Journal
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
Volume 23, Issue 20, Pages -Publisher
MDPI
DOI: 10.3390/ijms232012293
Keywords
ribosome; translation; Flow-seq; untranslated region; translation efficiency
Funding
- RFBR [17-00-00369, 17-00-00366, 17-00-00367]
- RSF [21-64-00006]
Ask authors/readers for more resources
Flow-seq is a method that combines fluorescently activated cell sorting and next-generation sequencing to deduce a large amount of data about translation efficiency from a single experiment. It has been demonstrated that a variable length 5'-UTR library can be created and analyzed with Flow-seq, and the influence of RNA secondary structure and Shine-Dalgarno sequences on translation efficiency is smaller for natural 5'-UTRs compared to randomized libraries.
Flow-seq is a method that combines fluorescently activated cell sorting and next-generation sequencing to deduce a large amount of data about translation efficiency from a single experiment. Here, we constructed a library of fluorescent protein-based reporters preceded by a set of 648 natural 5 '-untranslated regions (5 '-UTRs) of Escherichia coli genes. Usually, Flow-seq libraries are constructed using uniform-length sequence elements, in contrast to natural situations, where functional elements are of heterogenous lengths. Here, we demonstrated that a 5 '-UTR library of variable length could be created and analyzed with Flow-seq. In line with previous Flow-seq experiments with randomized 5 '-UTRs, we observed the influence of an RNA secondary structure and Shine-Dalgarno sequences on translation efficiency; however, the variability of these parameters for natural 5 '-UTRs in our library was smaller in comparison with randomized libraries. In line with this, we only observed a 30-fold difference in translation efficiency between the best and worst bins sorted with this factor. The results correlated with those obtained with ribosome profiling.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available