The University of Chicago Research Funding

• Principal Investigator: Justin Borevitz, PhD, Assistant Professor, Department of Ecology & Evolution, Committee on Evolutionary Biology
• Start Date: September 18, 2009
• Total Award Amount: $332,366

Public Health Relevance:

The development of fine scale linkage disequilibrium mapping methods will be broadly applicable. There is a tremendous interest in complex disease association mapping, but much debate over different approaches and little success to date. The studies proposed here in Arabidopsis will suggest successful paths for this daunting undertaking, as associations can be quickly confirmed to identify novel QTL.

Project Description

Our proposal will investigate the genetic and molecular basis of complex traits and their interactions with the environment using the model plant Arabidopsis thaliana. We will implement a multi use, high density oligo- nucleotide tiling array for whole genome resequencing. The sample will include a largely unstructured core set of 384 wild A. thaliana genomes. This will be usedto develop a very high resolution haplotype map, reveal genome wide patterns of variation, and suggest sites under natural selection. The ecologically relevant quantitative traits of flowering time and seedling elongation light response will be measured across two seasonal and two geographic environments which span the native range of A. thaliana.

This and future community phenotypic data will be used to develop and test methods for fine scale quantitative trait locus (QTL) association scanning capitalizing on the high density haplotype map. Whole genomeassociation mapping will be developed using coalescent models for detection and fine mapping. We will determine the functional molecular changes underlying two novel QTL utilizing the full powerof Arabidopsis genetics. Importantly this proposal will develop newtechnological inroads for using tiling arrays to generate high density haplotype maps as the foundation for whole genome association studies. These methods, once established, can then be extended to other model systems.

This award is funded under the American Recovery and Reinvestment Act of 2009, NIH Award number: 3R01GM073822-04S1