Classification, nomenclature, and database development for hepatitis C virus (HCV) and related viruses: proposals for standardization

Robertson, Betty H.; Myers, Gerald; Howard, Colin R.; Brettin, Tom; Bukh, Jens; Gaschen, Brian; Gojobori, Takashi; Maertens, Geert; Mizokami, Masashi; Nainan, Omana V.; Нетесов, С. В.; Nishioka, Kusuya; Simmonds, Peter; Smith, Donald B.; Stuyver, Lieven; Weiner, Amy J.

doi:10.1007/s007050050479

Cited by 429 publications

(329 citation statements)

References 55 publications

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“…Sequencing other viral regions is indicated for more accurate subtyping and molecular epidemiological studies (36), but this would require re-amplification of all samples after RNA detection with different pairs of primers. Other studies with different viral genomic regions should be carried out to better understand the dynamics of HCV infection in Brazil, since most available data come from 5'UTR analysis.…”

Section: Discussionmentioning

confidence: 99%

Geographic distribution of hepatitis C virus genotypes in Brazil

Campiotto

Pinho

Carrilho

et al. 2005

Braz J Med Biol Res

174

102

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Brazil is a country of continental dimension with a population of different ethnic backgrounds. Thus, a wide variation in the frequencies of hepatitis C virus (HCV) genotypes is expected to occur. To address this point, 1,688 sequential samples from chronic HCV patients were analyzed. HCV-RNA was amplified by the RT-PCR from blood samples collected from 1995 to 2000 at different laboratories located in different cities from all Brazilian States. Samples were collected in tubes containing a gel separator, centrifuged in the site of collection and sent by express mail in a refrigerated container to Laboratório Bioquímico Jardim Paulista, São Paulo, SP, Brazil. HCV-RNA was extracted from serum and submitted to RT and nested PCR using standard procedures. Nested PCR products were submitted to cycle sequencing reactions without prior purification. Sequences were analyzed for genotype determination and the following frequencies were found: 64.9% (1,095) for genotype 1, 4.6% (78) for genotype 2, 30.2% (510) for genotype 3, 0.2% (3) for genotype 4, and 0.1% (2) for genotype 5. The frequencies of HCV genotypes were statistically different among Brazilian regions (P = 0.00017). In all regions, genotype 1 was the most frequent (51.7 to 74.1%), reaching the highest value in the North; genotype 2 was more prevalent in the Center-West region (11.4%), especially in Mato Grosso State (25.8%), while genotype 3 was more common in the South (43.2%). Genotypes 4 and 5 were rarely found and only in the Southeast, in São Paulo State. The present data indicate the need for careful epidemiological surveys throughout Brazil since knowing the frequency and distribution of the genotypes would provide key information for understanding the spread of HCV.

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Section: Discussionmentioning

confidence: 99%

Geographic distribution of hepatitis C virus genotypes in Brazil

Campiotto

Pinho

Carrilho

et al. 2005

Braz J Med Biol Res

174

102

View full text Add to dashboard Cite

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“…HCV is an etiological agent of chronic hepatitis, which may progress to cirrhosis and hepatocellular carcinoma (Choo et al 1989). The genomic sequences from different HCV isolates are highly divergent (Kato et al 1989) and divided into six clades which are further subdivided into various numbers of subtypes (Robertson et al 1998). E1 and E2 consist of 192 and 426 amino acids, respectively (Kato et al 1990).…”

Section: Discussionmentioning

confidence: 99%

New Methods for Detecting Positive Selection at Single Amino Acid Sites

Suzuki

2004

J Mol Evol

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Inferring positive selection at single amino acid sites is of particular importance for studying evolutionary mechanisms of a protein. For this purpose, Suzuki and Gojobori (1999) developed a method (SG method) for comparing the rates of synonymous and nonsynonymous substitutions at each codon site in a protein-coding nucleotide sequence, using ancestral codons at interior nodes of the phylogenetic tree as inferred by the maximum parsimony method. In the SG method, however, selective neutrality of nucleotide substitutions cannot be tested at codon sites, where only termination codons are inferred at any interior node or the number of equally parsimonious inferences of ancestral codons at all interior nodes exceeds 10,000. Here I present a modified SG method which is free from these problems. Specifically, I use the distance-based Bayesian method for inferring the single most likely ancestral codon from 61 sense codons at each interior node. In the computer simulation and real data analysis, the modified SG method showed a higher overall efficiency of detecting positive selection than the original SG method, particularly at highly polymorphic codon sites. These results indicate that the modified SG method is useful for inferring positive selection at codon sites where neutrality cannot be tested by the original SG method. I also discuss that the p-distance is preferable to the number of synonymous substitutions for inferring the phylogenetic tree in the SG method, and present a maximum likelihood method for detecting positive selection at single amino acid sites, which produced reasonable results in the real data analysis.

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“…Hepatitis C virus (HCV) is a positive-sensed, single-stranded RNA virus of the Flaviviridae family [9]. HCV replication is mediated by NS5B and other nonstructural proteins that comprise the replication complex (RC).…”

Section: Introductionmentioning

confidence: 99%