Abstract
In this paper we address the problem of characterizing the RNA complement of a given cell type, that is, the set of RNA species and their relative copy number, from a large set of short sequence reads which have been randomly sampled from the cell’s RNA sequences through a sequencing experiment. We refer to this problem as the transcriptome reconstruction problem, and we specifically investigate, both theoretically and practically, the conditions under which the problem can be solved. We demonstrate that, even under the assumption of exact information, neither single read nor paired-end read sequences guarantee theoretically that the reconstruction problem has a unique solution. However, by investigating the behavior of the best annotated human gene set, we also show that, in practice, paired-end reads – but not single reads – may be sufficient to solve the vast majority of the transcript variants species and abundances. We finally show that, when we assume that the RNA species existing in the cell are known, single read sequences can effectively be used to infer transcript variant abundances.
This is a preview of subscription content, log in via an institution to check access.
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
Adams, M.D., et al.: Complementary DNA sequencing: expressed sequence tags and human genome project. Science 252(5013), 1651–1656 (1991)
Bellin, D., Werber, M., Theis, T., Schulz, B., Weisshaar, B., Schneider, K.: EST Sequencing, Annotation and Macroarray Transcriptome Analysis Identify Preferentially Root-Expressed Genes in Sugar Beet. Plant Biology 4(6), 700–710 (2002)
Bennett, S.T., Barnes, C., Cox, A., Davies, L., Brown, C.: Toward the 1,000 dollars human genome. Pharmacogenomics 6, 373–382 (2005)
Chen, J., Skiena, S.: Assembly For Double-Ended Short-Read Sequencing Technologies. In: Mardis, E., Kim, S., Tang, H. (eds.) Advances in Genome Sequencing Technology and Algorithms. Artech House Publishers (2007)
De Bona, F., Ossowski, S., Schneeberger, K., Rätsh, G.: Optimal Spliced Alignments of Short Sequence Reads. Bioinformatics (in press, 2008)
ENCODE Project Consortium. Identification and analysis of functional elements in 1 % of the human genome by the ENCODE pilot project. Nature 447, 799–816 (2007)
Harrow, J., et al.: GENCODE: producing a reference annotation for ENCODE. Genome Biology 7, S4 (2006)
Heber, S., Alekseyev, M., Sze, S.H., Tang, H., Pevzner, P.A.: Splicing graphs and EST assembly problem. Bioinformatics 18 (suppl. 1), 181–188 (2002)
Hoffmann, K.F., Dunne, D.W.: Characterization of the Schistosoma transcriptome opens up the world of helminth genomics. Genome Biology 5, 203 (2003)
Houde, M., et al.: Wheat EST resources for functional genomics of abiotic stress. BMC Genomics 7, 149 (2006)
Lander, E.S., et al.: Initial sequencing and analysis of the human genome. Nature 409(6822), 860–921 (2001)
Mironov, A.A., Fickett, J.W., Gelfand, M.S.: Frequent alternative splicing of human genes. Genome Research 9, 1288–1293 (1999)
Modrek, B., Resch, A., Grasso, C., Lee, C.: Genome-wide detection of alternative splicing in expressed sequences of human genes. Nucleic Acids Research 29, 2850–2859 (2001)
Pruitt, K.D., Tatusova, T., Maglott, D.R.: NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Research. 35, D61-D65 (2007)
Sammeth, M., Foissac, S., Guigo, R.: A General Definition and Nomenclature for Alternative Splicing Events. PLoS Computational Biology (in press, 2008)
Sammeth, M., Valiente, G., Guigo, R.: Bubbles: Alternative Splicing Events of Arbitrary Dimension in Splicing Graphs. In: Vingron, M., Wong, L. (eds.) RECOMB 2008. LNCS (LNBI), vol. 4955, pp. 372–395. Springer, Heidelberg (2008)
Sugnet, C.W., Kent, W.J., Ares, M., Haussler, D.: Transcriptome and genome conservation of alternative splicing events in humans and mice. In: Proceedings of the Pacific Symposium on Biocomputing, vol. 9, pp. 66–77 (2004)
Weber, A., Weber, K., Carr, K., Wilkerson, C., Ohlrogge, J.: Sampling the Arabidopsis Transcriptome with Massively Parallel Pyrosequencing. Plant Physiology 144, 32–42 (2007)
Xing, Y., Resch, A., Lee, C.: The multiassembly problem: reconstructing multiple transcript isoforms from EST fragment mixtures. Genome Research 14(3), 426–441 (2004)
Xing, Y., Yu, T., Wu, Y.N., Roy, M., Kim, J., Lee, C.: An expectation-maximization algorithm for probabilistic reconstructions of full-length isoforms from splice graphs. Nucleic Acids Research 34, 3150–3160 (2006)
Zerbino, D., Birney, E.: Velvet: Algorithms for de novo short read assembly using de Bruijn Graphs. Genome Research 18, 821–829 (2008)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lacroix, V., Sammeth, M., Guigo, R., Bergeron, A. (2008). Exact Transcriptome Reconstruction from Short Sequence Reads. In: Crandall, K.A., Lagergren, J. (eds) Algorithms in Bioinformatics. WABI 2008. Lecture Notes in Computer Science(), vol 5251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87361-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-540-87361-7_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87360-0
Online ISBN: 978-3-540-87361-7
eBook Packages: Computer ScienceComputer Science (R0)