Gramene,a tool for grass genomics

Gramene (http://www.gramene.org) is a comparative genome mapping database for grasses and a community resource for rice (Oryza sativa). It combines a semi-automatically generated database of cereal genomic and expressed sequence tag sequences, genetic maps, map relations, and publications, with a curated database of rice mutants (genes and alleles), molecular markers, and proteins. Gramene curators read and extract detailed information from published sources, summarize that information in a structured format, and establish links to related objects both inside and outside the database, providing seamless connections between independent sources of information. Genetic, physical, and sequence-based maps of rice serve as the fundamental organizing units and provide a common denominator for moving across species and genera within the grass family. Comparative maps of rice, maize (Zea mays), sorghum (Sorghum bicolor), barley (Hordeum vulgare), wheat (Triticum aestivum), and oat (Avena sativa) are anchored by a set of curated correspondences. In addition to sequence-based mappings found in comparative maps and rice genome displays, Gramene makes extensive use of controlled vocabularies to describe specific biological attributes in ways that permit users to query those domains and make comparisons across taxonomic groups. Proteins are annotated for functional significance using gene ontology terms that have been adopted by numerous model species databases. Genetic variants including phenotypes are annotated using plant ontology terms common to all plants and trait ontology terms that are specific to rice. In this paper, we present a brief overview of the search tools available to the plant research community in Gramene.     

An integrated physical and genetic map of the rice genome

Rice was chosen as a model organism for genome sequencing because of its economic importance, small genome size, and syntenic relationship with other cereal species. We have constructed a bacterial artificial chromosome fingerprint–based physical map of the rice genome to facilitate the whole-genome sequencing of rice. Most of the rice genome (~90.6%) was anchored genetically by overgo hybridization, DNA gel blot hybridization, and in silico anchoring. Genome sequencing data also were integrated into the rice physical map. Comparison of the genetic and physical maps reveals that recombination is suppressed severely in centromeric regions as well as on the short arms of chromosomes 4 and 10. This integrated high-resolution physical map of the rice genome will greatly facilitate whole-genome sequencing by helping to identify a minimum tiling path of clones to sequence. Furthermore, the physical map will aid map-based cloning of agronomically important genes and will provide an important tool for the comparative analysis of grass genomes.     

The Physical and Genetic Framework of the Maize B73 Genome

Maize is a major cereal crop and an important model system for basic biological research. Knowledge gained from maize research can also be used to genetically improve its grass relatives such as sorghum, wheat, and rice. The primary objective of the Maize Genome Sequencing Consortium (MGSC) was to generate a reference genome sequence that was integrated with both the physical and genetic maps. Using a previously published integrated genetic and physical map, combined with in-coming maize genomic sequence, new sequence-based genetic markers, and an optical map, we dynamically picked a minimum tiling path (MTP) of 16,910 bacterial artificial chromosome (BAC) and fosmid clones that were used by the MGSC to sequence the maize genome. The final MTP resulted in a significantly improved physical map that reduced the number of contigs from 721 to 435, incorporated a total of 8,315 mapped markers, and ordered and oriented the majority of FPC contigs. The new integrated physical and genetic map covered 2,120 Mb (93%) of the 2,300-Mb genome, of which 405 contigs were anchored to the genetic map, totaling 2,103.4 Mb (99.2% of the 2,120 Mb physical map). More importantly, 336 contigs, comprising 94.0% of the physical map (∼1,993 Mb), were ordered and oriented. Finally we used all available physical, sequence, genetic, and optical data to generate a golden path (AGP) of chromosome-based pseudomolecules, herein referred to as the B73 Reference Genome Sequence version 1 (B73 RefGen_v1).     

Gramene: development and integration of trait and gene ontologies for rice

Gramene (http://www.gramene.org/) is a comparative genome database for cereal crops and a community resource for rice. We are populating and curating Gramene with annotated rice (Oryza sativa) genomic sequence data and associated biological information including molecular markers, mutants, phenotypes, polymorphisms and Quantitative Trait Loci (QTL). In order to support queries across various data sets as well as across external databases, Gramene will employ three related controlled vocabularies. The specific goal of Gramene is, first to provide a Trait Ontology (TO) that can be used across the cereal crops to facilitate phenotypic comparisons both within and between the genera. Second, a vocabulary for plant anatomy terms, the Plant Ontology (PO) will facilitate the curation of morphological and anatomical feature information with respect to expression, localization of genes and gene products and the affected plant parts in a phenotype. The TO and PO are both in the early stages of development in collaboration with the International Rice Research Institute, TAIR and MaizeDB as part of the Plant Ontology Consortium. Finally, as part of another consortium comprising macromolecular databases from other model organisms, the Gene Ontology Consortium, we are annotating the confirmed and predicted protein entries from rice using both electronic and manual curation.     

