Project description:Similarities between speech and birdsong make songbirds advantageous for investigating the neurogenetics of learned vocal communication; a complex phenotype likely supported by ensembles of interacting genes in cortico-basal ganglia pathways of both species. To date, only FoxP2 has been identified as critical to both speech and birdsong. We performed weighted gene co-expression network analysis on microarray data from singing zebra finches to discover gene ensembles regulated during vocal behavior. We found ~2,000 singing- regulated genes comprising 3 co-expression groups unique to area X, the basal ganglia subregion dedicated to learned vocal-motor behavior. These contained known targets of human FOXP2 and potential avian targets. We validated novel biological pathways for vocalization. Our findings show that higher-order gene co-expression patterns, rather than expression levels, molecularly distinguish area X from the ventral striato-pallidum during singing. The previously unknown structure of singing-driven networks enables prioritization of molecular interactors that likely bear on human motor disorders, especially those affecting speech.
Project description:Similarities between speech and birdsong make songbirds advantageous for investigating the neurogenetics of learned vocal communication; a complex phenotype likely supported by ensembles of interacting genes in cortico-basal ganglia pathways of both species. To date, only FoxP2 has been identified as critical to both speech and birdsong. We performed weighted gene co-expression network analysis on microarray data from singing zebra finches to discover gene ensembles regulated during vocal behavior. We found ~2,000 singing- regulated genes comprising 3 co-expression groups unique to area X, the basal ganglia subregion dedicated to learned vocal-motor behavior. These contained known targets of human FOXP2 and potential avian targets. We validated novel biological pathways for vocalization. Our findings show that higher-order gene co-expression patterns, rather than expression levels, molecularly distinguish area X from the ventral striato-pallidum during singing. The previously unknown structure of singing-driven networks enables prioritization of molecular interactors that likely bear on human motor disorders, especially those affecting speech. Gene expression was measured in 2 basal ganglia sub-regions (area X & ventral striato-pallidum (VSP)) of 27 adult male zebra finches that sang different amounts of song over a 2hr period in the morning. 18 birds were allowed to sing freely, 9 birds were discouraged from singing by the presence of an investigator and those that sang fewer than 10 song motifs were considered “non-singers”.
Project description:We queried a songbird brain to discover behaviorally regulated transcriptional mechanisms relevant for speech behavior. About 10% of zebra finch genes showed regulation during singing, and most were brain-region specific. We propose that the brain-regional diversity of the singing-regulated gene networks is derived both from differential combinatorial binding of transcription factors and the epigenetic state of these genes before singing begins. To test this hypothesis, we measured H3K27ac two brain regions that participate in song production. The examination of H3K27ac in two brain regions of zebra finch in singing and silent conditions
Project description:We queried a songbird brain to discover behaviorally regulated transcriptional mechanisms relevant for speech behavior. About 10% of zebra finch genes showed regulation during singing, and most were brain-region specific. We propose that the brain-regional diversity of the singing-regulated gene networks is derived both from differential combinatorial binding of transcription factors and the epigenetic state of these genes before singing begins. To test this hypothesis, we measured H3K27ac two brain regions that participate in song production.
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.