Genome sequencing reveals the impact of non-canonical exon inclusions in rare genetic disease
Author Information
Author(s): Pitsava Georgia, Hawley Megan, Auriga Light, de Dios Ivan, Ko Arthur, Marmolejos Sofia, Almalvez Miguel, Chen Ingrid, Scozzaro Kaylee, Zhao Jianhua, Barrick Rebekah, Mew Nicholas Ah, Fusaro Vincent A., LoTempio Jonathan, Taylor Matthew, Mestroni Luisa, Graw Sharon, Milewicz Dianna, Guo Dongchuan, Murdock David R., Bujakowska Kinga M., Xiao Changrui, Délot Emmanuèle C., Berger Seth I., Vilain Eric
Primary Institution: Institute for Clinical and Translational Science, University of California, Irvine, CA, USA
Hypothesis
Can short-read genome sequencing increase the diagnostic yield in individuals with suspected Mendelian conditions and prior inconclusive clinical genetic testing?
Conclusion
Genome sequencing can overcome limitations of clinical genetic testing and highlights cryptic exon inclusion as a common mechanism for deep intronic variants causing Mendelian disease.
Supporting Evidence
- Genome sequencing identified a molecular diagnosis in 15.3% of previously unsolved cases.
- 55.5% of diagnoses were missed due to original testing not interrogating the causative variant regions.
- RNA sequencing confirmed cryptic exon inclusion in five cases due to deep intronic variants.
- Reanalysis of exome datasets could have detected 26% of newly diagnosed cases.
- Syndromic phenotypes had the highest solve rate at 25%.
Takeaway
This study shows that using advanced genome sequencing can help find genetic causes of diseases that were missed by earlier tests.
Methodology
Short-read genome sequencing and RNA sequencing were used to analyze genetic data from families with suspected Mendelian conditions.
Limitations
The study may not capture all genetic variants due to the limitations of current sequencing technologies.
Participant Demographics
The study included 353 families with a total of 754 participants, with various family structures and suspected Mendelian conditions.
Statistical Information
P-Value
0.03
Statistical Significance
p = 0.03
Digital Object Identifier (DOI)
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