Comparative Methods on Phylogenetic Networks

Transcription

1 Comparative Methods on Phylogenetic Networks Claudia Solís-Lemus Emory University Joint Statistical Meetings August 1, 2018

2 Phylogenetic What? Networks Why? Part I Part II How? When? PCM

3 What? Phylogenetic network Gene flow

4 What? Phylogenetic network 17% Hahn et al (2016) Explicit Implicit

5 Why? Phylogenetic network Main tree history Gene flow as noise

6 Why? Phylogenetic network Bootstrap support Mean Boostrap support Concatenation γ = k γ = Coalescent tree methods not robust to gene flow or other ASTRAL γ = k γ = NJst γ = k γ = White: true tree k k Number of Genes Number of genes k (Solís-Lemus, Yang, Ané, 2016, Syst Bio)

7 How? Phylogenetic network

8 How? Phylogenetic network Estimate gene trees MrBayes (Huelsenbeck, Ronquist, 2001) RAxML (Stamatakis, 2014)

9 How? Phylogenetic network Data

10 How? Phylogenetic network Maximum pseudolikelihood Data (Solís-Lemus, Ané, 2016, PLoS Genetics) (Solís-Lemus et al, 2017, MBE)

11 When? Phylogenetic network Goodness-of-fit test TICR Data? (Stenz et al, 2015, Syst Bio)

12 1183 genes, 24 swordtails and platyfish Xiphophorus fish data (Cui et al., 2013) γ= γ=0.19 X. hellerii X. alvarezi X. mayae X. signum X. clemenciae X. monticolus X. maculatus X. andersi X. milleri X. evelynae X. variatus X. couchianus X. gordoni X. meyeri X. xiphidium X. continens X. pygmaeus X. nigrensis X. multilineatus X. nezahuacoyotl X. montezumae X. birchmanni X. malinche X. cortezi SS SP NP NS (Solís-Lemus, Ané, 2016, PLoS Genetics)

13 Sword index Female preference Xiphophorus fish data (Cui et al., 2013) γ= γ=0.19 X. hellerii X. alvarezi X. mayae X. signum X. clemenciae X. monticolus X. maculatus X. andersi X. milleri X. evelynae X. variatus X. couchianus X. gordoni X. meyeri X. xiphidium X. continens X. pygmaeus X. nigrensis X. multilineatus X. nezahuacoyotl X. montezumae X. birchmanni X. malinche X. cortezi SS SP NP NS (Solís-Lemus, Ané, 2016, PLoS Genetics)

14 Trait models of evolution in networks l 4 X 4 γ 6b = 0.7 X 1 Hybrid Branch : γ 6a = 0.3 Tree Branch : γ 2 = 1 X 5 X 2 X 3 X 6 X 7 X 8 X 9 X 10 X 11 X 12 X 13 phenotype X 1 X 2 X 3 X 13 X 5 X 11 γ 6a X γ 6 6b X 12 X 4 X 10 X 7 X 8 X time time Brownian Motion + weighted average in hybrid X h = 1 X + p1 2 X p2 (Bastide et al, 2018, Syst Bio) Extends pedigree model for polygenic traits (Thomson, 2000) Similar model for allele frequencies (Pickrell & Pritchard, 2012)

15 Trait models of evolution in networks l 4 X 4 γ 6b = 0.7 X 1 Hybrid Branch : γ 6a = 0.3 Tree Branch : γ 2 = 1 X 5 X 2 X 3 X 6 X 7 X 8 X 9 X 10 X 11 X 12 X 13 phenotype X 1 X 2 X 3 X 13 X 5 X 11 γ 6a X γ 6 6b X 12 X 4 X 10 X 7 X 8 X time time Brownian Motion X N(X root, 2 V) + weighted average in hybrid X h = 1 X + p1 2 X p2 (Bastide et al, 2018, Syst Bio) Phylogenetic signal Ancestral reconstruction Phylogenetic regression Phylogenetic ANOVA

