Arraystar circRNA Microarrays are the first and only commercially available technology for sensitive and reliable circRNA expression profiling. The Mouse CircRNA Microarray covers 14,236 mouse circRNAs with stringent experimental support, carefully and comprehensively collected from the circular RNA studies 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 Mouse circRNA Microarray is designed for the global profiling of mouse circular RNAs. In order to detect circRNAs comprehensively and reliably, we have updated the circRNA repertoire represented in the previous Version 1.0. The newly designed V2.0 is to launch in July. The circular RNAs with stringent experimental supports are carefully curated from the landmark publications and presented on Arraystar Circular RNA Microarray, allowing the systematic profiling of the circRNA transcriptome on physiological and pathophysiological conditions. In addition, all the circRNAs are annotated with the potential target sites of miRNAs, which will be helpful for unravelling their functional roles as a natural miRNA sponge.
Arraystar circRNA arrays have been available for human and mouse. Each circRNA is represented by a circular splice junction probe that can identify individual circRNAs reliably and accurately, even in the presence of their linear counterparts. A random primer-based labeling system is coupled with RNase R-based sample pretreatment to ensure the specific and efficient labeling of circular RNAs. In addition, RNA Spike-In controls are used to monitor the labeling and hybridization efficiencies.
• Specific Circular Junction Probes
Enables the reliable and accurate identification of individual circRNAs, even in the presence of their linear counterparts (Fig. 1).
Figure 1. Arraystar circRNA Microarray V2.0 uses specific circular junction probes, enabling the reliable and accurate detection of 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 designed 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
Annotates the circRNAs with the potential target sites of miRNAs, which will be helpful for unravelling 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
Adds a set of exogenous RNA controls developed by the External RNA Controls Consortium (ERCC) to RNA samples. With these 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: detects low abundance RNAs accurately with a wide dynamic range of over 5 orders of magnitude.
- High Reproducibility: Technical replicates show tight correlation on Arraystar circRNA microarrays (R2>0.9).