Genetic Contributions to Individual Differences in Vocal Learning
While our prior work has described general features and mechanisms that characterize song learning, we have noted that there is striking variation across individuals in the quality of learning. Such behavioral differences provide a powerful starting point for investigating why the capacities for learning, and other complex phenotypes, differ across individuals and across the lifespan. This has motivated design of experiments that are intended to address how individual differences arise in the capacity for learning, and in the developmental regulation of learning.
Our approach is to precisely quantify phenotypic differences across individuals in song structure and song learning and to correlate these with underlying genetic differences. To accentuate phenotypic variation, we have generated a hybrid population by cross-breeding distinct species of finches. This population exhibits significant heritable variation in song phenotypes, as well as other complex traits (such as plumage). To understand the underlying basis of this variation we use high-throughput sequencing to generate genetic markers for parental strains to map genetic determinants of different phenotypes. The project will involve quantitative behavioral analysis to characterize differences in quality of song and song learning and other phenotypes across individuals, high throughput sequencing, and computational analysis to determine heritability of traits as well as potential linkage of genetic loci to traits of interest.