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Evolutionary Analysis

Evolutionary Analysis. Tara Harmer Luke The Richard Stockton College of NJ. Tree. Mathematical structure Model evolutionary history. Taxon 1. Taxon 2. Taxon 3. Taxon 4. Taxon 5. Taxon 6. Taxon 1. Outgroup. Taxon 2. Root. Sister taxa. Taxon 3. Branch. Taxon 4. Node. Taxon 5.

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Evolutionary Analysis

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  1. Evolutionary Analysis • Tara Harmer Luke • The Richard Stockton College of NJ

  2. Tree • Mathematical structure • Model evolutionary history

  3. Taxon 1 Taxon 2 Taxon 3 Taxon 4 Taxon 5 Taxon 6

  4. Taxon 1 Outgroup Taxon 2 Root Sister taxa Taxon 3 Branch Taxon 4 Node Taxon 5 Polytomy (more than one branch emerging from one node) Taxon 6 Tip

  5. (a) The astragalus is a synapomorphy that identifies artiodactyls as a monophyletic group. (b) If whales are related to hippos, then two changes occurred in the astragalus. ARTIODACTYLS Camel Whale Gain of pulley- shaped astragalus ARTIODACTYLS Peccary Camel Pig Peccary Gain of pulley- shaped astragalus Hippo Pig Whale Hippo Loss of pulley- shaped astragalus Astragalus (ankle bone) Deer Deer Cow Cow (c) Data on the presence and absence of SINE genes support the close relationship between whales and hippos. Locus 1 = gene present 0 = gene absent ? = still undetermined Cow Deer Whale Whales and hippos share four unique SINE genes (4, 5, 6, and 7) Hippo Pig Peccary Camel

  6. Phylogenetic Tree • shows ancestor-descendent relationships among populations or species • clarifies evolutionary relationships

  7. Root • Ancestor of all sequences on tree

  8. Taxon 1 Outgroup Taxon 2 Root Sister taxa Taxon 3 Branch Taxon 4 Node Taxon 5 Polytomy (more than one branch emerging from one node) Taxon 6 Tip

  9. 2 4 5 1 2 3 6 3 1 4 5 6 (a) (b) (c) 1 6 5 4 3 2

  10. 2 4 5 1 2 3 6 3 1 4 5 6 (a) (b) (c) 1 6 5 = = 4 3 2

  11. Types of Trees • Rooted • Unrooted

  12. Rooted Trees • Node identified as root, from which all other nodes descend • Have direction corresponding to evolutionary time

  13. Taxon 1 Outgroup Taxon 2 Root Sister taxa Taxon 3 Branch Taxon 4 Node Taxon 5 Polytomy (more than one branch emerging from one node) Taxon 6 Tip

  14. Unrooted Trees • Lacks root • Does not specify evolutionary relationships • Nothing about ancestors and descendents

  15. Unrooted Trees • Lacks root • Does not specify evolutionary relationships • Nothing about ancestors and descendents • Many tree-building programs generate unrooted trees!

  16. Number of possible phylogenetic trees

  17. Types of Trees • Cladogram • Phylogram

  18. Cladogram

  19. Cladogram • Relative recency of common ancestry

  20. Cladogram

  21. Cladogram • Relative recency of common ancestry • Does not show amount of evolutionary change

  22. Phylogram

  23. Phylogram • Also contains branch lengths • Numbers associated with branches • Amount of evolutionary change

  24. Phylogram

  25. Cladogram Phylogram

  26. Constructing a Tree • Construct multiple sequence alignment • Determine Tree reconstruction method • Build Tree • Evaluate Tree

  27. Constructing a Tree • Construct multiple sequence alignment • Determine Tree reconstruction method • Build Tree • Evaluate Tree

  28. Methods for Tree Reconstruction • Distance methods • Discrete methods

  29. Distance methods • measures sequence dissimilarity • UPGMA • Neighbor Joining (NJ)

  30. UPGMA(Unweighted Pair-Group Method with Arithmetic Mean) • Assumes constant rate of evolution • Sequential clustering algorithm

  31. Neighbor Joining (NJ) • also uses distance matrix • Sequentially find neighbors that minimize length of tree

  32. Neighbor Joining (NJ) • also uses distance matrix • Sequentially find neighbors that minimize length of tree A H B G C F D E

  33. Neighbor Joining (NJ) • also uses distance matrix • Sequentially find neighbors that minimize length of tree A A H H B B I G G C C F D F D E E

  34. Discrete methods • Maximum parsimony • Maximum likelihood

  35. Maximum Parsimony

  36. Maximum Parsimony Possible Trees: ((1,2),(3,4)) ((1,3),(2,4)) ((1,4),(2,3))

  37. Newick Format • represented in linear form by nested parentheses • how computers store trees A C B D E (((A,C)B)(D,E))

  38. Maximum Parsimony Possible Trees: ((1,2),(3,4)) ((1,3),(2,4)) ((1,4),(2,3))

  39. Maximum Parsimony 1 2 3 4

  40. Maximum Parsimony 1 + 1 + 2 + 1 + 0 =5 1 2 3 4

  41. Maximum Parsimony 2 + 2 + 1 + 1 + 0 =6 1 3 2 4

  42. Maximum Parsimony 1 3 2 4 1 2 3 4 Tree length: 5 6

  43. Maximum Parsimony 1 + 1 + 2 + 1 + 0 =5 1 2 3 4

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