Constructing Phylogenetic Trees. Gloria Rendon SC 11 - Education June, 2011

Transcription

1 Constructing Phylogenetic Trees Gloria Rendon SC 11 - Education June, 2011

2 Phylogenetic Tree Reconstruction PTR IN THE PAST: much of this work was done by making observations of anatomy and physiology and with comparisons in fossil records NOW: techniques have been developed in molecular biology for performing such evolutionary comparisons at the molecular level using computational tools.

3 Phylogenetic Tree Reconstruction is an (Inference) Problem Given n species m characters For each species, the values for all characters is known Goal: a fully labeled phylogenetic tree that best explains the given data (i.e. maximize a target function (score)) Assumptions: Characters are mutually independent After two species diverged, their further evolution is independent of each other Solution: exhaustive search of the tree space to find the best possible solution is unfeasible. Heuristic approach to finding an approximate solution that is close enough to the best solution.

4 Desired Properties of the data used in (Species) Phylogenetic Tree Reconstruction An ideal choice is a genomic region that: appears exactly once in every species has evolutionary history identical to that of the species exhibits a rate of change that is both fast enough to distinguish between closely related species and slow enough so that they resemble each other on any pair of distantly related species Small ribosomal subunit rrna, called 16s ribosomal RNA in prokaryotes and 18s ribosomal RNA in eukaryotes, has been found to be the best genomic segment for this type of analysis.

5 Many Possible Phylotrees The number of possible rooted phylogenetic trees that can be constructed with n sequences grows exponentially. (2n)!/n!*(n+1)! Where n is the number of nodes (internal and leaf nodes) For example, with five sequences and four internal nodes (so n=9); we have 4,862 possibilities; 98 of which are structurally different, seven of them are illustrated here.

6 Many Possible Phylotrees Several computational tools can produce more than one phylotree for a given set of sequences. Human expertise is usually necessary to make a judgment call on the most likely phylogeny for a given set of sequences. Lacking that, we can use bootstrapping as a second-best choice.

7 Is the phylotree correct? Bootstrapping techniques have been developed to test if not the correctness at least the reliability of the phylogeny calculated by a program Bootstrap quantifies the degree of support within the data for a particular branch given the evolutionary model and tree reconstruction method

8 Basic Procedure for building biological trees: ONE TWIG AT A TIME 1.Start with any TWO sequences and add the rest of the sequences one at a time. 2. Each new sequence becomes a leaf of the tree (meaning, nothing further can be attached to this point). 3. Use a particular model of evolution and method to choose the place where the new sequence ought to go, It should be closer to the sequence in the tree that it is most similar to than to any other sequence already in the tree. 4. Repeat steps 2 and 3 until all sequences have been inserted into the tree 5. Stop

9 Basic Procedure for building biological trees: ONE TWIG AT A TIME 1.Start with any TWO sequences and add the rest of the sequences one at a time. 2. Each new sequence becomes a leaf of the tree (meaning, nothing further can be attached to this point). 3. Use a particular model of evolution and method to choose the place where the new sequence ought to go, It should be closer to the sequence in the tree that it is most similar to than to any other sequence already in the tree. 4. Repeat steps 2 and 3 until all sequences have been inserted into the tree 5. Stop

10 Choice of a PTR Method Two broad categories exist: distance-based methods and sequence-based methods Distance-based methods first compute pairwise distances from the sequences and then use those distances to calculate the phylotree Sequence-based methods use the MSA of all the sequences and search for the best tree according to optimality criterion defined by a model

11 Properties of the PRT Methods Method Type of method Tree type Single tree? Tree score? Tree test? UPGMA distance ultrametric Yes No No Neighbor joining distance additive Yes No No Fitch-Margolish distance additive Yes No No Minimum evolution distance additive No Yes Yes Maximum parsimony sequence additive No Yes Yes Maximum likelihood sequence additive No Yes Yes Bayesian sequence additive No Yes Yes

12 Choice of a Model of Evolution Model Base composition R=1? Identical transition rates? Identical transversion rates? Reference JC 1:1:1:1 No Yes Yes Jukes and Cantor (1969) F81 Variable No Yes Yes Felsenstein(1981) K2P 1:1:1:1 Yes Yes Yes Kimura(1980) HKY85 Variable Yes No No Hasegawa et al.(1985) TN Variable Yes No Yes Tamura and Nei(1993) K3P Variable Yes No Yes Kimura(1981) SYM 1:1:1:1 Yes No No Zharkikh(1994) GTR Variable Yes No No Rodriguez et al.(1990)

