Global transcriptome profile of rice root in response to essential macronutrient deficiency

Deficiency of the three essential macronutrients, nitrogen, phosphorus and potassium, leads to large reduction in crop growth and yield. To characterize the molecular genetic basis of adaptation to macronutrient deprivation, we performed microarray analysis of rice root at 6 and 24 h after nitrogen, phosphorus and potassium deficiency treatments. The transcriptome response to nitrogen depletion occurred more rapidly than corresponding responses to phosphorus and potassium deprivation. We identified several genes important for response and adaptation to each nutrient deficiency. Furthermore, we found that signaling via reactive oxygen species is a common feature in response to macronutrient deficiency and signaling via jasmonic acid is associated with potassium depletion response. These results will facilitate deeper understanding of nutrient utilization of plants.

RiceFREND: a platform for retrieving coexpressed gene networks in rice

Similarity of gene expression across a wide range of biological conditions can be efficiently used in characterization of gene function. We have constructed a rice gene coexpression database, RiceFREND (http://ricefrend.dna.affrc.go.jp/), to identify gene modules with similar expression profiles and provide a platform for more accurate prediction of gene functions. Coexpression analysis of 27 201 genes was performed against 815 microarray data derived from expression profiling of various organs and tissues at different developmental stages, mature organs throughout the growth from transplanting until harvesting in the field and plant hormone treatment conditions, using a single microarray platform. The database is provided with two search options, namely, 'single guide gene search' and 'multiple guide gene search' to efficiently retrieve information on coexpressed genes. A user-friendly web interface facilitates visualization and interpretation of gene coexpression networks in HyperTree, Cytoscape Web and Graphviz formats. In addition, analysis tools for identification of enriched Gene Ontology terms and cis-elements provide clue for better prediction of biological functions associated with the coexpressed genes. These features allow users to clarify gene functions and gene regulatory networks that could lead to a more thorough understanding of many complex agronomic traits.

RiceXPro version 3.0: expanding the informatics resource for rice transcriptome

A wide range of resources on gene expression profiling enhance various strategies in plant molecular biology particularly in characterization of gene function. We have updated our gene expression profile database, RiceXPro (http://ricexpro.dna.affrc.go.jp/), to provide more comprehensive information on the transcriptome of rice encompassing the entire growth cycle and various experimental conditions. The gene expression profiles are currently grouped into three categories, namely, ‘field/development’ with 572 data corresponding to 12 data sets, ‘plant hormone’ with 143 data corresponding to 13 data sets and ‘cell- and tissue-type’ comprising of 38 microarray data. In addition to the interface for retrieving expression information of a gene/genes in each data set, we have incorporated an interface for a global approach in searching an overall view of the gene expression profiles from multiple data sets within each category. Furthermore, we have also added a BLAST search function that enables users to explore expression profile of a gene/genes with similarity to a query sequence. Therefore, the updated version of RiceXPro can be used more efficiently to survey the gene expression signature of rice in sufficient depth and may also provide clues on gene function of other cereal crops.

Comparison off genetic distance and order off DNA markers in five populations of rice

A group of about 300 evenly distributed DNA markers from a high density RFLP linkage map of rice constructed using an F2 population derived from a japonica variety, Nipponbare, and an indica variety, Kasalath, were used to evaluate gene order and genetic distance in four other rice mapping populations. The purpose of this study was to determine the degree to which information gained from the high density linkage map could be applied to other mapping populations, particularly with regard to its utility in bridging quantitative traits and molecular and physical mapping information. The mapping populations consisted of two F2 populations derived from Dao Ren Qiao/Fl-1084 and Kinandangputi/Fl-1007, recombinant inbred lines from Asominori/IR24, and a backcross population from Sasanishiki/Habataki//Sasanishiki. All DNA markers commonly mapped in the four populations showed the same linkage groups as in the Nipponbare/Kasalath linkage map with conserved linkage order. The genetic distance between markers among the different populations did not vary to a significant level in any of the 12 chromosomes. The differences in some markers could be attributed to the size of the population used in the construction of the linkage maps. Furthermore, the conservation of linkage order found in the distal region of chromosomes 11 and 12 was also confirmed in the RFLP maps based on the four populations of rice. These suggest that any major genetic information from the Nipponbare/Kasalath map can be expected to be approximately the same in other crosses or populations. This high density RFLP linkage map, which is being utilized in constructing a physical map of rice, can be very useful in interpreting genome structure with great accuracy in other populations. Key words : linkage map, japonica, indica, gene order, genetic distance.

