Foreign RNA spike-ins enable accurate allele-specific expression analysis at scale

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Allele-specific expression (ASE) analysis is crucial for understanding gene regulation.
• RNA sequencing (RNA-seq) experiments are susceptible to technical noise, which can affect ASE accuracy.
• Previous methods for noise correction, while accurate, were prohibitively expensive due to the need for multiple library replicates.

Purpose of the Study:

• To develop a cost-effective and highly accurate method for estimating technical noise in RNA-seq.
• To enable precise allele-specific expression analysis in large-scale studies.

Main Methods:

• A novel spike-in approach using distinct RNA added before library preparation was developed.
• The method, controlFreq, was validated using RNA from mouse, human, and Caenorhabditis elegans.
• The spike-in RNA was shown to reflect the technical noise across the entire library.

Main Results:

• The spike-in approach accurately estimates technical noise in RNA-seq experiments.
• This method significantly reduces the cost of ASE analysis, with an approximate cost increase of only 5%.
• controlFreq enables computationally efficient and highly accurate ASE analysis for large sample batches.

Conclusions:

• The controlFreq method provides a highly accurate and affordable solution for technical noise correction in ASE analysis.
• This approach facilitates large-scale genetic studies by making precise ASE quantification more accessible.
• The analysis pipeline is available as an R package on GitHub.