BackgroundRice research has been enabled by access to the high quality reference genome sequence generated in 2005 by the International Rice Genome Sequencing Project (IRGSP). To further facilitate genomic-enabled research, we have updated and validated the genome assembly and sequence for the Nipponbare cultivar of Oryza sativa (japonica group).ResultsThe Nipponbare genome assembly was updated by revising and validating the minimal tiling path of clones with the optical map for rice. Sequencing errors in the revised genome assembly were identified by re-sequencing the genome of two different Nipponbare individuals using the Illumina Genome Analyzer II/IIx platform. A total of 4,886 sequencing errors were identified in 321 Mb of the assembled genome indicating an error rate in the original IRGSP assembly of only 0.15 per 10,000 nucleotides. A small number (five) of insertions/deletions were identified using longer reads generated using the Roche 454 pyrosequencing platform. As the re-sequencing data were generated from two different individuals, we were able to identify a number of allelic differences between the original individual used in the IRGSP effort and the two individuals used in the re-sequencing effort. The revised assembly, termed Os-Nipponbare-Reference-IRGSP-1.0, is now being used in updated releases of the Rice Annotation Project and the Michigan State University Rice Genome Annotation Project, thereby providing a unified set of pseudomolecules for the rice community.ConclusionsA revised, error-corrected, and validated assembly of the Nipponbare cultivar of rice was generated using optical map data, re-sequencing data, and manual curation that will facilitate on-going and future research in rice. Detection of polymorphisms between three different Nipponbare individuals highlights that allelic differences between individuals should be considered in diversity studies.Electronic supplementary materialThe online version of this article (doi:10.1186/1939-8433-6-4) contains supplementary material, which is available to authorized users.

In The Institute for Genomic Research Rice Genome Annotation project (), we have continued to update the rice genome sequence with new data and improve the quality of the annotation. In our current release of annotation (Release 4.0; January 12, 2006), we have identified 42 653 non-transposable element-related genes encoding 49 472 gene models as a result of the detection of alternative splicing. We have refined our identification methods for transposable element-related genes resulting in 13 237 genes that are related to transposable elements. Through incorporation of multiple transcript and proteomic expression data sets, we have been able to annotate 24 799 genes (31 739 gene models), representing ∼50% of the total gene models, as expressed in the rice genome. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 59 tracks. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads.

SUMMARYMaize is an important model species and a major constituent of human and animal diets. It has also emerged as a potential feedstock and model system for bioenergy research due to recent worldwide interest in developing plant biomass-based, carbon-neutral liquid fuels. To understand how the underlying genome sequence results in specific plant phenotypes, information on the temporal and spatial transcription patterns of genes is crucial. Here we present a comprehensive atlas of global transcription profiles across developmental stages and plant organs. We used a NimbleGen microarray containing 80 301 probe sets to profile transcription patterns in 60 distinct tissues representing 11 major organ systems of inbred line B73. Of the 30 892 probe sets representing the filtered B73 gene models, 91.4% were expressed in at least one tissue. Interestingly, 44.5% of the probe sets were expressed in all tissues, indicating a substantial overlap of gene expression among plant organs. Clustering of maize tissues based on global gene expression profiles resulted in formation of groups of biologically related tissues. We utilized this dataset to examine the expression of genes that encode enzymes in the lignin biosynthetic pathway, and found that expansion of distinct gene families was accompanied by divergent, tissue-specific transcription patterns of the paralogs. This comprehensive expression atlas represents a valuable resource for gene discovery and functional characterization in maize.