Kaworu Ebana

Deletion in a gene associated with grain size increased yields during rice domestication

The domestication of crops involves a complex process of selection in plant evolution and is associated with changes in the DNA regulating agronomically important traits. Here we report the cloning of a newly identified QTL, qSW5 (QTL for seed width on chromosome 5), involved in the determination of grain width in rice. Through fine mapping, complementation testing and association analysis, we found that a deletion in qSW5 resulted in a significant increase in sink size owing to an increase in cell number in the outer glume of the rice flower; this trait might have been selected by ancient humans to increase yield of rice grains. In addition, we mapped two other defective functional nucleotide polymorphisms of rice domestication-related genes with genome-wide RFLP polymorphisms of various rice landraces. These analyses show that the qSW5 deletion had an important historical role in artificial selection, propagation of cultivation and natural crossings in rice domestication, and shed light on how the rice genome was domesticated.

An SNP Caused Loss of Seed Shattering During Rice Domestication

Loss of seed shattering was a key event in the domestication of major cereals. We revealed that the qSH1 gene, a major quantitative trait locus of seed shattering in rice, encodes a BEL1-type homeobox gene and demonstrated that a single-nucleotide polymorphism (SNP) in the 5′ regulatory region of the qSH1 gene caused loss of seed shattering owing to the absence of abscission layer formation. Haplotype analysis and association analysis in various rice collections revealed that the SNP was highly associated with shattering among japonica subspecies of rice, implying that it was a target of artificial selection during rice domestication.

Loss of Function of a Proline-Containing Protein Confers Durable Disease Resistance in Rice

Blast-Resistant Rice The durability of disease resistance for an agricultural crop reflects the extent to which the defense stands up to evolutionary dodges on the part of the pathogen. Pi21, which is a quantitative trait locus (QTL) of rice, contributes to a particularly durable resistance to a fungal rice blast disease: Rice plants carrying the resistant allele have been in cultivation for more than a century, and yet the pathogen has been unable to find a way through the defense. Fukuoka et al. (p. 998; see the news story by Normile) have now cloned the responsible Pi21 QTL allele and were able to separate Pi21 resistance from tightly linked reductions in grain quality, paving the way for more widespread use of this allele in rice breeding. Quantitative trait loci may offer a particularly durable strategy for disease resistance. Blast disease is a devastating fungal disease of rice, one of the world’s staple foods. Race-specific resistance to blast disease has usually not been durable. Here, we report the cloning of a previously unknown type of gene that confers non–race-specific resistance and its successful use in breeding. Pi21 encodes a proline-rich protein that includes a putative heavy metal–binding domain and putative protein-protein interaction motifs. Wild-type Pi21 appears to slow the plant’s defense responses, which may support optimization of defense mechanisms. Deletions in its proline-rich motif inhibit this slowing. Pi21 is separable from a closely linked gene conferring poor flavor. The resistant pi21 allele, which is found in some strains of japonica rice, could improve blast resistance of rice worldwide.

Fine definition of the pedigree haplotypes of closely related rice cultivars by means of genome-wide discovery of single-nucleotide polymorphisms.

BackgroundTo create useful gene combinations in crop breeding, it is necessary to clarify the dynamics of the genome composition created by breeding practices. A large quantity of single-nucleotide polymorphism (SNP) data is required to permit discrimination of chromosome segments among modern cultivars, which are genetically related. Here, we used a high-throughput sequencer to conduct whole-genome sequencing of an elite Japanese rice cultivar, Koshihikari, which is closely related to Nipponbare, whose genome sequencing has been completed. Then we designed a high-throughput typing array based on the SNP information by comparison of the two sequences. Finally, we applied this array to analyze historical representative rice cultivars to understand the dynamics of their genome composition.ResultsThe total 5.89-Gb sequence for Koshihikari, equivalent to 15.7× the entire rice genome, was mapped using the Pseudomolecules 4.0 database for Nipponbare. The resultant Koshihikari genome sequence corresponded to 80.1% of the Nipponbare sequence and led to the identification of 67 051 SNPs. A high-throughput typing array consisting of 1917 SNP sites distributed throughout the genome was designed to genotype 151 representative Japanese cultivars that have been grown during the past 150 years. We could identify the ancestral origin of the pedigree haplotypes in 60.9% of the Koshihikari genome and 18 consensus haplotype blocks which are inherited from traditional landraces to current improved varieties. Moreover, it was predicted that modern breeding practices have generally decreased genetic diversityConclusionsDetection of genome-wide SNPs by both high-throughput sequencer and typing array made it possible to evaluate genomic composition of genetically related rice varieties. With the aid of their pedigree information, we clarified the dynamics of chromosome recombination during the historical rice breeding process. We also found several genomic regions decreasing genetic diversity which might be caused by a recent human selection in rice breeding. The definition of pedigree haplotypes by means of genome-wide SNPs will facilitate next-generation breeding of rice and other crops.

