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Phylogenetic trees. 2 Phylogeny is the inference of evolutionary relationships. Traditionally, phylogeny relied on the comparison of morphological features.

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Presentation on theme: "Phylogenetic trees. 2 Phylogeny is the inference of evolutionary relationships. Traditionally, phylogeny relied on the comparison of morphological features."— Presentation transcript:

1 Phylogenetic trees

2 2 Phylogeny is the inference of evolutionary relationships. Traditionally, phylogeny relied on the comparison of morphological features between organisms. Today, molecular sequence data are mainly used for phylogenetic analyses. One tree of life A sketch Darwin made soon after returning from his voyage on HMS Beagle (1831–36) showed his thinking about the diversification of species from a single stock (see Figure, overleaf). This branching, extended by the concept of common descent,

3 3 Haeckel (1879)Pace (2001)

4 4 Molecular phylogeny uses trees to depict evolutionary relationships among organisms. These trees are based upon DNA and protein sequence data Human Chimpanzee Gorilla Orangutan Gorilla Chimpanzee Orangutan Human Molecular analysis: Chimpanzee is related more closely to human than the gorilla Pre-Molecular analysis: The great apes (chimpanzee, Gorilla & orangutan) Separate from the human

5 5 What can we learn from phylogenetics tree?

6 Was the extinct quagga more like a zebra or a horse? 1. Determine the closest relatives of one organism in which we are interested

7 7 Which species are closest to Human? Human Chimpanzee Gorilla Orangut an Gorilla Chimpanzee Orangutan Human

8 8 Example Metagenomics A new field in genomics aims the study the genomes recovered from environmental samples. A powerful tool to access the wealthy biodiversity of native environmental samples 2. Help to find the relationship between the species and identify new species

9 10 6 cells/ ml seawater 10 7 virus particles/ ml seawater >99% uncultivated microbes

10 10 From : “The Sorcerer II Global Ocean Sampling Expedition: Metagenomic Characterization of Viruses within Aquatic Microbial Samples” Williamson et al, PLOS ONE 2008

11 3. Discover a function of an unknown gene or protein 11 RBP1_HS RBP2_pig RBP_RAT ALP_HS ALPEC_BV ALPA1_RAT ECBLC Hypothetical protein X

12 12 Relationships can be represented by Phylogenetic Tree or Dendrogram A B C D E F

13 13 Phylogenetic Tree Terminology Graph composed of nodes & branches Each branch connects two adjacent nodes A B C D E F R

14 14 Rooted tree Human Chimp Chicken Gorilla Human Chimp Chicken Gorilla Un-rooted tree Phylogenetic Tree Terminology

15 15 Rooted vs. unrooted trees 1 2 3 31 2

16 16 How can we build a tree with molecular data? -Trees based on DNA sequence (rRNA) -Trees based on Protein sequences

17 17 Questions: Can DNA and proteins from the same gene produce different trees ? Can different genes have different evolutionary history ? Can different regions of the same gene produce different trees ?

18 18 Approach 1 - Distance methods Two steps : –Compute a distance between any two sequences from the MSA. –Find the tree that agrees most with the distance table. Algorithms : -Neighbor joining Approach 2 - State methods Algorithms: –Maximum parsimony (MP) –Maximum likelihood (ML)

19 Basic algorithm for constructing a rooted tree (UPGMA) Assumption: Divergence of sequences is assumed to occur at a constant rate  Distance to root is equal a d c b

20 20 abcd a0875 b8039 c7308 d5980 a d c b Basic Algorithm of Neighbor Joining (Unrooted tree) starting from a start diagram Initial star diagramDistance matrix

21 21 abcd a0875 b8039 c7308 d5980 a d c b Choose the nodes with the shortest distance and fuse them. Selection step

22 22 a Then recalculate the distance between the rest of the remaining sequences (a and d) to the new node (e) and remove the fused nodes from the table. d c,b e a ade a056 d507 e670 D (EA) = (D(AC)+ D(AB)-D(CB))/2 Next Step D (ED) = (D(DC)+ D(DB)-D(CB))/2 abcd a0875 b8039 c7308 d5980

23 23 In order to get a tree, un-fuse c and b by calculating their distance to the new node (e) !!!The distances Dce and Dde are calculated independently (the formula will be given in the tirgul) d c e a ade a056 d507 e670 b D ce D de Next Step

24 24 a a,d c e ade a056 d507 e670 b D ce D de f Next… We want to fuse the next closest nodes

25 25 a c e fe f04 e40 b D af D de f d D ce D bf Finally D (EF) = (D(EA)+ D(ED)-D(AD))/2 We need to calculate the distance between e and f

26 26 d c,b e a a,d c e b D ce D de f d a c e b D af D de f D ce D bf 12 3

27 27 IMPORTANT !!! Usually we don’t assume a constant mutation rate and in order to choose the nodes to fuse we have to calculate the relative distance matrix (Mij) representing the relative distance of each node to all other nodes

28 28 EXAMPLE A B C D E B 5 C 4 7 D 7 10 7 E 6 9 6 5 F 8 11 8 9 8 A B C D E B -13 C -11 D -10 -10.5 E -10 -11-13 F -10.5 -11 -11.5 Original distance MatrixRelative Distance Matrix (Mij) The Mij Table is used only to choose the closest pairs not for calculating the distances

29 29 Neighbor Joining (NJ) Reconstructs an unrooted tree Calculates branch lengths Based on pairwise distances In each stage, the two nearest nodes of the tree are chosen and defined as neighbors in our tree. This is done recursively until all of the nodes are paired together.

30 30 Advantages -It is fast and thus suited for large datasets -Permits lineages with largely different branch lengths Disadvantages - Sequence information is reduced - Gives only one possible tree Advantages and disadvantages of the neighbor-joining method

31 Problems with phylogenetic trees - Using different regions from a same alignment may produce different trees.

32 Problems with phylogenetic trees

33 Bacillus E.coli Pseudomonas Salmonella Aeromonas Lechevaliera Burkholderias Problems with phylogenetic trees

34 It is wrong to produce a tree based on distance values of the whole alignment What to do?: use bootstrap

35 35 A.We create new data sets by sampling N positions with replacement. B.We generate 100 - 1000 such pseudo-data sets. C.For each such data set we reconstruct a tree, using the same method. D.We note the agreement between the tree reconstructed from the pseudo-data set to the original tree. Note: we do not change the number of sequences ! Bootstrapping

36 Bootstrapped tree Less reliable Branch Highly reliable branch

37 37 Tools for tree reconstruction CLUSTALX (NJ method) Phylip -PHYLogeny Inference PackagePhylip –includes parsimony, distance matrix, and likelihood methods, including bootstrapping. Phyml (maximum likelihood method)Phyml MEGA (Molecular Evolution Genomic Analysis)MEGA More phylogeny programsphylogeny programs

38 38 362

39 39 http://www.phylogeny.fr


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