Bioinformatyka 2006/07 8/2007
Molecular evolution
1. Find protein sequences of alpha, beta and zeta hemoglobins from human and mouse (select organism name :” homo | musculus “, description hemoglobin, description “alpha | beta | zeta”, Note : mouse hemoglobins consist of two subunits (major beta1 and minor beta2, choose both)
2. Save all sequences in a fasta format file (you can select multiple entries by using check-boxes and clicking the save button. Next select “output to : file” and“save with view : Fasta2Seqs”)
3. Edit the saved file so lines containing sequences descriptions (starting with “>”) consist of up to 5-letter names (e.g use the form : HHA – for Human hemoglobin aplha; MHB1 – for mouse hemoglobin beta1; etc…. )
4. Make a multiple alignment using a T-Coffee ww server. Click on the link “clustalw_aln” to see the results. Keep the Firefox-T-Coffee window open for now.
5. Import your multiple alignment to the Jalview editor. ( find jalview applet using e.g google), run the fourth applet, select “input from textbox”, copy-paste your alignment from the Firefox-T-Coffee window (use : control-c, control-v)
6. Edit the multiple alignment by removing columns containing gaps. Select “output to textbox” and choose FASTA format. Keep the window open.
7. Use phylip www service to calculate persimony tree, e.g:
http://bioinfo.hku.hk/Pise/protpars.html
http://bioportal.cgb.indiana.edu/pise/protpars.html
8. Copy-paste your fasta alignment and calculate parsimony tree using bootstraps. (select Bootstrap options, check “Perform a bootstrap”, use 10 replicates, check “compute a consensus”)
9. See the results. Your 10 bootstrap trees are in “outfile”, the consensus tree is in “outfile.consense”. Does the consensus tree place proteins on correct branches?
10. Use a different method (Neighbour – Joining, N-J) to calculate consense tree. Use server :
http://bioinfo.hku.hk/Pise/protdist.html
http://bioportal.cgb.indiana.edu/pise/protdist.html
11. First create protdist matrix for NJ. Copy-paste your fasta alignment ald calculate protein distance matrices (select Bootstrap options, perform a bootstrap before analysis, use 10 replicates)
12. When the matrices are completed choose the “neighbor” program. Select “bootstrap options” , check “analyse multiple data sets”. Choose 10 data sets and compute a consensus tree.
13. Look at your results in “outfile.consense” file. Compare the two methods. Are the results identical? Why?
biologia