Publications

Abstract

Theories addressing the biological basis of language must be built on
an appreciation of the ways that molecular and neurobiological substrates
can contribute to aspects of human cognition. Here, we lay out
the principles by which a genome could potentially encode the necessary
information to produce a language-ready brain. We describe
what genes are; how they are regulated; and how they affect the formation,
function, and plasticity of neuronal circuits. At each step,
we give examples of molecules implicated in pathways that are important
for speech and language. Finally, we discuss technological advances
in genomics that are revealing considerable genotypic variation in
the human population, from rare mutations to common polymorphisms,
with the potential to relate this variation to natural variability
in speech and language skills. Moving forward, an interdisciplinary
approach to the language sciences, integrating genetics, neurobiology,
psychology, and linguistics, will be essential for a complete understanding
of our unique human capacities.

Abstract

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.

Abstract

The genetic basis of complex neurological disorders involving language are poorly understood, partly due to the multiple additive genetic risk factors that are thought to be responsible. Furthermore, these conditions are often syndromic in that they have a range of endophenotypes that may be associated with the disorder and that may be present in different combinations in patients. However, the emergence of individual genes implicated across multiple disorders has suggested that they might share similar underlying genetic mechanisms. The CNTNAP2 gene is an excellent example of this, as it has recently been implicated in a broad range of phenotypes including autism spectrum disorder (ASD), schizophrenia, intellectual disability, dyslexia and language impairment. This review considers the evidence implicating CNTNAP2 in these conditions, the genetic risk factors and mutations that have been identified in patient and population studies and how these relate to patient phenotypes. The role of CNTNAP2 is examined in the context of larger neurogenetic networks during development and disorder, given what is known regarding the regulation and function of this gene. Understanding the role of CNTNAP2 in diverse neurological disorders will further our understanding of how combinations of individual genetic risk factors can contribute to complex conditions