Dataset Information

Next-generation sequencing of HIV-1 RNA genomes: determination of error rates and minimizing artificial recombination.

ABSTRACT: Next-generation sequencing (NGS) is a valuable tool for the detection and quantification of HIV-1 variants in vivo. However, these technologies require detailed characterization and control of artificially induced errors to be applicable for accurate haplotype reconstruction. To investigate the occurrence of substitutions, insertions, and deletions at the individual steps of RT-PCR and NGS, 454 pyrosequencing was performed on amplified and non-amplified HIV-1 genomes. Artificial recombination was explored by mixing five different HIV-1 clonal strains (5-virus-mix) and applying different RT-PCR conditions followed by 454 pyrosequencing. Error rates ranged from 0.04-0.66% and were similar in amplified and non-amplified samples. Discrepancies were observed between forward and reverse reads, indicating that most errors were introduced during the pyrosequencing step. Using the 5-virus-mix, non-optimized, standard RT-PCR conditions introduced artificial recombinants in a fraction of at least 30% of the reads that subsequently led to an underestimation of true haplotype frequencies. We minimized the fraction of recombinants down to 0.9-2.6% by optimized, artifact-reducing RT-PCR conditions. This approach enabled correct haplotype reconstruction and frequency estimations consistent with reference data obtained by single genome amplification. RT-PCR conditions are crucial for correct frequency estimation and analysis of haplotypes in heterogeneous virus populations. We developed an RT-PCR procedure to generate NGS data useful for reliable haplotype reconstruction and quantification.

SUBMITTER: Di Giallonardo F

PROVIDER: S-EPMC3776835 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Next-generation sequencing of HIV-1 RNA genomes: determination of error rates and minimizing artificial recombination.

Di Giallonardo Francesca F Zagordi Osvaldo O Duport Yannick Y Leemann Christine C Joos Beda B Künzli-Gontarczyk Marzanna M Bruggmann Rémy R Beerenwinkel Niko N Günthard Huldrych F HF Metzner Karin J KJ

PloS one 20130918 9

Next-generation sequencing (NGS) is a valuable tool for the detection and quantification of HIV-1 variants in vivo. However, these technologies require detailed characterization and control of artificially induced errors to be applicable for accurate haplotype reconstruction. To investigate the occurrence of substitutions, insertions, and deletions at the individual steps of RT-PCR and NGS, 454 pyrosequencing was performed on amplified and non-amplified HIV-1 genomes. Artificial recombination wa ...[more]

PMID: 24058534

Similar Datasets

Project description:BackgroundClinical implementation of Next-Generation Sequencing (NGS) is challenged by poor control for stochastic sampling, library preparation biases and qualitative sequencing error. To address these challenges we developed and tested two hypotheses.MethodsHypothesis 1: Analytical variation in quantification is predicted by stochastic sampling effects at input of a) amplifiable nucleic acid target molecules into the library preparation, b) amplicons from library into sequencer, or c) both. We derived equations using Monte Carlo simulation to predict assay coefficient of variation (CV) based on these three working models and tested them against NGS data from specimens with well characterized molecule inputs and sequence counts prepared using competitive multiplex-PCR amplicon-based NGS library preparation method comprising synthetic internal standards (IS). Hypothesis 2: Frequencies of technically-derived qualitative sequencing errors (i.e., base substitution, insertion and deletion) observed at each base position in each target native template (NT) are concordant with those observed in respective competitive synthetic IS present in the same reaction. We measured error frequencies at each base position within amplicons from each of 30 target NT, then tested whether they correspond to those within the 30 respective IS.ResultsFor hypothesis 1, the Monte Carlo model derived from both sampling events best predicted CV and explained 74% of observed assay variance. For hypothesis 2, observed frequency and type of sequence variation at each base position within each IS was concordant with that observed in respective NTs (R2 = 0.93).ConclusionIn targeted NGS, synthetic competitive IS control for stochastic sampling at input of both target into library preparation and of target library product into sequencer, and control for qualitative errors generated during library preparation and sequencing. These controls enable accurate clinical diagnostic reporting of confidence limits and limit of detection for copy number measurement, and of frequency for each actionable mutation.

Project description:BackgroundAccumulating evidence implicates mitochondrial DNA (mtDNA) alleles, which are independent of the nuclear genome, in disease, especially in human metabolic diseases. However, this area of investigation has lagged behind in researching the nuclear alleles in complex traits, for example, in gout.MethodsNext-generation sequencing was utilized to investigate the relationship between mtDNA alleles and phenotypic variations in 52 male patients with gout and 104 age-matched male non-gout controls from the Taiwan Biobank whole-genome sequencing samples. Differences from a reference sequence (GRCh38) were identified. The sequence kernel association test (SKAT) was applied to identify gout-associated alleles in mitochondrial genes. The tools Polymorphism Phenotyping, Sorting Intolerant From Tolerant (SIFT), Predict the pathology of Mutations (PMUT), Human Mitochondrial Genome Database (mtDB), Multiple Alignment using Fast Fourier Transform (MAFFT), and Mammalian Mitochondrial tRNA Genes (Mamit-tRNA) were used to evaluate pathogenicity of alleles. Validation of selected alleles by quantitative polymerase chain reaction of single nucleotide polymorphisms (qPCR SNPs) was also performed.ResultsWe identified 456 alleles in patients with gout and 640 alleles in non-gout controls with 274 alleles shared by both. Mitochondrial genes were associated with gout, with MT-CO3, MT-TA, MT-TC, and MT-TT containing potentially pathogenic gout-associated alleles and displaying evidence of gene-gene interactions. All heteroplasmy levels of potentially pathogenic alleles exceeded metabolic thresholds for pathogenicity. Validation assays confirmed the next-generation sequencing results of selected alleles. Among them, potentially pathogenic MT-CO3 alleles correlated with high-density lipoprotein (HDL) levels (P?=?0.034).ConclusionThis study provided two scientific insights. First, this was the most extensive mitochondrial genomic profiling associated with gout. Second, our results supported the roles of mitochondria in gout and HDL, and this comprehensive analysis framework can be applied to other diseases in which mitochondrial dysfunction has been implicated.

Dataset Information

Next-generation sequencing of HIV-1 RNA genomes: determination of error rates and minimizing artificial recombination.

Publications

Next-generation sequencing of HIV-1 RNA genomes: determination of error rates and minimizing artificial recombination.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets