April 11, 2025
RNA sequencing (RNA-Seq) is a powerful and widely used method for transcriptome profiling. It provides comprehensive insights into gene expression, alternative splicing, and non-coding RNA. However, RNA-Seq analysis requires high-quality RNA samples to ensure accurate and reliable results.
According to Nanodrop, a 260/280 ratio of ~2.0 and a 260/230 ratio between 1.8–2.2 indicate RNA purity, which is a critical measure of RNA quality. A low 260/230 ratio can indicate contamination and, consequently, affect RNA-Seq analysis.
This article delves into the specifics of how a low 260/230 ratio impacts RNA-Seq data quality, focusing on contamination sources, their consequences on data integrity, and strategies to mitigate these issues.
The 260/230 ratio is an optical density (OD) ratio, determined by measuring absorbance at wavelengths 260 nm and 230 nm. RNA absorbs UV light at 260 nm, and contaminants typically absorb at 230 nm. The ratio is used as an indicator of RNA purity.
The recommended 260/230 ratio for RNA samples is typically 2.0 - 2.2. Ratios below this range suggest the presence of contaminants such as phenol, guanidine isothiocyanate, or other organic solvents.
A high 260/230 ratio implies that the RNA is free from contaminants that absorb at 230 nm. Low ratios, on the other hand, may point to contamination from substances used during RNA extraction or storage.
Several common contaminants contribute to low 260/230 ratios in RNA samples. These contaminants can come from reagents used in RNA extraction, improper handling of samples, or storage conditions.
A. Organic Contaminants
A study on RNA extraction methods from the COMET biobank highlights how contaminants like guanidine isothiocyanate and phenol, which absorb at 230 nm, lead to low 260/230 ratios.
These contaminants interfere with RNA purity and affect downstream applications like RNA-Seq. The study confirms that proper sample preparation is essential to ensure accurate RNA-Seq results by minimizing contamination.
B. Salt Contamination
Salt residues, particularly from buffer solutions used in RNA extraction, can affect the 260/230 ratio. These salts absorb at 230 nm and may result in inaccurate RNA quality assessments. High salt concentrations in RNA samples can interfere with the efficiency of reverse transcription or affect the quality of RNA-Seq reads.
C. DNA Contamination
While DNA contamination primarily affects the 260/280 ratio (due to its strong absorbance at 260 nm), in some cases, residual genomic DNA can contribute to a low 260/230 ratio. The DNA could potentially interfere with RNA-Seq analysis, especially in transcriptomic studies aimed at profiling RNA expression.
A low 260/230 ratio often signifies the presence of contaminants that can significantly impact RNA-Seq outcomes. This section explores the impact of low 260/230 ratios on enzymatic processes, transcript detection sensitivity, quantification metrics, and RNA integrity. These factors are crucial for ensuring high-quality, reproducible RNA-Seq data.
Enzymatic reactions form the core of RNA-Seq, and contaminants associated with low 260/230 ratios can disrupt these processes, leading to inefficient reactions and compromised results.
Reverse transcription is the first critical step in RNA-Seq, where RNA is converted into complementary DNA (cDNA) to serve as the template for subsequent amplification and sequencing. Reverse transcriptase enzymes, essential for this process, are particularly sensitive to contamination.
Guanidine thiocyanate, a chaotropic agent frequently used in RNA extraction, is known to absorb at 230 nm and can denature reverse transcriptase enzymes. Even trace amounts of guanidine thiocyanate in RNA samples can significantly impair the reverse transcription process by hindering the enzyme's activity. This leads to inefficient cDNA synthesis and incomplete representation of the transcriptome.
When RNA samples with low 260/230 ratios are subjected to RT, the resulting cDNA yield is often significantly lower than that obtained from high-purity samples. Contaminants reduce the reverse transcriptase efficiency, leading to incomplete or biased cDNA synthesis.
This not only diminishes the overall cDNA yield but also affects the diversity of transcripts captured, particularly low-abundance transcripts that are more susceptible to incomplete reverse transcription. Incomplete cDNA libraries result in underrepresentation of certain genes or transcript isoforms in the final dataset.
Polymerase chain reaction (PCR) amplification is used to increase the amount of cDNA for sequencing. Contaminants in RNA samples, particularly organic solvents like phenol, can interfere with the activity of the DNA polymerases required for PCR.
These organic contaminants, which absorb at 230 nm, inhibit the amplification process by affecting polymerase function. As a result, the efficiency of PCR amplification is reduced, and certain transcripts may be preferentially amplified while others are suppressed, leading to amplification bias.
Studies show that RNA samples with low 260/230 ratios often display elevated cycle threshold (Ct) values in quantitative PCR (qPCR). Higher Ct values reflect the need for more amplification cycles to detect the target product, indicating that the amplification efficiency is compromised due to contaminants.
This bias leads to inaccurate gene expression quantification, as the relative abundance of transcripts in the sample is not properly captured. The presence of contaminants skews the representation of gene expression, potentially leading to false positives or false negatives.