Molecular cloning of Sdr4, a regulator involved in seed dormancy and domestication of rice

Seed dormancy provides a strategy for flowering plants to survive adverse natural conditions. It is also an important agronomic trait affecting grain yield, quality, and processing performance. We cloned a rice quantitative trait locus, Sdr4, which contributes substantially to differences in seed dormancy between japonica (Nipponbare) and indica (Kasalath) cultivars. Sdr4 expression is positively regulated by OsVP1, a global regulator of seed maturation, and in turn positively regulates potential regulators of seed dormancy and represses the expression of postgerminative genes, suggesting that Sdr4 acts as an intermediate regulator of dormancy in the seed maturation program. Japonica cultivars have only the Nipponbare allele (Sdr4-n), which endows reduced dormancy, whereas both the Kasalath allele (Srd4-k) and Sdr4-n are widely distributed in the indica group, indicating prevalent introgression. Srd4-k also is found in the wild ancestor Oryza rufipogon, whereas Sdr4-n appears to have been produced through at least two mutation events from the closest O. rufipogon allele among the accessions examined. These results are discussed with respect to possible selection of the allele during the domestication process.

Natural Variation in Hd17, a Homolog of Arabidopsis ELF3 That is Involved in Rice Photoperiodic Flowering

Flowering time of rice depends strongly on photoperiodic responses. We previously identified a quantitative trait locus, Heading date 17 (Hd17), that is associated with a difference in flowering time between Japanese rice (Oryza sativa L.) cultivars. Here, we show that the difference may result from a single nucleotide polymorphism within a putative gene that encodes a homolog of the Arabidopsis EARLY FLOWERING 3 protein, which plays important roles in maintaining circadian rhythms. Our results demonstrate that natural variation in Hd17 may change the transcription level of a flowering repressor, Grain number, plant height and heading date 7 (Ghd7), suggesting that Hd17 is part of rices photoperiodic flowering pathway.

Dissection of genotype–phenotype associations in rice grains using metabolome quantitative trait loci analysis

A comprehensive and large-scale metabolome quantitative trait loci (mQTL) analysis was performed to investigate the genetic backgrounds associated with metabolic phenotypes in rice grains. The metabolome dataset consisted of 759 metabolite signals obtained from the grains of 85 lines of rice (Oryza sativa, Sasanishiki × Habataki back-crossed inbred lines). Metabolome analysis was performed using four mass spectrometry pipelines to enhance detection of different classes of metabolites. This mQTL analysis of a wide range of metabolites highlighted an uneven distribution of 802 mQTLs on the rice genome, as well as different modes of metabolic trait (m-trait) control among various types of metabolites. The levels of most metabolites within rice grains were highly sensitive to environmental factors, but only weakly associated with mQTLs. Coordinated control was observed for several groups of metabolites, such as amino acids linked to the mQTL hotspot on chromosome 3. For flavonoids, m-trait variation among the experimental lines was tightly governed by genetic factors that alter the glycosylation of flavones. Many loci affecting levels of metabolites were detected by QTL analysis, and plausible gene candidates were evaluated by in silico analysis. Several mQTLs profoundly influenced metabolite levels, providing insight into the control of rice metabolism. The genomic region and genes potentially responsible for the biosynthesis of apigenin-6,8-di-C-α-l-arabinoside are presented as an example of a critical mQTL identified by the analysis.

