AlleleSeq: analysis of allele-specific expression and binding in a network framework

Area of Science:

• Genomics
• Computational Biology
• Molecular Biology

Background:

• Allele-specific expression (ASE) and allele-specific binding (ASB) are crucial for understanding gene regulation.
• Differences between maternal and paternal alleles can impact gene function and disease susceptibility.

Purpose of the Study:

• To develop and validate a computational pipeline, AlleleSeq, for analyzing ASE and ASB.
• To identify and characterize allele-specific events in personal genomes.
• To investigate the interaction and coordination between ASE and ASB.

Main Methods:

• Construction of a diploid personal genome sequence and personalized gene annotation using genomic variants.
• Alignment of RNA-Seq and ChIP-Seq reads to the personalized genome.
• Identification of allele-specific events by comparing read counts between maternal and paternal alleles.
• Application of a regulatory network framework to analyze coordinated ASE and ASB.

Main Results:

• The AlleleSeq pipeline successfully identified allele-specific events, addressing technical challenges like mapping bias.
• Widespread allele-specific behavior was observed across functional genomic data sets, including X-chromosome inactivation.
• Correlation analyses and network motifs demonstrated mostly coordinated ASB and ASE across multiple transcription factors.

Conclusions:

• AlleleSeq provides a robust computational framework for studying ASE and ASB.
• The findings highlight the prevalence of allele-specific regulation and its coordination.
• This approach enhances our understanding of personalized gene regulation and its implications.