The ability of RNA-Seq to detect weakly expressed transcripts is one of its key advantages. However, low 260/230 ratios can significantly impair the sensitivity of RNA-Seq, making it difficult to detect low-abundance transcripts, such as long non-coding RNAs (lncRNAs), that are highly sensitive to RNA quality.
RNA-Seq relies on the efficient conversion of RNA into cDNA and its subsequent amplification and sequencing. Contaminants that lower the 260/230 ratio can inhibit these processes, leading to a loss of sensitivity in detecting weakly expressed transcripts.
For example, contaminants can introduce background noise or interfere with the binding of sequencing primers to the cDNA, reducing the efficiency of amplification and sequencing. This becomes particularly problematic when studying low-abundance RNA species, where every transcript needs to be detected with high sensitivity.
In RNA samples with low 260/230 ratios, the ability to detect weakly expressed transcripts diminishes, leading to incomplete transcriptomic profiles. This issue is exacerbated when studying long non-coding RNAs (lncRNAs), which are typically present at low levels and require high-quality RNA for accurate detection.
Low 260/230 ratios cause reduced amplification and sequencing of these RNAs, resulting in underrepresentation in the transcriptomic data. As a result, important regulatory molecules like lncRNAs may be overlooked, significantly limiting the scope of the study.
In a study on RNA sequencing from skin lesions, researchers found that low RNA quality, indicated by low 260/230 ratios, hindered the detection of long non-coding RNAs (lncRNAs). Contaminants in RNA samples reduced the sensitivity of RNA-Seq, leading to underrepresentation of these important regulatory molecules. This highlights the critical need for high-quality RNA to detect low-abundance transcripts accurately.
lncRNAs have gained increasing attention due to their regulatory roles in gene expression, chromatin remodeling, and cell signaling. However, they are typically present at very low levels, making their detection in RNA-Seq experiments challenging.
Low RNA quality, indicated by a low 260/230 ratio, can severely impact the detection of these molecules. Contaminants hinder the efficient synthesis of cDNA from lncRNAs, causing these molecules to be poorly represented or completely missed during sequencing.
The detection of lncRNAs in RNA-Seq data relies heavily on high-quality RNA. When RNA purity is compromised by contaminants, the amplification and sequencing of lncRNAs are inefficient, leading to incomplete transcriptomic profiles. This results in the loss of critical biological information, especially when studying the regulatory mechanisms of non-coding RNAs in diseases or developmental processes.
Accurate quantification of gene expression is a fundamental goal of RNA-Seq. However, low 260/230 ratios introduce significant variability into quantification metrics, particularly in the normalization process.
Normalization is crucial for controlling technical variability and ensuring that gene expression measurements are comparable across different samples. Typically, housekeeping genes are used as internal controls for normalization, assuming their expression remains stable across conditions.
However, when RNA samples have low 260/230 ratios, contaminants can affect the expression levels of housekeeping genes themselves, leading to skewed normalization results.
Contaminants can interfere with the expression of housekeeping genes, making them unreliable for normalization purposes. For instance, residual phenol or guanidine isothiocyanate may alter the expression of commonly used housekeeping genes like GAPDH, β-actin, or TBP, leading to erroneous conclusions.
As a result, normalization strategies relying on these genes become compromised, and gene expression levels can be misinterpreted.
Contaminants that lower the 260/230 ratio often introduce variability in the amplification process, leading to inconsistent cycle threshold (Ct) values in qPCR and RNA-Seq. High Ct values indicate inefficient amplification, which can make it difficult to quantify gene expression accurately.
RNA samples with low 260/230 ratios often exhibit higher Ct values, reflecting reduced amplification efficiency due to contaminants. This increased variability makes it difficult to compare gene expression across samples and conditions, undermining the reliability of the RNA-Seq data.
Furthermore, this variability complicates downstream analyses, such as differential gene expression studies, which rely on precise and reproducible quantification of transcript levels.
Library preparation is a critical step in RNA-Seq, where RNA is converted into cDNA, fragmented, and adapted for sequencing. RNA samples with low 260/230 ratios face several challenges during library preparation, which can impact the depth and quality of sequencing data.
For RNA-Seq, sequencing adapters must be ligated to the cDNA fragments to allow amplification and sequencing. When RNA samples have low 260/230 ratios, the ligation of these adapters becomes inefficient.
This results in poor library complexity, with fewer cDNA fragments available for sequencing. The reduced library complexity directly impacts the depth of sequencing, leading to incomplete transcriptomic profiles.
Low RNA purity leads to inefficient adapter ligation, reducing the overall complexity of the sequencing library. This results in fewer reads for each transcript, which reduces the depth of sequencing and limits the ability to detect low-abundance or rare transcripts. Incomplete libraries also complicate downstream analyses, such as differential gene expression or transcript isoform identification, leading to biased results.
