Development of 12 sets of chromosome segment substitution lines that enhance allele mining in Asian cultivated rice.

Many agronomic traits that are important in rice breeding are controlled by multiple genes. The extensive time and effort devoted so far to identifying and selecting such genes are still not enough to target multiple agronomic traits in practical breeding in Japan because of a lack of suitable plant materials in which to efficiently detect and validate beneficial alleles from diverse genetic resources. To facilitate the comprehensive analysis of genetic variation in agronomic traits among Asian cultivated rice, we developed 12 sets of chromosome segment substitution lines (CSSLs) with the japonica background, 11 of them in the same genetic background, using donors representing the genetic diversity of Asian cultivated rice. Using these materials, we overviewed the chromosomal locations of 1079 putative QTLs for seven agronomic traits and their allelic distribution in Asian cultivated rice through multiple linear regression analysis. The CSSLs will allow the effects of putative QTLs in the highly homogeneous japonica background to be validated.

Genomic divergence during feralization reveals both conserved and distinct mechanisms of parallel weediness evolution.

Agricultural weeds are the most important biotic constraints to global crop production, and chief among these is weedy rice. Despite increasing yield losses from weedy rice in recent years worldwide, the genetic basis of weediness evolution remains unclear. Using whole-genome sequence analyses, we examined the origins and adaptation of Japanese weedy rice. We find evidence for a weed origin from tropical japonica crop ancestry, which has not previously been documented in surveys of weedy rice worldwide. We further show that adaptation occurs largely through different genetic mechanisms between independently-evolved temperate japonica- and tropical japonica-derived strains; most genomic signatures of positive selection are unique within weed types. In addition, some weedy rice strains have evolved through hybridization between weedy and cultivated rice with adaptive introgression from the crop. Surprisingly, introgression from cultivated rice confers not only crop-like adaptive traits (such as shorter plant height, facilitating crop mimicry) but also weedy-like traits (such as seed dormancy). These findings reveal how hybridization with cultivated rice can promote persistence and proliferation of weedy rice.

Investigation of the Genetic Diversity of a Rice Core Collection of Japanese Landraces using Whole-Genome Sequencing.

The Rice Core Collection of Japanese Landraces (JRC) consisting of 50 accessions was developed by the genebank at the National Agriculture and Food Research Organization (NARO) in 2008. As a Japanese landrace core collection, the JRC has been used for many research projects, including screening for different phenotypes and allele mining for target genes. To understand the genetic diversity of Japanese Landraces, we performed whole-genome resequencing of these 50 accessions and obtained a total of 2,145,095 single nucleotide polymorphism (SNPs) and 317,832 insertion-deletions (indels) by mapping against the Oryza sativa ssp. japonica Nipponbare genome. A JRC phylogenetic tree based on 1,394 representative SNPs showed that JRC accessions were divided into two major groups and one small group. We used the multiple genome browser, TASUKE+, to examine the haplotypes of flowering genes and detected new mutations in these genes. Finally, we performed genome-wide association studies (GWAS) for agronomical traits using the JRC and another core collection, the World Rice Core Collection (WRC), comprising 69 accessions also provided by the NARO genebank. In leaf blade width, a strong peak close to NAL1, a key gene for the regulation of leaf width, and, in heading date, a peak near HESO1 involved in flowering regulation were observed in GWAS using the JRC. They were also detected in GWAS using the combined JRC + WRC. Thus, JRC and JRC + WRC are suitable populations for GWAS of particular traits.

Choosing the optimal population for a genome-wide association study: A simulation of whole-genome sequences from rice.

A genome-wide association study (GWAS) needs to have a suitable population. The factors that affect a GWAS (e.g. population structure, sample size, and sequence analysis and field testing costs) need to be considered. Mixed populations containing subpopulations of different genetic backgrounds may be suitable populations. We conducted simulation experiments to see if a population with high genetic diversity, such as a diversity panel, should be added to a target population, especially when the target population harbors small genetic diversity. The target population was 112 accessions of Oryza sativa L. subsp. japonica, mainly developed in Japan. We combined the target population with three populations that had higher genetic diversity. These were 100 indica accessions, 100 japonica accessions, and 100 accessions with various genetic backgrounds. The results showed that the GWAS's power with a mixed population was generally higher than with a separate population. Also, the optimal GWAS populations varied depending on the fixation index (FST ) of the quantitative trait nucleotides (QTNs) and the polymorphism of QTNs in each population. When a QTN was polymorphic in a target population, a target population combined with a higher diversity population improved the QTN's detection power. By investigating FST and the expected heterozygosity (He ) as factors influencing the detection power, we showed that single nucleotide polymorphisms with high FST or low He are less likely to be detected by GWAS with mixed populations. Sequenced or genotyped germplasm collections can improve the GWAS's detection power by using a subset of the collections with a target population.

