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Can You Sequence RNA with a RIN Score Below 7? The Truth About RNA Integrity

  • Writer: CLYTE research team
    CLYTE research team
  • 1 day ago
  • 6 min read
sequencing RNA with a RIN score below 7

In the high-stakes world of Next-Generation Sequencing (NGS), the RNA Integrity Number (RIN) is often treated as the ultimate gatekeeper. For years, the "Golden Rule" has been simple: if your RIN score is below 7, the sample is trash.

But what if your sample is a rare clinical biopsy, a precious ancient seed, or a unique environmental isolate? Do you really have to throw it away?

The short answer is no. While a RIN of 8–10 is ideal, modern sequencing technologies and library preparation strategies have made it entirely possible to generate high-quality data from RNA with RIN scores significantly lower than 7. This article dives deep into the science of RNA integrity, debunking the myths and offering actionable strategies for sequencing "less-than-perfect" samples.



What is the RIN Score and Why Does It Matter?

The RNA Integrity Number (RIN) is a metric developed by Agilent Technologies to standardize the assessment of RNA quality. Ranging from 1 (totally degraded) to 10 (completely intact), the RIN is calculated based on the electrophoretic trace of the RNA, specifically looking at the ratio of 28S to 18S ribosomal RNA (rRNA) bands.

  • RIN 10: Perfect, intact RNA.

  • RIN 7–9: High quality, suitable for almost all applications.

  • RIN 4–6: Partially degraded. Risk of 3' bias in standard protocols.

  • RIN < 4: Highly degraded. Requires specialized handling.


The "RIN 7" Myth

For standard PolyA-selection mRNA sequencing (Illumina), a RIN > 7 is recommended. This is because degradation typically starts at the 5' end of the transcript. If the RNA is fragmented, PolyA selection (which grabs the 3' tail) will only pull down the 3' end of the gene, leading to 3' bias and uneven coverage.

However, RIN is heavily biased toward rRNA integrity. In some organisms (like plants or bacteria) or specific tissue types, the rRNA might appear degraded while the mRNA of interest remains surprisingly stable.


When Can You Sequence with RIN < 7?

You can—and often should—sequence samples with lower RIN scores in the following scenarios:


1. MicroRNA (miRNA) Sequencing

If you are sequencing microRNAs (miRNAs), the RIN score is largely irrelevant.

  • Why? miRNAs are tiny (18–22 nucleotides). The degradation that lowers a RIN score affects long RNA molecules (like the 4000bp 28S rRNA). Small RNAs are naturally more stable and often survive conditions that destroy larger mRNAs.

  • Verdict: A RIN of 5 or 6 is often perfectly acceptable for small RNA sequencing.


2. FFPE and Clinical Samples

Formalin-Fixed Paraffin-Embedded (FFPE) tissues are notorious for degraded RNA, often yielding RIN scores of 2–3.

  • Strategy: Instead of RIN, look at the DV200 metric (the percentage of RNA fragments >200 nucleotides). If DV200 > 30%, you can usually get good data using specialized kits.


3. Rare or Irreplaceable Samples

A study on 1972 barley seeds (RIN ~2.5) demonstrated that valuable transcriptomic data could still be recovered. The researchers found that while the rRNA was degraded, the mRNA was intact enough to map reads to the genome.

  • Key Lesson: Don't toss a unique sample just because the bioanalyzer says "RIN 2.5."


How to Sequence Low-RIN Samples: The Strategies

If you are forced to work with RIN < 7, do not use a standard PolyA-selection kit. Use one of these alternatives:


1. Ribodepletion (rRNA Depletion)

This is the gold standard for low-quality RNA. Instead of pulling out good mRNA (PolyA), you subtract the bad stuff (rRNA).

  • Pros: Works on degraded RNA; keeps non-coding RNAs; no 3' bias.

  • Cons: More expensive than PolyA selection; requires more sequencing depth (reads).


2. 3' Tag Counting

If you only care about gene expression levels (counts) and not transcript structure (splice variants), 3' Tag Sequencing is a robust option.

  • Pros: Cheap; tolerant of degradation (since it only sequences the 3' tip anyway).

