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一种精确的基因组编辑方法揭示了对真核启动子活性的见解。

A Precise Genome Editing Method Reveals Insights into the Activity of Eukaryotic Promoters.

作者信息

Elison Gregory L, Song Ruijie, Acar Murat

机构信息

Department of Molecular Cellular and Developmental Biology, Yale University, 219 Prospect Street, New Haven, CT 06511, USA; Systems Biology Institute, Yale University, 850 West Campus Drive, West Haven, CT 06516, USA.

Systems Biology Institute, Yale University, 850 West Campus Drive, West Haven, CT 06516, USA; Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, 300 George Street, Suite 501, New Haven, CT 06511, USA.

出版信息

Cell Rep. 2017 Jan 3;18(1):275-286. doi: 10.1016/j.celrep.2016.12.014.

DOI:10.1016/j.celrep.2016.12.014
PMID:28052256
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5216458/
Abstract

Despite the availability of whole-genome sequences for almost all model organisms, making faithful predictions of gene expression levels based solely on the corresponding promoter sequences remains a challenge. Plasmid-based approaches and methods involving selection markers are not ideal due to copy-number fluctuations and their disruptive nature. Here, we present a genome editing method using the CRISPR/Cas9 complex and elucidate insights into the activity of canonical promoters in live yeast cells. The method involves the introduction of a novel cut site into a specific genomic location, followed by the integration of an edited sequence into the same location in a scarless manner. Using this method to edit the GAL1 and GAL80 promoter sequences, we found that the relative positioning of promoter elements was critically important for setting promoter activity levels in single cells. The method can be extended to other organisms to decode genotype-phenotype relationships in various gene networks.

摘要

尽管几乎所有模式生物都有全基因组序列,但仅根据相应的启动子序列准确预测基因表达水平仍然是一项挑战。基于质粒的方法以及涉及选择标记的方法并不理想,因为存在拷贝数波动及其干扰性。在此,我们提出一种使用CRISPR/Cas9复合物的基因组编辑方法,并阐明对活酵母细胞中典型启动子活性的见解。该方法包括在特定基因组位置引入一个新的切割位点,然后将编辑后的序列无痕整合到同一位置。使用这种方法编辑GAL1和GAL80启动子序列,我们发现启动子元件的相对位置对于设定单细胞中的启动子活性水平至关重要。该方法可以扩展到其他生物体,以解码各种基因网络中的基因型-表型关系。