Dae-Sik Kim
Sungkyunkwan University · 生化学・遺伝学・分子生物学
研究室紹介
Professor Dae-Sik Kim's research lab specializes in the development and application of precision genome-editing technologies, with a focus on improving the specificity and safety of CRISPR-based systems such as Cas9 and prime editors. The lab employs innovative in vitro and in-cell approaches—like Digenome-seq and nDigenome-seq—to comprehensively map on-target and off-target cleavage activities, particularly in the context of chromatin structure and transcriptional regulation. Their work also extends to clinical applications, including the molecular characterization of thyroid cancers and the optimization of medical imaging for brain tumor diagnosis.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15We present multiplex Digenome-seq to profile genome-wide specificities of up to 11 CRISPR-Cas9 nucleases simultaneously, saving time and reducing cost. Cell-free human genomic DNA was digested using multiple sgRNAs combined with the Cas9 protein and then subjected to whole-genome sequencing. In vitro cleavage patterns, characteristic of on- and off-target sites, were computationally identified across the genome using a new DNA cleavage scoring system. We found that many false-positive, bulge-typ
Programmable nucleases and deaminases, which include zinc-finger nucleases, transcription activator-like effector nucleases, CRISPR RNA-guided nucleases, and RNA-guided base editors, are now widely employed for the targeted modification of genomes in cells and organisms. These gene-editing tools hold tremendous promise for therapeutic applications. Importantly, these nucleases and deaminases may display off-target activity through the recognition of near-cognate DNA sequences to their target sit
Prime editors (PEs) enable targeted precise editing, including the generation of substitutions, insertions and deletions, in eukaryotic genomes. However, their genome-wide specificity has not been explored. Here, we developed Nickase-based Digenome-seq (nDigenome-seq), an in vitro assay that uses whole-genome sequencing to identify single-strand breaks induced by CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 (CRISPR-associated protein 9) nickase. We used nDigenome-seq t
To investigate whether and how CRISPR-Cas9 on-target and off-target activities are affected by chromatin in eukaryotic cells, we first identified a series of identical endogenous DNA sequences present in both open and closed chromatin regions and then measured mutation frequencies at these sites in human cells using Cas9 complexed with matched or mismatched sgRNAs. Unlike matched sgRNAs, mismatched sgRNAs were highly sensitive to chromatin states, suggesting that off-target but not on-target DNA
Advanced glycation end products (AGEs) have long been considered as potent molecules promoting neuronal cell death and contributing to neurodegenerative disorders such as Alzheimer's disease (AD). In this study, we demonstrate that AGE-albumin, the most abundant AGE product in human AD brains, is synthesized in activated microglial cells and secreted into the extracellular space. The rate of AGE-albumin synthesis in human microglial cells is markedly increased by amyloid-β exposure and oxidative
Electronic skin (E-skin) based on tactile sensors has great significance in next-generation electronics such as biomedical application and artificial intelligence that requires interaction with humans. To mimic the properties of human skin, high flexibility, excellent sensing capability, and sufficient spatial resolution through high-level sensor integration are required. Here, we report a highly sensitive pressure sensor matrix based on a piezoresistive cellulose/single-walled carbon nanotube-e
In this work, we introduce a novel algorithm for solving the textbook question answering (TQA) task which describes more realistic QA problems compared to other recent tasks. We mainly focus on two related issues with analysis of the TQA dataset. First, solving the TQA problems requires to comprehend multimodal contexts in complicated input data. To tackle this issue of extracting knowledge features from long text lessons and merging them with visual features, we establish a context graph from t