DOI: 10.5061/dryad.ht76hdrvn
title: Asymmetrical physiological cost of reproduction shapes caste-specific resource allocation in an ant, <i>Diacamma</i> cf. <i>indicum</i> from Japan

description: In eusocial insects, queens demonstrate high reproductive capacity and
 extended longevity, representing examples of the trade-off in resource
 allocation. Workers perform non-reproductive tasks, such as caring for
 broods and foraging, thus reducing the energetic demands of queens. As
 queens dedicate their lives to reproduction, these reduced energetic
 demands enable them to live longer, laying many eggs. However, the
 physiological specialisation of queens is markedly distinct from that of
 workers. This study examines the trade-off between immunocompetence and
 reproduction among castes in an ant species, Diacamma cf. indicum, from
 Japan, which lacks a morphological queen caste. First, gamergates
 (functional queens) exhibited higher expression of innate immunity genes
 than the workers. Second, to experimentally skew resource allocation
 toward immunocompetence, gamergates and reproductive workers were
 subjected to an immune challenge. As a result, the expression of the
 antimicrobial peptide gene Hymenoptaecin was increased in gamergates
 without compromising reproduction-related genes, such as Vitellogenin. In
 contrast, the expression of genes associated with reproduction was
 decreased in reproductive workers. Moreover, we revealed that gamergates
 possessed a remarkably low fat content, similar to non-reproductive
 foragers. These findings suggest that, while gamergates can overcome the
 trade-off, reproductive workers are constrained by the physiological costs
 of reproduction.
description: # Asymmetrical physiological cost of reproduction shapes caste-specific
 resource allocation in an ant, *Diacamma* cf. *indicum* from Japan Dataset
 DOI: [10.5061/dryad.ht76hdrvn](10.5061/dryad.ht76hdrvn) ## Description of
 the data and file structure This Excel workbook contains all datasets used
 in the analyses for this study. Each analysis is organized into a separate
 worksheet (tab). The name of each tab clearly indicates the corresponding
 analysis in which the dataset was used. Each tab corresponds to a specific
 analysis performed in the study. Tab names match the analysis names as
 referenced in the manuscript (e.g., "Fig.2a_Gene_efficiency").
 Columns within each tab are labeled to describe the variables and
 measurement details. ### Files and variables **Variables** dna: Dilution
 series cq: Ct values gene: gene name **Tab: Fig.2a_Gene_efficiency**
 **Variables** sample: Sample ID Caste: Category of behavioral caste
 Colony: Colony ID Gapdh: Ct value of gapdh  Def: Ct value of Def Hym: Ct
 value of Hym Toll: Ct value of Toll Imd: Ct value of Imd
 **Tab: Fig.2a_Normal_condition_Gene_CT** **Variables** Gene: gene name
 Comaresion: Combinatinon (F: forager; N: nurse; Q: gamergate) P: P value
 **Tab: Fig.2a_Pvalue** **Variables** sample: Sample ID Bacteria:
 Killed-bacteria treatment (1) and control (0) Caste: Category of caste (Q:
 gamergate) Treatment: Category of treatment (CQ: control gamergate; IQ:
 killed-bacteria treatment gamergate) Egg: Total number of eggs produced
 Rank: Category of reproductive individual (queen: gamergate) Gapdh: Ct
 value of gapdh  Def: Ct value of Def Vg: Ct value of Vg Hym: Ct value of
 Hym VgR: Ct value of VgR **Tab: Fig.2b_Immune_challenge_geneCT**
 **Variables** sample: Sample ID Bacteria: Killed-bacteria treatment (1)
 and control (0) Caste: Category of caste (W: worker) Treatment: Category
 of treatment (CW: control worker; IW: killed-bacteria treatment worker)
 Egg: Total number of eggs produced Rank: Category of reproductive
 individual (high: high reproductive worker) Gapdh: Ct value of gapdh  Def:
 Ct value of Def Vg: Ct value of Vg Hym: Ct value of Hym VgR: Ct value of
 VgR **Tab: Fig.2b_Immune_challenge_geneCT** **Variables** dna: Dilution
 series cq: Ct value gene: gene name
 **Tab: Fig.2bc_Immune_challenge_GeneEf** **Variables** Caste: Category of
 reproductive individual (high: high reproductive worker; queen: gamergate)
 Gene: gene name P: P value **Tab: Fig.2bc_Pvalue** **Variables** ID:
 Indiviudal ID Colony: Colony ID Caste: Category of caste (W: worker; Q:
 gamergate) Bacteria: Killed-bacteria treatment (1) and control (0) Total:
 Total number of products Rank: Category of reproductive individual (high:
 high reproductive worker; queen: gamergate) **Fig.S1_Egg number**
 **Valiables** Colony: Colony ID cast- Q- queen; W-worker bacteria- 
 present(1) or absent(0) total: total count rank: Q: used only for queens
 high: workers with unusually high “Total” values; NA: normal / not
 classified as high **Fig3_lipid_content** Colony: Colony ID Task: Category
 of caste (Queen: gamergate; Forager: forager worker; Nurse: nurse worker)
 Relative.quantity: Relative quantity of fat content #### File:
 All_data_revised.xlsx; RSOS_R_script.Rmd These analyses quantify gene
 expression, reproduction, and lipid content across castes and treatments
 using Bayesian qRT-PCR (MCMC.qpcr) and generalized (mixed) models, with
 colony as a random effect and multiple-testing correction (BH) to test
 immune, reproductive, and physiological differences among queens, workers,
 and treatments.