The last two decades have been nothing short of revolutionary for biologists. Advances in computation, biochemistry, and high-throughput sequencing have unveiled an intricate molecular landscape that defies traditional views of genetic information flow. Biology, sometimes perceived as chaotic and unpredictable, has revealed an underlying order that challenges known paradigms. Nowhere is this more evident than in the expanding field of epitranscriptomics, which explores the native chemical modifications that regulate RNA.
These discoveries have prompted scientists to revisit the central dogma, which states that information flows from DNA to RNA to protein. Although this framework has long been foundational in molecular biology, it does not fully account for the complexity of gene regulation. It is now clear that modifications to both DNA and RNA play a critical role in determining how and when genetic instructions are executed. While the field of DNA modifications has received significant attention and investment, the study of RNA modifications, collectively known as the epitranscriptome, has advanced more slowly due to technical challenges. Nevertheless, researchers have identified more than 150 distinct RNA modifications across all domains of life, underscoring their evolutionary conservation and regulatory importance. These modifications function as molecular signals that influence RNA stability, localization, splicing, and translation efficiency (Roundtree et al., 2017).
This growing body of knowledge reflects a broader shift in how RNA is understood within molecular biology. Rather than serving solely as a messenger between DNA and protein, RNA is now recognized as a highly versatile molecule capable of storing genetic information, catalyzing biochemical reactions, and guiding complex molecular processes, such as those involved in CRISPR-based gene editing. The catalytic properties of RNA were first identified in the 1980s through the discovery of self-splicing RNA molecules, which supported the hypothesis that early life may have relied on RNA-based systems. Since that time, interest in RNA has accelerated, particularly in the development of RNA-based therapeutics including mRNA vaccines, antisense oligonucleotides, and small RNA regulators. Additionally, a large portion of the human genome is transcribed into noncoding RNAs whose biological functions remain poorly understood (Cech, 2024). Across all of these contexts—whether structural, catalytic, or regulatory—RNA modifications provide a crucial layer of control, modulating RNA behavior and expanding the functional landscape of the transcriptome.
The realization that RNA modifications are integral to cellular function has far-reaching implications for human health. Many of these modifications are dynamically regulated in response to environmental cues, developmental stages, and disease conditions. Disruptions in RNA modification pathways have been associated with cancer, neurodegenerative diseases, metabolic disorders, and immune dysfunction (Jonkhout et al., 2017). This growing interest and significance is obvious when looking at the year-over-year growth in the number of publications that mention “RNA modifications”.
In this article, we explore RNA immunoprecipitation (RIP), the most widely used and trusted method for RNA modification detection. We will discuss its role in establishing epitranscriptomics as a field, as well as its limitations as the field continues to evolve.
To this day, immunoprecipitation-based methods remains the most widely used technique in the field, with methylated RNA immunoprecipitation (MeRIP) targeting N6-methyladenosine (m6A) among the earliest and most influential approaches (Dominissini et al., 2012; Meyer et al., 2012). These initial studies, which focused primarily on m6A due to the limited availability of antibodies for other RNA modifications, helped answer several foundational questions. Notably, these seminal papers demonstrated that m6A is enriched within DRACH sequence motifs, particularly near distal exon and 3′ UTR junctions. These global methylation patterns have since become reference standards, routinely used to validate results in nearly every m6A-related publication, regardless of the detection method employed. A simple literature search using the keywords “RNA modifications” and “immunoprecipitation” highlights the continued prominence of antibody-based enrichment as a core methodology in epitranscriptomics research. For m6A specifically, this reliance is even more pronounced, with nearly half of all m6A publications also mentioning “immunoprecipitation.” However, this reliance is not as strong for other abundant modifications. Although antibodies for inosine, 5-methylcytosine (m5C), and pseudouridine (Ψ) are commercially available, they are used far less frequently. While multiple antibodies for m6A have been validated and are broadly trusted by the field, the same cannot be said for other modifications, where validation is limited and performance is often inconsistent. This discrepancy perhaps reflects a widely acknowledged limitation of the method: the antibody itself.
The biggest challenge with RIP is its dependence on antibodies, which are notoriously variable in specificity and sensitivity. While antibodies exhibit high specificity when binding larger epitopes, such as protein targets, generating antibodies with both high affinity and specificity for small molecules—like a single nucleobase—has long been a challenge. Even the most widely used antibodies for m6A detection can exhibit off-target binding, resulting in false positives. This issue is so prevalent that entire groups have dedicated themselves to developing algorithms to calibrate and distinguish true modification signals from background noise (Li et al., 2024). RNA’s intrinsic structure presents further challenges for immunoprecipitation-based approaches. Its highly structured and negatively charged nature can limit antibody access, particularly when secondary or tertiary folding masks modification sites (Oberdoeffer & Gilbert, 2024). This issue is compounded by the fact that antibodies are typically raised against single nucleobase haptens conjugated to carrier proteins, which do not accurately reflect the structural and electrostatic environment of native RNA (Feederle & Schepers, 2017).
The bidentate nature of antibodies also biases fragment enrichment; RNA fragments with dense clusters of the targeted modification tend to be captured more efficiently than those with sparse or isolated sites due to cooperative binding by both arms of the antibody. This enrichment bias contributes to false negatives and can further distort the apparent distribution of modifications across the transcriptome.
Lastly, the technique’s accessibility has been a double-edged sword; numerous iterations of MeRIP have been developed, with each lab or group favoring different antibody clones. This variability presents a major challenge for data reproducibility and consistency across the field as antibody clones can vary drastically in specificity and bias. There can be less than 60% overlap in detected modification sites between clones (Zheng et al., 2018; McIntyre et al., 2020). These inconsistencies are further complicated by batch effects, variation between antibody lots, and the discontinuation of specific clones used in earlier studies.
Although RIP has been foundational in shaping the field, its limitations in reproducibility, sensitivity, and specificity are becoming increasingly clear. As epitranscriptomics advances, so too must the tools we use to study it.