Stochastic principles governing alternative splicing of RNA

Area of Science:

• Molecular Biology
• Genetics
• Biophysics

Background:

• Alternative splicing (AS) generates multiple transcript isoforms from a single gene, crucial for cellular function.
• The principles governing the dominance of major transcript isoforms remain largely unknown.
• Understanding isoform expression is vital for comprehending gene regulation and cellular physiology.

Purpose of the Study:

• To investigate the underlying principles that determine the dominance of major transcript isoforms.
• To develop a quantitative model for alternative splicing (AS) isoform expression.
• To explain previously unexplained observations in relative isoform expression.

Main Methods:

• Analysis of the physical alternative splicing (AS) process.
• Modeling AS as a stochastic minimization process.
• Statistical analysis of transcript isoform expression levels using extreme value distributions.

Main Results:

• The scaled expression levels of all transcript isoforms follow a universal Weibull extreme value distribution.
• A simple equation was derived to describe the median frequency of transcript isoforms based on their dominance.
• The developed two-parameter Weibull model statistically describes isoform distribution across all transcribed genes.

Conclusions:

• Alternative splicing (AS) dominance can be explained by a stochastic minimization process.
• The Weibull distribution provides a unifying statistical framework for understanding transcript isoform expression.
• This model offers insights into gene regulation and potential therapeutic targets related to AS.