Details:

Alternative Title:
BMC Genomics
Publisher's site:
http://dx.doi.org/10.1186/1471-2164-15-S5-S4
Personal Author:
Campo, David S; Dimitrova, Zoya; Yamasaki, Lilian; Skums, Pavel; Lau, Daryl TY; ... More +
Campo, David S; Dimitrova, Zoya; Yamasaki, Lilian; Skums, Pavel; Lau, Daryl TY; Vaughan, Gilberto; Forbi, Joseph C; Teo, Chong-Gee; Khudyakov, Yury; Less -
Description:
Background Next-generation sequencing (NGS) allows for sampling numerous viral variants from infected patients. This provides a novel opportunity to represent and study the mutational landscape of Hepatitis C Virus (HCV) within a single host. Results Intra-host variants of the HCV E1/E2 region were extensively sampled from 58 chronically infected patients. After NGS error correction, the average number of reads and variants obtained from each sample were 3202 and 464, respectively. The distance between each pair of variants was calculated and networks were created for each patient, where each node is a variant and two nodes are connected by a link if the nucleotide distance between them is 1. The work focused on large components having > 5% of all reads, which in average account for 93.7% of all reads found in a patient. Conclusions Most intra-host variants are organized into distinct single-mutation components that are: well separated from each other, represent genetic distances between viral variants, robust to sampling, reproducible and likely seeded during transmission events. Facilitated by NGS, large components offer a novel evolutionary framework for genetic analysis of intra-host viral populations and understanding transmission, immune escape and drug resistance.
Subject:
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Computer Simulation
Genetic Variation
Genotype
Hepacivirus
Hepatitis C
High-Throughput Nucleotide Sequencing
Humans
Mutation
Needle Sharing
Research
RNA, Viral
Sequence Analysis, DNA

Source:
BMC Genomics. 2014; 15(Suppl 5):S4.;
Document Type:
Journal Article;
Collection(s):
CDC Public Access
Main Document Checksum:
[+]
urn:sha256:fb2d918022983dbcda9437b9a7b9220ec670e897b663aaca7d76404c161848c8
File Type:

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