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    Individual-molecule Sequencing (IDMseq) of PANX1 gene in hESCs

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    Type
    Bioproject
    Dataset
    Authors
    Bi, Chongwei
    Wang, Lin
    Yuan, Baolei
    Zhou, Xuan
    Huang, Yanyi
    Li, Mo cc
    Li, Yu
    Pang, Yuhong
    Gao, Xin cc
    wang, sheng
    KAUST Department
    Bioscience Program
    Biological and Environmental Sciences and Engineering (BESE) Division
    Laboratory of Stem Cell and Regeneration, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia.
    Computer Science Program
    Computer Science
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Computational Bioscience Research Center (CBRC)
    Date
    2020-02-12
    Permanent link to this record
    http://hdl.handle.net/10754/666916
    
    Metadata
    Show full item record
    Abstract
    We develop a universal method to label individual DNA molecules for analyzing diverse types of rare genetic variants, with frequency as low as 4x10-5, using short- or long-read sequencing. It enables base-resolution haplotype-resolved quantitative characterization of rare variants. It provides the first quantitative evidence of persistent nonrandom large deletions and insertions following DNA repair of double-strand breaks induced by CRISPR-Cas9 in human pluripotent stem cells.
    Publisher
    NCBI
    Additional Links
    https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA606194
    Relations
    Is Supplement To:
    • [Article]
      Bi, C., Wang, L., Yuan, B., Zhou, X., Li, Y., Wang, S., … Li, M. (2020). Long-read individual-molecule sequencing reveals CRISPR-induced genetic heterogeneity in human ESCs. Genome Biology, 21(1). doi:10.1186/s13059-020-02143-8. DOI: 10.1186/s13059-020-02143-8 Handle: 10754/661565
    Collections
    Biological and Environmental Sciences and Engineering (BESE) Division; Bioscience Program; Computer Science Program; Computational Bioscience Research Center (CBRC); Datasets; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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