Project description:Studies of transcriptional networks in multi-cellular organisms usually focus on isolated cells and typically assume that the discovered gene networks represent those present in connected cells within a complex organ like the brain. However, similar cell types connected in diverse anatomical networks could differentially influence transcriptional networks. Here, we used laser capture microdissection, expression arrays, genome mapping, and computational inference to explore behaviorally regulated gene networks in the brains of awake, behaving songbirds producing a skilled motor behavior, singing. We found that at baseline, in the absence of singing, a large proportion of genes (17%, >3000) are differentially expressed in the different brain regions of the neural circuit that controls singing. These genes predominantly code for cell communication and connectivity proteins, and non-coding RNAs. Remarkably, the act of singing was associated with differential regulation of ~10% of the coding and non-coding genome. However, less than 1% of genes were singing-regulated in most brain regions and these were largely immediate early genes (IEGs), which peaked early, including the inducible transcription factors EGR1 and FOS. The remaining vast majority of behaviorally regulated gene expression was specific to one or a subset of brain regions, which peaked later. Promoters of the baseline, common, and diverse singing regulated gene clusters were enriched for different combinations of post-translationally activated transcription factors, like CREB, SRF, MEF2, MZF, and the IEG transcription factors. The results suggest that diverse cell-to-cell interactions and differential combinatorial binding of a small group of transcription factors may influence regional diversity of gene networks in seemingly similar cell types. Thus, in highly integrated neural circuits of intact behaving animals, transcriptional network diversity appears to be the rule, rather than the exception. Gene expression in Area X, HVC, LMAN, and Ra was measured before singing (0) or after singing for 0.5, 1, 2, 3, 4, 5, 6, and 7hours. Four-Six independent experiments were performed at each of the 9 timepoints.

Project description:Studies of transcriptional networks in multi-cellular organisms usually focus on isolated cells and typically assume that the discovered gene networks represent those present in connected cells within a complex organ like the brain. However, similar cell types connected in diverse anatomical networks could differentially influence transcriptional networks. Here, we used laser capture microdissection, expression arrays, genome mapping, and computational inference to explore behaviorally regulated gene networks in the brains of awake, behaving songbirds producing a skilled motor behavior, singing. We found that at baseline, in the absence of singing, a large proportion of genes (17%, >3000) are differentially expressed in the different brain regions of the neural circuit that controls singing. These genes predominantly code for cell communication and connectivity proteins, and non-coding RNAs. Remarkably, the act of singing was associated with differential regulation of ~10% of the coding and non-coding genome. However, less than 1% of genes were singing-regulated in most brain regions and these were largely immediate early genes (IEGs), which peaked early, including the inducible transcription factors EGR1 and FOS. The remaining vast majority of behaviorally regulated gene expression was specific to one or a subset of brain regions, which peaked later. Promoters of the baseline, common, and diverse singing regulated gene clusters were enriched for different combinations of post-translationally activated transcription factors, like CREB, SRF, MEF2, MZF, and the IEG transcription factors. The results suggest that diverse cell-to-cell interactions and differential combinatorial binding of a small group of transcription factors may influence regional diversity of gene networks in seemingly similar cell types. Thus, in highly integrated neural circuits of intact behaving animals, transcriptional network diversity appears to be the rule, rather than the exception.

Project description:Songbirds provide rich natural models for studying the relationships of brain anatomy, behavioral function, environmental signals and gene expression. Under the Songbird Neurogenomics Initiative, investigators from more than a dozen laboratories collected brain samples from six species of songbird under a range of experimental conditions, and 488 of these samples were analyzed systematically for gene expression by microarray. ANOVA was used to test 32 planned contrasts in the data, revealing the relative impact of different factors. The brain region from which tissue was taken had the greatest influence on gene expression profile, affecting the majority of signals measured by the 18,848 non-redundant cDNAs spotted on the microarray. Social and environmental manipulations had highly variable impact, ranging from nil in some cases to robust in others. Several specific genes were identified as points of interest in the evolution of mechanisms by which environmental signals influence behavior. The data were also analyzed using Weighted Gene Co-expression Network Analysis (WGCNA) followed by Gene Ontology (GO) analysis. This revealed modules of co-regulated genes that are also enriched for specific functional annotations such as M-bM-^@M-^\ribosomeM-bM-^@M-^] (expressed more highly in juvenile brain) and M-bM-^@M-^\dopamine metabolic processM-bM-^@M-^] (expressed more highly in striatal song control nucleus Area X). These results underscore the complexity of influences on neural gene expression and provide a resource for studying how these influences are integrated during natural experience. RNA samples were collected from six different songbird species (phylogeny in SI Appendix, Figure S1) and representing 80 different M-bM-^@M-^\treatmentsM-bM-^@M-^], i.e., combinations of species, brain region, sex, age, and behavioral state. The tissue samples were organized around 15 standalone experiments (Table 1 and SI Appendix, Table S1), contributed by investigators in a dozen different laboratories but analyzed under uniform conditions in a single laboratory as originally planned under the Songbird Neurogenomics Initiative. Each sample was hybridized to a zebra finch cDNA array along with a universal reference (a pool of zebra finch telencephalic RNA). e07: HVC of p55 and adult male zebra finches were collected after 20 days of food ad libitum or Timed Access to Food (TAF) to assess singing-driven differences in gene expression.

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Core and region enriched networks of behaviorally regulated genes: the singing epigenome

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