The Immunological Genome Project combines immunology and computational biology laboratories in an effort to establish a complete 'road map' of gene-expression and regulatory networks in all immune cells.

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.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Approximately 80% of the maize genome comprises highly repetitive sequences interspersed with single-copy, gene-rich sequences, and standard genome sequencing strategies are not readily adaptable to this type of genome. Methodologies that enrich for genic sequences might more rapidly generate useful results from complex genomes. Equivalent numbers of clones from maize selected by techniques called methylation filtering and High C0t selection were sequenced to generate approximately 200,000 reads (approximately 132 megabases), which were assembled into contigs. Combination of the two techniques resulted in a sixfold reduction in the effective genome size and a fourfold increase in the gene identification rate in comparison to a nonenriched library.