Assembling a model of the hierarchical trait of flight performance in drosophila

Active Project Grant Awarded Last action

Award ID
F32GM167010
Recipient
Awarding agency
Obligated
$78,392

Award facts

Assistance listing
93.859 Biomedical Research and Research Training
Completion date 0% complete
Place of performance
Columbia, MO 65211, USA

Award details come from USAspending.gov.

Description

As the agency reported it.

Abstract
Despite many great strides being made in the realms of human genetics, complex traits, and precision medicine, a GAP persists between the wealth of genetic knowledge science has accumulated and concrete outcomes for patients. There are still challenges with applying the results of genome wide association studies (GWAS) to individuals, resulting in precision medicine frequently falling short of its goals. Model systems represent a more malleable subject with the potential to clear up noise and hone in on a model of trait complexity that can then be applied to humans. Complex traits are hierarchical phenotypes, where many sub- phenotypes combine together to influence a main phenotype. As a result, we need an understanding of how sub-phenotypes combine and influence the main phenotype in order to understand the structure of complex traits in humans and utilize GWAS and precision medicine effectively. Only with this conceptual knowledge will we be able to understand complex traits and their causes. One complex, highly hierarchical trait in drosophila is flight performance. This models a human complex trait in that IT depends on many factors. We hypothesize that selecting drosophila for flight performance while evaluating their sub-phenotypes over time will give insight into how sub-phenotypes combine into a main complex trait. To determine what changes take place as a complex trait is evaluated, flies will be selected for flight performance for 30 generations, pooled genomic sequencing will be performed to track allele frequency changes over time, a suite of sub-phenotypes will be evaluated as the generations progress, gene expression changes will be analyzed, and selected changes will be mapped back to their genetic basis. To then more closely understand the changes in gene regulatory signals, chromatin structure will be profiled to identify changes, CO-accessibility analyses will be used to identify changes in gene regulatory pathways, and a hierarchy of sub-phenotypes will be compiled by comparing the flight performance results to the differential factors previously identified using a multi-variate statistical analysis. Through this training plan, I will learn more complex genetic techniques, acquire training in assessing fly morphology, improve statistical modelling, obtain further training on rigor and reproducibility techniques, and develop the skills necessary to run an independent lab. I additionally will have opportunities to communicate my science through publications and presentations, mentor students, prepare grant applications, and prepare job applications to become a tenure-track research professor. This project will further our understanding of how sub-phenotypes combine together into a complex trait, giving insight into how we can genetically and statistically conceptualize complex traits and GWAS results, leading to precision medicine with more effective outcomes for patients.

Quick answers

Who received award F32GM167010?

F32GM167010 was awarded to University Of Missouri System by National Institute of General Medical Sciences (National Institutes of Health) on February 1, 2027.

How much is award F32GM167010 worth?

$78,392 has been obligated on F32GM167010.

On GovTribe

See this award's full record

  • Every transaction and subaward
  • The recipient's other awards and teaming partners
  • Similar grant awards
  • Ask GovTribe AI about this award
Try for free Login