Bioinformatics Strategies for Identifying Regions of Epigenetic Deregulation Associated with Aberrant Transcript Splicing and RNA-editing

Mia D. Champion, Ryan A. Hlady, Huihuang Yan, Jared Evans, Jeff Nie, Jeong-Heon Lee, James M. Bogenberger, Kannabiran Nandakumar, Jaime Davila, Raymond Moore, Asha Nair, Daniel O'Brien, Yuan-Xiao Zhu, K. Martin Kortüm, Tamas Ordog, Zhiguo Zhang, Richard W. Joseph, A. Keith Stewart, Jean-Pierre Kocher, Eric Jonasch, Keith D. Robertson, Raoul Tibes, Thai H. Ho


Epigenetic modifications are associated with the regulation of co/post-transcriptional processing and differential transcript isoforms are known to be important during cancer progression. It remains unclear how disruptions of chromatin-based modifications contribute to tumorigenesis and how this knowledge can be leveraged to develop more potent treatment strategies that target specific isoforms or other products of the co/post-transcriptional regulation pathway. Rapid developments in all areas of next-generation sequencing (DNA, RNA-seq, ChIP-seq, Methyl-CpG, etc.) have provided new opportunities to develop novel integration and data-mining approaches, and also allows for exciting hypothesis driven bioinformatics and computational studies. Here, we present a program that we developed and summarize the results of applying our methods to analyze datasets from patient matched tumor or normal (T/N) paired samples, as well as cell lines that were either sensitive or resistant (S/R) to treatment with an anti-cancer drug, 5-Azacytidine ( We discuss additional options for user-defined approaches and general guidelines for simultaneously analyzing and annotating epigenetic and RNA-seq datasets in order to identify and rank significant regions of epigenetic deregulation associated with aberrant splicing and RNA-editing.


