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Intro to Phylogenetic Trees Lecture 5

Intro to Phylogenetic Trees Lecture 5. Sections 7.1, 7.2, in Durbin et al. Chapter 17 in Gusfield Slides by Shlomo Moran. Slight modifications by Benny Chor. Evolution. Evolution of new organisms is driven by Diversity

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Intro to Phylogenetic Trees Lecture 5

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  1. Intro to Phylogenetic TreesLecture 5 Sections 7.1, 7.2, in Durbin et al. Chapter 17 in Gusfield Slides by Shlomo Moran. Slight modifications by Benny Chor .

  2. Evolution Evolution of new organisms is driven by • Diversity • Different individuals carry different variants of the same basic blue print • Mutations • The DNA sequence can be changed due to single base changes, deletion/insertion of DNA segments, etc. • Selection bias

  3. The Tree of Life Source: Alberts et al

  4. Tree of life- a better picture D’après Ernst Haeckel, 1891

  5. Primate evolution A phylogeny is a tree that describes the sequence of speciation events that lead to the forming of a set of current day species; also called a phylogenetic tree.

  6. Historical Note • Until mid 1950’s phylogenies were constructed by experts based on their opinion (subjective criteria) • Since then, focus on objective criteria for constructing phylogenetic trees • Thousands of articles in the last decades • Important for many aspects of biology • Classification • Understanding biological mechanisms

  7. Morphological vs. Molecular • Classical phylogenetic analysis: morphological features: number of legs, lengths of legs, etc. • Modern biological methods allow to use molecular features • Gene sequences • Protein sequences • Analysis based on homologous sequences (e.g., globins) in different species

  8. Morphological topology Bonobo Chimpanzee Man Gorilla Sumatran orangutan Bornean orangutan Common gibbon Barbary ape Baboon White-fronted capuchin Slow loris Tree shrew Japanese pipistrelle Long-tailed bat Jamaican fruit-eating bat Horseshoe bat Little red flying fox Ryukyu flying fox Mouse Rat Glires Vole Cane-rat Guinea pig Squirrel Dormouse Rabbit Pika Pig Hippopotamus Sheep Cow Alpaca Blue whale Fin whale Sperm whale Donkey Horse Indian rhino White rhino Elephant Carnivora Aardvark Grey seal Harbor seal Dog Cat Asiatic shrew Insectivora Long-clawed shrew Small Madagascar hedgehog Hedgehog Gymnure Mole Armadillo Xenarthra Bandicoot Wallaroo Opossum Platypus (Based on Mc Kenna and Bell, 1997) Archonta Ungulata

  9. From sequences to a phylogenetic tree Rat QEPGGLVVPPTDA Rabbit QEPGGMVVPPTDA Gorilla QEPGGLVVPPTDA Cat REPGGLVVPPTEG There are many possible types of sequences to use (e.g. Mitochondrial vs Nuclear proteins).

  10. Perissodactyla Donkey Horse Carnivora Indian rhino White rhino Grey seal Harbor seal Dog Cetartiodactyla Cat Blue whale Fin whale Sperm whale Hippopotamus Sheep Cow Chiroptera Alpaca Pig Little red flying fox Ryukyu flying fox Moles+Shrews Horseshoe bat Japanese pipistrelle Long-tailed bat Afrotheria Jamaican fruit-eating bat Asiatic shrew Long-clawed shrew Mole Small Madagascar hedgehog Xenarthra Aardvark Elephant Armadillo Rabbit Lagomorpha + Scandentia Pika Tree shrew Bonobo Chimpanzee Man Gorilla Sumatran orangutan Primates Bornean orangutan Common gibbon Barbary ape Baboon White-fronted capuchin Rodentia 1 Slow loris Squirrel Dormouse Cane-rat Rodentia 2 Guinea pig Mouse Rat Vole Hedgehog Hedgehogs Gymnure Bandicoot Wallaroo Opossum Platypus Mitochondrial topology (Based on Pupko et al.,)

  11. Nuclear topology Chiroptera Round Eared Bat Eulipotyphla Flying Fox Hedgehog Pholidota Mole Pangolin Whale 1 Cetartiodactyla Hippo Cow Carnivora Pig Cat Dog Perissodactyla Horse Rhino Glires Rat Capybara 2 Scandentia+ Dermoptera Rabbit Flying Lemur Tree Shrew 3 Human Primate Galago Sloth Xenarthra 4 Hyrax Dugong Elephant Afrotheria Aardvark Elephant Shrew Opossum Kangaroo (Based on Pupko et al. slide) (tree by Madsenl)

  12. Theory of Evolution • Basic idea • speciation events lead to creation of different species. • Speciation caused by physical separation into groups where different genetic variants become dominant • Any two species share a (possibly distant) common ancestor

  13. Aardvark Bison Chimp Dog Elephant Phylogenenetic trees • Leafs - current day species • Nodes - hypothetical most recent common ancestors • Edges length - “time” from one speciation to the next

  14. Types of Trees A natural model to consider is that of rooted trees Common Ancestor

  15. Types of trees Unrooted tree represents the same phylogeny without the root node Depending on the model, data from current day species does not distinguish between different placements of the root.

