RNA Quality Assessment with the Agilent Automated Electrophoresis Systems

Importance of the Topic

Reliable evaluation of total RNA integrity is essential for molecular biology and genomics workflows. Fragment degradation or contamination can compromise downstream applications such as sequencing, qPCR and gene expression profiling. Automated electrophoresis platforms simplify and standardize RNA quality assessment by providing objective metrics to guide sample acceptance or further processing.

Study Objectives and Overview

This technical comparison assessed three Agilent automated electrophoresis systems – the 2100 Bioanalyzer, the 5200 Fragment Analyzer and the 4200 TapeStation – across four total RNA sources: human heart, mouse, corn and Escherichia coli. Intact and heat-degraded aliquots of each sample were run in triplicate to compare RNA quality numbers: the RNA Integrity Number (RIN), the RNA Quality Number (RQN) and the RIN equivalent (RINe).

Methodology and Instrumentation

• Sample preparation: Four RNA types were diluted to 200 ng per microliter. Intact samples were compared to thermally degraded counterparts.
• Bioanalyzer system: Employed microfluidic RNA 6000 Nano kits and eukaryote, plant or prokaryote assays depending on sample origin. Metric reported: RIN.
• Fragment Analyzer system: Used capillary electrophoresis with an RNA kit covering 200 to 6000 nucleotides. Metric reported: RQN.
• TapeStation system: Loaded ScreenTape devices in 16 lanes for up to 96 samples. Metric reported: RINe.
• Software settings: Eukaryotic, plant or prokaryotic RNA type selections were applied to match sample biology.

Main Results and Discussion

All three platforms generated comparable electropherogram profiles showing ribosomal peaks (18S/28S in eukaryotes, 16S/23S in prokaryotes, plus chloroplast rRNAs in plant samples) and a fast region indicative of small RNA fragments. Degraded samples exhibited reduced large-rRNA peak areas, elevated fast region signals and increased inter-peak smearing. Despite differences in separation technology, average quality scores for intact samples clustered around 7 to 9 for all platforms and sample types, with coefficients of variation below 3 percent. Degraded samples consistently scored 5 to 7, confirming each system’s ability to track integrity loss.

Benefits and Practical Applications

• Interchangeable metrics: RIN, RQN and RINe values align closely, enabling cross-laboratory comparisons.
• High throughput: Each system supports automated analysis of small volumes from 1 to 96 samples per run.
• Objective QC: Digital electropherograms and quality numbers reduce subjectivity in sample selection for sequencing and other sensitive assays.
• Broad applicability: Suitable for human, animal, plant and microbial total RNA evaluations.

Future Trends and Opportunities

Integration of automated electrophoresis into end-to-end sample processing will continue to accelerate. Advances in microfluidic and capillary design may further reduce assay time and sample requirements. Machine learning approaches applied to electropherogram patterns could refine quality scoring and detect specific degradation pathways. Expansion of combined DNA and RNA integrity assessments on a single platform may streamline nucleic acid workflows.

Conclusion

This study demonstrates that Agilent’s 2100 Bioanalyzer, 5200 Fragment Analyzer and 4200 TapeStation systems produce consistent and precise RNA integrity measurements across diverse sample types. Researchers can select any of these platforms with confidence that RIN, RQN or RINe values will be interchangeable for reliable quality control in genomics research.

References

1. Comparison of RIN and RQN for the Agilent 2100 Bioanalyzer and the Fragment Analyzer Systems Agilent Technologies technical overview publication number 5994-1860 2020
2. RNA Integrity Number RIN Standardization of RNA Quality Control Agilent Technologies application note publication number 5989-1165 2016
3. Quality Analysis of Eukaryotic Total RNA with the Agilent 5200 Fragment Analyzer System Agilent Technologies application note publication number 5994-0519 2019