  • Cons: You lose isoform/splicing information.


3. Adjusting Fragmentation

For RIN < 6, the RNA is already fragmented. Standard protocols often include a chemical fragmentation step. Skip or reduce this step for low-RIN samples to prevent turning your RNA into unusable dust.


10 Ways to Improve Your RNA Isolation (Before You Sequence)

The best way to deal with low RIN is to prevent it. Here are top tips to boost your score:

  1. Speed is Life: Harvest and stabilize tissue immediately. Minutes matter.

  2. Flash Freeze: Use liquid nitrogen instantly. Do not let tissue sit in the tube.

  3. Use RNaseZap: Clean your bench, pipettes, and gloves. RNases are everywhere (skin, dust, bacteria).

  4. Correct Lysis Buffer Volume: Too much tissue + too little buffer = incomplete lysis and endogenous RNase activity.

  5. Cold Centrifugation: Perform all spins at 4°C unless the protocol explicitly says otherwise.

  6. Avoid "Gene-Drive": Don't thaw samples until you are ready to add lysis buffer.

  7. Precipitate Properly: Use GlycoBlue or similar carriers to see your pellet and avoid losing it.

  8. Check Your Water: Use only Nuclease-Free water for elution.

  9. Store at -80°C: Never store RNA at -20°C for long periods.

  10. Know Your Tissue: Pancreas and spleen are rich in RNases; they require more aggressive lysis/stabilization than liver or brain.


Conclusion

A RIN score below 7 is a warning, not a stop sign. While a "perfect" 10 is the goal, modern science often happens in the messy reality of RIN 4s and 5s. By choosing the right library preparation method—specifically ribodepletion over PolyA selection—and understanding your specific application (like miRNA vs. full mRNA), you can turn "failed" samples into publishable discoveries.

Always check the DV200 for degraded samples, and if your sample is truly one-of-a-kind, try sequencing it anyway. You might be surprised by what you find.




FAQ: Common Questions About RNA Integrity & Sequencing

What is a good RIN score for RNA-seq?

A "good" RIN score depends entirely on your library preparation method. For standard PolyA selection (typically used for eukaryotic mRNA), a RIN score of 7 or higher is considered good, with 8–10 being ideal. High integrity ensures you capture full-length transcripts and avoid 3' bias. However, for rRNA depletion (Ribodepletion) methods, a RIN score of 2–6 is often acceptable because this method does not rely on the poly-A tail, making it robust for degraded samples.

What is the minimum RNA for sequencing?

"Minimum RNA" can refer to either quality or quantity:

  • Quantity (Input Amount): Modern "low-input" or "ultra-low input" kits (like SMART-Seq) can work with as little as 10 pg to 10 ng of total RNA, sometimes even from a single cell. Standard kits usually require 100 ng to 1 µg.

  • Quality (RIN): For standard PolyA sequencing, the functional minimum is usually RIN 6–7. For Ribodepletion or 3' Tag counting, meaningful data can be generated from samples with RIN scores as low as 2 or 3 (often seen in FFPE tissues), provided the DV200 score (percentage of fragments >200nt) is adequate.

What is the RIN RNA threshold?

There is no single universal threshold, but here are the industry standards:

  • Threshold > 8: Required for high-quality genome assembly or full-length transcript studies.

  • Threshold > 7: The standard cutoff for cost-effective PolyA-selected mRNA sequencing.

  • Threshold < 7: Requires switching to Ribodepletion or gene-panel specific kits.

  • Threshold N/A: For miRNA (microRNA) sequencing, the RIN threshold is largely irrelevant because small RNAs are stable even when larger rRNAs degrade.

What is the RIN value 10?

A RIN value of 10 represents completely intact, perfect quality RNA. In a RIN 10 sample, the 18S and 28S ribosomal RNA bands are distinct and sharp, with a high 28S:18S ratio (usually near 2.0), and there is virtually no smear of degraded RNA between or below the bands. While desirable, a RIN of 10 is difficult to achieve in tissues rich in nucleases (like the pancreas) or clinical samples, and is not strictly necessary for generating excellent sequencing data.




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