Researchers Develop Interactive Database for Translatable Circular RNAs Based on Multi-omics Evidence
Recently a specialized database TransCirc (https://www.biosino.org/transcirc/) that provides comprehensive evidences supporting the translation potential of circular RNAs (circRNAs) has been published online in Nucleic Acids Research on Oct. 19th, 2020, entitled “TransCirc: an interactive database for translatable circular RNAs based on multi-omics evidence”. This database was generated by integrating various direct and indirect evidences to predict coding potential of each human circRNA and the putative translation products.
Circular RNAs (circRNAs) have recently been demonstrated as a class of abundant and conserved RNAs in animals and plants. Previous studies have revealed that circRNAs may play diverse biological roles by functioning as either no-coding or coding RNAs. Because circRNAs are more stable than their linear counterpart, they can naturally function as competitors of the linear RNAs to play regulatory roles in gene expression. Since most circRNAs contain exonic sequences and are localized in cytoplasm, many of these circRNAs may also function as mRNA to direct protein translation.
Indeed, recent studies indicated that some cytoplasmic circRNAs can be effectively translated into detectable peptides, and many short sequences, including N-6-methyladenosine (m6A) sites, have been reported to function as IRES-like elements to drive circRNA translation. The translation of circRNA was up-regulated during cellular stresses, and some circRNA-encoded proteins were found to play key roles in regulating cancer cell growth.
However, the identification of circRNA-encoded protein has been a very difficult task, mainly because the sequences from circRNAs and their cognate linear mRNAs of host gene have a large overlap and differ only at the small window across back-splice junction. As a result, while a large number of circRNAs have been identified through high throughput transcriptome sequencing, a specialized and comprehensive database for translatable circRNAs is still lacking.
To meet this need, researchers from the CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health (SINH) of the Chinese Academy of Sciences (CAS) and the Bio-Med Big Data Center, SINH, CAS developed a comprehensive database, TransCirc, which contains information of >300000 circRNAs together with multi-omics evidence from published literatures to support circRNA translations.
TransCirc integrated seven types of evidences for circRNA translation, including: (i) ribosome/polysome binding evidences supporting the occupancy of ribosomes onto circRNAs; (ii) experimentally mapped translation initiation sites oncircRNAs; (iii) internal ribosome entry site on circRNAs; (iv) published N-6-methyladenosine modification data in circRNA that promote translation initiation; (v) lengths of the circRNA specific open reading frames; (vi) sequence composition scores from a machine learning prediction of all potential open reading frames; (vii) mass spectrometry data that directly support the circRNA encoded peptides across backsplice junctions.
This database provides an interactive data search engine and visualization interface for the translatable circRNAs and their translation products, as well as the regulatory elements that support its translation and analytic tools for potential function of circRNA encoded genes.
According to the researchers who developed the database, "We expect the TransCirc database will facilitate further analysis of circRNA function, and streamline the identification of circRNA translation product. All of the information and data is freely available at TransCirc."
The graduate student HUANG Wendi and Dr. LING Yunchao are the co-first authors of this work. Prof. WANG Zefeng is the corresponding author of this article and Prof. ZHANG Guoqing is the co-corresponding author. This work was supported by the Ministry of Science and Technology, the Chinese Academy of Sciences, the National Natural Science Foundation of China, and the Science and Technology Commission of Shanghai Municipality.
WANG Jin (Ms.)
Shanghai Institute of Nutrition and Health,
Chinese Academy of Sciences