MiR-RACE: an effective approach to accurately determine the sequence of computationally identified miRNAs.

Abstract

Computational prediction of microRNAs (miRNAs) is one of the most important approaches in microRNA studies. While validation of the predicted microRNAs' precise sequences is essential for further studies on their biogenesis, evolution, and functions, computational miRNA prediction methods, however, often fail to predict the accurate sequence of the mature miRNA within the precursor at the nucleotide precision level. Here, we depict a highly efficient method for determining the precise sequences of computationally predicted miRNAs. The method combines the generation of miRNA-enriched libraries, with 5'- and 3'-end adaptors being linked to the miRNA molecules, the reverse transcription of small RNAs with an oligo-d(T) anchor primer, two specific 5'- and 3'-miRNA-RACE (miR-RACE) PCR reactions and sequence-directed cloning. The efficiency of this method was demonstrated by the precise sequence validation of computationally predicted miRNAs in citrus, apple, and other fruit crops. Our ongoing research indicates that miR-RACE is also very useful to verify the sequences of putative miRNAs obtained by deep sequencing of small RNA libraries. The protocol of miR-RACE is rapid and can be completed within 2-3 days. miR-RACE should make the bioinformatic prediction of miRNAs more powerful and accurate.