Abstract
Circular RNAs (circRNAs) are formed by joining the 3′ and 5′ ends of RNA molecules. Identification of circRNAs is an important part of circRNA research. The circRNA prediction methods can predict the circRNAs with start and end positions in the chromosome but cannot identify the full-length circRNA sequences. We present an R package FcircSEC (Full Length circRNA Sequence Extraction and Classification) to extract the full-length circRNA sequences based on gene annotation and the output of any circRNA prediction tools whose output has a chromosome, start and end positions, and a strand for each circRNA. To validate FcircSEC, we have used three databases, circbase, circRNAdb, and plantcircbase. With information such as the chromosome and strand of each circRNA as the input, the identified sequences by FcircSEC are consistent with the databases. The novelty of FcircSEC is that it can take the output of state-of-the-art circRNA prediction tools as input and is applicable for human and other species. We also classify the circRNAs as exonic, intronic, and others. The R package FcircSEC is freely available.
Highlights
Circular RNAs are formed by joining a downstream 3′ splice donor site and an upstream 5′ splice acceptor site in the primary transcript [1]
Some circRNAs interact with RNA-binding proteins (RBPs) [15] very little enrichment in binding sites of RBPs is found for circRNA sequences compared with those of its corresponding linear mRNA
We present an R package FcircSEC to extract directly the full-length circRNA sequences and to classify the circRNAs utilizing the output of circRNA prediction methods and the gene annotation information
Summary
Circular RNAs (circRNAs) are formed by joining a downstream 3′ splice donor site and an upstream 5′ splice acceptor site in the primary transcript [1]. CircRNAs originate from exons close to the 5′ end of a protein coding gene and may consist of one or more exons. CircRNAs were first discovered approximately 40 years ago and thought to be an RNA splicing error [7]. A significant amount of circRNAs is identified through the high-throughput RNA sequencing and bioinformatics analysis [9, 10]. One of the important properties of circRNA is that they have tissue-specific expression. Several studies conclude that circRNAs are substantially enriched in brain tissues and the expression levels are dynamic during brain development of human and mice brain tissues [11,12,13]. CircRNAs show differential expressions between primary ovarian tumors and metastatic tumors in ovarian carcinoma [14].
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