Current corn (Zea mays L.) hybrids are produced using proprietary inbred lines as parents. These proprietary lines are protected by U.

Estimates of genetic variance and heritability provide useful guidelines for answering many questions which arise in a plant breeding program. In this paper we have attempted to (a) delineate appropriate questions which can be answered by estimation of genetic variance components and heritabilities (b) examine the assumptions necessary for estimation and (c) clarify the limitations imposed on interpretation of the estimates by the assumptions.

In one of the longest-running experiments in biology, researchers at the University of Illinois have selected for altered composition of the maize kernel since 1896. Here we use an association study to infer the genetic basis of dramatic changes that occurred in response to selection for changes in oil concentration. The study population was produced by a cross between the high-and low-selection lines at generation 70, followed by 10 generations of random mating and the derivation of 500 lines by selfing. These lines were genotyped for 488 genetic markers and the oil concentration was evaluated in replicated field trials.Three methods of analysis were tested in simulations for ability to detect quantitative trait loci (QTL). The most effective method was model selection in multiple regression. This method detected ‫05ف‬ QTL accounting for ‫%05ف‬ of the genetic variance, suggesting that Ͼ50 QTL are involved. The QTL effect estimates are small and largely additive. About 20% of the QTL have negative effects (i.e., not predicted by the parental difference), which is consistent with hitchhiking and small population size during selection. The large number of QTL detected accounts for the smooth and sustained response to selection throughout the twentieth century. T HE genetic architecture of a quantitative trait con-tries. An objective of our study is to identify genes that sists of a set of parameters that explain the genetic may be used to increase the oil concentration of maize component of trait variation within or among populakernels through plant breeding or genetic engineering. tions. These parameters include the number of quanti-The experiment reported here originated in 1896 tative trait loci (QTL) affecting the trait, their locations when C. G. Hopkins began the Illinois long-term selecin the genome, the frequencies of alternative genotypes tion lines, which have become a "textbook" example of segregating at the QTL, the pattern of linkage disequithe power of artificial selection (see review by Dudley libria among QTL, and the magnitudes of additive, and Lambert 2004). From an open-pollinated variety dominance, and epistatic effects. Knowledge of genetic of maize, Hopkins started two populations that were architecture has applications in two areas: (1) the identiselected divergently for the percentage of kernel dry fication of genes with utility in agriculture and/or treatweight that consists of oil ("oil concentration" or "perment of disease and (2) making inferences about the centage of oil"). These populations are called Illinois evolutionary processes that maintain genetic variation high oil (IHO) and Illinois low oil (ILO). In each generand those that cause divergence between populations.ation and each population, bulked kernels from each Here we report a study of oil variation in maize that has of a number of ears (half-sib families) were analyzed both types of application. and the highest (or lowest) 20% of ears were selected to The kernels of a modern maize (Zea mays L.) hybrid be parents o...

The use of molecular markers to enhance plant breeding efforts is being widely studied. A major area of research is the use of molecular markers to identify and manipulate chromosome segments QTL (quantitative trait locus or loci depending on context) controlling quantitative traits. The objective of this paper is to review the theory and results associated with the use of molecular markers to manipulate QTL in plant breeding programs. First, methods of identifying marker‐ QTL associations are considered. The various statistical methods used for this purpose are reviewed along with a discussion of appropriate probability levels to use in declaring associations real. The effects of genotype × environment interaction and repeatability between populations are then considered. Following the section on identification of associations, the use of marker‐QTL associations in breeding procedures is reviewed. A review of procedures useful for small numbers of QTL is followed by a review of procedures appropriate when large numbers of QTL are found. The use of marker‐QTL associations for multiple trait selection is considered. Throughout the review, appropriate theory is considered and results which have been obtained are presented.

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