Determinants of RNA Integrity and Purity

RNA quality is a critical determinant for the success of many downstream applications, including microarray analysis. For this reason, if you are planning microarray analysis experiments, it is important to fully consider the factors that affect the quality of your RNA.

Tissue-Specific Responses to Injury Affect RNA Integrity
Traditionally, efforts to preserve RNA quality have focused on methods of tissue storage and disruption, with the goal of minimizing RNase activity. However, a more critical determinant is actually the RNA quality within tissues before the RNA expression pattern is 'frozen' by preservation. RNA integrity within the cell is dependent on a complex series of responses that are set in motion in response to insult, as well as the interval between the time of injury and tissue preservation. The mechanisms of RNA degradation can be both complex and varied, as is the resulting impact on the mRNA population. Therefore, no matter how carefully you prepare your RNA, the integrity is often determined before the tissue sample reaches your hands.

Residual Contaminants --
The Hidden RNA Quality Factor
Even the most intact RNA will not perform well if the sample contains trace contaminants. The most detrimental contaminants are residual organics, metals, and proteins such as nucleases. RNA that contains these impurities will perform poorly in most enzymatic applications.

Residual contaminants are most often a problem in RNA isolated with single-step organic extraction protocols. Although relatively fast and easy, single-step extraction may not be sufficient to remove contaminants from some tissues, especially if you exceed the recommendation for input sample amount. Organic contaminants are often carried over into samples during aqueous phase transfer; to avoid this, leave some of the aqueous phase behind during phase separation.

We recommend a combination of phenol based and solid phase extraction methods to avoid this inadvertent carryover of contaminants. Several studies have shown that RNA isolated by a combination of both techniques provides superior array data than RNA isolated by either method alone (1-3). Figure 1 compares the Agilent 2100 bioanalyzer profiles of RNA isolated with a single-step organic extraction method to RNA further purified using solid phase extraction with Ambion's MEGAclear™ Kit. In overnight stability tests, the 28S:18S rRNA ratio of the RNA isolated by the single-step protocol decreased 32% when incubated at 37°C compared to the control stored at ­20°C (compare Figure 1, Panels A and B), indicating the presence of residual contaminants in the RNA. However, no change in the rRNA ratio was observed between the MEGAclear-purified samples stored at ­20°C and 37°C (compare Panels C and D). These data illustrate the negative impact of residual contaminants on RNA integrity and their potential to inhibit downstream enzymatic applications. Therefore, if your RNA was obtained using a one-step method and has not performed well, we recommend the use of MEGAclear as a fast and convenient solid phase clean-up method.

Figure 1. A Combination of Single Step Organic Extraction and Solid Phase RNA Extraction Improves RNA Quality. RNA was extracted either using single phase organic extraction (A, B) or single phase organic extraction followed by purification with Ambion's MEGAclear Kit (C, D). The RNA was stored overnight at either ­20ºC (A, C) or 37ºC (B, D).

Removing Genomic DNA and Small RNAs
Other contaminants that can affect total RNA performance in downstream applications are residual DNA contamination and small RNAs such as 5S and tRNAs. Residual genomic DNA contamination is most problematic in tissues with high cell densities, such as spleen or tissue culture cells. Figure 2 shows examples of gross contamination with genomic DNA. High molecular weight genomic DNA typically migrates as a broad, larger molecular weight peak that is well separated from rRNA peaks (Panel A). Note, also, that the base-line is high in this electropherogram: this is generally a signature of underlying genomic DNA contamination. Genomic DNA that has been partially sheared can sometimes migrate between the 18S and 28S rRNA ribosomal bands (Panel B), making it difficult to accurately determine the rRNA ratio. Incomplete DNase I digestion can generate small molecular weight DNA fragments between 50­200 bases in size (Panel C). The most common causes of incomplete DNA digestion are residual contaminants (high salt, residual organics, etc) that inhibit enzyme activity, or the use of an insufficient amount of DNase I. To efficiently remove genomic DNA, we recommend treating your samples with Ambion's TURBO DNase™, a DNase I with improved activity. MEGAclear can also be used to rapidly purify RNA following DNase I treatment.

