Long-read transcriptome analysis using IsoRanker for identifying pathogenic variants in Mendelian conditions

Area of Science:

• Genomics
• Transcriptomics
• Rare disease genetics

Background:

• Identifying pathogenic non-coding variants for Mendelian conditions is difficult due to unknown functional impacts.
• Non-coding variants can alter gene function and contribute to rare diseases, but their detection and interpretation remain challenging.

Purpose of the Study:

• To develop and validate IsoRanker, a long-read transcriptome sequencing framework, for prioritizing functionally relevant non-coding variants.
• To improve the diagnosis of rare diseases by providing isoform-level functional evidence for non-coding variants.

Main Methods:

• Utilized paired cycloheximide-treated and untreated fibroblast transcriptomes from 31 individuals.
• Employed long-read transcriptome sequencing linked to phased long-read genomes.
• Developed IsoRanker to detect outlier expression, allelic imbalance, and nonsense-mediated decay (NMD) for variant prioritization.

Main Results:

• IsoRanker successfully identified known transcript alterations and nominated new diagnostic leads in previously unsolved cases.
• The framework demonstrated robustness in subsampling analyses.
• In one case, IsoRanker identified biallelic non-coding variants in HARS1, leading to targeted therapy.

Conclusions:

• IsoRanker, combined with NMD-aware transcriptomics, provides an effective method for generating isoform-level functional evidence.
• This approach enhances the classification of non-coding variants and supports rare disease diagnosis.
• IsoRanker facilitates the identification of novel gene isoforms and their functional impact on disease.