We demonstrate the feasibility of generating thousands of transgenic Drosophila melanogaster lines in which the expression of an exogenous gene is reproducibly directed to distinct small subsets of cells in the adult brain. We expect the expression patterns produced by the collection of 5,000 lines that we are currently generating to encompass all neurons in the brain in a variety of intersecting patterns. Overlapping 3-kb DNA fragments from the flanking noncoding and intronic regions of genes thought to have patterned expression in the adult brain were inserted into a defined genomic location by site-specific recombination. These fragments were then assayed for their ability to function as transcriptional enhancers in conjunction with a synthetic core promoter designed to work with a wide variety of enhancer types. An analysis of 44 fragments from four genes found that >80% drive expression patterns in the brain; the observed patterns were, on average, comprised of <100 cells. Our results suggest that the D. melanogaster genome contains >50,000 enhancers and that multiple enhancers drive distinct subsets of expression of a gene in each tissue and developmental stage. We expect that these lines will be valuable tools for neuroanatomy as well as for the elucidation of neuronal circuits and information flow in the fly brain.enhancer ͉ gene expression ͉ promoter ͉ transcription ͉ transgenic

A comparative analysis of the genomes of Drosophila melanogaster, Caenorhabditis elegans, and Saccharomyces cerevisiae-and the proteins they are predicted to encode-was undertaken in the context of cellular, developmental, and evolutionary processes. The nonredundant protein sets of flies and worms are similar in size and are only twice that of yeast, but different gene families are expanded in each genome, and the multidomain proteins and signaling pathways of the fly and worm are far more complex than those of yeast. The fly has orthologs to 177 of the 289 human disease genes examined and provides the foundation for rapid analysis of some of the basic processes involved in human disease.

No abstract

The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them. FlyBase biologists successfully used Apollo to annotate the Drosophila melanogaster genome and it is increasingly being used as a starting point for the development of customized annotation editing tools for other genome projects. RationaleUnadorned genomic sequence data is simply a string of As, Ts, Gs, and Cs, with perhaps an associated confidence value for each base. In this raw state, sequence data provides very little biological insight. To utilize any sequence it must be interpreted in the context of other biological knowledge. This is the process of annotation, the task of adding explanatory notations to the sequence text. We define an annotation as the biological evaluation and explanation of a specific region on a nucleic acid sequence that includes, but is not limited to, gene transcripts. Any feature that can be anchored to the sequence -for example, an exon, a promoter, a transposable element, a regulatory region, or a CpG island -is an annotation. The genomic sequence will stabilize and reach a finite endpoint, but the annotations will continue to evolve indefinitely, as biological knowledge increases. To understand the genetic legacy of an organism we must interpret its genomic sequence, translating the information it contains in molecular form into humanreadable annotations.Part of this process is purely computational, and in its simplest terms can be described as a process of recognition: can anything be located that is somehow already familiar? The first obvious tactic is to collect sequences that may represent interesting biological features and to search the genomic sequence in order to discover the presence or absence of similar sequences. The principle is the same whether the sequences used in this comparison are expressed sequence tags (ESTs), full-length cDNAs, repeated elements or highly conserved sequences, and whether the sequences come from the same species, a closely related species or a distantly

authors note errors in three sentences in the second paragraph on page 15042, left column. The corrected paragraph is reprinted below, and the revised sentences appear in boldface. The authors are grateful to Dr. Benny Abraham for identifying the errors.The reported SNP for CD24 is a replacement of C at nucleotide 226 by T (C3T) in the coding region of exon 2 (GenBank accession no. NM013230), which results in a substitution of Ala at amino acid 57 by Val near the GPI anchorage site of the mature protein. The genomic DNA was isolated from Ϸ5 ϫ 10 6 human peripheral blood leukocytes (PBL) by using the QIAamp DNA Blood Minikit (Qiagen, Valencia, CA). DNA fragments bearing this SNP site were amplified by PCR by using a forward primer (TTG TTG CCA CTT GGC ATT TTT GAG GC) and a reverse primer (GGA TTG GGT TTA GAA GAT GGG GAA A). The PCR conditions were as follows: 94°C for 1 min, 50°C for 1 min, and 72°C for 1 min, for 35 cycles. The predicted CD24 PCR fragment is 453 bp long. The C3T change yielded a BstXI restriction enzyme site at nucleotide 225, which allowed us to differentiate these two different CD24 alleles by restriction fragment length polymorphism analysis. Briefly, an aliquot of CD24 PCR products was digested with BstXI for 16 h at 50°C. The digested products were then separated in a 2.5% agarose gel. The predicted digestion pattern is as follows: PCR products of T226 allele will be cut into two small fragments (325 and 129 bp), whereas those of the C226 will be completely resistant. A combination of the two types of the products at close to 50% levels indicates the heterozygosity of the subject. 1073͞pnas.0501422102), the authors note the following regarding the homology of conceptual translations of putative noncoding RNA (pncr) transcripts to known proteins. The report correctly states that for all candidate noncoding transcripts curated in this study, BLASTX analyses using default parameters return no results. However, subsequent analyses of those candidates designated by this study as pncr genes using BLASTP with a PAM30 substitution matrix has revealed homology to known proteins for 2 of the 17 genes listed in Table 2: pncr005:2R and pncr006:X. Homology to a conceptual translation was found for a third transcript, pncr007:3R. We are therefore withdrawing the pncr gene designations in these three cases. No protein homology is detected for other pncr transcripts under these parameters.

Background: The recent completion of the Drosophila melanogaster genomic sequence to high quality and the availability of a greatly expanded set of Drosophila cDNA sequences, aligning to 78% of the predicted euchromatic genes, afforded FlyBase the opportunity to significantly improve genomic annotations. We made the annotation process more rigorous by inspecting each gene visually, utilizing a comprehensive set of curation rules, requiring traceable evidence for each gene model, and comparing each predicted peptide to SWISS-PROT and TrEMBL sequences.

The National Center for Biomedical Ontology (http://bioontology.org) is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists funded by the NIH Roadmap to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are: (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. The Center is working toward these objectives by providing tools to develop ontologies and to annotate experimental data, and by developing resources to integrate and relate existing ontologies as well as by creating repositories of biomedical data that are annotated using those ontologies. The Center is providing training workshops in ontology design, development, and usage, and is also pursuing research in ontology evaluation, quality, and use of ontologies to promote scientific discovery. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease.

An annotation is any feature that can be tied to genomic sequence, such as an exon, transcript, promoter, or transposable element. As biological knowledge increases, annotations of different types need to be added and modified, and links to other sources of information need to be incorporated, to allow biologists to easily access all of the available sequence analysis data and design appropriate experiments. The Apollo genome browser and editor offers biologists these capabilities. Apollo can display many different types of computational evidence, such as alignments and similarities based on BLAST searches (UNITS & ), and enables biologists to utilize computational evidence to create and edit gene models and other genomic features, e.g., using experimental evidence to refine exon‐intron structures predicted by gene prediction algorithms. This protocol describes simple ways to browse genome annotation data, as well as techniques for editing annotations and loading data from different sources.