Literature DB >> 33562654

A Trans-Omics Comparison Reveals Common Gene Expression Strategies in Four Model Organisms and Exposes Similarities and Differences between Them.

Jaume Forés-Martos1, Anabel Forte2, José García-Martínez1, José E Pérez-Ortín1.   

Abstract

The ultimate goal of gene expression regulation is on the protein level. However, because the amounts of mRNAs and proteins are controlled by their synthesis and degradation rates, the cellular amount of a given protein can be attained by following different strategies. By studying omics data for six expression variables (mRNA and protein amounts, plus their synthesis and decay rates), we previously demonstrated the existence of common expression strategies (CESs) for functionally related genes in the yeast Saccharomyces cerevisiae. Here we extend that study to two other eukaryotes: the yeast Schizosaccharomyces pombe and cultured human HeLa cells. We also use genomic data from the model prokaryote Escherichia coli as an external reference. We show that six-variable profiles (6VPs) can be constructed for every gene and that these 6VPs are similar for genes with similar functions in all the studied organisms. The differences in 6VPs between organisms can be used to establish their phylogenetic relationships. The analysis of the correlations among the six variables supports the hypothesis that most gene expression control occurs in actively growing organisms at the transcription rate level, and that translation plays a minor role. We propose that living organisms use CESs for the genes acting on the same physiological pathways, especially for those belonging to stable macromolecular complexes, but CESs have been modeled by evolution to adapt to the specific life circumstances of each organism.

Entities:  

Keywords:  mRNA stability; phenogram; protein stability; transcription rate; translation rate

Year:  2021        PMID: 33562654      PMCID: PMC7914595          DOI: 10.3390/cells10020334

Source DB:  PubMed          Journal:  Cells        ISSN: 2073-4409            Impact factor:   6.600


  81 in total

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Authors:  Yulei Wang; Chih Long Liu; John D Storey; Robert J Tibshirani; Daniel Herschlag; Patrick O Brown
Journal:  Proc Natl Acad Sci U S A       Date:  2002-04-23       Impact factor: 11.205

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Authors:  F H CRICK
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3.  Reconstructing evolutionary relationships from functional data: a consistent classification of organisms based on translation inhibition response.

Authors:  Carlos Briones; Susanna C Manrubia; Ester Lázaro; Antonio Lazcano; Ricardo Amils
Journal:  Mol Phylogenet Evol       Date:  2004-12-15       Impact factor: 4.286

4.  Evolution. Systematic humanization of yeast genes reveals conserved functions and genetic modularity.

Authors:  Aashiq H Kachroo; Jon M Laurent; Christopher M Yellman; Austin G Meyer; Claus O Wilke; Edward M Marcotte
Journal:  Science       Date:  2015-05-22       Impact factor: 47.728

5.  Gene Ontology Semantic Similarity Analysis Using GOSemSim.

Authors:  Guangchuang Yu
Journal:  Methods Mol Biol       Date:  2020

6.  Escherichia coli achieves faster growth by increasing catalytic and translation rates of proteins.

Authors:  Kaspar Valgepea; Kaarel Adamberg; Andrus Seiman; Raivo Vilu
Journal:  Mol Biosyst       Date:  2013-09

7.  A complete set of nascent transcription rates for yeast genes.

Authors:  Vicent Pelechano; Sebastián Chávez; José E Pérez-Ortín
Journal:  PLoS One       Date:  2010-11-16       Impact factor: 3.240

8.  Transcriptome-wide Analysis of Roles for tRNA Modifications in Translational Regulation.

Authors:  Hsin-Jung Chou; Elisa Donnard; H Tobias Gustafsson; Manuel Garber; Oliver J Rando
Journal:  Mol Cell       Date:  2017-11-30       Impact factor: 17.970

9.  Genome-wide determination of RNA stability reveals hundreds of short-lived noncoding transcripts in mammals.

Authors:  Hidenori Tani; Rena Mizutani; Kazi Abdus Salam; Keiko Tano; Kenichi Ijiri; Ai Wakamatsu; Takao Isogai; Yutaka Suzuki; Nobuyoshi Akimitsu
Journal:  Genome Res       Date:  2012-02-27       Impact factor: 9.043

10.  Multiplexed gene control reveals rapid mRNA turnover.

Authors:  Antoine Baudrimont; Sylvia Voegeli; Eduardo Calero Viloria; Fabian Stritt; Marine Lenon; Takeo Wada; Vincent Jaquet; Attila Becskei
Journal:  Sci Adv       Date:  2017-07-12       Impact factor: 14.136

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  1 in total

1.  Modulation of RNA stability regulates gene expression in two opposite ways: through buffering of RNA levels upon global perturbations and by supporting adapted differential expression.

Authors:  Marie-Line Faucillion; Anna-Mia Johansson; Jan Larsson
Journal:  Nucleic Acids Res       Date:  2022-05-06       Impact factor: 19.160

  1 in total

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