Arraystar Human Circular RNA Microarray

  • Description
  • Highlights
  • Database

Arraystar circRNA Microarrays are the first and only commercially available technology for sensitive and reliable circRNA expression profiling. The Human CircRNA Microarray covers 13,617 human circRNAs with stringent experimental support, carefully and comprehensively collected from the circular RNA studies and the landmark publications.

Circular RNA (circRNA) is a novel type of RNA that, unlike linear RNA, forms a covalently closed continuous loop, some of which are highly represented in the eukaryotic transcriptome. Most of these circRNAs are generated from exonic or intronic sequences, are conserved across species, and often show tissue/developmental-stage-specific expression. Circular RNAs are more stable than linear RNAs owing to their higher nuclease stability, which constitutes an enormous advantage from a clinical point of view as a novel class of biomarkers. In addition, circRNAs have been shown to function as natural miRNA sponge transcripts, the so-called competing endogenous RNAs (ceRNAs) in diverse species. Their interaction with disease associated miRNAs suggests the potential importance of circular RNAs in disease regulation.

To facilitate the analysis of circRNAs, Arraystar has developed the first commercially-available circRNA microarray. Arraystar Human circRNA Microarray is designed for the global profiling of human circular RNAs. In order to detect circRNAs comprehensively and reliably, we have updated the circRNA repertoire represented in the previous Version 1.0 and launched the newly designed V2.0. All the circular RNAs with stringent experimental support are carefully and comprehensively curated from the most recent publications, allowing systematic profiling of the circRNA transcriptome under physiological and pathophysiological conditions. The circRNAs are annotated with predicted miRNA target sites to help unravel their functional roles as a natural miRNA sponge. Potential associations of the circRNAs with human diseases are established by identifying interactions between circRNAs and disease-associated miRNAs or by mapping disease-associated SNPs to the circRNA loci. Each circRNA is represented by a circular splice junction probe that can detect the circRNA reliably and accurately, even in the presence of its linear counterparts. A random primer-based labeling system is coupled with RNase R sample pretreatment to ensure specific and efficient labeling of circular RNAs. RNA Spike-In controls are included to monitor the labeling and hybridization efficiencies. 

Product NameCatalog NoFormatPrice
Arraystar Human Circular RNA Microarray V2.0 AS-CR-H-V2.0 8*15K

• Specific Circular Junction Probes

Reliably and accurately identify individual circRNAs, even in the presence of their linear counterparts (Fig. 1).


Figure 1. Arraystar circRNA Microarray V2.0 uses specific circular junction probes to accurately and reliably detect each individual circRNAs, even in the presence of their linear counterparts. The linear RNA at the bottom is alternatively processed to generate a circular variant above. A probe is designd to target the circRNA-specific junction site, where the 5' end of exon A joins together with the 3' end of exon B.

Detailed annotation for circRNA-miRNA association

Annotation of potential miRNA target sites on the circular RNAs helps to unravel their functional roles as a natural miRNA sponge (Fig. 2).


Figure 2. The association between circular RNA and conserved miRNAs is annotated in detail.

• The preferred choice over RNA-sequencing, as RNA-seq is currently inadequate for such task due to the particular properties of circular RNA.    Learn more >


Figure 3. RNA-seq quantification reliability vs read depth. Typical RNA-seq has a depth of < 30 mil reads for mRNAs (blue circle), which is  < 0.5 mil for cross circular junction reads (red circle). Less than 5% circular junctions can be reliably quantified. Adopted from Labaj et al, (2011) Bioinformatics [PMID 21685096].

Spike-in RNA controls

A set of exogenous RNA controls developed by the External RNA Controls Consortium (ERCC) are added to the RNA samples. With the spike-in controls, procedural effects occurring during RNA amplification, labeling, and hybridization can be corrected. The limit of detection is more accurately determined, and the results across samples are compared more reliably.

Guaranteed performance

- Better sensitivity: Low abundance RNAs are accurately detected with a wide dynamic range of over 5 orders of magnitude (Fig. 4).


Figure 4. A wide dynamic detection range of over 5 orders of magnitude with Arraystar's circRNA microarrays.

- High Reproducibility: Technical replicates show tight correlation on Arraystar circRNA microarrays (R2>0.9)  (Fig. 5).


Figure 5.   High reproducibility on Arraystar circRNA arrays.


Total Number of Distinct Probes 13,617
Probe Length 60 nt
Probe Selection Region Probes targeting circRNA-specific junctions
Probe Specificity Transcript-specific
Labeling Method Random primer labeling coupled with RNase R sample pretreatment to ensure specific and efficient labeling of circular RNAs.
Circular RNA Sources
Salzman's circRNAs [4] 8,529
Memczak's circRNAs [3] 1,601
Zhang's circRNAs [6] 93
Zhang's circRNAs [5] 4,980
Jeck's circRNAs [2] 3,769
Guo's circRNAs [1] 5,536
Array Format 8 * 15K












1. Guo, J. U., V. Agarwal, et al. (2014). "Expanded identification and characterization of mammalian circular RNAs." Genome Biol 15(7): 409.
2. Jeck, W. R., J. A. Sorrentino, et al. (2013). "Circular RNAs are abundant, conserved, and associated with ALU repeats." RNA 19(2): 141-157.
3. Memczak, S., M. Jens, et al. (2013). "Circular RNAs are a large class of animal RNAs with regulatory potency." Nature 495(7441): 333-338.
4. Salzman, J., R. E. Chen, et al. (2013). "Cell-type specific features of circular RNA expression." PLoS Genet 9(9): e1003777.
5. Zhang, X. O., H. B. Wang, et al. (2014). "Complementary sequence-mediated exon circularization." Cell 159(1): 134-147.
6. Zhang, Y., X. O. Zhang, et al. (2013). "Circular intronic long noncoding RNAs." Mol Cell 51(6): 792-806.