miRmedon

miRmedon detects adenosine-to-inosine (A-to-I) editing events in microRNAs (miRNAs) from trimmed small RNA sequencing (FASTQ) data to characterize ADAR-mediated miRNA editing.

Key Features:

• Detection of Multiple Editing Sites: Detects multiple A-to-I editing events within a single miRNA sequence, enabling identification of validated multi-site editing.
• Handling Multi-Locus Transcription: Accounts for multi-locus transcription of human miRNAs (approximately 20% of loci), allowing reads originating from multiple genomic loci to be considered.
• Integration with Genomic Variation Data: Incorporates large-scale human variation data to identify editing events in miRNA genes harboring single nucleotide polymorphisms (SNPs) or insertions/deletions (indels), reported in ~73% of human miRNA loci.
• Advanced Alignment Techniques: Uses a combination of local and global alignments to accurately map small-RNA reads and improve identification of editing events.
• Error Distribution Analysis: Compares inferred editing and sequencing error distributions to distinguish true A-to-I editing from sequencing errors or other artifacts.

Scientific Applications:

• miRNA editing characterization: Characterizing ADAR-mediated A-to-I editing patterns in miRNAs across samples and conditions.
• Neurodevelopmental disorders: Investigating roles of miRNA A-to-I editing in neurodevelopmental processes and disorders.
• Cancer biology: Studying altered miRNA editing associated with cancer progression and tumor biology.

Methodology:

Inputs are trimmed small-RNA FASTQ reads; the pipeline performs local and global alignments, incorporates large-scale human variation data, compares inferred editing and sequencing error distributions, and outputs detailed reports of A-to-I editing events with read counts and sequences for edited and non-edited miRNAs, while utilizing several external software tools and Python libraries.