Applied Bioinformatics Week 8 Jens Allmer

Theory I

Phylogeny Sources –Sequences –Clades –Organisms Why –Understand evolution –Strain diversity –Epidemiology –Gene predicion

? globin plants Ath-g analogs

Dendrogram

Phylogenetic Tree

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)

Branch Length Arbitrary Similarity Evolutionary Time

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.

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

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

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

Neighbor Joining Bottom-up clustering method 1.Create distance map 2.Join closest nodes 3.Do (1-2) until fully joined

Least Squares Standard approximation approach –Minimizes the sum of the error (squares) Example PGLS –Phylogenetic Generalized Least Squares –Needs additional data (traits)

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

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

Tree Accuracy Bootstrapping –Resample –Recompute –Do many times –Compare results

End Theory I Mindmap Break

Practice I

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

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

Easy Tree 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

Phylip (More elaborate tree) phylip-uk.html Choose protdist from the page Paste the MSA Bootstrapping e.g.:

Phylip Run the query Click further analysis

Click Run Select full screen view There is your tree

Ugly Tree Let’s face it the tree is quite ugly 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

Tree Topologies

Other Resources enetics_software

MSA Try all the above and compare the resulting MSAs

Editing Alignments Start the applet Choose File – Input Alignment – from Textbox Copy and paste the ClustalW alignment

Playtime Be creative Explore the functions For saving you need to install locally JAVA applets are not allowed to save to your computer