Read length versus depth of coverage for viral quasispecies reconstruction

Setu: a pipeline for the robust assembly of SARS-CoV-2 genomes

Setu is an efficient pipeline integrating currently available open source bioinformatic tools to perform rapid de novo assembly to assist tracking of severe acute respiratory syndrome coronavirus 2 genome evolution in clinical data, being particularly useful for institutions with limited computing resources or personnel not familiar with bioinformatic pipelines.

Influence of Environmental Factors and Genome Diversity on Cumulative COVID-19 Cases in the Highland Region of China: Comparative Correlational Study

BACKGROUND

The novel coronavirus SARS-CoV-2 caused the global COVID-19 pandemic. Emerging reports support lower mortality and reduced case numbers in highland areas; however, comparative studies on the cumulative impact of environmental factors and viral genetic diversity on COVID-19 infection rates have not been performed to date.

OBJECTIVE

The aims of this study were to determine the difference in COVID-19 infection rates between high and low altitudes, and to explore whether the difference in the pandemic trend in the high-altitude region of China compared to that of the lowlands is influenced by environmental factors, population density, and biological mechanisms.

METHODS

We examined the correlation between population density and COVID-19 cases through linear regression. A zero-shot model was applied to identify possible factors correlated to COVID-19 infection. We further analyzed the correlation of meteorological and air quality factors with infection cases using the Spearman correlation coefficient. Mixed-effects multiple linear regression was applied to evaluate the associations between selected factors and COVID-19 cases adjusting for covariates. Lastly, the relationship between environmental factors and mutation frequency was evaluated using the same correlation techniques mentioned above.

RESULTS

Among the 24,826 confirmed COVID-19 cases reported from 40 cities in China from January 23, 2020, to July 7, 2022, 98.4% (n=24,430) were found in the lowlands. Population density was positively correlated with COVID-19 cases in all regions (ρ=0.641, P=.003). In high-altitude areas, the number of COVID-19 cases was negatively associated with temperature, sunlight hours, and UV index (P=.003, P=.001, and P=.009, respectively) and was positively associated with wind speed (ρ=0.388, P<.001), whereas no correlation was found between meteorological factors and COVID-19 cases in the lowlands. After controlling for covariates, the mixed-effects model also showed positive associations of fine particulate matter (PM2.5) and carbon monoxide (CO) with COVID-19 cases (P=.002 and P<.001, respectively). Sequence variant analysis showed lower genetic diversity among nucleotides for each SARS-CoV-2 genome (P<.001) and three open reading frames (P<.001) in high altitudes compared to 300 sequences analyzed from low altitudes. Moreover, the frequencies of 44 nonsynonymous mutations and 32 synonymous mutations were significantly different between the high- and low-altitude groups (P<.001, mutation frequency>0.1). Key nonsynonymous mutations showed positive correlations with altitude, wind speed, and air pressure and showed negative correlations with temperature, UV index, and sunlight hours.

CONCLUSIONS

By comparison with the lowlands, the number of confirmed COVID-19 cases was substantially lower in high-altitude regions of China, and the population density, temperature, sunlight hours, UV index, wind speed, PM2.5, and CO influenced the cumulative pandemic trend in the highlands. The identified influence of environmental factors on SARS-CoV-2 sequence variants adds knowledge of the impact of altitude on COVID-19 infection, offering novel suggestions for preventive intervention.

Evolutionary Analysis of Pre-S/S Mutations in HBeAg-Negative Chronic Hepatitis B With HBsAg < 100 IU/ml

Background: Hepatitis B surface antigen (HBsAg) and viral load are important clinical indicators for antiviral therapy. Few studies have evaluated viral sequence biomarkers predicting the risk of hepatocellular carcinoma (HCC) in the stage, which show a low serological response (HBsAg < 100 IU/ml) and high viral levels (HBV DNA > 2,000 IU/ml). This study aims to determine the trend of the biological prevalence within the pre-S/S regions of special model of inactive CHB infection. Methods: We used Sanger sequencing, quantitative HBV serology (HBeAg and HBsAg), and liver function index to identify whether HBV genome sequences are associated with long-term risk of further HCC progression in special inactive CHB infection. Results: HBV sequencing analysis of 28 CHB patients with special infectious pattern showed higher genetic diversity among four opening reading frames (ORFs) (p < 0.001). However, dN/dS ratios of HBsAg and pre-C/C regions in the experimental group showed no significantly different from those in the HCC group (p = 0.06), while significantly lower in polymerase and HBxAg regions of the experimental group (p < 0.001). In addition, seven positively selected sites were identified in pre-S1, five in pre-S2, and four in S, in which five sites (128H/135Q/135R/139L/141P) were among "α" determinant. Conclusions: These mutations in the pre-S/S region might be associated with the HCC phenotype of low HBsAg expression, with the P region possibly impacting high viral loads. Increased viral diversity across the HBV genome is also associated with low levels of HBsAg. The cumulative evolutionary changes in the HBV pre-S/S regions shows that facilitate immune evasion should be monitored individually. Due to the similarity of evolutionary characteristics in HCC, low serological responses and high viremia may be associated with the risk of further disease progression.

Streamlined Subpopulation, Subtype, and Recombination Analysis of HIV-1 Half-Genome Sequences Generated by High-Throughput Sequencing

The highly recombinogenic nature of human immunodeficiency virus type 1 (HIV-1) leads to recombination and emergence of quasispecies. It is important to reliably identify subpopulations to understand the complexity of a viral population for drug resistance surveillance and vaccine development. High-throughput sequencing (HTS) provides improved resolution over Sanger sequencing for the analysis of heterogeneous viral subpopulations. However, current methods of analysis of HTS reads are unable to fully address accurate population reconstruction. Hence, there is a dire need for a more sensitive, accurate, user-friendly, and cost-effective method to analyze viral quasispecies. For this purpose, we have improved the HIVE-hexahedron algorithm that we previously developed with in silico short sequences to analyze raw HTS short reads. The significance of this study is that our standalone algorithm enables a streamlined analysis of quasispecies, subtype, and recombination patterns from long HIV-1 genome regions without the need of additional sequence analysis tools. Distinct viral populations and recombination patterns identified by HIVE-hexahedron are further validated by comparison with sequences obtained by single genome sequencing (SGS).

High-throughput sequencing (HTS) has been widely used to characterize HIV-1 genome sequences. There are no algorithms currently that can directly determine genotype and quasispecies population using short HTS reads generated from long genome sequences without additional software. To establish a robust subpopulation, subtype, and recombination analysis workflow, we amplified the HIV-1 3′-half genome from plasma samples of 65 HIV-1-infected individuals and sequenced the entire amplicon (∼4,500 bp) by HTS. With direct analysis of raw reads using HIVE-hexahedron, we showed that 48% of samples harbored 2 to 13 subpopulations. We identified various subtypes (17 A1s, 4 Bs, 27 Cs, 6 CRF02_AGs, and 11 unique recombinant forms) and defined recombinant breakpoints of 10 recombinants. These results were validated with viral genome sequences generated by single genome sequencing (SGS) or the analysis of consensus sequence of the HTS reads. The HIVE-hexahedron workflow is more sensitive and accurate than just evaluating the consensus sequence and also more cost-effective than SGS.

IMPORTANCE The highly recombinogenic nature of human immunodeficiency virus type 1 (HIV-1) leads to recombination and emergence of quasispecies. It is important to reliably identify subpopulations to understand the complexity of a viral population for drug resistance surveillance and vaccine development. High-throughput sequencing (HTS) provides improved resolution over Sanger sequencing for the analysis of heterogeneous viral subpopulations. However, current methods of analysis of HTS reads are unable to fully address accurate population reconstruction. Hence, there is a dire need for a more sensitive, accurate, user-friendly, and cost-effective method to analyze viral quasispecies. For this purpose, we have improved the HIVE-hexahedron algorithm that we previously developed with in silico short sequences to analyze raw HTS short reads. The significance of this study is that our standalone algorithm enables a streamlined analysis of quasispecies, subtype, and recombination patterns from long HIV-1 genome regions without the need of additional sequence analysis tools. Distinct viral populations and recombination patterns identified by HIVE-hexahedron are further validated by comparison with sequences obtained by single genome sequencing (SGS).

