Statistical approach for optimal use of genetic information collected on historical pedigrees

Abstract

This invention provides a novel means of predicting plant phenotypes that incorporates previously unusable dense marker data derived from historical pedigrees. The method operates by collecting information from a population pertaining to one or more loci, which is used to build one or more matrices by calculating, for the alleles present at the measured loci, the probability that the alleles are identical by descent. These matrices are then used to develop a second set of one or more matrices in which each value represents the probability that a certain individual in the population descended from a certain ancestral (founder) genotype. This set of second matrices can then be used as part of a breeding program for selecting and breeding individuals from the population or can be used to better classify the individuals in the population, leading to improved plant phenotypes.

What is claimed is: 
     
         1 . A method for producing a selection matrix useful for selecting from a population a subset of individuals that have an increased probability of producing progeny having one or more phenotypes, the method comprising:
 a. collecting pedigree and genotype information pertaining to one or more loci in one or more individual in a population;   b. building a first matrix by calculating the probability that alleles present at one or more loci in the one or more individuals are identical by descent in the population, based on the pedigree and genotype information; and   c. using the first matrix to calculate a selection matrix that classifies one or more individuals from the population into groups, wherein the selection matrix is calculated by grouping individuals that exceed a threshold on the entries of the first matrix in a manner that enforces transitivity of group membership;   
       wherein at least one step of the method is implemented on a computer. 
     
     
         2 . The method of  claim 1 , wherein the first matrix is calculated using one or more of the group consisting of stochastic algorithms, deterministic algorithms, maximum likelihood algorithms, and descent graph methods. 
     
     
         3 . The method of  claim 1 , wherein the selection matrix is calculated using a latent class model, a non-negative matrix factorization model, or a bilinear model. 
     
     
         4 . The method of  claim 1 , wherein the population comprises members of a plant species. 
     
     
         5 . The method of  claim 4 , wherein the plant species is selected from the group consisting of maize, wheat, rice, millet, barley, sorghum, rye, soybean, alfalfa, oilseed Brassica, cotton, sunflower, potato, and tomato. 
     
     
         6 . The method of  claim 1 , wherein the one or more phenotypes are selected from the group consisting of yield, leaf angle, anthesis-silking interval (ASI), staygreen duration, early growth rate, overall growth rate, growth pattern, maximum biomass, total biomass, nitrogen use efficiency, water use efficiency, tocol content, oleic acid content, phytic acid content, amino acid composition, oil quality or quantity, energy availability, digestibility, fatty acid composition, a pathogen defense mechanism, lysine and sulfur levels, starch synthesis, disease resistance, herbicide resistance, male sterility, plant vigor, nutrient content, hemicellulose content, cellulose production, cold tolerance, salt tolerance, heat tolerance, drought tolerance, grain moisture content, stalk lodging, root lodging, root pulling resistance, stand establishment, emergence, midsilk, test weight, protein content, starch percentage, relative maturity, plant height, seed size, disease resistance genes, heading date, resistance to insects, brittle snap, stalk breakage, resistance to fungus, seed moisture, head shape, hullability, seedling vigor, beginning bloom date, maturity date, seed shatter, winter survival, fiber strength, ear height, plant barrenness, seed number, seed weight, and color grade. 
     
     
         7 . The method of  claim 6 , wherein the one or more phenotypes include drought tolerance. 
     
     
         8 . The method of  claim 1 , wherein the population is a doubled haploid population. 
     
     
         9 . The method of  claim 1 , wherein the population is from a biparental cross. 
     
     
         10 . The method of  claim 1 , wherein the population is a backcross population. 
     
     
         11 . The method of  claim 8 , wherein the one or more traits comprise an improvement in one or more phenotypes selected from the group consisting of yield, leaf angle, anthesis-silking interval (ASI), staygreen duration, early growth rate, overall growth rate, growth pattern, maximum biomass, total biomass, nitrogen use efficiency, water use efficiency, tocol content, oleic acid content, phytic acid content, amino acid composition, oil quality or quantity, energy availability, digestibility, fatty acid composition, a pathogen defense mechanism, lysine and sulfur levels, starch synthesis, disease resistance, herbicide resistance, male sterility, plant vigor, nutrient content, hemicellulose content, cellulose production, cold tolerance, salt tolerance, heat tolerance, drought tolerance, grain moisture content, stalk lodging, root lodging, root pulling resistance, stand establishment, emergence, midsilk, test weight, protein content, starch percentage, relative maturity, plant height, seed size, disease resistance genes, heading date, resistance to insects, brittle snap, stalk breakage, resistance to fungus, seed moisture, head shape, hullability, seedling vigor, beginning bloom date, maturity date, seed shatter, winter survival, fiber strength, ear height, plant barrenness, seed number, seed weight, and color grade. 
     
     
         12 . The method of  claim 11 , wherein the one or more phenotypes include drought tolerance. 
     
     
         13 . A method of predicting a polymorphic genomic region for a population derived from a cross, the method comprising:
 a. collecting pedigree and genotype information pertaining to one or more loci in at least one individual in a population;   b. building a first matrix by calculating the probability that alleles present at one or more loci in the one or more individuals are identical by descent in the population, based on the pedigree and genotype information;   c. using the first matrix to produce a second matrix that classifies one or more individuals from the population;   d. using the second matrix to select a subset of the individuals from the population that have an increased probability of having at least one polymorphic genomic region; and,   e. breeding the selected individuals;   
       wherein at least one step of the method is implemented on a computer. 
     
     
         14 . The method of  claim 13 , wherein the polymorphic genomic region is associated with a trait of interest. 
     
     
         15 . The method of  claim 13 , wherein the population comprises members of a plant species. 
     
     
         16 . The method of  claim 15 , wherein the plant species is selected from the group consisting of maize, wheat, rice, millet, barley, sorghum, rye, soybean, alfalfa, oilseed  Brassica , cotton, sunflower, potato, and tomato. 
     
     
         17 . The method of  claim 14 , wherein the trait of interest is selected from the group consisting of yield, leaf angle, anthesis-silking interval (ASI), staygreen duration, early growth rate, overall growth rate, growth pattern, maximum biomass, total biomass, nitrogen use efficiency, water use efficiency, tocol content, oleic acid content, phytic acid content, amino acid composition, oil quality or quantity, energy availability, digestibility, fatty acid composition, a pathogen defense mechanism, lysine and sulfur levels, starch synthesis, disease resistance, herbicide resistance, male sterility, plant vigor, nutrient content, hemicellulose content, cellulose production, cold tolerance, salt tolerance, heat tolerance, drought tolerance, grain moisture content, stalk lodging, root lodging, root pulling resistance, stand establishment, emergence, midsilk, test weight, protein content, starch percentage, relative maturity, plant height, seed size, disease resistance genes, heading date, resistance to insects, brittle snap, stalk breakage, resistance to fungus, seed moisture, head shape, hullability, seedling vigor, beginning bloom date, maturity date, seed shatter, winter survival, fiber strength, ear height, plant barrenness, seed number, seed weight, and color grade. 
     
     
         18 . The method of  claim 13 , wherein the population is a doubled haploid population. 
     
     
         19 . The method of  claim 18 , wherein the polymorphic genomic region is associated with drought tolerance.