miR-Island

miR-Island annotates plant microRNAs and quantifies their expression from next-generation sequencing (NGS) data to support miRNA discovery and profiling.

Key Features:

• Ultrafast processing: Applies a pseudogenomic approach to streamline miRNA precursor candidate extraction and reduces processing time for precursor extraction (e.g., from 85 seconds to 19 seconds in Salvia miltiorrhiza).
• Parallel RNA secondary structure prediction: Uses parallel processing for RNA secondary structure prediction, reducing time for 3957 S. miltiorrhiza precursors from 90 seconds to 32 seconds.
• Memory efficiency: Operates with minimized memory usage suitable for standard personal computers while performing miRNA annotation and expression analysis.
• Accuracy and performance: Identified 128 miRNAs in Arabidopsis including 68 known miRNAs from miRBase, and compared to ShortStack (55 miRNAs) and miRDeep-P (175 miRNAs, 57 in miRBase) shows favorable identification results.
• Comparative speed: Completed Arabidopsis miRNA annotation in 18 minutes, which is less than half the time of ShortStack and about 9% of the time of miRDeep-P, and processed three additional plant datasets in under 50% of ShortStack time and under 2.5% of miRDeep-P time.

Scientific Applications:

• Plant miRNA annotation: Enables annotation of miRNAs in plant genomes from NGS data.
• Expression profiling: Supports quantification of miRNA expression from next-generation sequencing datasets.
• Novel miRNA discovery: Facilitates discovery of novel miRNAs by extracting precursor candidates and predicting RNA secondary structures.
• miRNA-mediated gene regulation studies: Aids exploration of miRNA roles in gene regulation across diverse plant species.

Methodology:

Performs miRNA precursor extraction using a pseudogenomic approach and performs parallelized RNA secondary structure prediction on next-generation sequencing data for annotation and expression analysis.