  1. Ast, G., 2004. How did alternative splicing evolve?, Nat Rev Genet, vol. 5, no. 10, pp. 773-782.
  2. Athanasiadis, A, Rich, A & Maas, S., 2004. Widespread A-to-I RNA editing of Alu-containing mRNAs in the human transcriptome. , PLoS Biol, vol. 2, p. e391.
  3. Bazak, L, Haviv, A, Barak, M, Jacob-Hirsch, J, Deng, P, Zhang, R, Isaacs, FJ, Rechavi, G, Li, JB, Eisenberg, E & Levanon, EY., 2014. A-to-I RNA editing occurs at over a hundred million genomic sites, located in a majority of human genes, Genome Res., vol. 24, pp. 365-376.
  4. Bioconductor Software Packages. Accessed November, 2014. Available from : <
  5. Champion, MD., Accessed November, 2014. ChIP-RNAseqPRO: A strategy for identifying regions of epigenetic deregulation associated with aberrant transcript splicing and RNA-editing sites. Available from: <>.
  6. Chen, L, Li, Y, Lin, CH, Chan, TH, Chow, RK, Song, Y, Liu, M, Yuan, YF, Fu, L, Kong, KL, Qi, L, Li, Y & Zhang N, TA, Kwong DL, Man K, Lo CM, Lok S, Tenen DG, Guan XY., 2013. Recoding RNA editing of AZIN1 predisposes to hepatocellular carcinoma., Nature Medicine, vol. 19, no. 2, pp. 209-16.
  7. Choudhury, Y, Tay, FC, Lam, DH, Sandanaraj, E, Tang, C, Ang, BT & Wang, S., 2012. Attenuated adenosineto-inosine editing of microRNA-376a* promotes invasiveness of glioblastoma cells., J Clin Invest, vol. 122, no. 11, pp. 4059-76.
  8. Cieslik, M & Bekiranov, S., 2014. Combinatorial epigenetic patterns as quantitative predictors of chromatin biology., BMC Genomics, vol. 15, p. 76.
  9. The ENCODE Project Consortium, 2011. A users guide to the encyclopedia of DNA elements (ENCODE)., PLoS Biol, vol. 9, no. 4, p. e1001046.
  10. dbSNP. version 137. Accessed November, 2014. Available from: <>
  11. ESP6500. Accessed November, 2014. Available from: <>.
  12. Eswaran, J, Horvath, A, Godbole, S, Reddy, SD, Mudvari, P, Ohshiro, K, Cyanam, D, Nair, S , Fuqua, SAW, Polyak, K, Florea, LD, Kumar, R., 2013. RNA sequencing of cancer reveals novel splicing alterations, Scientific Reports, vol. 3, p. 1689.
  13. Feinberg, AP, Ohlsson, R & Henikoff, S., 2006. The epigenetic progenitor origin of human cancer, Nature, vol. 7, pp. 21-33.
  14. Feschotte, C., 2008. Transposable elements and the evolution of regulatory networks., Nat Rev Genet, vol. 9, pp. 397-405.
  15. Frischmeyer, PA & Dietz, HC., 1999. Nonsense-mediated mRNA decay in health and disease., Hum Mol Genet, vol. 8, no. 10, pp. 1893-900.
  16. Gardner, LB., 2011. Nonsense mediated RNA decay regulation by cellular stress; implications for tumorigenesis, Mol Cancer Res, vol. 8, no. 3, pp. 295- 308.
  17. HapMap. Accessed November, 2014. Available from: <>
  18. Huda, A, Mariño-Ramírez, L & Jordan, IK., 2010. Epigenetic histone modifications of human transposable elements: genome defense versus exaptation., Mob DNA. , vol. 1, no. 1.
  19. Illumina. Infinium Human Methylation450 Bead Chip. Accessed November, 2014. Available from: < s/datasheet_humanmethylation450.pdf>.
  20. Jiang, H & Wong, WH., 2009. Statistical inferences for isoform expression in RNA-Seq, Bioinformatics, vol. 25, no. 8, pp. 1026-1032.
  21. Jin, B, Ernst, J, Tiedemann, RL, Xu, H, Sureshchandra, S, Kellis, M, Dalton, S, Liu, C, Choi, JH & Robertson, KD., 2012. Linking DNA methyltransferases to epigenetic marks and nucleosome structure genomewide in human tumor cells., Cell Rep, vol. 2, no. 5, pp. 1411-24.
  22. Kidwell, MG & Lisch, DR., 2000. Transposable elements and host genome evolution, Trends Ecol Evol, vol. 15, pp. 95-99.
  23. Kim, DD, Kim, TT, Walsh, T, Kobayashi, Y, Matise, TC, Buyske, S & Gabriel, A., 2004. Widespread RNA editing of embedded alu elements in the human transcriptome., Genome Res., vol. 14, no. 9, pp. 1719- 25.
  24. Kiran, A & Baranov, PV., 2010. DARNED: a DAtabase of RNa EDiting in humans., Bioinformatics, vol. 26, no. 14, pp. 1772-6.
  25. Levanon, E, Eisenberg, Y, Yelin, E, Nemzer, R, Hallengger, M, Shemesh, R, Fligelman, ZY, Shoshan, A, Pollock, SR & Sztybel, D., 2004. Systematic identification of abundant A-to-I editing sites in the human transcriptome, Nat Biotechnol, vol. 22, pp. 1001-1005.
  26. Li, B, Ruotti, V, Stewart, RM, Thomson, JA & Dewey, CN., 2010. RNA-Seq gene expression estimation with read mapping uncertainty, Bioinformatics, vol. 26, no. 4, pp. 493-500.
  27. Li, JB, Levanon, EY, Yoon, JK, Aach, J, Xie, B, Leproust, E, Zhang, K, Gao, Y & Church, GM., 2009. Genomewide identification of human RNA editing sites by parallel DNA capturing and sequencing., Science, vol. 324, no. 5931, pp. 1210-3.
  28. Luco, RF, Pan, Q, Tominaga, K, Blencowe, BJ, PereiraSmith, OM & Misteli, T., 2010. Regulation of alternative splicing by histone modifications., Science, vol. 327, no. 5968, pp. 996-1000.
  29. Makalowski, W, Mitchell, GA & Labuda, D., 1994. Alu sequences in the coding regions of mRNA: a source of protein
  30. variability. , Trends Genet, vol. 10, pp. 188-193.
  31. Maksimovic, J, Gordon, L & Oshlack, A., 2012. SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips., Genome Biol, vol. 13, no. 6, p. R44.
  32. Nicolae, M, Mangul, S, Mandoiu, II & Zelikovsky, A., 2011. Estimation of alternative splicing isoform frequencies from RNA-Seq data., Algorithms Mol Biol, vol. 6, no. 1, p. 9.
  33. Paz, N, Levanon, EY, Amariglio, N, Heimberger, AB, Ram, Z, Constantini, S, Barbash, ZS, Adamsky, K, Safran, M, Hirschberg, A, Krupsky, M, Ben-Dov, I, Cazacu, S, Mikkelsen, T, Brodie, C, Eisenberg, E & Rechavi, G., 2007. Altered adenosine-to-inosine RNA editing in human cancer., Genome Res., vol. 17, no. 11, pp. 1586-95.
  34. Pepke, S, Wold, BJ & Mortazavi, A., 2014. Computation for ChIP-seq and RNA-seq studies, Nat Methods, vol. 6, no. 11, pp. S22-S32.
  35. Ramaswami, G & Li, JB., 2014. RADAR: a rigorously annotated database of A-to-I RNA editing, Nucleic Acids Res. , vol. 42, no. (Database Issue), pp. D109- 13.
  36. Rueter, SM, Dawson, TR & Emeson, RB., 1999. Regulation of alternative splicing by RNA editing, Nature, vol. 399, pp. 75-80.
  37. Simon, JM, Hacker, KE, Singh, D, Brannon, AR, Parker, JS, Weiser, M, Ho, TH, Kuan, PF, Jonasch, E, Furey, TS, Prins, JF, J.D., L, Rathmell, WK & Davis, IJ., 2014. Variation in chromatin accessibility in human kidney cancer links H3K36 methyltransferase loss with widespread RNA processing defects., Genome Res., vol. 24, no. 2, pp. 241-50.
  38. Trapnell, C, Williams, BA, Pertea, G, Mortazavi, A, Kwan, G, van Baren, MJ, Salzberg, SL, Wold, BJ & Pachter, L., 2010. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation., Nat Biotechnol, vol. 28, no. 5, pp. 511-5.
  39. Veloso, A, Kirkconnell, KS, Magnuson, B, Biewen, B, Paulsen, MT, Wilson, TE & Ljungman, M., 2014. Rate of elongation by RNA polymerase II is associated with specific gene features and epigenetic modifications, Genome Res., vol. 24, no. 6, pp. 896- 905.
  40. Wang, C, Davila, JI, Baheti, S, Bhagwate, AV, Wang, X, Kocher, JP, Slager, SL, Feldman, AL, Novak, AJ, Cerhan, JR, Thompson, EA & Asmann, YW., 2014. RVboost: RNA-Seq variants prioritization using a boosting method., Bioinformatics.
  41. Wang, IX, So, E, Devlin, JL, Zhao, Y, Wu, M & Cheung, VG., 2013. ADAR regulates RNA editing, transcript stability, and gene expression., Cell Rep, vol. 5, no. 3, pp. 849-60.
  42. Zang, C, Schones, DE, Zeng, C, Cui, K, Zhao, K & Peng, W., 2009. A clustering approach for identification of enriched domains from histone modification ChIP-Seq data, Bioinformatics, vol. 25, pp. 1952-1958.
  43. Zhao, Q, Caballero, OL, Davis, ID, Jonasch, E, Tamboli, P, Yung, WK, Weinstein, JN & Yao, J., 2013. Tumorspecific isoform switch of the fibroblast growth factor receptor 2 underlies the mesenchymal and malignant phenotypes of clear cell renal cell carcinomas., Clin Cancer Res., vol. 19, no. 9, pp. 2460-72.
  44. Zhao, S, Fung-Leung, W-P, Bittner, A, Ngo, K & Liu, X., 2014. Comparison of RNA-Seq and Microarray in Transcriptome Profiling of Activated T Cells, PLoS One, vol. 9, no. 1, p. e'644.

