Gene-tree/species-tree discordance and diversification

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Gene-tree/species-tree discordance and
diversification
Sara Ruane CUNY (CSI, GC)
R. Alex Pyron The GW Univ.
Frank Burbrink CUNY (CSI, GC)
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Understanding patterns of diversification

• Ecological Opportunity
• Key Innovations
• Competition
• Extinction
• Ecological Limits

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History of the study

• Paleontological Research
• Understand patterns of speciation and extinction
  through time
• Simpson (1944, 1953)
• Sloss (1950)
• Sepkoski (1979)
• Stanley (1979)
• Raup (1985)
• Foote (1993)

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Sloss 1950
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Molecular Phylogenetic Approaches

• Waiting times between speciation
• Slowinski and Guiher (1989)
• Harvey et al. (1991, 1994)
• Nee et al. (1992, 1994)
• Pybus and Harvey (2000)
• Rabosky (2006, 2008)
• Purvis et al. (2009)

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Gamma and Rate Variable Models

• Gamma (?) examines the density of nodes relative
  to time
• Models of diversification
• 1 ) Constant
• Yule, Birth-Death
• 2) Variable
• Yule2, Yule3, DDL, DDX

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Plethodon ouachitae Complex
Early
Late
Even (Yule)
Log(Lineages)
Time
Gamma 2.2 (LB/Ext)
Gamma -4.5 (DDL)
Gamma -1.3 (Yule)
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External Problems with Molecular Trees

• Only Looking at the winners
• Extinction dynamics must come from data external
  to the tree or tame diversification rate
  variation across a tree
• Can we see all speciation events?

Quental and Marshall (2010)
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Internal Problems Gene-Tree/Species-Tree
Discordance
A
B
(See Edwards and Beerli 2000)
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What does ?t tell us?

• Increasing 2Ne (T/2) increases ?t
• Gene div gt Species div
• ?t will be small as div time between species
  becomes large, because ?t will be a small
  fraction of the total gene divergence
• At deep div SG
• At shallow div SltltG

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Simulating gene trees from species trees
?t
Tree Depth
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Impact on diversification estimation

• Disproportionally pushes younger nodes towards to
  the root
• Density of nodes increases gt root.
• Decreasing ? (early burst!)
• Variable diversification models
• Impact of T (4Neµ)?

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Simulations

• In R
• (Phybase, Ape, Geiger, Laser, Phangorn)
• Simulate Species Trees (ST)
• Yule ?0 and BD
• Taxa 25-100
• Simulate Gene Trees (GT)
• T 0.0001-100
• T G distribution

Burbrink Pyron 2011
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What are we looking for?

• Impact of T on ?-error (GT ST)
• Topology (RF Distance)

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Simulation Results
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Implications

• T gt 1 yields a pattern of early burst (-?)
• T gt 1 also increases topological discordance
• Is T gt 1 likely?
• Most studies of extant populations are well below
  1.0.

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Empirical Study

• Group with all species sampled
• Enough genes to construct a species trees
• Lampropeltis
• 21 species of snakes
• Throughout North America and South America
• 12 Loci

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Comparisons

• Tested fit of model for all genes and partitions
• Species Trees (Beast) 3-7 individuals /species
• Individual Gene Trees (Beast)
• Concatenated gene trees with mtDNA
• Concatenated gene trees nuclear genes only
• Two calibration points

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Lampropeltis Concat Gene Tree Depth Error
R20.87 Plt4.36x10-7
?t
Tree Depth
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Null Distribution Yule
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SpeciesTree -0.169 Yule
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SpeciesTree -0.169 Yule
Nucl Gene Trees -1.512 to 0.415 Yule
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SpeciesTree -0.169 Yule
Nucl GT -1.512 to 0.415 Yule
mtDNA GT -2.19 DDL
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SpeciesTree -0.169 Yule
Concat GT mtdna and nuc -2.474 DDL
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SpeciesTree -0.169 Yule
Concat mtdna and nuc -2.474 DDL
Concat nuc -2.11 Yule2
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Is ?-errorassociated with topological
discordance?
R20.083 P0.787
?-error
RF
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Issues

• Increasing T increases ?-error
• Mean T for Lampropeltis 0.0055 (Max0.04)
• GT/ST divergence and ? discordance shouldnt be
  high
• Nuclear gene trees ? are similar to ST
• mtDNA estimates (alone or with other genes)
• of ? are underestimated (early burst)

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Why mtDNA Problems?

• Model underparametrization decreases ? (Revell et
  al. 2005)
• Saturation Driven Compression
• Deeper nodes are
• artificially compressed
• Decreases ?
• Usually at very old time scales
• In Lampropeltis, mtDNA
• ? (substitutions) increases
• towards terminal branches
• (W 604.5, P 0.0002477)

Hugall et al. 2007, Sanders et al. 2008, Zheng
et al. 2011
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Conclusions

• mtDNA GTs poorly estimate diversification
  dynamics
• Use Species Trees!
• And include fossils (if possible)
• Investigate Impact on other comparative methods
• Simulations account for
• T
• Substitution variation
• GT uncertainty

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Thanks to

• My coauthors (Sara and Alex), PSC-CUNY, and NSF.

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Simulation Results
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Sloss 1950