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 but is susceptible to technical noise in RNA sequencing (RNA-seq).
• Previous methods using technical replicates for noise correction are accurate but prohibitively expensive for large-scale studies.
• A cost-effective and accurate method is needed to mitigate technical noise in ASE analysis.

Approach:

• Developed a novel spike-in approach using distinct RNA added before library preparation to capture library-wide technical noise.
• Validated the method experimentally using cross-species RNA combinations (mouse, human, *C. elegans*) for accurate noise estimation.
• Introduced the R package `controlFreq` for computationally efficient and highly accurate ASE analysis.

Key Points:

• The spike-in approach accurately reflects technical noise across entire RNA-seq libraries.
• Experimental validation confirmed the effectiveness of the spike-in method across different species.
• The `controlFreq` approach enables large-scale ASE studies with minimal cost increase (~5%).

Conclusions:

• The `controlFreq` method provides a highly accurate and cost-effective solution for analyzing allele-specific expression.
• This approach significantly reduces the financial barrier for large-scale genomic studies requiring precise ASE quantification.
• The analysis pipeline is publicly available as an R package, facilitating widespread adoption.