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Accelerating Research by Quantifying RNA Integrity

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As the mediator between DNA-based genetic information and protein synthesis, RNA (ribonucleic acid) plays a key role in cell activity. That's why researchers are using RNA to detect the underlying molecular mechanisms of health problems such as cancer and cardiovascular disease.

For these scientists, the quality of their experiments—and the resulting conclusions—depends on the integrity of the RNA samples they use. Several variables can affect sample quality. As an example, RNA resides in living cells taken from biological samples that are as unique as the individual donors who provide them. What's more, RNA begins to deteriorate at the moment of extraction and its condition depends on factors such as the health of the donor, the elapsed time between removal and preservation, and the storage method.

An assessment of RNA integrity is a critical first step in obtaining meaningful gene expression data. Many labs use subjective, qualitative methods to assess RNA quality before an experiment. This provides helpful guidance but cannot ensure the repeatability or reproducibility of a study. A quantitative approach to quality control would provide an objective way to assess, document and describe RNA integrity—and accelerate research into diagnostics and therapeutics.

Impairing research and results

The absence of sound quantitative measures impacts research in several ways. For one, it hinders the sharing of data and methods between labs. It also limits the reproducibility of the methods and results researchers submit to peer-reviewed publications. In addition, the lack of metrics makes it difficult to submit verifiable data to regulatory agencies such as the US Food and Drug Administration, and this slows the application of RNA-based methods to clinical studies.

The lack of integrity metrics also affects results. As an example, differences in RNA quality can cause a study to provide a false indication of biological differences between samples. Further, a qualitative assessment does little to help researchers distinguish variations in the biological samples from methodological variations.

Quantifying RNA integrity

Traditional qualitative approaches rely on ribosomal ratios, which are typically evaluated via visual inspection of slab gel results. Microfluidics-based (bioanalyzer) alternatives can show greater detail, such as the size distribution of RNA fragments, and deliver a numerical value for the ribosomal ratio. However, when using the Agilent 2100 bioanalyzer, researchers found that the ribosomal ratio does not provide an adequate description of RNA integrity.

 example RIN results 
Example RIN results: When testing an identical RNA sample in various dilutions, identical RINs are obtained (within narrow limits); however, the ribosomal ratios show a much lesser degree of reproducibility.

To help standardize the interpretation of RNA integrity, Agilent has introduced a new tool for RNA assessment. The RNA integrity number (RIN) measures RNA quality and grades it on a quantitative scale of 1 (poor) to 10 (high). RIN is based on a software algorithm that works with the 2100 bioanalyzer and Agilent RNA 6000 Nano LabChip® kit. This method enables scientists to measure the integrity of total RNA samples from eukaryotic organisms.

The application note "RNA Integrity Number (RIN) – Standardization of RNA Quality Control" describes the software algorithm in detail. The algorithm was developed using neural networks and adaptive learning in conjunction with a large database of eukaryote total RNA samples (mainly human, rat and mouse). As shown in the application note, the RIN value is highly independent of the amount of RNA used and the origin of the eukaryote RNA sample.

Utilizing RIN scores

A RIN score provides an objective measure of RNA quality, but it does not predefine an "acceptable" level of quality. Over time, the research and medical communities may define those standards through scientific papers, and it's likely the resulting standards will be specific to sample type and experiment type.

Within the industry, reagent companies could potentially use the RIN scale to measure and market the quality of their RNA samples. Their customers could also use RIN to assess sample quality upon receipt and just prior to an experiment.

These are a few examples of the RIN tool's value. By eliminating the arbitrary, subjective classification of total RNA, RIN is a major step forward in the standardization of RNA integrity assessment. Ultimately, its quantitative values can improve the reproducibility and comparison of RNA-based experiments between instruments, between labs and across the research community.

For more information

To learn more—and to download the RIN software—please visit the RIN page in the Lab-on-a-Chip section of our Web site. You can also download a cover story from Genomics & Proteomics magazine and read what David Ginzinger, John Quackenbush, Janet Warrington and many other researchers think about this new approach to RNA quality assessment. For additional information about these and other Agilent life sciences products and resources, please visit the Life Sciences/Chemical Analysis main page.

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