Unknown

Dataset Information

0

Ribosome occupancy profiles are conserved between structurally and evolutionarily related yeast domains.


ABSTRACT:

Motivation

Protein synthesis is a non-equilibrium process, meaning that the speed of translation can influence the ability of proteins to fold and function. Assuming that structurally similar proteins fold by similar pathways, the profile of translation speed along an mRNA should be evolutionarily conserved between related proteins to direct correct folding and downstream function. The only evidence to date for such conservation of translation speed between homologous proteins has used codon rarity as a proxy for translation speed. There are, however, many other factors including mRNA structure and the chemistry of the amino acids in the A- and P-sites of the ribosome that influence the speed of amino acid addition.

Results

Ribosome profiling experiments provide a signal directly proportional to the underlying translation times at the level of individual codons. We compared ribosome occupancy profiles (extracted from five different large-scale yeast ribosome profiling studies) between related protein domains to more directly test if their translation schedule was conserved. Our analysis reveals that the ribosome occupancy profiles of paralogous domains tend to be significantly more similar to one another than to profiles of non-paralogous domains. This trend does not depend on domain length, structural classes, amino acid composition, or sequence similarity. Our results indicate that entire ribosome occupancy profiles and not just rare codon locations are conserved between even distantly related domains in yeast, providing support for the hypothesis that translation schedule is conserved between structurally related domains to retain folding pathways and facilitate efficient folding.

Availability

Python3 code is available on GitHub at https://github.com/DanNissley/Compare-ribosome-occupancy-profiles.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Nissley DA 

PROVIDER: S-EPMC8317121 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC1948957 | biostudies-literature
| S-EPMC165665 | biostudies-literature
| S-EPMC2373605 | biostudies-literature
| S-EPMC8791257 | biostudies-literature
| S-EPMC2877573 | biostudies-literature
| S-EPMC1182216 | biostudies-literature
| S-EPMC5068261 | biostudies-literature
2018-03-01 | GSE106246 | GEO
| S-EPMC5625922 | biostudies-literature
| S-EPMC3210774 | biostudies-literature