Laura K. Reed - US grants

DESCRIPTION (provided by applicant): This study is directly relevant to the National Institute of General Medical Sciences Division of Genetics and Developmental Biology's goal to support basic research in to the genetics of complex traits. One of the next great hurdles in the quest to improve human health is to understand complex disease traits that involve both genetic predisposition and environmental factors. In this study, I will develop Drosophila as a model system for the high throughput study of complex metabolic disease resulting from interactions between genotype and environment. Metabolic Syndrome, a constellation of energy metabolism-linked symptoms in humans, which has a prevalence of as much as 34% in developed countries, correlates with a dramatic increase in the risk of cardiovascular disease and type 2 diabetes. Metabolic Syndrome is a result of the environment (diet and activity levels) interacting with genotype. The immediate goals of this project are to test for the relative contributions of the "common disease-common variant" (CD-CV) and "rare allele of major effect" (RAME) hypotheses as the underlying genetic models and to parse the roles of different dietary components in the manifestation of Metabolic Syndrome-like symptoms in Drosophila. The specific aims are to 1: Screen for natural variation in phenotypic response to dietary manipulation (control, high sugar, high fat) and identify lines with aberrant metabolic responses to diet (e.g. excessive weight gain). 2: Identify genetic lines bearing major effect alleles for aberrant dietary response by testing for Mendelian inheritance;the frequency of major effect loci will elucidate whether the metabolic disorders are due to RAME or CD-CV. 3: Perform metabolomic profiles of over 200 metabolites and energy storage molecules in natural isolates showing varied response to diet to identify the metabolic pathways that may be responsible for the variations in response to diet. 4: Perform gene expression profiling to test for the correlation between enzyme expression and metabolite abundance in extreme dietary response phenotypes. Understanding the mechanisms underlying complex genetic disease requires manipulative experimentation, but humans are not good subjects for such experimentation. Model organisms such as Drosophila can be surveyed for natural genetic variation and then be subject to subsequent experimentation to identify the mechanisms of the complex genetic disease. Understanding the role of diet in exposing genetically based metabolic disorders hidden in a population (such as Metabolic Syndrome) is critical to learning how to treat and prevent metabolic disease in humans;Drosophila provides an ideal system to conduct these initial studies, necessary to develop testable hypotheses about the causes of the analogous human disease.

DESCRIPTION (provided by applicant): Diseases linked to Metabolic Syndrome (MetS) such at type-2 diabetes and cardiovascular disease are rapidly increasing due to the influences of a modern Westernized-life style, but the genetic, environmental, and physiological mechanisms linking the symptoms of Metabolic-syndrome remain to be elucidated. Large scale studies to systematically assess how genotype interacts with the environment to cause complex disease are very difficult in humans, but such studies are relatively tractable in genetic models systems such as Drosophila melanogaster. We have shown previously that that there is a very substantial contribution of genotype-by-environment interactions to the phenotypic variation observed for MetS-like symptoms in a naturally genetically variable population of D. melanogaster. We have also been able to demonstrate clear correlations between metabolomic and gene expression profiles and these symptoms as they vary across diet. Finally, we have shown that genetic variance in some of these traits increase with a perturbing high fat diet, indicating the exposure of cryptic genetic variation for these symptoms could contribute to increases in disease. In this study we will build off the community resources for complex genetic trait analysis of the Macdonald-Long synthetic recombinant inbred line (RIL) population and the Drosophila Genomic Reference Panel (DGRP) to map the genetic basis of genotype-by-diet interactions. First, using the 1700 Macdonald-Long Advanced Intercross synthetic RILs, we will map the genetic basis of MetS-like symptoms and the regions controlling genotype-by- environment interactions contributing to these symptoms to within 1 cM of the causal locus when the flies are raised on a normal verses high fat diet. We should be able to estimate both the effect size and population frequency of causative alleles. Second, based of the phenotypes measured in the F1 RIL population, 200 lines demonstrating the largest genotype-by-diet interaction effects will be selected for metabolomic and expression profiling. Metabolomic profiling will identify several hundred primary metabolite and whole genome expression profiles will be generated by microarray analysis. We will characterize the metabolomic and expression module structure that drives the genotype-by-environment interactions and link those pathways back to specific genetic variants. Finally, we will attempt to replicate the findings from the synthetic RIL population through association mapping in the natural variants represented in the 192 lines of the DGRP. The ultimate goal of this work is to identify genomic regions, metabolic pathways, physiological mechanisms, and dietary influences likely to be of importance to Metabolic Syndrome in humans.

Unusual adaptations to the environment have long fascinated scientists and the public. There has been much research to understand the evolution of morphological structures (e.g., shape, color, size). However, far less is known about the evolution of novel biochemical adaptations and the impact of these adaptations on the biodiversity of the organisms in which they appear. Of particular interest is how these traits arise if they are costly to the individuals who harbor them. This research investigates the evolution of biochemical adaptations and the genetic and ecological mechanisms that shape them. The research explores the tolerance of insects (fruit flies) to potent toxins in mushrooms that they consume. By investigating the mechanism of toxin tolerance and how this unique adaptation is maintained in this model system, the research will enhance the general understanding of how novel traits emerge and shape biodiversity. This project also includes activities designed to increase public scientific literacy and familiarity with biodiversity by training teachers and students, from middle school to the undergraduate level (particularly from underrepresented minorities), and generating photographic identification guides for insect species associated with mushrooms.

