Jun 28, 2014

Multi-locus analysis of genomic time series data from experimental evolution

BioRxiv : the Preprint Server for Biology
Jonathan Terhorst, Yun S. Song

Abstract

Genomic time series data generated by evolve-and-resequence (E&R) experiments offer a powerful window into the mechanisms that drive evolution. However, standard population genetic inference procedures do not account for sampling serially over time, and new methods are needed to make full use of modern experimental evolution data. To address this problem, we develop a Gaussian process approximation to the multi-locus Wright-Fisher process with selection over a time course of tens of generations. The mean and covariance structure of the Gaussian process are obtained by computing the corresponding moments in discrete-time Wright-Fisher models conditioned on the presence of a linked selected site. This enables our method to account for the effects of linkage and selection, both along the genome and across sampled time points, in an approximate but principled manner. Using simulated data, we demonstrate the power of our method to correctly detect, locate and estimate the fitness of a selected allele from among several linked sites. We also study how this power changes for different values of selection strength, initial haplotypic diversity, population size, sampling frequency, experimental duration, number of replicates, and sequen...Continue Reading

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Mentioned in this Paper

Genome
Recombination, Genetic
Nucleic Acid Sequencing
Site
Genomics
Sequencing
Toxic Epidermal Necrolysis
Analysis
Locus
Alleles

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