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. 2012 Apr 24;109(17):6490-5.
doi: 10.1073/pnas.1202734109. Epub 2012 Apr 9.

Social environment is associated with gene regulatory variation in the rhesus macaque immune system

Jenny Tung  1 , Luis B Barreiro, Zachary P Johnson, Kasper D Hansen, Vasiliki Michopoulos, Donna Toufexis, Katelyn Michelini, Mark E Wilson, Yoav Gilad
Affiliations

Social environment is associated with gene regulatory variation in the rhesus macaque immune system

Jenny Tung et al. Proc Natl Acad Sci U S A. .

Abstract

Variation in the social environment is a fundamental component of many vertebrate societies. In humans and other primates, adverse social environments often translate into lasting physiological costs. The biological mechanisms associated with these effects are therefore of great interest, both for understanding the evolutionary impacts of social behavior and in the context of human health. However, large gaps remain in our understanding of the mechanisms that mediate these effects at the molecular level. Here we addressed these questions by leveraging the power of an experimental system that consisted of 10 social groups of female macaques, in which each individual's social status (i.e., dominance rank) could be experimentally controlled. Using this paradigm, we show that dominance rank results in a widespread, yet plastic, imprint on gene regulation, such that peripheral blood mononuclear cell gene expression data alone predict social status with 80% accuracy. We investigated the mechanistic basis of these effects using cell type-specific gene expression profiling and glucocorticoid resistance assays, which together contributed to rank effects on gene expression levels for 694 (70%) of the 987 rank-related genes. We also explored the possible contribution of DNA methylation levels to these effects, and identified global associations between dominance rank and methylation profiles that suggest epigenetic flexibility in response to status-related behavioral cues. Together, these results illuminate the importance of the molecular response to social conditions, particularly in the immune system, and demonstrate a key role for gene regulation in linking the social environment to individual physiology.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Parallel effects of dominance rank on social environment and gene expression levels. (A) Low-ranking individuals experience more aggression from group mates than high-ranking individuals (P < 10−6, R2 = 0.42, n = 49). (B) This social experience is mirrored by gene expression profiles that vary according to rank. Principal component (PC)1 explains 20.2% of overall variance in gene expression and is correlated with rank (P = 0.03, R2 = 0.10, n = 49). (C) Heatmaps of log2-transformed gene expression levels for rank-associated genes. Values are shown after controlling for differences in means among social groups; 0 roughly corresponds to mean expression levels.
Fig. 2.
Fig. 2.
Rank–gene expression associations among inflammation-related immune genes. Low-ranking females tend to overexpress inflammation-related genes: (A) PTGS2 (P = 0.004); (B) IL8RB (P = 0.003); and (C) NFATC1 (P < 10−3).
Fig. 3.
Fig. 3.
Gene expression data are sufficient to predict relative position in the social hierarchy. (A) Boxplot of predictive accuracy for 10 training set individuals, across 1,000 cross-validation iterations (dashed line shows expected accuracy under random prediction), and (B) histogram of the sum of absolute error between predicted rank class and true rank class, under random assignment. Black arrow, median sum of absolute error across the 1,000 true leave-k-out iterations (P = 0.002). (C) Shifts in dominance rank experienced by seven females in the dataset. Solid arrows, cases in which females changed rank classes; dashed arrows, cases in which females changed rank within rank classes; check marks, correct predictions; x, incorrect prediction.
Fig. 4.
Fig. 4.
Effects of tissue composition and glucocorticoid-mediated regulation on rank-associated gene expression levels. (A) Low-ranking individuals exhibit lower proportions of CD8+ T cells in PBMCs (P = 0.047, n = 39; y axis shows the residuals of T-cell proportions after controlling for social group). (Inset) Example data for a rank 1 female and a rank 5 female; x axis shows staining for CD4+ (helper) T cells and y axis shows staining for CD8+ (cytotoxic) T cells. (C) Low-ranking individuals exhibit decreased GC negative feedback (P = 0.005, n = 49). The y axis represents levels of circulating cortisol 17 h post-dexamethasone administration. (B and D) Distribution of rank–gene expression partial correlation coefficients for genes in which we inferred a contribution of tissue composition (B, n = 301 genes) or an effect of GC regulation (D, n = 596 genes). Blue density plots show the distribution of partial correlation coefficients without taking into account tissue composition or GC data; tan density plots show the same distribution after considering these data. The magnitude of the rank–gene expression relationship decreases but remains distinct from the background set of all genes (in gray; n = 6,097 genes).
Fig. 5.
Fig. 5.
DNA methylation levels distinguish high-ranking and low-ranking females. (A) A neighbor-joining tree based on DNA methylation levels within 20 kb around the transcription start sites of rank-associated genes (445,059 CpG sites). (B) A heatmap of the same data reveals positive pairwise correlations between individuals of the same rank but not between individuals of different ranks.
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