  16. Tree a Tree b Rooted versus unrooted trees Tree c b a c Represents all three rooted trees

  17. Positioning Roots in Unrooted Trees • We can estimate the position of the root by introducing an outgroup: • a set of species that are definitely distant from all the species of interest Proposed root Falcon Aardvark Bison Chimp Dog Elephant

  18. Type of Data • Distance-based • Input is a matrix of distances between species • Can be fraction of residue they disagree on, or alignment score between them, or … • Character-based • Examine each character (e.g., residue) separately

  19. Two Methods of Tree Construction • Distance- A weighted tree that realizes the distances between the objects. • Character Based – A tree that optimizes an objective function based on all characters in input sequences (major methods are parsimony and likelihood). We start with distance based methods, considering the following question: Given a set of species (leaves in a supposed tree), and distances between them – construct a phylogeny which best “fits” the distances.

  20. Exact solution: Additive sets Given a set M of L objects with an L×Ldistance matrix: • d(i,i)=0, and for i≠j, d(i,j)>0 • d(i,j)=d(j,i). • For all i,j,k it holds that d(i,k) ≤ d(i,j)+d(j,k). Can we construct a weighted tree which realizes these distances?

  21. Additive sets (cont) We say that the set M with L objects is additive if there is a tree T, L of its nodes correspond to the L objects, with positive weights on the edges, such that for all i,j, d(i,j) = dT(i,j), the length of the path from i to j in T. Note: Sometimes the tree is required to be binary, and then the edge weights are required to be non-negative.

  22. k c b j m a i Three objects sets always additive: For L=3: There is always a (unique) tree with one internal node. Thus

  23. How about four objects? L=4: Not all sets with 4 objects are additive: eg, there is no tree which realizes the below distances.

  24. k i l j The Four Points Condition Theorem: A set M of L objectsis additive iff any subset of four objects can be labeled i,j,k,l so that: d(i,k) + d(j,l) = d(i,l) +d(k,j) ≥ d(i,j) + d(k,l) We call {{i,j},{k,l}} the “split” of {i,j,k,l}. Proof: Additivity 4 Points Condition: By the figure...

  25. 4P Condition Additivity: Induction on the number of objects, L. For L≤ 3 the condition is empty and tree exists. Consider L=4. B = d(i,k) +d(j,l) = d(i,l) +d(j,k) ≥ d(i,j) + d(k,l) = A Let y = (B – A)/2 ≥ 0. Then the tree should look as follows: We have to find the distances a,b, c and f. k c f l n y b a m i j

  26. Tree construction for L=4 • Construct the tree by the given distances as follows: • Construct a tree for {i, j,k}, with internal vertex m • Add vertex n ,d(m,n) = y • Add edge (n,l), c+f=d(k,l) l k f f f f c Remains to prove: d(i,l) = dT(i,l) d(j,l) = dT(j,l) n n n n y b j m a i

  27. l k f c n y b j m a i Proof for L=4 By the 4 points condition and the definition of y: d(i,l) = d(i,j) + d(k,l) +2y -d(k,j) = a + y + f = dT(i,l) (the middle equality holds since d(i,j), d(k,l) and d(k,j) are realized by the tree) d(j,l) = dT(j,l) is proved similarly.

  28. L cij bij j aij mij i Induction step for L>4: • Remove Object L from the set • By induction, there is a tree, T’, for {1,2,…,L-1}. • For each pair of labeled nodes (i,j) in T’, let aij, bij, cij be defined by the following figure:

  29. L cij bij j aij mij T’ i Induction step: • Pick i and j that minimize cij. • T is constructed by adding L (and possibly mij) to T’, as in the figure. Then d(i,L) = dT(i,L) and d(j,L) = dT(j,L) Remains to prove: For each k ≠ i,j: d(k,L) = dT(k,L).

  30. L cij k bij j mij n aij T’ i Induction step (cont.) Let k ≠i,j be an arbitrary node in T’, and let n be the branching point of k in the path from i to j. By the minimality of cij , {{i,j},{k,L}} is not a “split” of {i,j,k,L}. So assume WLOG that {{i,L},{j,k}} is a “split” of {i,j, k,L}.

  31. L cij k bij j n mij aij T’ i Induction step (end) Since {{i,L},{j,k}} is a split, by the 4 points condition d(L,k) = d(i,k) + d(L,j) - d(i,j) d(i,k) = dT(i,k) and d(i,j) = dT(i,j) by induction, and d(L,j) = dT(L,j) by the construction. Hence d(L,k) = dT(L,k). QED

  32. Dangers of Paralogs If we happen to consider genes 1A, 2B, and 3A of species 1,2,3, we get a wrong tree that does not represent the phylogeny of the host species of the given sequences because duplication does not create new species. Gene Duplication S S S Speciation events 2B 1B 3A 3B 2A 1A In the sequel we assume all given sequences are orthologs.

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