The RIN: an RNA integrity number for assigning integrity values to RNA measurements

TLDR

RNA integrity is critical for accurate gene‑expression profiling, yet the commonly used 28S:18S ribosomal RNA ratio has proven inconsistent, leaving no reliable standard for assessing sample quality. The study aims to develop an automated, high‑throughput method to unambiguously estimate RNA integrity using microcapillary electrophoretic separation. By automatically extracting features from electropherogram signals and applying Bayesian regression models, the authors trained an algorithm on Agilent 2100 bioanalyzer data to quantify RNA integrity. The resulting algorithm yields a user‑independent RNA integrity number (RIN) that reliably standardizes quality control and outperforms traditional ratio‑based approaches by integrating multiple electropherogram regions.

Abstract

Abstract Background The integrity of RNA molecules is of paramount importance for experiments that try to reflect the snapshot of gene expression at the moment of RNA extraction. Until recently, there has been no reliable standard for estimating the integrity of RNA samples and the ratio of 28S:18S ribosomal RNA, the common measure for this purpose, has been shown to be inconsistent. The advent of microcapillary electrophoretic RNA separation provides the basis for an automated high-throughput approach, in order to estimate the integrity of RNA samples in an unambiguous way. Methods A method is introduced that automatically selects features from signal measurements and constructs regression models based on a Bayesian learning technique. Feature spaces of different dimensionality are compared in the Bayesian framework, which allows selecting a final feature combination corresponding to models with high posterior probability. Results This approach is applied to a large collection of electrophoretic RNA measurements recorded with an Agilent 2100 bioanalyzer to extract an algorithm that describes RNA integrity. The resulting algorithm is a user-independent, automated and reliable procedure for standardization of RNA quality control that allows the calculation of an RNA integrity number (RIN). Conclusion Our results show the importance of taking characteristics of several regions of the recorded electropherogram into account in order to get a robust and reliable prediction of RNA integrity, especially if compared to traditional methods.