Ultra-deep mutant spectrum profiling: improving sequencing accuracy using overlapping read pairs

作者：Chen Harris Haiyin^*; Borucki Monica K; Torres Clinton; Slezak Tom R; Allen Jonathan E

来源：BMC Genomics, 2013, 14(1): 96.

DOI：10.1186/1471-2164-14-96

• Quasispecies
• Viral evolution
• DNA mutational analysis
• High-throughput sequencing
• Diagnostics
• Biomarker
• Rare mutations
• Sequencing error correction
• Overlapping read pairs

Backgound: High throughput sequencing is beginning to make a transformative impact in the area of viral evolution. Deep sequencing has the potential to reveal the mutant spectrum within a viral sample at high resolution, thus enabling the close examination of viral mutational dynamics both within- and between-hosts. The challenge however, is to accurately model the errors in the sequencing data and differentiate real viral mutations, particularly those that exist at low frequencies, from sequencing errors.
Results: We demonstrate that overlapping read pairs (ORP) - generated by combining short fragment sequencing libraries and longer sequencing reads - significantly reduce sequencing error rates and improve rare variant detection accuracy. Using this sequencing protocol and an error model optimized for variant detection, we are able to capture a large number of genetic mutations present within a viral population at ultra-low frequency levels (<0.05%).
Conclusions: Our rare variant detection strategies have important implications beyond viral evolution and can be applied to any basic and clinical research area that requires the identification of rare mutations.

• 出版日期2013-2-12