An accretive detection method for in silico identification and validation of circular RNAs in wheat (Triticum aestivum L.) using RT-qPCR.

Abstract

Circular RNAs (circRNAs) are novel class of non-coding RNAs, which are involved in various functions at the transcriptional and post-transcriptional level in response to a fungal pathogen (Puccinia triticina), including microRNA (miRNA) sponge, RNA binding proteins sponge, regulation of parental gene and biomarkers. Detailed analysis of wheat circRNAs is essential to accelerate the regulated expression of fungal miRNAs. Therefore, we suggest a protocol to aid circRNA identification through RNA-Seq data using various algorithms based on perl script followed by validation through divergent primer designing, standard PCR, and RT-qPCR assays. The divergent primer has been widely used to detect, validate, and quantify back-spliced junction (BSJ) of circRNAs. The procedure covers index file formation, circRNA identification and BSJ detections. However, the laboratory validation of circRNA includes wheat genomic DNA isolation, RNA isolation and its cDNA conversion upto validation. In this study, we identified 28 circRNAs from RNA-Seq of S0 and R0, wherein six circRNAs are commonly present and 75% of the identified circRNAs were belongs to inter-genic, 14% were exonic and intronic category were 11%. Divergent primer designing method successfully validated the two circRNAs via RT-qPCR assay, where circRNA_2 showed less relative expression pattern than circRNA_1 in contrast with housekeeping genes. Thus, our results of identified and validated circRNAs showed that, this protocol is quite helpful, relatively easy, reliable, and accurate for large datasets as other algorithms need various dependencies and have complex scripts with high chances of error occurrence. Additionally, analysis time will vary depending on the expertise level and the number of RNA-Seq data. This proposed protocol can also be used for a wide range of monocotyledons belonging to the Poaceae plant family.