Predicting biomass of rice with intermediate traits: Modeling method combining crop growth models and genomic prediction models.

Genomic prediction (GP) is expected to become a powerful technology for accelerating the genetic improvement of complex crop traits. Several GP models have been proposed to enhance their applications in plant breeding, including environmental effects and genotype-by-environment interactions (G×E). In this study, we proposed a two-step model for plant biomass prediction wherein environmental information and growth-related traits were considered. First, the growth-related traits were predicted by GP. Second, the biomass was predicted from the GP-predicted values and environmental data using machine learning or crop growth modeling. We applied the model to a 2-year-old field trial dataset of recombinant inbred lines of japonica rice and evaluated the prediction accuracy with training and testing data by cross-validation performed over two years. Therefore, the proposed model achieved an equivalent or a higher correlation between the observed and predicted values (0.53 and 0.65 for each year, respectively) than the model in which biomass was directly predicted by GP (0.40 and 0.65 for each year, respectively). This result indicated that including growth-related traits enhanced accuracy of biomass prediction. Our findings are expected to contribute to the spread of the use of GP in crop breeding by enabling more precise prediction of environmental effects on crop traits.

Whole genome sequencing data of Oryza sativa L. cv. Takanari.

Oryza sativa L. 'Takanari' is one of the most productive indica cultivars [1,2]. Reciprocal chromosome segment substitution lines (CSSLs) derived from a cross between 'Koshihikari' and 'Takanari' are useful tools for the detection and precise mapping of target quantitative trait loci (QTL) in 'Takanari'. Although the available Os-Nipponbare-Reference-IRGSP-1.0 reference genome is available and useful for evaluating genetic diversity among japonica cultivars, it is not always useful for evaluating genetic diversity harbored by indica cultivars such as 'Takanari'. To reveal sequence variants in 'Takanari' and to exploit these variants in rice breeding programs, the whole genome of 'Takanari' was sequenced using a combination of Illumina HiSeq X Ten (20,983,495 reads and %GC 43) and PacBio (2,847,220 high-quality subreads). NGS data obtained have been deposited in the DNA Data Bank of Japan (DDBJ) under accession number DRA007557.

Genetic variation in rice (Oryza sativa L.) germplasm from northern Laos.

We assessed genetic variation in rice germplasm in northern Laos and Vientiane province from polymorphism data of SSR markers. We classified 314 accessions into three clusters; Ia (corresponding to the lowland Japonica Group), Ib (upland Japonica Group) and II (Indica Group). The accessions of cluster Ib grew mainly in mountainous fields, and those of cluster II grew commonly in basins and along rivers. The few accessions of cluster Ia grew in only three provinces: Houaphanh, Xiangkhouang and Vientiane. Lowland cultivars in cluster II were predominant in Vientiane. Variations in heading date under short-day conditions in 2014 and long-day conditions in 2015 indicate that many accessions were sensitive to the photoperiod on account of complex genetic mechanisms underlying both photoperiod sensitivity and basic vegetative growth. A total of 219 among whole accessions were classified into 6 groups: E1-3 and L1-3. E2 and E3 were dominant in clusters Ib and II; E1 and L1-3 were minor groups. These results demonstrate characteristic distributions of the Indica and Japonica Group's germplasms in northern Laos and their genetic variation in heading date.

Endosperm enzyme activity is responsible for texture and eating quality of cooked rice grains in Japanese cultivars.

Eating quality of cooked rice grains is an important determinant of its market price and consumer acceptance. To comprehensively assess the variation of eating-quality traits in 152 Japanese rice cultivars, we evaluated activities of eight endosperm enzymes related to degradation of starch and cell-wall polysaccharides. Endosperm enzyme activities showed a wide range of variations and were lower in recently developed cultivars than in landraces and old improved cultivars. Activities of most endosperm enzymes correlated significantly with the eating-quality score and surface texture of cooked rice grains. Principal component analysis revealed that rice cultivars with high eating-quality scores had high stickiness of the grain surface and low levels of endosperm enzyme activities. These results suggest that endosperm enzyme activities control texture and eating quality of cooked rice grains in Japanese rice cultivars.

