Estimation of population allele frequencies from next‐generation sequencing data: pool‐versus individual‐based genotyping

Abstract

Molecular markers produced by next-generation sequencing (NGS) technologies are revolutionizing genetic research. However, the costs of analysing large numbers of individual genomes remain prohibitive for most population genetics studies. Here, we present results based on mathematical derivations showing that, under many realistic experimental designs, NGS of DNA pools from diploid individuals allows to estimate the allele frequencies at single nucleotide polymorphisms (SNPs) with at least the same accuracy as individual-based analyses, for considerably lower library construction and sequencing efforts. These findings remain true when taking into account the possibility of substantially unequal contributions of each individual to the final pool of sequence reads. We propose the intuitive notion of effective pool size to account for unequal pooling and derive a Bayesian hierarchical model to estimate this parameter directly from the data. We provide a user-friendly application assessing the accuracy of allele frequency estimation from both pool- and individual-based NGS population data under various sampling, sequencing depth and experimental error designs. We illustrate our findings with theoretical examples and real data sets corresponding to SNP loci obtained using restriction site-associated DNA (RAD) sequencing in pool- and individual-based experiments carried out on the same population of the pine processionary moth (Thaumetopoea pityocampa). NGS of DNA pools might not be optimal for all types of studies but provides a cost-effective approach for estimating allele frequencies for very large numbers of SNPs. It thus allows comparison of genome-wide patterns of genetic variation for large numbers of individuals in multiple populations.

Directional genetic differentiation and relative migration

“…2013; Fung and Keenan 2014). As less common alleles (or alleles only present in one population) are used as an indication of no gene flow, rates estimated by the model may be slightly inflated if applied to imprecisely estimated allele frequencies.…”

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

“…(Indeed, there is a discussion on the utility and power of pooled sequencing [37,[43][44][45].) The same multi-locus model underlying our approach can be applied to develop a method for analyzing haplotypic time series data, and we will explore incorporating such an extension into our method.…”

A framework for incorporating evolutionary genomics into biodiversity conservation and management

“…Dual-end barcode sets of 384 or more now exist for the identification of individuals, which makes large sample sizes economical. One limitation of RRS approaches is that loci can suffer from "allelic dropout" due to polymorphisms in restriction sites [60,61], which may lead to an overestimate of divergence.…”

“…As little as 1× coverage of each diploid individual's genome is needed, further reducing cost. However, a lower level of coverage will not adequately represent the pool of individuals, especially when the pool is small to begin with, and can therefore produce misleading population parameter estimates; see [60,61,67]. Guidelines [51,60,61,67] and software packages such as ngsTools [68] and npstat [69], which carry out likelihood-based estimation of allele frequencies, are now available to help tackle these challenges.…”