five

ActD timecourse in mESCs

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://www.ncbi.nlm.nih.gov/sra/SRP312928
下载链接
链接失效反馈
官方服务:
资源简介:
mRNAs are generally assumed to be loaded instantly with ribosomes upon entry into the cytoplasm. To measure ribosome density on nascent mRNA, we developed nascent Ribo-Seq (nRibo-Seq) by combining Ribo-Seq with progressive 4-thiouridine labelling. In mouse macrophages, we experimentally determined, for the first time, the lag between the appearance of nascent RNA and its association with ribosomes, which was calculated to be 20 - 22 min for bulk mRNA, and approximated the time it takes for mRNAs to be fully loaded with ribosomes to be 41 - 44 min. Notably, ribosomal loading time is adapted to gene function as rapid loading was observed with highly regulated genes. The lag and ribosomal loading time correlate positively with ORF size and half-life, and negatively with tRNA adaptation indices. Similar results were obtained in mESCs, where the lag between IN and FP was even more pronounced with 35 - 38 min. We validated our measurements after stimulation of macrophages with lipopolysaccharide, where the lag between cytoplasmic and translated mRNA leads to a corresponding uncoupling between input and ribosome-protected fragments. Uncoupling is stronger for mRNAs with long ORFs or half-lives, a finding we also confirmed at the level of protein production by nascent chain proteomics. As a consequence of the lag in ribosome loading, ribosome density measurements are distorted when performed under conditions where mRNA levels are far from steady state expression, and transcriptional changes affect ribosome density in a passive way. This study uncovers an unexpected and considerable lag in ribosome loading, and provides guidelines for the interpretation of Ribo-Seq data taking passive effects on ribosome density into account. Overall design: Transcriptional shut-off with ActD followed by RNA-Seq to determine mRNA half-lives on a transcriptome-wide scale in mouse embryonic stem cells (mESCs).
创建时间:
2021-09-09
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