Journal of Integrative Bioinformatics (Sep 2017)

Computer Analysis of Glioma Transcriptome Profiling: Alternative Splicing Events

  • Babenko Vladimir N.,
  • Gubanova Natalya V.,
  • Bragin Anatoly O.,
  • Chadaeva Irina V.,
  • Vasiliev Gennady V.,
  • Medvedeva Irina V.,
  • Gaytan Alexey S.,
  • Krivoshapkin Alexey L.,
  • Orlov Yuriy L.

DOI
https://doi.org/10.1515/jib-2017-0022
Journal volume & issue
Vol. 14, no. 3
pp. 513 – 26

Abstract

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Here we present the analysis of alternative splicing events on an example of glioblastoma cell culture samples using a set of computer tools in combination with database integration. The gene expression profiles of glioblastoma were obtained from cell culture samples of primary glioblastoma which were isolated and processed for RNA extraction. Transcriptome profiling of normal brain samples and glioblastoma were done by Illumina sequencing. The significant differentially expressed exon-level probes and their corresponding genes were identified using a combination of the splicing index method. Previous studies indicated that tumor-specific alternative splicing is important in the regulation of gene expression and corresponding protein functions during cancer development. Multiple alternative splicing transcripts have been identified as progression markers, including generalized splicing abnormalities and tumor- and stage-specific events. We used a set of computer tools which were recently applied to analysis of gene expression in laboratory animals to study differential splicing events. We found 69 transcripts that are differentially alternatively spliced. Three cancer-associated genes were considered in detail, in particular: APP (amyloid beta precursor protein), CASC4 (cancer susceptibility candidate 4) and TP53. Such alternative splicing opens new perspectives for cancer research.

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