Reconstructing the history of variation in effective population size along phylogenies

Lanore

Molecular Biology and Evolution

2021

Self Cite

Mutation-selection phylogenetic codon models are grounded on population genetics first principles and represent a principled approach for investigating the intricate interplay between mutation, selection and drift. In their current form, mutation-selection codon models are entirely characterized by the collection of site-specific amino-acid fitness profiles. However, thus far, they have relied on the assumption of a constant genetic drift, translating into a unique effective population size (Ne) across the phylogeny, clearly an unrealistic assumption. This assumption can be alleviated by introducing variation in Ne between lineages. In addition to Ne, the mutation rate (μ) is susceptible to vary between lineages, and both should co-vary with life-history traits (LHTs). This suggests that the model should more globally account for the joint evolutionary process followed by all of these lineage-specific variables (Ne, μ, and LHTs). In this direction, we introduce an extended mutation-selection model jointly reconstructing in a Bayesian Monte Carlo framework the fitness landscape across sites and long-term trends in Ne, μ and LHTs along the phylogeny, from an alignment of DNA coding sequences and a matrix of observed LHTs in extant species. The model was tested against simulated data and applied to empirical data in mammals, isopods and primates. The reconstructed history of Ne in these groups appears to correlate with LHTs or ecological variables in a way that suggests that the reconstruction is reasonable, at least in its global trends. On the other hand, the range of variation in Ne inferred across species is surprisingly narrow. This last point suggests that some of the assumptions of the model, in particular concerning the assumed absence of epistatic interactions between sites, are potentially problematic.

“…Again, the total range of the inferred variation in

across the entire tree is narrow, with ratio of 6.4 at most between high and low

. These results contrast with the finding of Brevet and Lartillot (2021) on the same data set based on

-based codon models, where the estimated

was found to span several orders of magnitude, and correlated positively with π S .…”

Section: Resultscontrasting

confidence: 99%

), are available for 10 species across the data set and are expected to correlate with

according to population genetics ( Eyre-walker and Keightley 2007 ; Galtier 2016 ).…”

Section: Resultsmentioning

confidence: 99%

Inferring Long-Term Effective Population Size with Mutation–Selection Models

Lanore

Molecular Biology and Evolution

2021

Self Cite

“…These analyses showed mitigated support for a negative relation between ω and N e (Lanfear et al , 2014). More recently, phylogenetic integrative methods refined the estimate of covariation between ω and N e along lineages by leveraging polymorphism data (Brevet and Lartillot, 2019). This approach gives an estimate of in primates (supplementary materials) at least one order of magnitude greater than the quantitative estimate obtained above from the biophysical model.…”

Section: Discussionmentioning

confidence: 99%

A theoretical approach for quantifying the impact of changes in effective population size and expression level on the rate of coding sequence evolution

2021

Preprint

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Molecular sequences are shaped by selection, where the strength of selection relative to drift is determined by effective population size (Ne). Populations with high Ne 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 Ne, a result proven under general conditions. Together, the response of ω to changes in Ne 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 Ne 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 Ne 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 Ne.

“…Next, our empirical framework was also applied on a set of genes sampled across primates, taken from Perelman et al (2011) and reanalysed in Brevet and Lartillot (2019). In addition to LHTs (mass, female maturity, generation time and longevity), information about nuclear synonymous diversity (π S ) and nonsynonymous over synonymous diversity (π N /π S ), are available for 10 species across the dataset and are expected to correlate with N e according to population genetics (Eyre-walker and Keightley, 2007;Galtier, 2016).…”

Section: Empirical Experimentsmentioning

confidence: 99%

“…using polymorphism), this effect could be used to leverage a quantitative estimate of the statistical distribution of epistatic effects. (Brevet and Lartillot, 2019). This method implicitly relies on a nearly-neutral model, assuming a fixed and gamma-shaped distribution of fitness effects across non-synonymous mutations.…”

Section: Reliability Of the Inference Of The Phylogenetic History Of N Ementioning

confidence: 99%

Inferring long-term effective population size with Mutation-Selection models

Lanore

2021

Preprint

Self Cite

Mutation-selection phylogenetic codon models are grounded on population genetics first principles and represent a principled approach for investigating the intricate interplay between mutation, selection and drift. In their current form, mutation-selection codon models are entirely characterized by the collection of site-specific amino-acid fitness profiles. However, thus far, they have relied on the assumption of a constant genetic drift, translating into a unique effective population size (Ne) across the phylogeny, clearly an unreasonable hypothesis. This assumption can be alleviated by introducing variation in Ne between lineages. In addition to Ne, the mutation rate (μ) is susceptible to vary between lineages, and both should co-vary with life-history traits (LHTs). This suggests that the model should more globally account for the joint evolutionary process followed by all of these lineage-specific variables (Ne, μ, and LHTs). In this direction, we introduce an extended mutation-selection model jointly reconstructing in a Bayesian Monte Carlo framework the fitness landscape across sites and long-term trends in Ne, μ and LHTs along the phylogeny, from an alignment of DNA coding sequences and a matrix of observed LHTs in extant species. The model was tested against simulated data and applied to empirical data in mammals, isopods and primates. The reconstructed history of Ne in these groups appears to correlate with LHTs or ecological variables in a way that suggests that the reconstruction is reasonable, at least in its global trends. On the other hand, the range of variation in Ne inferred across species is surprisingly narrow. This last point suggests that some of the assumptions of the model, in particular concerning the assumed absence of epistatic interactions between sites, are potentially problematic.