# Tree Building What is a tree ? How to build a tree ? Cladograms Trees

## Presentation on theme: "Tree Building What is a tree ? How to build a tree ? Cladograms Trees"— Presentation transcript:

Tree Building What is a tree ? How to build a tree ? Cladograms Trees
* 07/16/96 Tree Building What is a tree ? Cladograms Trees Scenario How to build a tree ? Observations First Principles Assumptions Methods Tree Building implies (at least) the two questions shown on the sheet.

What is a tree ? Cladograms and Trees
* 07/16/96 What is a tree ? Cladograms and Trees Both are graphs in mathematical terms: A graph is a collection of nodes (vertices) and lines / branches (edges) connecting the nodes. A cladogram/tree for our purposes is allowed at most one edge between any two vertices. In a strict mathematical context there is no difference between the two cladistic notions of cladogram and tree.

* 07/16/96 Cladogram & Trees - 1 The degree of a node is the number of branches that contain that node. A node of degree 1 is called a leaf (or terminal node) All nodes that are not leaves are called internal.

* 07/16/96 Cladograms & Trees - 2 A tree is elementary if no node has degree 2 (‘net-work’ in cladistic jargon). In a cladistic context unrooted cladograms are often referred to as ‘networks’. In a graph theoretical context that is not correct. Both are ‘trees’. A root is a distinguished node with degree 2, locating the ‘start’ of the tree.

* 07/16/96 Cladograms & Trees - 3 An unrooted tree is binary if every node has degree 1 or 3. A rooted tree is binary if it has a root of degree 2 and every other node has degree 1 or 3.

Cladograms & Trees - 4 C A B ? Labeled rooted binary tree Label Leaf
* 07/16/96 Cladograms & Trees - 4 C A B Label Leaf A picture of a ‘tree’ to illustrate all the concepts introduced in the earlier sheets. Branch ? Node Root Labeled rooted binary tree

* 07/16/96 Cladograms & Trees - 5 What’s the difference? Cladogram Cladogenesis: branching events as indicated by character state changes Tree + Anagenesis: amount and duration of change + inference of ancestor-descendant relationships In a cladistic or phylogenetic-systematics context, what exactly is the difference between a cladogram and a tree ?

* 07/16/96 A Cladogram is a: Statement about the distribution of (shared) character states. Branching diagram depicting nested sets of synapomorphies resulting in a summary statement of sister-group relations among taxa. Two definitions to bring some clarity. The last one is more precise and therefore to be preferred.

Nested sets of Synapomorphies
* 07/16/96 Nested sets of Synapomorphies Detection of relationships by distribution of character-states in species X, Y, and Z. X Z Y aBCde aBCdE abcdE Characters observed in the three species and the states inferred in their putative common ancestors (on the inner nodes) are listed on each, with lower case letters implying primitive states (I.e., ‘A’ is the derived or advanced homologue of ‘a’). Synapomorphies are shared derived character states, homologues features characterizing monophyletic groups. Shared primitive characters, symplesiomorphies, are homologues features inherited from a more remote stem species, so that their distribution is wider than the group of immediate interest. Autapomorphies are a third class of character states, those unique to a species, e.g., ‘A’ and ‘D’ in species X. Monophyletic groups, those characterized by synapomorphies, can also be defined in terms of relationships: a monophyletic group (e.g., X + Y) contains species which are more closely related to each other than to any species outside the group. BC Syn-apomorphy E convergence ad Sym-plesiomorphy aBCde abcde

Relationship, and Kind of Groups
* 07/16/96 Relationship, and Kind of Groups Relationship criterion: Recency of common ancestry “A species X is more closely related to another species Y than it is to another species Z if, and only if, it has at least one stem species in common with species Y that is not a stem species of Z” (Hennig, 1966, p.74) X and Y are sistergroups.

A Phylogenetic Tree is a:
* 07/16/96 A Phylogenetic Tree is a: Branching diagram where: the nodes represent real or hypothetical ancestors, the branching represents speciation, and the branches represent descent with modification. A complete definition for a Phylogenetic Tree.

* 07/16/96 Cladograms & Trees - 6 Cladogram = set of trees Every picture tells a story A B C ? =

* 07/16/96 Cladogram = Set of Trees A B C = ? A C B ? A B C ? A B C C B A B C A B A C ? B A C ?

* 07/16/96 The Cladistic Party Line ... “There is simply no possible way to distinguish ancestors from extinct lineages.” “… if something is in fact an ancestor, there are no data that can refute the hypothesis that it is an extinct lineage and not an ancestor.” (Mark Siddal, 09/01/96, sci.bio.systematics).

* 07/16/96 … and its Counterpart “…’A is the ancestor of B’ is a perfectly valid hypothesis, and one that is easily falsified. All it would take to falsify it is to find an autapomorphy in A that is not found in B.” (Ron DeBry, 18/01/96, sci.bio.systematics)

* 07/16/96 How to build a cladogram Observations Character-state distri-butions over taxa (data matrix), or derivation thereof (distance matrix) First principles Assumptions Process Model Data Type and Quality

First Principles Evolution (descent with modification) occurs.
* 07/16/96 First Principles Evolution (descent with modification) occurs. Evolution results predominantly in a hierarchical scheme of relationships among the entities involved. ...?

* 07/16/96 Assumptions - 1 “ The fact that parsimony methods are known to fail in reconstructing phylogeny when there are unequal rates of evolution, and fail in a systematic way (e.g., put long branches together when they really should each go with one of the short branches) suggest […] that certain conditions of the process of evolution have to be met in order for the method to be useful […]. If a method is only useful when certain conditions of the evolutionary process are met, I would think that these conditions might as well be thought of as assumptions.” (Andrew J. Roger, 08/01/96, sci.bio.systematics)

* 07/16/96 Process “I have a pretty good idea of how evolution works, thus I can check how my data fit these ideas.” “Given the phylogeny, what is the probability to find the data as I did ?” Model = Statistical Framework Maximum likelihood

* 07/16/96 Assumptions - 2 “The philosophical part that deserves more explanation is how you get from whatever general principles you invoke (‘parsimony’) to the specific numerical method used.” “Compatibility methods represent discarding a character because it has some sign of conflict with others. If there are two kinds of characters, really horribly noisy and pretty clean, that is a sensible thing to do. If there are instead two kinds, pretty clean and a little noisy, it is not. So I do not see how the principle of parsimony decides in advance which of these situations we are facing.” (Joe Felsenstein, 14/12/95, sci.bio.systematics)

* 07/16/96 Data “My data will tell me what the optimal set of branching events is and from there I will try to grasp what actually could have happened.” Parsimony Group / Component Compatibility Character Compatibility

Observations Molecular data Morphological data Anatomical data
* 07/16/96 Observations Molecular data DNA sequences: nuclear, mitochondrial, ribosomal DNA-DNA hybridization Restriction-site and -fragment Allelic isozymes Morphological data Anatomical data Chemical data

Black Boxes ? Phylogenetic Principles - 1 Trees Observations
* 07/16/96 Black Boxes ? Phylogenetic Trees Principles - 1 Observations Assumptions Assumptions Optimality Methods Cladogram(s)

Download ppt "Tree Building What is a tree ? How to build a tree ? Cladograms Trees"

Similar presentations