Correction of sequence-dependent ambiguous bases (Ns) from the 454 pyrosequencing system

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• 16S ribosomal RNA (16S) gene pyrosequencing is a key method for microbial diversity assessment.
• Pyrosequencing reads with ambiguous bases (Ns) are typically discarded, potentially introducing bias.
• Previous assumptions suggested Ns arise from non-sequence-dependent, high error rates.

Purpose of the Study:

• To investigate if Ns in pyrosequencing reads occur in a sequence-dependent manner.
• To develop and validate a method for correcting sequence-dependent N errors.
• To assess the impact of N correction on microbial community analysis and genome sequencing.

Main Methods:

• Analysis of pyrosequencing reads and flow value data to identify N error patterns.
• Development of an algorithm to correct Ns based on identified sequence-specific patterns.
• Application of the N correction algorithm to 16S, bphD, and nifH amplicon reads from mock and soil communities, and metagenome data.

Main Results:

• Pyrosequencing N errors exhibit a sequence-dependent pattern, often following homopolymers.
• The developed algorithm corrected a high percentage of Ns in amplicon reads (16S: 86.54%, bphD: 81.37%, nifH: 81.55%) with high precision.
• N correction reduced taxonomic biases in amplicon and shotgun sequencing data, improving accuracy.

Conclusions:

• Ns in pyrosequencing are not random but follow predictable, sequence-dependent patterns.
• A novel algorithm effectively corrects these Ns, enhancing the precision of microbial community analysis.
• This method improves the accuracy of 16S rRNA gene sequencing and broader genomic applications using pyrosequencing data.