Taeko Shibaya

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.

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.

Uncovering of major genetic factors generating naturally occurring variation in heading date among Asian rice cultivars.

To dissect the genetic factors controlling naturally occurring variation of heading date in Asian rice cultivars, we performed QTL analyses using F2 populations derived from crosses between a japonica cultivar, Koshihikari, and each of 12 cultivars originating from various regions in Asia. These 12 diverse cultivars varied in heading date under natural field conditions in Tsukuba, Japan. Transgressive segregation was observed in 10 F2 combinations. QTL analyses using multiple crosses revealed a comprehensive series of loci involved in natural variation in flowering time. One to four QTLs were detected in each cross combination, and some QTLs were shared among combinations. The chromosomal locations of these QTLs corresponded well with those detected in other studies. The allelic effects of the QTLs varied among the cross combinations. Sequence analysis of several previously cloned genes controlling heading date, including Hd1, Hd3a, Hd6, RFT1, and Ghd7, identified several functional polymorphisms, indicating that allelic variation at these loci probably contributes to variation in heading date. Taken together, the QTL and sequencing results indicate that a large portion of the phenotypic variation in heading date in Asian rice cultivars could be generated by combinations of different alleles (possibly both loss- and gain-of-function) of the QTLs detected in this study.

Genome-Wide Haplotype Changes Produced by Artificial Selection during Modern Rice Breeding in Japan

During the last 90 years, the breeding of rice has delivered cultivars with improved agronomic and economic characteristics. Crossing of different lines and successive artificial selection of progeny based on their phenotypes have changed the chromosomal constitution of the ancestors of modern rice; however, the nature of these changes is unclear. The recent accumulation of data for genome-wide single-nucleotide polymorphisms (SNPs) in rice has allowed us to investigate the change in haplotype structure and composition. To assess the impact of these changes during modern breeding, we studied 177 Japanese rice accessions, which were categorized into three groups: landraces, improved cultivars developed from 1931 to 1974 (the early breeding phase), and improved cultivars developed from 1975 to 2005 (the late breeding phase). Phylogenetic tree and structure analysis indicated genetic differentiation between non-irrigated (upland) and irrigated (lowland) rice groups as well as genetic structuring within the irrigated rice group that corresponded to the existence of three subgroups. Pedigree analysis revealed that a limited number of landraces and cultivars was used for breeding at the beginning of the period of systematic breeding and that 11 landraces accounted for 70% of the ancestors of the modern improved cultivars. The values for linkage disequilibrium estimated from SNP alleles and the haplotype diversity determined from consecutive alleles in five-SNP windows indicated that haplotype blocks became less diverse over time as a result of the breeding process. A decrease in haplotype diversity, caused by a reduced number of polymorphisms in the haplotype blocks, was observed in several chromosomal regions. However, our results also indicate that new haplotype polymorphisms have been generated across the genome during the breeding process. These findings will facilitate our understanding of the association between particular haplotypes and desirable phenotypes in modern Japanese rice cultivars.

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

BackgroundRice is a major source of dietary intake of arsenic (As) for the populations that consume rice as a staple food. Therefore, it is necessary to reduce the As concentration in rice to avoid the potential risk to human health. In this study, the genetic diversity in As accumulation and As speciation in rice grains was investigated using a world rice core collection (WRC) comprising 69 accessions grown over a 3-year period. Moreover, quantitative trait locus (QTL) analysis was conducted to identify QTLs controlling the dimethylarsinic acid (DMA) content of rice grains.ResultsThere was a 3-fold difference in the grain As concentration of WRC. Concentrations of total-As, inorganic As, and DMA were significantly affected by genotype, year, and genotype-year interaction effects. Among the WRC accessions, Local Basmati and Tima (indica type) were identified as cultivars with the lowest stable total-As and inorganic As concentrations. Using an F2 population derived from Padi Perak (a high-DMA accession) and Koshihikari (a low-DMA cultivar), we identified two QTLs on chromosome 6 (qDMAs6.1 and qDMAs6.2) and one QTL on chromosome 8 (qDMAs8) that were responsible for variations in the grain DMA concentration. Approximately 73% of total phenotypic variance in DMA was explained by the three QTLs.ConclusionsBased on the results provided, one strategy for developing rice cultivars with a low level of toxic As would be to change the proportion of organic As on the basis of a low level of total As content.

Advanced backcross QTL analysis reveals complicated genetic control of rice grain shape in a japonica × indica cross

Grain shape is an important trait for improving rice yield. A number of quantitative trait loci (QTLs) for this trait have been identified by using primary F2 mapping populations and recombinant inbred lines, in which QTLs with a small effect are harder to detect than they would be in advanced generations. In this study, we developed two advanced mapping populations (chromosome segment substitution lines [CSSLs] and BC4F2 lines consisting of more than 2000 individuals) in the genetic backgrounds of two improved cultivars: a japonica cultivar (Koshihikari) with short, round grains, and an indica cultivar (IR64) with long, slender grains. We compared the ability of these materials to reveal QTLs for grain shape with that of an F2 population. Only 8 QTLs for grain length or grain width were detected in the F2 population, versus 47 in the CSSL population and 65 in the BC4F2 population. These results strongly suggest that advanced mapping populations can reveal QTLs for agronomic traits under complicated genetic control, and that DNA markers linked with the QTLs are useful for choosing superior allelic combinations to enhance grain shape in the Koshihikari and IR64 genetic backgrounds.

Genetic architecture of variation in heading date among Asian rice accessions.

BackgroundHeading date, a crucial factor determining regional and seasonal adaptation in rice (Oryza sativa L.), has been a major selection target in breeding programs. Although considerable progress has been made in our understanding of the molecular regulation of heading date in rice during last two decades, the previously isolated genes and identified quantitative trait loci (QTLs) cannot fully explain the natural variation for heading date in diverse rice accessions.ResultsTo genetically dissect naturally occurring variation in rice heading date, we collected QTLs in advanced-backcross populations derived from multiple crosses of the japonica rice accession Koshihikari (as a common parental line) with 11 diverse rice accessions (5 indica, 3 aus, and 3 japonica) that originate from various regions of Asia. QTL analyses of over 14,000 backcrossed individuals revealed 255 QTLs distributed widely across the rice genome. Among the detected QTLs, 128 QTLs corresponded to genomic positions of heading date genes identified by previous studies, such as Hd1, Hd6, Hd3a, Ghd7, DTH8, and RFT1. The other 127 QTLs were detected in different chromosomal regions than heading date genes.ConclusionsOur results indicate that advanced-backcross progeny allowed us to detect and confirm QTLs with relatively small additive effects, and the natural variation in rice heading date could result from combinations of large- and small-effect QTLs. We also found differences in the genetic architecture of heading date (flowering time) among maize, Arabidopsis, and rice.

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.

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: