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    Long-Read Sequencing Improves the Detection of Structural Variations Impacting Complex Non-Coding Elements of the Genome

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    204-2021.132 Ghausia Begum, Ammar Albanna, Asma Bankapur, Nasna Nassir, Richa Tambi, Bakhrom K. Berdiev, Noushad Karuvantevida, Deena Alhashmi, Alawi Alsheikh-Ali, Mohammed Uddin (11.61Mb)
    Date
    2021
    Author
    Begum, Ghausia
    Albanna, Ammar
    Bankapur, Asma
    Berdiev, Bakhrom K.
    Karuvantevida, Noushad
    Alhashmi, Deena
    Alsheikh-Ali, Alawi A.
    Uddin, Mohammed
    Nassir, Nasna
    Tambi, Richa
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    Abstract
    Abstract: The advent of long-read sequencing offers a new assessment method of detecting genomic structural variation (SV) in numerous rare genetic diseases. For autism spectrum disorders (ASD) cases where pathogenic variants fail to be found in the protein-coding genic regions along chromosomes, we proposed a scalable workflow to characterize the risk factor of SVs impacting non-coding elements of the genome. We applied whole-genome sequencing on an Emirati family having three children with ASD using long and short-read sequencing technology. A series of analytical pipelines were established to identify a set of SVs with high sensitivity and specificity. At 15-fold coverage, we observed that long-read sequencing technology (987 variants) detected a significantly higher number of SVs when compared to variants detected using short-read technology (509 variants) (p-value < 1.1020 _ 10􀀀57). Further comparison showed 97.9% of long-read sequencing variants were spanning within the 1–100 kb size range (p-value < 9.080 _ 10􀀀67) and impacting over 5000 genes. Moreover, long-read variants detected 604 non-coding RNAs (p-value < 9.02 _ 10􀀀9), comprising 58% microRNA, 31.9% lncRNA, and 9.1% snoRNA. Even at low coverage, long-read sequencing has shown to be a reliable technology in detecting SVs impacting complex elements of the genome.
    URI
    https://repository.mbru.ac.ae/handle/1/931
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