The Royal Society
Browse
rsob240007_si_002.pdf (1.11 MB)

SUPPLEMENTARY DATA from Regional random mutagenesis driven by multiple sgRNAs and diverse on-target genome editing events to identify functionally important elements in non-coding regions

Download (1.11 MB)
Version 2 2024-03-20, 07:15
Version 1 2024-02-27, 09:06
journal contribution
posted on 2024-03-20, 07:15 authored by Kento Morimoto, Hayate Suzuki, Akihiro Kuno, Yoko Daitoku, Yoko Tanimoto, Kanako Kato, Kazuya Murata, Fumihiro Sugiyama, Seiya Mizuno
Functional regions that regulate biological phenomena are interspersed throughout eukaryotic genomes. The most definitive approach for identifying such regions is to confirm the phenotype of cells or organisms in which specific regions have been mutated or removed from the genome. This approach is invaluable for the functional analysis of genes with a defined functional element, the protein-coding sequence. By contrast, no functional analysis platforms have been established for the study of cis-elements or microRNA cluster regions consisting of multiple microRNAs with functional overlap. Whole-genome mutagenesis approaches, such as via N-ethyl-N-nitrosourea and gene trapping, have greatly contributed to elucidating the function of coding genes. These methods almost never induce deletions of genomic regions or multiple mutations within a narrow region. In other words, cis-elements and microRNA clusters cannot be effectively targeted in such a manner. Herein, we established a novel region-specific random mutagenesis method named CRISPR- and transposase-based regional mutagenesis (CTRL-mutagenesis). We demonstrate that CTRL-mutagenesis randomly induces diverse mutations within target regions in murine embryonic stem cells. Comparative analysis of mutants harbouring subtly different mutations within the same region would facilitate the further study of cis-element and microRNA clusters.

History

Usage metrics

    Open Biology

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC