Application of RNA subcellular fraction estimation method to explore RNA localization regulation

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• RNA localization is crucial for diverse biological processes.
• Subcellular fractionation sequencing reveals global RNA localization patterns.
• Existing methods for calculating RNA localization ratios have limitations, potentially skewing results due to variations in total RNA abundance across fractions.

Purpose of the Study:

• To develop a computational method for accurately estimating relative RNA abundances in different subcellular fractions.
• To address the limitations of existing relative localization ratio calculations.
• To provide a custom tool for analyzing RNA localization patterns.

Main Methods:

• Development of a computational method named 'subcellular fraction abundance estimator'.
• The method estimates relative RNA abundances, accounting for differences in total RNA content across fractions.
• Validation of estimated ratios against existing reports and experimental spike-in methods.

Main Results:

• The developed method provides accurate relative RNA abundance ratios consistent with previous findings.
• Application of the tool revealed RNA localization patterns in cell lines.
• Identified RNA-binding protein (RBP) motifs associated with specific localization patterns and demonstrated that different gene isoforms can have distinct localization patterns.

Conclusions:

• The 'subcellular fraction abundance estimator' tool accurately quantifies RNA localization.
• This tool will aid researchers in future subcellular fractionation-based sequencing studies.
• Facilitates deeper exploration of RNA localization's role in various biological functions.