Your browser doesn't support javascript.
loading
On the Decoupling of Evolutionary Changes in mRNA and Protein Levels.
Jiang, Daohan; Cope, Alexander L; Zhang, Jianzhi; Pennell, Matt.
Afiliación
  • Jiang D; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
  • Cope AL; Department of Genetics, Rutgers University, Piscataway, NJ, USA.
  • Zhang J; Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ, USA.
  • Pennell M; Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA.
Mol Biol Evol ; 40(8)2023 08 03.
Article en En | MEDLINE | ID: mdl-37498582
Variation in gene expression across lineages is thought to explain much of the observed phenotypic variation and adaptation. The protein is closer to the target of natural selection but gene expression is typically measured as the amount of mRNA. The broad assumption that mRNA levels are good proxies for protein levels has been undermined by a number of studies reporting moderate or weak correlations between the two measures across species. One biological explanation for this discrepancy is that there has been compensatory evolution between the mRNA level and regulation of translation. However, we do not understand the evolutionary conditions necessary for this to occur nor the expected strength of the correlation between mRNA and protein levels. Here, we develop a theoretical model for the coevolution of mRNA and protein levels and investigate the dynamics of the model over time. We find that compensatory evolution is widespread when there is stabilizing selection on the protein level; this observation held true across a variety of regulatory pathways. When the protein level is under directional selection, the mRNA level of a gene and the translation rate of the same gene were negatively correlated across lineages but positively correlated across genes. These findings help explain results from comparative studies of gene expression and potentially enable researchers to disentangle biological and statistical hypotheses for the mismatch between transcriptomic and proteomic data.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ARN Mensajero / Proteínas / Evolución Molecular Tipo de estudio: Prognostic_studies Idioma: En Revista: Mol Biol Evol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ARN Mensajero / Proteínas / Evolución Molecular Tipo de estudio: Prognostic_studies Idioma: En Revista: Mol Biol Evol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos