A genome-wide circular RNA transcriptome in rat. Issue 1 (7th September 2021)

• Record Type: Journal Article
• Authors: Sharma, Disha; Sehgal, Paras; Sivasubbu, Sridhar; Scaria, Vinod
• Is Part Of: Biology methods & protocols. Volume 6:Issue 1(2021)
• Publication Date: 2021-09-07
• Subjects: RNA-Seq -- circular RNA -- circRNA -- rat -- transcriptome -- noncoding RNAs; Biology -- Methodology -- Periodicals; 570.1
• DOI: 10.1093/biomethods/bpab016
• Languages: English
• ISSNs: 2396-8923

Abstract

Abstract: Circular RNAs (circRNAs) are a novel class of noncoding RNAs that back-splice from 5ʹ donor site and 3ʹ acceptor sites to form a circular structure. A number of circRNAs have been discovered in model organisms including human, mouse, Drosophila, among other organisms. There are a few candidate-based studies on circRNAs in rat, a well-studied model organism as well. A number of pipelines have been published to identify the back splice junctions for the discovery of circRNAs but studies comparing these tools have suggested that a combination of tools would be a better approach to identify high-confidence circRNAs. The availability of a recent dataset of transcriptomes encompassing 11 tissues, 4 developmental stages, and 2 genders motivated us to explore the landscape of circRNAs in the organism in this context. In order to understand the difference among different pipelines, we employed five different combinations of tools to identify circular RNAs from the dataset. We compared the results of the different combination of tools/pipelines with respect to alignment, total number of circRNAs identified and read-coverage. In addition, we identified tissue-specific, development-stage specific and gender-specific circRNAs and further independently validated 16 circRNA junctions out of 24 selected candidates in 5 tissue samples and estimated the quantitative expression of five circRNA candidates using real-time polymerase chain reaction and our analysis suggests three candidates as tissue-enriched. This study is one of the most comprehensive studies which provides a map of circRNAs transcriptome as well as to understand the difference among different computational pipelines in rat.