Abstract

Social insect colonies exhibit colony-level phenotypes such as social immunity and task coordination, which are produced by the individual phenotypes. Mapping the genetic basis of such phenotypes requires associating the colony-level phenotype with the genotypes in the colony. In this paper, we examine alternative approaches to DNA extraction, library construction, and sequencing for genome wide association studies (GWAS) of colony-level traits using a population sample of Cataglyphis niger ants. We evaluate the accuracy of allele frequency estimation from sequencing a pool of individuals (pool-seq) from each colony using either whole-genome sequencing or reduced representation genomic sequencing. Based on empirical measurement of the experimental noise in sequenced DNA pools, we show that reduced representation pool-seq is drastically less accurate than whole-genome pool-seq. Surprisingly, normalized pooling of samples did not result in greater accuracy than un-normalized pooling. Subsequently, we evaluate the power of the alternative approaches for detecting quantitative trait loci (QTL) of colony-level traits by using simulations that account for an environmental effect on the phenotype. Our results can inform experimental designs and enable optimizing the power of GWAS depending on budget, availability of samples and research goals. We conclude that for a given budget, sequencing un-normalized pools of individuals from each colony provides optimal QTL detection power.

Highlights

  • Social insect colonies depend on the collective performance of a large number of individual workers

  • We investigated the effect of sequencing depth on the accuracy of pool-seq allele frequency estimation by sub-sampling the whole-genome sequencing (WG-seq) reads by a factor of 2/3, 1/2, or 1/3

  • We report the first use of empirical measurements of experimental error in pooling DNA from multiple individuals for the purpose of evaluating the power of genome wide association studies (GWAS) for detecting quantitative trait loci (QTL) of colony-level traits

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Summary

Introduction

Social insect colonies depend on the collective performance of a large number of individual workers Such collective performance gives rise to extended, colony-level phenotypes such as social immune responses to pathogens and parasites, coordinated defense against intruders, information transfer and processing, a colonial pheromonal odor that facilitates nestmate recognition, alternative social structures, etc. “Emergent phenotypes” are phenotypes that emerge from the interaction of multiple individuals and are not apparent at the individual level These include foraging patterns and nest architectures [5,6]. Identifying genes responsible for these higher order traits is a challenging endeavor that warrants multilevel modeling

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