Additionally, RNA sequencing will remain an essential part of monitoring vaccine efficacy and safety. Biostate AI makes RNA sequencing accessible at an unmatched scale and cost. Offering total RNA-Seq services for all sample types—such as FFPE tissue, blood, and cell cultures—it covers everything from RNA extraction to sequencing and data analysis.
This end-to-end service ensures high-quality results, which is essential for large-scale research and clinical applications, particularly when handling RNA samples with low 260/230 ratios that require expert purification and precise library preparation.
Sequencing platforms often implement stringent quality control (QC) measures to ensure that only high-quality samples are used for sequencing. RNA samples with low 260/230 ratios are more likely to fail these QC checks, leading to their exclusion from sequencing pipelines.
Low-quality RNA samples that fail QC checks due to low 260/230 ratios are often excluded from sequencing, wasting valuable biological material and limiting the scope of the experiment. In some cases, RNA may need to be re-extracted or purified, causing delays and increasing costs.
The RNA Integrity Number (RIN) is a widely used metric for assessing RNA integrity, with scores ranging from 1 (degraded RNA) to 10 (intact RNA). Low 260/230 ratios often correlate with poor RIN scores, indicating that RNA integrity has been compromised during extraction or handling.
A low 260/230 ratio is often accompanied by lower RIN scores, which suggest that RNA degradation has occurred, particularly in the 28S and 18S rRNA bands. RNA degradation significantly impacts the reliability of RNA-Seq data, as fragmented RNA leads to incomplete transcript coverage and biased quantification.
Poor RIN scores (typically below 7) are associated with degraded RNA, which cannot produce reliable sequencing results. Degraded RNA leads to missing or fragmented transcript data, reducing the completeness of gene expression profiles. For RNA-Seq to provide accurate results, it is essential that RNA samples maintain high integrity, as indicated by both RIN and 260/230 ratios.
To avoid the issues associated with low 260/230 ratios, it is important to follow best practices during RNA extraction, purification, and handling. Ensuring high RNA purity will minimize the impact of contaminants on RNA-Seq analysis.
In this context, RNA sequencing platforms like Biostate AI offer comprehensive RNA-Seq services, covering RNA extraction, library preparation, sequencing, and data analysis.
Biostate AI's affordable, end-to-end service streamlines the entire RNA-Seq process, making it more accessible and efficient for researchers working on both large-scale studies and more targeted research applications.
The expert services ensure that RNA samples, particularly those at risk of contamination, are handled optimally for reliable and reproducible sequencing results.
Over-drying RNA samples can degrade RNA and introduce contaminants. RNA should be stored at -80°C in a buffer that protects it from degradation and contamination. This helps preserve RNA integrity and maintains the 260/230 ratio within the ideal range.
Low 260/230 ratios in RNA samples represent contamination that can have profound effects on RNA-Seq analysis, with contaminants like guanidine thiocyanate and phenol interfering with critical processes. This issue leads to incomplete cDNA synthesis, biased amplification, and reduced detection of weakly expressed transcripts, ultimately compromising data quality.
As RNA-Seq technology advances, the importance of addressing low 260/230 ratios grows. By optimizing RNA extraction protocols and performing rigorous quality control, researchers can ensure high-quality data.
Biostate AI empowers researchers with an end-to-end RNA-Seq solution, offering optimized tools for sample preparation, quality control, and data analysis. This comprehensive platform ensures reliable, reproducible, and accurate RNA-Seq results, helping both academic and clinical researchers gain deeper insights into transcriptomic data.
The information present in this article is provided only for informational purposes and should not be interpreted as medical advice. Treatment strategies, including those related to gene expression and regulatory mechanisms, should only be pursued under the guidance of a qualified healthcare professional.
Always consult a healthcare provider or genetic counselor before making decisions about your research or any treatments based on gene expression analysis.
1. What is the importance of the A260/A280 and A260/A230 ratios?
The A260/A280 ratio is used to assess protein contamination in RNA, with a value around 2.0 indicating pure RNA. A lower value suggests protein contamination. The A260/A230 ratio measures contamination from organic solvents like phenol or guanidine, with a value between 1.8–2.2 indicating clean RNA. Both ratios are essential for ensuring RNA purity before applications like RNA-Seq or PCR.
2. What does a 260/280 ratio lower than 1.8 indicate about the RNA isolate?
A 260/280 ratio lower than 1.8 suggests contamination by proteins or phenol. This indicates that the RNA isolate may have residual contamination, compromising its purity. Such low ratios may impair downstream applications like cDNA synthesis and amplification.
3. How to remove salt contamination from RNA?
Salt contamination in RNA can be removed through ethanol precipitation, where ethanol and sodium acetate are added to the RNA sample, followed by centrifugation and washing with 70% ethanol. However, in high-throughput labs, silica-column or magnetic bead cleanups are more commonly used as scalable alternatives for RNA purification. The cleaned RNA is then resuspended in RNase-free water or buffer for further analysis.