13 Which Model to Use?

14 Illustrating the procedure manually with a toy example 1.Start with any TWO sequences and add the rest of the sequences one at a time. 2. Each new sequence becomes a leaf of the tree (meaning, nothing further can be attached to this point). 3. Use a particular model of evolution and method to choose the place where the new sequence ought to go, It should be closer to the sequence in the tree that it is most similar to than to any other sequence already in the tree. 4. Repeat steps 2 and 3 until all sequences have been inserted into the tree 5. Stop

15 Illustrating the procedure manually with a toy example 1. Calculate a multiple sequence alignment with all the sequences that you want in your tree. This step is not manually done. Sequence Sequence Alignment Length Name A sequence alignment is a way of arranging the sequences of DNA, RNA, or proteins to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences.

16 Illustrating the procedure manually with a toy example 1. Calculate a multiple sequence alignment with all the sequences that you want in your tree. This step is not manually done. Once the alignment is calculated; the similarity between any pair of sequences is established and phylogenetic relationships can be predicted. For example, here, the smaller the score in a cell, the higher the similarity is for the pair of sequences

17 For this toy example we start with the alignment results start with 2 sequences, for instance seq3 and seq4 add seq1 If next to seq3, consider Score(seq1,seq3)=51 If next to seq4, consider Score(seq1,seq4)=51 So seq1 goes in another branch add seq2 If next to seq1, consider Score(seq2,seq1)=48 If next to seq3, consider Score(seq2,seq3)=66 So seq2 goes in seq1 s branch add seq5 If next to seq1, consider Score(seq5,seq1)=70 If next to seq2, consider Score(seq5,seq2)=85 So, seq5 goes in another branch

18 Using tools to reconstruct a Phylogenetic Tree

19 Example2: Phylogeny of Proteobacteria 16s ribosomal RNA sequences from 38 species in these families: alphaproteobacteria, betaproteobacteria, gammaproteobacteria, deltaproteobacteria, and epsilonproteobacteria Tree 1: generated using ML and GTR Tree 2: generated using ML Tree 3: generated using UPGMA and JR correction, removing gaps Tree 4: generated using UPGMA and JR correction, no gaps were removed Tree 5: condense Tree 3 obtained by a bootstrap analysis; branches with bootstrap value below 75% have been contracted

20 Tree1: Delta and Epsilon branched off early from the rest of the family Tree2: Gamma and Beta branched off early from the rest of the family

21 Trees 3 and 4 calculated with UPGMA, a distance-based method, have the branching off of Epsilon happening earlier than in Trees 1 and 2, which were calculated using maximum likelihood.

22 As a result of bootstrapping, we may end up with a nonbinary tree like in this case.

23 Where are the Phylogeny Tools in the Mobyle Web Server?

24 Exercise 1 Phylotree of the eight imaginary species We are going to revisit the example we used in the previous lesson. Up until this point, we have aligned the sequences of the eight imaginary species of the solar system with a multiple sequence alignment tool: ClustalW. Let us go back to the results of ClustalW for the set containing the sequences of the eight imaginary species and use those results to reconstruct a likely phylogeny of the species. Since it is possible to end up with different phylotrees; we are going to actually tweak the parameters of the tool and see what phylotree it produces each time. In real life we would need to be guided by the expert opinion of a taxonomist as to which tree is the most likely phylogeny for the species.

25 Exercise 1 Phylotree of the eight imaginary species Open the browser again and go back to the results of ClustalW for the set containing the sequences of the eight imaginary species Click on the pull-down menu next to the button further analysis located in the alignment frame Select PUZZLE from the pull down menu first; Then click on further analysis [the alignment is loaded into the input frame of the puzzle tool] Note: PUZZLE is a phylogenetic tool that uses ML and NJ; suitable for large trees.

