five

Identification of two short internal ribosome entry sites selected from libraries of random oligonucleotides

收藏
PubMed Central2001-02-13 更新2026-05-02 收录
下载链接:
https://pmc.ncbi.nlm.nih.gov/articles/PMC29281/
下载链接
链接失效反馈
官方服务:
资源简介:
Sequences that control translation of mRNA may play critical roles in regulating protein levels. One such element is the internal ribosome entry site (IRES). We previously showed that a 9-nt segment in the 5′ leader sequence of the mRNA encoding Gtx homeodomain protein could function as an IRES. To identify other short sequences with similar properties, we designed a selection procedure that uses a retroviral vector to express dicistronic mRNAs encoding enhanced green and cyan fluorescent proteins as the first and second cistrons, respectively. Expression of the second cistron was dependent upon the intercistronic sequences and was indicative of IRES activity. B104 cells were infected with two retroviral libraries that contained random sequences of 9 or 18 nt in the intercistronic region. Cells expressing both cistrons were sorted, and sequences recovered from selected cells were reassayed for IRES activity in a dual luciferase dicistronic mRNA. Two novel IRESes were identified by this procedure, and both contained segments with complementarity to 18S rRNA. When multiple copies of either segment were linked together, IRES activities were dramatically enhanced. Moreover, these synthetic IRESes were differentially active in various cell types. These properties are similar to those of the previously identified 9-nt IRES module from Gtx mRNA. These results provide further evidence that short nucleotide sequences can function as IRESes and support the idea that some cellular IRESes may be composed of shorter functional modules. The ability to identify IRES modules with specific expression properties may be useful in the design of vectors for biotechnology and gene therapy.
提供机构:
National Academy of Sciences
创建时间:
2001-02-13
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作