Description of grain weight distribution leading to genomic selection for grain-filling characteristics in rice.

Grain-filling ability is one of the factors that controls grain yield in rice (Oryza sativa L.). We developed a method for describing grain weight distribution, which is the probability density function of single grain weight in a panicle, using 128 Japanese rice varieties. With this method, we quantitively analyzed genotypic differences in grain-filling ability and used the grain weight distribution parameters for genomic prediction subject to genetic improvement in grain yield in rice. The novel description method could represent the observed grain weight distribution with five genotype-specific parameters of a mixture of two gamma distributions. The estimated genotype-specific parameters representing the proportion of filled grains had applicability to explain the grain filling ability of genotypes comparable to that of sink-filling rate and the conventionally measured proportion of filled grains, which suggested the efficiency and flexibility of grain weight distribution parameters to handle several genotypes. We revealed that perfectly filled grains have to be prioritized over partially filled grains for the optimum allocation of the source of yield in a panicle, from the analysis for obtaining an ideal shape of grain weight distribution. We conducted genomic prediction of grain weight distribution considering five genotype-specific parameters of the distribution as phenotypes relating to grain filling ability. The proportion of filled grains, average weight of filled grains, and variance of filled grain weight, which were considered to control grain yield to a certain degree, were predicted with accuracies of 0.30, 0.28, and 0.53, respectively. The proposed description method of grain weight distribution facilitated not only the investigation of the optimum allocation of nutrients in a panicle for realizing high grain-filling ability, but also allowed genomic selection of grain weight distribution.

Ethylene-gibberellin signaling underlies adaptation of rice to periodic flooding.

Most plants do poorly when flooded. Certain rice varieties, known as deepwater rice, survive periodic flooding and consequent oxygen deficiency by activating internode growth of stems to keep above the water. Here, we identify the gibberellin biosynthesis gene, SD1 (SEMIDWARF1), whose loss-of-function allele catapulted the rice Green Revolution, as being responsible for submergence-induced internode elongation. When submerged, plants carrying the deepwater rice-specific SD1 haplotype amplify a signaling relay in which the SD1 gene is transcriptionally activated by an ethylene-responsive transcription factor, OsEIL1a. The SD1 protein directs increased synthesis of gibberellins, largely GA4, which promote internode elongation. Evolutionary analysis shows that the deepwater rice-specific haplotype was derived from standing variation in wild rice and selected for deepwater rice cultivation in Bangladesh.

Correction to: Genetic diversity of arsenic accumulation in rice and QTL analysis of methylated arsenic in rice grains.

The authors of article "Genetic diversity of arsenic accumulation in rice and QTL analysis of methylated arsenic in rice grains" (Kuramata et al. 2013) would like to note that the original version of the article online unfortunately contains the following errors.

Genetic dissection of grain traits in Yamadanishiki, an excellent sake-brewing rice cultivar.

KEY MESSAGE: The grain traits of Yamadanishiki, an excellent sake-brewing rice cultivar in Japan, are governed by multiple QTLs, namely, a total of 42 QTLs including six major QTLs. Japanese rice wine (sake) is produced using brewing rice (Oryza sativa L.) that carries traits desirable for sake-brewing, such as a larger grain size and higher white-core expression rate (WCE) compared to cooking rice cultivars. However, the genetic basis for these traits in brewing rice cultivars is still unclear. We performed analyses of quantitative trait locus (QTL) of grain and days to heading over 3 years on populations derived from crosses between Koshihikari, a cooking rice, and Yamadanishiki, an excellent sake-brewing rice. A total of 42 QTLs were detected for the grain traits, and the Yamadanishiki alleles at 16 QTLs contributed to larger grain size. Two major QTLs essential for regulating both 100-grain weight (GWt) and grain width (GWh) were harbored in the same regions on chromosomes 5 and 10. An interaction was noted between the environment and the QTL associated with WCE on chromosome 6, which was detected in two of 3 years. In addition, two QTLs for WCE on chromosomes 3 and 10 overlapped with the QTLs for GWt and GWh, suggesting that QTLs associated with grain size also play an important role in the formation of white-core. Despite differences in the rate of grain growth in both Koshihikari and Yamadanishiki across 2 years, the WCE in Yamadanishiki remained consistent, thus demonstrating that the formation of white-core does not depend on grain filling speed. These data can be informative for programs involved in breeding better cooking and brewing rice cultivars.

