SMILE

Stochastic Models for the Inference of Life Evolution

Population genomics from pool sequencing

Ferretti, L., Ramos-Onsins, S. E., Pérez-Enciso, M.

Molecular Ecology

2013

Next generation sequencing of pooled samples is an effective approach for studies of variability and differentiation in populations. In this paper we provide a comprehensive set of estimators of the most common statistics in population genetics based on the frequency spectrum, namely the Watterson estimator θW, nucleotide pairwise diversity Π, Tajima's D, Fu and Li's D and F, Fay and Wu's H, McDonald-Kreitman and HKA tests and FST, corrected for sequencing errors and ascertainment bias. In a simulation study, we show that pool and individual θ estimates are highly correlated and discuss how the performance of the statistics vary with read depth and sample size in different evolutionary scenarios. As an application, we reanalyse sequences from Drosophila mauritiana and from an evolution experiment in Drosophila melanogaster. These methods are useful for population genetic projects with limited budget, study of communities of individuals that are hard to isolate, or autopolyploid species.

Bibtex

@article{ferretti_population_2013,
Author = {Ferretti, Luca and Ramos-Onsins, Sebastián E. and
Pérez-Enciso, Miguel},
Title = {Population genomics from pool sequencing},
Journal = {Molecular Ecology},
Volume = {22},
Number = {22},
Pages = {5561--5576},
abstract = {Next generation sequencing of pooled samples is an
effective approach for studies of variability and
differentiation in populations. In this paper we
provide a comprehensive set of estimators of the most
common statistics in population genetics based on the
frequency spectrum, namely the Watterson estimator θW,
nucleotide pairwise diversity Π, Tajima's D, Fu and
Li's D and F, Fay and Wu's H, McDonald-Kreitman and HKA
tests and FST, corrected for sequencing errors and
ascertainment bias. In a simulation study, we show that
pool and individual θ estimates are highly correlated
and discuss how the performance of the statistics vary
with read depth and sample size in different
evolutionary scenarios. As an application, we reanalyse
sequences from Drosophila mauritiana and from an
evolution experiment in Drosophila melanogaster. These
methods are useful for population genetic projects with
limited budget, study of communities of individuals
that are hard to isolate, or autopolyploid species.},
doi = {10.1111/mec.12522},
issn = {1365-294X},
language = {eng},
month = nov,
pmid = {24102736},
year = 2013
}

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