Abstract
The RNA genome of the hepatitis C virus (HCV) undergoes rapid evolutionary change. Efforts to control this virus would benefit from the advent of facile methods to identify characteristic features of HCV RNA and proteins, and to condense the vast amount of mutational data into a readily interpretable form. Many HCV sequences are available in GenBank. To facilitate analysis, consensus sequences were constructed to eliminate the overrepresentation of certain genotypes, such as genotype 1, and a novel package of sequence analysis tools was developed. Mutation Master generates profiles of point mutations in a population of sequences and produces a set of visual displays and tables indicating the number, frequency, and character of substitutions. It can be used to analyze hundreds of sequences at a time. When applied to 255 HCV core protein sequences, Mutation Master identified variable domains and a series of mutations meriting further investigation. It flagged position 4, for example, where 90% or more of all sequences in genotypes 1, 2, 4, and 5, have N4, whereas those in genotypes 3, 6, 7, 8, 9, and 10 have L4. This pattern is noteworthy: L (hydrophobic) to N (polar) substitutions are generally rare, and genotypes 1, 2, 4, and 5 do not form a recognized super family of sequences. Thus, the L4N substitution probably arose independently several times. Moreover, not one member of genotypes 1, 2, 4, or 5 has L4 and not one member of genotypes 3, 6, 7, 8, 9, or 10 has N4. This nonoverlapping pattern suggests that coordinated changes at position 4 and a second site are required to yield a viable virus. The package generated a table of genotype-specific substitutions whose future analysis may help to identify interacting amino acids. Three substitutions were present in 100% of genotype 2 members and absent from all others: A68D, R74K, and R114H. Finally, this study revealed thatARFP, a novel protein encoded in an overlapping reading frame, is as conserved as conventional HCV proteins, a result supporting a role for ARFP in the viral life cycle. Whereas most conventional programs for phylogenetic analysis of sequences provide information about overall relatedness of genes or genomes, this program highlights and profiles point mutations. This is important because determinants of pathogenicity and drug susceptibility are likely to result from changes at only one or two key nucleotides or amino acid sites, and would not be detected by the type of pairwise comparisons that have usually been performed on HCV to date. This study is the first application of Mutation Master, which is now available upon request (http://tandem.biomath.mssm.edu/mutationmaster.html).
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