Inter- Versus Intra-Host Sequence Diversity of pH1N1 and Associated Clinical Outcomes

The diversity of RNA viruses dictates their evolution in a particular host, community or environment. Here, we reported within- and between-host pH1N1virus diversity at consensus and sub-consensus levels over a three-year period (2015-2017) and its implications on disease severity. A total of 90 nasal samples positive for the pH1N1 virus were deep-sequenced and analyzed to detect low-frequency variants (LFVs) and haplotypes. Parallel evolution of LFVs was seen in the hemagglutinin (HA) gene across three scales: among patients (33%), across years (22%), and at global scale. Remarkably, investigating the emergence of LFVs at the consensus level demonstrated that within-host virus evolution recapitulates evolutionary dynamics seen at the global scale. Analysis of virus diversity at the HA haplotype level revealed the clustering of low-frequency haplotypes from early 2015 with dominant strains of 2016, indicating rapid haplotype evolution. Haplotype sharing was also noticed in all years, strongly suggesting haplotype transmission among patients infected during a specific influenza season. Finally, more than half of patients with severe symptoms harbored a larger number of haplotypes, mostly in patients under the age of five. Therefore, patient age, haplotype diversity, and the presence of certain LFVs should be considered when interpreting illness severity. In addition to its importance in understanding virus evolution, sub-consensus virus diversity together with whole genome sequencing is essential to explain variabilities in clinical outcomes that cannot be explained by either analysis alone.

A proofreading-impaired herpesvirus generates populations with quasispecies-like structure

RNA virus populations are composed of highly diverse individuals that form a cloud of related sequences commonly referred to as a 'quasispecies'^1-3. This diversity arises as a consequence of low-fidelity genome replication^4,5. By contrast, DNA virus populations contain more uniform individuals with similar fitness⁶. Genome diversity is often correlated with increased fitness in RNA viruses, while DNA viruses are thought to require more faithful genome replication. During DNA replication, erroneously incorporated bases are removed by a 3'-5' exonuclease, a highly conserved enzymatic function of replicative DNA but not RNA polymerases. This proofreading process enhances replication fidelity and ensures the genome integrity of DNA organisms, including large DNA viruses⁷. Here, we show that a herpesvirus can tolerate impaired exonucleolytic proofreading, resulting in DNA virus populations, which, as in RNA viruses⁸, are composed of highly diverse genotypes of variable individual fitness. This indicates that herpesvirus mutant diversity may compensate for individual fitness loss. Notably, in vivo infection with diverse virus populations results in a marked increase in virulence compared to genetically homogenous parental virus. While we cannot exclude that the increase in virulence is caused by selection of and/or interactions between individual genotypes, our findings are consistent with quasispecies dynamics. Our results contrast with traditional views of DNA virus replication and evolution, and indicate that a substantial increase in population diversity can lead to higher virulence.

Genomic characterization of hepatitis C virus transmitted founder variants with deep sequencing

Transfer of hepatitis C virus (HCV) infection from a donor to a new recipient is associated with a bottleneck of genetic diversity in the transmitted viral variants. Existing data suggests that one, or very few, variants emerge from this bottleneck to establish the infection (transmitted founder [T/F] variants). In HCV, very few T/F variants have been characterized due to the challenges of obtaining early infection samples and of high throughput viral genome sequencing. This study used a large, acute HCV, deep-sequenced dataset from first viremia samples collected in nine prospective cohorts across four countries, to estimate the prevalence of single T/F viruses, and to identify host and virus-related factors associated with infections initiated by a single T/F variant. The short reads generated by Illumina sequencing were used to reconstruct viral haplotypes with two haplotype reconstruction algorithms. The haplotypes were examined for random mutations (Poisson distribution) and a star-like phylogeny to identify T/F viruses. The findings were cross-validated by haplotype reconstructions across three regions of the genome (Core-E2, NS3, NS5A) to minimize the possibility of spurious overestimation of single T/F variants. Of 190 acute infection samples examined, 54 were very early acute infections (HCV antibody negative, RNA positive), and single transmitted founders were identified in 14 (26%, 95% CI: 16-39%) after cross validation across multiple regions of the genome with two haplotype reconstruction algorithms. The presence of a single T/F virus was not associated with any host or virus-related factors, notably viral genotype or spontaneous clearance. In conclusion, approximately one in four new HCV infections originates from a single T/F virus. Resolution of genomic sequences of single T/F variants is the first step in exploring unique properties of these variants in the infection of host hepatocytes.

A high-throughput SNP discovery strategy for RNA-seq data

Background

Single nucleotide polymorphisms (SNP) have been applied as important molecular markers in genetics and breeding studies. The rapid advance of next generation sequencing (NGS) provides a high-throughput means of SNP discovery. However, SNP development is limited by the availability of reliable SNP discovery methods. Especially, the optimum assembler and SNP caller for accurate SNP prediction from next generation sequencing data are not known.

Results

Herein we performed SNP prediction based on RNA-seq data of peach and mandarin peel tissue under a comprehensive comparison of two paired-end read lengths (125 bp and 150 bp), five assemblers (Trinity, IDBA, oases, SOAPdenovo, Trans-abyss) and two SNP callers (GATK and GBS). The predicted SNPs were compared with the authentic SNPs identified via PCR amplification followed by gene cloning and sequencing procedures. A total of 40 and 240 authentic SNPs were presented in five anthocyanin biosynthesis related genes in peach and in nine carotenogenic genes in mandarin. Putative SNPs predicted from the same RNA-seq data with different strategies led to quite divergent results. The rate of false positive SNPs was significantly lower when the paired-end read length was 150 bp compared with 125 bp. Trinity was superior to the other four assemblers and GATK was substantially superior to GBS due to a low rate of missing authentic SNPs. The combination of assembler Trinity, SNP caller GATK, and the paired-end read length 150 bp had the best performance in SNP discovery with 100% accuracy both in peach and in mandarin cases. This strategy was applied to the characterization of SNPs in peach and mandarin transcriptomes.

Conclusions

Through comparison of authentic SNPs obtained by PCR cloning strategy and putative SNPs predicted from different combinations of five assemblers, two SNP callers, and two paired-end read lengths, we provided a reliable and efficient strategy, Trinity-GATK with 150 bp paired-end read length, for SNP discovery from RNA-seq data. This strategy discovered SNP at 100% accuracy in peach and mandarin cases and might be applicable to a wide range of plants and other organisms.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5533-4) contains supplementary material, which is available to authorized users.

Link between the numbers of particles and variants founding new HIV-1 infections depends on the timing of transmission

Understanding which HIV-1 variants are most likely to be transmitted is important for vaccine design and predicting virus evolution. Since most infections are founded by single variants, it has been suggested that selection at transmission has a key role in governing which variants are transmitted. We show that the composition of the viral population within the donor at the time of transmission is also important. To support this argument, we developed a probabilistic model describing HIV-1 transmission in an untreated population, and parameterised the model using both within-host next generation sequencing data and population-level epidemiological data on heterosexual transmission. The most basic HIV-1 transmission models cannot explain simultaneously the low probability of transmission and the non-negligible proportion of infections founded by multiple variants. In our model, transmission can only occur when environmental conditions are appropriate (e.g. abrasions are present in the genital tract of the potential recipient), allowing these observations to be reconciled. As well as reproducing features of transmission in real populations, our model demonstrates that, contrary to expectation, there is not a simple link between the number of viral variants and the number of viral particles founding each new infection. These quantities depend on the timing of transmission, and infections can be founded with small numbers of variants yet large numbers of particles. Including selection, or a bias towards early transmission (e.g. due to treatment), acts to enhance this conclusion. In addition, we find that infections initiated by multiple variants are most likely to have derived from donors with intermediate set-point viral loads, and not from individuals with high set-point viral loads as might be expected. We therefore emphasise the importance of considering viral diversity in donors, and the timings of transmissions, when trying to discern the complex factors governing single or multiple variant transmission.

