42


!43


!44


Evolution of eukaryotes from Archaea
(a)

Methanococcus jannaschii
Methanothermobacter thermautotrophicus

1

Pyrococcus furiosus

Arabidopsis thaliana
Giardia lamblia

Thermoplasma volcanium
Giardia lamblia
1

Homo sapiens

1

Saccharomyces cerevisiae

Trichomonas vaginalis
Naegleria gruberi
Homo sapiens

Dictyostelium discoideum
Trypanosoma brucei
Entamoeba histolytica

Eukaryota

Naegleria gruberi

1

Thalassiosira pseudonana

1

Archaeoglobus fulgidus


Methanosarcina mazei

Trypanosoma brucei


1

Cenarchaeum symbiosum


Thaumarchaeota

Pyrococcus furiosus

1

Caldivirga maquilingensis

Caldiarchaeum subterraneum Aigarchaeota

Pyrobaculum aerophilum


1

Thermofilum pendens

Sulfolobus solfataricus

Crenarchaeota

Hyperthermus butylicus

Staphylothermus marinus

Euryarchaeota


Nitrosopumilus maritimus
Korarchaeum cryptofilum Korarchaeota

1

Eukaryota



0.83

4873


Euryarchaeota


1

T. A. Williams et al.

(b)



Crenarchaeota

Ignicoccus hospitalis


Aeropyrum pernix


Clostridium acetobutylicum

Aeropyrum pernix

Synechocystis sp.

Campylobacter jejuni


Escherichia coli

Escherichia coli

Rhodopseudomonas palustris

Bacteria



Treponema pallidum

Bacteria

Synechocystis sp.

Chlamydia trachomatis

Treponema pallidum

Rhodopirellula baltica


0.2


0.2


(c)


(d )


1

Pyrococcus furiosus

1

Euryarchaeota

Pyrococcus furiosus




1

1

Giardia lamblia
Naegleria gruberi

0.57

Trypanosoma brucei

Eukaryota

1

Homo sapiens

Homo sapiens

Trypanosoma brucei


Naegleria gruberi

1




1



0.97

Crenarchaeota



Crenarchaeota

Aeropyrum pernix

Aeropyrum pernix




Escherichia coli

Synechocystis sp.

Synechocystis sp.

Treponema pallidum

Bacteria

Treponema pallidum

Bacteria

Escherichia coli




0.2

Eukaryota


Thaumarchaeota


1

Thaumarchaeota

Giardia lamblia


1

Euryarchaeota



0.2

Figure 1. Phylogenies of Bacteria, Archaea and eukaryotes inferred from concatenated rRNA. (a) A Bayesian phylogeny of Bacteria, Archaea and eukaryotes inferred under the GTR model, showing an eocyte-like topology in which eukaryotes emerge
from within the Archaea with maximal support (posterior probability (PP) ¼ 1). (b) Removal of recently characterized archaeal
groups (the Thaumarchaeota, Aigarchaeota and Korarchaeota) converts this tree into a canonical three-domains topology,
again with maximal support (PP ¼ 1), indicating that sampling plays an important role in the resolution of these ancient
relationships. Analyses of the full dataset using the better-fitting NDRH þ NDCH (c) and CAT (d ) models recover maximally
supported eocyte-like topologies; these models also recover eocyte-like topologies on the reduced dataset, without the TAK
sequences (see the electronic supplementary material, figure S1). Branch lengths are proportional to substitutions per site.


!45



With New Data

(a)



(a) Methanococcus jannaschii


(b) (b)


Euryarchaeota

1
Pyrococcus furiosus


Euryarchaeota

Pyrococcus furiosus



Methanosarcina mazei mazei
Methanosarcina

Giardia lamblia
Giardia lamblia

Giardia lamblia lamblia
Giardia
1

1

1

1

Naegleria gruberi gruberi
Naegleria

1

1

Homo sapiens
Homo sapiens


1

1

Trypanosoma brucei
Trypanosoma brucei

1




0.83

1




1



Aeropyrum pernix

Aeropyrum pernix

Synechocystis sp.
Campylobacter
Synechocystis sp. jejuni

Escherichia
Campylobacter jejuni coli

Escherichia coli

Escherichia coli
Clostridium palustris
Rhodopseudomonasacetobutylicum


0.2

Chlamydia trachomatisSlides

Crenarchaeota

Crenarchaeota

Aeropyrum pernix

Aeropyrum pernix

Treponema pallidum





1


Crenarchaeota

Sulfolobus solfataricus marinus
Staphylothermus
Crenarchaeota

Treponema
Synechocystis sp. pallidum

Euryarchaeota
Euryarchaeota



Clostridium Synechocystis sp.
acetobutylicum




1


Pyrococcus furiosus
1 Pyrococcus furiosus


Thermoﬁlum Sulfolobus solfataricus
pendens

1


Thaumarchaeota

Thaumarchaeota

1


Trypanosoma
Trypanosoma brucei brucei

0.83

Naegleria gruberi
Naegleria gruberi

1

1



Eukaryota
Eukaryota


Arabidopsis thalianathaliana
Arabidopsis
Homo
Homo sapiens sapiens
Eukaryota
Eukaryota


Without New Data


1


Escherichia coli
Treponema pallidum

Bacteria

Bacteria

Bacteria

Treponema pallidum

Bacteria


0.2


for UC Davis EVE161 Course Taught by Jonathan Eisen Winter 2014
0.2

!46


0.2
Better Models


(c)


1


(d )

Pyrococcus furiosus

1

Euryarchaeota



Pyrococcus furiosus




1

1

Giardia lamblia
Naegleria gruberi

0.57

Trypanosoma brucei

Eukaryota

1

Homo sapiens

Homo sapiens

Trypanosoma brucei


Naegleria gruberi

1




1



0.97

Crenarchaeota



Crenarchaeota

Aeropyrum pernix

Aeropyrum pernix




Escherichia coli

Synechocystis sp.

