StarSeeker: an automated tool for mature duplex microRNA sequence identification based on secondary structure modeling of precursor molecule

Abstract

Background: MicroRNAs (miRNAs) are small, non-coding RNA molecules that play a key role in gene regulation in both plants and animals. MicroRNA biogenesis involves the enzymatic processing of a primary RNA transcript. The final step is the production of a duplex molecule, often designated as miRNA:miRNA*, that will yield a functional miRNA by separation of the two strands. This miRNA will be incorporated into the RNA-induced silencing complex, which subsequently will bind to its target mRNA in order to suppress its expression. The analysis of miRNAs is still a developing area for computational biology with many open questions regarding the structure and function of this important class of molecules. Here, we present StarSeeker, a simple tool that outputs the putative miRNA* sequence given the precursor and the mature sequences.

Results: We evaluated StarSeeker using a dataset consisting of all plant sequences available in miRBase (6992 precursor sequences and 8496 mature sequences). The program returned a total of 15,468 predicted miRNA* sequences. Of these, 2650 sequences were matched to annotated miRNAs (~ 90% of the miRBase-annotated sequences). The remaining predictions could not be verified, mainly because they do not comply with the rule requiring the two overhanging nucleotides in the duplex molecule.

Conclusions: The expression pattern of some miRNAs in plants can be altered under various abiotic stress conditions. Potential miRNA* molecules that do not degrade can thus be detected and also discovered in high-throughput sequencing data, helping us to understand their role in gene regulation.

Keywords: Plant transcriptome; Sequence prediction; Transcription regulation; miRNA maturation.

Fig. 1

Part of miRNA biogenesis route in plants. The main difference from animal biogenesis is that in plants, the two cleavages are performed by the same enzyme (DCL1) inside the nucleus instead of two different enzymes (Drosha, Dicer), one inside and one outside the nucleus. The two hanging nucleotides in each side of the duplex can be seen. After this process, the duplex exits the nucleus and separates

Fig. 2

a The secondary structure of a pre-miRNA molecule. The gaps in base-pairing are represented by the “dash” character. Mismatches in the stem part that lead to unpaired bases can be seen. The loop is shown at the rightmost part of the molecule. b The first line represents the primary structure of the pri-miRNA shown in a and the second line indicates the “dot-bracket notation” of the same molecule

Fig. 3

A pre-miRNA molecule with the sequences of miRNA and miRNA* highlighted in pink. Notice that the highlighted part is displaced by two nucleotides relatively to the one above it

Fig. 4

Input and results of running StarSeeker on all plant data contained in miRBase. The input files contained 6992 precursors and 8496 miRNAs. The output was 15,468 miRNAs*, because some mature sequences were matched to more than one precursor due to conserved genes and miRNA families among different species

Fig. 5

Evaluation of the output of running StarSeeker on plant sequences from miRBase. Of the 15,468 sequences that existed in the output file, 2650 were matched with the initial source mature miRNA data and 12,818 are considered novel miRNAs* and their existence can be verified by RNA-Seq experiments

Fig. 6

MiRBase entry of miR-160c from Arabidopsis sp. In this entry, the two annotated sequences of miRNA and miRNA* do not follow the biogenesis rule of two hanging nucleotides, as there are three nucleotides left in each end. This type of entries could not be verified during the evaluation process because the algorithm works only with the normal two-nucleotide ends duplexes