Ribonucleic acid, or RNA, is an essential molecule in all known forms of life, acting as a messenger that carries genetic instructions from DNA to the cellular machinery responsible for building proteins. Their integrity directly impacts biological processes. For scientific experiments to yield reliable and accurate results, the RNA used must be of high quality. DV200 is a significant metric employed to assess this quality, particularly when dealing with challenging biological samples.
The Concept of RNA Quality
RNA quality in a biological context refers to the intactness, purity, and lack of degradation of RNA molecules within a sample. RNA molecules are less stable than DNA and susceptible to degradation by ribonucleases (RNases), enzymes present almost everywhere. Maintaining high RNA quality is important for the success of molecular biology experiments, such as those studying gene expression or performing sequencing. Degraded RNA fragments the molecular “blueprint,” potentially leading to inaccurate or misleading experimental outcomes.
Degraded RNA can lead to biased or incomplete results in experiments like RNA sequencing, skewing gene expression profiles and leading to incorrect conclusions. Therefore, assessing RNA integrity is an important step in many biological investigations, ensuring the reliability of subsequent analyses. Various metrics exist to evaluate RNA quality, each with its strengths depending on the sample type and downstream application.
What is the DV200 Metric?
DV200 quantifies the percentage of RNA fragments in a sample greater than 200 nucleotides in length. This metric addresses challenges in assessing RNA quality, especially when overall integrity scores like the RNA Integrity Number (RIN) are insufficient. The scientific rationale behind DV200 is that it focuses on the proportion of longer RNA fragments, which are more relevant for certain molecular applications.
The DV200 metric was developed by Illumina to improve RNA integrity assessment, especially for degraded samples where RIN values may not be sensitive or reliable predictors of successful library preparation, directly indicating the extent of fragmentation. This contrasts with metrics like RIN, which rely on the presence and ratio of ribosomal RNA peaks, frequently absent in highly degraded samples. The DV200 value is obtained by analyzing RNA samples using platforms like the LabChip GX Touch system or Agilent Bioanalyzer, where software calculates the percentage of fragments above 200 nucleotides.
Why DV200 is Essential for Specific Experiments
DV200 becomes an important quality metric for highly fragmented or degraded RNA samples. This includes Formalin-Fixed Paraffin-Embedded (FFPE) tissues, which undergo substantial chemical modification and RNA degradation during processing. Formalin fixation causes cross-linking between nucleic acids and proteins, degrading RNA transcripts into smaller fragments. DV200 is a reliable metric for assessing FFPE RNA quality, often surpassing traditional RIN scores.
A sufficient DV200 value is important for next-generation sequencing (NGS) library preparations, such as RNA-Seq or targeted sequencing, which rely on longer RNA fragments. For example, a DV200 of at least 50% is recommended for spatial transcriptomics using FFPE samples. Low DV200 values can lead to experimental failure or biased results, as shorter fragments may not be efficiently captured or sequenced, impacting gene expression analysis accuracy. While some hybridization assays tolerate lower DV200 values, the metric still offers valuable guidance for sequencing and library preparation.
Practical Interpretation of DV200 Values
Interpreting DV200 results involves understanding what different percentage values indicate about RNA quality and suitability for downstream applications. A higher DV200 percentage signifies better RNA quality, indicating a greater proportion of longer, more intact RNA fragments. For instance, a DV200 of 70% or higher is considered indicative of high-quality RNA, while values below 70% suggest increasing degradation.
Thresholds for acceptable DV200 values vary depending on the experiment or sequencing platform. For many next-generation sequencing applications, a DV200 value of at least 30% is considered suitable, although some protocols may recommend higher percentages, such as a DV200 of 50% or more for certain spatial gene expression libraries. Using RNA samples with a DV200 below 30% is not recommended for many sequencing applications, as it can lead to lower yields of sequencing libraries or reduced median transcripts per cell. In some cases, even samples with very low DV200 values, such as 8% to 16%, have been successfully used with optimized RNA-seq workflows, demonstrating that careful protocol adjustments can sometimes overcome severe degradation challenges.