Multi-task Gaussian process for imputing missing data in multi-trait and multi-environment trials.

KEY MESSAGE: A method based on a multi-task Gaussian process using self-measuring similarity gave increased accuracy for imputing missing phenotypic data in multi-trait and multi-environment trials. Multi-environmental trial (MET) data often encounter the problem of missing data. Accurate imputation of missing data makes subsequent analysis more effective and the results easier to understand. Moreover, accurate imputation may help to reduce the cost of phenotyping for thinned-out lines tested in METs. METs are generally performed for multiple traits that are correlated to each other. Correlation among traits can be useful information for imputation, but single-trait-based methods cannot utilize information shared by traits that are correlated. In this paper, we propose imputation methods based on a multi-task Gaussian process (MTGP) using self-measuring similarity kernels reflecting relationships among traits, genotypes, and environments. This framework allows us to use genetic correlation among multi-trait multi-environment data and also to combine MET data and marker genotype data. We compared the accuracy of three MTGP methods and iterative regularized PCA using rice MET data. Two scenarios for the generation of missing data at various missing rates were considered. The MTGP performed a better imputation accuracy than regularized PCA, especially at high missing rates. Under the 'uniform' scenario, in which missing data arise randomly, inclusion of marker genotype data in the imputation increased the imputation accuracy at high missing rates. Under the 'fiber' scenario, in which missing data arise in all traits for some combinations between genotypes and environments, the inclusion of marker genotype data decreased the imputation accuracy for most traits while increasing the accuracy in a few traits remarkably. The proposed methods will be useful for solving the missing data problem in MET data.

Hd18, Encoding Histone Acetylase Related to Arabidopsis FLOWERING LOCUS D, is Involved in the Control of Flowering Time in Rice.

Flowering time is one of the most important agronomic traits in rice (Oryza sativa L.), because it defines harvest seasons and cultivation areas, and affects yields. We used a map-based strategy to clone Heading date 18 (Hd18). The difference in flowering time between the Japanese rice cultivars Koshihikari and Hayamasari was due to a single nucleotide polymorphism within the Hd18 gene, which encodes an amine oxidase domain-containing protein and is homologous to Arabidopsis FLOWERING LOCUS D (FLD). The Hayamasari Hd18 allele and knockdown of Hd18 gene expression delayed the flowering time of rice plants regardless of the day-length condition. Structural modeling of the Hd18 protein suggested that the non-synonymous substitution changed protein stability and function due to differences in interdomain hydrogen bond formation. Compared with those in Koshihikari, the expression levels of the flowering-time genes Early heading date 1 (Ehd1), Heading date 3a (Hd3a) and Rice flowering locus T1 (RFT1) were lower in a near-isogenic line with the Hayamasari Hd18 allele in a Koshihikari genetic background. We revealed that Hd18 acts as an accelerator in the rice flowering pathway under both short- and long-day conditions by elevating transcription levels of Ehd1 Gene expression analysis also suggested the involvement of MADS-box genes such as OsMADS50, OsMADS51 and OsMADS56 in the Hd18-associated regulation of Ehd1 These results suggest that, like FLD, its rice homolog accelerates flowering time but is involved in rice flowering pathways that differ from the autonomous pathways in Arabidopsis.

Variation in cooking and eating quality traits in Japanese rice germplasm accessions.

The eating quality of cooked rice is important and determines its market price and consumer acceptance. To comprehensively describe the variation of eating quality in 183 rice germplasm accessions, we evaluated 33 eating-quality traits including amylose and protein contents, pasting properties of rice flour, and texture of cooked rice grains. All eating-quality traits varied widely in the germplasm accessions. Principal-components analysis (PCA) revealed that allelic differences in the Wx gene explained the largest proportion of phenotypic variation of the eating-quality traits. In 146 accessions of non-glutinous temperate japonica rice, PCA revealed that protein content and surface texture of the cooked rice grains significantly explained phenotypic variations of the eating-quality traits. An allelic difference based on simple sequence repeats, which was located near a quantitative trait locus (QTL) on the short arm of chromosome 3, was associated with differences in the eating quality of non-glutinous temperate japonica rice. These results suggest that eating quality is controlled by genetic factors, including the Wx gene and the QTL on chromosome 3, in Japanese rice accessions. These genetic factors have been consciously selected for eating quality during rice breeding programs in Japan.

