Temporal Analysis of Effective Population Size and Mating System in a Social Wasp. (24th September 2021)

• Record Type: Journal Article
• Authors: Dyson, Carl J; Piscano, Olivia L; Durham, Rebecca M; Thompson, Veronica J; Johnson, Catherine H; Goodisman, Michael A D
• Editors: Booth, Warren
• Is Part Of: Journal of heredity. Volume 112:Number 7(2021)
• Page Start: 626
• Page End: 634
• Publication Date: 2021-09-24
• Subjects: DNA microsatellite -- Eusocial -- Hymenoptera -- polyandry -- social behavior -- yellowjacket wasp; Breeding -- Periodicals; Plant breeding -- Periodicals; Heredity -- Periodicals; 576.5
• DOI: 10.1093/jhered/esab057
• Languages: English
• ISSNs: 0022-1503

Abstract

Abstract: Highly social species are successful because they cooperate in obligately integrated societies. We examined temporal genetic variation in the eusocial wasp Vespula maculifrons to gain a greater understanding of evolution in highly social taxa. First, we wished to test if effective population sizes of eusocial species were relatively low due to the reproductive division of labor that characterizes eusocial taxa. We thus estimated the effective population size of V. maculifrons by examining temporal changes in population allele frequencies. We sampled the genetic composition of a V. maculifrons population at 3 separate timepoints spanning a 13-year period. We found that effective population size ranged in the hundreds of individuals, which is similar to estimates in other, non-eusocial taxa. Second, we estimated levels of polyandry in V. maculifrons in different years to determine if queen mating system varied over time. We found no significant change in the number or skew of males mated to queens. In addition, mating skew was not significant within V. maculifrons colonies. Therefore, our data suggest that queen mate number may be subject to stabilizing selection in this taxon. Overall, our study provides novel insight into the selective processes operating in eusocial species by analyzing temporal genetic changes within populations.