Allele-specific expression analysis: pipelines, applications, challenges, and unmet needs
File(s)
Published version
Author(s)
Mattevi, Stefania
Mazzarotto, Francesco
Martini, Paolo
Type
Journal Article
Abstract
In diploid organisms, genes typically exhibit balanced expression of maternal and paternal alleles. However, exceptions exist, such as autosomal genes with allele-specific expression, where genetic and epigenetic variations can lead to the exclusive or preferential expression of a particular allele. In this context, allele-specific expression analysis serves as a powerful tool for understanding gene regulation, with significant functional and clinical implications.
Despite their increasing importance, current analysis pipelines face notable limitations including a lack of end-to-end solutions, restricted options for multi-omics integration, and insufficient support for single-cell sequencing technologies.
This review critically assesses 26 cutting-edge pipelines for allele-specific expression analysis, focusing on their input requirements, capabilities, and applications in the field. Pipelines are categorized based on their ability to handle various data types, support haplotype phasing, employ statistical approaches, and provide graphical outputs. Most pipelines fail to automate preprocessing, integrate multi-omic data, and support high-throughput single-cell sequencing. Future advancements should prioritize the development of automated multi-omic workflows, implementing visualization options, and enhancing compatibility with single-cell technologies. By addressing these gaps, next-generation allele-specific expression pipelines will offer insights into the mechanisms of allele-specific expression regulation, thereby advancing our understanding of its biological and clinical significance.
Despite their increasing importance, current analysis pipelines face notable limitations including a lack of end-to-end solutions, restricted options for multi-omics integration, and insufficient support for single-cell sequencing technologies.
This review critically assesses 26 cutting-edge pipelines for allele-specific expression analysis, focusing on their input requirements, capabilities, and applications in the field. Pipelines are categorized based on their ability to handle various data types, support haplotype phasing, employ statistical approaches, and provide graphical outputs. Most pipelines fail to automate preprocessing, integrate multi-omic data, and support high-throughput single-cell sequencing. Future advancements should prioritize the development of automated multi-omic workflows, implementing visualization options, and enhancing compatibility with single-cell technologies. By addressing these gaps, next-generation allele-specific expression pipelines will offer insights into the mechanisms of allele-specific expression regulation, thereby advancing our understanding of its biological and clinical significance.
Date Issued
2025-09-01
Date Acceptance
2025-07-31
Citation
Computers in Biology and Medicine, 2025, 196 (Part B), pp.110890-110890
ISSN
0010-4825
Publisher
Elsevier BV
Start Page
110890
End Page
110890
Journal / Book Title
Computers in Biology and Medicine
Volume
196
Issue
Part B
Copyright Statement
© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/40759060
PII: S0010-4825(25)01242-9
Subjects
Humans
Alleles
Single-Cell Analysis
Gene Expression Profiling
Animals
High-Throughput Nucleotide Sequencing
Publication Status
Published
Coverage Spatial
United States
Article Number
110890
Date Publish Online
2025-08-03