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic selection in autogamous crops, especially bringing long-term improvement.

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.

The Birth of a Black Rice Gene and Its Local Spread by Introgression.

The origin and spread of novel agronomic traits during crop domestication are complex events in plant evolution. Wild rice (Oryza rufipogon) has red grains due to the accumulation of proanthocyanidins, whereas most cultivated rice (Oryza sativa) varieties have white grains induced by a defective allele in the Rc basic helix-loop-helix (bHLH) gene. Although the events surrounding the origin and spread of black rice traits remain unknown, varieties with black grains due to anthocyanin accumulation are distributed in various locations throughout Asia. Here, we show that the black grain trait originated from ectopic expression of the Kala4 bHLH gene due to rearrangement in the promoter region. Both the Rc and Kala4 genes activate upstream flavonol biosynthesis genes, such as chalcone synthase and dihydroflavonol-4-reductase, and downstream genes, such as leucoanthocyanidin reductase and leucoanthocyanidin dioxygenase, to produce the respective specific pigments. Genome analysis of 21 black rice varieties as well as red- and white-grained landraces demonstrated that black rice arose in tropical japonica and its subsequent spread to the indica subspecies can be attributed to the causal alleles of Kala4. The relatively small size of genomic fragments of tropical japonica origin in some indica varieties indicates that refined introgression must have occurred by natural crossbreeding in the course of evolution of the black trait in rice.

Natural Variation in the Flag Leaf Morphology of Rice Due to a Mutation of the NARROW LEAF 1 Gene in Oryza sativa L.

We investigated the natural variations in the flag leaf morphology of rice. We conducted a principal component analysis based on nine flag leaf morphology traits using 103 accessions from the National Institute of Agrobiological Sciences Core Collection. The first component explained 39% of total variance, and the variable with highest loading was the width of the flag leaf (WFL). A genome-wide association analysis of 102 diverse Japanese accessions revealed that marker RM6992 on chromosome 4 was highly associated with WFL. In analyses of progenies derived from a cross between Takanari and Akenohoshi, the most significant quantitative trait locus (QTL) for WFL was in a 10.3-kb region containing the NARROW LEAF 1 (NAL1) gene, located 0.4 Mb downstream of RM6992. Analyses of chromosomal segment substitution lines indicated that a mutation (G1509A single-nucleotide mutation, causing an R233H amino acid substitution in NAL1) was present at the QTL. This explained 13 and 20% of total variability in WFL and the distance between small vascular bundles, respectively. The mutation apparently occurred during rice domestication and spread into japonica, tropical japonica, and indica subgroups. Notably, one accession, Phulba, had a NAL1 allele encoding only the N-terminal, or one-fourth, of the wild-type peptide. Given that the Phulba allele and the histidine-type allele showed essentially the same phenotype, the histidine-type allele was regarded as malfunctional. The phenotypes of transgenic plants varied depending on the ratio of histidine-type alleles to arginine-type alleles, raising the possibility that H(233)-type products function differently from and compete with R(233)-type products.

Detection of QTLs for white-back and basal-white grains caused by high temperature during ripening period in japonica rice.

There is increasing evidence that global warming affects the development of rice. High temperatures during ripening increase the ratio of undesirable chalky grains followed by deteriorating grain appearance quality. In order to detect quantitative trait loci (QTLs) controlling the occurrence of white-back and basal-white chalky grains of brown rice, QTL analysis was performed using recombinant inbred lines derived from a cross between two strains, 'Tsukushiroman' (sensitive to heat stress) and 'Chikushi 52' (tolerant of heat stress). The F7 and F8 lines were exposed to heat stress during the ripening period in two locations, Fukuoka and Kagoshima, in Japan. QTLs for white-back grains and basal-white grains were detected on chromosomes 1, 3, and 8, and those for basal-white grains were detected on chromosomes 2, 3, and 12. QTLs on chromosome 8 for white-back grains were shared in the plants grown in both locations. Near-isogenic lines (NILs), which harbored a segment from 'Chikushi 52' on chromosome 8 with the genetic background of 'Tsukushiroman', showed relatively lower ratios of white-back grains than 'Tsukushiroman'. Therefore, insertion of the 'Chikushi 52' genomic region of the QTL on chromosome 8 can improve the quality of rice when it is grown under heat stress conditions.