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Although the size of an organism is a defining feature, little is known about the mechanisms that set the final size of organs and whole organisms. Here we describe Arabidopsis DA1, encoding a predicted ubiquitin receptor, which sets final seed and organ size by restricting the period of cell proliferation. The mutant protein encoded by the da1-1 allele has a negative activity toward DA1 and a DA1-related (DAR) protein, and overexpression of a da1-1 cDNA dramatically increases seed and organ size of wild-type plants, identifying this small gene family as important regulators of seed and organ size in plants.

We present an analysis of the chicken (Gallus gallus) transcriptome based on the full insert sequences for 19,626 cDNAs, combined with 485,337 EST sequences. The cDNA data set has been functionally annotated and describes a minimum of 11,929 chicken coding genes, including the sequence for 2260 full-length cDNAs together with a collection of noncoding (nc) cDNAs that have been stringently filtered to remove untranslated regions of coding mRNAs. The combined collection of cDNAs and ESTs describe 62,546 clustered transcripts and provide transcriptional evidence for a total of 18,989 chicken genes, including 88% of the annotated Ensembl gene set. Analysis of the ncRNAs reveals a set that is highly conserved in chickens and mammals, including sequences for 14 pri-miRNAs encoding 23 different miRNAs. The data sets described here provide a transcriptome toolkit linked to physical clones for bioinformaticians and experimental biologists who wish to use chicken systems as a low-cost, accessible alternative to mammals for the analysis of vertebrate development, immunology, and cell biology.

To contribute to our understanding of the genome complexity of sugarcane, we undertook a large-scale expressed sequence tag (EST) program. More than 260,000 cDNA clones were partially sequenced from 26 standard cDNA libraries generated from different sugarcane tissues. After the processing of the sequences, 237,954 high-quality ESTs were identified. These ESTs were assembled into 43,141 putative transcripts. Of the assembled sequences, 35.6% presented no matches with existing sequences in public databases. A global analysis of the whole SUCEST data set indicated that 14,409 assembled sequences (33% of the total) contained at least one cDNA clone with a full-length insert. Annotation of the 43,141 assembled sequences associated almost 50% of the putative identified sugarcane genes with protein metabolism, cellular communication/signal transduction, bioenergetics, and stress responses. Inspection of the translated assembled sequences for conserved protein domains revealed 40,821 amino acid sequences with 1415 Pfam domains. Reassembling the consensus sequences of the 43,141 transcripts revealed a 22% redundancy in the first assembling. This indicated that possibly 33,620 unique genes had been identified and indicated that >90% of the sugarcane expressed genes were tagged.

Plant pathogenic microbes have the remarkable ability to manipulate biochemical, physiological, and morphological processes in their host plants. These manipulations are achieved through a diverse array of effector molecules that can either promote infection or trigger defense responses. We describe a general functional genomics approach aimed at identifying extracellular effector proteins from plant pathogenic microorganisms by combining data mining of expressed sequence tags (ESTs) with virus-based high-throughput functional expression assays in plants. PexFinder, an algorithm for automated identification of extracellular proteins from EST data sets, was developed and applied to 2147 ESTs from the oomycete plant pathogen Phytophthora infestans. The program identified 261 ESTs (12.2%) corresponding to a set of 142 nonredundant Pex (Phytophthora extracellular protein) cDNAs. Of these, 78 (55%) Pex cDNAs were novel with no significant matches in public databases. Validation of PexFinder was performed using proteomic analysis of secreted protein of P. infestans. To identify which of the Pex cDNAs encode effector proteins that manipulate plant processes, high-throughput functional expression assays in plants were performed on 63 of the identified cDNAs using an Agrobacterium tumefaciens binary vector carrying the potato virus X (PVX) genome. This led to the discovery of two novel necrosis-inducing cDNAs, crn1 and crn2, encoding extracellular proteins that belong to a large and complex protein family in Phytophthora. Further characterization of the crn genes indicated that they are both expressed in P. infestans during colonization of the host plant tomato and that crn2 induced defense-response genes in tomato. Our results indicate that combining data mining using PexFinder with PVX-based functional assays can facilitate the discovery of novel pathogen effector proteins. In principle, this strategy can be applied to a variety of eukaryotic plant pathogens, including oomycetes, fungi, and nematodes.

