Congratulations on your research start! I also got my start in research as an undergraduate studying fungi. It sounds like you are off to a good start. I hope you are working with someone to help guide you along the way.

You didn't give us any reason why you chose to study myosin-related pathogenicity genes, but I am sure there is a reason this will fit into a "broader research scheme" here. I wouldn't be surprised that you are not seing any strong homology with human genes; the fungi and animals diverged from each other a long, long time ago and have vastly different life strategies. If your phylogenetic trees are robust you will be able to eliminate sequences which should not be in your analysis. This is not necessarily easy to do, so I would work with your research advisor to figure this out. It's a subtle type of analysis which is hard to describe. You will need to have have a well-supported phylogenetic tree that you are able to discuss and inspect.

I'm not certain you should be using ClustalW to make a phylogenetic tree; you may be able to "make a tree" but it will not be the best tree you can make. I would choose a phylogenetic program (see below) which uses (at least) a maximum-likelihood approach, but more than one approach (such as adding a Bayesian approach) will help.

This is a highly simplified version of what I do when I am constructing phylogenetic trees: (1) first choose sequences representing your gene/proteins (you did this through BLAST), (2) align the sequences using a program and inspect the alignment by eye, (3) make sure the sequences are then in a text format that phylogenetic programs can work with (such as NEXUS or XML), (4) let the algorithms run on one or more (see here and here) phylogenetic programs, and (5) visualize your data, and repeat until you are comfortable with your phylogenetic tree (your evolutionary hypothesis).

Since you're new to phylogenetics I would recommend two books: Tree Thinking, more on the theory side of things, and Phylogenetic Trees Made Easy, more on the practical data analysis side of things.

Best of luck with you research and let me know how it's going! I'll keep my eyes open for your published paper!

From your description of the question you're trying to address, I'm not so sure that building phylogenetic trees is the best way (at least initially) for you to be going.

It sounds to me as though the key question is "Which biological functions are likely involved in the pathogenicity of this fungus?", and/or, more specifically, "What might be the function of these pathogenicity genes?"

In this case, the way I'd begin addressing this, similar to what you've done, is to run BLAST (and then if that doesn't get me significant matches, PSI-BLAST/HMMER/Interpro scan) to identify proteins, or regions of other proteins, that are likely to have similar structures/functions as your pathogenicity proteins. These functions (of the proteins which have been studied in more detail elsewhere) then become hypotheses for the function of your pathogenicity proteins.

Thus, I'd be focusing on carrying out sequence-similarity focused database searches.

When you draw a tree using a set of sequences, you are assuming/asserting already that the sequences have a similar structure/are "evolutionary related", and are then asking "what is the pattern of transfer of genetic information between the sequences I observe" - and it doesn't sound, to me, as though that kind of question/answer is going to be so useful in addressing the main questions I've suggested above.

Another issue - if the sequence similarity between sequences you are including in a multiple sequence alignment (MSA) that you then estimate a tree from are so divergent that you get such "high" E-values from them in BLAST, then any phylogeny-like structure you estimate from them is likely to be full of errors. You can still use this thing which looks like a phylogeny to make inferences about the degree of similarity between different sequences, but I would strongly recommend not making inferences about degree of relatedness etc. between the sequences.

And a final point - and E-value close to 1 (e.g. 0.5) from BLAST suggests that the sequences may well not have similar structure/function. When similarity is so low, then one thing to do is to turn to more sensitive methods (PSI-BLAST, HMMER, as I suggest above).

Hope this helps.

HI,

I would download the protein sequences of all the Fungal species from JGI. Then find the Orthologs using OrthoMCL and grep out the secreted effectors or pathogenic genes, then use RAxML and/Or MrBayes for the phylogenetic analysis on the predicted OrthoMCL orthologs of pathogenic genes. I would do the whole analysis locally on Unix machine. Hope this would help you.

Best, Rahul