1a.Objectives (from AD-416)
The proposed work is a joint effort to develop genomic and bioinformatic approaches to dissect maize, grape and other crops' agronomic traits. The goal is to identify specific genes and alleles that could be used in crop improvement.
1. Develop and molecularly characterize germplasm that capture high levels of genetic diversity.
2. Characterize germplasm for a wide range of agronomic and developmental traits.
3. Develop statistical analysis approaches for relating genotype and phenotype. Deploy these analysis approaches in easy to use software for the entire community.
1b.Approach (from AD-416)
1. Inbred lines and testcross germplasm will be created that will be efficient for trait dissection. The USDA maize and grape germplasm will be genotyped with high throughput next generation sequencing technologies.
2. Germplasm will be evaluated in replicated field trials for agronomic and developmental traits in both temperate and tropical environments.
3. Statistical approaches will be developed to deal with complex haplotypes, rare alleles, quantitative trait model building approaches, and breeding prediction. The software will be deployed in open source statistical scripts and in the TASSEL software package.
In 2010, researchers at Cornell have identified the molecular basis of genes controlling leaf development. Cornell provided bioinformatic support and extensive phenotyping efforts for characterizing 5000 diverse maize lines for multiple traits. A Cornell statistical geneticist has developed a creative and novel approach for accelerating computation of the mixed model by up to 1 million fold, and he also found methods for increasing the statistical power of the approach. This will allow complex traits to be analyzed much more rapidly and whole genomes can be analyzed.
In the grape project, researchers in collaboration with Ware (USDA-ARS) and the curators of the USDA grape collection genotype over 2000 samples were genotyped with 9000 SNPs. They determined relatedness among this set of germplasm, and surprisingly were able to show that nearly every Vitis vinifera (wine and table grapes) variety are related to one another by first degree relationships.
Additionally, they have collaborated extensively in the integration of the advanced statistics into TASSEL. This project is monitored through weekly meetings.