Application of CRISPR technologies for the efficient development of models of human disease
Application of CRISPR technologies for the efficient development of models of human disease
批准号:
2275743
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --
中文摘要
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英文摘要
CRISPR/Cas9 is a programmable site-specific nuclease that can be used to manipulate the sequence of DNA in a precise and efficient manner. Using these "genome editing" approaches, genes can be knocked out of the genome to allow an assessment of their function in both stem cell and animal models. Furthermore, single nucleotide variants which have been found to associate with a particular disease progression or susceptibility can also be introduced into these systems, allowing models of human disease to be interrogated within the laboratory.As well as being an effective genome-editing tool, the CRISPR/Cas9 system, if rendered catalytically inactive, serves as a very effective programmable site-specific DNA binding protein. Using this system, effector domains which can either up- or down-regulate gene expression can be recruited to gene promoters and regulatory regions, allowing tuneable manipulation of gene expression levels - so called CRISPRa (activation) and CRISPRi (inactivation) technology. Since it is becoming clear that much of the genomic variation which influences disease, lies within regulatory regions of the genome, the development of robust systems for manipulating gene expression in models systems will enable insights into how perturbations in gene expression networks underlie changes in disease susceptibility and progression.This research project will focus on efficient methods of implementing and combining CRISPR systems for targeted deletion, inhibition and activation to model disease-associated genomic changes. Working in both stem cells and mouse embryos, the project aims to explore new possibilities for accurate models of human disease, with a particular focus on reducing the animal cost of disease model generation.
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