The Evolution of Gene-Specific Transcriptional Noise Is Driven by Selection at the Pathway Level
| Autor: | Julien Y. Dutheil, Natasa Puzovic, Gustavo Valadares Barroso |
|---|---|
| Přispěvatelé: | Max Planck Institute for Evolutionary Biology, Max-Planck-Gesellschaft, Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UR226 |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
MESH: Gene Ontology
0301 basic medicine Transcription Genetic MESH: Selection Genetic Gene regulatory network Gene Expression Mice Gene expression Protein Interaction Mapping MESH: Animals MESH: Models Genetic Protein Interaction Maps MESH: Protein Interaction Maps MESH: Evolution Molecular Regulation of gene expression Genetics Natural selection MESH: Genomics Systems Biology food and beverages MESH: Transcription Factors Genomics MESH: Gene Expression Regulation biological networks MESH: Systems Biology expression noise Single-Cell Analysis Transcriptional noise MESH: Computational Biology Protein Binding inorganic chemicals Systems biology Biology Investigations complex mixtures Evolution Molecular MESH: Gene Expression Profiling 03 medical and health sciences medicine MESH: Protein Binding Mus musculus Animals Selection Genetic MESH: Mice Gene [SDV.GEN]Life Sciences [q-bio]/Genetics Models Genetic MESH: Transcription Genetic MESH: Transcriptome Gene Expression Profiling MESH: Protein Interaction Mapping Computational Biology medicine.disease equipment and supplies Gene expression profiling 030104 developmental biology evolution of gene expression Gene Ontology Gene Expression Regulation MESH: Genome-Wide Association Study bacteria Transcriptome MESH: Single-Cell Analysis Genome-Wide Association Study Transcription Factors |
| Zdroj: | Genetics Genetics, Genetics Society of America, 2018, 208 (1), pp.173-189. ⟨10.1534/genetics.117.300467⟩ |
| ISSN: | 1943-2631 0016-6731 |
| DOI: | 10.1534/genetics.117.300467⟩ |
| Popis: | Gene expression is a noisy process: in constant environment and genotype, cell to cell variability occurs because of randomness of biochemical reactions... Biochemical reactions within individual cells result from the interactions of molecules, typically in small numbers. Consequently, the inherent stochasticity of binding and diffusion processes generates noise along the cascade that leads to the synthesis of a protein from its encoding gene. As a result, isogenic cell populations display phenotypic variability even in homogeneous environments. The extent and consequences of this stochastic gene expression have only recently been assessed on a genome-wide scale, owing, in particular, to the advent of single-cell transcriptomics. However, the evolutionary forces shaping this stochasticity have yet to be unraveled. Here, we take advantage of two recently published data sets for the single-cell transcriptome of the domestic mouse Mus musculus to characterize the effect of natural selection on gene-specific transcriptional stochasticity. We show that noise levels in the mRNA distributions (also known as transcriptional noise) significantly correlate with three-dimensional nuclear domain organization, evolutionary constraints on the encoded protein, and gene age. However, the position of the encoded protein in a biological pathway is the main factor that explains observed levels of transcriptional noise, in agreement with models of noise propagation within gene networks. Because transcriptional noise is under widespread selection, we argue that it constitutes an important component of the phenotype and that variance of expression is a potential target of adaptation. Stochastic gene expression should therefore be considered together with the mean expression level in functional and evolutionary studies of gene expression. |
| Databáze: | OpenAIRE |
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