BACKGROUND:The impact of raltegravir-resistant HIV-1 minority variants (MVs) on raltegravir treatment failure is unknown. Illumina sequencing offers greater throughput than 454, but sequence analysis tools for viral sequencing are needed. We evaluated Illumina and 454 for the detection of HIV-1 raltegravir-resistant MVs.METHODS:A5262 was a single-arm study of raltegravir and darunavir/ritonavir in treatment-naïve patients. Pre-treatment plasma was obtained from 5 participants with raltegravir resistance at the time of virologic failure. A control library was created by pooling integrase clones at predefined proportions. Multiplexed sequencing was performed with Illumina and 454 platforms at comparable costs. Illumina sequence analysis was performed with the novel snp-assess tool and 454 sequencing was analyzed with V-Phaser.RESULTS:Illumina sequencing resulted in significantly higher sequence coverage and a 0.095% limit of detection. Illumina accurately detected all MVs in the control library at ≥0.5% and 7/10 MVs expected at 0.1%. 454 sequencing failed to detect any MVs at 0.1% with 5 false positive calls. For MVs detected in the patient samples by both 454 and Illumina, the correlation in the detected variant frequencies was high (R2 = 0.92, P<0.001). Illumina sequencing detected 2.4-fold greater nucleotide MVs and 2.9-fold greater amino acid MVs compared to 454. The only raltegravir-resistant MV detected was an E138K mutation in one participant by Illumina sequencing, but not by 454.CONCLUSIONS:In participants of A5262 with raltegravir resistance at virologic failure, baseline raltegravir-resistant MVs were rarely detected. At comparable costs to 454 sequencing, Illumina demonstrated greater depth of coverage, increased sensitivity for detecting HIV MVs, and fewer false positive variant calls.

Background Massively parallel sequencing offers the possibility of revolutionizing the study of viral populations by providing ultra deep sequencing (tens to hundreds of thousand fold coverage) of complete viral genomes. However, differentiation of true low frequency variants from sequencing errors remains challenging. Results We developed a software package, V-Phaser 2, for inferring intrahost diversity within viral populations. This program adds three major new methodologies to the state of the art: a technique to efficiently utilize paired end read data for calling phased variants, a new strategy to represent and infer length polymorphisms, and an in line filter for erroneous calls arising from systematic sequencing artifacts. We have also heavily optimized memory and run time performance. This combination of algorithmic and technical advances allows V-Phaser 2 to fully utilize extremely deep paired end sequencing data (such as generated by Illumina sequencers) to accurately infer low frequency intrahost variants in viral populations in reasonable time on a standard desktop computer. V-Phaser 2 was validated and compared to both QuRe and the original V-Phaser on three datasets obtained from two viral populations: a mixture of eight known strains of West Nile Virus (WNV) sequenced on both 454 Titanium and Illumina MiSeq and a mixture of twenty-four known strains of WNV sequenced only on 454 Titanium. V-Phaser 2 outperformed the other two programs in both sensitivity and specificity while using more than five fold less time and memory. Conclusions We developed V-Phaser 2, a publicly available software tool (V-Phaser 2 can be accessed via: http://www.broadinstitute.org/scientific-community/science/projects/viral-genomics/v-phaser-2 and is freely available for academic use) that enables the efficient analysis of ultra-deep sequencing data produced by common next generation sequencing platforms for viral populations.

Deep sequencing technologies have the potential to transform the study of highly variable viral pathogens by providing a rapid and cost-effective approach to sensitively characterize rapidly evolving viral quasispecies. Here, we report on a high-throughput whole HIV-1 genome deep sequencing platform that combines 454 pyrosequencing with novel assembly and variant detection algorithms. In one subject we combined these genetic data with detailed immunological analyses to comprehensively evaluate viral evolution and immune escape during the acute phase of HIV-1 infection. The majority of early, low frequency mutations represented viral adaptation to host CD8+ T cell responses, evidence of strong immune selection pressure occurring during the early decline from peak viremia. CD8+ T cell responses capable of recognizing these low frequency escape variants coincided with the selection and evolution of more effective secondary HLA-anchor escape mutations. Frequent, and in some cases rapid, reversion of transmitted mutations was also observed across the viral genome. When located within restricted CD8 epitopes these low frequency reverting mutations were sufficient to prime de novo responses to these epitopes, again illustrating the capacity of the immune response to recognize and respond to low frequency variants. More importantly, rapid viral escape from the most immunodominant CD8+ T cell responses coincided with plateauing of the initial viral load decline in this subject, suggestive of a potential link between maintenance of effective, dominant CD8 responses and the degree of early viremia reduction. We conclude that the early control of HIV-1 replication by immunodominant CD8+ T cell responses may be substantially influenced by rapid, low frequency viral adaptations not detected by conventional sequencing approaches, which warrants further investigation. These data support the critical need for vaccine-induced CD8+ T cell responses to target more highly constrained regions of the virus in order to ensure the maintenance of immunodominant CD8 responses and the sustained decline of early viremia.

