Comparison of Analysis Tools for miRNA High Throughput Sequencing Using Nerve Crush as a Model

Area of Science:

• Neuroscience
• Genomics
• Molecular Biology

Background:

• Next-generation sequencing enables high-throughput miRNA profiling, but its application in neurological studies is limited.
• Inaccessible tissues (brain, spinal cord) and low RNA yields from biofluids (blood, CSF) pose challenges for neurological miRNA research.

Purpose of the Study:

• To investigate miRNA expression changes in response to acute nerve crush injury using a mouse model.
• To evaluate the impact of sequencing depth on miRNA detection in muscle tissue and blood plasma.
• To compare different bioinformatics software packages for miRNA analysis and novel miRNA prediction.

Main Methods:

• Assayed miRNA expression from mouse muscle tissue and blood plasma after acute nerve crush.
• Varied sequencing depth to assess its effect on detectable miRNAs and mature miRNA coverage.
• Analyzed data using miRDeep2, miRNAKey, miRExpress, DESeq, and EdgeR.
• Validated novel miRNA predictions using quantitative reverse transcription PCR (qRT-PCR).

Main Results:

• Sequencing depth significantly influences the number of detectable miRNAs, varying by sample type (muscle vs. plasma).
• Low starting RNA amounts, as seen in mouse plasma, hinder achieving high-depth mature miRNA coverage.
• Different software packages yield varying results in read mapping and differential expression analysis.
• miRDeep2 showed potential for novel miRNA prediction, validated by qRT-PCR.

Conclusions:

• Each tissue type requires independent assessment of sequencing depth for adequate miRNA differential expression detection.
• Balancing sequencing depth with cost is essential for efficient miRNA profiling in neurological studies.
• Biofluid sampling presents challenges for deep miRNA sequencing due to low RNA quantities.