Gu & Nei 1999 MBE have nice trees of mouse MHC alleles in Fig 6 and Fig 7, but they are built with the entire coding sequence of the gene.
I can't seem to find a tree of mouse MHC alleles built with just the exon that encodes the peptide binding groove (ex 3 for Class IA, ex 2 for Class IIB).
Any leads?
Thanks, Federico. I agree about the usefulness of neutral characters for reconstructing phylogenetic history. Here, though, my interest in not in reconstructing the evolutionary history of these genes but in looking at patterns of functional similarity of the peptide binding groove in the extant set of alleles.
Thanks, Federico. Yes, it's looking like that's the way I'll have to proceed! Thanks!
I agree with Federico's suggestion to extract the regions that encode the putative binding site and construct a 'phenetic' tree that only considers pairwise differences between peptide binding sites. I did this to infer MHC 'supertypes', i.e.clusters of MHC variants that differ with respect to putative binding sites they code for in dolphins. That worked fairly well, and the amino acids these supertypes encode did differ with respect to physiochemical properties and are under strong selection. I would recommend to use UPGMA clustering rather than a more complex way of inferring evolutionary relationships--which is, as you said, not what you want. Our study hasn't been published yet, but if you are interested, I could give you more details on this--it sounds like you are aiming for the same. The closest method to this supertype classification (analogous to what you seem to be describing) is published in Reche & Reinherz 2007, but there are other methods published--see below:
Reche PA, Reinherz EL (2007) Definition of MHC supertypes through clustering of MHC peptide binding repertoires. Methods in Molecular Biology, 409, 163-173.
Sette A, Sidney J (1998) HLA supertypes and supermotifs: a functional perspective on HLA polymorphism. Current Opinion in Immunology, 10, 478-482.
Doytchinova IA, Guan P, Flower DR (2004) Identifiying human MHC supertypes using bioinformatic methods. Journal of Immunology, 172, 4314-23.
Doytchinova IA, Flower D (2005) In silico identification of supertypes for class II MHCs. Journal of Immunology, 174, 7085-7095.
Sette A, Sidney J (1998) HLA supertypes and supermotifs: a functional perspective on HLA polymorphism. Current Opinion in Immunology, 10, 478-482.
Sette A, Sidney J (1999) Nine major HLA class I supertypes account for the vast preponderance of HLA-A and –B polymorphism. Immunogenetics, 50, 201- 212.
Sidney J, Peters B, Frahm N, Brander C, Sette A (2008). HLA class I supertypes: a revised and updated classification. BMC Immunology, 9, doi:10.1186/1471- 2172-9-1.
Flower D, Doytchinova IA (2002). Immunoinformatics and the prediction of immunogenicity. Applied Bioinformatics, 1, 167-176.
Yu K, Petrovsky N, Schonbach C, Koh JY, Brusic V (2002) Methods for prediction of peptide binding to MHC molecules: a comparative study. Molecular Medicine, 8, 137-148.
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