Challenges with using primer IDs to improve accuracy of next generation sequencing

Area of Science:

• Molecular Biology
• Virology
• Genomics

Background:

• Next-generation sequencing (NGS) technologies, including ultra-deep pyrosequencing (UDPS), enable detailed analysis of complex biological populations like RNA viruses.
• Sequencing and sample preparation introduce errors, limiting the accuracy of UDPS for investigating viral populations.

Purpose of the Study:

• To evaluate the efficacy of the Primer ID methodology in mitigating errors during UDPS of RNA viruses.
• To assess the impact of Primer ID tagging on the accuracy and reliability of consensus sequence generation.

Main Methods:

• The Primer ID methodology was applied to 257,846 UDPS reads from an HIV-1 plasmid clone and patient plasma samples.
• Each cDNA molecule was tagged with an 11-nucleotide random Primer ID before PCR and sequencing.
• Consensus sequences were generated from reads sharing identical Primer IDs (minimum of three occurrences).

Main Results:

• The number of consensus sequences obtained was low, even with a high number of input molecules, due to skewed resampling frequencies.
• PCR errors within Primer IDs led to an overestimation of the number of unique templates sequenced.
• Some consensus sequences contained errors attributed to UDPS error hotspots and PCR errors in Primer IDs.

Conclusions:

• The Primer ID methodology has the potential to enhance the accuracy of deep sequencing for complex viral populations.
• Further optimization is needed to achieve more even resampling frequencies and to effectively identify and eliminate artefactual consensus sequences caused by PCR errors in Primer IDs.