A universal core genetic map for rice

To facilitate the creation of easily comparable, low-resolution genetic maps with evenly distributed markers in rice (Oryza sativa L.), we conceived of and developed a Universal Core Genetic Map (UCGM). With this aim, we derived a set of 165 anchors, representing clusters of three microsatellite or simple sequence repeat (SSR) markers arranged into non-recombining groups. Each anchor consists of at least three, closely linked SSRs, located within a distance below the genetic resolution provided by common, segregating populations (<500 individuals). We chose anchors that were evenly distributed across the rice chromosomes, with spacing between 2 and 3.5 Mbp (except in the telomeric regions, where spacing was 1.5 Mbp). Anchor selection was performed using in silico tools and data: the O. sativa cv. Nipponbare rice genome sequence, the CHARM tool, information from the Gramene database and the OrygenesDB database. Sixteen AA-genome accessions of the Oryza genus were used to evaluate polymorphisms for the selected markers, including accessions from O. sativa, O. glaberrima, O. barthii, O. rufipogon, O. glumaepatula and O. meridionalis. High levels of polymorphism were found for the tested O. sativa × O. glaberrima or O. sativa × wild rice combinations. We developed Paddy Map, a simple database that is helpful in selecting optimal sets of polymorphic SSRs for any cross that involves the previously mentioned species. Validation of the UCGM was done by using it to develop three interspecific genetic maps and by comparing genetic SSR locations with their physical positions on the rice pseudomolecules. In this study, we demonstrate that the UCGM is a useful tool for the rice genetics and breeding community, especially in strategies based on interspecific hybridisation.     

Development of Gene-Based SSR Markers in Rice Bean (Vigna umbellata L.) Based on Transcriptome Data

Rice bean (Vigna umbellata (Thunb.) Ohwi & Ohashi) is a warm season annual legume mainly grown in East Asia. Only scarce genomic resources are currently available for this legume crop species and no simple sequence repeat (SSR) markers have been specifically developed for rice bean yet. In this study, approximately 26 million high quality cDNA sequence reads were obtained from rice bean using Illumina paired-end sequencing technology and assembled into 71,929 unigenes with an average length of 986 bp. Of these unigenes, 38,840 (33.2%) showed significant similarity to proteins in the NCBI non-redundant protein and nucleotide sequence databases. Furthermore, 30,170 (76.3%) could be classified into gene ontology categories, 25,451 (64.4%) into Swiss-Prot categories and 21,982 (55.6%) into KOG database categories (E-value < 1.0E-5). A total of 9,301 (23.5%) were mapped onto 118 pathways using the Kyoto Encyclopedia of Genes and Genome (KEGG) pathway database. A total of 3,011 genic SSRs were identified as potential molecular markers. AG/CT (30.3%), AAG/CTT (8.1%) and AGAA/TTCT (20.0%) are the three main repeat motifs. A total of 300 SSR loci were randomly selected for validation by using PCR amplification. Of these loci, 23 primer pairs were polymorphic among 32 rice bean accessions. A UPGMA dendrogram revealed three major clusters among 32 rice bean accessions. The large number of SSR-containing sequences and genic SSRs in this study will be valuable for the construction of high-resolution genetic linkage maps, association or comparative mapping and genetic analyses of various Vigna species.     

