medellin2009
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Seminar at SIU, Medellín Friday August 28th, 2009TRANSCRIPT
Origin and Evolution of Early Eukaryotes
James McInerney,National University of Ireland Maynooth,
August 25th, 2009,
And the LORD God made all kinds oftrees grow out of the ground--treesthat were pleasing to the eye andgood for food. In the middle of thegarden were the tree of life and thetree of the knowledge of good andevil.
Genesis 2:9
Hypothesis Implied Relationship s Phylogenetic signals expected in genomic analys e s
Tree of lifea Archaea and Eukaryota are sister groups.
Eukaryotic genes should show 3 monophyletic domains or Eukaryota Archaebacteria .
Eukaryota-firstb
Eukaryota is the first diverging domain, while Eubacteria and Archaea are sister groups.
Most eukaryotic genes should not have a prokaryotic homologue. Others should show 3 monophyletic domains or Eukaryota with Archaebacteria .
Eocytec Eukaryota is the sister group of Crenarchaeota .
Eukaryotic genes with Crenarchaeota .
Phagotrophyd Eukaryota and Archaea are sister groups. This group stemmed from Actinobacteria .
Eukaryotic genes with Archaebacteria, and these two with Actinobacteria.
Serial endosymbiosise
Symbiosis of a Thermoplasma-like archaeon and a spirochete (Eubacteria). Mitochondria probably via symbiosis with an -proteobacterium.
Eukaryotic genes with Thermoplasma, spirochetes or -Proteobacteria .
Syntrophy-1f
Eukaryota originated through the symbiosis of a methanogen and a -proteobacterium.
Eukaryotic genes with methanogenic Archaea (or within Euryarchaeota), - or
-Proteobacteria.
Hydrogen Hypothesisg
Eukaryota originated through the symbiosis of a methanogen and an -proteobacterium (the mitochondrion) .
Eukaryotic genes with methanogenic Archaea (or within Euryarchaeota) or -Proteobacteria .
Syntrophy-2h Eukaryota originated through the symbiosis of a sulfur-methabolising Thermoplasmatales-like euryarchaeote and an -proteobacterium (the mitochondrion) .
Eukaryotic genes with Thermoplasmatales (or within Euryarchaeota) or -Proteobacteria .
Ring of lifei Eukaryota originated through the symbiosis of a Crenarchaeota and an -proteobacterium.
Eukaryotic genes with Crenarchaeota or -Proteobacteria.
Mitochondrion origins
Rhodospirillum rubrum
• Rickettsia prowazekii
Comparisons of the same bacterialspecies
E. coli K12 E. Coli 0157:H7
Horizontal gene transferdoes occur between species
McInerney, J.O., Cotton, J.A. and Pisani, D. (2008) The Prokaryotic Tree of Life:Past, Present...and Future? Trends in Ecology and Evolution 23 (5) 276-281
Doubts concerning a universal tree
…most archaeal and bacterial genomes (and
the inferred ancestral eukaryotic nuclear
genome) contain genes from multiple
sources.
…If "chimerism" or "lateral gene transfer"
cannot be dismissed as trivial in extent or
limited to special categories of genes, then
no hierarchical universal classification can
be taken as natural.Phylogenetic classification and the universal tree.Doolittle WF. Science. 1999 Nov 19;286(5444):1443
Ford Doolittle
The importance of congruence• “The importance, for
classification, of triflingcharacters, mainly depends ontheir being correlated withseveral other characters of moreor less importance. The valueindeed of an aggregate ofcharacters is very evident ...aclassification founded on anysingle character, howeverimportant that may be, hasalways failed.”
• Charles Darwin
• Origin of Species, Ch. 13
Candidate Supertree
….
x1 x2 x3 x4 x... xn
Source Trees
Score = ∑xn
Supertree Source tree
Alpha-proteobacteria
Fitzpatrick, D.A., Creevey, C.J. and McInerney, J.O. (2006). Genome Phylogenies Indicate a Meaningful α-Proteobacterial Phylogeny andSupport A Grouping of the Mitochondria With the Rickettsiales. Molecular Biology and Evolution 23: 74-85.
The mitochondrion isdescended from a common
ancestor with theRickettsiales.
