Publications

Abstract

Zoonoses are infectious diseases transmitted from animals to humans. Bats have been suggested to harbour more zoonotic viruses than any other mammalian order1. Infections in bats are largely asymptomatic2,3, indicating limited tissue-damaging inflammation and immunopathology. To investigate the genomic basis of disease resistance, the Bat1K project generated reference-quality genomes of ten bat species, including potential viral reservoirs. Here we describe a systematic analysis covering 115 mammalian genomes that revealed that signatures of selection in immune genes are more prevalent in bats than in other mammalian orders. We found an excess of immune gene adaptations in the ancestral chiropteran branch and in many descending bat lineages, highlighting viral entry and detection factors, and regulators of antiviral and inflammatory responses. ISG15, which is an antiviral gene contributing to hyperinflammation during COVID-19 (refs. 4,5), exhibits key residue changes in rhinolophid and hipposiderid bats. Cellular infection experiments show species-specific antiviral differences and an essential role of protein conjugation in antiviral function of bat ISG15, separate from its role in secretion and inflammation in humans. Furthermore, in contrast to humans, ISG15 in most rhinolophid and hipposiderid bats has strong anti-SARS-CoV-2 activity. Our work reveals molecular mechanisms that contribute to viral tolerance and disease resistance in bats.

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.