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Gene-tree/species-tree discordance and diversification

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 diversification. Ecological Opportunity Key Innovations Competition Extinction Ecological Limits. History of the study.

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Gene-tree/species-tree discordance and diversification

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  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 (γ) 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 Present Species/Population Divergence (S) Δt =2Ne or Θ/2 Gene Divergence (G) (See Edwards and Beerli 2000)

  10. What does Δt tell us? • Increasing 2Ne (Θ/2) increases Δt • Gene div > Species div • Δt will be small as div time between species becomes large, because Δt will be a small fraction of the total gene divergence • At deep div S=G • At shallow div S<<G

  11. Simulating gene trees from species trees Δt Tree Depth

  12. Impact on diversification estimation • Disproportionally pushes younger nodes towards to the root • Density of nodes increases > root. • Decreasing γ (early burst!) • Variable diversification models • Impact of Θ (4Neµ)?

  13. Simulations • In R • (Phybase, Ape, Geiger, Laser, Phangorn) • Simulate Species Trees (ST) • Yule [γ=0] and BD • Taxa: 25-100 • Simulate Gene Trees (GT) • Θ: 0.0001-100 • Θ: Γ distribution Burbrink & Pyron 2011

  14. What are we looking for? • Impact of Θ on γ-error (GT – ST) • Topology (RF Distance)

  15. Simulation Results

  16. Implications • Θ > 1 yields a pattern of early burst (-γ) • Θ > 1 also increases topological discordance • Is Θ > 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 R2=0.87 P<4.36x10-7 Δt 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 γ-errorassociated with topological discordance? R2=0.083 P=0.787 γ-error RF

  27. Issues • Increasing Θ increases γ-error • Mean Θ for Lampropeltis = 0.0055 (Max=0.04) • GT/ST divergence and γ discordance shouldn’t be high • Nuclear gene trees γ are similar to ST • mtDNA estimates (alone or with other genes) of γ are underestimated (early burst)

  28. Why mtDNA Problems? • Model underparametrization decreases γ (Revell et al. 2005) • Saturation Driven Compression* • Deeper nodes are artificially compressed • Decreases γ • Usually at very old time scales • In Lampropeltis, mtDNA Ε (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: • Θ • 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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