Transcriptomic basis and evolution of the ant nurse-larval social interactome

PLoS Genet. 2019 May 20;15(5):e1008156. doi: 10.1371/journal.pgen.1008156. eCollection 2019 May.

Abstract

Development is often strongly regulated by interactions among close relatives, but the underlying molecular mechanisms are largely unknown. In eusocial insects, interactions between caregiving worker nurses and larvae regulate larval development and resultant adult phenotypes. Here, we begin to characterize the social interactome regulating ant larval development by collecting and sequencing the transcriptomes of interacting nurses and larvae across time. We find that the majority of nurse and larval transcriptomes exhibit parallel expression dynamics across larval development. We leverage this widespread nurse-larva gene co-expression to infer putative social gene regulatory networks acting between nurses and larvae. Genes with the strongest inferred social effects tend to be peripheral elements of within-tissue regulatory networks and are often known to encode secreted proteins. This includes interesting candidates such as the nurse-expressed giant-lens, which may influence larval epidermal growth factor signaling, a pathway known to influence various aspects of insect development. Finally, we find that genes with the strongest signatures of social regulation tend to experience relaxed selective constraint and are evolutionarily young. Overall, our study provides a first glimpse into the molecular and evolutionary features of the social mechanisms that regulate all aspects of social life.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Ants / genetics*
  • Behavior, Animal / physiology
  • Gene Expression Profiling / methods
  • Gene Regulatory Networks / genetics
  • Genes, Insect / genetics
  • Insecta / genetics
  • Insecta / growth & development
  • Larva / genetics
  • Larva / growth & development*
  • Social Behavior
  • Transcriptome / genetics

Grants and funding

This work was funded by the National Science Foundation (grant number IOS-1452520 to TAL), and subsidy funding from Okinawa Institute of Technology, https://www.oist.jp/ to ASM. The National Science Foundation, https://www.nsf.gov/ also funded MRW (DGE-1321851). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.