Molecular breeding methods
Improved molecular breeding methods include a method in which an association data set is developed by associating the phenotypes of a broad population of individuals with the individual genotypes. The association data set is used in conjunction with a growth model in order to select breeding pairs likely to generate offspring with one or more desirable traits.
1. A method for selecting individuals in a breeding program, said method comprising:
a. growing a genetically diverse population of training individuals, wherein said training individuals are plants;
b. phenotyping the genetically diverse population of training individuals to generate a phenotype training data set;
c. associating the phenotype training data set with a genotype training data set comprising genetic information across the genome of each training individual, integrating a crop growth model into a rejection sampling algorithm for estimation of genotypic marker effects and linking the estimation of effects of genotypic markers with the crop growth model to generate an association training data set;
d. genotyping a genetically diverse population of breeding individuals, wherein said breeding individuals are plants;
e. selecting breeding pairs from the genetically diverse population of breeding individuals based genotypes using the association training data set and the crop growth model, estimating effects of genotypic markers and linking the estimation of effects of genotypic markers with the crop growth model to select breeding pairs likely to generate offspring with one or more desired traits;
f. crossing the breeding pairs to generate offspring; and
g. growing the offspring with the one or more desired traits.
2. The method of claim 1 , further comprising crossing said selected breeding individuals.
3. The method of claim 1 , wherein said genotypic information for the individual is obtained via genotyping using SNP markers.
4. The method of claim 1 , wherein said breeding individuals are homozygous.
5. The method of claim 1 , wherein said breeding individuals are plants.
6. The method of claim 5 , wherein said plant is selected from the group consisting of: maize, soybean, sunflower, sorghum, canola, wheat, alfalfa, cotton, rice, barley, millet, sugar cane and switchgrass.
7. The method of claim 1 , wherein said breeding individuals are animals.
8. The method of claim 1 , wherein the method is applied to plant breeding.
9. The method of claim 1 , wherein the method is applied to animal breeding.
10. The method of claim 5 , further comprising a genetically diverse population that includes individuals carrying one or more transgenes.
11. The method of claim 5 , further comprising a genetically diverse population that includes individuals with DNA edited with Cas9.
12. The method of claim 1 , wherein said genotypic information for the individual is obtained by analyses of gene expression, metabolite concentration, or protein concentration.
13. The method of claim 1 , wherein the rejection sampling algorithm is an approximate Bayesian computation algorithm.
14. The method of claim 1 , wherein the crop growth model incorporates environmental and/or plant management information.
15. The method of claim 1 , wherein the crop growth model incorporates elements that model the dynamics of plant processes.
16. The method of claim 1 , wherein the crop growth model models the functional relationship between a complex trait and underlying component traits.