Literature DB >> 28007979

Secreted Proteins Defy the Expression Level-Evolutionary Rate Anticorrelation.

Felix Feyertag1, Patricia M Berninsone1, David Alvarez-Ponce1.   

Abstract

The rates of evolution of the proteins of any organism vary across orders of magnitude. A primary factor influencing rates of protein evolution is expression. A strong negative correlation between expression levels and evolutionary rates (the so-called E-R anticorrelation) has been observed in virtually all studied organisms. This effect is currently attributed to the abundance-dependent fitness costs of misfolding and unspecific protein-protein interactions, among other factors. Secreted proteins are folded in the endoplasmic reticulum, a compartment where chaperones, folding catalysts, and stringent quality control mechanisms promote their correct folding and may reduce the fitness costs of misfolding. In addition, confinement of secreted proteins to the extracellular space may reduce misinteractions and their deleterious effects. We hypothesize that each of these factors (the secretory pathway quality control and extracellular location) may reduce the strength of the E-R anticorrelation. Indeed, here we show that among human proteins that are secreted to the extracellular space, rates of evolution do not correlate with protein abundances. This trend is robust to controlling for several potentially confounding factors and is also observed when analyzing protein abundance data for 6 human tissues. In addition, analysis of mRNA abundance data for 32 human tissues shows that the E-R correlation is always less negative, and sometimes nonsignificant, in secreted proteins. Similar observations were made in Caenorhabditis elegans and in Escherichia coli, and to a lesser extent in Drosophila melanogaster, Saccharomyces cerevisiae and Arabidopsis thaliana. Our observations contribute to understand the causes of the E-R anticorrelation.
© The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  E–R anticorrelation; dN/dS; expression levels; rates of evolution; secreted proteins.

Mesh:

Substances:

Year:  2017        PMID: 28007979      PMCID: PMC5896516          DOI: 10.1093/molbev/msw268

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  97 in total

1.  Codon usage tabulated from international DNA sequence databases: status for the year 2000.

Authors:  Y Nakamura; T Gojobori; T Ikemura
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis.

Authors:  J Castresana
Journal:  Mol Biol Evol       Date:  2000-04       Impact factor: 16.240

3.  Intrinsic errors in genome annotation.

Authors:  D Devos; A Valencia
Journal:  Trends Genet       Date:  2001-08       Impact factor: 11.639

4.  Integrating high-throughput and computational data elucidates bacterial networks.

Authors:  Markus W Covert; Eric M Knight; Jennifer L Reed; Markus J Herrgard; Bernhard O Palsson
Journal:  Nature       Date:  2004-05-06       Impact factor: 49.962

5.  The codon Adaptation Index--a measure of directional synonymous codon usage bias, and its potential applications.

Authors:  P M Sharp; W H Li
Journal:  Nucleic Acids Res       Date:  1987-02-11       Impact factor: 16.971

6.  A surveillance pathway monitors the fitness of the endoplasmic reticulum to control its inheritance.

Authors:  Anna Babour; Alicia A Bicknell; Joel Tourtellotte; Maho Niwa
Journal:  Cell       Date:  2010-07-08       Impact factor: 41.582

Review 7.  Determinants of the rate of protein sequence evolution.

Authors:  Jianzhi Zhang; Jian-Rong Yang
Journal:  Nat Rev Genet       Date:  2015-06-09       Impact factor: 53.242

8.  ProTherm and ProNIT: thermodynamic databases for proteins and protein-nucleic acid interactions.

Authors:  M D Shaji Kumar; K Abdulla Bava; M Michael Gromiha; Ponraj Prabakaran; Koji Kitajima; Hatsuho Uedaira; Akinori Sarai
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

9.  ArrayExpress update--simplifying data submissions.

Authors:  Nikolay Kolesnikov; Emma Hastings; Maria Keays; Olga Melnichuk; Y Amy Tang; Eleanor Williams; Miroslaw Dylag; Natalja Kurbatova; Marco Brandizi; Tony Burdett; Karyn Megy; Ekaterina Pilicheva; Gabriella Rustici; Andrew Tikhonov; Helen Parkinson; Robert Petryszak; Ugis Sarkans; Alvis Brazma
Journal:  Nucleic Acids Res       Date:  2014-10-31       Impact factor: 16.971

Review 10.  Conserved and plant-unique strategies for overcoming endoplasmic reticulum stress.

Authors:  Cristina Ruberti; Federica Brandizzi
Journal:  Front Plant Sci       Date:  2014-02-26       Impact factor: 5.753

View more
  6 in total

1.  The Old and the New: Discovery Proteomics Identifies Putative Novel Seminal Fluid Proteins in Drosophila.

Authors:  Timothy L Karr; Helen Southern; Matthew A Rosenow; Toni I Gossmann; Rhonda R Snook
Journal:  Mol Cell Proteomics       Date:  2019-02-13       Impact factor: 5.911

2.  Gene expression of functionally-related genes coevolves across fungal species: detecting coevolution of gene expression using phylogenetic comparative methods.

Authors:  Alexander L Cope; Brian C O'Meara; Michael A Gilchrist
Journal:  BMC Genomics       Date:  2020-05-20       Impact factor: 3.969

3.  Gene expression variation in the brains of harvester ant foragers is associated with collective behavior.

Authors:  Daniel Ari Friedman; Ryan Alexander York; Austin Travis Hilliard; Deborah M Gordon
Journal:  Commun Biol       Date:  2020-03-05

4.  Extracellular Domains of Transmembrane Proteins Defy the Expression Level-Evolutionary Rate Anticorrelation.

Authors:  Chandra Sarkar; David Alvarez-Ponce
Journal:  Genome Biol Evol       Date:  2022-01-04       Impact factor: 3.416

5.  Position Matters: Network Centrality Considerably Impacts Rates of Protein Evolution in the Human Protein-Protein Interaction Network.

Authors:  David Alvarez-Ponce; Felix Feyertag; Sandip Chakraborty
Journal:  Genome Biol Evol       Date:  2017-06-01       Impact factor: 3.416

6.  Correlates of evolutionary rates in the murine sperm proteome.

Authors:  Julia Schumacher; Holger Herlyn
Journal:  BMC Evol Biol       Date:  2018-03-27       Impact factor: 3.260

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.