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Convergent transcriptional specializations in the brains of humans and song-learning birds.
Abstract
Song-learning birds and humans share independently evolved similarities in brain pathways
for vocal learning that are essential for song and speech and are not found in most
other species. Comparisons of brain transcriptomes of song-learning birds and humans
relative to vocal nonlearners identified convergent gene expression specializations
in specific song and speech brain regions of avian vocal learners and humans. The
strongest shared profiles relate bird motor and striatal song-learning nuclei, respectively,
with human laryngeal motor cortex and parts of the striatum that control speech production
and learning. Most of the associated genes function in motor control and brain connectivity.
Thus, convergent behavior and neural connectivity for a complex trait are associated
with convergent specialized expression of multiple genes.
Type
Journal articleSubject
AdultAnimals
Birds
Brain
Brain Mapping
Corpus Striatum
Evolution, Molecular
Finches
Gene Expression Regulation
Humans
Learning
Male
Motor Cortex
Neural Pathways
Species Specificity
Speech
Transcription, Genetic
Transcriptome
Vocalization, Animal
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https://hdl.handle.net/10161/11149Published Version (Please cite this version)
10.1126/science.1256846Publication Info
Pfenning, Andreas R; Hara, Erina; Whitney, Osceola; Rivas, Miriam V; Wang, Rui; Roulhac,
Petra L; ... Jarvis, Erich D (2014). Convergent transcriptional specializations in the brains of humans and song-learning
birds. Science, 346(6215). pp. 1256846. 10.1126/science.1256846. Retrieved from https://hdl.handle.net/10161/11149.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
Martin Arthur Moseley III
Adjunct Professor in the Department of Cell Biology
Erik James Soderblom
Associate Research Professor of Cell Biology
Director, Proteomics and Metabolomics Core Facility
J. Will Thompson
Adjunct Assistant Professor in the Department of Pharmacology & Cancer Biology
Dr. Thompson's research focuses on the development and deployment of proteomics and
metabolomics mass spectrometry techniques for the analysis of biological systems.
He served as the Assistant Director of the Proteomics and Metabolomics Shared Resource
in the Duke School of Medicine from 2007-2021. He currently maintains collaborations
in metabolomics and proteomics research at Duke, and develops new tools for chemical
analysis as a Princi
Alphabetical list of authors with Scholars@Duke profiles.

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