Flies from some groups of Drosophila feed on both toxic and non-toxic mushrooms, and can tolerate high doses of potent cyclopeptide mushroom toxins that are deadly to most other multi-cellular organisms. This research tests hypotheses that predict that: 1) tolerance to these toxic cyclopeptides evolved multiple times; 2) the genetic mechanism of tolerance is not the same in all species; and 3) trade-offs between the physiological costs of tolerance and the benefits of access to a low-competition resource maintain tolerance. The mechanisms of tolerance and their evolution within different fly species are being characterized using metabolomic and transcriptomic analyses that are analyzed in a phylogenetic framework. To assess the genetic basis of variation in toxin tolerance, the researchers are performing artificial selection experiments and genome sequencing. Finally, observational and competition experiments are being used to identify how selective pressures maintain toxin tolerance in natural populations. In sum, this research will provide an in-depth evolutionary, ecological, and physiological assessment of a costly and novel biochemical adaptation, and its impact on biodiversity.

Project Summary The Genomics Education Partnership (GEP) is a nationwide faculty-driven collaboration that, through training, mentorship, and outreach enables a broad range of institutions to introduce bioinformatics into the undergraduate curriculum. Bioinformatics training extends the teaching of molecular biology, strengthens students' computer science and math skills, and emphasizes the power of computational approaches to explore biological systems. Inquiry-driven genomics research engages students in scientific discovery while maintaining a widely distributed network of teacher-scientists proficient in cutting edge experimental techniques. To date the GEP has trained hundreds of faculty and impacted thousands of undergraduates. A majority of participating faculty and students are women, and a third of GEP participant institutions are minority-serving. From the start, the GEP has sought to: 1. Introduce bioinformatics into the undergraduate curriculum through research 2. Create a scalable system to tackle big projects with many students working in parallel 3. Model ?team science? through collaboration of a widely dispersed team 4. Publish results in the scientific literature with faculty and student authors co-authors 5. Publish assessment results to contribute to the scholarship of teaching and learning. The GEP engages undergraduates in meaningful genomics research regardless of the selectivity, location, or research focus of their institution, as supported by our published assessments of education outcomes. This IPERT proposal will further enhance the GEP's commitment to inclusive training of the scientific workforce. Specific Aim 1 will develop regional nodes to recruit, train, and mentor inclusive local communities of faculty and students engaged in genomics teaching and research. New faculty recruitment locally and at equity-promoting national STEM conferences will focus on institutions that serve students from underrepresented groups. Regional symposia will enable undergraduate students' direct dissemination of their research and participation in the scientific community. Specific Aim 2 will broaden the GEP's scientific scope, capacity, and dissemination by creating a new investigator-initiated, undergraduate-powered gene annotation workflow, with an associated genomics curriculum, that will enable community annotation projects for any eukaryotic genome, driving scalable team science approaches to novel and emerging genomics questions. This new platform incorporates rapid open-access micropublication of gene reports by undergraduate authors, further engaging students in their science.

With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR), this project aims to serve the national interest by improving undergraduate education in genomics. As the economy becomes more dependent on science and technology, the need for highly capable STEM workers is increasingly important. As a result, high-quality STEM education is critical for the U.S. economy, particularly STEM education that includes training in data science. It is also important to identify successful strategies to retain and inspire undergraduate STEM students, especially those from underrepresented groups, so that they may thrive in STEM careers. To help address STEM education needs, the Genomics Education Partnership seeks to integrate active learning into the undergraduate curriculum through Course-based Undergraduate Research Experiences (CUREs) centered in genomics. In these CUREs, students engage in authentic scientific research and develop valuable skills in data science while also practicing problem solving and perseverance to produce a scientific publication. The only tool required for a student to carry out the research is access to the internet, making the program financially accessible to all institutions, including ones that are under-resourced. This project has four objectives: 1) to restructure the Genomics Education Partnership to more widely distribute management and oversight responsibilities throughout the Genomics Education Partnership; 2) to identify effective strategies for recruiting and retaining faculty from community colleges as Genomics Education Partnership members; 3) to develop and optimize a system of online training for new faculty members in the Genomics Education Partnership; and 4) to diversify the scientific projects included in the CUREs. Achieving these objectives will contribute to a cost-effective program that provides high-quality CUREs to a greater diversity of undergraduate students.

The Genomics Education Partnership is a dispersed Community of Practice founded in 2005 that integrates active learning into the curriculum through genomics-centered CUREs. Its research projects investigate the evolution of genes and genomes, as well as CURE effectiveness. Since its inception, the Genomics Education Partnership has used a centralized leadership structure to create a nationwide research and teaching consortium. To meet challenges associated with growth and diversifying its scientific and pedagogical impact, while maintaining its core mission and achieve sustainability, the Genomics Education Partnership is transitioning to a distributed leadership structure and broadening the scope of Genomics Education Partnership's scientific research projects. The Genomics Education Partnership will optimize a suite of virtual tools to facilitate collaboration and build community across its geographically dispersed members and trainees. Further, it will provide mentorship and teaching assistant support for faculty implementing the curriculum in under-resourced institutional environments. CUREs have been demonstrated to have substantial benefits for minority and disadvantaged students in STEM. The Genomics Education Partnership CURE is an extremely low-cost research opportunity for students, making it financially accessible to a broad range of institutional types. This project will increase the diversity of engaged faculty, students, and institutions. Further, this transition in the Genomics Education Partnership provides the opportunity to identify factors that improve the organization's resilience and scalability providing a model for sustaining and expanding a STEM Community of Practice. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.

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.