SVEngine: an efficient and versatile simulator of genome structural variations with features of cancer clonal evolution

Background

Simulating genome sequence data with variant features facilitates the development and benchmarking of structural variant analysis programs. However, there are only a few data simulators that provide structural variants in silico and even fewer that provide variants with different allelic fraction and haplotypes.

Findings

We developed SVEngine, an open-source tool to address this need. SVEngine simulates next-generation sequencing data with embedded structural variations. As input, SVEngine takes template haploid sequences (FASTA) and an external variant file, a variant distribution file, and/or a clonal phylogeny tree file (NEWICK) as input. Subsequently, it simulates and outputs sequence contigs (FASTAs), sequence reads (FASTQs), and/or post-alignment files (BAMs). All of the files contain the desired variants, along with BED files containing the ground truth. SVEngine's flexible design process enables one to specify size, position, and allelic fraction for deletions, insertions, duplications, inversions, and translocations. Finally, SVEngine simulates sequence data that replicate the characteristics of a sequencing library with mixed sizes of DNA insert molecules. To improve the compute speed, SVEngine is highly parallelized to reduce the simulation time.

Conclusions

We demonstrated the versatile features of SVEngine and its improved runtime comparisons with other available simulators. SVEngine's features include the simulation of locus-specific variant frequency designed to mimic the phylogeny of cancer clonal evolution. We validated SVEngine's accuracy by simulating genome-wide structural variants of NA12878 and a heterogeneous cancer genome. Our evaluation included checking various sequencing mapping features such as coverage change, read clipping, insert size shift, and neighboring hanging read pairs for representative variant types. Structural variant callers Lumpy and Manta and tumor heterogeneity estimator THetA2 were able to perform realistically on the simulated data. SVEngine is implemented as a standard Python package and is freely available for academic use .

Quantitative characterization of hepatitis delta virus genome edition by next-generation sequencing

AIM

To determine the capacity of next-generation sequencing (NGS) for quantifying edited and unedited HDV populations, and to confirm if edition is a general phenomenon taking place along the entire HDV region analyzed, as we previously reported (Homs M et al. PLoS One 2016, 11, e0158557).

METHODS

Four serum samples from 4 patients with chronic HDV/HBV infection were included in the study. The region selected for analysis covered 360 nucleotides (nt), positions 910-1270 of the HDV genome, which included the HDAg ORF editing site (nt 1014 within codon 196). Quantification of edited and unedited genomes was performed by molecular cloning and Sanger sequencing and by NGS. To evaluate the reliability of the NGS values obtained, we combined a clone with an edited codon and one with an unedited codon in known percentages in a series of artificial mixtures, which were then analyzed by NGS. In addition, we determined the nt changes occurring over the complete amplified region after excluding the editing codon (196) to evaluate edition along it.

RESULTS

In total, 11,208 quality-filtered sequences were obtained in the 4 samples. The 95% confidence intervals for the proportions of unedited populations by molecular cloning and NGS were overlapping, and those of cloning were wider, indicating that they are comparable and that NGS is more precise than cloning. Unedited genomes predominated over edited ones in all 4 samples analyzed by NGS and in 3 of the 4 samples analyzed by molecular cloning. In total, 83,276 quality-filtered sequences were obtained from the artificial mixtures. Percentages of the two viral populations detected by NGS in these mixtures were comparable to the expected percentages. Evaluation of edition along the HDV coding region showed that transitions were more frequent than transversions, accounting for 63.09% and 36.91%, respectively. Interestingly, among the 4 possible transition-type changes, G:A and A:G accounted for 73.86% of the total.

CONCLUSION

Next-generation sequencing proved useful to quantify edited and unedited HDV genomes, and provided relevant information on the HDV quasispecies.

Separation and assembly of deep sequencing data into discrete sub-population genomes

Sequence heterogeneity is a common characteristic of RNA viruses that is often referred to as sub-populations or quasispecies. Traditional techniques used for assembly of short sequence reads produced by deep sequencing, such as de-novo assemblers, ignore the underlying diversity. Here, we introduce a novel algorithm that simultaneously assembles discrete sequences of multiple genomes present in populations. Using in silico data we were able to detect populations at as low as 0.1% frequency with complete global genome reconstruction and in a single sample detected 16 resolved sequences with no mismatches. We also applied the algorithm to high throughput sequencing data obtained for viruses present in sewage samples and successfully detected multiple sub-populations and recombination events in these diverse mixtures. High sensitivity of the algorithm also enables genomic analysis of heterogeneous pathogen genomes from patient samples and accurate detection of intra-host diversity, enabling not just basic research in personalized medicine but also accurate diagnostics and monitoring drug therapies, which are critical in clinical and regulatory decision-making process.

Software Dedicated to Virus Sequence Analysis "Bioinformatics Goes Viral"

Computer-assisted technologies of the genomic structure, biological function, and evolution of viruses remain a largely neglected area of research. The attention of bioinformaticians to this challenging field is currently unsatisfying in respect to its medical and biological importance. The power of new genome sequencing technologies, associated with new tools to handle "big data", provides unprecedented opportunities to address fundamental questions in virology. Here, we present an overview of the current technologies, challenges, and advantages of Next-Generation Sequencing (NGS) in relation to the field of virology. We present how viral sequences can be detected de novo out of current short-read NGS data. Furthermore, we discuss the challenges and applications of viral quasispecies and how secondary structures, commonly shaped by RNA viruses, can be computationally predicted. The phylogenetic analysis of viruses, as another ubiquitous field in virology, forms an essential element of describing viral epidemics and challenges current algorithms. Recently, the first specialized virus-bioinformatic organizations have been established. We need to bring together virologists and bioinformaticians and provide a platform for the implementation of interdisciplinary collaborative projects at local and international scales. Above all, there is an urgent need for dedicated software tools to tackle various challenges in virology.

Comparison of error correction algorithms for Ion Torrent PGM data: application to hepatitis B virus

Ion Torrent Personal Genome Machine (PGM) technology is a mid-length read, low-cost and high-speed next-generation sequencing platform with a relatively high insertion and deletion (indel) error rate. A full systematic assessment of the effectiveness of various error correction algorithms in PGM viral datasets (e.g., hepatitis B virus (HBV)) has not been performed. We examined 19 quality-trimmed PGM datasets for the HBV reverse transcriptase (RT) region and found a total error rate of 0.48% ± 0.12%. Deletion errors were clearly present at the ends of homopolymer runs. Tests using both real and simulated data showed that the algorithms differed in their abilities to detect and correct errors and that the error rate and sequencing depth significantly affected the performance. Of the algorithms tested, Pollux showed a better overall performance but tended to over-correct 'genuine' substitution variants, whereas Fiona proved to be better at distinguishing these variants from sequencing errors. We found that the combined use of Pollux and Fiona gave the best results when error-correcting Ion Torrent PGM viral data.

Genotyping assay for differentiation of wild-type and vaccine viruses in subjects immunized with live attenuated influenza vaccine

Live attenuated influenza vaccines (LAIVs) are considered as safe and effective tool to control influenza in different age groups, especially in young children. An important part of the LAIV safety evaluation is the detection of vaccine virus replication in the nasopharynx of the vaccinees, with special attention to a potential virus transmission to the unvaccinated close contacts. Conducting LAIV clinical trials in some geographical regions with year-round circulation of influenza viruses warrants the development of robust and reliable tools for differentiating vaccine viruses from wild-type influenza viruses in nasal pharyngeal wash (NPW) specimens of vaccinated subjects. Here we report the development of genotyping assay for the detection of wild-type and vaccine-type influenza virus genes in NPW specimens of young children immunized with Russian-backbone seasonal trivalent LAIV using Sanger sequencing from newly designed universal primers. The new primer set allowed amplification and sequencing of short fragments of viral genes in NPW specimens and appeared to be more sensitive than conventional real-time RT-PCR protocols routinely used for the detection and typing/subtyping of influenza virus in humans. Furthermore, the new assay is capable of defining the origin of wild-type influenza virus through BLAST search with the generated sequences of viral genes fragments.

