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.

Background and Aims High night temperatures are more harmful to grain weight in rice than high day temperatures. Grain growth rate and growth duration were investigated to determine which was the cause of the decrease in final grain weight under high night temperatures. Endosperm cell number and cell sizes were also examined to determine which might cause the decrease in final grain weight.Methods Rice plants were grown outdoors in plastic pots and moved at heading time to three temperaturecontrolled glasshouses under high night temperature (HNT; 22/34 C), high day temperature (HDT; 34/22 C) and control conditions (CONT; 22/22 C). Grains were sampled periodically, and the time-course of grain growth was divided into rate and duration by logistic regression analysis. Endosperm cell numbers and cell sizes were analysed by digitalized hand-tracing images of endosperm cross-sections.Key Results The duration of grain growth was reduced by high temperature both day and night. However, the rate of grain growth was lower in HNT than in HDT. The number of cells in endosperm cross-sections in HNT was similar to that in HDT, and higher than that in CONT. The average cell area was smaller in HNT than in either CONT or HDT. The differences in average cell areas between HNT and HDT were greater at distances 60-80 % from the central point of endosperm towards the endosperm surface.Conclusions The results show that HNT compared with HDT reduced the final grain weight by a reduction in grain growth rate in the early or middle stages of grain filling, and also reduced cell size midway between the central point and the surface of endosperm.ª 2005 Annals of Botany Company

). SUMMARYA 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-a-L-arabinoside are presented as an example of a critical mQTL identified by the analysis.

Plants produce structurally diverse secondary (specialized) metabolites to increase their fitness for survival under adverse environments. Several bioactive compounds for new drugs have been identified through screening of plant extracts. In this study, genome-wide association studies (GWAS) were conducted to investigate the genetic architecture behind the natural variation of rice secondary metabolites. GWAS using the metabolome data of 175 rice accessions successfully identified 323 associations among 143 single nucleotide polymorphisms (SNPs) and 89 metabolites. The data analysis highlighted that levels of many metabolites are tightly associated with a small number of strong quantitative trait loci (QTLs). The tight association may be a mechanism generating strains with distinct metabolic composition through the crossing of two different strains. The results indicate that one plant species produces more diverse phytochemicals than previously expected, and plants still contain many useful compounds for human applications.

Over the past two decades, genetic dissection of complex phenotypes of economic and biological interest has revealed the chromosomal locations of many quantitative trait loci (QTLs) in rice and their contributions to phenotypic variation. Mapping resolution has varied considerably among QTL studies owing to differences in population size and number of DNA markers used. Additionally, the same QTLs have often been reported with different locus designations. This situation has made it difficult to determine allelic relationships among QTLs and to compare their positions. To facilitate reliable comparisons of rice QTLs, we extracted QTL information from published research papers and constructed a database of 1,051 representative QTLs, which we classified into 21 trait categories. This database (QTL Annotation Rice Online database; Q-TARO, http://qtaro.abr.affrc.go.jp/) consists of two web interfaces. One interface is a table containing information on the mapping of each QTL and its genetic parameters. The other interface is a genome viewer for viewing genomic locations of the QTLs. Q-TARO clearly displays the co-localization of QTLs and distribution of QTL clusters on the rice genome.

Completion of the genome analysis followed by extensive comprehensive studies on a variety of genes and gene families of rice (Oryza sativa) resulted in rapid accumulation of information concerning the presence of many complex traits that are governed by a number of genes of distinct functions in this most important crop cultivated worldwide. The genetic and molecular biological dissection of many important rice phenotypes has contributed to our understanding of the complex nature of the genetic control with respect to these phenotypes. However, in spite of the considerable advances made in the field, details of genetic control remain largely unsolved, thereby hampering our exploitation of this useful information in the breeding of new rice cultivars. To further strengthen the field application of the genome science data of rice obtained so far, we need to develop more powerful genomics-assisted methods for rice breeding based on information derived from various quantitative trait loci (QTL) and related analyses. In this review, we describe recent progresses and outcomes in rice QTL analyses, problems associated with the application of the technology to rice breeding and their implications for the genetic study of other crops along with future perspectives of the relevant fields.

BackgroundThe high-quality sequence information and rich bioinformatics tools available for rice have contributed to remarkable advances in functional genomics. To facilitate the application of gene function information to the study of natural variation in rice, we comprehensively searched for articles related to rice functional genomics and extracted information on functionally characterized genes.ResultsAs of 31 March 2012, 702 functionally characterized genes were annotated. This number represents about 1.6% of the predicted loci in the Rice Annotation Project Database. The compiled gene information is organized to facilitate direct comparisons with quantitative trait locus (QTL) information in the Q-TARO database. Comparison of genomic locations between functionally characterized genes and the QTLs revealed that QTL clusters were often co-localized with high-density gene regions, and that the genes associated with the QTLs in these clusters were different genes, suggesting that these QTL clusters are likely to be explained by tightly linked but distinct genes. Information on the functionally characterized genes compiled during this study is now available in the O verview of Functionally Characterized G enes in R ice O nline database (OGRO) on the Q-TARO website (http://qtaro.abr.affrc.go.jp/ogro). The database has two interfaces: a table containing gene information, and a genome viewer that allows users to compare the locations of QTLs and functionally characterized genes.ConclusionsOGRO on Q-TARO will facilitate a candidate-gene approach to identifying the genes responsible for QTLs. Because the QTL descriptions in Q-TARO contain information on agronomic traits, such comparisons will also facilitate the annotation of functionally characterized genes in terms of their effects on traits important for rice breeding. The increasing amount of information on rice gene function being generated from mutant panels and other types of studies will make the OGRO database even more valuable in the future.Electronic supplementary materialThe online version of this article (doi:10.1186/1939-8433-5-26) contains supplementary material, which is available to authorized users.

Semi-dwarfing genes have contributed to enhanced lodging resistance, resulting in increased crop productivity. In the history of grain sorghum breeding, the spontaneous mutation, dw1 found in Memphis in 1905, was the first widely used semi-dwarfing gene. Here, we report the identification and characterization of Dw1. We performed quantitative trait locus (QTL) analysis and cloning, and revealed that Dw1 encodes a novel uncharacterized protein. Knockdown or T-DNA insertion lines of orthologous genes in rice and Arabidopsis also showed semi-dwarfism similar to that of a nearly isogenic line (NIL) carrying dw1 (NIL-dw1) of sorghum. A histological analysis of the NIL-dw1 revealed that the longitudinal parenchymal cell lengths of the internode were almost the same between NIL-dw1 and wildtype, while the number of cells per internode was significantly reduced in NIL-dw1. NIL-dw1dw3, carrying both dw1 and dw3 (involved in auxin transport), showed a synergistic phenotype. These observations demonstrate that the dw1 reduced the cell proliferation activity in the internodes, and the synergistic effect of dw1 and dw3 contributes to improved lodging resistance and mechanical harvesting.