Worker survival and egg production– but not transcriptional activity– respond to queen number in the highly polygynous, invasive ant Tapinoma magnum

In social animals, reproductive activity and ageing patterns are influenced by group composition. A well-documented phenomenon in monogynous (one-queen) insect societies is that queen presence affects worker fecundity and longevity. Little is known about whether and how workers respond to queen number variation in polygynous (multi-queen) species and how their queens age. We created queenless, one-queen, and two-queen colonies of the invasive, polygynous ant Tapinoma magnum to examine worker survival, ovary and oocyte development, oxidative stress resistance, and fat body gene expression. Additionally, we compared fecundity, and brain and fat body transcriptomes of young and old queens. Queenless workers experienced the highest mortality, contrasting with monogynous species where queen removal typically extends lifespan. Workers in single-queen colonies lived longer with a higher egg-laying potential than in two-queen colonies. Queen number did not directly affect oxidative stress resis..., , , # Worker survival and egg production– but not transcriptional activity– respond to queen number in the highly polygynous, invasive ant *Tapinoma magnum* [https://doi.org/10.5061/dryad.j0zpc86p3](https://doi.org/10.5061/dryad.j0zpc86p3) This repository is divided into four main folders (.zip) and contains R scripts (.Rmd format) and raw data files (.txt, .xlsx and .csv format) to reproduce the results from the 58-day survival experiment, the worker survival in the oxidative stress experiment, the fecundity analyses of workers and queens, the head width measurement as well as the gene expression analysis of the worker and queen dataset. We further provide the scripts for gene ontology enrichment analyses and the Blastx outputs for the different lists of DEGs (workers and queens) together with the corresponding DESesq2 output files. ## Description of the data and file structure All R scripts are in .Rmd format and input raw files in either .txt, .xlsx or .csv format. The folder \"**sur...