Robert M. Stephens

A graphical method is presented for displaying the patterns in a set of aligned sequences. The characters representing the sequence are stacked on top of each other for each position in the aligned sequences. The height of each letter is made proportional to its frequency, and the letters are sorted so the most common one is on top. The height of the entire stack is then adjusted to signify the information content of the sequences at that position. From these 'sequence logos', one can determine not only the consensus sequence but also the relative frequency of bases and the information content (measured in bits) at every position in a site or sequence. The logo displays both significant residues and subtle sequence patterns.

All tools in the DAVID Bioinformatics Resources aim to provide functional interpretation of large lists of genes derived from genomic studies. The newly updated DAVID Bioinformatics Resources consists of the DAVID Knowledgebase and five integrated, web-based functional annotation tool suites: the DAVID Gene Functional Classification Tool, the DAVID Functional Annotation Tool, the DAVID Gene ID Conversion Tool, the DAVID Gene Name Viewer and the DAVID NIAID Pathogen Genome Browser. The expanded DAVID Knowledgebase now integrates almost all major and well-known public bioinformatics resources centralized by the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of diverse gene/protein identifiers and annotation terms from a variety of public bioinformatics databases. For any uploaded gene list, the DAVID Resources now provides not only the typical gene-term enrichment analysis, but also new tools and functions that allow users to condense large gene lists into gene functional groups, convert between gene/protein identifiers, visualize many-genes-to-many-terms relationships, cluster redundant and heterogeneous terms into groups, search for interesting and related genes or terms, dynamically view genes from their lists on bio-pathways and more. With DAVID (http://david.niaid.nih.gov), investigators gain more power to interpret the biological mechanisms associated with large gene lists.

SUMMARY: The database for annotation, visualization and integrated discovery (DAVID), which can be freely accessed at http://david.abcc.ncifcrf.gov/, is a web-based online bioinformatics resource that aims to provide tools for the functional interpretation of large lists of genes/proteins. It has been used by researchers from more than 5000 institutes worldwide, with a daily submission rate of ∼1200 gene lists from ∼400 unique researchers, and has been cited by more than 6000 scientific publications. However, the current web interface does not support programmatic access to DAVID, and the uniform resource locator (URL)-based application programming interface (API) has a limit on URL size and is stateless in nature as it uses URL request and response messages to communicate with the server, without keeping any state-related details. DAVID-WS (web service) has been developed to automate user tasks by providing stateful web services to access DAVID programmatically without the need for human interactions. AVAILABILITY: The web service and sample clients (written in Java, Perl, Python and Matlab) are made freely available under the DAVID License at http://david.abcc.ncifcrf.gov/content.jsp?file=WS.html.

MicroRNAs are small noncoding RNAs that regulate the expression of protein-coding genes. To evaluate the involvement of microRNAs in prostate cancer, we determined genome-wide expression of microRNAs and mRNAs in 60 primary prostate tumors and 16 nontumor prostate tissues. The mRNA analysis revealed that key components of microRNA processing and several microRNA host genes, e.g., MCM7 and C9orf5, were significantly up-regulated in prostate tumors. Consistent with these findings, tumors expressed the miR-106b-25 cluster, which maps to intron 13 of MCM7, and miR-32, which maps to intron 14 of C9orf5, at significantly higher levels than nontumor prostate. The expression levels of other microRNAs, including a number of miR-106b-25 cluster homologues, were also altered in prostate tumors. Additional differences in microRNA abundance were found between organ-confined tumors and those with extraprostatic disease extension. Lastly, we found evidence that some microRNAs are androgen-regulated and that tumor microRNAs influence transcript abundance of protein-coding target genes in the cancerous prostate. In cell culture, E2F1 and p21/WAF1 were identified as targets of miR-106b, Bim of miR-32, and exportin-6 and protein tyrosine kinase 9 of miR-1. In summary, microRNA expression becomes altered with the development and progression of prostate cancer. Some of these microRNAs regulate the expression of cancer-related genes in prostate cancer cells.