Abstract

Background: Whole-genome sequencing has become routine for population genetic studies. Sequencing of individuals provides maximal data but is rather expensive and fewer samples can be studied. In contrast, sequencing a pool of samples (pool-seq) can provide sufficient data, while presenting less of an economic challenge. Few studies have compared the two approaches to infer population genetic structure and diversity in real datasets. Here, we apply individual sequencing (ind-seq) and pool-seq to the study of Western honey bees (Apis mellifera). Methods: We collected honey bee workers that belonged to 14 populations, including 13 subspecies, totaling 1347 colonies, who were individually (139 individuals) and pool-sequenced (14 pools). We compared allele frequencies, genetic diversity estimates, and population structure as inferred by the two approaches. Results: Pool-seq and ind-seq revealed near identical population structure and genetic diversities, albeit at different costs. While pool-seq provides genome-wide polymorphism data at considerably lower costs, ind-seq can provide additional information, including the identification of population substructures, hybridization, or individual outliers. Conclusions: If costs are not the limiting factor, we recommend using ind-seq, as population genetic structure can be inferred similarly well, with the advantage gained from individual genetic information. Not least, it also significantly reduces the effort required for the collection of numerous samples and their further processing in the laboratory.

Highlights

  • Studying population genetic structure and diversity is the basis of our understanding of biodiversity and the conservation of species [1]

  • Whole-genome sequencing of individuals provides genetic data at the highest resoWhole-genome sequencing of individuals provides at the sample highest resolution

  • Thisgrants rather expensive approach can only applied to aempirically limited sample size, while pool-seq data for a much larger sample set

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Summary

Introduction

Studying population genetic structure and diversity is the basis of our understanding of biodiversity and the conservation of species [1]. To make the best use of limited resources, different sampling and sequencing approaches to study population structure are being adopted, which can be summarized as (i) covering whole genomes, but sampling few individuals When sequencing individually a limited number of samples per population, the estimate of the allele frequencies and the sampling variance stems directly from the selection of individuals [11]. Pool-seq has been statistically shown to produce more accurate estimates of population allele frequencies at a lower cost than sequencing of individuals [9,11,12,13]. Few studies have compared the two approaches to infer population genetic structure and diversity in real datasets. Genetic diversity estimates, and population structure as inferred by the two approaches

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