Circular RNA: The evolving potential in the disease world

Table 3 Genome-wide identification of circular RNAs: How it began

Ref.	Genome-wide identification of circRNAs
Salzman et al[18], 2012	Aimed to distinguish cancer-specific exon scrambling events
	Identified 2748 scrambled isoforms in Hela and H9 embryonic stem cells
	Conclusion: 98% of scrambled isoforms represent circRNAs
Jeck et al[8], 2013	Classified circular transcripts based on their levels of abundance using three stringencies categories (low, medium, high)
	Conclusion: circRNAs are conserved, stable, and nonrandom products of RNA splicing that could be involved in the control of gene expression
Memczak et al[7], 2013	Developed a computational method to detect circRNAs
	Conclusion: circRNAs form a significant class of post-transcriptional regulators
Guo et al[19], 2014	Identified and quantified human circRNAs from ENCODE Ribozero RNA-seq data
	Conclusion: Most circRNAs are nonsignificant side-products of splicing error
Zhang et al[20], 2014	Developed CIRCexplorer to distinguish thousands of circRNAs in humans with p(A)-wloRNase R RNA-seq data
	Conclusion: Alternative circularization paired with alternative splicing can generate additional circRNAs from one gene, which is suggestive of the new line of complexity in gene regulation

circRNA: Circular RNAs.