Synechocystis sp.

Treponema pallidum

Bacteria

Treponema pallidum

Bacteria

Escherichia coli




0.2

Eukaryota


Thaumarchaeota


1

Thaumarchaeota

Giardia lamblia


1

Euryarchaeota


0.2

!47


!48


!49


!50

Concatenated Proteins


4874

(a)



Pyrococcus furiosus

(b)


0.51


Euryarchaeota


Thermoplasma acidophilum



Pyrococcus furiosus


1


Giardia lamblia
1

Giardia lamblia


1

Phytophthora ramorum
Homo sapiens

0.81 0.99

Naegleria gruberi
Leishmania major

Eukaryota

Homo sapiens

Leishmania major


1


1

Caldiarchaeum subterraneum

Phytophthora ramorum
Korarchaeum cryptoﬁlum

Thaumarchaeota

Nitrosoarchaeum limnia

Aigarchaeota

1
1
0.99


Crenarchaeota

1


Crenarchaeota


Aeropyrum pernix



Aeropyrum pernix

Escherichia coli

0.5

Treponema pallidum




Thaumarchaeota



Nitrosoarchaeum limnia

1

Korarchaeota
Aigarchaeota

Caldiarchaeum subterraneum


0.99

Eukaryota



0.99

Euryarchaeota

Bacteria

Synechocystis sp.

0.2

Figure 2. Phylogenies of Bacteria, Archaea and eukaryotes inferred from conserved protein-coding genes. (a) A phylogeny
inferred from 29 concatenated proteins conserved between Bacteria, Archaea and eukaryotes. An eocyte topology was recovered with strong (PP ¼ 0.99) support. In this phylogeny, the eukaryotes emerge as the sister group of Korarchaeum, nested with
the TACK superphylum. (b) A phylogeny inferred from 63 concatenated proteins shared between Archaea and eukaryotes. The
position of the root is not explicitly indicated. However, based on the result from (a) and the electronic supplementary material,
table S4, it is likely to be either within, or on the branch leading to, the Euryarchaea. If this position is correct, then the tree
shows the eukaryotes emerging as the sister group to the TACK superphylum, including Korarchaeum. These trees were
inferred using the CAT model in PHYLOBAYES. Branch lengths are proportional to substitutions per site, except the truncated
bacterial branch in (a). for UC Davis EVE161 Course Taught by Jonathan Eisen Winter 2014
Slides

!51


!52


!53

Tree Congruence

4876


(b)

(a)

no. tests passed (P > 0.05)

250
frequency

model
CAT20
LG

60

300

200
150
100

50
40
30
20
10

50

0

0
1

2

3
distance

4

saturation and
site-specific
compositional
homoplasy biochemical diversity heterogeneity

5

(c)

model
CAT20
LG

1.2
1.0

density

0.8
0.6
0.4
0.2
0
1.0

1.5

2.0
distance

2.5

3.0

Figure 3. Analysing incongruence using a novel measure of distance between gene trees. We used distributions of pairwise geodesic distances between gene trees to compare levels of incongruence inferred under different evolutionary models. (a) The
distribution of distances under a single model (CAT20) can be used to identify obvious outliers corresponding to highly incongruent gene trees; a single gene was responsible for the peak highlighted in red, and was removed from subsequent analyses.
(b) Overview of model-fitting tests (posterior predictive simulations) for each gene in the 64AE dataset. The height of the bars
indicates the proportion of genes that ‘passed’ a test under a particular model; we said that a test was passed when the value of
the test statistic on the real data fell within the central 95% of the distribution of values produced by posterior predictive simulation. The results suggest that CAT20 fits better than LG, successfully accounting for the observed levels of saturation and
homoplasy in all but one of the alignments. Both models do a poor job of modelling the site-specific selective constraints in
our dataset, although again CAT20 performs better than LG (13 passes as opposed to 0). (c) Comparison of the distance distributions inferred under the CAT20 and LG models. The trees inferred under the better-fitting CAT20 model are significantly
more congruent than those inferred under LG (mean distance: 2.68 versus 3.22, p , 0.0001). The significance of this difference was assessed using a permutation test that took the correlations between pairwise distances into account (see §4). These
results suggest that a significant portion of the incongruence in this dataset of informational genes can be attributed to model
misspecification, rather than genuinely distinct evolutionary histories.

3. CONCLUSIONS

theories of eukaryotic origins [1]. Here, we have com-

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EVE 161 Lecture 4

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