Dataset Information

Genotyping Influenza Virus by Next-Generation Deep Sequencing in Clinical Specimens.

ABSTRACT: Rapid and accurate identification of an influenza outbreak is essential for patient care and treatment. We describe a next-generation sequencing (NGS)-based, unbiased deep sequencing method in clinical specimens to investigate an influenza outbreak. Nasopharyngeal swabs from patients were collected for molecular epidemiological analysis. Total RNA was sequenced by using the NGS technology as paired-end 250 bp reads. Total of 7 to 12 million reads were obtained. After mapping to the human reference genome, we analyzed the 3-4% of reads that originated from a non-human source. A BLAST search of the contigs reconstructed de novo revealed high sequence similarity with that of the pandemic H1N1 virus. In the phylogenetic analysis, the HA gene of our samples clustered closely with that of A/Senegal/VR785/2010(H1N1), A/Wisconsin/11/2013(H1N1), and A/Korea/01/2009(H1N1), and the NA gene of our samples clustered closely with A/Wisconsin/11/2013(H1N1). This study suggests that NGS-based unbiased sequencing can be effectively applied to investigate molecular characteristics of nosocomial influenza outbreak by using clinical specimens such as nasopharyngeal swabs.

SUBMITTER: Seong MW

PROVIDER: S-EPMC4773267 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Genotyping Influenza Virus by Next-Generation Deep Sequencing in Clinical Specimens.

Seong Moon Woo MW Cho Sung Im SI Park Hyunwoong H Seo Soo Hyun SH Lee Seung Jun SJ Kim Eui Chong EC Park Sung Sup SS

Annals of laboratory medicine 20160501 3

Rapid and accurate identification of an influenza outbreak is essential for patient care and treatment. We describe a next-generation sequencing (NGS)-based, unbiased deep sequencing method in clinical specimens to investigate an influenza outbreak. Nasopharyngeal swabs from patients were collected for molecular epidemiological analysis. Total RNA was sequenced by using the NGS technology as paired-end 250 bp reads. Total of 7 to 12 million reads were obtained. After mapping to the human referen ...[more]

PMID: 26915615

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Project description:Genotyping of the human leucocyte antigen (HLA) is indispensable for various medical treatments. However, unambiguous genotyping is technically challenging due to high polymorphism of the corresponding genomic region. Next-generation sequencing is changing the landscape of genotyping. In addition to high throughput of data, its additional advantage is that DNA templates are derived from single molecules, which is a strong merit for the phasing problem. Although most currently developed technologies use genomic DNA, use of cDNA could enable genotyping with reduced costs in data production and analysis. We thus developed an HLA genotyping system based on next-generation sequencing of cDNA.Each HLA gene was divided into 3 or 4 target regions subjected to PCR amplification and subsequent sequencing with Ion Torrent PGM. The sequence data were then subjected to an automated analysis. The principle of the analysis was to construct candidate sequences generated from all possible combinations of variable bases and arrange them in decreasing order of the number of reads. Upon collecting candidate sequences from all target regions, 2 haplotypes were usually assigned. Cases not assigned 2 haplotypes were forwarded to 4 additional processes: selection of candidate sequences applying more stringent criteria, removal of artificial haplotypes, selection of candidate sequences with a relaxed threshold for sequence matching, and countermeasure for incomplete sequences in the HLA database.The genotyping system was evaluated using 30 samples; the overall accuracy was 97.0% at the field 3 level and 98.3% at the G group level. With one sample, genotyping of DPB1 was not completed due to short read size. We then developed a method for complete sequencing of individual molecules of the DPB1 gene, using the molecular barcode technology.The performance of the automatic genotyping system was comparable to that of systems developed in previous studies. Thus, next-generation sequencing of cDNA is a viable option for HLA genotyping.

Dataset Information

Genotyping Influenza Virus by Next-Generation Deep Sequencing in Clinical Specimens.

Publications

Genotyping Influenza Virus by Next-Generation Deep Sequencing in Clinical Specimens.

Similar Datasets

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