RNA viruses are the causative agents for AIDS, influenza, SARS, and other serious health threats. Development of rapid and broadly applicable methods for complete viral genome sequencing is highly desirable to fully understand all aspects of these infectious agents as well as for surveillance of viral pandemic threats and emerging pathogens. However, traditional viral detection methods rely on prior sequence or antigen knowledge. In this study, we describe sequence-independent amplification for samples containing ultra-low amounts of viral RNA coupled with Illumina sequencing and de novo assembly optimized for viral genomes. With 5 million reads, we capture 96 to 100% of the viral protein coding region of HIV, respiratory syncytial and West Nile viral samples from as little as 100 copies of viral RNA. The methods presented here are scalable to large numbers of samples and capable of generating full or near full length viral genomes from clone and clinical samples with low amounts of viral RNA, without prior sequence information and in the presence of substantial host contamination.

ABSTRACT Analogous to observations in RNA viruses such as human immunodeficiency virus, genetic variation associated with intrahost dengue virus (DENV) populations has been postulated to influence viral fitness and disease pathogenesis. Previous attempts to investigate intrahost genetic variation in DENV characterized only a few viral genes or a limited number of full-length genomes. We developed a whole-genome amplification approach coupled with deep sequencing to capture intrahost diversity across the entire coding region of DENV-2. Using this approach, we sequenced DENV-2 genomes from the serum of 22 Nicaraguan individuals with secondary DENV infection and captured ∼75% of the DENV genome in each sample (range, 40 to 98%). We identified and quantified variants using a highly sensitive and specific method and determined that the extent of diversity was considerably lower than previous estimates. Significant differences in intrahost diversity were detected between genes and also between antigenically distinct domains of the Envelope gene. Interestingly, a strong association was discerned between the extent of intrahost diversity in a few genes and viral clade identity. Additionally, the abundance of viral variants within a host, as well as the impact of viral mutations on amino acid encoding and predicted protein function, determined whether intrahost variants were observed at the interhost level in circulating Nicaraguan DENV-2 populations, strongly suggestive of purifying selection across transmission events. Our data illustrate the value of high-coverage genome-wide analysis of intrahost diversity for high-resolution mapping of the relationship between intrahost diversity and clinical, epidemiological, and virological parameters of viral infection.

Background. Infection with hepatitis C virus (HCV) is a burgeoning worldwide public health problem, with 170 million infected individuals and an estimated 20 million deaths in the coming decades. While 6 main genotypes generally distinguish the global geographic diversity of HCV, a multitude of closely related subtypes within these genotypes are poorly defined and may influence clinical outcome and treatment options. Unfortunately, the paucity of genetic data from many of these subtypes makes time-consuming primer walking the limiting step for sequencing understudied subtypes.Methods. Here we combined long-range polymerase chain reaction amplification with pyrosequencing for a rapid approach to generate the complete viral coding region of 31 samples representing poorly defined HCV subtypes.Results. Phylogenetic classification based on full genome sequences validated previously identified HCV subtypes, identified a recombinant sequence, and identified a new distinct subtype of genotype 4. Unlike conventional sequencing methods, use of deep sequencing also facilitated characterization of minor drug resistance variants within these uncommon or, in some cases, previously uncharacterized HCV subtypes.Conclusions. These data aid in the classification of uncommon HCV subtypes while also providing a high-resolution view of viral diversity within infected patients, which may be relevant to the development of therapeutic regimens to minimize drug resistance.

BACKGROUND:Extensive genetic diversity in viral populations within infected hosts and the divergence of variants from existing reference genomes impede the analysis of deep viral sequencing data. A de novo population consensus assembly is valuable both as a single linear representation of the population and as a backbone on which intra-host variants can be accurately mapped. The availability of consensus assemblies and robustly mapped variants are crucial to the genetic study of viral disease progression, transmission dynamics, and viral evolution. Existing de novo assembly techniques fail to robustly assemble ultra-deep sequence data from genetically heterogeneous populations such as viruses into full-length genomes due to the presence of extensive genetic variability, contaminants, and variable sequence coverage.RESULTS:We present VICUNA, a de novo assembly algorithm suitable for generating consensus assemblies from genetically heterogeneous populations. We demonstrate its effectiveness on Dengue, Human Immunodeficiency and West Nile viral populations, representing a range of intra-host diversity. Compared to state-of-the-art assemblers designed for haploid or diploid systems, VICUNA recovers full-length consensus and captures insertion/deletion polymorphisms in diverse samples. Final assemblies maintain a high base calling accuracy. VICUNA program is publicly available at: http://www.broadinstitute.org/scientific-community/science/projects/viral-genomics/ viral-genomics-analysis-software.CONCLUSIONS:We developed VICUNA, a publicly available software tool, that enables consensus assembly of ultra-deep sequence derived from diverse viral populations. While VICUNA was developed for the analysis of viral populations, its application to other heterogeneous sequence data sets such as metagenomic or tumor cell population samples may prove beneficial in these fields of research.

