Changes between Version 1 and Version 2 of Courses/ComputationalMolecularBiologyResearch2016/P3


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Timestamp:
2016-01-29T19:04:34+01:00 (8 years ago)
Author:
Pieter Neerincx
Comment:

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  • Courses/ComputationalMolecularBiologyResearch2016/P3

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     1= Analysis of trans-spliced transcripts in RNA seq data =
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    33== Supervisors ==
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     5Birgit Sikkema-Raddatz and Lennart Johansson 
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    67== Introduction ==
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     9It is known that in eukaryotic cells trans-splicing of pre-mRNAs occurs (1). In case of such trans splicing, fragments of different pre-mRNA molecules are spliced into a single mature molecule. It has been hypothesized that trans-splicing may be involved in cancer development,  by facilitating chromosomal rearrangements (2). We would like to analyse whether  trans-spliced RNA is present in RNA-seq data of healthy subjects.  Various tools to detect fusion transcripts in paired-end RNA-seq data are available (3). 
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    9 == Project 3 - ==
     11== Project 3 ==
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     13In the student research project first a literature search will be performed to complete the list of available tools. Secondly, a theoretical assessment of these tools is done and the most promising tools are chosen for testing. The performance of the selected tools is tested, for instance using a public available data set containing synthetic gene fusions (4). After testing in-house RNA-seq data can be analysed for the presence of fusion RNA molecules that may be created by trans-splicing.
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     15== Refs ==
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     171. Y. Yang and C. Walsh, “Spliceosome-Mediated RNA -splicing,” Mol. Ther., vol. 12, no. 6, pp. 1006–1012, 2005.
     182. P. G. Zaphiropoulos, “Trans-splicing in Higher Eukaryotes: Implications for Cancer Development?,” Front. Genet., vol. 2, no. December, p. 92, 2011.
     193. S. Liu, W.-H. Tsai, Y. Ding, R. Chen, Z. Fang, Z. Huo, S. Kim, T. Ma, T.-Y. Chang, N. M. Priedigkeit, A. V. Lee, J. Luo, H.-W. Wang, I.-F. Chung, and G. C. Tseng, “Comprehensive evaluation of fusion transcript detection algorithms and a meta-caller to combine top performing methods in paired-end RNA-seq data,” Nucleic Acids Res., pp. 1–15, 2015.
     204. W. D. Tembe, S. J. Pond, C. Legendre, H.-Y. Chuang, W. S. Liang, N. E. Kim, V. Montel, S. Wong, T. K. !McDaniel, D. W. Craig, and J. D. Carpten, “Open-access synthetic spike-in mRNA-seq data for cancer gene fusions,” BMC Genomics, vol. 15, no. 1, p. 824, 2014.
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