Molecular phylogenetics 4

1
Molecular phylogenetics 4

• Level 3 Molecular Evolution and Bioinformatics
• Jim Provan

Page and Holmes Sections 6.7-8
2
Have we got the true tree?

• Several approaches developed to answer this
  question
• Analysis
• In some cases (e.g. UPGMA) the phylogenetic
  method is simple enough that we can establish
  mathematically the exact conditions under which
  it will fail
• Parsimony can fail under particular distribution
  of edge lengths
• Known phylogenies
• Best evidence for success of a tree-building
  method would be if it could accurately
  reconstruct a known phylogeny
• Typically, only known phylogenies exist for
  crop plants and laboratory animals and even these
  are often suspect
• Growth of bacteriophage T7 in the presence of
  mutagens allowed comparison of tree building
  methods

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Have we got the true tree?

• Several approaches (continued)
• Simulation
• Provide software with a tree and evolve DNA
  sequences along branches according to some model
• Supply the resulting sequences for a range of
  tree-building methods and determine which (if
  any) recover the original tree
• An advantage of this approach is that we can
  explore the effects of a wide range of parameters
  on the performance of tree reconstruction methods
• A disadvantage is that the models used to
  generate the new sequences may be unrealistic,
  particularly in biasing the model towards a
  particular method

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The Felsenstein Zone
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Congruence

• Congruence is the agreement between estimates of
  phylogeny based on different characters
• If data sets are independent, the probability of
  obtaining similar trees is extremely small
• Conversely, if different data sets give similar
  trees then this suggests that both reflect the
  same underlying cause, namely they reflect the
  same evolutionary history
• Two ways of using congruence
• To validate a method of inference a method that
  constantly recovers similar trees from different
  data sets will be preferred to a method that
  produces different trees from different data sets
• To validate a new source of data does a newly
  sequenced gene contain phylogenetic information?

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Sampling error

• If a data set contains homoplasy then different
  nucleotide sites support different trees
• Which tree(s) a given data set supports depends
  on which characters have been sampled
• Estimates of phylogeny based on samples will be
  accompanied by sample error
• Effects of sampling error evident by comparing
  trees for different mitochondrial genes
• Since there is no recombination, all
  mitochondrial genes share the same evolutionary
  history
• Several different trees were obtained
• Sampling of taxa is also important

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Bootstrapping

• Bootstrapping is a way of calculating sampling
  error without taking repeated samples from the
  population / species under study
• Mimics the technique of repeated sampling from
  the original population by resampling from the
  original sample
• Each resampling is a pseudoreplicate
• Bootstrapping can be applied to phylogenetics by
  taking several pseudoreplicates
• Sampling with replacement gives a new data set
  based on the original sample
• Some sites represented more than once
• Some sites not represented at all
• Pseudoreplicate can be used to construct a new
  tree

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Bootstrapping
1 2 3 4 5 6 7 8 9 Human T C C T T A A A
A Chimp T T C T A T A A A Gorilla T T A C A A T
A A Orang-utan C C A C A A A T A Gibbon C C A C
A A A A T
2 7 7 3 1 7 4 9 6 C A A C T A T A A C A A C T
A T A T A T T A T T C A A A A A A C A C A A A
A A A C A C T A
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Bootstrapping
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What can go wrong?

• Sampling error
• Almost all phylogenies are based on a sample of
  some sort
• Especially true given the vagaries of homoplasy
• Incorrect model of sequence evolution
• All methods make implicit or explicit assumptions
  about evolutionary process
• Example is problem of base composition
• An AT rich part of a gene may be more similar to
  an AT rich part of a different gene purely by
  chance
• Tree structure
• Evolutionary history is not always simple
• Rapid cladogenesis
• Widely differing rates of divergence
• Horizontal gene transfer