Viruses diversify over time within hosts, often undercutting the effectiveness of host defenses and therapeutic interventions. To design successful vaccines and therapeutics, it is critical to better understand viral diversification, including comprehensively characterizing the genetic variants in viral intra-host populations and modeling changes from transmission through the course of infection. Massively parallel sequencing technologies can overcome the cost constraints of older sequencing methods and obtain the high sequence coverage needed to detect rare genetic variants (< 1%) within an infected host, and to assay variants without prior knowledge. Critical to interpreting deep sequence data sets is the ability to distinguish biological variants from process errors with high sensitivity and specificity. To address this challenge, we describe V-Phaser, an algorithm able to recognize rare biological variants in mixed populations. V-Phaser uses covariation (i.e. phasing) between observed variants to increase sensitivity and an expectation maximization algorithm that iteratively recalibrates base quality scores to increase specificity. Overall, V-Phaser achieved > 97% sensitivity and > 97% specificity on control read sets. On data derived from a patient after four years of HIV-1 infection, V-Phaser detected 2,015 variants across the -10 kb genome, including 603 rare variants (< 1% frequency) detected only using phase information. V-Phaser identified variants at frequencies down to 0.2%, comparable to the detection threshold of allele-specific PCR, a method that requires prior knowledge of the variants. The high sensitivity and specificity of V-Phaser enables identifying and tracking changes in low frequency variants in mixed populations such as RNA viruses.

Little is known about the rate at which genetic variation is generated within intrahost populations of dengue virus (DENV) and what implications this diversity has for dengue pathogenesis, disease severity, and host immunity. Previous studies of intrahost DENV variation have used a low frequency of sampling and/or experimental methods that do not fully account for errors generated through amplification and sequencing of viral RNAs. We investigated the extent and pattern of genetic diversity in sequence data in domain III (DIII) of the envelope (E) gene in serial plasma samples (n = 49) taken from 17 patients infected with DENV type 1 (DENV-1), totaling some 8,458 clones. Statistically rigorous approaches were employed to account for artifactual variants resulting from amplification and sequencing, which we suggest have played a major role in previous studies of intrahost genetic variation. Accordingly, nucleotide sequence diversities of viral populations were very low, with conservative estimates of the average levels of genetic diversity ranging from 0 to 0.0013. Despite such sequence conservation, we observed clear evidence for mixed infection, with the presence of multiple phylogenetically distinct lineages present within the same host, while the presence of stop codon mutations in some samples suggests the action of complementation. In contrast to some previous studies we observed no relationship between the extent and pattern of DENV-1 genetic diversity and disease severity, immune status, or level of viremia.

Viral diseases such as HIV/AIDS and Dengue have an enormous impact on human health worldwide. Despite this, application of new sequencing technologies to viral genomics has lagged. We are using genome sequence data to study how populations of single stranded RNA viruses, including HIV, Dengue, West Nile and Hepatitis C, evolve within infected individuals in response to host immune, therapeutic and vaccine pressures. To support this, we have developed high-throughput sequencing, assembly and population profiling pipelines based on 454 and Illumina technology that are tuned to the specific needs of viral sequencing. These strategies can capture full genome sequences and can profile sequence diversity at each residue in the genome with unprecedented sensitivity. Our analytical pipeline for 454 and Illumina data (i) generates complete genome assemblies from short sequencing reads derived from populations with high rates of variation; and (ii) detects and quantifies variants in these populations with high sensitivity, while differentiating true variants from process errors. Initial results with our viral sequencing and analysis pipeline are extremely promising. We detected rare variants to below 1% frequency, revolutionizing our ability to accurately assess the earliest events in viral evolution. We have demonstrated effective assessment of genome-wide diversity during acute HIV infection, enabling rapid, affordable, and highly sensitive identification of the earliest cellular immune responses to HIV. This has allowed us to detect earlier evolutionary events, demonstrating, for example, that HIV cytotoxic T-lymphocyte (CTL) escape can occur much faster than previously known. In addition, we have shown that the extent of intra-host diversity in Flaviviruses such as DENV and WNV is different between these closely related viruses with the latter exhibiting greater genetic diversity. The results presented here demonstrate the power of scalable, next generation sequencing-based methodologies as a genome-wide and unbiased global approach to profiling genomic diversity in intra-host populations of single stranded RNA viruses.