De novo assembly of highly polymorphic metagenomic data using in situ generated reference sequences and a novel BLAST-based assembly pipeline

Background

The accuracy of metagenomic assembly is usually compromised by high levels of polymorphism due to divergent reads from the same genomic region recognized as different loci when sequenced and assembled together. A viral quasispecies is a group of abundant and diversified genetically related viruses found in a single carrier. Current mainstream assembly methods, such as Velvet and SOAPdenovo, were not originally intended for the assembly of such metagenomics data, and therefore demands for new methods to provide accurate and informative assembly results for metagenomic data.

Results

In this study, we present a hybrid method for assembling highly polymorphic data combining the partial de novo-reference assembly (PDR) strategy and the BLAST-based assembly pipeline (BBAP). The PDR strategy generates in situ reference sequences through de novo assembly of a randomly extracted partial data set which is subsequently used for the reference assembly for the full data set. BBAP employs a greedy algorithm to assemble polymorphic reads. We used 12 hepatitis B virus quasispecies NGS data sets from a previous study to assess and compare the performance of both PDR and BBAP. Analyses suggest the high polymorphism of a full metagenomic data set leads to fragmentized de novo assembly results, whereas the biased or limited representation of external reference sequences included fewer reads into the assembly with lower assembly accuracy and variation sensitivity. In comparison, the PDR generated in situ reference sequence incorporated more reads into the final PDR assembly of the full metagenomics data set along with greater accuracy and higher variation sensitivity. BBAP assembly results also suggest higher assembly efficiency and accuracy compared to other assembly methods. Additionally, BBAP assembly recovered HBV structural variants that were not observed amongst assembly results of other methods. Together, PDR/BBAP assembly results were significantly better than other compared methods.

Conclusions

Both PDR and BBAP independently increased the assembly efficiency and accuracy of highly polymorphic data, and assembly performances were further improved when used together. BBAP also provides nucleotide frequency information. Together, PDR and BBAP provide powerful tools for metagenomic data studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1630-z) contains supplementary material, which is available to authorized users.

Evolution of full-length genomes of HBV quasispecies in sera of patients with a coexistence of HBsAg and anti-HBs antibodies

Although the evolutionary changes of viral quasispecies are correlated to the pathological status of a disease, little is known in the coexistence of hepatitis B surface antigen (HBsAg) and antibodies to these antigens (anti-HBs). To examine evolutionary changes in hepatitis B virus (HBV) and their relationship to the coexistence of HBsAg and anti-HBs antibodies, HBV genomes in patients with a coexistence of HBsAg and anti-HBs antibodies (experimental group) and HBsAg positive without anti-HBs (control group) were assessed. Our results showed that quasispecies diversity was significantly higher in the experimental group for large HBsAg (LHBsAg), middle HBsAg (MHBsAg), and HBsAg genes. LHBsAg harbored dN/dS values eight times higher in the experimental group; however, the mean dN/dS ratios in genes HbxAg, Pol and PreC/C of the experimental patients had an opposite trend. Phylogenetic trees in the experimental group were more complex than the control group. More positive selection sites, mutations and deletions were observed in the experimental group in specific regions. Furthermore, several amino acid variants in epitopes were potentially associated with the immune evasion. In conclusion, cumulative evolutionary changes in HBV genome that facilitate immune evasion provide insights into the genetic mechanism of a coexistence of HBsAg and anti-HBs antibodies.

MinVar: A rapid and versatile tool for HIV-1 drug resistance genotyping by deep sequencing

Genotypic monitoring of drug-resistance mutations (DRMs) in HIV-1 infected individuals is strongly recommended to guide selection of the initial antiretroviral therapy (ART) and changes of drug regimens. Traditionally, mutations conferring drug resistance are detected by population sequencing of the reverse transcribed viral RNA encoding the HIV-1 enzymes target by ART, followed by manual analysis and interpretation of Sanger sequencing traces. This process is labor intensive, relies on subjective interpretation from the operator, and offers limited sensitivity as only mutations above 20% frequency can be reliably detected. Here we present MinVar, a pipeline for the analysis of deep sequencing data, which allows reliable and automated detection of DRMs down to 5%. We evaluated MinVar with data from amplicon sequencing of defined mixtures of molecular virus clones with known DRM and plasma samples of viremic HIV-1 infected individuals and we compared it to VirVarSeq, another virus variant detection tool exclusively working on Illumina deep sequencing data. MinVar was designed to be compatible with a diverse range of sequencing platforms and allows the detection of DRMs and insertions/deletions from deep sequencing data without the need to perform additional bioinformatics analysis, a prerequisite to a widespread implementation of HIV-1 genotyping using deep sequencing in routine diagnostic settings.

Recent advances in inferring viral diversity from high-throughput sequencing data

Rapidly evolving RNA viruses prevail within a host as a collection of closely related variants, referred to as viral quasispecies. Advances in high-throughput sequencing (HTS) technologies have facilitated the assessment of the genetic diversity of such virus populations at an unprecedented level of detail. However, analysis of HTS data from virus populations is challenging due to short, error-prone reads. In order to account for uncertainties originating from these limitations, several computational and statistical methods have been developed for studying the genetic heterogeneity of virus population. Here, we review methods for the analysis of HTS reads, including approaches to local diversity estimation and global haplotype reconstruction. Challenges posed by aligning reads, as well as the impact of reference biases on diversity estimates are also discussed. In addition, we address some of the experimental approaches designed to improve the biological signal-to-noise ratio. In the future, computational methods for the analysis of heterogeneous virus populations are likely to continue being complemented by technological developments.

Detection of Natural Resistance-Associated Substitutions by Ion Semiconductor Technology in HCV1b Positive, Direct-Acting Antiviral Agents-Naïve Patients

Naturally occurring resistance-associated substitutions (RASs) can negatively impact the response to direct-acting antivirals (DAAs) agents-based therapies for hepatitis C virus (HCV) infection. Herein, we set out to characterize the RASs in the HCV1b genome from serum samples of DAA-naïve patients in the context of the SINERGIE (South Italian Network for Rational Guidelines and International Epidemiology, 2014) project. We deep-sequenced the NS3/4A protease region of the viral population using the Ion Torrent Personal Genome Machine, and patient-specific majority rule consensus sequence summaries were constructed with a combination of freely available next generation sequencing data analysis software. We detected NS3/4A protease major and minor variants associated with resistance to boceprevir (V36L), telaprevir (V36L, I132V), simeprevir (V36L), and grazoprevir (V36L, V170I). Furthermore, we sequenced part of HCV NS5B polymerase using Sanger-sequencing and detected a natural RAS for dasabuvir (C316N). This mutation could be important for treatment strategies in cases of previous therapy failure.

Estimation of genetic diversity in viral populations from next generation sequencing data with extremely deep coverage

Background

In this paper we propose a method and discuss its computational implementation as an integrated tool for the analysis of viral genetic diversity on data generated by high-throughput sequencing. The main motivation for this work is to better understand the genetic diversity of viruses with high rates of nucleotide substitution, as HIV-1 and Influenza. Most methods for viral diversity estimation proposed so far are intended to take benefit of the longer reads produced by some next-generation sequencing platforms in order to estimate a population of haplotypes which represent the diversity of the original population. The method proposed here is custom-made to take advantage of the very low error rate and extremely deep coverage per site, which are the main features of some neglected technologies that have not received much attention due to the short length of its reads, which precludes haplotype estimation. This approach allowed us to avoid some hard problems related to haplotype reconstruction (need of long reads, preliminary error filtering and assembly).

