The three important traits for cooking and eating quality of rice grains are controlled by a single locus in an elite rice hybrid, Shanyou 63

Identification of quantitative trait loci for grain quality in an advanced backcross population derived from the Oryza sativa variety IR64 and the wild relative O. rufipogon

The objective of this study was to identify quantitative trait loci (QTLs) associated with grain quality in rice. Two hundred eighty-five BC(2)F(2 )families developed from an interspecific cross between cv IR64 and Oryza rufipogon (IRGC 105491) were evaluated for 14 seed quality traits. A total of 165 markers consisting of 131 single sequence repeats and 34 restriction fragment length polymorphism markers were used to create a genetic linkage map spanning the 12 rice chromosomes. Twenty-three independent QTLs were identified using single point analysis, interval mapping, and composite interval mapping. These loci consisted of one QTL for filled rough/total rough rice ratio, two for grain density, one for percentage of de-husked rice grains, two for percentage of green rice grains, three for percentage of damaged-yellow rice grains, two for percentage of red rice grains, one for milled rice recovery, three for head rice recovery, four for broken rice grains, two for crushed rice grains, one for amylose content, and one for gel consistency. For most of the QTLs identified in this study, the O. rufipogon-derived allele contributed an undesirable effect. For amylose content and gel consistency, the O. rufipogon allele may be useful in an IR64 background, depending on the cultural preferences of the consumer. Careful selection against the regions associated with negative effects will be required to avoid unwanted grain quality characteristics during the development of improved varieties for yield and yield components using introgressions from O. rufipogon.

Mapping quantitative trait loci underlying triploid endosperm traits

Endosperm, which is derived from two polar nuclei fusing with one sperm, is a triploid tissue in cereals. Endosperm tissue determines the grain quality of cereals. Improving grain quality is one of the important breeding objectives in cereals. However, current statistical methods for mapping quantitative trait loci (QTL) under diploid genetic control have not been effective for dealing with endosperm traits because of the complexity of their triploid inheritance. In this paper, we derive for the first time the conditional probabilities of F(3) endosperm QTL genotypes given different flanking marker genotypes in F(2) plants. Using these probabilities, we develop a multiple linear regression method implemented via the iteratively reweighted least-squares (IRWLS) algorithm and a maximum likelihood method (ML) implemented via the expectation-maximization (EM) algorithm to map QTL underlying endosperm traits. We use the mean value of endosperm traits of F(3) seeds as the dependent variable and the expectations of genotypic indicators for additive and dominance effect of a putative QTL flanked by a pair of markers as independent variables for IRWLS mapping. However, if an endosperm trait is measured quantitatively using a single endosperm sample, the ML mapping method can be used to separate the two dominance effects. Efficiency of the methods is verified through extensive Monte Carlo simulation studies. Results of simulation show that the proposed methods provide accurate estimates of both the QTL effects and locations with very high statistical power. With these methods, we are now ready to map endosperm traits, as we can for regular quantitative trait under diploid control.

Statistical methods for dissecting triploid endosperm traits using molecular markers. An autogamous model

The endosperm, a result of double fertilization in flowering plants, is a triploid tissue whose genetic composition is more complex than diploid tissue. We present a new maximum-likelihood-based statistical method for mapping quantitative trait loci (QTL) underlying endosperm traits in an autogamous plant. Genetic mapping of quantitative endosperm traits is qualitatively different from traits for other plant organs because the endosperm displays complicated trisomic inheritance and represents a younger generation than its mother plant. Our endosperm mapping method is based on two different experimental designs: (1) a one-stage design in which marker information is derived from the maternal genome and (2) a two-stage hierarchical design in which marker information is derived from both the maternal and offspring genomes (embryos). Under the one-stage design, the position and additive effect of a putative QTL can be well estimated, but the estimates of the dominant and epistatic effects are upward biased and imprecise. The two-stage hierarchical design, which extracts more genetic information from the material, typically improves the accuracy and precision of the dominant and epistatic effects for an endosperm trait. We discuss the effects on the estimation of QTL parameters of different sampling strategies under the two-stage hierarchical design. Our method will be broadly useful in mapping endosperm traits for many agriculturally important crop plants and also make it possible to study the genetic significance of double fertilization in the evolution of higher plants.