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Published on: May 19, 2019
LongAllele: a joint inference framework for allele-specific analysis on long-read bulk and single-cell RNA sequencing
Biorxiv : the Preprint Server for Biology
|May 18, 2026
Summary
LongAllele improves allele-specific expression analysis from RNA sequencing by jointly inferring variants and haplotypes. This phasability-aware method enhances accuracy, reduces false positives, and provides multi-scale cis-regulation insights.
Area of Science:
- Genomics
- Molecular Biology
- Bioinformatics
Background:
- Allele-specific analysis of RNA sequencing (RNA-seq) is crucial for understanding cis-regulatory effects.
- Existing methods for haplotype inference and allelic testing in RNA-seq are limited, often separating steps and propagating errors.
- Current approaches can ignore non-phasable reads, leading to biased results and inflated false positives.
Purpose of the Study:
- To develop a novel statistical framework, LongAllele, for joint inference of heterozygous variants, haplotype structure, and read-haplotype assignments from long-read RNA-seq data.
- To introduce a phasability-aware testing strategy that accounts for non-phasable reads to improve accuracy and reduce false positives.
- To enable comprehensive, multi-scale allelic testing across gene, isoform, and local event levels for a detailed view of cis-regulation.
Main Methods:
- Developed LongAllele, a statistical framework utilizing an expectation-maximization algorithm.
- Implemented joint inference of heterozygous variants, haplotype structure, and read-haplotype assignments.
- Introduced phasability-aware testing to explicitly handle non-phasable reads.
Main Results:
- LongAllele successfully applied to bulk and single-cell long-read RNA-seq datasets (GTEx, PBMCs, hippocampus).
- Revealed greater tissue and cell-type variability in expression-level allelic regulation compared to isoform-level regulation.
- Identified high-impact regulatory variants, including rare splice-site mutations missed by other callers, and demonstrated purifying selection constraints on allelic imbalance.
Conclusions:
- LongAllele provides a unified and accurate framework for haplotype-resolved cis-regulatory analysis using long-read RNA-seq.
- The phasability-aware approach significantly improves the reliability of allelic testing by incorporating all reads.
- The multi-scale analysis capability offers deeper insights into the complexities of gene regulation across different biological contexts.
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