16 Trait models of evolution in networks l 4 X 4 γ 6b = 0.7 X 1 Hybrid Branch : γ 6a = 0.3 Tree Branch : γ 2 = 1 X 5 X 2 X 3 X 6 X 7 X 8 X 9 X 10 X 11 X 12 X 13 phenotype X 1 X 2 X 3 X 13 X 5 X 11 γ 6a X γ 6 6b X 12 X 4 X 10 X 7 X 8 X time time V ij = tij P p i path to i Pp P j path to j p i p t j e2p i \p j e if tree if network X N(X root, 2 V) (Bastide et al, 2018, Syst Bio)

17 Sword index Female preference Ancestral reconstruction: common ancestor likely had sword Phylogenetic regression: positive association between sword index and female preference but not significant (p = 0.106) Y i = X i + i where N(0, V) Preference Sword Index * X. maculatus X. andersi 0.23* 0.28 X. milleri 0.25* 0.25* 0.25* * 0.2* X. gordoni X. meyeri X. couchianus X. variatus X. evelynae X. xiphidium * X. nigrensis X. multilineatus X. pygmaeus X. continens X. malinche X. birchmanni -0.12* 0.37 X. cortezi X. montezumae * 0.62* * 0.62* X. clemenciae X. monticolus X. signum X. hellerii X. alvarezi X. mayae

18 Test for transgressive evolution X h = 1 X p1 + 2 X p2 + h l 4 X 4 γ 6b = 0.7 X 1 Hybrid Branch : γ 6a = 0.3 Tree Branch : γ 2 = 1 X 5 X 2 X 3 X 6 X 7 X 8 X 9 X 10 X 11 X 12 X 13 phenotype X 1 X 2 X 3 X 13 X 5 X 11 γ 6a X γ 6 6b X 12 X 4 X 10 X 7 X 8 X time time h =0 h = h No transgressive evolution Single-effect transgressive evolution Multi-effect transgressive evolution F tests Hybrid value: shift from parents range

19 Test for transgressive evolution X h = 1 X p1 + 2 X p2 + h l 4 X 4 γ 6b = 0.7 X 1 Hybrid Branch : γ 6a = 0.3 Tree Branch : γ 2 = 1 X 5 X 2 X 3 X 6 X 7 X 8 X 9 X 10 X 11 X 12 X 13 phenotype X 1 X 2 X 3 X 13 X 5 X 11 γ 6a X γ 6 6b X 12 X 4 X 10 X 7 X 8 X time Sword index: no evidence Female preference: evidence for heterogeneous (p = 0.009) time Hybrid value: shift from parents range

20 Step-by-step tutorial Online documentation Google user group (Solís-Lemus et al, 2017, MBE)

21 Acknowledgements Cécile Ané Bret Larget Douglas Bates Paul Bastide Ricardo Kriebel Will Sparks David Baum Mengyao Yang John Malloy John Spaw Noah Stenz Nan Ji Jordan Vonderwell Josh McGrath

22 Anomalous unrooted gene trees with gene flow Frequency among gene trees Quartet =0.0 =0.1 =0.3 AB CD CA BD CB AD t 1 = t 2 =0.01,t 3 = t 4 = t 5 =1 ILS: no AUGT on 4 taxa (Degnan, 2013) ILS+HGT: AUGT on 4 taxa (Solís-Lemus, Yang, Ané, 2016, Syst Bio)

23 Anomaly zone with gene flow 0.45 match species tree conflict species tree γ (Solís-Lemus, Yang, Ané, 2016, Syst Bio)

24 SNaQ performance Good diamond Bad diamond (Solís-Lemus, Ané, 2016, PLoS Genetics)

25 Idea of proof of identifiability: hybridization System of equations {CFnetwork} System of equations {CFtree}

26 Idea of proof of identifiability: hybridization Solution to CFnetwork = CFtree if