The spectrum of human rhodopsin disease mutations through the lens of interspecific variation.
Mutations in rhodopsin, the visual pigment found in rod cells, account for a large fraction of genetic changes underlying the human retinal diseases, Retinitis Pigmentosa (RP). The availability of rhodopsin sequences from a large number of vertebrates has allowed us to investigate factors important in the development of RP by contrasting interspecific differences (long-term evolutionary patterns) with RP disease mutation data. We find that disease mutations in rhodopsin are overabundant in highly conserved sites and that amino acid positions with any potential of variability among vertebrates are likely to harbour disease mutations less frequently. At any amino acid position in rhodopsin, the set of disease-associated amino acids does not show any commonality with the set of amino acids present among species. The disease mutations are biochemically four times more radical than the interspecific (neutral) variation. This pattern is also observed when disease mutations are categorized based on clinical classifications that reflect biochemical, physiological and psychophysical traits such as protein folding, cone electroretinogram (ERG) amplitude, pattern of visual field loss, and equivalent field diameter. We also found that for artificial mutations (those not observed in nature interspecifically), there was a positive relationship between the biochemical distance and the magnitude of blue shift in the absorption spectrum maximum. We introduce the concept of the expected chemical severity based on the normal human codon at a position. Results reveal that the analysis of disease mutations in the context of the original codon is very important for the practical application of evolutionary principles when comparing original and disease amino acid mutations. We conclude that the analysis of rhodopsin data clearly demonstrates the usefulness of molecular evolutionary analyses for understanding patterns of clinical as well as artificial mutations and underscores the biomedical insights that can be gained by using simple measures of biochemical difference in the context of evolutionary divergence.