Real-Time Selective Sequencing with RUBRIC: Read Until with Basecall and Reference-Informed Criteria

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Nanopore sequencing offers real-time data analysis.
• Selective sequencing aims to enrich target molecules and reduce background noise.
• Existing methods like pattern-matching Read Until have limitations.

Purpose of the Study:

• To introduce and evaluate RUBRIC, a novel real-time selective sequencing method.
• To demonstrate RUBRIC's ability for on-line basecalling and alignment-based decision making.
• To assess RUBRIC's performance across various parameters and sample types.

Main Methods:

• Utilized the Oxford MinION nanopore sequencer.
• Implemented RUBRIC for real-time selective sequencing based on on-line basecalling and alignment.
• Tested RUBRIC on mixed human/bacteria samples and CRISPR/Cas9-cut DNA.
• Developed a generalized model for performance estimation.

Main Results:

• RUBRIC enables real-time selective sequencing by actively rejecting non-informative DNA.
• On-line basecalling allows alignment against references for sequence/reject decisions.
• RUBRIC demonstrated effectiveness in background depletion and target enrichment.
• Performance was evaluated across diverse sample compositions and computational setups.

Conclusions:

• RUBRIC represents a significant advancement in real-time selective nanopore sequencing.
• The method offers a powerful tool for targeted sequencing applications.
• RUBRIC's performance can be modeled and optimized for specific experimental needs.