Rob Beiko - #SMBE12 presentation

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Rob Beiko A network of everything??

description

Short presentation about just how messy prokaryotic phylogeny can be, and some first attempts to make sense of the data using different network approaches.

Transcript of Rob Beiko - #SMBE12 presentation

Page 1: Rob Beiko - #SMBE12 presentation

Rob Beiko

A network of everything??

Page 2: Rob Beiko - #SMBE12 presentation

the basis of microbial taxonomy

Woese et al (1990) PNAS

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contrasting 16S trees

Trimmed & RY-recoded

Morgan Langille, Conor Meehan

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concatenated protein trees?Concatenated alignment of 92 single-copy Lachnospiraceae proteins(minimum support value 0.91)

Conor Meehan, Chris Whidden

Ribosomal protein L7AdSPR = 10

Most protein trees reject this topology (AU test)

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phylogenomics writ large

Build "all the trees of all the genes", and summarize the patterns that emerge

Can summarize properties of TREES,build SUPERTREES,

or try to construct NETWORKS

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2005: highways of gene sharing

144 genomes, 22,432 treesSupertree analysis, common pathways of LGT Beiko et al. (2005) PNAS

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2011: "telling the whole story"

1173 genomes

159,905 treesGenome

networks

Beiko (2011) Biol Direct

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Neighbor-net of 298 genomes(mean normalized BLASTP distances)

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Nearest neighbors of Acidithiobacillus in 504 phylogenetic trees

not shown: 795 trees w/multiple partnersalso not shown: 333 trees with other, less common partners

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the curious case of Acidithiobacillus

Trait-based taxonomy: A. and many other acidophiles grouped into Thiomonas16S was used to carve up the group in different genera (and classes)Phylogenomics actually brings the group back together!

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Intergenomic affinity graph

Nodes are genera

Edges connect genera with substantial phylogenetic connections (sisters in at least five trees & count of such trees at least 20% of strongest affinity)

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Galled network of 13 trees with Coprothermobacter partners and Archaea (for rooting)

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example network• Challenges:–Many different sources of discordance– Taxonomic overlap is poor– Need to root trees– The best threshold for inclusion of

reticulations is not obvious

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open problems• Orthology, alignment, trees• Testing for model violations• Feeding statistical support to networks• Duplication and loss (DLT scenarios)• Merging different lines of genomic evidence

• Deciding what to show and what to exclude:– Statistical: Count / frequency threshold?– Biological: Adaptive vs. "churn"?– Topological: Distance of transfer?

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Fin