Published online 25 May 2010 Nucleic Acids Research, 2010, Vol. 38, Web Server issue W281–W285 doi:10.1093/nar/gkq444 SFmap: a web server for motif analysis and prediction of splicing factor binding sites Inbal Paz1, Martin Akerman2, Iris Dror1, Idit Kosti1 and Yael Mandel-Gutfreund1,* 1Faculty of Biology, Technion – Israel Institute of Technology, Haifa 32000, Israel and 2Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA Received February 15, 2010; Revised May 2, 2010; Accepted May 9, 2010 ABSTRACT Alternative splicing (AS) is a post-transcriptional process considered to be responsible for the huge diversity of proteins in higher eukaryotes. AS events are regulated by different splicing factors (SFs) that bind to sequence elements on the RNA. SFmap is a web server for predicting putative SF binding sites in genomic data (http://sfmap.technion.ac.il). SFmap implements the COS(WR) algorithm, which computes similarity scores for a given regulatory motif based on information derived from its sequence environment and its evolutionary conser- vation. Input for SFmap is a human genomic sequence or a list of sequences in FASTA format that can either be uploaded from a file or pasted into a window. SFmap searches within a given sequence for significant hits of binding motifs that are either stored in our database or defined by the user. SFmap results are provided both as a text file and as a graphical web interface. INTRODUCTION Alternative splicing (AS) is a post-transcriptional process that generates multiple mRNA isoforms from the same gene. In recent years, AS has emerged as one of the major sources of diversity and functional complexity in humans and other vertebrates (1). Misregulation of AS is also largely associated with human diseases (2). The AS process requires a core splicing mechanism that binds to splicing signals around the exon/intron junctions. Core splicing signals include: (i) the canonical 50-splice site (‘GU’ in humans) and the 30-splice site (‘AG’ in humans), located at the 50- and 30-ends of the intron, respectively; (ii) the polypyrimidine tract (PPT) located upstream of the 30-splice site; and (iii) the branch site (conserved ‘A’ in humans) located upstream of the PPT. A web server for mapping splicing signals is available at http://sroogle.tau .ac.il (3). The core splicing signals, however, are not suﬃ- cient for accurate recognition of exon/intron junctions. It is well established that additional cis-regulatory elements exist in the exons and the ﬂanking introns that bind to diﬀerent RNA-binding proteins, acting as splicing factors (SFs) (4). In general, the cis-regulatory elements are rela- tively short and degenerative sequences, and in many cases, are present in multiple copies on the RNA (5). These SFs can act as positive or negative eﬀectors of the splicing reaction by interacting diﬀerentially with exonic or intronic splicing enhancers (ESEs/ISEs) and silencers (ESSs/ISSs), respectively. In recent years, several methodologies for identifying SF binding sites have been developed (6–10); for review see (11). Most of the available methods for detecting cis- regulatory splicing elements, such as RESCUE-ESE (relative enhancer and silencer classiﬁcation by unanimous enrichment) (7), PESE (8) and the method by Goren et al. (10), use a de novo prediction approach for detecting motifs enriched in splicing regulatory regions. These methods are generally designed to detect cis-regulatory elements; however, they do not attempt to assign a speciﬁc trans-factor to a detected cis-regulatory motif. For example, the RESCUE-ESE web server http://genes .mit.edu/burgelab/rescue-ese/ searches for hexamers that are associated with ESE based on their higher frequency of occurrence in exons versus introns, as well as their sig- niﬁcantly higher frequency in exons with weak (non-consensus) splice sites compared to exons with strong (consensus) splice sites (7). A diﬀerent approach is applied using ESEﬁnder http://rulai.cshl.edu (6). The ESEﬁnder web site presents a search interface for detect- ing signiﬁcant matches of ﬁve ESEs related to four SR proteins: SF2/ASF, SC35, SRp40 and SRp55. The ESEs position speciﬁc scoring matrices were derived using func- tional systematic evolution of ligands by exponential en- richment (12). Another strategy RegRNA http://regrna .mbc.nctu.edu.tw/ was recently developed for identifying *To whom correspondence should be addressed. Tel: 972 4 8293958; Fax: 972 4 8225153; Email: yaelmg@tx.technion.ac.il The authors wish it to be known that, in their opinion, the ﬁrst two authors should be regarded as joint First Authors. The Author(s) 2010. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.