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Identification of Prostate Cancer LncRNAs by RNA-Seq

  • Hu, Cheng-Cheng (Laboratory of Biomedical Engineering, Chongqing Medical University) ;
  • Gan, Ping (Laboratory of Biomedical Engineering, Chongqing Medical University) ;
  • Zhang, Rui-Ying (Laboratory of Biomedical Engineering, Chongqing Medical University) ;
  • Xue, