Location: Plant Genetics Research
Project Number: 5070-21000-041-06-R
Project Type: Reimbursable Cooperative Agreement
Start Date: Aug 15, 2016
End Date: Jul 31, 2019
The objective of the project is to characterize the architecture of highland adaptation in maize, which will greatly inform our understanding of the evolutionary history of maize and will generate valuable data for continued crop improvement.
We will be using multiple distinct methodologies. First, we will utilize two mapping populations developed by crossing a highland landrace by a lowland landrace to identify regions of the genome (quantitative trait loci; QTL) that control specific traits thought to underlie highland adaptation (e.g., macrohairs, pigmentation). One population is derived from Mexican landraces (one highland, one lowland); the second population is derived from South American landraces (one high, one low). Second, we will use a teosinte collection across an altitudinal gradient in Mexico to identify candidate genomic regions under selection in the highlands using admixture-mapping methods. This will also lead to an independent set of candidate genes for functional characterization. Once we discover regions of the genome underlying these traits, we will proceed with functional characterization of promising candidate genes. Third, we are developing a series of near isogenic lines (NILs) carrying introgressions from highland landraces into the B73 background for previously identified candidate regions (e.g. a chromosomal inversion on chromosome 4 that is associated with highland adaptation). These NILs will be phenotyped in low-, mid-, and high-altitude sites to determine the phenotypes associated with the candidate genes, and will also be sampled for expression analyses in the next approach. Fourth, we will use an RNA-seq approach to identify genes which are differentially expressed in highland, lowland, and mid-elevation locations in the NILs carrying candidate regions to determine which genes are involved in the adaptation of these genomic regions to the various altitudes. In addition, the RNA seq approach will be used to identify genes from landraces themselves, without bias of a priori candidates.