Results

We propose to measure genetic diversity of a viral population through a family of multinomial probability distributions indexed by the sites of the virus genome, each one representing the distribution of nucleic bases per site. Moreover, the implementation of the method focuses on two main optimization strategies: a read mapping/alignment procedure that aims at the recovery of the maximum possible number of short-reads; the inference of the multinomial parameters in a Bayesian framework with smoothed Dirichlet estimation. The Bayesian approach provides conditional probability distributions for the multinomial parameters allowing one to take into account the prior information of the control experiment and providing a natural way to separate signal from noise, since it automatically furnishes Bayesian confidence intervals and thus avoids the drawbacks of preliminary error filtering.

Conclusions

The methods described in this paper have been implemented as an integrated tool called Tanden (Tool for Analysis of Diversity in Viral Populations) and successfully tested on samples obtained from HIV-1 strain NL4-3 (group M, subtype B) cultivations on primary human cell cultures in many distinct viral propagation conditions. Tanden is written in C# (Microsoft), runs on the Windows operating system, and can be downloaded from: http://tanden.url.ph/.

Quantifying Next Generation Sequencing Sample Pre-Processing Bias in HIV-1 Complete Genome Sequencing

Genetic analyses play a central role in infectious disease research. Massively parallelized “mechanical cloning” and sequencing technologies were quickly adopted by HIV researchers in order to broaden the understanding of the clinical importance of minor drug-resistant variants. These efforts have, however, remained largely limited to small genomic regions. The growing need to monitor multiple genome regions for drug resistance testing, as well as the obvious benefit for studying evolutionary and epidemic processes makes complete genome sequencing an important goal in viral research. In addition, a major drawback for NGS applications to RNA viruses is the need for large quantities of input DNA. Here, we use a generic overlapping amplicon-based near full-genome amplification protocol to compare low-input enzymatic fragmentation (Nextera™) with conventional mechanical shearing for Roche 454 sequencing. We find that the fragmentation method has only a modest impact on the characterization of the population composition and that for reliable results, the variation introduced at all steps of the procedure—from nucleic acid extraction to sequencing—should be taken into account, a finding that is also relevant for NGS technologies that are now more commonly used. Furthermore, by applying our protocol to deep sequence a number of pre-therapy plasma and PBMC samples, we illustrate the potential benefits of a near complete genome sequencing approach in routine genotyping.

HIV-1 Tropism Determines Different Mutation Profiles in Proviral DNA

In order to establish new infections HIV-1 particles need to attach to receptors expressed on the cellular surface. HIV-1 particles interact with a cell membrane receptor known as CD4 and subsequently with another cell membrane molecule known as a co-receptor. Two major different co-receptors have been identified: C-C chemokine Receptor type 5 (CCR5) and C-X-C chemokine Receptor type 4 (CXCR4) Previous reports have demonstrated cellular modifications upon HIV-1 binding to its co-receptors including gene expression modulations. Here we investigated the effect of viral binding to either CCR5 or CXCR4 co-receptors on viral diversity after a single round of reverse transcription. CCR5 and CXCR4 pseudotyped viruses were used to infect non-stimulated and stimulated PBMCs and purified CD4 positive cells. We adopted the SOLiD methodology to sequence virtually the entire proviral DNA from all experimental infections. Infections with CCR5 and CXCR4 pseudotyped virus resulted in different patterns of genetic diversification. CCR5 virus infections produced extensive proviral diversity while in CXCR4 infections a more localized substitution process was observed. In addition, we present pioneering results of a recently developed method for the analysis of SOLiD generated sequencing data applicable to the study of viral quasi-species. Our findings demonstrate the feasibility of viral quasi-species evaluation by NGS methodologies. We presented for the first time strong evidence for a host cell driving mechanism acting on the HIV-1 genetic variability under the control of co-receptor stimulation. Additional investigations are needed to further clarify this question, which is relevant to viral diversification process and consequent disease progression.

Characterization of Full-Length Genomes of Hepatitis B Virus Quasispecies in Sera of Patients at Different Phases of Infection

Hepatitis B virus (HBV) infection results in different clinical presentation due to different levels of immune response. Our study aimed to characterize HBV full-length genome quasispecies (QS) in patients with different phases of infection to better understand its pathogenesis. Forty treatment-naive HBV-infected patients were enrolled, including 10 cases of acute hepatitis B (AHB), 9 cases of immunotolerant (IT) HBV carriers, 11 cases of chronic hepatitis B (CHB), and 10 cases of acute-on-chronic liver failure (ACLF). The present study was conducted by clone-based sequencing. QS heterogeneity within each open reading frame was calculated. The mutation frequency index (MFI) and amino acid variations within the large HBsAg, HBcAg, and HBxAg regions were analyzed based on the different infection phases. In total, 606 HBV full-length sequences were obtained. HBV QS had higher heterogeneity in ACLF and CHB than that in IT among chronically infected individuals. AHB patients had the lower QS heterogeneity at onset than those with chronic infection. ACLF patients had the highest frequency of mutations in the core promoter and precore region. A triple mutation (A1762T/G1764A/G1896A) was observed more frequently in genotype C than in genotype B. The MFI indicated that specific peptides of the studied regions had more frequent mutations in ACLF. Furthermore, several amino acid variations, known as T- and B-cell epitopes, were potentially associated with the immunoactive phase of infection. More HBV genome mutations and deletions were observed in patients with more severe diseases, particularly in specific regions of the core and preS regions, the clinical significance and mechanism of which need to be further investigated.

Performance assessment of the Illumina massively parallel sequencing platform for deep sequencing analysis of viral minority variants

Massively parallel sequencing (MPS) technology has opened new avenues to study viral dynamics and treatment-induced resistance mechanisms of infections such as human immunodeficiency virus (HIV) and hepatitis C virus (HCV). Whereas the Roche/454 platform has been used widely for the detection of low-frequent drug resistant variants, more recently developed short-read MPS technologies have the advantage of delivering a higher sequencing depth at a lower cost per sequenced base. This study assesses the performance characteristics of Illumina MPS technology for the characterization of genetic variability in viral populations by deep sequencing. The reported results from MPS experiments comprising HIV and HCV plasmids demonstrate that a 0.5-1% lower limit of detection can be achieved readily with Illumina MPS while retaining good accuracy also at low frequencies. Deep sequencing of a set of clinical samples (12 HIV and 9 HCV patients), designed at a similar budget for both MPS platforms, reveals a comparable lower limit of detection for Illumina and Roche/454. Finally, this study shows the possibility to apply Illumina's paired-end sequencing as a strategy to assess linkage between different mutations identified in individual viral subspecies. These results support the use of Illumina as another MPS platform of choice for deep sequencing of viral minority species.

Distinguishing low frequency mutations from RT-PCR and sequence errors in viral deep sequencing data

BACKGROUND

RNA viruses have high mutation rates and exist within their hosts as large, complex and heterogeneous populations, comprising a spectrum of related but non-identical genome sequences. Next generation sequencing is revolutionising the study of viral populations by enabling the ultra deep sequencing of their genomes, and the subsequent identification of the full spectrum of variants within the population. Identification of low frequency variants is important for our understanding of mutational dynamics, disease progression, immune pressure, and for the detection of drug resistant or pathogenic mutations. However, the current challenge is to accurately model the errors in the sequence data and distinguish real viral variants, particularly those that exist at low frequency, from errors introduced during sequencing and sample processing, which can both be substantial.

RESULTS

We have created a novel set of laboratory control samples that are derived from a plasmid containing a full-length viral genome with extremely limited diversity in the starting population. One sample was sequenced without PCR amplification whilst the other samples were subjected to increasing amounts of RT and PCR amplification prior to ultra-deep sequencing. This enabled the level of error introduced by the RT and PCR processes to be assessed and minimum frequency thresholds to be set for true viral variant identification. We developed a genome-scale computational model of the sample processing and NGS calling process to gain a detailed understanding of the errors at each step, which predicted that RT and PCR errors are more likely to occur at some genomic sites than others. The model can also be used to investigate whether the number of observed mutations at a given site of interest is greater than would be expected from processing errors alone in any NGS data set. After providing basic sample processing information and the site's coverage and quality scores, the model utilises the fitted RT-PCR error distributions to simulate the number of mutations that would be observed from processing errors alone.

