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    Analysis of transcript-deleterious variants in Mendelian disorders: implications for RNA-based diagnostics

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    Type
    Dataset
    Authors
    Maddirevula, Sateesh
    Kuwahara, Hiroyuki
    Ewida, Nour
    Shamseldin, Hanan E.
    Patel, Nisha
    AlZahrani, Fatema
    AlSheddi, Tarfa
    AlObeid, Eman
    Alenazi, Mona
    Alsaif, Hessa S.
    Alqahtani, Maha
    AlAli, Maha
    Al Ali, Hatoon
    Helaby, Rana
    Ibrahim, Niema
    Abdulwahab, Firdous
    Hashem, Mais
    Hanna, Nadine
    Monies, Dorota
    Derar, Nada
    Alsagheir, Afaf
    Alhashem, Amal
    Alsaleem, Badr
    Alhebbi, Hamoud
    Wali, Sami
    Umarov, Ramzan
    Gao, Xin cc
    Alkuraya, Fowzan S.
    KAUST Department
    Computational Bioscience Research Center (CBRC)
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Structural and Functional Bioinformatics Group
    Date
    2020
    Permanent link to this record
    http://hdl.handle.net/10754/664967
    
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    Abstract
    Abstract Background At least 50% of patients with suspected Mendelian disorders remain undiagnosed after whole-exome sequencing (WES), and the extent to which non-coding variants that are not captured by WES contribute to this fraction is unclear. Whole transcriptome sequencing is a promising supplement to WES, although empirical data on the contribution of RNA analysis to the diagnosis of Mendelian diseases on a large scale are scarce. Results Here, we describe our experience with transcript-deleterious variants (TDVs) based on a cohort of 5647 families with suspected Mendelian diseases. We first interrogate all families for which the respective Mendelian phenotype could be mapped to a single locus to obtain an unbiased estimate of the contribution of TDVs at 18.9%. We examine the entire cohort and find that TDVs account for 15% of all “solved” cases. We compare the results of RT-PCR to in silico prediction. Definitive results from RT-PCR are obtained from blood-derived RNA for the overwhelming majority of variants (84.1%), and only a small minority (2.6%) fail analysis on all available RNA sources (blood-, skin fibroblast-, and urine renal epithelial cells-derived), which has important implications for the clinical application of RNA-seq. We also show that RNA analysis can establish the diagnosis in 13.5% of 155 patients who had received “negative” clinical WES reports. Finally, our data suggest a role for TDVs in modulating penetrance even in otherwise highly penetrant Mendelian disorders. Conclusions Our results provide much needed empirical data for the impending implementation of diagnostic RNA-seq in conjunction with genome sequencing.
    Citation
    Sateesh Maddirevula, Kuwahara, H., Ewida, N., Shamseldin, H. E., Patel, N., Alzahrani, F., Tarfa AlSheddi, AlObeid, E., Alenazi, M., Hessa S. Alsaif, Alqahtani, M., AlAli, M., Hatoon Al Ali, Helaby, R., Niema Ibrahim, Firdous Abdulwahab, Hashem, M., Hanna, N., Monies, D., … Alkuraya, F. S. (2020). Analysis of transcript-deleterious variants in Mendelian disorders: implications for RNA-based diagnostics. figshare. https://doi.org/10.6084/M9.FIGSHARE.C.5026505.V1
    Publisher
    figshare
    DOI
    10.6084/m9.figshare.c.5026505.v1
    Relations
    Is Supplement To:
    • [Article]
      Maddirevula, S., Kuwahara, H., Ewida, N., Shamseldin, H. E., Patel, N., Alzahrani, F., … Alkuraya, F. S. (2020). Analysis of transcript-deleterious variants in Mendelian disorders: implications for RNA-based diagnostics. Genome Biology, 21(1). doi:10.1186/s13059-020-02053-9. DOI: 10.1186/s13059-020-02053-9 HANDLE: 10754/663747
    ae974a485f413a2113503eed53cd6c53
    10.6084/m9.figshare.c.5026505.v1
    Scopus Count
    Collections
    Structural and Functional Bioinformatics Group; Computer Science Program; Computational Bioscience Research Center (CBRC); Datasets; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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