Anchoring of rice BAC clones to the rice genetic map in silico

A wealth of molecular resources have been developed for rice genomics, including dense genetic maps, expressed sequence tags (ESTs), yeast artificial chromosome maps, bacterial artificial chromosome (BAC) libraries and BAC end sequence databases. Integration of genetic and physical maps involves labor-intensive empirical experiments. To accelerate the integration of the bacterial clone resources with the genetic map for the International Rice Genome Sequencing Project, we cleaned and filtered the available EST and BAC end sequences for repetitive sequences and then searched all available rice genetic markers with our filtered databases. We identified 418 genetic markers that aligned with at least one BAC end sequence with >95% sequence identity, providing a set of large insert clones with an average separation of 1 Mb that can serve as nucleation points for the sequencing phase of the International Rice Genome Sequencing Project.     

Colinearity and gene density in grass genomes

Grasses are the single most important plant family in agriculture. In the past years, comparative genetic mapping has revealed conserved gene order (colinearity) among many grass species. Recently, the first studies at gene level have demonstrated that microcolinearity of genes is less conserved: small scale rearrangements and deletions complicate the microcolinearity between closely related species, such as sorghum and maize, but also between rice and other crop plants. In spite of these problems, rice remains the model plant for grasses as there is limited useful colinearity between Arabidopsis and grasses. However, studies in rice have to be complemented by more intensive genetic work on grass species with large genomes (maize, Triticeae). Gene-rich chromosomal regions in species with large genomes, such as wheat, have a high gene density and are ideal targets for partial genome sequencing.     

An integrated physical, genetic and cytogenetic map of Brachypodium distachyon, a model system for grass research

The pooid subfamily of grasses includes some of the most important crop, forage and turf species, such as wheat, barley and Lolium. Developing genomic resources, such as whole-genome physical maps, for analysing the large and complex genomes of these crops and for facilitating biological research in grasses is an important goal in plant biology. We describe a bacterial artificial chromosome (BAC)-based physical map of the wild pooid grass Brachypodium distachyon and integrate this with whole genome shotgun sequence (WGS) assemblies using BAC end sequences (BES). The resulting physical map contains 26 contigs spanning the 272 Mb genome. BES from the physical map were also used to integrate a genetic map. This provides an independent validation and confirmation of the published WGS assembly. Mapped BACs were used in Fluorescence In Situ Hybridisation (FISH) experiments to align the integrated physical map and sequence assemblies to chromosomes with high resolution. The physical, genetic and cytogenetic maps, integrated with whole genome shotgun sequence assemblies, enhance the accuracy and durability of this important genome sequence and will directly facilitate gene isolation.     

How Can We Use Genomics to Improve Cereals with Rice as a Reference Genome?

Rice serves as a model crop for cereal genomics. The availability of complete genome sequences, together with various genomic resources available for both rice and Arabidopsis, have revolutionized our understanding of the genetic make-up of crop plants. Both macrocolinearity revealed by comparative mapping and microcolinearity revealed by sequence comparisons among the grasses indicate that sequencing and functional analysis of the rice genome will have a significant impact on other cereals in terms of both genomic studies and crop improvement. The availability of mutants, introgression libraries, and advanced transformation techniques make functional genomics in rice and other cereals more manageable than ever before. A wide array of genetic markers, including anchor markers for comparative mapping, SSRs and SNPs are widely used in genetic mapping, germplasm evaluation and marker assisted selection. An integrated database that combines genome information for rice and other cereals is key to the effective utilization of all genomics resources for cereal improvement. To maximize the potential of genomics for plant breeding, experiments must be further miniaturized and costs must be reduced. Many techniques, including targeted gene disruption or allele substitution, insertional mutagenesis, RNA interference and homologous recombination, need to be refined before they can be widely used in functional genomic analysis and plant breeding.     

One large-insert plant-transformation-competent BIBAC library and three BAC libraries of Japonica rice for genome research in rice and other grasses

We report one large-insert BIBAC library and three BAC libraries for japonica rice cv Nipponbare. The BIBAC library was constructed in the HindIII site of a plant-transformation-competent binary vector (pCLD04541) and the three BAC libraries were constructed in the BamHI, HindIII and EcoRI sites of a BAC vector (pECBAC1), respectively. Each library contains 23,040 clones, has an average insert size of 130 kb, 170 kb, 150 kb and 156 kb, and covers 6.7x, 8.7x, 7.7x and 8.0 x rice haploid genomes, respectively. The combined libraries contain 92,160 clones in total, covering 31.1 x rice haploid genomes. To demonstrate their utility, we screened the libraries with 55 DNA markers mapped to chromosome 8 of the rice genetic maps and analyzed a number of clones by the restriction fingerprinting and contig assembly method. The results indicate that the libraries completely cover the rice genome and, thus, are well-suited for genome research in rice and other gramineous crops. The BIBAC library represents the first plant-transformation-competent large-insert DNA library for rice, which will streamline map-based cloning, functional analysis of the rice genome sequence and molecular breeding in rice and other grass species. These libraries are being used in the development of a whole-genome, BAC/BIBAC-based, integrated physical, genetic and sequence map of rice and in the research of genome-wide comparative genomics of grass species.     

