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Exon Recombination

Exon Recombination

The evolution of new genes is critical for speciation. Exon recombination, also known as exon shuffling or domain shuffling, is an important means of new gene formation. It is observed across vertebrates, invertebrates, and in some plants such as potatoes and sunflowers. During exon recombination, exons from the same or different genes recombine and produce new exon-intron combinations, which might evolve into new genes.
Exon shuffling follows “splice frame rules.” Each exon...

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In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

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Efficient reinterpretation of rare disease cases using Exomiser.

Letizia Vestito¹, Julius O B Jacobsen¹, Susan Walker²

¹William Harvey Research Institute, Clinical Pharmacology and Precision Medicine, Queen Mary University of London, London, UK.

NPJ Genomic Medicine

|December 18, 2024

Summary

Reanalyzing whole genome sequencing data with Exomiser identifies new rare disease diagnoses. This phenotype-driven tool efficiently prioritizes variants, improving diagnostic yield for unsolved cases.

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Last Updated: Jun 4, 2025

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

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Published on: August 20, 2019

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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Area of Science:

Genomics
Rare Disease Research
Clinical Bioinformatics

Background:

Whole genome sequencing (WGS) has advanced rare disease research, yet a significant percentage of patients remain undiagnosed.
Reanalysis of WGS data is crucial for identifying new diagnoses, particularly with evolving knowledge of disease-gene associations.
Efficient tools are needed to support the clinical interpretation of WGS data for rare disease diagnosis.

Purpose of the Study:

To develop and optimize a reanalysis strategy using Exomiser for efficient identification of rare disease candidates.
To evaluate the performance of Exomiser in reanalyzing previously unsolved WGS cases, focusing on recent gene discoveries and variant classifications.
To assess the utility of Exomiser's automated ACMG/AMP classifier in variant interpretation.

Main Methods:

Implemented a reanalysis strategy utilizing Exomiser, a phenotype-driven variant prioritization tool.
Optimized Exomiser settings to identify candidate variants from new disease gene discoveries and updated variant classifications.
Integrated Exomiser's automated ACMG/AMP variant classifier into the reanalysis workflow.

Main Results:

Exomiser reanalysis identified new diagnoses in 463 of 24,015 previously unsolved rare disease cases within the 100,000 Genomes Project.
The optimized reanalysis strategy achieved high recall (82%) and precision (88%) in highlighting new diagnostic candidates.
The automated ACMG/AMP classifier successfully reclassified 92% of variants from unknown significance to pathogenic/likely pathogenic.

Conclusions:

Exomiser provides an efficient and effective tool for reinterpreting previously unsolved whole genome sequencing cases in rare disease research.
The developed reanalysis strategy significantly enhances the diagnostic yield by incorporating recent genetic discoveries and automated variant classification.
This approach streamlines clinical interpretation, accelerating the diagnosis for patients with rare diseases.