Biology subjects

Wilkins, J. F.

Publications and source records attributed to Wilkins, J. F..

2 recordsLinked to original sources

bioRxiv2018

Intragenomic Conflict over Bet-Hedging

Genomic imprinting, where an alleles expression pattern depends on its parental origin, is thought to result primarily from an intragenomic evolutionary conflict. Imprinted genes are widely expressed in the brain and have been linked to various phenotypes, including behaviors related to risk tolerance. In this paper, we analyze a model of evolutionary bet-hedging in a system with imprinted gene expression. Previous analyses of bet-hedging have shown that natural selection may favor alleles and traits that reduce reproductive variance, even at the expense of reducing mean reproductive success, with the trade-off between mean and variance depending on the population size. In species where the sexes have different reproductive variances, this bet-hedging trade-off differs between maternally and paternally inherited alleles. Where males have the higher reproductive variance, alleles are more strongly selected to reduce variance when paternally inherited than when maternally inherited. We connect this result to phenotypes connected with specific imprinted genes, including delay discounting and social dominance. The empirical patterns are consistent with paternally expressed imprinted genes promoting risk-averse behaviors that reduce reproductive variance. Conversely, maternally expressed imprinted genes promote risk-tolerant, variance-increasing behaviors. We indicate how future research might further test the hypotheses suggested by our analysis.

evolutionary biology↗

bioRxiv2017

Quantifying uncertainty in the inference of generalized coalescents

We develop inference methods for generalized coalescent models, such as the{Lambda} - and{Xi} -coalescents, which have recently been proposed for populations with broad offspring distributions, repeated selective sweeps, or strong selection. These are all populations that may not be adequately described by the usual Kingman coalescent. A roadblock to the application of such models has been the lack of effective tools for inferring an appropriate model, which stems from difficulties in evaluating the associated likelihoods. We overcome these difficulties by introducing estimators that are both computationally tractable and statistically efficient. We use these estimators to obtain point estimates and confidence intervals for the parameters of the coalescent models, and p-values for the hypothesis that the population is described by the Kingman coalescent. Our approach is based on the theory of unbiased estimating equations, which is more general than composite likelihood and may be applicable in other areas of statistical genetics. Our main focus is on inference from linked site-frequency spectra using parameterized families of{Lambda} -coalescents. We show that useful inferences may be made from non-singleton data alone if singletons are suspect due to sequencing or data-cleaning errors, although the data requirements are greatly increased. We apply our method to mitochondrial sequence data from Gadus morhua, the Atlantic cod.

genetics↗