KIS SPLICE: de-novo calling alternative splicing events from RNA-seq data

BMC Bioinformatics

Proceedings

Rayan Chikhi¹  Pavlos Antoniou¹  Pierre Peterlongo¹  Raluca Uricaru²  Vincent Lacroix³  Marie-France Sagot³  Janice Kielbassa³  Gustavo AT Sacomoto³ 

[1] Centre de recherche INRIA Rennes - Bretagne Atlantique, IRISA, Campus universitaire de Beaulieu, Rennes, France;Centre de recherche INRIA Rennes - Bretagne Atlantique, IRISA, Campus universitaire de Beaulieu, Rennes, France;INRA UMR118, Amélioration des Plantes et Biotech. Végétales, Rennes, France;INRIA Grenoble Rhône-Alpes, France;Université de Lyon, F-69000, Lyon, France;Université Lyon 1; CNRS, UMR5558, Laboratoire de Biométrie et Biologie Evolutive, F-69622, Villeurbanne, France;

关键词: Short Path;    Reference Genome;    Splice Event;    Variable Part;    Alternative Transcript;   

DOI  :  10.1186/1471-2105-13-S6-S5

来源: Springer

【 摘 要 】

BackgroundIn this paper, we address the problem of identifying and quantifying polymorphisms in RNA-seq data when no reference genome is available, without assembling the full transcripts. Based on the fundamental idea that each polymorphism corresponds to a recognisable pattern in a De Bruijn graph constructed from the RNA-seq reads, we propose a general model for all polymorphisms in such graphs. We then introduce an exact algorithm, called KIS SPLICE, to extract alternative splicing events.ResultsWe show that KIS SPLICE enables to identify more correct events than general purpose transcriptome assemblers. Additionally, on a 71 M reads dataset from human brain and liver tissues, KIS SPLICE identified 3497 alternative splicing events, out of which 56% are not present in the annotations, which confirms recent estimates showing that the complexity of alternative splicing has been largely underestimated so far.ConclusionsWe propose new models and algorithms for the detection of polymorphism in RNA-seq data. This opens the way to a new kind of studies on large HTS RNA-seq datasets, where the focus is not the global reconstruction of full-length transcripts, but local assembly of polymorphic regions. KIS SPLICE is available for download at http://alcovna.genouest.org/kissplice/.

【 授权许可】

Unknown   
© Sacomoto et al.; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.