26 Exercise 1 Phylotree of the eight imaginary species [the alignment is loaded into the input frame of the puzzle tool] How can you check? The name of the current tool should read Tree-Puzzle.. The frame for alignment file should contain the result that ClustalW produced. Leave all the other parameters unchanged with their default values and click on RUN

27 Exercise 1 Phylotree of the eight imaginary species The output page of PUZZLE consists of several frames as indicated in this figure with numbers Is the output file with everything 2. Is the output tree in Newick format 3. Is the output distance file 4. Is the standard output report. We are just interested in the tree. Click on view with archaeopteryx to see the tree in graphical form

28 Exercise 1 Phylotree of the eight imaginary species Close the window that shows the tree. Now, we are going to repeat the same steps changing only the parameters of the PUZZLE tool Go back to the ClustalW results page and start all over. When you get to the puzzle page; scroll down to the Quartet puzzling options and change AT LEAST the value of the last entry that reads Display as outgroup? N N should be a number [1-8]; the default value is 1 Then press RUN and check the tree

29 Exercise 1 Phylotree of the eight imaginary species Now, let s try lvb, a phylogeny tool that uses parsimony to calculate trees from dna sequences. Go back to the ClustalW results page and start all over. From the pull-down menu close to the further analysis button; choose lvb. Then click on further analysis [wait for the results to get loaded onto the input box of the lvb page] Then press RUN and check the tree.

30 Exercise 1 Phylotree of the eight imaginary species Now, let s try quicktree, a phylogeny tool that uses least-squre distances to calculate trees. Go back to the ClustalW results page and start all over. From the pull-down menu close to the further analysis button; choose quicktree. Then click on further analysis [wait for the results to get loaded onto the input box of the quicktree page] Then press RUN and check the tree.

31 Exercise 1 Phylotree of the eight imaginary species All three PRT programs produced ONE unrooted phylogenetic tree. Lvb s tree has NO branch length estimates.

32 Exercise 2: Produce the phylogeny of the three kingdom of Carl Woese The first kingdom, Eukaryotes, is made up of sequences 1-3 The second kingdom, bacteria, is made up of sequences 4-9 The third kingdom, Archaea, is made up of sequences 10-13

33 Exercise 2: Produce the phylogeny of the three kingdom of Carl Woese 1.Open the browser select align/multiple/mafft 2. Upload the file called woese.fasta located in the exercise folder 3. Run the mafft program to obtain the multiple sequence alignment 4.Click on the pull-down menu next to the button further analysis located in the alignment frame 3.Select PUZZLE from the pull down menu first; then click on further analysis [the alignment is loaded into the input frame of the PUZZLE tool] 4.Click on RUN [wait until the result is available] 5.To view the resulting phylogenetic tree, scroll down to the frame named output tree and then click on view with archaeopteryx

34 Exercise 2: Produce the phylogeny of the three kingdom of Carl Woese 6. Repeat steps 3-5 using lvb instead of PUZZLE to obtain a tree using parsimony 7. Repeat steps 3-5 using Quicktree instead of PUZZLE to obtain a tree using distances. 8. Compare the trees Q:The dataset contains a sequence that proves to be a challenge for computational PTR tools, which sequence is that? Q:Are the trees identical? If not, which tree seems to be more accurate?

35 Exercise 2: Produce the phylogeny of the three kingdom of Carl Woese

36 Exercise 3: Produce the phylogeny of the Eukaryotic species 1.Open the browser select align/multiple/mafft 2. Upload the file called 18s.rRNA.seqs.fasta located in the exercise folder 3. Run the mafft program to obtain the multiple sequence alignment 4.Click on the pull-down menu next to the button further analysis located in the alignment frame 3.Select PUZZLE from the pull down menu first; then click on further analysis [the alignment is loaded into the input frame of the PUZZLE tool] 4.Click on RUN [wait until the result is available] 5.To view the resulting phylogenetic tree, scroll down to the frame named output tree and then click on view with archaeopteryx

37 Additional Readings Enumerating binary trees: Nei, M. and Kumar, S. Molecular evolution and phylogenetics. Oxford University Press Chapter 5 Bodoroski, M and Ekisheva, S. Problems and solutions in biological sequence analysis. Cambridge University Press, Chapter 7 Gusfield, D. Algorithms on strings, trees, and sequences: computer science and computational biology. Cambridge University Press, Chapter 17 Pevsner, J. Bioinformatics and functional genomics. Hoboken, N.J. : Wiley- Blackwell, pp Tateno, Y, M. Nei, AND F. Tajima. Accuracy of estimated phylogenetic trees from molecular data. J Mol Evol. 1982;18(6):