This action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2020, Integrative Research Investigating the Rules of Life Governing Interactions Between Genomes, Environment and Phenotypes. The fellowship supports research and training of the Fellow that will contribute to the area of Rules of Life in innovative ways. Social behavior can vary greatly between individuals, with genetic and environmental factors impacting the development of sociability. The Fellow will apply a novel approach in the field of behavioral neuroscience—the examination of many genetically diverse mouse strains from the large Collaborative Cross (CC) mouse genetic reference panel (GRP)—to examine genetic and environmental regulators of social outcomes. This approach is important because basic research into the impact of genes and environment on brain and behavior has historically been conducted in only a very small number of inbred laboratory rodent strains, limiting genetic variation that is essential for understanding how genes impact complex behaviors. Thus, research incorporating increased genetic diversity to investigate genetic and environmental regulators of behavioral outcomes may lead to new discoveries that are more applicable to genetically diverse populations, such as humans. This fellowship will broaden participation in neuroscience by facilitating the intellectual and professional development of underrepresented students recruited from the LA-HIP and USC McNair Scholars Program.
The CC mouse panel was created by a global team of researchers to study the biological regulation of polygenic traits and consists of ~60 strains of highly genetically diverse mice. By examining early social interactions across the CC GRP, the Fellow will identify strains with the lowest and highest mother-pup interactions. Behavioral testing of adult offspring will allow long-term effects of strain genetic background and maternal care to be examined. The relationship between genetic background and actual gene expression patterns in the brain from the most behaviorally extreme strains will be examined to identify underlying mechanisms. Computational modeling will establish gene transcription patterns across neural networks that can be compared between behaviorally extreme strains with different levels of maternal experience to identify mechanisms of social behavioral variation. The Fellow will receive training in the best approaches for integrative analyses of comprehensive datasets across biological levels of analyses to address complex questions across a population. In addition, the Fellow will train in scientific communication and mentorship by presenting to the public at local events and training students from underrepresented groups.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