The Mouse Genome Sequencing Consortium and the RIKEN Genome Exploration Research grouphave generated large sets of sequence data representing the mouse genome and transcriptome, respectively. These data provide a valuable foundation for genomic research. The challenges for the informatics community are how to integrate these data with the ever-expanding knowledge about the roles of genes and gene products in biological processes, and how to provide useful views to the scientific community. Public resources, such as the National Center for Biotechnology Information (NCBI; http://www.ncbi.nih.gov), and model organism databases, such as the Mouse Genome Informatics database (MGI; http://www.informatics.jax.org), maintain the primary data and provide connections between sequence and biology. In this paper, we describe how the partnership of MGI and NCBI LocusLink contributes to the integration of sequence and biology, especially in the context of the large-scale genome and transcriptome data now available for the laboratory mouse. In particular, we describe the methods and results of integration of 60,770 FANTOM2 mouse cDNAs with gene records in the databases of MGI and LocusLink.

FACTS (Functional Association/Annotation of cDNA Clones from Text/Sequence Sources) is a semiautomated knowledge discovery and annotation system that integrates molecular function information derived from sequence analysis results (sequence inferred) with functional information extracted from text. Text-inferred information was extracted from keyword-based retrievals of MEDLINE abstracts and by matching of gene or protein names to OMIM, BIND, and DIP database entries. Using FACTS, we found that 47.5% of the 60,770 RIKEN mouse cDNA FANTOM2 clone annotations were informative for text searches. MEDLINE queries yielded molecular interaction-containing sentences for 23.1% of the clones. When disease MeSH and GO terms were matched with retrieved abstracts, 22.7% of clones were associated with potential diseases, and 32.5% with GO identifiers. A significant number (23.5%) of disease MeSH-associated clones were also found to have a hereditary disease association (OMIM Morbidmap). Inferred neoplastic and nervous system disease represented 49.6% and 36.0% of disease MeSH-associated clones, respectively. A comparison of sequence-based GO assignments with informative text-based GO assignments revealed that for 78.2% of clones, identical GO assignments were provided for that clone by either method, whereas for 21.8% of clones, the assignments differed. In contrast, for OMIM assignments, only 28.5% of clones had identical sequence-based and text-based OMIM assignments. Sequence, sentence, and term-based functional associations are included in the FACTS database (http://facts.gsc.riken.go.jp/), which permits results to be annotated and explored through web-accessible keyword and sequence search interfaces. The FACTS database will be a critical tool for investigating the functional complexity of the mouse transcriptome, cDNA-inferred interactome (molecular interactions), and pathome (pathologies).

Three hundred cDNAs containing putatively entire open reading frames (ORFs) for previously undefined genes were obtained from CD34+ hematopoietic stem/progenitor cells (HSPCs), based on EST cataloging, clone sequencing, in silico cloning, and rapid amplification of cDNA ends (RACE). The cDNA sizes ranged from 360 to 3496 bp and their ORFs coded for peptides of 58-752 amino acids. Public database search indicated that 225 cDNAs exhibited sequence similarities to genes identified across a variety of species. Homology analysis led to the recognition of 50 basic structural motifs/domains among these cDNAs. Genomic exon-intron organization could be established in 243 genes by integration of cDNA data with genome sequence information. Interestingly, a new gene named as HSPC070 on 3p was found to share a sequence of 105bp in 3' UTR with RAF gene in reversed transcription orientation. Chromosomal localizations were obtained using electronic mapping for 192 genes and with radiation hybrid (RH) for 38 genes. Macroarray technique was applied to screen the gene expression patterns in five hematopoietic cell lines (NB4, HL60, U937, K562, and Jurkat) and a number of genes with differential expression were found. The resource work has provided a wide range of information useful not only for expression genomics and annotation of genomic DNA sequence, but also for further research on the function of genes involved in hematopoietic development and differentiation.