Publications

Abstract

Past events like fluctuations in population size and post-glacial colonization processes may influence the relative importance of genetic drift, migration and selection when determining the present day patterns of genetic variation. We disentangle how drift, selection and migration shape neutral and adaptive genetic variation in 12 moor frog populations along a 1700 km latitudinal gradient. We studied genetic differentiation and variation at a MHC exon II locus and a set of 18 microsatellites.
Results

Using outlier analyses, we identified the MHC II exon 2 (corresponding to the β-2 domain) locus and one microsatellite locus (RCO8640) to be subject to diversifying selection, while five microsatellite loci showed signals of stabilizing selection among populations. STRUCTURE and DAPC analyses on the neutral microsatellites assigned populations to a northern and a southern cluster, reflecting two different post-glacial colonization routes found in previous studies. Genetic variation overall was lower in the northern cluster. The signature of selection on MHC exon II was weaker in the northern cluster, possibly as a consequence of smaller and more fragmented populations.
Conclusion

Our results show that historical demographic processes combined with selection and drift have led to a complex pattern of differentiation along the gradient where some loci are more divergent among populations than predicted from drift expectations due to diversifying selection, while other loci are more uniform among populations due to stabilizing selection. Importantly, both overall and MHC genetic variation are lower at northern latitudes. Due to lower evolutionary potential, the low genetic variation in northern populations may increase the risk of extinction when confronted with emerging pathogens and climate change.

Abstract

A commentary on
FOXP2 drives neuronal differentiation by interacting with retinoic acid signaling pathways

by Devanna, P., Middelbeek, J., and Vernes, S. C. (2014). Front. Cell. Neurosci. 8:305. doi: 10.3389/fncel.2014.00305

Abstract

Understanding the biological foundations of language is vital to gaining insight into how the capacity for language may have evolved in humans. Animal models can be exploited to learn about the biological underpinnings of shared human traits, and although no other animals display speech or language, a range of behaviors found throughout the animal kingdom are relevant to speech and spoken language. To date, such investigations have been dominated by studies of our closest primate relatives searching for shared traits, or more distantly related species that are sophisticated vocal communicators, like songbirds. Herein I make the case for turning our attention to the Chiropterans, to shed new light on the biological encoding and evolution of human language-relevant traits. Bats employ complex vocalizations to facilitate navigation as well as social interactions, and are exquisitely tuned to acoustic information. Furthermore, bats display behaviors such as vocal learning and vocal turn-taking that are directly pertinent for human spoken language. Emerging technologies are now allowing the study of bat vocal communication, from the behavioral to the neurobiological and molecular level. Although it is clear that no single animal model can reflect the complexity of human language, by comparing such findings across diverse species we can identify the shared biological mechanisms likely to have influenced the evolution of human language. Keywords

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.