Finding a novel QTL responsible for kernel cracking resistance from CSSLs of 'Itadaki' (O. sativa L.) × donor O. rufipogon.

To find new QTLs responsible for kernel cracking resistance, we screened 50 CSSLs derived from the moderately resistant cultivar 'Itadaki' (O. sativa L.) and the donor O. rufipogon. Two lines, IRSL 30 and IRSL 37, were selected as resistant. QTL analyses of the percentage of cracked kernels (PCK) in F4 individuals derived from "Itadaki/IRSL 30" and "Itadaki/IRSL 37" identified a major QTL, qCR (Cracking Resistance) 8-2, at the same position on chromosome 8 in both populations. 'IRSL 30' and 'IRSL 37' had a reduced PCK. These results show that qCR8-2 is likely to be an important QTL for kernel cracking resistance. Both lines had long awns, linked to qCR8-2, but the awnless line 'Chukei 19301' was also derived from "Itadaki/IRSL 37", so qCR8-2 is distinct from the gene for awn development. We consider that qCR8-2 will help in the breeding of new rice cultivars with high cracking resistance and in elucidating the physiological mechanism of kernel cracking.

Exploring the areas of applicability of whole-genome prediction methods for Asian rice (Oryza sativa L.).

KEY MESSAGE: Our simulation results clarify the areas of applicability of nine prediction methods and suggest the factors that affect their accuracy at predicting empirical traits. Whole-genome prediction is used to predict genetic value from genome-wide markers. The choice of method is important for successful prediction. We compared nine methods using empirical data for eight phenological and morphological traits of Asian rice cultivars (Oryza sativa L.) and data simulated from real marker genotype data. The methods were genomic BLUP (GBLUP), reproducing kernel Hilbert spaces regression (RKHS), Lasso, elastic net, random forest (RForest), Bayesian lasso (Blasso), extended Bayesian lasso (EBlasso), weighted Bayesian shrinkage regression (wBSR), and the average of all methods (Ave). The objectives were to evaluate the predictive ability of these methods in a cultivar population, to characterize them by exploring the area of applicability of each method using simulation, and to investigate the causes of their different accuracies for empirical traits. GBLUP was the most accurate for one trait, RKHS and Ave for two, and RForest for three traits. In the simulation, Blasso, EBlasso, and Ave showed stable performance across the simulated scenarios, whereas the other methods, except wBSR, had specific areas of applicability; wBSR performed poorly in most scenarios. For each method, the accuracy ranking for the empirical traits was largely consistent with that in one of the simulated scenarios, suggesting that the simulation conditions reflected the factors that affected the method accuracy for the empirical results. This study will be useful for genomic prediction not only in Asian rice, but also in populations from other crops with relatively small training sets and strong linkage disequilibrium structures.

qAC2, a novel QTL that interacts with Wx and controls the low amylose content in rice (Oryza sativa L.).

KEY MESSAGE: This manuscript reports the fine mapping of a novel QTL, qAC2 controlling the low amylose in rice. The action mechanism of the qAC2 is also investigated by the analysis of genetic interactions to Wx (a), Wx (b), du1, du2 and du3. Amylose content of the rice (Oryza sativa L.) endosperm greatly affects starch properties and eating quality of cooked rice. Seeds of japonica rice cultivar Kuiku162 have low amylose content (AC) and good eating quality. Our analysis revealed a novel QTL, designated as qAC2 that contributed to the low AC of Kuiku162. qAC2 was fine mapped within a 74.9-kb region between two insertion and deletion markers, KID3001 and KID5101, on the long arm of chromosome 2. Seven genes are predicted in this region, but none of them is known to be related to the regulation of AC. The AC of a near-isogenic line (NIL110) carrying qAC2 (Kuiku), the Kuiku162 allele of qAC2, in the genetic background of japonica cultivar Itadaki was lower by 1.1% points than that of Itadaki. The chain length distributions of amylopectin were similar in NIL110 and Itadaki; therefore, the low AC of NIL110 was caused by a decrease in the actual AC, but not by a difference in the amylopectin structure. The interaction analyses revealed that qAC2 (Kuiku) has epistatic interaction with Wx (a). The qAC2 (Kuiku) has epistatic interactions with two loci, du1 and du2, on Wx (b), whereas the genetic effect of qAC2 (Kuiku) has additive to that of du3 on Wx (b). Thus, similar to du1 and du2, qAC2 may have a function related to Wx (b) mRNA splicing.

