RIP-qPCR (RNA immunoprecipitation qPCR) is a targeted assay that combines RNA immunoprecipitation with quantitative RT-PCR to confirm specific RNA–protein interactions in cells or tissues. CD Genomics provides an end-to-end RIP-qPCR service, from experimental design and antibody selection to qPCR data analysis and reporting, strictly for research use only.

RIP-qPCR (RNA immunoprecipitation qPCR) is a targeted assay used to confirm RNA–protein interactions in living cells or tissues. It combines RNA immunoprecipitation (RIP) with quantitative RT-PCR to measure how strongly a specific protein or RNA modification is enriched on defined transcripts, instead of just tracking global RNA levels.
In a RIP-qPCR experiment, an antibody captures an RNA-binding protein or a modification-marked RNA together with its bound RNAs. After RNA purification and reverse transcription, qPCR quantifies each candidate transcript in the RIP fraction relative to IgG and input controls. This focused, quantitative readout makes RIP-qPCR a natural follow-up to discovery methods such as RIP-seq or CLIP-seq when you need to confirm and prioritise key interactions.
By providing gene-level enrichment data, RIP-qPCR helps separate genuine binding events from simple expression changes. The resulting profiles give you clearer insight into post-transcriptional regulation and RNA epigenetics and can be used directly in figures, models, and reviewer responses.

RIP-qPCR follows a controlled workflow that preserves native RNA–protein complexes and produces reliable fold-enrichment values.
Cells or tissues are gently lysed in RNase-free buffer to release intact RNA–protein complexes while limiting RNA fragmentation.
A specific antibody against the target RNA-binding protein or RNA modification is added with Protein A/G beads. An IgG control is processed in parallel to capture non-specific background.
After washing away unbound components, proteins are digested and co-precipitated RNA is purified using column- or reagent-based methods under RNase-free conditions.
RNA from RIP, IgG, and input fractions is converted into cDNA by reverse transcription using standardised protocols.
qPCR assays for each candidate RNA are run across all fractions. The resulting Ct values are used to calculate relative enrichment and fold changes within and between conditions.
This stepwise RIP-qPCR protocol is optimized specifically for RNA–protein interaction analysis, helping to minimise non-specific binding and RNA degradation. In practice, this yields consistent enrichment patterns that can be compared across replicates, time points, and experimental groups.
You should consider RIP-qPCR when you already have candidate RNAs or proteins and need clear, quantitative evidence of their interactions. Instead of running another broad sequencing screen, RIP-qPCR lets you test a focused set of transcripts in defined biological contexts, especially in RNA biology and RNA epigenetics studies.
Transcriptome-wide methods such as RIP-seq, CLIP-seq, and RNA pull-down often produce long lists of potential binding targets. RIP-qPCR helps you decide which of these interactions are truly robust.
This targeted validation step turns discovery data into concise, gene-level evidence that reviewers and project teams can interpret quickly.
In RNA epigenetics, RIP-qPCR is a practical way to study how modifications such as m6A and ac4C affect specific transcripts.
These experiments are particularly relevant in immune regulation, antiviral immunity, and cancer models, where subtle changes in RNA modification can reshape pathway activity.
RIP-qPCR is well suited to comparative designs where interaction strength may change across conditions.
This type of analysis supports mode-of-action work and target validation in translational and drug discovery programs.
RIP-qPCR can be extended beyond mRNA to cover a broad range of RNA species, which is important in complex regulatory systems.
For infection biology, oncology, and systems-level RNA studies, this broader view offers more realistic insight than focusing on mRNA alone.
RIP-qPCR is one of several options for studying RNA–protein interactions. It is most useful when you already know which transcripts you care about and need focused, quantitative validation rather than another discovery-scale experiment.
| Method | Main Question | Scale | Typical Output | Best Used For |
|---|---|---|---|---|
| RIP-qPCR | Does this protein/modification bind these specific RNAs? | Targeted (tens of genes) | Ct values, fold enrichment for selected transcripts | Validating candidates, comparing conditions, mechanism panels |
| RIP-seq | Which RNAs are associated with this protein? | Genome-wide | Enriched transcript lists, peak profiles | Discovery of binding targets and pathways |
| CLIP-seq (and variants) | Where on the RNA does the protein bind? | Genome-wide, nucleotide-level | Crosslink sites, binding maps | High-resolution binding site mapping |
| RNA pull-down | Which proteins bind this specific RNA or RNA motif? | Proteome-level | Protein ID lists (often by MS) | Discovering protein partners of one RNA |
In many projects, RIP-qPCR sits at the validation and mechanism stage, complementing earlier sequencing-based screens rather than replacing them.
Choosing a RIP-qPCR service means trusting a partner with both your samples and your hypotheses. CD Genomics is set up to support projects that move from broad RNA–protein interaction discovery to focused, quantitative validation, without adding extra work to your team.
We handle the full RNA immunoprecipitation qPCR workflow, from design to data. You provide cells or tissue and your target list; we take care of buffer selection, RIP conditions, qPCR setup, and analysis.
This helps you move faster from candidate interactions to validated results that can go into figures and decision decks.
RIP experiments are sensitive to antibodies, lysis conditions, and wash steps. To stabilise performance, we use commercial RIP kits and standardised protocols where possible, then adapt them to your system only as needed.
These design choices help lower the risk of failed pulls or misleading enrichment caused by non-specific binding.
RIP-qPCR is only useful if the final data are easy to interpret and share. Our reporting focuses on clear, quantitative summaries suited to manuscripts, presentations, and internal reviews.
You receive a dataset that can be dropped directly into your own analysis pipeline or converted into figure panels with minimal editing.
Good RIP-qPCR starts with good design. Our scientists work with you to align antibody choice, target selection, and replicates with your research questions.
This reduces the risk of redesigning experiments mid-project and helps ensure that your RIP-qPCR service run answers the questions you actually care about.
Our RIP-qPCR workflow is built as a straightforward service pipeline. You send us cells or tissue with your questions and target list; we handle the lab work and data processing under standardised, research-use-only conditions.
1. Project Consultation and Assay Design
We start with a short technical discussion to align the experiment with your goals. Together we define the RNA-binding protein or modification, select target and control transcripts, and agree on species, sample types, and biological replicates.
2. Sample Receipt and Initial QC
When your samples arrive, we log and verify them, checking identity, amount, and storage conditions. If needed, we perform small pilot checks to confirm that the material is suitable for RIP-qPCR before proceeding.
3. RIP Experiment (Lysis and Immunoprecipitation)
We perform gentle lysis and RNA immunoprecipitation using optimized buffers, commercial RIP reagents, and your chosen antibody, with IgG and input processed in parallel. The focus is to preserve native RNA–protein complexes while keeping background low and conditions consistent across all samples.
4. RNA Purification and cDNA Preparation
After immunoprecipitation, we purify RNA from RIP, IgG, and input fractions and convert it into cDNA using standardised reverse transcription protocols. This provides clean, comparable templates for downstream qPCR.
5. Quantitative RT-qPCR
We run qPCR assays for your selected targets and controls with technical replicates across all fractions. The resulting Ct values form the quantitative backbone for calculating enrichment and comparing conditions.
6. Data Analysis and Reporting
Finally, we transform raw qPCR outputs into interpretable RIP-qPCR results. You receive Ct tables, fold-enrichment summaries, and key plots, along with concise methods and QC notes, plus the option to discuss the data with our scientists for interpretation and next-step planning.
Note: Detailed protocol-level steps (lysis, IP, purification, cDNA, qPCR) are described conceptually in the earlier "How Does RIP-qPCR Work?" section; here the emphasis is on how CD Genomics organises and manages the service around your project.

RIP-qPCR data analysis turns raw Ct values into quantitative measures of RNA–protein interaction strength. At CD Genomics, we use a standardised pipeline to check assay quality, apply appropriate normalisation, and summarise enrichment so you can compare genes and conditions with confidence.
Only data that pass these checks are used for downstream enrichment calculations.
Normalisation and Fold-Enrichment Calculation
This expresses binding as fold enrichment, making it clear which RNAs are truly associated with the target protein or modification.
Comparative Analysis and Summaries
These outputs give you a transparent link from qPCR data to interaction profiles that are ready for figures, internal reviews, or follow-up experiments.
You receive a compact, ready-to-use data package at the end of each RIP-qPCR project.
Example RIP-qPCR Ct values for a target gene.
RIP-qPCR amplification plot showing multiple qPCR fluorescence curves and Ct points across PCR cycles
RIP-qPCR melt curve confirming assay specificity
| Sample Type | Recommended Minimum Input per Condition | Notes |
|---|---|---|
| Cultured cells | ≥ 5 × 10⁸ cells | Adherent or suspension cell lines or primary cells |
| Tissue (fresh-frozen) | ≥ 500 mg | Animal or human research tissue |
| Other (e.g. organoids, special samples) | Case by case | Please contact us for feasibility |
Storage and Shipping Guidelines
Sound RIP-qPCR data starts with a simple but well-planned design. We help you set up basic controls, replicates, and primers so enrichment values are easy to interpret.
These controls separate true RNA–protein interactions from background and expression changes.
Processing all conditions in parallel helps reduce batch effects.
We can support primer and target selection for mRNA, lncRNA, circRNA, and viral RNA according to your study goals.
References
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