Dataset Information

Molecular analysis of HBV genotypes and subgenotypes in the Central-East region of Tunisia.

ABSTRACT: BACKGROUND: In Tunisia, country of intermediate endemicity for Hepatitis B virus (HBV) infection, most molecular studies on the virus have been carried out in the North of the country and little is known about other regions. The aim of this study was to determine HBV genotype and subgenotypes in Central-East Tunisia. A total of 217 HBs antigen positive patients were enrolled and determination of genotype was investigated in 130 patients with detectable HBV DNA. HBV genotyping methods were: PCR-RFLP on the pre-S region, a PCR using type-specific primers in the S region (TSP-PCR) and partial sequencing in the pre-S region. RESULTS: Three genotypes (D, B and A) were detected by the PCR-RFLP method and two (D and A) with the TSP-PCR method, the concordance between the two methods was 93%. Sequencing and phylogenetic analysis of 32 strains, retrieved the same genotype (D and A) for samples with concordant results and genotype D for samples with discordant results. The sequences of discordant genotypes had a restriction site in the pre-S gene which led to erroneous result by the PCR-RFLP method. Thus, prevalence of genotype D and A was 96% and 4%, respectively. Phylogenetic analysis showed the predominance of two subgenotypes D1 (55%) and D7 (41%). Only one strain clustered with D3 subgenotype (3%). CONCLUSIONS: Predominance of subgenotype D7 appears to occur in northern regions of Africa with transition to subgenotype D1 in the East of the continent. HBV genetic variability may lead to wrong results in rapid genotyping methods and sequence analysis is needed to clarify atypical results.

SUBMITTER: Hannachi N

PROVIDER: S-EPMC2989323 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Molecular analysis of HBV genotypes and subgenotypes in the Central-East region of Tunisia.

Hannachi Naila N Fredj Nadia Ben NB Bahri Olfa O Thibault Vincent V Ferjani Asma A Gharbi Jawhar J Triki Henda H Boukadida Jalel J

Virology journal 20101104

<h4>Background</h4>In Tunisia, country of intermediate endemicity for Hepatitis B virus (HBV) infection, most molecular studies on the virus have been carried out in the North of the country and little is known about other regions. The aim of this study was to determine HBV genotype and subgenotypes in Central-East Tunisia. A total of 217 HBs antigen positive patients were enrolled and determination of genotype was investigated in 130 patients with detectable HBV DNA. HBV genotyping methods were ...[more]

PMID: 21050489

Similar Datasets

Project description:Hepatitis B virus (HBV) infection is a common problem in the world, especially in China. More than 60-80% of hepatocellular carcinoma (HCC) cases can be attributed to HBV infection in high HBV prevalent regions. Although traditional Sanger sequencing has been extensively used to investigate HBV sequences, NGS is becoming more commonly used. Further, it is unknown whether word pattern frequencies of HBV reads by Next Generation Sequencing (NGS) can be used to investigate HBV genotypes and predict HCC status. In this study, we used NGS to sequence the pre-S region of the HBV sequence of 94 HCC patients and 45 chronic HBV (CHB) infected individuals. Word pattern frequencies among the sequence data of all individuals were calculated and compared using the Manhattan distance. The individuals were grouped using principal coordinate analysis (PCoA) and hierarchical clustering. Word pattern frequencies were also used to build prediction models for HCC status using both K-nearest neighbors (KNN) and support vector machine (SVM). We showed the extremely high power of analyzing HBV sequences using word patterns. Our key findings include that the first principal coordinate of the PCoA analysis was highly associated with the fraction of genotype B (or C) sequences and the second principal coordinate was significantly associated with the probability of having HCC. Hierarchical clustering first groups the individuals according to their major genotypes followed by their HCC status. Using cross-validation, high area under the receiver operational characteristic curve (AUC) of around 0.88 for KNN and 0.92 for SVM were obtained. In the independent data set of 46 HCC patients and 31 CHB individuals, a good AUC score of 0.77 was obtained using SVM. It was further shown that 3000 reads for each individual can yield stable prediction results for SVM. Thus, another key finding is that word patterns can be used to predict HCC status with high accuracy. Therefore, our study shows clearly that word pattern frequencies of HBV sequences contain much information about the composition of different HBV genotypes and the HCC status of an individual.

Dataset Information

Molecular analysis of HBV genotypes and subgenotypes in the Central-East region of Tunisia.

Publications

Molecular analysis of HBV genotypes and subgenotypes in the Central-East region of Tunisia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets