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Circular RNAs (circRNAs) are a class of covalently closed non-coding RNAs formed through back-splicing. Lacking both 5' caps and 3' poly(A) tails, circRNAs exhibit exceptional stability, with half-lives often exceeding 48 hours—significantly longer than most linear mRNAs (~10 hours). In recent years, the number and functional diversity of circRNAs have been rapidly revealed; for instance, the circBase database catalogs over 170,000 human circRNAs, highlighting their prevalence in the transcriptome. Emerging clinical studies suggest circRNAs hold considerable potential in precision medicine and drug development.
Figure 1. Classification and diverse functions of circRNAs.(Bagheri Moghaddam M, et al., 2022)
CircRNA detection is challenging due to the lack of poly(A) tails and overlap with linear transcripts, requiring back-splice junction-specific probes. While RNA-seq enables novel circRNA discovery, microarrays provide a cost-effective, high-throughput, and reproducible platform for sensitive genome-wide quantification of known circRNAs, supporting functional studies, biomarker discovery, and drug development.
Leveraging advanced microarray platforms, Creative Biogene provides a high-sensitivity, high-specificity, and customizable one-stop circRNA expression profiling service. We handle the complete workflow—from RNA quality control to data analysis and interpretation—ensuring accurate, reliable results while delivering biologically and clinically meaningful insights.
For low-input samples, optimized RNA extraction and enrichment strategies ensure sensitivity and accuracy.
| Array Type | Format | Detectable circRNAs | Database Source |
| Human circRNA Array-V2.0 | 8 × 15K | 13,600 | circBase |
| Mouse circRNA Array-2.0 | 8 × 15K | 14,200 | circBase |
| Rat circRNA Array-2.0 | 8 × 15K | 14,100 | circBase |
| Human circRNA Microarray-V2.0 | 4 × 180K | 170,340 | circBase |
Custom array design is also available to meet species-specific or study-specific requirements.
Creative Biogene provides end-to-end support, including qPCR/primer design, Sanger validation, circRNA pulldown/RIP/luciferase assays, custom circRNA vectors and intervention molecules, and targeted panels integrating miRNA/mRNA, forming a complete "network-evidence chain." For further information about our circRNA microarray service, please feel free to contact us.
Q1: Can circRNA microarray profiling be performed with limited sample amounts?
A: Yes. For tissue or cell samples, we recommend ≥1 µg total RNA, RIN ≥7.0, and OD260/280 of 1.9–2.1 for robust, reproducible signals. For low-RNA body fluids (serum, plasma), 1–2 mL starting material is generally sufficient. RNase R enrichment can improve circRNA detection. Ultra-low input samples can be evaluated for low-input enhanced protocols. All samples should be stored at –80°C after collection, avoiding repeated freeze-thaw cycles. Detailed sample collection and shipping guidelines are provided.
Q2: How does circRNA microarray compare with RNA sequencing?
A: RNA-seq excels at discovering novel circRNAs but is more complex, costly, and less stable for low-abundance quantification. circRNA microarrays use junction-spanning probes for stable, reproducible quantification across large cohorts, with excellent sensitivity and dynamic range, especially suitable for differential expression screening. Often, RNA-seq is used for exploratory discovery, followed by microarray or qPCR validation.
Q3: How many replicates are recommended to ensure reliable results?
A: Typically, at least three biological replicates per group are recommended for statistical power. For heterogeneous samples, additional replicates may be needed. Internal controls and spike-ins correct for signal variation. Standardized protocols and normalization algorithms reduce technical bias and control false positives, ensuring high-confidence, reproducible results.
Q4: What deliverables are provided after analysis?
A: A comprehensive dataset and analysis report are provided, including raw and normalized expression matrices, differential expression lists, visualizations (volcano plots, heatmaps, PCA), functional annotations, predicted circRNA–miRNA–mRNA networks, and pathway enrichment analysis. QC metrics, such as inter-sample correlation and spike-in performance, are also included.
Q5: What steps should follow after candidate circRNAs are identified?
A: A three-step validation strategy is recommended: molecular verification, interaction/pathway validation, and functional/phenotypic assays.
1. Molecular verification:
2. Interaction and pathway validation:
3. Functional and phenotypic validation:
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