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J Biol Res (Thessalon). 2018 Jun 15;25:11. doi: 10.1186/s40709-018-0081-7. eCollection 2018 Dec.

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

Author information

1
1Department of Genetics, Development & Molecular Biology, School of Biology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
2
3Present Address: School of Medicine, University of Crete, Voutes University Campus, 70013 Heraklion, Crete, Greece.
3
2Department of Computational Biology, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland.

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

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