# Introduction to Bioinformatics AS Laboratory Assignment 6

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4 only a good metric for highly similar sequences (what we have here). Other metrics have been developed to take into account the fact that a single residue may mutate back over evolutionary time. You can get a summary of these distance measures at the following website, but we will only use the p-distance here: From the main MEGA window, select Distances Compute Pairwise. You will be presented with a list of options. Change the substitution model to Amino Acid p-distance. Then, calculate the distance matrix by clicking Compute. b. Which two proteins are most similar? Which are most different? (3 points) Part 2: Building Phylogenetic Trees Building a Neighbor Joining (NJ) Tree One of the distance-based methods we discussed in class was the neighbor-joining tree algorthm. This method forms a distance based tree by constructing a starting star shaped tree and reshaping the tree until the most similar sequences are joined as neighbors. This method, like the UPGMA method, will produce very good (but not always perfect) phylogenetic trees. From the main MEGA window, click on the Phylogeny Construct Phylogeny Neighbor Joining option. You will be presented with a similar option menu as before. Again, make sure that p-distance is being used as the substitution distance metric, and compute the tree. As you view the tree, you can click on and select different branches and nodes. When a branch or node is selected, you can perform several operations using the buttons on the left such as specify roots, flip branches, etc. You can also click on the i button at the top of a window to determine how long each branch is. c. Using the information menu, determine the horizontal distance between the Giardia and Euplotes phyla. To do this, sum up all the horizontal distances between the two OTUs. Compare this to the value calculated by the distance matrix and explain. (5 points) From within the tree explorer it is possible not only view the phylogram in the rooted view, but it is also possible to view the tree from a radiation perspective with no explicit root. To do this, click on the picture of the tree next to the i button near the top of the window. You should be able to select radiation as a tree format. You can either save this tree in MEGA s proprietary format, or you can export the image as an extended metafile, which can be read into Microsoft Word or various image editors. MEGA s format allows you to edit the tree later, whereas the metafile allows you to use the tree in other programs. To save the tree, select File Save at the top of the menu. Choose a good file name for your tree, just in case you need to view it again. Also, export an extended metafile by selecting Image Save as Extended Metafile (EMF). 4

5 d. Upload your radiation tree in extended metafile format to the course website. (5 points) Building a Maximum Parsimony (MP) Tree The procedure for building a maximum parsimony tree is similar. Remember that this method simply examines the differences between sequences, so no implicit distance measure is needed. There are parameters that are of some importance, however: mainly, we will have to tell the program how to search for trees, as in general there are too many trees to search exhaustively and thus a heuristic search is needed. From the main MEGA window, select Phylogeny Construct Phylogeny Maximum Parsimony Tree. At the top of the window, you will see a tab labeled MP Tree Search Options. Click this tab. The options here will determine how the software will search for optimal MP trees. The three options are different methods that generate many trees and select the best. Since character based methods do not use distances, there may be many optimal trees the first technique is guaranteed to find all the optimal trees, whereas the second and third are heuristic algorithms and may not find all the optimal trees. For now, leave the setting at Close-Neighbor Interchange with the default options. Then, construct the tree by selecting the Options Summary tab and clicking Compute. When you view the result, the default display is a cladogram. Change this to a phylogram by making sure the Display Only Topology toggle button is off. Then, you will be able to determine how many amino acids are different between each sequence by looking at the scale. We will see why the topology only button is on by default. For heuristic methods of calculating trees, you will see that the Tree # option can be changed at the top of the window. This allows you to scroll through the solutions identified by the search. e. Scroll through several of the solutions with the topology only option off, then scroll through the trees with the option on. Which setting gives the more consistent answer? What is the difference between a topology only tree and a phylogram? (3 points) The advantage to using a bona fide phylogram is obvious: you can immediately grasp the distance equivalent between two sequences. Ideally, we would like to possess some quantifiable difference between proteins, and this can be done by averaging the many different solutions we calculated heuristically into a consensus tree. To calculate the consensus tree, select the right-most button at the top of the tree window. This will allow you to specify a consensus cutoff: Specifying a cutoff of 50% will average all the trees and list topologies that are consistent with more than 50% of the solutions. By default, calculating the consensus tree is still not a phylogram: while you can have more confidence in the topology, the quantitative relations between taxa is still not displayed. To display a true consensus phylogram (realizing that it is likely not correct here), you must deselect the Compute Condensed Tree button and once again make sure the Topology Only button is toggled off. The numbers by each taxon are indicative of how many (what percentage) of the solutions support using that phylogenetic distance. 5

6 f. Submit a copy of your consensus phylogram with a 50% cutoff as an extended metafile. Compare this image to your (rectangular) NJ tree. (5 points) We have calculated the tree using a heuristic method. Now, let s calculate the consensus tree using all of the optimal MP trees determined by the Max-Mini Branch and Bound method. This method of searching for optimal MP trees is guaranteed to find all of the (degenerate) optimal solutions without performing an exhaustive search of the possible trees. g. Repeat the steps you completed above, this time using the Max-Mini Branch and Bound method for constructing the tree. Generate a rectangular consensus phylogram at the 50% cutoff as you did in part (f), and submit your image as an EMF file to the course website. Compare the three trees you have made so far. (3 points) Part 3: Bootstrapping Although we have determined the optimal solutions to our phylogenetic tree problem, we have not investigated how robust are trees are. That is, if some of our data were to be removed, would we still likely obtain the same tree, or are our trees held together by loose threads of homology? To calculate this, we can perform a bootstrap analysis on our tree. This will systematically remove several columns from the alignment and examine what happens to the tree as a result. Similar to the method of calculating consensus trees, one can then estimate how often a particular branch occurs based on the number of times it shows up in the partially deleted data. We will perform a bootstrap analysis on our branch and bound solutions. To do this, construct an MP tree as before and select the branch and bound search method. This time, however, select the Test of Phylogeny tab. Click on Bootstrap, and use the default options, which will generate 500 different data sets using our original alignment. When you run the calculation, you will notice that it takes somewhat longer to compute the tree. On your new tree window, you will notice a tab appears that allows you to view the Bootstrap consensus sequence. This tree can be viewed like any other, and you can turn on or off topology only, etc. h. Submit a copy of your bootstrap consensus phylogram as an extended metafile. Given that a bootstrap cutoff of 70% or higher corresponds approximately to a p-value of 0.05 or above, what can you say about the statistical significance of this tree? (5 points) i. How do you think you could improve the statistical significance of this tree? (3 points) When you have finished the lab, save the files you wish to keep and copy them to your Macintosh desktop. Then, delete the files from the Windows XP machine, and turn it off using the Start Menu options. 6

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