Discovery of Genome-Wide DNA Polymorphisms in a Landrace Cultivar of Japonica Rice by Whole-Genome Sequencing

Molecular breeding approaches are of growing importance to crop improvement. However, closely related cultivars generally used for crossing material lack sufficient known DNA polymorphisms due to their genetic relatedness. Next-generation sequencing allows the identification of a massive number of DNA polymorphisms such as single nucleotide polymorphisms (SNPs) and insertions–deletions (InDels) between highly homologous genomes. Using this technology, we performed whole-genome sequencing of a landrace of japonica rice, Omachi, which is used for sake brewing and is an important source for modern cultivars. A total of 229 million reads, each comprising 75 nucleotides of the Omachi genome, was generated with 45-fold coverage and uniquely mapped to 89.7% of the Nipponbare genome, a closely related cultivar. We identified 132,462 SNPs, 16,448 insertions and 19,318 deletions between the Omachi and Nipponbare genomes. An SNP array was designed to validate 731 selected SNPs, resulting in validation rates of 95 and 88% for the Omachi and Nipponbare genomes, respectively. Among the 577 SNPs validated in both genomes, 532 are entirely new SNP markers not previously reported between related rice cultivars. We also validated InDels on a part of chromosome 2 as DNA markers and successfully genotyped five japonica rice cultivars. Our results present the methodology and extensive data on SNPs and InDels available for whole-genome genotyping and marker-assisted breeding. The polymorphism information between Omachi and Nipponbare is available at NGRC_Rice_Omachi (http://www.nodai-genome.org/oryza_sativa_en.html).

Artificial selection for a green revolution gene during japonica rice domestication

The semidwarf phenotype has been extensively selected during modern crop breeding as an agronomically important trait. Introduction of the semidwarf gene, semi-dwarf1 (sd1), which encodes a gibberellin biosynthesis enzyme, made significant contributions to the “green revolution” in rice (Oryza sativa L.). Here we report that SD1 was involved not only in modern breeding including the green revolution, but also in early steps of rice domestication. We identified two SNPs in O. sativa subspecies (ssp.) japonica SD1 as functional nucleotide polymorphisms (FNPs) responsible for shorter culm length and low gibberellin biosynthetic activity. Genetic diversity analysis among O. sativa ssp. japonica and indica, along with their wild ancestor O. rufipogon Griff, revealed that these FNPs clearly differentiate the japonica landrace and O. rufipogon. We also found a dramatic reduction in nucleotide diversity around SD1 only in the japonica landrace, not in the indica landrace or O. rufipogon. These findings indicate that SD1 has been subjected to artificial selection in rice evolution and that the FNPs participated in japonica domestication, suggesting that ancient humans already used the green revolution gene.

SmartGrain: High-throughput phenotyping software for measuring seed shape through image analysis

Seed shape and size are among the most important agronomic traits because they affect yield and market price. To obtain accurate seed size data, a large number of measurements are needed because there is little difference in size among seeds from one plant. To promote genetic analysis and selection for seed shape in plant breeding, efficient, reliable, high-throughput seed phenotyping methods are required. We developed SmartGrain software for high-throughput measurement of seed shape. This software uses a new image analysis method to reduce the time taken in the preparation of seeds and in image capture. Outlines of seeds are automatically recognized from digital images, and several shape parameters, such as seed length, width, area, and perimeter length, are calculated. To validate the software, we performed a quantitative trait locus (QTL) analysis for rice (Oryza sativa) seed shape using backcrossed inbred lines derived from a cross between japonica cultivars Koshihikari and Nipponbare, which showed small differences in seed shape. SmartGrain removed areas of awns and pedicels automatically, and several QTLs were detected for six shape parameters. The allelic effect of a QTL for seed length detected on chromosome 11 was confirmed in advanced backcross progeny; the cv Nipponbare allele increased seed length and, thus, seed weight. High-throughput measurement with SmartGrain reduced sampling error and made it possible to distinguish between lines with small differences in seed shape. SmartGrain could accurately recognize seed not only of rice but also of several other species, including Arabidopsis (Arabidopsis thaliana). The software is free to researchers.