Abstract
The main challenge in de novo assembly of NGS data is certainly to deal with repeats that are longer than the reads. This is particularly true for RNA-seq data, since coverage information cannot be used to flag repeated sequences, of which transposable elements are one of the main examples. Most transcriptome assemblers are based on de Bruijn graphs and have no clear and explicit model for repeats in RNA-seq data, relying instead on heuristics to deal with them. The results of this work are twofold. First, we introduce a formal model for representing high copy-number repeats in RNA-seq data and exploit its properties to infer a combinatorial characteristic of repeat-associated subgraphs. We show that the problem of identifying in a de Bruijn graph a subgraph with this characteristic is NP-complete. In a second step, we show that in the specific case of a local assembly of alternative splicing (AS) events, using our combinatorial characterization we can implicitly avoid such subgraphs. In particular, we designed and implemented an algorithm to efficiently identify AS events that are not included in repeated regions. Finally, we validate our results using synthetic data. We also give an indication of the usefulness of our method on real data.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bern, M., Plassmann, P.: The steiner problem with edge lengths 1 and 2. Information Processing Letters (1989)
Carroll, M.L., Roy-Engel, A.M., Nguyen, S.V., Salem, A.-H., et al.: Large-scale analysis of the alu ya5 and yb8 subfamilies and their contribution to human genomic diversity. Journal of Molecular Biology 311(1), 17–40 (2001)
Djebali, S., Davis, C., Merkel, A., Dobin, A., et al.: Landscape of transcription in human cells. Nature (2012)
Grabherr, M., Haas, B., Yassour, M., Levin, J., et al.: Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biot. (2011)
Griebel, T., Zacher, B., Ribeca, P., Raineri, E., et al.: Modelling and simulating generic RNA-Seq experiments with the flux simulator. Nucleic Acids Res. (2012)
Jurka, J., Bao, W., Kojima, K.: Families of transposable elements, population structure and the origin of species. Biology Direct 6(1), 44 (2011)
Kent, W.J.: BLAT–the BLAST-like alignment tool. Genome Res. 12 (2002)
Myers, E., Sutton, G., Delcher, A., Dew, I., et al.: A whole-genome assembly of drosophila. Science 287(5461), 2196–2204 (2000)
Novák, P., Neumann, P., Macas, J.: Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data. BMC Bioinf. (2010)
Peng, Y., Leung, H., Yiu, S.-M., Lv, M.-J., et al.: IDBA-tran: a more robust de novo de bruijn graph assembler for transcriptomes with uneven expression levels. Bioinf. 29(13) (2013)
Robertson, G., Schein, J., Chiu, R., Corbett, R., et al.: De novo assembly and analysis of RNA-seq data. Nat. Met. 7(11), 909–912 (2010)
Sacomoto, G., Kielbassa, J., Chikhi, R., Uricaru, R., et al.: KISSPLICE: de-novo calling alternative splicing events from RNA-seq data. BMC Bioinformatics 13(Suppl 6), S5 (2012)
Sacomoto, G., Lacroix, V., Sagot, M.-F.: A polynomial delay algorithm for the enumeration of bubbles with length constraints in directed graphs and its application to the detection of alternative splicing in RNA-seq data. In: Darling, A., Stoye, J. (eds.) WABI 2013. LNCS, vol. 8126, pp. 99–111. Springer, Heidelberg (2013)
Schulz, M., Zerbino, D., Vingron, M., Birney, E.: Oases: robust de novo RNA-seq assembly across the dynamic range of expression levels. Bioinf. (2012)
Smit, A.F.A., Hubley, R., Green, P.: RepeatMasker Open-3.0, 1996-2004
Tilgner, H., Knowles, D., Johnson, R., Davis, C., et al.: Deep sequencing of subcellular RNA fractions shows splicing to be predominantly co-transcriptional in the human genome but inefficient for lncRNAs. Genome Res. (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sacomoto, G., Sinaimeri, B., Marchet, C., Miele, V., Sagot, MF., Lacroix, V. (2014). Navigating in a Sea of Repeats in RNA-seq without Drowning. In: Brown, D., Morgenstern, B. (eds) Algorithms in Bioinformatics. WABI 2014. Lecture Notes in Computer Science(), vol 8701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44753-6_7
Download citation
DOI: https://doi.org/10.1007/978-3-662-44753-6_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-44752-9
Online ISBN: 978-3-662-44753-6
eBook Packages: Computer ScienceComputer Science (R0)