tijeco/molecularevolutiontutorial

Tutorial for

Molecular Evolution Tutorial

Tutorial for BIOL 6210 (Applied Pylogentics)

HYPHY stuff: all files need for this tutorial are here

Identification of pervasive positive selection in cone snail venom

1. Get the file Conus.01.fas

2. We will now do the FUBAR analysis

• This is a site specific method for detecting selection at the amino acid level, helpful in arms race scenarios

3. Go to http://www.datamonkey.org/

**4. ** Select choose file, select Conus.01.fas

• Then, press Upload

5. If your data is no bueno, this is where it will let you know

• It accepts fasta alignments and nexus files
• Also listed here should be information about the alignments
• If all is well, press Proceed to the analysis menu

6. Under Method select FUBAR

7. For now leave everything else alone and just press Run

• If you had a nexus file, you could specify your own tree in Newick format
• For now we'll just let it use a generated neighbor joining tree :cry:

8. The results will look like the following

• This is a heat map showing sites are under positive selection and negative selection

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PAML stuff

Identification of positive seleciton in the serine/threonine-protein kinase gene family

• In the evolution vertebrates, we would like to know if the branch leading to the Teleost fishes (genes A50 to A54)

You will need the following files

1. TF105351.Eut.3.phy

• this is the alignment file

2. TF105351.Eut.3.53876.tree

• this is the newick tree with the branch of interest selected

3. TF105351.Eut.3.53876.ctl

• CodeML configuration file for alternative model

4. TF105351.Eut.3.53876.fixed.ctl

• CodeML configuration file for null model

Run the following commands

codeml TF105351.Eut.3.53876.ctl
codeml TF105351.Eut.3.53876.fixed.ctl

Analyze results

Get liklihood values

grep lnL TF105351.Eut.3.53876.mlc

lnL(ntime: 41  np: 46):  -4707.209701      +0.000000

Liklihood value for alternative model is -4707.209701

grep lnL TF105351.Eut.3.53876.fixed.mlc

lnL(ntime: 41  np: 45):  -4710.222252      +0.000000

Liklihood value for null model is -4710.222252

ΔLRT = 2×(lnL1 - lnL0) = 2×(-4707.209701 - (-4710.222252)) = 6.02578

The degree of freedom is 1 (np1 - np0 = 46 - 45). p-value = 0.01098 (under χ²) => significant.