The impact of read depth and read length on RNA-seq splicing analysis

Area of Science:

• Life Sciences
• Genomics
• Molecular Biology

Background:

• Alternative splicing (AS) is a crucial regulatory mechanism in eukaryotic gene expression.
• Quantifying AS differences typically relies on transcriptome-wide short-read RNA sequencing (RNA-seq) data.
• The suitability of RNA-seq data for AS analysis is influenced by library characteristics.

Purpose of the Study:

• To investigate the impact of RNA-seq library characteristics, specifically read length and read depth, on alternative splicing analysis.
• To demonstrate how these factors influence the detection, quantification, and classification of AS events.
• To provide guidance for researchers selecting RNA-seq specifications for AS studies.

Main Methods:

• Utilized two standard ENCODE datasets with known AS variations.
• Modulated read length and read depth of the RNA-seq data.
• Employed the MAJIQ algorithm for state-of-the-art AS event analysis.

Main Results:

• Both increased read length and higher read depth significantly improved the sensitivity of AS detection.
• Precision in quantifying and classifying AS events was also enhanced by these library specifications.
• The study identified optimal RNA-seq parameters for robust AS analysis.

Conclusions:

• Researchers should consider longer reads and greater read depth for more accurate alternative splicing analyses.
• Informed choices regarding RNA-seq library specifications are critical for reliable AS event quantification.
• This work offers practical insights for optimizing RNA-seq experimental design in AS research.