Population structure in Japanese rice population.

It is essential to elucidate genetic diversity and relationships among even related individuals and populations for plant breeding and genetic analysis. Since Japanese rice breeding has improved agronomic traits such as yield and eating quality, modern Japanese rice cultivars originated from narrow genetic resource and closely related. To resolve the population structure and genetic diversity in Japanese rice population, we used a total of 706 alleles detected by 134 simple sequence repeat markers in a total of 114 cultivars composed of 94 improved varieties and 20 landraces, which are representative and important for Japanese rice breeding. The landraces exhibit greater gene diversity than improved lines, suggesting that landraces can provide additional genetic diversity for future breeding. Model-based Bayesian clustering analysis revealed six subgroups and admixture situation in the cultivars, showing good agreement with pedigree information. This method could be superior to phylogenetic method in classifying a related population. The leading Japanese rice cultivar, Koshihikari is unique due to the specific genome constitution. We defined Japanese rice diverse sets that capture the maximum number of alleles for given sample sizes. These sets are useful for a variety of genetic application in Japanese rice cultivars.

Uncovering a Nuisance Influence of a Phenological Trait of Plants Using a Nonlinear Structural Equation: Application to Days to Heading and Culm Length in Asian Cultivated Rice (Oryza Sativa L.).

Phenological traits of plants, such as flowering time, are linked to growth phase transition. Thus, phenological traits often influence other traits through the modification of the duration of growth period. This influence is a nuisance in plant breeding because it hampers genetic evaluation of the influenced traits. Genetic effects on the influenced traits have two components, one that directly affects the traits and one that indirectly affects the traits via the phenological trait. These cannot be distinguished by phenotypic evaluation and ordinary linear regression models. Consequently, if a phenological trait is modified by introgression or editing of the responsible genes, the phenotypes of the influenced traits can change unexpectedly. To uncover the influence of the phenological trait and evaluate the direct genetic effects on the influenced traits, we developed a nonlinear structural equation (NSE) incorporating a nonlinear influence of the phenological trait. We applied the NSE to real data for cultivated rice (Oryza sativa L.): days to heading (DH) as a phenological trait and culm length (CL) as the influenced trait. This showed that CL of the cultivars that showed extremely early heading was shortened by the strong influence of DH. In a simulation study, it was shown that the NSE was able to infer the nonlinear influence and direct genetic effects with reasonable accuracy. However, the NSE failed to infer the linear influence in this study. When no influence was simulated, an ordinary bi-trait linear model (OLM) tended to infer the genetic effects more accurately. In such cases, however, by comparing the NSE and OLM using an information criterion, we could assess whether the nonlinear assumption of the NSE was appropriate for the data analyzed. This study demonstrates the usefulness of the NSE in revealing the phenotypic influence of phenological traits.

High potential of a transposon mPing as a marker system in japonica x japonica cross in rice.

Although quantitative traits loci (QTL) analysis has been widely performed to isolate agronomically important genes, it has been difficult to obtain molecular markers between individuals with similar phenotypes (assortative mating). Recently, the miniature inverted-repeat transposable element mPing was shown to be active in the japonica strain Gimbozu EG4 where it had accumulated more than 1000 copies. In contrast, most other japonicas, including Nipponbare, have 50 or fewer mPing insertions in their genome. In this study we have exploited the polymorphism of mPing insertion sites to generate 150 PCR markers in a cross between the closely related japonicas, Nipponbare x Gimbozu (EG4). These new markers were distributed in genic regions of the whole genome and showed significantly higher polymorphism (150 of 183) than all other molecular markers tested including short sequence repeat markers (46 of 661). In addition, we performed QTL analysis with these markers using recombinant inbred lines derived from Nipponbare x Gimbozu EG4, and successfully mapped a locus involved in heading date on the short arm of chromosome 6. Moreover, we could easily map two novel loci involved in the culm length on the short arms of chromosomes 3 and 10.