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Mild M, Hedskog C, Jernberg J, Albert J
PLoS ONE 6 (7) e22741 [2011-07-25; online 2011-07-25]
Ultra-deep pyrosequencing (UDPS) has been used to detect minority variants within HIV-1 populations. Some aspects of the quality and reproducibility of UDPS have been previously evaluated, but comprehensive studies are still needed. In this study the UDPS technology (FLX platform) was evaluated by analyzing a 120 base pair fragment of the HIV-1 pol gene from plasma samples from two patients and artificial mixtures of molecular clones. UDPS was performed using an optimized experimental protocol and an in-house data cleaning strategy. Nine samples and mixtures were analyzed and the average number of reads per sample was 19,404 (range 8,858-26,846). The two patient plasma samples were analyzed twice and quantification of viral variants was found to be highly repeatable for variants representing >0.27% of the virus population, whereas some variants representing 0.11-0.27% were detected in only one of the two UDPS runs. Bland-Altman analysis showed that a repeated measurement would have a 95% likelihood to lie approximately within ±0.5 log(10) of the initial estimate. A similar level of agreement was observed for variant frequency estimates in forward vs. reverse sequencing direction, but here the agreement was higher for common variants than for rare variants. UDPS following PCR amplification with alternative primers indicated that some variants may be incorrectly quantified due to primer-related selective amplification. Finally, the in vitro recombination rate during PCR was evaluated using artificial mixtures of clones and was found to be low. The most abundant in vitro recombinant represented 0.25% of all UDPS reads. This study demonstrates that this UDPS protocol results in low experimental noise and high repeatability, which is relevant for future research and clinical use of the UDPS technology. The low rate of in vitro recombination suggests that this UDPS system can be used to study genetic variants and mutational linkage.
NGI Stockholm (Genomics Applications)
NGI Stockholm (Genomics Production)
National Genomics Infrastructure
PubMed 21799940
DOI 10.1371/journal.pone.0022741
Crossref 10.1371/journal.pone.0022741
pii: PONE-D-11-01646
pmc: PMC3143174