CONCLUSIONS

These data sets and models provide an effective means of separating true viral mutations from those erroneously introduced during sample processing and sequencing.

Deconvoluting the composition of low-frequency hepatitis C viral quasispecies: comparison of genotypes and NS3 resistance-associated variants between HCV/HIV coinfected hemophiliacs and HCV monoinfected patients in Japan

Pre-existing low-frequency resistance-associated variants (RAVs) may jeopardize successful sustained virological responses (SVR) to HCV treatment with direct-acting antivirals (DAAs). However, the potential impact of low-frequency (∼0.1%) mutations, concatenated mutations (haplotypes), and their association with genotypes (Gts) on the treatment outcome has not yet been elucidated, most probably owing to the difficulty in detecting pre-existing minor haplotypes with sufficient length and accuracy. Herein, we characterize a methodological framework based on Illumina MiSeq next-generation sequencing (NGS) coupled with bioinformatics of quasispecies reconstruction (QSR) to realize highly accurate variant calling and genotype-haplotype detection. The core-to-NS3 protease coding sequences in 10 HCV monoinfected patients, 5 of whom had a history of blood transfusion, and 11 HCV/HIV coinfected patients with hemophilia, were studied. Simulation experiments showed that, for minor variants constituting more than 1%, our framework achieved a positive predictive value (PPV) of 100% and sensitivities of 91.7–100% for genotyping and 80.6% for RAV screening. Genotyping analysis indicated the prevalence of dominant Gt1a infection in coinfected patients (6/11 vs 0/10, p = 0.01). For clinical samples, minor genotype overlapping infection was prevalent in HCV/HIV coinfected hemophiliacs (10/11) and patients who experienced whole-blood transfusion (4/5) but none in patients without exposure to blood (0/5). As for RAV screening, the Q80K/R and S122K/R variants were particularly prevalent among minor RAVs observed, detected in 12/21 and 6/21 cases, respectively. Q80K was detected only in coinfected patients, whereas Q80R was predominantly detected in monoinfected patients (1/11 vs 7/10, p < 0.01). Multivariate interdependence analysis revealed the previously unrecognized prevalence of Gt1b-Q80K, in HCV/HIV coinfected hemophiliacs [Odds ratio = 13.4 (3.48–51.9), p < 0.01]. Our study revealed the distinct characteristics of viral quasispecies between the subgroups specified above and the feasibility of NGS and QSR-based genetic deconvolution of pre-existing minor Gts, RAVs, and their interrelationships.

Estimating Fitness of Viral Quasispecies from Next-Generation Sequencing Data

The quasispecies model is ubiquitous in the study of viruses. While having lead to a number of insights that have stood the test of time, the quasispecies model has mostly been discussed in a theoretical fashion with little support of data. With next-generation sequencing (NGS), this situation is changing and a wealth of data can now be produced in a time- and cost-efficient manner. NGS can, after removal of technical errors, yield an exceedingly detailed picture of the viral population structure. The widespread availability of cross-sectional data can be used to study fitness landscapes of viral populations in the quasispecies model. This chapter highlights methods that estimate the strength of selection in selective sweeps, assesses marginal fitness effects of quasispecies, and finally infers the fitness landscape of a viral quasispecies, all on the basis of NGS data.

Full-length haplotype reconstruction to infer the structure of heterogeneous virus populations

Next-generation sequencing (NGS) technologies enable new insights into the diversity of virus populations within their hosts. Diversity estimation is currently restricted to single-nucleotide variants or to local fragments of no more than a few hundred nucleotides defined by the length of sequence reads. To study complex heterogeneous virus populations comprehensively, novel methods are required that allow for complete reconstruction of the individual viral haplotypes. Here, we show that assembly of whole viral genomes of ∼8600 nucleotides length is feasible from mixtures of heterogeneous HIV-1 strains derived from defined combinations of cloned virus strains and from clinical samples of an HIV-1 superinfected individual. Haplotype reconstruction was achieved using optimized experimental protocols and computational methods for amplification, sequencing and assembly. We comparatively assessed the performance of the three NGS platforms 454 Life Sciences/Roche, Illumina and Pacific Biosciences for this task. Our results prove and delineate the feasibility of NGS-based full-length viral haplotype reconstruction and provide new tools for studying evolution and pathogenesis of viruses.

Transcriptomic analysis of Prunus domestica undergoing hypersensitive response to plum pox virus infection

Plum pox virus (PPV) infects Prunus trees around the globe, posing serious fruit production problems and causing severe economic losses. One variety of Prunus domestica, named ‘Jojo’, develops a hypersensitive response to viral infection. Here we compared infected and non-infected samples using next-generation RNA sequencing to characterize the genetic complexity of the viral population in infected samples and to identify genes involved in development of the resistance response. Analysis of viral reads from the infected samples allowed reconstruction of a PPV-D consensus sequence. De novo reconstruction showed a second viral isolate of the PPV-Rec strain. RNA-seq analysis of PPV-infected ‘Jojo’ trees identified 2,234 and 786 unigenes that were significantly up- or downregulated, respectively (false discovery rate; FDR≤0.01). Expression of genes associated with defense was generally enhanced, while expression of those related to photosynthesis was repressed. Of the total of 3,020 differentially expressed unigenes, 154 were characterized as potential resistance genes, 10 of which were included in the NBS-LRR type. Given their possible role in plant defense, we selected 75 additional unigenes as candidates for further study. The combination of next-generation sequencing and a Prunus variety that develops a hypersensitive response to PPV infection provided an opportunity to study the factors involved in this plant defense mechanism. Transcriptomic analysis presented an overview of the changes that occur during PPV infection as a whole, and identified candidates suitable for further functional characterization.

HIVE-hexagon: high-performance, parallelized sequence alignment for next-generation sequencing data analysis

Due to the size of Next-Generation Sequencing data, the computational challenge of sequence alignment has been vast. Inexact alignments can take up to 90% of total CPU time in bioinformatics pipelines. High-performance Integrated Virtual Environment (HIVE), a cloud-based environment optimized for storage and analysis of extra-large data, presents an algorithmic solution: the HIVE-hexagon DNA sequence aligner. HIVE-hexagon implements novel approaches to exploit both characteristics of sequence space and CPU, RAM and Input/Output (I/O) architecture to quickly compute accurate alignments. Key components of HIVE-hexagon include non-redundification and sorting of sequences; floating diagonals of linearized dynamic programming matrices; and consideration of cross-similarity to minimize computations.

AVAILABILITY

https://hive.biochemistry.gwu.edu/hive/

HIV-1 quasispecies delineation by tag linkage deep sequencing

Trade-offs between throughput, read length, and error rates in high-throughput sequencing limit certain applications such as monitoring viral quasispecies. Here, we describe a molecular-based tag linkage method that allows assemblage of short sequence reads into long DNA fragments. It enables haplotype phasing with high accuracy and sensitivity to interrogate individual viral sequences in a quasispecies. This approach is demonstrated to deduce ∼2000 unique 1.3 kb viral sequences from HIV-1 quasispecies in vivo and after passaging ex vivo with a detection limit of ∼0.005% to ∼0.001%. Reproducibility of the method is validated quantitatively and qualitatively by a technical replicate. This approach can improve monitoring of the genetic architecture and evolution dynamics in any quasispecies population.

Inference with viral quasispecies diversity indices: clonal and NGS approaches

Given the inherent dynamics of a viral quasispecies, we are often interested in the comparison of diversity indices of sequential samples of a patient, or in the comparison of diversity indices of virus in groups of patients in a treated versus control design. It is then important to make sure that the diversity measures from each sample may be compared with no bias and within a consistent statistical framework. In the present report, we review some indices often used as measures for viral quasispecies complexity and provide means for statistical inference, applying procedures taken from the ecology field. In particular, we examine the Shannon entropy and the mutation frequency, and we discuss the appropriateness of different normalization methods of the Shannon entropy found in the literature. By taking amplicons ultra-deep pyrosequencing (UDPS) raw data as a surrogate of a real hepatitis C virus viral population, we study through in-silico sampling the statistical properties of these indices under two methods of viral quasispecies sampling, classical cloning followed by Sanger sequencing (CCSS) and next-generation sequencing (NGS) such as UDPS. We propose solutions specific to each of the two sampling methods-CCSS and NGS-to guarantee statistically conforming conclusions as free of bias as possible.

CONTACT

josep.gregori@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

Comparison of illumina and 454 deep sequencing in participants failing raltegravir-based antiretroviral therapy

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.

Viral quasispecies assembly via maximal clique enumeration

Virus populations can display high genetic diversity within individual hosts. The intra-host collection of viral haplotypes, called viral quasispecies, is an important determinant of virulence, pathogenesis, and treatment outcome. We present HaploClique, a computational approach to reconstruct the structure of a viral quasispecies from next-generation sequencing data as obtained from bulk sequencing of mixed virus samples. We develop a statistical model for paired-end reads accounting for mutations, insertions, and deletions. Using an iterative maximal clique enumeration approach, read pairs are assembled into haplotypes of increasing length, eventually enabling global haplotype assembly. The performance of our quasispecies assembly method is assessed on simulated data for varying population characteristics and sequencing technology parameters. Owing to its paired-end handling, HaploClique compares favorably to state-of-the-art haplotype inference methods. It can reconstruct error-free full-length haplotypes from low coverage samples and detect large insertions and deletions at low frequencies. We applied HaploClique to sequencing data derived from a clinical hepatitis C virus population of an infected patient and discovered a novel deletion of length 357±167 bp that was validated by two independent long-read sequencing experiments. HaploClique is available at https://github.com/armintoepfer/haploclique. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5.

Comparison of three next-generation sequencing platforms for metagenomic sequencing and identification of pathogens in blood

Background

The introduction of benchtop sequencers has made adoption of whole genome sequencing possible for a broader community of researchers than ever before. Concurrently, metagenomic sequencing (MGS) is rapidly emerging as a tool for interrogating complex samples that defy conventional analyses. In addition, next-generation sequencers are increasingly being used in clinical or related settings, for instance to track outbreaks. However, information regarding the analytical sensitivity or limit of detection (LoD) of benchtop sequencers is currently lacking. Furthermore, the specificity of sequence information at or near the LoD is unknown.

Results

In the present study, we assess the ability of three next-generation sequencing platforms to identify a pathogen (viral or bacterial) present in low titers in a clinically relevant sample (blood). Our results indicate that the Roche-454 Titanium platform is capable of detecting Dengue virus at titers as low as 1X10^2.5 pfu/mL, corresponding to an estimated 5.4X10⁴ genome copies/ml maximum. The increased throughput of the benchtop sequencers, the Ion Torrent PGM and Illumina MiSeq platforms, enabled detection of viral genomes at concentrations as low as 1X10⁴ genome copies/mL. Platform-specific biases were evident in sequence read distributions as well as viral genome coverage. For bacterial samples, only the MiSeq platform was able to provide sequencing reads that could be unambiguously classified as originating from Bacillus anthracis.

Conclusion

The analytical sensitivity of all three platforms approaches that of standard qPCR assays. Although all platforms were able to detect pathogens at the levels tested, there were several noteworthy differences. The Roche-454 Titanium platform produced consistently longer reads, even when compared with the latest chemistry updates for the PGM platform. The MiSeq platform produced consistently greater depth and breadth of coverage, while the Ion Torrent was unequaled for speed of sequencing. None of the platforms were able to verify a single nucleotide polymorphism responsible for antiviral resistance in an Influenza A strain isolated from the 2009 H1N1 pandemic. Overall, the benchtop platforms perform well for identification of pathogens from a representative clinical sample. However, unlike identification, characterization of pathogens is likely to require higher titers, multiple libraries and/or multiple sequencing runs.

Sensitive deep-sequencing-based HIV-1 genotyping assay to simultaneously determine susceptibility to protease, reverse transcriptase, integrase, and maturation inhibitors, as well as HIV-1 coreceptor tropism

With 29 individual antiretroviral drugs available from six classes that are approved for the treatment of HIV-1 infection, a combination of different phenotypic and genotypic tests is currently needed to monitor HIV-infected individuals. In this study, we developed a novel HIV-1 genotypic assay based on deep sequencing (DeepGen HIV) to simultaneously assess HIV-1 susceptibilities to all drugs targeting the three viral enzymes and to predict HIV-1 coreceptor tropism. Patient-derived gag-p2/NCp7/p1/p6/pol-PR/RT/IN- and env-C2V3 PCR products were sequenced using the Ion Torrent Personal Genome Machine. Reads spanning the 3' end of the Gag, protease (PR), reverse transcriptase (RT), integrase (IN), and V3 regions were extracted, truncated, translated, and assembled for genotype and HIV-1 coreceptor tropism determination. DeepGen HIV consistently detected both minority drug-resistant viruses and non-R5 HIV-1 variants from clinical specimens with viral loads of ≥1,000 copies/ml and from B and non-B subtypes. Additional mutations associated with resistance to PR, RT, and IN inhibitors, previously undetected by standard (Sanger) population sequencing, were reliably identified at frequencies as low as 1%. DeepGen HIV results correlated with phenotypic (original Trofile, 92%; enhanced-sensitivity Trofile assay [ESTA], 80%; TROCAI, 81%; and VeriTrop, 80%) and genotypic (population sequencing/Geno2Pheno with a 10% false-positive rate [FPR], 84%) HIV-1 tropism test results. DeepGen HIV (83%) and Trofile (85%) showed similar concordances with the clinical response following an 8-day course of maraviroc monotherapy (MCT). In summary, this novel all-inclusive HIV-1 genotypic and coreceptor tropism assay, based on deep sequencing of the PR, RT, IN, and V3 regions, permits simultaneous multiplex detection of low-level drug-resistant and/or non-R5 viruses in up to 96 clinical samples. This comprehensive test, the first of its class, will be instrumental in the development of new antiretroviral drugs and, more importantly, will aid in the treatment and management of HIV-infected individuals.

Ultra-deep pyrosequencing (UDPS) data treatment to study amplicon HCV minor variants

We have investigated the reliability and reproducibility of HCV viral quasispecies quantification by ultra-deep pyrosequencing (UDPS) methods. Our study has been divided in two parts. First of all, by UDPS sequencing of clone mixes samples we have established the global noise level of UDPS and fine tuned a data treatment workflow previously optimized for HBV sequence analysis. Secondly, we have studied the reproducibility of the methodology by comparing 5 amplicons from two patient samples on three massive sequencing platforms (FLX+, FLX and Junior) after applying the error filters developed from the clonal/control study. After noise filtering the UDPS results, the three replicates showed the same 12 polymorphic sites above 0.7%, with a mean CV of 4.86%. Two polymorphic sites below 0.6% were identified by two replicates and one replicate respectively. A total of 25, 23 and 26 haplotypes were detected by GS-Junior, GS-FLX and GS-FLX+. The observed CVs for the normalized Shannon entropy (Sn), the mutation frequency (Mf), and the nucleotidic diversity (Pi) were 1.46%, 3.96% and 3.78%. The mean absolute difference in the two patients (5 amplicons each), in the GS-FLX and GS-FLX+, were 1.46%, 3.96% and 3.78% for Sn, Mf and Pi. No false polymorphic site was observed above 0.5%. Our results indicate that UDPS is an optimal alternative to molecular cloning for quantitative study of HCV viral quasispecies populations, both in complexity and composition. We propose an UDPS data treatment workflow for amplicons from the RNA viral quasispecies which, at a sequencing depth of at least 10,000 reads per strand, enables to obtain sequences and frequencies of consensus haplotypes above 0.5% abundance with no erroneous mutations, with high confidence, resistant mutants as minor variants at the level of 1%, with high confidence that variants are not missed, and highly confident measures of quasispecies complexity.

