1. Applied Bioinformatics Week 8 Jens Allmer

2. Practice I

3. Topic Multiple Sequence Alignment Review –Building an MSA –Editing an MSA Dendrograms Phylogenetic Trees

4. Choosing Sequences How many? –10 – 15 (less than 50 would be good) Seqs should be >30% and <90% identical Prefer seqs of similar length Prefer seqs without internal repeats or extract them

5. Choosing Sequences While choosing your sequences give them good names Some sequences should be well annotated

6. Create an MSA This time use 20 – 50 sequences –From different species Use ClustalW for alignment Most ClustalW servers display a dendrogram Confirm this by using a few of them

7. Gathering Sequences Download the sequences as a FASTA file as well Most programs will support this format

8. Output Formats Many different formats –FASTA widely supported –PdfOnly for printing/ storing/ sharing –PirSimilar to fasta –Msfcommon MSA format –Alnsubset of msf

9. Converting Formats http://bioweb.pasteur.fr/seqanal/interface s/fmtseq.html Names (>…) no longer than 15 characters Different formats maintain different data Converting will introduce the problem of loosing data Make sure to have a master copy

10. Editing Alignments http://www.jalview.org Start the program Choose File – Input Alignment – from Textbox Copy and paste the ClustalW alignment

11. Dendrogram Jalview also allows you to view different types of Dendrograms based on different similarity measures Use Jalview and compare the trees that are constructed based on the different measures

12. End Practice I 15 min break

13. Theory I

14. Phylogeny Sources –Sequences –Clades –Organims Why –Understand evolution –Strain diversity –Epidemiology –Gene predicion

15. Dendrogram http://en.wikipedia.org/wiki/Dendrogram

16. Phylogenetic Tree

17. Tree Terminology All circled elements (e.g.: a) are called node(s) The connections between them are called edge(s) or branch(es) The first node that forms the tree is called root (here abcdef) Terminal nodes that have only one connection are called leaf(ves) (e.g.: a) Unrooted Trees (remove red root)

18. Branch Length Arbitrary Similarity Evolutionary Time

19. Tree types A dendrogram is a broad term for the diagrammatic representation of a phylogenetic tree. A cladogram is a tree formed using cladistic methods. This type of tree only represents a branching pattern, i.e., its branch lengths do not represent time. A phylogram is a phylogenetic tree that explicitly represents number of character changes through its branch lengths. A chronogram is a phylogenetic tree that explicitly represents evolutionary time through its branch lengths.

20. Sequences DNA –Sensitive but quite divergent at longer distances –Use for very closely related organisms cDNA –Still sensitve but less divergent (e.g. introns) –Use for closely related families Protein –Least sensitive but most useful for more distant relationships –Use for distantly related species 16S RNA –Exists in all organisms –Highly conserved

21. Overall Process Get Sequences Construct MSA Compute pairwise distances (for some methods) Build Tree –Topology –Branch Lengths Estimate accuracy, reliability –Build several different trees for that Visualize the tree

22. Computational Tree Formation Distance Methods –Neighbor-Joining –Least-Squares –UPGMA Parsimony –Least number of evolutionary steps Maximum Likelihood –Highest probable tree to fit to the hypothesis is constructed

23. Neighbor Joining Bottom-up clustering method 1.Create distance map 2.Join closest nodes 3.Do (1-2) until fully joined http://en.wikipedia.org/wiki/Neighbor_joining

24. Least Squares Standard approximation approach –Minimizes the sum of the error (squares) Example PGLS –Phylogenetic Generalized Least Squares –Needs additional data (traits) http://www.dynamicgeometry.com/General_Resources/Advanced_Sketch_Gallery/Other_Explorations/Statistics_Collection/Least_Squares.html

25. UPGMA Unweighted Pair Group Method with Arithmetic Mean –Aglomerative hierarchial clustering method –Assumes constant rate of evolution

26. Similarity Measures Sequence –Number of different positions –Weighted differences Substitution Matrices –Pairwise alignments NW, SW,.. Additional measurements or knowlege –Traits Parsimony –Number of changes for tree paths

27. Tree Accuracy Bootstrapping –Resample –Recompute –Do many times –Compare results http://www.sciencedirect.com/science/article/pii/S0191814107000156

28. http://goergen.deviantart.com/art/Magic-Forrest-Wallpaper-139108299

29. End Theory I Mindmap Break

30. Practice II

31. Where to get Trees Most servers that allow for MSA will also provide at least the guide tree which was used to construct the alignment If that’s all you are interested in you don’t need to go any further

32. Edit your MSA Remove blocks consisting of mostly gaps (using JalView) Remove N- and C-termini if not conserved well

33. Easy Tree www.ebi.ac.uk/clustalw/ Paste your alignment Select a tree type Other options need to be set (see right) Press run Make a screen shot You can paste it where needed

34. Phylip (More elaborate tree) http://bioweb.pasteur.fr/seqanal/phylogeny/ phylip-uk.html Choose protdist from the page Paste the MSA Bootstrapping e.g.:

35. Phylip Run the query Click further analysis

36. Click Run Select full screen view There is your tree

37. Ugly Tree Let’s face it the tree is quite ugly http:// iubio.bio.indiana.edu/treeapp/treeprint-form.html Select the consense.outtree from the previous website and paste it into the box Select submit to create the tree Play around with the formats and settings

38. Tree Topologies

41. Other Resources http://en.wikipedia.org/wiki/List_of_phylog enetics_software http://itol.embl.de/