Paper Citation

in Harvard Style

Champion M., Hlady R., Yan H., Evans J., Nie J., Lee J., Bogenberger J., Nandakumar K., Davila J., Moore R., Nair A., O'Brien D., Zhu Y., Kortüm K., Ordog T., Zhang Z., Joseph R., Stewart A., Kocher J., Jonasch E., Robertson K., Tibes R. and H. Ho T. (2015). Bioinformatics Strategies for Identifying Regions of Epigenetic Deregulation Associated with Aberrant Transcript Splicing and RNA-editing . In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015) ISBN 978-989-758-070-3, pages 163-170. DOI: 10.5220/0005248001630170

in Bibtex Style

author={Mia D. Champion and Ryan A. Hlady and Huihuang Yan and Jared Evans and Jeff Nie and Jeong-Heon Lee and James M. Bogenberger and Kannabiran Nandakumar and Jaime Davila and Raymond Moore and Asha Nair and Daniel O'Brien and Yuan-Xiao Zhu and K. Martin Kortüm and Tamas Ordog and Zhiguo Zhang and Richard W. Joseph and A. Keith Stewart and Jean-Pierre Kocher and Eric Jonasch and Keith D. Robertson and Raoul Tibes and Thai H. Ho},
title={Bioinformatics Strategies for Identifying Regions of Epigenetic Deregulation Associated with Aberrant Transcript Splicing and RNA-editing},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015)},

in EndNote Style

JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015)
TI - Bioinformatics Strategies for Identifying Regions of Epigenetic Deregulation Associated with Aberrant Transcript Splicing and RNA-editing
SN - 978-989-758-070-3
AU - Champion M.
AU - Hlady R.
AU - Yan H.
AU - Evans J.
AU - Nie J.
AU - Lee J.
AU - Bogenberger J.
AU - Nandakumar K.
AU - Davila J.
AU - Moore R.
AU - Nair A.
AU - O'Brien D.
AU - Zhu Y.
AU - Kortüm K.
AU - Ordog T.
AU - Zhang Z.
AU - Joseph R.
AU - Stewart A.
AU - Kocher J.
AU - Jonasch E.
AU - Robertson K.
AU - Tibes R.
AU - H. Ho T.
PY - 2015
SP - 163
EP - 170
DO - 10.5220/0005248001630170