Castrignanò T, D'Antonio M, Anselmo A, Carrabino D, D'Onorio De Meo A, D'Erchia A M, Licciulli F, Mangiulli M, Mignone F, Pavesi G, Picardi E, Riva A, Rizzi R, Bonizzoni P, Pesole G
Consorzio Interuniversitario per le Applicazioni di Supercalcolo per Università e Ricerca, CASPUR, Rome, Italy.
Bioinformatics. 2008 May 15;24(10):1300-4. doi: 10.1093/bioinformatics/btn113. Epub 2008 Apr 3.
Alternative splicing has recently emerged as a key mechanism responsible for the expansion of transcriptome and proteome complexity in human and other organisms. Although several online resources devoted to alternative splicing analysis are available they may suffer from limitations related both to the computational methodologies adopted and to the extent of the annotations they provide that prevent the full exploitation of the available data. Furthermore, current resources provide limited query and download facilities.
ASPicDB is a database designed to provide access to reliable annotations of the alternative splicing pattern of human genes and to the functional annotation of predicted splicing isoforms. Splice-site detection and full-length transcript modeling have been carried out by a genome-wide application of the ASPic algorithm, based on the multiple alignments of gene-related transcripts (typically a Unigene cluster) to the genomic sequence, a strategy that greatly improves prediction accuracy compared to methods based on independent and progressive alignments. Enhanced query and download facilities for annotations and sequences allow users to select and extract specific sets of data related to genes, transcripts and introns fulfilling a combination of user-defined criteria. Several tabular and graphical views of the results are presented, providing a comprehensive assessment of the functional implication of alternative splicing in the gene set under investigation. ASPicDB, which is regularly updated on a monthly basis, also includes information on tissue-specific splicing patterns of normal and cancer cells, based on available EST sequences and their library source annotation.
可变剪接最近已成为一种关键机制,它导致人类和其他生物体中转录组和蛋白质组复杂性的增加。尽管有几个致力于可变剪接分析的在线资源,但它们可能存在与所采用的计算方法以及所提供注释的范围相关的局限性,这些局限性阻碍了对可用数据的充分利用。此外,当前资源提供的查询和下载功能有限。
ASPicDB是一个数据库,旨在提供对人类基因可变剪接模式的可靠注释以及对预测剪接异构体的功能注释的访问。剪接位点检测和全长转录本建模是通过在全基因组范围内应用ASPic算法来进行的,该算法基于与基因组序列的基因相关转录本(通常是一个单基因簇)的多重比对,与基于独立和渐进比对的方法相比,这种策略大大提高了预测准确性。增强的注释和序列查询及下载功能允许用户选择和提取与满足用户定义标准组合的基因、转录本和内含子相关的特定数据集。呈现了结果的几种表格和图形视图,提供了对所研究基因集中可变剪接功能含义的全面评估。ASPicDB每月定期更新,还包括基于可用EST序列及其文库来源注释的正常细胞和癌细胞组织特异性剪接模式的信息。