Presentations

Abstract

Bats are able to employ an astonishin- gly 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 obvious 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 vo- cal bat species, P. discolor. To identify functional, biologically relevant gene networks, we utilized two contrasting co-expression network analysis methods with distinct underlying algorithms; WGCNA and MCLUST. These methods typically need large sample sizes for correct clustering, which can be prohibitive where samples are limited, such as in this study. To overcome this, we built on the WGCNA and MCLUST methods to develop a novel approach for identifying robust co-expression gene networks using few samples (≤6). Using this approach, we were able to ge- nerate tissue-specific functional gene networks from the bat PAG, a brain region fundamental for mammalian vocalization. The most highly connected of the networks identified in our study represented a cluster of genes involved in glu- tamatergic synaptic transmission. Glutamatergic signaling plays an essential role in vocalizations elicited from the PAG, suggesting that the gene network uncovered here is mechanistically impor - tant for vocal-motor control in mammals. These findings show that our innovative gene clustering approach can reveal robust biologically relevant gene co-expression networks with limited sample sizes. Moreover, this work reports the first gene network analysis performed in a bat brain and establishes P. discolor as a novel, tractable model system for understanding the genetics of vocal communication.

Abstract

The unique capacity for language is a fundamental trait of humankind, and is of intense interest across diverse fields including linguistics, anthropology, cognitive and neuro-science, and molecular and evolutionary biology. Importantly, language is not an abstract entity, but has developed within a biological system with its own capacities and constraints. Thus, understanding the biology of language, including underlying genetic mechanisms, has the potential to inform some of the central questions in the language sciences such as what are the innate components of the human system that allow language acquisition and what are the biological constraints on this system that determine what constitutes a possible language. To date, the genetic underpinnings of language remain poorly understood as, with current techniques, the molecular mechanisms acting during communicative behavior cannot be directly assayed in humans. Non-human animals do not have language, but they do display complex vocal communicative abilities that share aspects of human vocal communication. For example some animals use antiphonal vocalizations in which vocal-motor outputs are adapted in response to conspecific vocalizations. Others display simple syntax in which sound types are combined in a specific order. A handful of animal species are able to perform vocal production learning, the ability to learn and modify vocalizations based on conspecific inputs – an ability essential for the evolution of spoken language. Thus we can use animal models to understand how these abilities are evolutionarily encoded in the brain and gain insights into the origins of spoken language. I will discuss the use of animal models to directly interrogate genetic networks acting in the brain during communicative behavior. I will also show how we can couple these animal models with cell based assays and in vitro molecular techniques to understand the function of these genes at a molecular, cellular and whole brain level. Ultimately we can apply these findings to human populations to determine how genetic variants relate to human speech and language phenotypes.