4.8 Article

Behavior-specific changes in transcriptional modules lead to distinct and predictable neurogenomic states

Publisher

NATL ACAD SCIENCES
DOI: 10.1073/pnas.1114093108

Keywords

Apis mellifera; gene regulation; social behavior; systems biology

Funding

  1. National Science Foundation [EF25852]
  2. National Institutes of Health [1DP1OD006416]
  3. National Cancer Institute Howard Temin Pathway
  4. Department of Defense [W81XWH-08-1-0420]
  5. Grand Duchy of Luxembourg
  6. Roy J. Carver Charitable Trust

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Using brain transcriptomic profiles from 853 individual honey bees exhibiting 48 distinct behavioral phenotypes in naturalistic contexts, we report that behavior-specific neurogenomic states can be inferred from the coordinated action of transcription factors (TFs) and their predicted target genes. Unsupervised hierarchical clustering of these transcriptomic profiles showed three clusters that correspond to three ecologically important behavioral categories: aggression, maturation, and foraging. To explore the genetic influences potentially regulating these behavior-specific neurogenomic states, we reconstructed a brain transcriptional regulatory network (TRN) model. This brain TRN quantitatively predicts with high accuracy gene expression changes of more than 2,000 genes involved in behavior, even for behavioral phenotypes on which it was not trained, suggesting that there is a core set of TFs that regulates behavior-specific gene expression in the bee brain, and other TFs more specific to particular categories. TFs playing key roles in the TRN include well-known regulators of neural and behavioral plasticity, e.g., Creb, as well as TFs better known in other biological contexts, e.g ., NF-kappa B (immunity). Our results reveal three insights concerning the relationship between genes and behavior. First, distinct behaviors are subserved by distinct neurogenomic states in the brain. Second, the neurogenomic states underlying different behaviors rely upon both shared and distinct transcriptional modules. Third, despite the complexity of the brain, simple linear relationships between TFs and their putative target genes are a surprisingly prominent feature of the networks underlying behavior.

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