Quantifying the impact of changes in effective population size and expression level on the rate of coding sequence evolution

Autor: Thibault Latrille, Nicolas Lartillot
Přispěvatelé: Bioinformatique, phylogénie et génomique évolutive (BPGE), Département PEGASE [LBBE] (PEGASE), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)
Rok vydání: 2021
Předmět:
0106 biological sciences
Population genetics
expression level
[SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics
Phylogenetics and taxonomy
010603 evolutionary biology
01 natural sciences
Evolution
Molecular
03 medical and health sciences
Negative selection
Effective population size
[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry
Molecular Biology/Genomics [q-bio.GN]
Selection
Genetic
Ecology
Evolution
Behavior and Systematics
Selection (genetic algorithm)
030304 developmental biology
Mathematics
Population Density
[STAT.AP]Statistics [stat]/Applications [stat.AP]
0303 health sciences
Sequence
Models
Genetic
drift
[SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE]
Substitution (logic)
Expression (computer science)
substitution rate
protein stability
population-genetics
Mutation
Biological system
[STAT.ME]Statistics [stat]/Methodology [stat.ME]
Neutral mutation
Zdroj: Theoretical Population Biology
Theoretical Population Biology, 2021, 142, pp.57-66. ⟨10.1016/j.tpb.2021.09.005⟩
Theoretical Population Biology, Elsevier, 2021, 142, pp.57-66. ⟨10.1016/j.tpb.2021.09.005⟩
ISSN: 0040-5809
1096-0325
DOI: 10.1016/j.tpb.2021.09.005
Popis: Molecular sequences are shaped by selection, where the strength of selection relative to drift is determined by effective population size ( N e ). Populations with high N e are expected to undergo stronger purifying selection, and consequently to show a lower substitution rate for selected mutations relative to the substitution rate for neutral mutations ( ω ). However, computational models based on biophysics of protein stability have suggested that ω can also be independent of N e . Together, the response of ω to changes in N e depends on the specific mapping from sequence to fitness. Importantly, an increase in protein expression level has been found empirically to result in decrease of ω , an observation predicted by theoretical models assuming selection for protein stability. Here, we derive a theoretical approximation for the response of ω to changes in N e and expression level, under an explicit genotype-phenotype-fitness map. The method is generally valid for additive traits and log-concave fitness functions. We applied these results to protein undergoing selection for their conformational stability and corroborate out findings with simulations under more complex models. We predict a weak response of ω to changes in either N e or expression level, which are interchangeable. Based on empirical data, we propose that fitness based on the conformational stability may not be a sufficient mechanism to explain the empirically observed variation in ω across species. Other aspects of protein biophysics might be explored, such as protein–protein interactions, which can lead to a stronger response of ω to changes in N e .
Databáze: OpenAIRE
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