Figure 2. Different Types of Genomic DNA Contamination In Total RNA Preparations. Agilent 2100 bioanalyzer electropherograms of RNA contaminated with high molecular weight genomic DNA (A), partially sheared genomic DNA (B), and small DNA fragments generated by incomplete DNase I digestion (C).

Small RNAs, such as 5S and tRNAs, are efficiently recovered in organic extraction methods but are depleted in column-based purification methods (compare Panels A and C, and Panels B and D in Figure 1). At Ambion, we have found that total RNA samples in which small RNAs have been removed by solid phase extraction (following organic extraction) show superior performance in RNA amplification compared to RNA isolated by organic extraction only. Since small RNAs can comprise as much as 15% of total RNA, their removal effectively increases the percent of mRNA within the total RNA sample and decreases the potential for interference during cDNA synthesis.

The rRNA Ratio Should Not Be Used as the Sole Indicator of mRNA Quality
The 28S:18S rRNA ratio has traditionally been viewed as the primary indicator of RNA quality, with a ratio of 2.0 considered to be indicative of high quality, intact RNA. However, with widespread use of the Agilent 2100 bioanalyzer, it has become increasingly clear that the long time standard of a 2.0 rRNA ratio is difficult to meet, especially in RNA derived from clinical samples. This has led researchers to question the wisdom of using the ratio of the 28S and 18S rRNAs, two highly structured and long-lived molecules, as the sole measure of the quality of the underlying mRNA. At Ambion, we find that total RNAs with 28S:18S rRNA ratios of 1.0 or greater usually provide high quality intact mRNA, and perform well in a variety of applications.

One way to extrapolate information about sample integrity is to carefully evaluate the baseline in the bioanalyzer electropherogram. In high quality RNA (rRNA ratio near 2.0), the baseline above and below the 18S and 28S rRNA peaks will be relatively flat. As the 28S rRNA breaks down, the degradation products will cause the baseline between and below the 18S and 28S rRNA peaks to rise. The 18S and 28S rRNAs will appear to be riding on top of the baseline.

As a cautionary note, some total RNAs will often contain classes of small RNAs that may initially appear to be breakdown products but are actually abundant tissue-specific mRNAs (Figure 3). These abundant small RNAs are most often found in RNA isolated from reproductive and intestinal tissues. Their fluorescence can sometimes dwarf that of the rRNAs. Generally, they can be distinguished from degradation products because the rRNA ratio of the sample will be greater than 1.0 and the baseline between the small RNAs and the 18S RNA will be relatively low.

Figure 3. Low Baseline Fluorescence Indicates Good RNA Quality. (A) Partially degraded total RNA. The 28:18S rRNA ratio is 0.9 and the baseline fluorescence is elevated both between the 28S and 18S and below the 18S, making the rRNA peaks appear to be riding on top of the baseline. (B) Human intestinal RNA containing abundant small RNAs. This sample can be distinguished from partially degraded RNA by the relatively high 28S:18S rRNA ratio, and the relatively low baseline both between the 28S and 18S peaks, and immediately below the 18S peak.

Our data suggest that, aside from integrity, trace contaminants may be the largest contributor to poor performance in sensitive enzymatic applications such as amplification for microarray analysis. Most often impurities interfere with cDNA synthesis steps, resulting in reduced size and yield of aRNA following in vitro transcription. In fact, a recent study on the impact of moderate RNA degradation on microarray analysis suggests that while the loss of the 5' end of transcripts results in higher ratios of hybridization to 3' end probes than 5' end probes, the number of genes detected or differentially expressed is not significantly reduced (4). Stated simply, RNA quality can be defined as the sum of RNA integrity and RNA purity. Many researchers are finding that their application may be tolerant of some loss in RNA integrity, as long as their RNA is free of residual contaminants.

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