81 A total of 20 variants were observed, 17 of which were locate

81 A total of 20 variants were observed, 17 of which were located in the coding region. Two variants in the N-terminal and five in the C-terminal caused an amino acid exchange (Figure 3b), which amounted to a much higher calculated density of SNPs in the coding region, about, one SNP every 84 bp. The human β2-adrenergic receptor gene (ADRB2), about 3 kb, has been resequenced in a total of several hundred individuals70; 15 variants, 8 in Inhibitors,research,lifescience,medical the 5′ regulatory region including the leader peptide and 7 in the coding region, have been identified, at a roughly comparable spacing

of one SNP every 175 to 200 bp.55,70 The mutation in the leader peptide and three coding SNPs, two of which were located in the N-terminal, were found to be functionally significant57-59; by far the majority of variants were highly frequent. The human CB1 cannabinoid Inhibitors,research,lifescience,medical receptor gene (CNR1), another member of the G protein-coupled receptor gene family, was found to be remarkably invariable within and between species,62 when analyzing a total of about 200 individuals including European- and African-Americans Inhibitors,research,lifescience,medical as well as Europeans exhibiting extreme responses to cannabis use; only two silent substitutions were observed within about 1500 bp coding region. Similarly, notable invariability

was observed in the coding Inhibitors,research,lifescience,medical regions of two chemokine receptor gene subtypes (Ohl et al, selleck kinase inhibitor unpublished data). Finally, completely invariable coding exons and few SNPs in intronic regions were found in the human promelanin

concentrating hormone gene (PMCH), a neuropeptide and endogenous ligand (Hoehe et al, unpublished data). Taken together, current, approaches to describe, evaluate, Inhibitors,research,lifescience,medical and compare genetic variation in candidate genes remain in many aspects grossly insufficient and merely descriptive. They rely predominantly on the determination of frequency patterns and average values that describe and distinguish variability per se, as well as different categories of variants or functional gene sequence classes. These approaches allow, however, specific predictions of the nature and distribution of SNPs in the estimated 30 000 human genes, ie, in a study about 300-fold larger. Consequently, they may also allow extrapolations Resminostat on the nature and amount of variability in potential drug targets. On the other hand, without knowledge of the specific functional variation in the genes underlying given nucleotide diversity, which will have to be based upon characterization of entire, individually different, forms of the gene and its product, the implications of the variability of candidate genes may hardly be evaluated and compared. The previous approaches to the characterization of genetic variation are in essence single SNP oriented.

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