5. assess reliability
DESCRIPTION
123456789. taxa1. CGATCGTTA. taxa2. CAATGATAG. taxa3. CGCTGATAA. CGCTGATCG. taxa4. Dataset1: 729338554. Dataset2: 631981282. …. Dataset1: 1-3-56789. Dataset2: 12-45678-. …. 5. Assess Reliability. Resampling to produce pseudo-dataset (random weighting). 100. 73. I. Bootstrap. - PowerPoint PPT PresentationTRANSCRIPT
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5. Assess Reliability
I. Bootstrap
Resampling to produce pseudo-dataset (random weighting)
II. Jacknife
Sampling with replacement
III. Permutation test
Random deletion of sub-dataset
Randomize dataset to build null likelihood distribution
CGATCGTTA
CAATGATAG
CGCTGATAACGCTGATCG
taxa1
taxa2
taxa3
taxa4
123456789
Dataset1: 729338554Dataset2: 631981282…
Dataset1: 1-3-56789Dataset2: 12-45678-…
10073
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• Was the ancestor of bacteria a thermophile?– Reconstructed EF-Tu at key nodes (Gaucher et al., 2003)
• All ancestral types have high Topt
Reconstructed ancestral sequences to infer environment
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Genetic exchange in bacteria/archaea
• Transformation– Used by Griffiths, and later Avery
to show DNA is genetic material– Some bacteria naturally competent
• Transduction– Generalized & specialized
• Conjugation– High-frequency recombinants (Hfr)
• All are partial and unidirectional
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Detecting HGT from genomes: atypical nt composition
• Recent transfers often have unique signature
• “Molecular archaeology” of E. coli (Lawrence & Ochman, 1998)
– 17.6% HGT, but amelioration since– Calculated age distribution based on
average rate of divergence (Hacker & Carniel, 2001)
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HGT genes often clustered
• HGT genes often clustered in large islands encoding related function
• Could HGT itself drive operon formation?– Selfish operon theory (Lawrence & Roth, 1996)
– Linkage increases chance of co-transfer of cluster– Recent analysis (Price et al., 2005)
• Identified HGT events and new operons in E. coli• No particular enrichment of HGT in new
operons• Role of co-regulation instead?
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Detecting HGT: incongruent phylogeny/synteny
• Any incongruent phylogeny could be explained by HGT or independent gene loss
HGT only Loss only
(Koonin, 2003)
Ex: glycerol-3-P DH
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Detecting HGT: H4MPT pathway
• Tree based upon concatenated sequences (bootstrap = distance/parsimony; Kalyuzhnaya et al., 2005)
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Detecting HGT: H4MPT pathway
different
similar
(Kalyuzhnaya et al., 2005)
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Detecting HGT: H4MPT pathway
different
similar
New C1 genes found due to clustering
(Kalyuzhnaya et al., 2005)
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Detecting HGT: H4MPT pathway
E
Euryarchaeaota
Crenarchaeaota
Proteobacteria
LUCA
Other Bacteria
D
Euryarchaeaota
Crenarchaeaota
Proteobacteria
Planctomycetes
LUCA
Other Bacteria
Planctomycetes
E
Euryarchaeaota
Crenarchaeaota
Proteobacteria
LUCA
Other Bacteria
D
Euryarchaeaota
Crenarchaeaota
Proteobacteria
Planctomycetes
LUCA
Other Bacteria
Planctomycetes
A
Euryarchaeaota
Crenarchaeaota
Proteobacteria
Planctomycetes
LUCA
Other Bacteria
Euryarchaeaota
Crenarchaeaota
Proteobacteria
Planctomycetes
LUCA
Other Bacteria
B
Euryarchaeaota
Crenarchaeaota
Proteobacteria
PlanctomycetesOther Bacteria
C
LUCA
A
Euryarchaeaota
Crenarchaeaota
Proteobacteria
Planctomycetes
LUCA
Other Bacteria
Euryarchaeaota
Crenarchaeaota
Proteobacteria
Planctomycetes
LUCA
Other Bacteria
B
Euryarchaeaota
Crenarchaeaota
Proteobacteria
PlanctomycetesOther Bacteria
C
LUCA
Scenarios for pathway evolution (Chistoserdova et al.,
2004)
(Kalyuzhnaya et al., 2005)
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Detecting HGT: plants!?!(Davis & Wurdack, 2004)
Rafflesia (Malpighiales)Rafflesia (Malpighiales)
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Detecting HGT: differential gene content
• Analysis of three E. coli (Welch et al., 2002)
– Shared genes >95% similarity– Each genome only ~½ core genes– Combination of HGT & differential loss
• Identity of non-core genes?– Unusually AT-rich & short
(Daubin & Ochman, 2004)
– Tend to be more environment-specific (Pál et al., 2005)
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Detecting HGT: differential gene content
• Analysis of three E. coli (Welch et al., 2002)
– Shared genes >95% similarity– Each genome only ~½ core genes– Combination of HGT & differential loss
• Identity of non-core genes?– Unusually AT-rich & short
(Daubin & Ochman, 2004)
– Tend to be more environment-specific and “attach” to network periphery (Pál et al., 2005)
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Measurements of natural horizontal gene transfer (HGT)
• Method for in situ plasmid transfer (Sørensen et al., 2005)
• 20-100x higher rate than culture-dep. method
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Measurements of natural horizontal gene transfer (HGT)
• Sort via FACS, amplify 16S rRNA & sequence
• Visualize in situ on leaf
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Limitations to HGT
• Environmental parameters: conjugation in ocean?– Phage appear to be major vectors for exchange
amongst Prochlorococcus (Lindell et al., 2004)
– Some encode unstable photosynthesis proteins that are expressed during infection (Lindell et al., 2005)
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Limitations to HGT
• Environmental parameters: conjugation in ocean?– Phage appear to be major vectors for exchange
amongst Prochlorococcus (Lindell et al., 2004)
– Some encode unstable photosynthesis proteins that are expressed during infection (Lindell et al., 2005)
– Fate and process of incorporating HGT genes into network?
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Can gene histories be retraced?
• trp operon (Xie et al., 2004)
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Can gene histories be retraced?
• “Highways of gene sharing” (Bieko et al., 2005)
– >220000 proteins from 144 genomes
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Can gene histories be retraced?• “Net of life” (Kunin et al., 2005)
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Is there still a tree?: (Daubin et al., 2003)
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Is there still a tree?: (Daubin et al., 2003)
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Is there still a tree?: (Doolittle & Bapteste, 2007)
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“Automated TOL”(Ciccarelli et al., 2006)
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