Core and region-enriched networks of behaviorally regulated genes and the singing genome.
Abstract
Songbirds represent an important model organism for elucidating molecular mechanisms
that link genes with complex behaviors, in part because they have discrete vocal learning
circuits that have parallels with those that mediate human speech. We found that ~10%
of the genes in the avian genome were regulated by singing, and we found a striking
regional diversity of both basal and singing-induced programs in the four key song
nuclei of the zebra finch, a vocal learning songbird. The region-enriched patterns
were a result of distinct combinations of region-enriched transcription factors (TFs),
their binding motifs, and presinging acetylation of histone 3 at lysine 27 (H3K27ac)
enhancer activity in the regulatory regions of the associated genes. RNA interference
manipulations validated the role of the calcium-response transcription factor (CaRF)
in regulating genes preferentially expressed in specific song nuclei in response to
singing. Thus, differential combinatorial binding of a small group of activity-regulated
TFs and predefined epigenetic enhancer activity influences the anatomical diversity
of behaviorally regulated gene networks.
Type
Journal articleSubject
AcetylationAnimals
Avian Proteins
Brain
Enhancer Elements, Genetic
Epigenesis, Genetic
Finches
Gene Expression Regulation
Gene Regulatory Networks
Genome
Histones
Male
Regulatory Sequences, Nucleic Acid
Transcription Factors
Transcriptome
Vocalization, Animal
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https://hdl.handle.net/10161/11150Published Version (Please cite this version)
10.1126/science.1256780Publication Info
Whitney, Osceola; Pfenning, Andreas R; Howard, Jason T; Blatti, Charles A; Liu, Fang;
Ward, James M; ... Jarvis, Erich D (2014). Core and region-enriched networks of behaviorally regulated genes and the singing
genome. Science, 346(6215). pp. 1256780. 10.1126/science.1256780. Retrieved from https://hdl.handle.net/10161/11150.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Alexander J. Hartemink
Professor of Computer Science
Computational biology, machine learning, Bayesian statistics, transcriptional regulation,
genomics and epigenomics, graphical models, Bayesian networks, hidden Markov models, systems
biology, computational neurobiology, classification, feature selection
Erich David Jarvis
Adjunct Professor in the Deptartment of Neurobiology
Dr. Jarvis' laboratory studies the neurobiology of vocal communication. Emphasis is
placed on the molecular pathways involved in the perception and production of learned
vocalizations. They use an integrative approach that combines behavioral, anatomical,
electrophysiological and molecular biological techniques. The main animal model used
is songbirds, one of the few vertebrate groups that evolved the ability to learn vocalizations.
The generality of the discoveries is tested in other vocal lear
Anne Elizabeth West
Professor of Neurobiology
The long term goal of our laboratory is to understand at a cellular/molecular level
how neuronal activity regulates the formation and maturation of synapses during brain
development, and ultimately to use genetic model systems to understand how defects
in this developmental process lead to cognitive dysfunction.
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