PRINCIPLES OF PHYLOGENETICS ECOLOGY AND EVOLUTION Integrative Biology 200B Spring 2011 University of California Berkeley B D Mishler Jan 27 2011 Qualitative character evolution within a cladogram In this portion of the class we are interested in examining how discrete state characters evolve on a tree individually and together These are characters that meet the discrete state criteria for taxonomic characters that we discussed earlier Other quantitatively varying characters can also be studied but they require different methods which we ll cover later When we do such mapping we are inferring history trying to use our knowledge of the observed twigs of the trees semaphoronts OTUs to infer traits of hypothesized ancestors Hypothetical Taxonomic Units HTUs The historical concept of homology discussed in the first lecture both requires and makes possible these kinds of inference When we focus on the question of character evolution we will assume that we have already obtained a phylogeny with possible uncertainties As we map the history of particular characters we are not reevaluating the underlying phylogenetic hypothesis Some have argued that you must not include a character for phylogeny reconstruction and then also map its ancestral states to test evolutionary hypotheses What do you think Mapping of character states on a tree is an essential starting point for comparative methods related to phenotypic traits The analysis of ancestral derived states is central to phylogenetic approaches to questions of adaptation divergent convergent evolution and correlated evolution A typical adaptive hypothesis posits that trait X is an adaptation to selective pressure Y For example tough evergreen leaves termed sclerophylls are an adaptation to semi arid environments This hypothesis may be tested in various ways but one of the key predictions is that lineages with sclerophyll leaves first encountered semi arid environments and then evolved sclerophylly If they evolved sclerophylly before encountering the hypothesized selective environment then this trait must have evolved and thus be an adaptation in response to some other factor This is one type of question that would lead you to conduct a comparative test I Ancestral states under parsimony The simplest approach to mapping ancestral states is the parsimony principle we seek the reconstruction that requires the fewest evolutionary steps or transitions between character states We don t know that evolution proceeded in this way but the basic argument for parsimony is that we should not assume any additional evolutionary events beyond the minimum number necessary to explain the observed patterns After calculating the ancestral states for a character we can then test a number of hypotheses regarding the number of steps their distribution on a tree the polarity of character change and the sequences or associations of change in two or more characters The exact algorithm for calculating ancestral states by parsimony depends on the type of character and the assumed cost of transition among different states 1 Unordered traits have 2 or more states and all transitions require only a single step 2 Ordered traits have 3 or more states on an ordinal scale and the number of steps is equal to the difference in state values i e from 1 to 3 requires 2 steps 3 Dollo traits change is only allowed from ancestral to derived state reversals require infinite steps 4 Arbitrary step matrices allow user to assign any desired cost structure to transitions In many cases most parsimonious reconstructions MPR can be estimated visually though it is easy to miss alternative equally parsimonious reconstructions when there are several gains and losses Equivocal assignments to HTUs are quite frequent under parsimony when there is close homoplasy so be aware There are two ways to arbitrarily resolve equivocal assignments ACCTRAN vs DELTRAN To illustrate the mechanics of parsimony reconstruction the formal algorithm for Fitch parsimony for unordered states is provided below Note In contrast with the maximum likelihood methods we will study next lecture branch lengths are not incorporated in parsimony algorithms One can calculate a branch length after the fact based on the number of characters that change on a branch but they are not used in the process of determining the MPR A number of specific types of hypotheses can be tested with these character mappings estimating phylogenetic conservatism covered below polarity of character changes in one character trends association of state changes in two or more characters next lecture Fitch parsimony algorithm ancestral reconstruction of an unordered trait binary or multistate simplified algorithm for bifurcating tree no polytomies with no internally fixed states Set notation Intersection the items shared by both sets Union the combined list of items from both sets The null or empty set Definitions downpass an algorithm that starts at the terminal taxa and works downward through the ancestral nodes so all daughter nodes must be visited before visiting a deeper ancestral node uppass an algorithm that starts at the root and progresses upwards to the terminals MPR Most Parsimonious Reconstruction P Q M N nodes of the tree see figure on board S downpass state set F uppass state set L length of tree number of changes assign RHS to LHS Start with L 0 Algorithm 1 Fitch downpass algorithm if N is terminal DN observed trait value else DN DP DQ if DN DN DP DQ L L 1 Algorithm 2 Fitch uppass algorithm if N is root UN DN else UN DS UM if UN UN DS UM Algorithm 3 Assign MPR at each node MPRroot DN MPRN UM DP DQ if MPRN MPRN UM DP DP DQ UM DQ if MPRN MPRN UM DP DQ 2 Is a trait conserved Null models for the number of changes on a tree After reconstructing the evolutionary history of a trait you might wish to test a hypothesis about whether the trait has undergone an unusually small or large number of transitions between alternative states This is the question of phylogenetic signal if the trait exhibits a small number of transitions then it will be conserved over large portions of the tree and close relatives will tend to exhibit the same state high phylogenetic signal conserved trait If the trait exhibits a large number of changes then close relatives will frequently have different states low phylogenetic signal divergent convergent trait Testing the hypothesis of phylogenetic signal requires that we compare the observed number of transitions to some
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