GeneCards (www.genecards.org) is a comprehensive, authoritative compendium of annotative information about human genes, widely used for nearly 15 years. Its gene-centric content is automatically mined and integrated from over 80 digital sources, resulting in a web-based deep-linked card for each of >73 000 human gene entries, encompassing the following categories: protein coding, pseudogene, RNA gene, genetic locus, cluster and uncategorized. We now introduce GeneCards Version 3, featuring a speedy and sophisticated search engine and a revamped, technologically enabling infrastructure, catering to the expanding needs of biomedical researchers. A key focus is on gene-set analyses, which leverage GeneCards’ unique wealth of combinatorial annotations. These include the GeneALaCart batch query facility, which tabulates user-selected annotations for multiple genes and GeneDecks, which identifies similar genes with shared annotations, and finds set-shared annotations by descriptor enrichment analysis. Such set-centric features address a host of applications, including microarray data analysis, cross-database annotation mapping and gene-disorder associations for drug targeting. We highlight the new Version 3 database architecture, its multi-faceted search engine, and its semi-automated quality assurance system. Data enhancements include an expanded visualization of gene expression patterns in normal and cancer tissues, an integrated alternative splicing pattern display, and augmented multi-source SNPs and pathways sections. GeneCards now provides direct links to gene-related research reagents such as antibodies, recombinant proteins, DNA clones and inhibitory RNAs and features gene-related drugs and compounds lists. We also portray the GeneCards Inferred Functionality Score annotation landscape tool for scoring a gene’s functional information status. Finally, we delineate examples of applications and collaborations that have benefited from the GeneCards suite. Database URL:www.genecards.org

Core promoter elements play a pivotal role in the transcriptional output, yet they are often detected manually within sequences of interest. Here, we present 2 contributions to the detection and curation of core promoter elements within given sequences. First, the Elements Navigation Tool (ElemeNT) is a user-friendly web-based, interactive tool for prediction and display of putative core promoter elements and their biologically-relevant combinations. Second, the CORE database summarizes ElemeNT-predicted core promoter elements near CAGE and RNA-seq-defined Drosophila melanogaster transcription start sites (TSSs). ElemeNT's predictions are based on biologically-functional core promoter elements, and can be used to infer core promoter compositions. ElemeNT does not assume prior knowledge of the actual TSS position, and can therefore assist in annotation of any given sequence. These resources, freely accessible at http://lifefaculty.biu.ac.il/gershon-tamar/index.php/resources, facilitate the identification of core promoter elements as active contributors to gene expression.

Small nucleolar RNAs (snoRNAs) constitute newly discovered noncoding small RNAs, most of which function in guiding modifications such as 2′-O-ribose methylation and pseudouridylation on rRNAs and snRNAs. To investigate the genome organization of Trypanosoma brucei snoRNAs and the pattern of rRNA modifications, we used a whole-genome approach to identify the repertoire of these guide RNAs. Twenty-one clusters encoding for 57 C/D snoRNAs and 34 H/ACA-like RNAs, which have the potential to direct 84 methylations and 32 pseudouridines, respectively, were identified. The number of 2′-O-methyls (Nms) identified on rRNA represent 80% of the expected modifications. The modifications guided by these RNAs suggest that trypanosomes contain many modifications and guide RNAs relative to their genome size. Interestingly, ~40% of the Nms are species-specific modifications that do not exist in yeast, humans, or plants, and 40% of the species-specific predicted modifications are located in unique positions outside the highly conserved domains. Although most of the guide RNAs were found in reiterated clusters, a few single-copy genes were identified. The large repertoire of modifications and guide RNAs in trypanosomes suggests that these modifications possibly play a central role in these parasites.

Complete information regarding transcriptional and posttranscriptional gene regulation in stem cells is necessary to understand the regulation of self-renewal and differentiation. Alternative splicing is a prevalent mode of posttranscriptional regulation, and occurs in approximately one half of all mammalian genes. The frequency and functional impact of alternative splicing in stem cells are yet to be determined. In this study we combine computational and experimental methods to identify splice variants in embryonic and hematopoietic stem cells on a genome-wide scale. Using EST collections derived from stem cells, we detect alternative splicing in >1,000 genes. Systematic RT-PCR and sequencing studies show confirmation of computational predictions at a level of 80%. We find that alternative splicing can modify multiple components of signaling pathways important for stem cell function. We also analyze the distribution of splice variants across different classes of genes. We find that tissue-specific genes have a higher tendency to undergo alternative splicing than ubiquitously expressed genes. Furthermore, the patterns of alternative splicing are only weakly conserved between orthologous genes in human and mouse. Our studies reveal extensive modification of the stem cell molecular repertoire by alternative splicing and provide insights into its overall role as a mechanism of generating genomic diversity.

Background: The human genome encodes thousands of unique long non-coding RNAs (lncRNAs), and these transcripts are emerging as critical regulators of gene expression and cell fate. However, the transcriptional regulation of their expression is not fully understood. The pivotal transcription factor E2F1 which can induce both proliferation and cell death, is a critical downstream target of the tumor suppressor, RB. The retinoblastoma pathway is often inactivated in human tumors resulting in deregulated E2F activity. Results: Here, we report that lncRNA XLOC 006942, which we named ERIC, is regulated by E2F1 and, most probably, also E2F3. We show that expression levels of ERIC were elevated upon activation of exogenous E2F1, E2F3 or endogenous E2Fs. Moreover, knockdown of either E2F1 or E2F3 reduced ERIC levels and endogenous E2F1 binds ERIC’s promoter. Expression of ERIC was cell cycle regulated and peaked in G1 in an E2F1-dependent manner. Inhibition of ERIC expression increased E2F1-mediated apoptosis, suggesting that E2F1 and ERIC constitute a negative feedback loop that modulates E2F1 activity. Furthermore, ERIC levels were increased following DNA damage by the chemotherapeutic drug Etoposide, and inhibition of ERIC expression enhanced Etoposide -induced apoptosis. Conclusions: Our data identify ERIC as a novel lncRNA that is transcriptionally regulated by E2Fs, and restricts apoptosis induced by E2F1, as well as by DNA damage.