Comparison of next-generation sequencing and clone-based sequencing in analysis of hepatitis B virus reverse transcriptase quasispecies heterogeneity

We previously reported that, based on clone-based sequencing (CBS), hepatitis B virus (HBV) heterogeneity within the reverse transcriptase (RT) region was a predictor of antiviral efficacy. Here, by comparing ultradeep pyrosequencing (UDPS), i.e., next-generation sequencing (NGS), with CBS in characterizing the genetic heterogeneity of HBV quasispecies within the RT region, we evaluated the performance of UDPS in the analysis of HBV viral populations. HBV genomic DNA was extracted from serum samples from 31 antiviral treatment-naive patients with chronic hepatitis B. The RT region quasispecies were analyzed in parallel using CBS and UDPS. Characterization of quasispecies heterogeneity was conducted using bioinformatics analysis. Quasispecies complexity values were calculated with the formula Sn = -Σi(pilnpi)/lnN. The number of qualified strains obtained by UDPS was much larger than that obtained by CBS (P < 0.001). Pearson analysis showed that there was a positive correlation of quasispecies complexity values at the nucleotide level for the two methods (P < 0.05), while the complexity value derived from UDPS data was higher than that derived from CBS data (P < 0.001). Study of the prevalences of variations within the RT region showed that CBS detected an average of 9.7 ± 1.1 amino acid substitutions/sample and UDPS detected an average of 16.2 ± 1.4 amino acid substitutions/sample. The phylogenetic analysis based on UDPS data showed more genetic entities than did that based on CBS data. Viral heterogeneity determination by the UDPS technique is more sensitive and efficient in terms of low-abundance variation detection and quasispecies simulation than that by the CBS method, although imperfect, and thus sheds light on the future clinical application of NGS in HBV quasispecies studies.

Accurate single nucleotide variant detection in viral populations by combining probabilistic clustering with a statistical test of strand bias

Background

Deep sequencing is a powerful tool for assessing viral genetic diversity. Such experiments harness the high coverage afforded by next generation sequencing protocols by treating sequencing reads as a population sample. Distinguishing true single nucleotide variants (SNVs) from sequencing errors remains challenging, however. Current protocols are characterised by high false positive rates, with results requiring time consuming manual checking.

Results

By statistical modelling, we show that if multiple variant sites are considered at once, SNVs can be called reliably from high coverage viral deep sequencing data at frequencies lower than the error rate of the sequencing technology, and that SNV calling accuracy increases as true sequence diversity within a read length increases. We demonstrate these findings on two control data sets, showing that SNV detection is more reliable on a high diversity human immunodeficiency virus sample as compared to a moderate diversity sample of hepatitis C virus. Finally, we show that in situations where probabilistic clustering retains false positive SNVs (for instance due to insufficient sample diversity or systematic errors), applying a strand bias test based on a beta-binomial model of forward read distribution can improve precision, with negligible cost to true positive recall.

Conclusions

By combining probabilistic clustering (implemented in the program ShoRAH) with a statistical test of strand bias, SNVs may be called from deeply sequenced viral populations with high accuracy.

Using high-throughput sequencing to leverage surveillance of genetic diversity and oseltamivir resistance: a pilot study during the 2009 influenza A(H1N1) pandemic

BACKGROUND

Influenza viruses display a high mutation rate and complex evolutionary patterns. Next-generation sequencing (NGS) has been widely used for qualitative and semi-quantitative assessment of genetic diversity in complex biological samples. The "deep sequencing" approach, enabled by the enormous throughput of current NGS platforms, allows the identification of rare genetic viral variants in targeted genetic regions, but is usually limited to a small number of samples.

METHODOLOGY AND PRINCIPAL FINDINGS

We designed a proof-of-principle study to test whether redistributing sequencing throughput from a high depth-small sample number towards a low depth-large sample number approach is feasible and contributes to influenza epidemiological surveillance. Using 454-Roche sequencing, we sequenced at a rather low depth, a 307 bp amplicon of the neuraminidase gene of the Influenza A(H1N1) pandemic (A(H1N1)pdm) virus from cDNA amplicons pooled in 48 barcoded libraries obtained from nasal swab samples of infected patients (n  =  299) taken from May to November, 2009 pandemic period in Mexico. This approach revealed that during the transition from the first (May-July) to second wave (September-November) of the pandemic, the initial genetic variants were replaced by the N248D mutation in the NA gene, and enabled the establishment of temporal and geographic associations with genetic diversity and the identification of mutations associated with oseltamivir resistance.

CONCLUSIONS

NGS sequencing of a short amplicon from the NA gene at low sequencing depth allowed genetic screening of a large number of samples, providing insights to viral genetic diversity dynamics and the identification of genetic variants associated with oseltamivir resistance. Further research is needed to explain the observed replacement of the genetic variants seen during the second wave. As sequencing throughput rises and library multiplexing and automation improves, we foresee that the approach presented here can be scaled up for global genetic surveillance of influenza and other infectious diseases.

Whole-genome, deep pyrosequencing analysis of a duck influenza A virus evolution in swine cells

We studied the sub-population level evolution of a duck influenza A virus isolate during passage in swine tracheal cells. The complete genomes of the A/mallard/Netherlands/10-Nmkt/1999 strain and its swine cell-passaged descendent were analysed by 454 pyrosequencing with coverage depth ranging from several hundred to several thousand reads at any point. This allowed characterization of defined minority sub-populations of gene segments 2, 3, 4, 5, 7, and 8 present in the original isolate. These minority sub-populations ranged between 9.5% (for segment 2) and 46% (for segment 4) of their respective gene segments in the parental stock. They were likely contributed by one or more viruses circulating within the same area, at the same period and in the same or a sympatric host species. The minority sub-populations of segments 3, 4, and 5 became extinct upon viral passage in swine cells, whereas the minority sub-populations of segments 2, 7 and 8 completely replaced their majority counterparts. The swine cell-passaged virus was therefore a three-segment reassortant and also harboured point mutations in segments 3 and 4. The passaged virus was more homogenous than the parental stock, with only 17 minority single nucleotide polymorphisms present above 5% frequency across the whole genome. Though limited here to one sample, this deep sequencing approach highlights the evolutionary versatility of influenza viruses whereby they exploit their genetic diversity, predilection for mixed infection and reassortment to adapt to a new host environmental niche.

Next-generation sequencing technologies in diagnostic virology

The data deluge produced by next-generation sequencing (NGS) technologies is an appealing feature for clinical virologists that are involved in the diagnosis of emerging viral infections, molecular epidemiology of viral pathogens, drug-resistance testing, and also like to do some basic and clinical research. Indeed, NGS platforms are being implemented in many clinical and research laboratories, as the costs of these platforms are progressively decreasing. We provide here some suggestions for virologists who are planning to implement a NGS platform in their clinical laboratory and an overview on the potential applications of these technologies in diagnostic virology.

Sequencing approach to analyze the role of quasispecies for classical swine fever

Classical swine fever virus (CSFV) is a positive-sense RNA virus with a high degree of genetic variability among isolates. High diversity is also found in virulence, with strains covering the complete spectrum from avirulent to highly virulent. The underlying genetic determinants are far from being understood. Since RNA polymerases of RNA viruses lack any proof-reading activity, different genome variations called haplotypes, occur during replication. A set of haplotypes is referred to as a viral quasispecies. Genetic variability can be a fitness advantage through facilitating of a more effective escape from the host immune response. In order to investigate the correlation of quasispecies composition and virulence in vivo, we analyzed next-generation sequencing data of CSFV isolates of varying virulence. Viral samples from pigs infected with the highly virulent isolates "Koslov" and "Brescia" showed higher quasispecies diversity and more nucleotide variability, compared to samples of pigs infected with low and moderately virulent isolates.