Application of Phylogenetic Networks in Evolutionary Studies

1. Application of Phylogenetic Networks in Evolutionary Studies Daniel H. Huson and David Bryant Presented by Peggy Wang

2. The plan • Terminology • Split networks: • What are they? • How can they be interpreted? • Phylogenetic inference • SplitsTree4

3. A tree of terms..

4. Terminology • phylogenetic network any network in which taxa are represented by nodes and their evolutionary relationships are represented by edges

5. Types of networks • phylogenetic tree Leaf labeled tree that represents the evolutionary history of a set of taxa, possibly with branch(edge) lengths, either unrooted or rooted. • reticulate network Phylogenetic tree + additional edges. Nodes with more than two parents represent reticulate events such as hybridization, recombination and hgt • split network Represents incompatible and ambiguous signals in a data set. Parallel edges represents splits computed from data. Incompatible splits may result in nodes that do not represent ancestral species.

6. Wait… whats a split again? • split A partition of the taxa into two nonempty subsets, such as the partition obtained when we remove a branch from a phylogenetic tree. • split network (formally) For a given taxon set X and set of splits S, we define a split network N to be a connected graph in which some of the nodes are labeled by taxa and all edges are labeled by splits.

7. Removing all edges associated with a given split s in S divides N into two connected components, one part containing all taxa on one side of S and the other part containing all taxa on the other side. The edges along any shortest path in N are all associated with different splits. A split network contains exactly the same information as a list of splits with a weight for each split.

8. Every split network represents a unique collection of splits. • A given collection of splits can have many different split network representations. • The interpretation of the network depends on how the splits were constructed and assigned weights…

9. Interpreting Split Networks: Representing multiple trees • We can use split networks to summarize a large collection of trees. • Code each individual tree as a collection of splits • Define a summary set of splits • Represent the set using a split network. • Consensus networks • Constructed from all splits appearing in at least some fixed proportion of input trees

10. Interpreting Split Networks:Representing multiple trees • Confidence sets • Assign an interval for the weights of each split • A tree is contained within the split network N if • Every split in the tree is a split in the network • For every split in the tree, the corresponding branch length is contained within the corresponding interval • For every split in the network not in the tree, the assigned interval contains zero. . N

11. Interpreting Split Networks:Representing multiple trees Geometric interpretation: Index splits from 1 to m. Tree can be coded as a point in m-dimensional space: the ith coordinate is the length of the ith split, or 0 if that split is not present in the tree.

12. Interpreting Splits Networks:Networks and systematic error • Sampling error Random error resulting from a small sample size (number of sites). Deal with these errors using nonparametric bootstrap, multiple samples from posterior distribution • Systematic error Mistakes in the assumptions of a model or method which cause data to be misinterpreted. Likely to occur with large, multigene, heterogeneous data sets. How to deal with these errors?

13. Interpreting Splits Networks:Networks and systematic error • Phylogenetic inference • Construct a split network using the best available model and method. • Determine if the network is significantly different from a tree. • If the tree is significantly non-treelike, then there is probably an error in the model. If possible, improve the model and try again. • If the network is treelike, and there is no significant sampling error, the continue with a tree-based phylogenetic analysis.

14. Reticulate Networks 2 disagreeing trees Split network represents all splits present in either of the two trees Reticulate network Explains the differences in the two trees using 3 reticulation events

15. SplitsTree4 • Integrates a wide range of phylogenetic network and phylogenetic tree methods, inference tools, data management utilities, and validation methods. • Included methods for inferring split networks: • From character data. Median networks, parsimony splits, spectral analysis • From distance matrices. Split decomposition and neighbor-net • From sets of trees. Consensus networks and supernetworks. • Also constructs other types of phylogenetic networks, eg recombination and hybridization networks • User friendly?!

16. Jukes-Cantor p=0.75 q=0.05 0<r<0.4 Example 1:Heterogeneous Evolution

17. Example 2:Animal Phylogeny Coelomate hypothesis Ecdysozoa hypothesis

18. More examples..Dusky dolphins 60 variables (sites of DNA) 35 haplotypes Neighbor-joining tree with bootstrap values Consensus network of 3 MP trees Split decomposition network 95% confidence network Median network Neighbor-net network

19. Conclusion! • Split networks are useful for visualization. • However they are not useful for making conclusive phylogenetic analysis. • SplitsTree4 encompasses many tools, but are they really that useful?