RPASE: Individual-based allele-specific expression detection without prior knowledge of haplotype phase

Area of Science:

• Genomics
• Evolutionary Biology
• Bioinformatics

Background:

• Gene expression variation significantly impacts phenotypic diversity and divergence.
• Analyzing allele-specific expression (ASE) provides crucial insights into gene expression regulation.

Purpose of the Study:

• To introduce a novel computational method, RPASE (Read-backed Phasing-based ASE detection), for identifying genes exhibiting ASE.
• To enable individual-based, gene-level tests for ASE using readily available data.

Main Methods:

• RPASE utilizes mapped RNA-sequence (RNA-seq) data and single nucleotide polymorphisms (SNPs) from an individual.
• The method aggregates information across multiple, dependent SNPs for robust ASE detection.
• It generates individual-based, gene-level tests for allele-specific expression.

Main Results:

• RPASE demonstrated strong performance in simulations and comparative analyses.
• Application of RPASE to multiple bird species revealed a substantial landscape of ASE.
• The findings suggest ASE plays a significant role in avian gene expression.

Conclusions:

• RPASE is an effective tool for detecting ASE, enhancing our understanding of gene regulation.
• The prevalence of ASE in birds highlights its importance in evolutionary processes.
• This method facilitates broader investigations into the genetic basis of phenotypic variation.