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
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.
The parasite Trypanosoma brucei, the causative agent of sleeping sickness, cycles between an insect and a mammalian host. Here, we investigated the presence of pseudouridines (Ψs) on the spliceosomal small nuclear RNAs (snRNAs), which may enable growth at the very different temperatures characterizing the two hosts. To this end, we performed the first high-throughput mapping of spliceosomal snRNA Ψs by small RNA Ψ-seq. The analysis revealed 42 Ψs on T. brucei snRNAs, which is the highest number reported so far. We show that a trypanosome protein analogous to human protein WDR79, is essential for guiding Ψ on snRNAs but not on rRNAs. snoRNA species implicated in snRNA pseudouridylation were identified by a genome-wide approach based on ligation of RNAs following in vivo UV cross-linking. snRNA Ψs are guided by single hairpin snoRNAs, also implicated in rRNA modification. Depletion of such guiding snoRNA by RNAi compromised the guided modification on snRNA and reduced parasite growth at elevated temperatures. We further demonstrate that Ψ strengthens U4/U6 RNA–RNA and U2B"/U2A’ proteins-U2 snRNA interaction at elevated temperatures. The existence of single hairpin RNAs that modify both the spliceosome and ribosome RNAs is unique for these parasites, and may be related to their ability to cycle between their two hosts that differ in temperature.
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