Pisani, D., Cotton, J.A. and McInerney, J.O. (2007). Supertrees Disentangle the ChimericalOrigin of Eukaryote Genomes. Molecular Biology and Evolution. 24(8):1752–1760.
Bacteria
Archaebacteria
Modularity
Protocol• All Saccharomyces cerevisiae proteins
subjected to homology search againstCaenorhabditis elegans, Arabidopsis thaliana,Schizosaccharomyces pombe, Neurosporacrassa, Ashbya gossypii, Trypanosoma cruzi.
• Multiple alignment of resulting significant hits andprofile search against prokaryotic genomes (197bacterial, 22 archaebacterial).
• Two datasets used:– Phylogeny-dependent– Phylogeny independent
Overview• 2,460 out of 6,704 genes have prokaryotic
homologs.• 1,980 genes have a eubacterial best hit,
480 archaebacterial.• 952 genes have only eubacterial
homologs, 216 only archaebacterial.
So there is a larger role foreubacterial homologs
•Right?
Importance?
• Which is more important….– An informational or an operational gene?– A highly-expressed gene or a lowly-
expressed gene?– A gene that is central to metabolism or
one that is peripheral?– A gene that is lethal upon knockout or one
that is not?
Odds ratio• We describe associations between factors using
the odds ratio.• e.g., the odds of being archaebacterial for
informational genes is calculated as theprobability of an informational gene having anarchaebacterial homolog, divided by theprobability of the gene having a eubacterialhomolog.
• We can similarly calculate the odds of beingarchaebacterial for operational genes, and theodds ratio is the ratio of these two odds.
Confirmation of informationalbias
• We confirm a significant bias towardsarchaebacterial homology for genes withinformational functions (odds ratio(or)=2.37; 95% confidence interval(ci)=1.59-3.52), although genes witharchaebacterial homologs are found acrossmost gene ontology biological processes.
Link between lethality andinformational genes
• Lethal genes are almost three times aslikely to have archaebacterial homologsthan bacterial ones (or=2.96; 2.32-3.77).
• Informational genes are significantly morelikely to be lethal than operational genes(or=2.98; 2.03-4.40).
Link between lethality andArchaebacterial homology
• Lethality of archaebacterial genes is almostidentical across the two categories (forinformational genes, or=2.01; 0.92-4.41; foroperational genes, or=1.89; 1.43-2.47)
DATATYPE Bact Arch All p-value
L phase, number of SAGE tags sequenced 1.76 (1.43,2.17) 3.42 (2.15,5.16) 1.96 (1.74,2.21) 0.0034
S phase, number of SAGE tags sequenced 1.93 (1.59,2.33) 2.97 (1.94,4.35) 2.05 (1.82,2.30) 0.0395
G2/M phase boundary, number of SAGE tags
sequenced
1.55 (1.27,1.88) 2.99 (1.97,4.39) 2.04 (1.81,2.28) 0.0028
Closeness Centrality in interaction network 0.314
(0.312,0.316)
0.324
(0.321,0.327)
0.316
(0.315,0.317)
< 0.0001
Degree in interaction network 15.91
(15.20,16.62)
20.90
(19.33,22.48)
18.02
(17.60,18.48)
< 0.0001
Number of homologs in yeast genome 13.13
(12.09,14.16)
8.02 (6.89,9.22) 7.58 (7.14,8.04) 1
P-values are bootstrap probabilities for the mean of the statistic in archaebacteriabeing less than or equal to the mean in eubacteria, based on 10,000 replicates.
Threonine and lysine metabolism
Pentose phosphate pathway
Arginine metabolism
• Irish Centre for High End Computing• NUIM HPC
• Funding:– Marie Curie– SFI– IRCSET.
• Prokaryotic “Tree”– Chris Creevey
– David Fitzpatrick
– Mary O’Connell
– Melissa Pentony
– Simon Travers
– Rhoda Kinsella
– Gayle Philip
– Jennifer Commins
– Thomas Keane
• Eukaryote “Tree”– Davide Pisani– James Cotton– Angela McCann
• Supertree Theory– Dr. Mark Wilkinson,
Natural History Museum.