Estimating the Effective Population Size from Temporal Allele Frequency Changes in Experimental Evolution

摘要

The effective population size (![Formula][1]/img) is a major factor determining allele frequency changes in natural and experimental populations. Temporal methods provide a powerful and simple approach to estimate short-term ![Formula][2]/img They use allele frequency shifts between temporal samples to calculate the standardized variance, which is directly related to ![Formula][3]/img Here we focus on experimental evolution studies that often rely on repeated sequencing of samples in pools (Pool-seq). Pool-seq is cost-effective and often outperforms individual-based sequencing in estimating allele frequencies, but it is associated with atypical sampling properties: Additional to sampling individuals, sequencing DNA in pools leads to a second round of sampling, which increases the variance of allele frequency estimates. We propose a new estimator of ![Formula][4]/img which relies on allele frequency changes in temporal data and corrects for the variance in both sampling steps. In simulations, we obtain accurate ![Formula][5]/img estimates, as long as the drift variance is not too small compared to the sampling and sequencing variance. In addition to genome-wide ![Formula][6]/img estimates, we extend our method using a recursive partitioning approach to estimate ![Formula][7]/img locally along the chromosome. Since the type I error is controlled, our method permits the identification of genomic regions that differ significantly in their ![Formula][8]/img estimates. We present an application to Pool-seq data from experimental evolution with Drosophila and provide recommendations for whole-genome data. The estimator is computationally efficient and available as an R package at https://github.com/ThomasTaus/Nest. [1]: /embed/mml-math-1.gif [2]: /embed/mml-math-2.gif [3]: /embed/mml-math-3.gif [4]: /embed/mml-math-4.gif [5]: /embed/mml-math-5.gif [6]: /embed/mml-math-6.gif [7]: /embed/mml-math-7.gif [8]: /embed/mml-math-8.gif