至今,GenScript的服务及产品已被Cell, Nature, Science, PNAS等1300多家生物医药类杂志引用近万次,处于行业领先水平。NIH、哈佛、耶鲁、斯坦福、普林斯顿、杜克大学等约400家全球著名机构使用GenScript的基因合成、多肽服务、抗体服务和蛋白服务等成功地发表科研成果,再次证明GenScript 有能力帮助业内科学家Make research easy.
文献搜索
Rapid generation of hypomorphic mutations.
Nat Commun.2017;
Arthur Laura L,Chung Joyce J,Jankirama Preetam,Keefer Kathryn M,Kolotilin Igor,Pavlovic-Djuranovic Slavica,Chalker Douglas L,Grbic Vojislava,Green Rachel,Menassa Rima,True Heather L,Skeath James B,Djuranovic Se
Hypomorphic mutations are a valuable tool for both genetic analysis of gene function and for synthetic biology applications. However, current methods to generate hypomorphic mutations are limited to a specific organism, change gene expression unpredictably, or depend on changes in spatial-temporal expression of the targeted gene. Here we present a simple and predictable method to generate hypomorphic mutations in model organisms by targeting translation elongation. Adding consecutive adenosine nucleotides, so-called polyA tracks, to the gene coding sequence of interest will decrease translation elongation efficiency, and in all tested cell cultures and model organisms, this decreases mRNA stabilit... More
Hypomorphic mutations are a valuable tool for both genetic analysis of gene function and for synthetic biology applications. However, current methods to generate hypomorphic mutations are limited to a specific organism, change gene expression unpredictably, or depend on changes in spatial-temporal expression of the targeted gene. Here we present a simple and predictable method to generate hypomorphic mutations in model organisms by targeting translation elongation. Adding consecutive adenosine nucleotides, so-called polyA tracks, to the gene coding sequence of interest will decrease translation elongation efficiency, and in all tested cell cultures and model organisms, this decreases mRNA stability and protein expression. We show that protein expression is adjustable independent of promoter strength and can be further modulated by changing sequence features of the polyA tracks. These characteristics make this method highly predictable and tractable for generation of programmable allelic series with a range of expression levels.