It sounds like the reviewers would like to know which family or group of N-acetyl transferase enzyme you are working on.   Humans, for example, have 18 different genes for different N-acetyl transferase enzymes.  Most of the human enzymes are in the GCN5 related N-acetyltransferases family, but some are in other families such as the Arylamine N-acetyltransferase family.

If you do a BLAST search and pull out the same enzyme from 30 different insects and build a tree, this will tell you how closely related your insect is to other insects, but will not tell you which enzyme family your are studying.

https://en.wikipedia.org/wiki/N-acetyltransferase

http://supfam.org/SUPERFAMILY/cgi-bin/scop.cgi?sunid=54047

http://www.genenames.org/cgi-bin/genefamilies/set/1134

First of all you need to find the best substition model for your data. The model will affect your analyze, then you need to decide which character (Distance methods, Parsimony methods, and Likelihood ) you should use. The choice is all depends on your data.

In Minumum Evolution tress; distance measures that correct for multiple hits at the same sites are used, and a topology showing the smallest value of the sum of all branches (S). It takes time because S valuesfor all topologies are evaluated. The number of possible topologies (unrooted trees) rapidly increases with the number of taxa so it becomes very difficult to examine all topologies. In this case, one may use the neighbor-joining method. While the NJ tree is usually the same as the ME tree, when the number of taxa is small the difference between the NJ and ME trees can be substantial. Parsimony trees could be confusing for the beginners because its statistical model little bit different.

For further information you can read:

Swofford DL, Olsen GJ, Waddell PJ & Hillis DM (1996). Phylogenetic Inference. In Hiillis DM, Moritz D, and Mable BK, editors, Molecular Systematics, pp. 407-514.Sinauer Associates, Sunderland, Massachusetts.

Page RDM & Holmes EC (1998) Molecular Evolution: A Phylogenetic Approach. Blackwell Science, Oxford, U.K.

Nei M & Kumar S (2000) Molecular Evolution and Phylogenetics. Oxford University Press, New York.

It sounds like the reviewers would like to know which family or group of N-acetyl transferase enzyme you are working on.   Humans, for example, have 18 different genes for different N-acetyl transferase enzymes.  Most of the human enzymes are in the GCN5 related N-acetyltransferases family, but some are in other families such as the Arylamine N-acetyltransferase family.

If you do a BLAST search and pull out the same enzyme from 30 different insects and build a tree, this will tell you how closely related your insect is to other insects, but will not tell you which enzyme family your are studying.

https://en.wikipedia.org/wiki/N-acetyltransferase

http://supfam.org/SUPERFAMILY/cgi-bin/scop.cgi?sunid=54047

http://www.genenames.org/cgi-bin/genefamilies/set/1134

Thanks for your advice everyone. Brian, I think you might be correct. If I make a tree consisting of the GNAT superfamily, then split it into the different NATs this will give a much clearer picture as to how it relates to other NATs.

And thanks Dilruba for your statistical advice, it's much needed!!

Thanks all! I'll get on it

Usually Maximum Likelihood or Bayesian is the best approach, even better doing both. Instead of search for the best model, simply use the universal GTR. Model adjustment was important when ML analysis was very time consuming and the more complex the model, the longer the analysis. Nowadays this is not a problem; you can run data with thousands of sequences under ML with GTR for example on the Cipres server using RAxML or MrBayes, and it takes a few hours. Therefore I would always use GTR. But of course you need to specify all this in your methods section. By the way, RAxML is a great tool for ML analysis and many other things, so you are not limited to MEGA.