Encoding Knowledge in the Genome

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Infants are innately attracted to face-like objects, suggesting that they ‘know’ what a face looks like without ever having seen one. How does the genome encode instructions for assembling neural circuits that innately recognize specific complex patterns, such as a face? Pattern recognition is critical for much of human behavior and deficits in recognition abilities are associated with numerous disorders (e.g. prosopagnosia, autism spectrum disorder, different neurodegenerative diseases, recent stroke). Understanding the genetic features that specify the development of innate recognition circuits will provide new avenues for treatments of pattern recognition disorders. Presently, such a detailed link between the genome and neural circuit specification remains a fundamental mystery at the intersection of genomics, neuroscience and behavior. To shed light on the problem we need to identify how a genome that encodes neural circuits, which innately recognizing a specific complex pattern, differs from an ancestor that lacked the same recognition abilities. This presents a major hurdle as most examples of innate pattern recognition abilities, such as face recognition in primates, tend to be evolutionarily ancient and as a result very difficult to genetically dissect. The present work proposes to study the genetic changes that have given rise to novel facial recognition abilities in a unique species of paper wasp. The paper wasp, Polistes fuscatus, has highly variable facial patterns that they use to recognize individual nestmates within their small societies. Like humans, faces are special stimuli for these wasps, but their closely related sister species lack specialized facial processing. Dissecting the genetic basis of the recent evolution of innate recognition of faces in P. fuscatus is possible because of its remarkably low genetic divergence with relatives, high recombination rates and small genome size which all facilitate identification of specific genetic changes that encode circuit specificity. The relatively simple brains of wasps further aid the task. The studies will use a combination of imaging of face-selective neurons, comparative developmental transcriptomics within and between species and comparative genomics to decipher the genetic elements involved in assembling circuits that recognize a specific complex pattern. This genome-wide approach will provide an unbiased view of the of loci involved in specifying circuit development and the genomic features encoding information in circuits. Additionally, the proposed work will develop this unique species of wasp as a powerful invertebrate model for the genomics and neurobiology of complex, individually-differentiated social behaviors that are rare among insects but are the cornerstone of vertebrate and human societies. Most importantly, however, this research will contribute to a deeper and richer understanding of how genomes encode the design of neural circuits for specific recognition tasks.