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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) Understanding patterns of ... – PowerPoint PPT presentation

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Title: Gene-tree/species-tree discordance and diversification


1
Gene-tree/species-tree discordance and
diversification
Sara Ruane CUNY (CSI, GC)
R. Alex Pyron The GW Univ.
Frank Burbrink CUNY (CSI, GC)
2
Understanding patterns of diversification
  • Ecological Opportunity
  • Key Innovations
  • Competition
  • Extinction
  • Ecological Limits

3
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)

4
Sloss 1950
5
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)

6
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

7
Plethodon ouachitae Complex
Early
Late
Even (Yule)
Log(Lineages)
Time
Gamma 2.2 (LB/Ext)
Gamma -4.5 (DDL)
Gamma -1.3 (Yule)
8
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)
9
Internal Problems Gene-Tree/Species-Tree
Discordance
A
B
(See Edwards and Beerli 2000)
10
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

11
Simulating gene trees from species trees
?t
Tree Depth
12
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)?

13
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
14
What are we looking for?
  • Impact of T on ?-error (GT ST)
  • Topology (RF Distance)

15
Simulation Results
16
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.

17
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

18
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

19
Lampropeltis Concat Gene Tree Depth Error
R20.87 Plt4.36x10-7
?t
Tree Depth
20
Null Distribution Yule
21
SpeciesTree -0.169 Yule
22
SpeciesTree -0.169 Yule
Nucl Gene Trees -1.512 to 0.415 Yule
23
SpeciesTree -0.169 Yule
Nucl GT -1.512 to 0.415 Yule
mtDNA GT -2.19 DDL
24
SpeciesTree -0.169 Yule
Concat GT mtdna and nuc -2.474 DDL
25
SpeciesTree -0.169 Yule
Concat mtdna and nuc -2.474 DDL
Concat nuc -2.11 Yule2
26
Is ?-errorassociated with topological
discordance?
R20.083 P0.787
?-error
RF
27
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)

28
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
29
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

30
Thanks to
  • My coauthors (Sara and Alex), PSC-CUNY, and NSF.

31
Simulation Results
32
Sloss 1950
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