GEO DataSets

(Submitter supplied) Human speech is one of the few examples of vocal learning among mammals, yet ~half of avian species exhibit this ability. Its genetic basis is unknown beyond a shared requirement for FoxP2 in both humans and zebra finches. Here we manipulated FoxP2 isoforms in Area X during a critical period for song development, delineating, for the first time, unique contributions of each to vocal learning. We used weighted gene coexpression network analysis of RNA-seq data to construct transcriptional profiles and found gene modules correlated to singing, learning, or vocal variability. more...

Organism:

Taeniopygia guttata

Type:

Expression profiling by high throughput sequencing

Platform:

GPL23198

38 Samples

Download data: TSV

(Submitter supplied) 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. more...

Organism:

Taeniopygia guttata

Type:

Expression profiling by array

Platform:

GPL15081

54 Samples

Download data: TXT

(Submitter supplied) Production of learned vocalizations requires precise selection and accurate sequencing of appropriate vocal-motor actions. The basal ganglia are essential for the selection and sequencing of motor actions, but the cellular specializations and circuit mechanisms governing accurate sequencing of vocalizations are unknown. Here, we use single-nucleus RNA sequencing and genetic manipulations to map basal ganglia cell types and circuits involved in the production of songbird vocal sequences. more...

Organism:

Taeniopygia guttata

Type:

Expression profiling by high throughput sequencing

Platform:

GPL27119

2 Samples

Download data: TXT

(Submitter supplied) 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. more...

Organism:

Taeniopygia guttata

Type:

Genome binding/occupancy profiling by high throughput sequencing

Platform:

GPL19155

8 Samples

Download data: BW, TXT

(Submitter supplied) 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. more...

Organism:

Taeniopygia guttata

Type:

Expression profiling by array

Platform:

GPL9856

170 Samples

Download data: TXT

(Submitter supplied) The evolution of the six-layered neocortex is often credited with an increased capacity for complex behaviors and cognition in humans and other mammals. However, birds, despite lacking a laminated neocortex, display complex and non-instinctual behaviors including vocal learning, tool use, and problem-solving1,2. The evolution of brain circuits and cell-types supporting advanced behavioral repertoires remains poorly understood. more...

Organism:

Taeniopygia guttata

Type:

Expression profiling by high throughput sequencing

Platform:

GPL27119

4 Samples

Download data: TXT

(Submitter supplied) Gene network analysis aims to understand how large groups of genes coordinate their activity to support complex biological functions. Gene coexpression networks are constructed on the basis of coordinated change in expression levels. However, a majority of genes have multiple versions or isoforms, often with distinct functionality. Gene cosplicing networks aim to capture coordinated changes in either isoform levels or relative ratios for different genes, which in principle could happen even with constant overall expression levels. more...

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL13112

60 Samples

Download data: TXT