An Atlas of Genomic Resources for Studying Rosaceae Fruits and Ornamentals

A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.

Motivation: Robust large-scale sequence analysis is a major challenge in modern genomic science, where biologists are frequently trying to characterize many millions of sequences. Here, we describe a new Java-based architecture for the widely used protein function prediction software package InterProScan. Developments include improvements and additions to the outputs of the software and the complete reimplementation of the software framework, resulting in a flexible and stable system that is able to use both multiprocessor machines and/or conventional clusters to achieve scalable distributed data analysis. InterProScan is freely available for download from the EMBl-EBI FTP site and the open source code is hosted at Google Code. Availability and implementation: InterProScan is distributed via FTP at ftp://ftp.ebi.ac.uk/pub/software/unix/iprscan/5/ and the source code is available from http://code.google.com/p/interproscan/. Contact: http://www.ebi.ac.uk/support or interhelp@ebi.ac.uk or mitchell@ebi.ac.uk

Abstract miRBase catalogs, names and distributes microRNA gene sequences. The latest release of miRBase (v22) contains microRNA sequences from 271 organisms: 38 589 hairpin precursors and 48 860 mature microRNAs. We describe improvements to the database and website to provide more information about the quality of microRNA gene annotations, and the cellular functions of their products. We have collected 1493 small RNA deep sequencing datasets and mapped a total of 5.5 billion reads to microRNA sequences. The read mapping patterns provide strong support for the validity of between 20% and 65% of microRNA annotations in different well-studied animal genomes, and evidence for the removal of >200 sequences from the database. To improve the availability of microRNA functional information, we are disseminating Gene Ontology terms annotated against miRBase sequences. We have also used a text-mining approach to search for microRNA gene names in the full-text of open access articles. Over 500 000 sentences from 18 542 papers contain microRNA names. We score these sentences for functional information and link them with 12 519 microRNA entries. The sentences themselves, and word clouds built from them, provide effective summaries of the functional information about specific microRNAs. miRBase is publicly and freely available at http://mirbase.org/.