How Many Transcripts Does It Take to Reconstruct the Splice Graph?

  • Paul Jenkins
  • Rune Lyngsø
  • Jotun Hein
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4175)


Alternative splicing has emerged as an important biological process which increases the number of transcripts obtainable from a gene. Given a sample of transcripts, the alternative splicing graph (ASG) can be constructed—a mathematical object minimally explaining these transcripts. Most research has so far been devoted to the reconstruction of ASGs from a sample of transcripts, but little has been done on the confidence we can have in these ASGs providing the full picture of alternative splicing. We address this problem by proposing probabilistic models of transcript generation, under which growth of the inferred ASG is investigated. These models are used in novel methods to test the nature of the collection of real transcripts from which the ASG was derived, which we illustrate on example genes. Statistical comparisons of the proposed models were also performed, showing evidence for variation in the pattern of dependencies between donor and acceptor sites.


Alternative Splice Splice Event Path Cover Cassette Exon Alternative Splice Site 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Johnson, J.M., Castle, J., Garrett-Engele, P., Kan, Z., Loerch, P.M., Armour, C.D., Santos, R., Schadt, E.E., Stoughton, R., Shoemaker, D.D.: Genome-wide survey of human alternative pre-mRNA splicing with exon junction microarrays. Science 302, 2141–2144 (2003)CrossRefGoogle Scholar
  2. 2.
    Leipzig, J., Pevzner, P., Heber, S.: The alternative splicing gallery (ASG): bridging the gap between genome and transcriptome. Nucleic Acids Research 32, 3977–3983 (2004)CrossRefGoogle Scholar
  3. 3.
    Lareau, L.F., Green, R.E., Bhatnagar, R.S., Brenner, S.E.: The evolving roles of alternative splicing. Current Opinions in Structural Biology 14, 273–282 (2004)CrossRefGoogle Scholar
  4. 4.
    Black, D.L.: Mechanisms of alternative pre-messenger RNA splicing. Annual Review of Biochemistry 72, 291–336 (2003)CrossRefGoogle Scholar
  5. 5.
    Lopez, A.J.: Alternative splicing of pre-mRNA: developmental consequences and mechanisms of regulation. Annual Review of Genetics 32, 279–305 (1998)CrossRefGoogle Scholar
  6. 6.
    Pan, Q., Shai, O., Misquitta, C., Zhang, W., Saltzman, A.L., Mohammad, N., Babak, T., Siu, H., Hughes, T.R., Morris, Q.D., Frey, B.J., Blencowe, B.J.: Revealing global regulatory features of mammalian alternative splicing using a quantitative microarray platform. Molecular Cell 16, 929–941 (2004)CrossRefGoogle Scholar
  7. 7.
    Heber, S., Alekseyev, M., Sze, S.H., Tang, H., Pevzner, P.A.: Splicing graphs and EST assembly problem. Bioinformatics 18, S181–S188 (2002)Google Scholar
  8. 8.
    Black, D.L.: A simple answer for a splicing conundrum. Proceedings of the National Academy of Sciences of the United States of America 102, 4927–4928 (2005)CrossRefGoogle Scholar
  9. 9.
    Ibrahim, E.C., Schaal, T.D., Hertel, K.J., Reed, R., Maniatis, T.: Serine/arginine-rich protein-dependent suppression of exon skipping by exonic splicing enhancers. Proceedings of the National Academy of Sciences of the United States of America 102, 5002–5007 (2005)CrossRefGoogle Scholar
  10. 10.
    Lee, C., Atanelov, L., Modrek, B., Xing, Y.: ASAP: the alternative splicing annotation project. Nucleic Acids Research 31, 101–105 (2003)CrossRefGoogle Scholar
  11. 11.
    Li, W.N., Reddy, S.M., Sahni, S.: On path selection in combinational logic circuits. IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems 8, 56–63 (1989)CrossRefGoogle Scholar
  12. 12.
    Lee, C., Roy, M.: Analysis of alternative splicing with microarrays: successes and challenges. Genome Biology 5, 231 (2004)CrossRefGoogle Scholar
  13. 13.
    Lee, C., Wang, Q.: Bioinformatics analysis of alternative splicing. Briefings in Bioinformatics 6, 23–33 (2005)CrossRefGoogle Scholar
  14. 14.
    Castle, J., Garrett-Engele, P., Armour, C.D., Duenwald, S.J., Loerch, P.M., Meyer, M.R., Schadt, E.E., Stoughton, R., Parrish, M.L., Shoemaker, D.D., Johnson, J.M.: Optimization of oligonucleotide arrays and RNA amplification protocols for analysis of transcript structure and alternative splicing. Genome Biology 4, R66 (2003)CrossRefGoogle Scholar
  15. 15.
    Modrek, B., Lee, C.: A genomic view of alternative splicing. Nature Genetics 30, 13–19 (2002)CrossRefGoogle Scholar
  16. 16.
    Tabuchi, K., Südhof, T.C.: Structure and evolution of neurexins: insight into the mechanism of alternative splicing. Genomics 79, 849–859 (2002)CrossRefGoogle Scholar
  17. 17.
    Frank, N.Y., Margaryan, A., Huang, Y., Schatton, T., Waaga-Gasser, A.M., Gassser, M., Sayegh, M.H., Sadee, W., Frank, M.H.: ABCB5-mediated doxorubicin transport and chemoresistance in human malignant melanoma. Cancer Research 65, 4320–4333 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Paul Jenkins
    • 1
  • Rune Lyngsø
    • 1
  • Jotun Hein
    • 1
  1. 1.Dept. of StatisticsOxford UniversityOxfordUnited Kingdom

Personalised recommendations