The International Rice Information System. A platform for meta-analysis of rice crop data

Ambiguous germplasm identification; difficulty in tracing pedigree information; and lack of integration between genetic resources, characterization, breeding, evaluation, and utilization data are constraints in developing knowledge-intensive crop improvement programs. To address these constraints, the International Crop Information System (www.icis.cgiar.org), a database system for the management and integration of global information on genetic resources and crop improvement for any crop, was developed by genetic resource specialists, crop scientists, and information technicians associated with the Consultative Group for International Agricultural Research and collaborative partners. The International Rice Information System (www.iris.irri.org) is the rice (Oryza species) implementation of the International Crop Information System. New components are now being added to the International Rice Information System to handle the diversity of rice functional genomics data including genomic sequence data, molecular genetic data, expression data, and proteomic information. Users access information in the database through stand-alone programs and Web interfaces, which offer specialized applications and customized views to researchers with different interests.     

WheatGenome.info: an integrated database and portal for wheat genome information

Bread wheat (Triticum aestivum) is one of the most important crop plants, globally providing staple food for a large proportion of the human population. However, improvement of this crop has been limited due to its large and complex genome. Advances in genomics are supporting wheat crop improvement. We provide a variety of web-based systems hosting wheat genome and genomic data to support wheat research and crop improvement. WheatGenome.info is an integrated database resource which includes multiple web-based applications. These include a GBrowse2-based wheat genome viewer with BLAST search portal, TAGdb for searching wheat second-generation genome sequence data, wheat autoSNPdb, links to wheat genetic maps using CMap and CMap3D, and a wheat genome Wiki to allow interaction between diverse wheat genome sequencing activities. This system includes links to a variety of wheat genome resources hosted at other research organizations. This integrated database aims to accelerate wheat genome research and is freely accessible via the web interface at http://www.wheatgenome.info/.     

GrainGenes 2.0. an improved resource for the small-grains community

GrainGenes (http://wheat.pw.usda.gov) is an international database for genetic and genomic information about Triticeae species (wheat [Triticum aestivum], barley [Hordeum vulgare], rye [Secale cereale], and their wild relatives) and oat (Avena sativa) and its wild relatives. A major strength of the GrainGenes project is the interaction of the curators with database users in the research community, placing GrainGenes as both a data repository and information hub. The primary intensively curated data classes are genetic and physical maps, probes used for mapping, classical genes, quantitative trait loci, and contact information for Triticeae and oat scientists. Curation of these classes involves important contributions from the GrainGenes community, both as primary data sources and reviewers of published data. Other partially automated data classes include literature references, sequences, and links to other databases. Beyond the GrainGenes database per se, the Web site incorporates other more specific databases, informational topics, and downloadable files. For example, unique BLAST datasets of sequences applicable to Triticeae research include mapped wheat expressed sequence tags, expressed sequence tag-derived simple sequence repeats, and repetitive sequences. In 2004, the GrainGenes project migrated from the AceDB database and separate Web site to an integrated relational database and Internet resource, a major step forward in database delivery. The process of this migration and its impacts on database curation and maintenance are described, and a perspective on how a genomic database can expedite research and crop improvement is provided.     

QTL mapping in rice

In the past 10 years, interest in applying the tools of molecular genetics to the problem of increasing world rice production has resulted in the generation of two highly saturated, molecular linkage maps of rice, and the localization of numerous genes and quantitative trait loci (QTLs). Primary studies have identified QTLs associated with disease resistance, abiotic stress tolerance and yield potential of rice in a range of ecosystems. The ability to identify, manipulate and potentially clone individual genes involved in quantitatively inherited characters, combined with the demonstrated conservation of numerous linkage blocks among members of the grass family, emphasizes the contribution of map-based genetic analyses both to applied and to basic crop research.     

