Accuracy and quality of massively parallel DNA pyrosequencing

TLDR

Massively parallel pyrosequencing improves sequencing efficiency, yet the Roche GS20’s per‑base accuracy is only ~96%, and unlike genome projects, microbial diversity studies cannot rely on redundant consensus assemblies to correct errors. The study aimed to empirically determine the per‑base error rate of the Roche GS20 system. This was achieved by tag‑sequencing the V6 hypervariable region of cloned microbial ribosomal DNA. The authors found that unassembled GS20 reads achieve 99.5% accuracy, and filtering low‑quality reads raises accuracy to ≥99.75%, exceeding traditional capillary sequencing.

Abstract

Abstract Background Massively parallel pyrosequencing systems have increased the efficiency of DNA sequencing, although the published per-base accuracy of a Roche GS20 is only 96%. In genome projects, highly redundant consensus assemblies can compensate for sequencing errors. In contrast, studies of microbial diversity that catalogue differences between PCR amplicons of ribosomal RNA genes (rDNA) or other conserved gene families cannot take advantage of consensus assemblies to detect and minimize incorrect base calls. Results We performed an empirical study of the per-base error rate for the Roche GS20 system using sequences of the V6 hypervariable region from cloned microbial ribosomal DNA (tag sequencing). We calculated a 99.5% accuracy rate in unassembled sequences, and identified several factors that can be used to remove a small percentage of low-quality reads, improving the accuracy to 99.75% or better. Conclusion By using objective criteria to eliminate low quality data, the quality of individual GS20 sequence reads in molecular ecological applications can surpass the accuracy of traditional capillary methods.