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Development of a low bias method for characterizing viral populations using next generation sequencing technology.

ABSTRACT: With an estimated 38 million people worldwide currently infected with human immunodeficiency virus (HIV), and an additional 4.1 million people becoming infected each year, it is important to understand how this virus mutates and develops resistance in order to design successful therapies.We report a novel experimental method for amplifying full-length HIV genomes without the use of sequence-specific primers for high throughput DNA sequencing, followed by assembly of full length viral genome sequences from the resulting large dataset. Illumina was chosen for sequencing due to its ability to provide greater coverage of the HIV genome compared to prior methods, allowing for more comprehensive characterization of the heterogeneity present in the HIV samples analyzed. Our novel amplification method in combination with Illumina sequencing was used to analyze two HIV populations: a homogenous HIV population based on the canonical NL4-3 strain and a heterogeneous viral population obtained from a HIV patient's infected T cells. In addition, the resulting sequence was analyzed using a new computational approach to obtain a consensus sequence and several metrics of diversity.This study demonstrates how a lower bias amplification method in combination with next generation DNA sequencing provides in-depth, complete coverage of the HIV genome, enabling a stronger characterization of the quasispecies present in a clinically relevant HIV population as well as future study of how HIV mutates in response to a selective pressure.

SUBMITTER: Willerth SM

PROVIDER: S-EPMC2962647 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Development of a low bias method for characterizing viral populations using next generation sequencing technology.

Willerth Stephanie M SM Pedro Hélder A M HA Pachter Lior L Humeau Laurent M LM Arkin Adam P AP Schaffer David V DV

PloS one 20101022 10

<h4>Background</h4>With an estimated 38 million people worldwide currently infected with human immunodeficiency virus (HIV), and an additional 4.1 million people becoming infected each year, it is important to understand how this virus mutates and develops resistance in order to design successful therapies.<h4>Methodology/principal findings</h4>We report a novel experimental method for amplifying full-length HIV genomes without the use of sequence-specific primers for high throughput DNA sequenc ...[more]

PMID: 21042592

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Project description:Full-length human immunodeficiency virus type 1 (HIV-1) RNA serves as the genome or as an mRNA, or this RNA undergoes splicing using four donors and 10 acceptors to create over 50 physiologically relevant transcripts in two size classes (1.8 kb and 4 kb). We developed an assay using Primer ID-tagged deep sequencing to quantify HIV-1 splicing. Using the lab strain NL4-3, we found that A5 (env/nef) is the most commonly used acceptor (about 50%) and A3 (tat) the least used (about 3%). Two small exons are made when a splice to acceptor A1 or A2 is followed by activation of donor D2 or D3, and the high-level use of D2 and D3 dramatically reduces the amount of vif and vpr transcripts. We observed distinct patterns of temperature sensitivity of splicing to acceptors A1 and A2. In addition, disruption of a conserved structure proximal to A1 caused a 10-fold reduction in all transcripts that utilized A1. Analysis of a panel of subtype B transmitted/founder viruses showed that splicing patterns are conserved, but with surprising variability of usage. A subtype C isolate was similar, while a simian immunodeficiency virus (SIV) isolate showed significant differences. We also observed transsplicing from a downstream donor on one transcript to an upstream acceptor on a different transcript, which we detected in 0.3% of 1.8-kb RNA reads. There were several examples of splicing suppression when the env intron was retained in the 4-kb size class. These results demonstrate the utility of this assay and identify new examples of HIV-1 splicing regulation. IMPORTANCE During HIV-1 replication, over 50 conserved spliced RNA variants are generated. The splicing assay described here uses new developments in deep-sequencing technology combined with Primer ID-tagged cDNA primers to efficiently quantify HIV-1 splicing at a depth that allows even low-frequency splice variants to be monitored. We have used this assay to examine several features of HIV-1 splicing and to identify new examples of different mechanisms of regulation of these splicing patterns. This splicing assay can be used to explore in detail how HIV-1 splicing is regulated and, with moderate throughput, could be used to screen for structural elements, small molecules, and host factors that alter these relatively conserved splicing patterns.

Project description:Genes of the vertebrate major histocompatibility complex (MHC) are of great interest to biologists because of their important role in immunity and disease, and their extremely high levels of genetic diversity. Next generation sequencing (NGS) technologies are quickly becoming the method of choice for high-throughput genotyping of multi-locus templates like MHC in non-model organisms. Previous approaches to genotyping MHC genes using NGS technologies suffer from two problems:1) a "gray zone" where low frequency alleles and high frequency artifacts can be difficult to disentangle and 2) a similar sequence problem, where very similar alleles can be difficult to distinguish as two distinct alleles. Here were present a new method for genotyping MHC loci--Stepwise Threshold Clustering (STC)--that addresses these problems by taking full advantage of the increase in sequence data provided by NGS technologies. Unlike previous approaches for genotyping MHC with NGS data that attempt to classify individual sequences as alleles or artifacts, STC uses a quasi-Dirichlet clustering algorithm to cluster similar sequences at increasing levels of sequence similarity. By applying frequency and similarity based criteria to clusters rather than individual sequences, STC is able to successfully identify clusters of sequences that correspond to individual or similar alleles present in the genomes of individual samples. Furthermore, STC does not require duplicate runs of all samples, increasing the number of samples that can be genotyped in a given project. We show how the STC method works using a single sample library. We then apply STC to 295 threespine stickleback (Gasterosteus aculeatus) samples from four populations and show that neighboring populations differ significantly in MHC allele pools. We show that STC is a reliable, accurate, efficient, and flexible method for genotyping MHC that will be of use to biologists interested in a variety of downstream applications.

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Development of a low bias method for characterizing viral populations using next generation sequencing technology.

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Development of a low bias method for characterizing viral populations using next generation sequencing technology.

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