Comparative study of population genomic approaches for mapping colony-level traits

• DOI: 10.1371/journal.pcbi.1007653
• Publication Date: 2020-03-27T17:35:10Z
• Authors: Shani Inbar; Pnina Cohen; Tal Yahav; Eyal Privman
• Keywords: 0301 basic medicine; 0303 health sciences; Behavior, Animal; Genotype; Whole Genome Sequencing; QH301-705.5; Ants; Quantitative Trait Loci; Chromosome Mapping; Polymorphism, Single Nucleotide; 03 medical and health sciences; Phenotype; Gene Frequency; Animals; Metagenomics; Biology (General); Social Behavior; Alleles; Research Article; Genome-Wide Association Study

AbstractSocial insect colonies exhibit colony-level phenotypes such as social immunity and task coordination, which are the sum of 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 (GWAS) studies of colony-level traits. We evaluate the accuracy of allele frequency estimation in sequencing a pool of individuals (pool-seq) from each colony in either whole-genome sequencing or reduced representation genomic sequencing. Based on empirical measurement of the experimental noise in sequencing DNA pools, we show that whole-genome pool-seq is more accurate than reduced representation pool-seq. 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 achieves greater QTL detection power.