Skip to main content

Navigating in a Sea of Repeats in RNA-seq without Drowning

  • Conference paper
Algorithms in Bioinformatics (WABI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 8701))

Included in the following conference series:

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Bern, M., Plassmann, P.: The steiner problem with edge lengths 1 and 2. Information Processing Letters (1989)

    Google Scholar 

  2. 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)

    Article  Google Scholar 

  3. Djebali, S., Davis, C., Merkel, A., Dobin, A., et al.: Landscape of transcription in human cells. Nature (2012)

    Google Scholar 

  4. 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)

    Google Scholar 

  5. 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)

    Google Scholar 

  6. Jurka, J., Bao, W., Kojima, K.: Families of transposable elements, population structure and the origin of species. Biology Direct 6(1), 44 (2011)

    Article  Google Scholar 

  7. Kent, W.J.: BLAT–the BLAST-like alignment tool. Genome Res. 12 (2002)

    Google Scholar 

  8. Myers, E., Sutton, G., Delcher, A., Dew, I., et al.: A whole-genome assembly of drosophila. Science 287(5461), 2196–2204 (2000)

    Article  Google Scholar 

  9. Novák, P., Neumann, P., Macas, J.: Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data. BMC Bioinf. (2010)

    Google Scholar 

  10. 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)

    Google Scholar 

  11. 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)

    Article  Google Scholar 

  12. 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)

    Google Scholar 

  13. 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)

    Chapter  Google Scholar 

  14. Schulz, M., Zerbino, D., Vingron, M., Birney, E.: Oases: robust de novo RNA-seq assembly across the dynamic range of expression levels. Bioinf. (2012)

    Google Scholar 

  15. Smit, A.F.A., Hubley, R., Green, P.: RepeatMasker Open-3.0, 1996-2004

    Google Scholar 

  16. 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)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints 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)

Publish with us

Policies and ethics