Evidence and evolutionary analysis of ancient whole-genome duplication in barley predating the divergence from rice

Background  

Well preserved genomic colinearity among agronomically important grass species such as rice, maize, Sorghum, wheat and barley provides access to whole-genome structure information even in species lacking a reference genome sequence. We investigated footprints of whole-genome duplication (WGD) in barley that shaped the cereal ancestor genome by analyzing shared synteny with rice using a ~2000 gene-based barley genetic map and the rice genome reference sequence.     

Anchor probes for comparative mapping of grass genera

 Comparative mapping of cDNA clones provides an important foundation for examining structural conservation among the chromosomes of diverse genera and for establishing hypotheses about the relationship between gene structure and function in a wide range of organisms. In this study, “anchor probes” were selected from cDNA libraries developed from rice, oat, and barley that were informative for comparative mapping in the grass family. One thousand eight hundred probes were screened on garden blots containing DNA of rice, maize, sorghum, sugarcane, wheat, barley, and oat, and 152 of them were selected as “anchors” because (1) they hybridized to the majority of target grass species based on Southern analysis, (2) they appeared to be low or single copy in rice, and (3) they helped provide reasonably good genome coverage in all species. Probes were screened for polymorphism on mapping parents, and polymorphic markers were mapped onto existing species-specific linkage maps of rice, oat, maize, and wheat. In wheat, both polymorphic and monomorphic markers could be assigned to chromosomes or chromosome arms based on hybridization to nullitetrasomic and ditelosomic stocks. Linkage among anchored loci allowed the identification of homoeologous regions of these distantly related genomes. Anchor probes were sequenced from both ends, providing an average of 260 bp in each direction, and sequences were deposited in GenBank. BLAST was used to compare the sequences with each other and with a non-redundant protein sequence database maintained at the European Molecular Biology Laboratory (EMBL). Of the anchor probes identified in this study 78% showed significant similarity to protein sequences for known genes with BLASTX scores exceeding 100. Received: 27 June 1997 / Accepted: 17 July 1997     

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     

Transcriptome Sequencing of Mung Bean (Vigna radiate L.) Genes and the Identification of EST-SSR Markers

Mung bean (Vigna radiate (L.) Wilczek) is an important traditional food legume crop, with high economic and nutritional value. It is widely grown in China and other Asian countries. Despite its importance, genomic information is currently unavailable for this crop plant species or some of its close relatives in the Vigna genus. In this study, more than 103 million high quality cDNA sequence reads were obtained from mung bean using Illumina paired-end sequencing technology. The processed reads were assembled into 48,693 unigenes with an average length of 874 bp. Of these unigenes, 25,820 (53.0%) and 23,235 (47.7%) showed significant similarity to proteins in the NCBI non-redundant protein and nucleotide sequence databases, respectively. Furthermore, 19,242 (39.5%) could be classified into gene ontology categories, 18,316 (37.6%) into Swiss-Prot categories and 10,918 (22.4%) into KOG database categories (E-value < 1.0E-5). A total of 6,585 (8.3%) were mapped onto 244 pathways using the Kyoto Encyclopedia of Genes and Genome (KEGG) pathway database. Among the unigenes, 10,053 sequences contained a unique simple sequence repeat (SSR), and 2,303 sequences contained more than one SSR together in the same expressed sequence tag (EST). A total of 13,134 EST-SSRs were identified as potential molecular markers, with mono-nucleotide A/T repeats being the most abundant motif class and G/C repeats being rare. In this SSR analysis, we found five main repeat motifs: AG/CT (30.8%), GAA/TTC (12.6%), AAAT/ATTT (6.8%), AAAAT/ATTTT (6.2%) and AAAAAT/ATTTTT (1.9%). A total of 200 SSR loci were randomly selected for validation by PCR amplification as EST-SSR markers. Of these, 66 marker primer pairs produced reproducible amplicons that were polymorphic among 31 mung bean accessions selected from diverse geographical locations. The large number of SSR-containing sequences found in this study will be valuable for the construction of a high-resolution genetic linkage maps, association or comparative mapping and genetic analyses of various Vigna species.