Gene networks are fundamental to animal development, and though the complexity of these networks has been mapped in model organisms, the critical connection between network evolution and organismal diversity remains unclear. This project provides a unique perspective to these complex biological networks by investigating how new fruit fly pigmentation patterns were achieved through the modification of connections between pivotal members of a pigmentation gene network. Using candidate gene and genome-scale approaches it will be determined how a key regulatory protein is connected to and thereby controls the utilization of a battery of target genes necessary to make a pigmentation pattern. Furthermore, comparing network connections within and between related species that exhibit different pigmentation patterns will reveal how these connections evolved and how network interactions affect natural variation in the production of this key regulatory protein.
An enhanced understanding of this model gene network will aid both the evolutionary and developmental biology communities in the construction and testing of hypotheses as to how other gene networks operate and have changed to control diverse traits in diverse lineages. Moreover, these outcomes bear upon the human condition as genetic differences in the DNA sequences connecting regulatory proteins to their target genes is a major yet poorly understood cause of variation between individuals. This project will achieve numerous broader impacts, including: training opportunities for undergraduate and graduate students, the development of both lab exercises for high school biology curricula and research experiences for high school students, and interactions at University symposia and on visitations to area High Schools with non-scientific students and teachers to communicate the contributions of evolutionary developmental biology to modern scientific thought and the value of scientific research to society.
Intellectual Merit: A molecular understanding of evolutionary differences in morphology remains one of the major challenges in our grasp of evolutionary change. Drosophila "fruitflies" have historically been an excellent model for understanding the basis of genetic inheritance, developmental signaling, and evolution, as many of the mechanisms discovered in this system pertain quite broadly to other biological systems. The extensive diversity of body pigmentation phenotypes among fruitflies represents an experimentally accessible system in which to identify networks, genes, and individual mutations that have been altered during trait evolution. During the course of the project, we identified mutations in several genes that contribute to relevant differences in pigmentation phenotypes. These included novel classes of mutations that alter "transcriptional silencer elements", fragments of DNA that inactivate gene expression. We elucidated how several genes are connected together into regulatory networks by which the product of one gene activates or represses the expression of downstream genes. This work identified dozens of new genes within the network controlling pigmentation. Moreover, we investigated how such networks evolve to generate cohesive changes within multiple genes to generate a concerted phenotype. Overall, this work has provided a much clearer picture detailing how individual mutations operate within the context of such networks to generate phenotypic outcomes. Broader Impacts: During the course of the project, we promoted student training, broadened the participation of underrepresented minorities in science, and developed tools for the scientific community. We trained graduate students (3), technicians (2), and undergraduates (14) in scientific research. We provided extended laboratory research experiences for four high school students in School2Careers, a Pittsburgh area program that provides on-the-job training and academic tutoring to at-risk urban high school students. The PI developed resources for the GenePalette software program, a tool used by many researchers to access and analyze genomic sequences.
