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  A novel approach identifies the first transcriptome networks in bats: A new genetic model for vocal communication

Rodenas-Cuadrado, P., Chen, X. S., Wiegrebe, L., Firzlaff, U., & Vernes, S. C. (2015). A novel approach identifies the first transcriptome networks in bats: A new genetic model for vocal communication. BMC Genomics, 16: 836. doi:10.1186/s12864-015-2068-1.

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Raw reads from the RNA sequencing in NCBI bioproject repository (Ergänzendes Material)
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Rodenas-Cuadrado, Pedro1, Autor           
Chen, Xiaowei Sylvia1, Autor           
Wiegrebe, L.2, Autor
Firzlaff, U.3, Autor
Vernes, Sonja C.1, 4, 5, Autor           
Affiliations:
1Language and Genetics Department, MPI for Psycholinguistics, Max Planck Society, ou_792549              
2Ludwig-Maximilians-Universität, Division of Neurobiology, Department Biology II, Großhaderner Straße 2, Munich D-82152, Planegg-Martinsried, Germany , ou_persistent22              
3Lehrstuhl für Zoologie, TU München, Liesel-Beckmann-Str. 4, Munich 85350, Freising-Weihenstephan, Germany , ou_persistent22              
4Donders Institute for Brain, Cognition and Behaviour, External Organizations, ou_55236              
5Neurogenetics of Vocal Communication Group, MPI for Psycholinguistics, Max Planck Society, Wundtlaan 1, 6525 XD Nijmegen, NL, ou_2231636              

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 Zusammenfassung: Background Bats are able to employ an astonishingly complex vocal repertoire for navigating their environment and conveying social information. A handful of species also show evidence for vocal learning, an extremely rare ability shared only with humans and few other animals. However, despite their potential for the study of vocal communication, bats remain severely understudied at a molecular level. To address this fundamental gap we performed the first transcriptome profiling and genetic interrogation of molecular networks in the brain of a highly vocal bat species, Phyllostomus discolor. Results Gene network analysis typically needs large sample sizes for correct clustering, this can be prohibitive where samples are limited, such as in this study. To overcome this, we developed a novel bioinformatics methodology for identifying robust co-expression gene networks using few samples (N=6). Using this approach, we identified tissue-specific functional gene networks from the bat PAG, a brain region fundamental for mammalian vocalisation. The most highly connected network identified represented a cluster of genes involved in glutamatergic synaptic transmission. Glutamatergic receptors play a significant role in vocalisation from the PAG, suggesting that this gene network may be mechanistically important for vocal-motor control in mammals. Conclusion We have developed an innovative approach to cluster co-expressing gene networks and show that it is highly effective in detecting robust functional gene networks with limited sample sizes. Moreover, this work represents the first gene network analysis performed in a bat brain and establishes bats as a novel, tractable model system for understanding the genetics of vocal mammalian communication.

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Sprache(n): eng - English
 Datum: 20152015-10-22
 Publikationsstatus: Online veröffentlicht
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 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1186/s12864-015-2068-1
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Titel: BMC Genomics
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: BioMed Central
Seiten: - Band / Heft: 16 Artikelnummer: 836 Start- / Endseite: - Identifikator: ISSN: 1471-2164
CoNE: https://pure.mpg.de/cone/journals/resource/111000136905010