Evolution and Phylogenetic Tools

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Evolution and Phylogenetic Tools
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Representing Relationships Among Clades

• Clades are organisms having common ancestor
• Represent as cluster or nodes on a rooted or
  unrooted tree.
• Characteristics of trees
• Topology relationship of clades
• Edge length time
• Root ancestry
• Probably requires an outgroup
• May require additional assumptions, like
  molecular clock

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Characters for Constructing Phylograms

• Heritable traits
• Physical traits
• Behaviors
• Biological sequences
• Proteins
• DNA

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Traditional Characters
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• Four limbs
• (Ray-finned fishes (Amphibians (Lizards Snakes)
  Birds Mammals))

Birds
Lizards
Snakes
Mammals
Amphibians
Ray-finned fishes
Four limbs
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Complications (1)

• Snakes?
• Ancestors of snakes had limbs
• Some snakes have rudimentary limbs
• Walking fish?
• Different embryology
• Highly modified pectoral fins

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Complications (2)

• Selection may cause elimination or reduction of a
  character
• Convergent evolution may impose similar
  characters on separate clades.
• Horizontal gene transfer

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Ideal Phylogenetic Tools

• Methods should be
• Efficient
• Time to compute answer
• Powerful
• Data should not be wasted
• Consistent
• Repeated tests generate the same answer
• Robust
• Tolerant of variability

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What are we looking for out of phylogenetics?

• Find evidence to group organisms into less
  inclusive clades
• Uncover evolutionary mechanism favoring and
  restricting diversity
• Build true evolutionary tree
• Look at sequence diversity for protein or set of
  proteins

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General Considerations

• Compare orthologs among a set of clades
• Different orthologs may generate different trees
• Why
• Common genetic targets for evolutionary biology
• Myoglobin
• 16S ribosomal RNA
• Cytochrome Oxidase (subunit 1)
• CytochromeB

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Statistical Methods for Making Trees

• Maximum parsimony
• UPMGA Unweighted Pair Group Method with
  Arithmetic mean
• Neighbor joining

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Maximum parsimony

• Frequently used with morphological data
• Non-parametric
• Uses matrix of characters and a defined, explicit
  optimality criterion
• Characters divided into states
• Placenta present absent
• Genome membrane-bound nucleus no nucleus
• ProteinX,positionY (any of 20 amino acids)
• Trees evaluated by calculating minimum steps to
  explain distributions of each character
• Tends not to be consistent or effienent

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UPMGA

• Bottom-up clustering pairwise distances
• Often outputs as rooted tree from using
  assumptions like molecular clock

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Neighbor joining

• Highly efficient can be used for larger datasets
  than maximum parsimony
• Bottom-up clustering
• Frequently used for molecular sequence
• Decision at each step favoring least total branch
  length

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Phylogenetic Analysis

• Basic Algorithm
• Align all pairs of sequences to calculate
  distance matrix
• Calculate phylogenetic tree from distance matrix
• Calculate branch lengthsFor the case of
  ClustalW Perform progressive alignments based on
  the phylogenetic tree

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Distance Matrix / Pairwise Alignments

• Fast Approximate Method
• Heuristic
• Scores calculated as
• of k-tuples matches between two sequences
  (gap penalty of gaps)
• k1,2 for aa, 2-4 for dna
• Slow Accurate Method
• Dynamic Programming
• Score
• 1 (( of identities / length of sequences) /
  100))

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Tree Construction

• UPGMA
• Unweighted Pair Group Method by Arithmetic Mean
• Simplest method of tree construction
• Assumes equal rates of mutation along the
  branches
• UPGMA Algorithm
• Definition Node in a tree is called an
  Operational Taxonomic Unit (OTU)
• From distance matrix, cluster pair of OTUs with
  smallest distance, and calculate new distance
• Repeat previous step until clusters converge

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UPGMA

• Cluster pair with smallest distance
• Recalculate distance matrix

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UPGMA

• Calculate new distance using composite OTU(A,B)
• Distance between a simple OTU and a composite OTU
  is the average of the distances between the
  simple OTU and the constituent simple OTUs of the
  composite OTU
• dist (A,B),C (dist A,C dist B,C) / 2 (4
  4) / 2 4dist (A,B),D (dist A,D dist B,D) /
  2 (6 6) / 2 6dist (A,B),E (dist A,E
  dist B,E) / 2 (6 6) / 2 6 dist (A,B),F
  (dist A,F dist B,F) / 2 (8 8) / 2 8

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UPGMA

• Calculate new distance using composite OTU(A,B)
• Distance between a simple OTU and a composite OTU
  is the average of the distances between the
  simple OTU and the constituent simple OTUs of the
  composite OTU

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UPGMA

• Second Iteration

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UPGMA

• Third Iteration

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UPGMA

• Fourth Iteration

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UPGMA

• Fifth Iteration

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Tree Construction

• Neighbor-Joining
• Assumes unequal rates of mutation along each
  branch
• Produces tree with branch lengths proportional to
  estimated divergence along each branch
• Neighbor-Joining Algorithm
• Find pairs of OTUs that minimize total branch
  length at each stage of clustering starting with
  a starlike tree (Minimum-Evolution Tree).

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Neighbor-Joining

• Start with a star tree with N nodes
• Combine the pair with the smallest branch lengths
• Continue until all N-3 interior branches are
  found
• Dij distance between OTUs i and j

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Definitions

• Lab branch lengths between nodes a and b
• Sum of branch lengths

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Definitions

• Assuming 1 2 are any pair of neighbors
• Any pair of OTUs can take the position of 1
  2, N(N-1)/2 waysof choosing pairs
• Choose the pair that gives the smallest branch
  lengths

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Definitions

• Branch length between XY is now
• Removing XY givestwo star-like trees,total
  branch lengths are

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Definitions

• Sum of all branch lengths
• If 12 are closestneighbors, join themto make
  new OTU and recalculate distance

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Definitions

• To find the actual tree branch lengths, Z is OTU
  including all but 1 2

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Neighbor-Joining

• Start with distance matrix below to calculate sum
  of branch lengths using

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Neighbor-Joining

• Calculate sum of branch lengths

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Neighbor-Joining

• Calculate sum of branch lengths

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Neighbor-Joining

• Calculate sum of branch lengths
• Combine OTUs,Estimate branch lengths

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Neighbor-Joining

• Calculate sum of branch lengths
• Recalculate distances

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Neighbor-Joining

• Calculate sum of branch lengths
• Recalculate distances

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Neighbor-Joining

• Based on new distance matrix, recalculate sum of
  branch lengths

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Neighbor-Joining

• Start next iteration, nodes 5 6

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Neighbor-Joining
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Neighbor-Joining

• Next Iteration (1-2) 3

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Neighbor-Joining
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Neighbor-Joining
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Neighbor-Joining

• Final tree

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