Efficient analysis of sgRNA and its impurities

Reliable analysis of single guide RNA (sgRNA) is essential for ensuring high-quality results in CRISPR-Cas genome editing. However, analysis can be challenging due to its relatively large size (~100 nucleotides) and the presence of closely related impurities such as n–1 or n+1 variants. A new Application Note based on data by Belgium-based Quality Assistance SA presents an effective approach using ion-pair reversed-phase HPLC combined with the bioinert YMC Accura Triart Bio C18 column.

Bioinert hardware for reproducible analysis

RNA molecules tend to interact with metal surfaces, leading to adsorption, analyte loss, and carry-over. Additionally, sgRNA can form complex secondary structures depending on temperature, salt concentration, and pH, which can affect chromatographic behaviour. The bioinert coating of the YMC Accura column minimises these interactions and ensures reliable, reproducible results.

Optimised phase for large biomolecules

The wide-pore stationary phase of the YMC Accura Triart Bio C18 column is specifically designed for large biomolecules such as oligonucleotides. It enables efficient mass transfer, resulting in improved peak shapes and high-resolution separations. Clear separation of full-length sgRNA from closely related truncation impurities is achieved, even when differences in length are minimal.

Consistent performance and high sensitivity

The method demonstrates consistent performance across a range of concentrations, maintaining high resolution even at low sample levels. Blank runs confirm the absence of carry-over, highlighting the effectiveness of the bioinert system in preventing non-specific interactions—an important factor for routine analytical workflows.

High-resolution impurity profiling

Multiple impurity species, including n–1, n–2, and n–5 variants, are successfully resolved in a single run and clearly distinguished from full-length sgRNA. This enables accurate impurity profiling and supports a deeper understanding of sample quality.

Overall, this approach provides robust, sensitive, and reproducible sgRNA analysis, supporting confident quality assessment in gene editing workflows.

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