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Until recently, the genome-wide annotation of 3′ untranslated regions received less attention than coding regions and the delineation of intron/exon boundaries. In this paper, data produced for samples in Human, Chicken and A. thaliana by the novel single-molecule, strand-specific, Direct RNA Sequencing technology from Helicos Biosciences which locates 3′ polyadenylation sites to within +/− 2 nt, were combined with archival EST and RNA-Seq data. Nine examples are illustrated where this combination of data allowed: (1) gene and 3′ UTR re-annotation (including extension of one 3′ UTR by 5.9 kb); (2) disentangling of gene expression in complex regions; (3) clearer interpretation of small RNA expression and (4) identification of novel genes. While the specific examples displayed here may become obsolete as genome sequences and their annotations are refined, the principles laid out in this paper will be of general use both to those annotating genomes and those seeking to interpret existing publically available annotations in the context of their own experimental data.", "publicationTitle": "PLoS ONE", "publisher": "", "place": "", "date": "April 10, 2014", "volume": "9", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "e94270", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "PLoS ONE", "DOI": "10.1371/journal.pone.0094270", "citationKey": "", "url": "http://dx.doi.org/10.1371/journal.pone.0094270", "accessDate": "2015-05-11T11:11:43Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "PLoS Journals", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [ "BMPUPZ8J" ], "relations": {}, "dateAdded": "2015-05-11T11:11:43Z", "dateModified": "2015-05-11T11:11:43Z" } }, { "key": "GNDS224M", "version": 25, "library": { "type": "group", "id": 317134, "name": "measuresmatter", "links": { "alternate": { "href": "https://www.zotero.org/groups/measuresmatter", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/317134/items/GNDS224M", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/measuresmatter/items/GNDS224M", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/317134/items/IK4EGNM9", "type": "application/json" } }, "meta": { "createdByUser": { "id": 327401, "username": "Blahah404", "name": "Richard Smith-Unna", "links": { "alternate": { "href": "https://www.zotero.org/blahah404", "type": "text/html" } } } }, "data": { "key": "GNDS224M", "version": 25, "parentItem": "IK4EGNM9", "itemType": "attachment", "linkMode": "imported_url", "title": "Snapshot", "accessDate": "2015-05-11T11:11:41Z", "url": "http://biorxiv.org/content/early/2015/02/26/008763", "note": "", "contentType": "text/html", "charset": "utf-8", "filename": "008763.html", "md5": "41869bb00c20fa3d537f595402b46c84", "mtime": 1431342702000, "tags": [], "relations": {}, "dateAdded": "2015-05-11T11:11:41Z", "dateModified": "2015-05-11T11:11:41Z" } }, { "key": "IK4EGNM9", "version": 24, "library": { "type": "group", "id": 317134, "name": "measuresmatter", "links": { "alternate": { "href": "https://www.zotero.org/groups/measuresmatter", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/317134/items/IK4EGNM9", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/measuresmatter/items/IK4EGNM9", "type": "text/html" } }, "meta": { "createdByUser": { "id": 327401, "username": "Blahah404", "name": "Richard Smith-Unna", "links": { "alternate": { "href": "https://www.zotero.org/blahah404", "type": "text/html" } } }, "creatorSummary": "Alamancos et al.", "parsedDate": "2015-02-26", "numChildren": 2 }, "data": { "key": "IK4EGNM9", "version": 24, "itemType": "journalArticle", "title": "Leveraging transcript quantification for fast computation of alternative splicing profiles", "creators": [ { "creatorType": "author", "firstName": "Gael P.", "lastName": "Alamancos" }, { "creatorType": "author", "firstName": "Amadís", "lastName": "Pagès" }, { "creatorType": "author", "firstName": "Juan L.", "lastName": "Trincado" }, { "creatorType": "author", "firstName": "Nicolás", "lastName": "Bellora" }, { "creatorType": "author", "firstName": "Eduardo", "lastName": "Eyras" } ], "abstractNote": "Alternative splicing plays an essential role in many cellular processes and bears major relevance in the understanding of multiple diseases, including cancer. High-throughput RNA sequencing allows genome-wide analyses of splicing across multiple conditions. However, the increasing number of available datasets represents a major challenge in terms of computation time and storage requirements. We describe SUPPA, a computational tool to calculate relative inclusion values of alternative splicing events, exploiting fast transcript quantification. SUPPA accuracy is comparable and sometimes superior to standard methods using simulated as well as real RNA sequencing data compared to experimentally validated events. We assess the variability in terms of the choice of annotation and provide evidence that using complete transcripts rather than more transcripts per gene provides better estimates. Moreover, SUPPA coupled with de novo transcript reconstruction methods does not achieve accuracies as high as using quantification of known transcripts, but remains comparable to existing methods. Finally, we show that SUPPA is more than 1000 times faster than standard methods. Coupled with fast transcript quantification, SUPPA provides inclusion values at a much higher speed than existing methods without compromising accuracy, thereby facilitating the systematic splicing analysis of large datasets with limited computational resources. 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