Methodology article

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

Andreas Schroeder^1,3 , Odilo Mueller² , Susanne Stocker^1,4 , Ruediger Salowsky¹ , Michael Leiber¹ , Marcus Gassmann¹ , Samar Lightfoot² , Wolfram Menzel⁵ , Martin Granzow⁶ and Thomas Ragg⁶

¹Agilent Technologies, Hewlett-Packard-Strasse 8, 76337 Waldbronn, Germany.

²Agilent Technologies, 5301 Stevens Creek Blvd., Santa Clara, CA 95051, USA

³ABP, Schiphol Boulevard 239, 1118 BH Schiphol. The Netherlands.

⁴Roche Diagnostics GmbH, Nonnenwald 2, 82372 Penzberg, Germany.

⁵Universität Karlsruhe, ILKD, Am Fasanengarten 5, 76131 Karlsruhe, Germany.

⁶quantiom bioinformatics GmbH & Co. KG, Ringstrasse 61, 76356 Weingarten, Germany.

author email corresponding author email

BMC Molecular Biology 2006, 7:3doi:10.1186/1471-2199-7-3

Published:	31 January 2006

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.