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

Capturing the Effects of Domestication on Vocal Learning Complexity

Domesticated and vocal learning species can serve as informative model organisms for the reduction of reactive aggression and emergence of speech in our lineage. Amidst mounting evidence that domestication modifies vocal repertoires across different species, we focus on the domesticated Bengalese finch, which has a more complex song than the wild-type white-rumped munia. Our explanation for this effect revolves around the glutamate neurotransmitter system. Glutamate signaling (i) is implicated in birdsong learning, (ii) controls dopamine activity in neural circuits crucial for vocal learning, (iii) is disproportionately targeted in the evolution of domesticates, and (iv) regulates stress responses and aggressive behaviors attenuated under domestication. We propose that attenuated excitation of stress-related neural circuits potentiates vocal learning via altered dopaminergic signaling.

Cyto- and myeloarchitectural brain atlas of the pale spear-nosed bat (Phyllostomus discolor) in CT Aided Stereotaxic Coordinates

The pale spear-nosed bat Phyllostomus discolor, a microchiropteran bat, is well established as an animal model for research on the auditory system, echolocation and social communication of species-specific vocalizations. We have created a brain atlas of Phyllostomus discolor that provides high-quality histological material for identification of brain structures in reliable stereotaxic coordinates to strengthen neurobiological studies of this key species. The new atlas combines high-resolution images of frontal sections alternately stained for cell bodies (Nissl) and myelinated fibers (Gallyas) at 49 rostrocaudal levels, at intervals of 350 µm. To facilitate comparisons with other species, brain structures were named according to the widely accepted Paxinos nomenclature and previous neuroanatomical studies of other bat species. Outlines of auditory cortical fields, as defined in earlier studies, were mapped onto atlas sections and onto the brain surface, together with the architectonic subdivisions of the neocortex. X-ray computerized tomography (CT) of the bat's head was used to establish the relationship between coordinates of brain structures and the skull. We used profile lines and the occipital crest as skull landmarks to line up skull and brain in standard atlas coordinates. An easily reproducible protocol allows sectioning of experimental brains in the standard frontal plane of the atlas. An electronic version of the atlas plates and supplementary material is available from https://doi.org/10.12751/g-node.8bbcxy.

Network Medicine in the Age of Biomedical Big Data

Network medicine is an emerging area of research dealing with molecular and genetic interactions, network biomarkers of disease, and therapeutic target discovery. Large-scale biomedical data generation offers a unique opportunity to assess the effect and impact of cellular heterogeneity and environmental perturbations on the observed phenotype. Marrying the two, network medicine with biomedical data provides a framework to build meaningful models and extract impactful results at a network level. In this review, we survey existing network types and biomedical data sources. More importantly, we delve into ways in which the network medicine approach, aided by phenotype-specific biomedical data, can be gainfully applied. We provide three paradigms, mainly dealing with three major biological network archetypes: protein-protein interaction, expression-based, and gene regulatory networks. For each of these paradigms, we discuss a broad overview of philosophies under which various network methods work. We also provide a few examples in each paradigm as a test case of its successful application. Finally, we delineate several opportunities and challenges in the field of network medicine. We hope this review provides a lexicon for researchers from biological sciences and network theory to come on the same page to work on research areas that require interdisciplinary expertise. Taken together, the understanding gained from combining biomedical data with networks can be useful for characterizing disease etiologies and identifying therapeutic targets, which, in turn, will lead to better preventive medicine with translational impact on personalized healthcare.

Time matters! Developmental shift in gene expression between the head and the trunk region of the cichlid fish Astatotilapia burtoni

BACKGROUND

Differential gene expression can be translated into differing phenotypic traits. Especially during embryogenesis, specific gene expression networks regulate the development of different body structures. Cichlid fishes, with their impressive phenotypic diversity and propensity to radiate, are an emerging model system in the genomics era. Here we set out to investigate gene expression throughout development in the well-studied cichlid fish Astatotilapia burtoni, native to Lake Tanganyika and its affluent rivers.

RESULTS

Combining RNA-sequencing from different developmental time points as well as integrating adult gene expression data, we constructed a new genome annotation for A. burtoni comprising 103,253 transcripts (stemming from 52,584 genomic loci) as well as a new reference transcriptome set. We compared our transcriptome to the available reference genome, redefining transcripts and adding new annotations. We show that about half of these transcripts have coding potential. We also characterize transcripts that are not present in the genome assembly. Next, using our newly constructed comprehensive reference transcriptome, we characterized differential gene expression through time and showed that gene expression is shifted between different body parts. We constructed a gene expression network that identified connected genes responsible for particular phenotypes and made use of it to focus on genes under potential positive selection in A. burtoni, which were implicated in fin development and vision.

CONCLUSIONS

We provide new genomic resources for the cichlid fish Astatotilapia burtoni, which will contribute to its further establishment as a model system. Tracing gene expression through time, we identified gene networks underlying particular functions, which will help to understand the genetic basis of phenotypic diversity in cichlids.

What bats have to say about speech and language

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.