Different modes of non-genetic inheritance are expected to affect population persistence in fluctuating environments. We here analyze Caenorhabiditis elegans density-independent per capita growth rate time series on 36 populations experiencing 6 controlled sequences of challenging oxygen level fluctuations across 60 generations, and parameterize competing models of non-genetic inheritance in order to explain observed dynamics. Our analysis shows that phenotypic plasticity and anticipatory maternal effects are sufficient to explain growth rate dynamics, but that a carryover model where ``epigenetic" memory is imperfectly transmitted and might be reset at each generation is a better fit to the data. We further find that this epigenetic memory is asymmetric since it is kept for longer when populations are exposed to the more challenging environment. Our analysis suggests that population persistence in fluctuating environments depends on the non-genetic inheritance of phenotypes whose expression is regulated across multiple generations.
Additive Maternal Effect Model Code
Rmarkdown file for running only the "additive" model of the maternal effects model.
AdditiveModel.Rmd
Additive maternal effects model stan file
Additive maternal effects model stan file
AdditiveTGP_logscale.stan
Maternal Effects stan file
Maternal Effects stan file
AME.stan
Phenotypic carryover stan file
Carryover stan file which includes generated quantities that can be used for additional statistical analysis. Output using this stan file is quite large
Carryover_generatedQuant.stan
Phenotypic carryover stan file
Carryover stan file which does not include generated quantities. Output using this stan file is smaller.
Carryover.stan
Simulation code for population genetic data
Forward stochastic simulation of population genetic process to generate null model time-series data
CreatePopGenSim.nb
Growth rate time series dataset rmd
Population growth rate time series data in R format
GrowthData-normoxia_anoxia.rds
Population growth rate time series dataset
Population growth rate time series dataset in csv format.
GrowthRateTimeSeries.csv
Main analysis file
This is the main R file for running the analysis. It includes descriptive plots of the time series data, Bayesian fitting for the alternative models, and comparison of LOO values.
MainStats.Rmd
Generate plots of phenotype dynamics
Rmarkdown to generate the figures that show the dynamics of the hidden S phenotype.
PhenotypePlots.Rmd
Generate posterior predictive plots
Rmarkdown to perform posterior predictive fit analysis. This requires the model fitting ourput from MainStats to already be complete.
PosteriorPredictiveFits.Rmd
Fit models to simulated data.
Rmarkdown to fit the alternative models to a set of simulated data.
RunStanSimData.Rmd
simulated data from population genetic model
Simulated time-series data from forward popualtion genetic model.
simdata.csv