A bioinformatics approach to microRNA-sequencing analysis.

Area of Science:

• Bioinformatics
• Genomics
• Molecular Biology

Background:

• Next Generation Sequencing (NGS) data is rapidly expanding, necessitating clear bioinformatics analysis pipelines.
• MicroRNA-sequencing (miRNA-sequencing) is a newer omics application with fewer standardized bioinformatics protocols compared to transcriptomics.
• Detailed bioinformatics analysis, including Unique Molecular Identifiers (UMIs), is often lacking in published miRNA-sequencing studies.

Purpose of the Study:

• To provide a detailed and customizable bioinformatics pipeline for miRNA-sequencing data analysis.
• To improve the understanding and reproducibility of miRNA-sequencing data analysis for researchers.
• To address the gap in detailed bioinformatics protocols for miRNA-sequencing.

Main Methods:

• Development of a customizable miRNA bioinformatics pipeline using human osteoarthritis plasma samples.
• Quality assessment of raw sequencing data files.
• Reference-based alignment and counts generation for miRNA expression levels.
• Methods for novel miRNA discovery.

Main Results:

• A comprehensive description of a miRNA bioinformatics pipeline is provided.
• The pipeline includes steps for quality control, alignment, expression quantification, and novel miRNA identification.
• The methods are applicable across various sample types.

Conclusions:

• The developed pipeline enhances clarity and reproducibility in the bioinformatics analysis of miRNA-sequencing data.
• This work promotes the sharing of detailed protocols within the NGS field.
• Researchers can utilize this pipeline to better understand and analyze their miRNA-sequencing datasets.