Post-transcriptional mechanisms modulate the consequences of adaptive copy number variation.


Journal

bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
23 Oct 2023
Historique:
pubmed: 14 11 2023
medline: 14 11 2023
entrez: 14 11 2023
Statut: epublish

Résumé

Copy-number variants (CNVs) are large-scale amplifications or deletions of DNA that can drive rapid adaptive evolution and result in large-scale changes in gene expression. Whereas alterations in the copy number of one or more genes within a CNV can confer a selective advantage, other genes within a CNV can decrease fitness when their dosage is changed. Dosage compensation - in which the gene expression output from multiple gene copies is less than expected - is one means by which an organism can mitigate the fitness costs of deleterious gene amplification. Previous research has shown evidence for dosage compensation at both the transcriptional level and at the level of protein expression; however, the extent of compensation differs substantially between genes, strains, and studies. Here, we investigated sources of dosage compensation at multiple levels of gene expression regulation by defining the transcriptome, translatome and proteome of experimentally evolved yeast (

Identifiants

pubmed: 37961325
doi: 10.1101/2023.10.20.563336
pmc: PMC10634702
pii:
doi:

Types de publication

Preprint

Langues

eng

Subventions

Organisme : NIGMS NIH HHS
ID : F32 GM131573
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM134066
Pays : United States

Auteurs

Pieter Spealman (P)

Center for Genomics and Systems Biology, Department of Biology, New York University.

Carolina de Santana (C)

Laboratório de Microbiologia Ambiental e Saúde Pública - Universidade Estadual de Feira de Santana (UEFS), Bahia.

Titir De (T)

Center for Genomics and Systems Biology, Department of Biology, New York University.

David Gresham (D)

Center for Genomics and Systems Biology, Department of Biology, New York University.

Classifications MeSH