Genome-wide transcriptome dissection of the rice root system: implications for developmental and physiological functions

The root system is a crucial determinant of plant growth potential because of its important functions, e.g. uptake of water and nutrients, structural support and interaction with symbiotic organisms. Elucidating the molecular mechanism of root development and functions is therefore necessary for improving plant productivity, particularly for crop plants, including rice (Oryza sativa). As an initial step towards developing a comprehensive understanding of the root system, we performed a large-scale transcriptome analysis of the rice root via a combined laser microdissection and microarray approach. The crown root was divided into eight developmental stages along the longitudinal axis and three radial tissue types at two different developmental stages, namely: epidermis, exodermis and sclerenchyma; cortex; and endodermis, pericycle and stele. We analyzed a total of 38 microarray data and identified 22,297 genes corresponding to 17,010 loci that showed sufficient signal intensity as well as developmental- and tissue type-specific transcriptome signatures. Moreover, we clarified gene networks associated with root cap function and lateral root formation, and further revealed antagonistic and synergistic interactions of phytohormones such as auxin, cytokinin, brassinosteroids and ethylene, based on the expression pattern of genes related to phytohormone biosynthesis and signaling. Expression profiling of transporter genes defined not only major sites for uptake and transport of water and nutrients, but also distinct signatures of the radial transport system from the rhizosphere to the xylem vessel for each nutrient. All data can be accessed from our gene expression profile database, RiceXPro (http://ricexpro.dna.affrc.go.jp), thereby providing useful information for understanding the molecular mechanisms involved in root system development of crop plants.

Rice TOGO Browser: A platform to retrieve integrated information on rice functional and applied genomics

The Rice TOGO Browser is an online public resource designed to facilitate integration and visualization of mapping data of bacterial artificial chromosome (BAC)/P1-derived artificial chromosome (PAC) clones, genes, restriction fragment length polymorphism (RFLP)/simple sequence repeat (SSR) markers and phenotype data represented as quantitative trait loci (QTLs) onto the genome sequence, and to provide a platform for more efficient utilization of genome information from the point of view of applied genomics as well as functional genomics. Three search options, namely keyword search, region search and trait search, generate various types of data in a user-friendly interface with three distinct viewers, a chromosome viewer, an integrated map viewer and a sequence viewer, thereby providing the opportunity to view the position of genes and/or QTLs at the chromosomal level and to retrieve any sequence information in a user-defined genome region. Furthermore, the gene list, marker list and genome sequence in a specified region delineated by RFLP/SSR markers and any sequences designed as primers can be viewed and downloaded to support forward genetics approaches. An additional feature of this database is the graphical viewer for BLAST search to reveal information not only for regions with significant sequence similarity but also for regions adjacent to those with similarity but with no hits between sequences. An easy to use and intuitive user interface can help a wide range of users in retrieving integrated mapping information including agronomically important traits on the rice genome sequence. The database can be accessed at http://agri-trait.dna.affrc.go.jp/.

RiceXPro: a platform for monitoring gene expression in japonica rice grown under natural field conditions

Elucidating the function of all predicted genes in rice remains as the ultimate goal in cereal genomics in order to ensure the development of improved varieties that will sustain an expanding world population. We constructed a gene expression database (RiceXPro, URL: http://ricexpro.dna.affrc.go.jp/) to provide an overview of the transcriptional changes throughout the growth of the rice plant in the field. RiceXPro contains two data sets corresponding to spatiotemporal gene expression profiles of various organs and tissues, and continuous gene expression profiles of leaf from transplanting to harvesting. A user-friendly web interface enables the extraction of specific gene expression profiles by keyword and chromosome search, and basic data analysis, thereby providing useful information as to the organ/tissue and developmental stage specificity of expression of a particular gene. Analysis tools such as t-test, calculation of fold change and degree of correlation facilitate the comparison of expression profiles between two random samples and the prediction of function of uncharacterized genes. As a repository of expression data encompassing growth in the field, this database can provide baseline information of genes that underlie various agronomically important traits in rice.

The Rice Annotation Project Database (RAP-DB): 2008 update

The Rice Annotation Project Database (RAP-DB) was created to provide the genome sequence assembly of the International Rice Genome Sequencing Project (IRGSP), manually curated annotation of the sequence, and other genomics information that could be useful for comprehensive understanding of the rice biology. Since the last publication of the RAP-DB, the IRGSP genome has been revised and reassembled. In addition, a large number of rice-expressed sequence tags have been released, and functional genomics resources have been produced worldwide. Thus, we have thoroughly updated our genome annotation by manual curation of all the functional descriptions of rice genes. The latest version of the RAP-DB contains a variety of annotation data as follows: clone positions, structures and functions of 31 439 genes validated by cDNAs, RNA genes detected by massively parallel signature sequencing (MPSS) technology and sequence similarity, flanking sequences of mutant lines, transposable elements, etc. Other annotation data such as Gnomon can be displayed along with those of RAP for comparison. We have also developed a new keyword search system to allow the user to access useful information. The RAP-DB is available at: http://rapdb.dna.affrc.go.jp/ and http://rapdb.lab.nig.ac.jp/.

Curated genome annotation of Oryza sativa ssp. japonica and comparative genome analysis with Arabidopsis thaliana

We present here the annotation of the complete genome of rice Oryza sativa L. ssp. japonica cultivar Nipponbare. All functional annotations for proteins and non-protein-coding RNA (npRNA) candidates were manually curated. Functions were identified or inferred in 19,969 (70%) of the proteins, and 131 possible npRNAs (including 58 antisense transcripts) were found. Almost 5000 annotated protein-coding genes were found to be disrupted in insertional mutant lines, which will accelerate future experimental validation of the annotations. The rice loci were determined by using cDNA sequences obtained from rice and other representative cereals. Our conservative estimate based on these loci and an extrapolation suggested that the gene number of rice is approximately 32,000, which is smaller than previous estimates. We conducted comparative analyses between rice and Arabidopsis thaliana and found that both genomes possessed several lineage-specific genes, which might account for the observed differences between these species, while they had similar sets of predicted functional domains among the protein sequences. A system to control translational efficiency seems to be conserved across large evolutionary distances. Moreover, the evolutionary process of protein-coding genes was examined. Our results suggest that natural selection may have played a role for duplicated genes in both species, so that duplication was suppressed or favored in a manner that depended on the function of a gene.

The Rice Annotation Project Database (RAP-DB): hub for Oryza sativa ssp. japonica genome information

With the completion of the rice genome sequencing, a standardized annotation is necessary so that the information from the genome sequence can be fully utilized in understanding the biology of rice and other cereal crops. An annotation jamboree was held in Japan with the aim of annotating and manually curating all the genes in the rice genome. Here we present the Rice Annotation Project Database (RAP-DB), which has been developed to provide access to the annotation data. The RAP-DB has two different types of annotation viewers, BLAST and BLAT search, and other useful features. By connecting the annotations to other rice genomics data, such as full-length cDNAs and Tos17 mutant lines, the RAP-DB serves as a hub for rice genomics. All of the resources can be accessed through .

Rice Annotation Database (RAD): a contig-oriented database for map-based rice genomics

A contig-oriented database for annotation of the rice genome has been constructed to facilitate map-based rice genomics. The Rice Annotation Database has the following functional features: (i) extensive effort of manual annotations of P1-derived artificial chromosome/bacterial artificial chromosome clones can be merged at chromosome and contig-level; (ii) concise visualization of the annotation information such as the predicted genes, results of various prediction programs (RiceHMM, Genscan, Genscan+, Fgenesh, GeneMark, etc.), homology to expressed sequence tag, full-length cDNA and protein; (iii) user-friendly clone / gene query system; (iv) download functions for nucleotide, amino acid and coding sequences; (v) analysis of various features of the genome (GC-content, average value, etc.); and (vi) genome-wide homology search (BLAST) of contig- and chromosome-level genome sequence to allow comparative analysis with the genome sequence of other organisms. As of October 2004, the database contains a total of 215 Mb sequence with relevant annotation results including 30 000 manually curated genes. The database can provide the latest information on manual annotation as well as a comprehensive structural analysis of various features of the rice genome. The database can be accessed at http://rad.dna.affrc.go.jp/.

From mapping to sequencing, post-sequencing and beyond

The Rice Genome Research Program (RGP) in Japan has been collaborating with the international community in elucidating a complete high-quality sequence of the rice genome. As the pioneer in large-scale analysis of the rice genome, the RGP has successfully established the fundamental tools for genome research such as a genetic map, a yeast artificial chromosome (YAC)-based physical map, a transcript map and a phage P1 artificial chromosome (PAC)/bacterial artificial chromosome (BAC) sequence-ready physical map, which serve as common resources for genome sequencing. Among the 12 rice chromosomes, the RGP is in charge of sequencing six chromosomes covering 52% of the 390 Mb total length of the genome. The contribution of the RGP to the realization of decoding the rice genome sequence with high accuracy and deciphering the genetic information in the genome will have a great impact in understanding the biology of the rice plant that provides a major food source for almost half of the world's population. A high-quality draft sequence (phase 2) was completed in December 2002. Since then, much of the finished quality sequence (phase 3) has become available in public databases. With the completion of sequencing in December 2004, it is expected that the genome sequence would facilitate innovative research in functional and applied genomics. A map-based genome sequence is indispensable for further improvement of current rice varieties and for development of novel varieties carrying agronomically important traits such as high yield potential and tolerance to both biotic and abiotic stresses. In addition to genome sequencing, various related projects have been initiated to generate valuable resources, which could serve as indispensable tools in clarifying the structure and function of the rice genome. These resources have been made available to the scientific community through the Rice Genome Resource Center (RGRC) of the National Institute of Agrobiological Sciences (NIAS) to enable rapid progress in research that will lead to thorough understanding of the rice plant. As the next trend in rice genome research will focus on determining the function of about 40,000-50,000 genes predicted in the genome as well as applying various genomics tools in rice breeding, an unlimited access to rice DNA and seed stocks will provide a broad community of scientists with the necessary materials for formulating new concepts, developing innovative research and making new scientific discoveries in rice genomics.

The genome sequence and structure of rice chromosome 1

The rice species Oryza sativa is considered to be a model plant because of its small genome size, extensive genetic map, relative ease of transformation and synteny with other cereal crops. Here we report the essentially complete sequence of chromosome 1, the longest chromosome in the rice genome. We summarize characteristics of the chromosome structure and the biological insight gained from the sequence. The analysis of 43.3 megabases (Mb) of non-overlapping sequence reveals 6,756 protein coding genes, of which 3,161 show homology to proteins of Arabidopsis thaliana, another model plant. About 30% (2,073) of the genes have been functionally categorized. Rice chromosome 1 is (G + C)-rich, especially in its coding regions, and is characterized by several gene families that are dispersed or arranged in tandem repeats. Comparison with a draft sequence indicates the importance of a high-quality finished sequence.

The genome sequence and structure of rice chromosome 1

The rice species Oryza sativa is considered to be a model plant because of its small genome size, extensive genetic map, relative ease of transformation and synteny with other cereal crops. Here we report the essentially complete sequence of chromosome 1, the longest chromosome in the rice genome. We summarize characteristics of the chromosome structure and the biological insight gained from the sequence. The analysis of 43.3 megabases (Mb) of non-overlapping sequence reveals 6,756 protein coding genes, of which 3,161 show homology to proteins of Arabidopsis thaliana, another model plant. About 30% (2,073) of the genes have been functionally categorized. Rice chromosome 1 is (G + C)-rich, especially in its coding regions, and is characterized by several gene families that are dispersed or arranged in tandem repeats. Comparison with a draft sequence indicates the importance of a high-quality finished sequence.

Rice at the forefront of plant genome informatics

As rice genomicsdata continue to accumulate at a rapid rate, are becoming more valuable to warehouse and access large and rigorous data sets. This article gives an overview of available resources on rice bioinformatics and their role in elucidating and propagating biological and genomic information in rice. Of particular focus here is the informatics infrastructure developed at the Rice Genome Research Program (RGP) following an extensive rice genome analysis. The database named INE (Integrated Rice Genome Explorer) integrates the genetic and physical mapping information with the genome sequence being generated in collaboration with the International Rice Genome Sequencing Project (IRGSP). Database links are initially evaluated using an interoperable query tool to explore and compare data across the rice and maize genome databases and potential application to multiple crop database querying. A proposed logistics for interlinking these resources is presented to integrate, manipulate and analyze information on the rice genome. One of the biggest challenges of rice bioinformatics lies in the emerging role of rice as a model system among grass crop species. In view of the importance of comparative genetics in the formulation of new knowledge on plant genomes and genes, comparative bioinformatics remains an essential strategy to gain new insights on the needs and expectations on rice genomics.

RiceGAAS: an automated annotation system and database for rice genome sequence

An extensive effort of the International Rice Genome Sequencing Project (IRGSP) has resulted in rapid accumulation of genome sequence, and >137 Mb has already been made available to the public domain as of August 2001. This requires a high-throughput annotation scheme to extract biologically useful and timely information from the sequence data on a regular basis. A new automated annotation system and database called Rice Genome Automated Annotation System (RiceGAAS) has been developed to execute a reliable and up-to-date analysis of the genome sequence as well as to store and retrieve the results of annotation. The system has the following functional features: (i) collection of rice genome sequences from GenBank; (ii) execution of gene prediction and homology search programs; (iii) integration of results from various analyses and automatic interpretation of coding regions; (iv) re-execution of analysis, integration and automatic interpretation with the latest entries in reference databases; (v) integrated visualization of the stored data using web-based graphical view. RiceGAAS also has a data submission mechanism that allows public users to perform fully automated annotation of their own sequences. The system can be accessed at http://RiceGAAS.dna.affrc.go.jp/.

A physical map with yeast artificial chromosome (YAC) clones covering 63% of the 12 rice chromosomes

A new YAC (yeast artificial chromosome) physical map of the 12 rice chromosomes was constructed utilizing the latest molecular linkage map. The 1439 DNA markers on the rice genetic map selected a total of 1892 YACs from a YAC library. A total of 675 distinct YACs were assigned to specific chromosomal locations. In all chromosomes, 297 YAC contigs and 142 YAC islands were formed. The total physical length of these contigs and islands was estimated to 270 Mb which corresponds to approximately 63% of the entire rice genome (430 Mb). Because the physical length of each YAC contig has been measured, we could then estimate the physical distance between genetic markers more precisely than previously. In the course of constructing the new physical map, the DNA markers mapped at 0.0-cM intervals were ordered accurately and the presence of potentially duplicated regions among the chromosomes was detected. The physical map combined with the genetic map will form the basis for elucidation of the rice genome structure, map-based cloning of agronomically important genes, and genome sequencing.

A physical map with yeast artificial chromosome (YAC) clones covering 63% of the 12 rice chromosomes

A new YAC (yeast artificial chromosome) physical map of the 12 rice chromosomes was constructed utilizing the latest molecular linkage map. The 1439 DNA markers on the rice genetic map selected a total of 1892 YACs from a YAC library. A total of 675 distinct YACs were assigned to specific chromosomal locations. In all chromosomes, 297 YAC contigs and 142 YAC islands were formed. The total physical length of these contigs and islands was estimated to 270 Mb which corresponds to approximately 63% of the entire rice genome (430 Mb). Because the physical length of each YAC contig has been measured, we could then estimate the physical distance between genetic markers more precisely than previously. In the course of constructing the new physical map, the DNA markers mapped at 0.0-cM intervals were ordered accurately and the presence of potentially duplicated regions among the chromosomes was detected. The physical map combined with the genetic map will form the basis for elucidation of the rice genome structure, map-based cloning of agronomically important genes, and genome sequencing.Key words: physical mapping, YAC contig, rice genome, rice chromosomes.

INE: a rice genome database with an integrated map view

The Rice Genome Research Program (RGP) launched a large-scale rice genome sequencing in 1998 aimed at decoding all genetic information in rice. A new genome database called INE (INtegrated rice genome Explorer) has been developed in order to integrate all the genomic information that has been accumulated so far and to correlate these data with the genome sequence. A web interface based on Java applet provides a rapid viewing capability in the database. The first operational version of the database has been completed which includes a genetic map, a physical map using YAC (Yeast Artificial Chromosome) clones and PAC (P1-derived Artificial Chromosome) contigs. These maps are displayed graphically so that the positional relationships among the mapped markers on each chromosome can be easily resolved. INE incorporates the sequences and annotations of the PAC contig. A site on low quality information ensures that all submitted sequence data comply with the standard for accuracy. As a repository of rice genome sequence, INE will also serve as a common database of all sequence data obtained by collaborating members of the International Rice Genome Sequencing Project (IRGSP). The database can be accessed at http://www. dna.affrc.go.jp:82/giot/INE. html or its mirror site at http://www.staff.or.jp/giot/INE.html

A high-density rice genetic linkage map with 2275 markers using a single F2 population

A 2275-marker genetic map of rice (Oryza sativa L.) covering 1521.6 cM in the Kosambi function has been constructed using 186 F2 plants from a single cross between the japonica variety Nipponbare and the indica variety Kasalath. The map provides the most detailed and informative genetic map of any plant. Centromere locations on 12 linkage groups were determined by dosage analysis of secondary and telotrisomics using > 130 DNA markers located on respective chromosome arms. A limited influence on meiotic recombination inhibition by the centromere in the genetic map was discussed. The main sources of the markers in this map were expressed sequence tag (EST) clones from Nipponbare callus, root, and shoot libraries. We mapped 1455 loci using ESTs; 615 of these loci showed significant similarities to known genes, including single-copy genes, family genes, and isozyme genes. The high-resolution genetic map permitted us to characterize meiotic recombinations in the whole genome. Positive interference of meiotic recombination was detected both by the distribution of recombination number per each chromosome and by the distribution of double crossover interval lengths.

Rice molecular genetic map using RFLPs and its applications

In the past decade, notable progress has been made in rice molecular genetic mapping using genomic or cDNA clones. A total of over 3000 DNA markers, mainly with RFLPs, have been mapped on the rice genome. In addition, many studies related to tagging of genes of interest, gene isolation by map-based cloning and comparative mapping between cereal genomes have advanced along with the development of a high-density molecular genetic map. Thus rice is considered a pivotal plant among cereal crops and, in addition to Arabidopsis, is a model plant in genome analysis. In this article, the current status of the construction of rice molecular genetic maps and their applications are reviewed.

Physical mapping of rice chromosomes 8 and 9 with YAC clones

First efforts for physical mapping of rice chromosomes 8 and 9 were carried out by ordering YAC clones of a rice genomic DNA library covering six genome equivalents with mapped DNA markers. A total of 79 and 74 markers from chromosomes 8 and 9, respectively, were analyzed by YAC colony and Southern hybridization using RFLP markers of cDNA and genomic clones, and by polymerase chain reaction (PCR) screening using PCR-derived and sequence-tagged site (STS) markers. As a result, 252 YAC clones were confirmed to contain the mapped DNA fragments on both chromosomes. A contig map was constructed by ordering these YAC clones and about 53% and 43% genome coverage was obtained for chromosomes 8 and 9, respectively, assuming a YAC clone size of 350 kb and overlap between neighboring YACs of 50%. A continuous array of YAC clones with minimum overlap gave a total size of 18.9 Mb for chromosome 8 and 15.6 Mb for chromosome 9, which are close to previous estimates. These contig maps may provide valuable information that can be useful in understanding chromosome structure and isolating specific genes by map-based cloning.

A 300 kilobase interval genetic map of rice including 883 expressed sequences

We have constructed a high resolution rice genetic map containing 1,383 DNA markers at an average interval of 300 kilobases (kb). The markers, distributed along 1,575 cM on 12 linkage groups, comprise 883 cDNAs, 265 genomic DNAs, 147 randomly amplified polymorphic DNAs (RAPD) and 88 other DNAs. cDNAs were derived from rice root and callus, analysed by single-run sequencing and searched for similarities with known proteins. Nearly 260 rice genes are newly identified and mapped, and genomic DNA and cloned RAPD fragments were also sequenced to generate STSs. Our map is the first significant gene expression map in plants. It is also the densest genetic map available in plants and the first to be backed up comprehensively by clone sequence data.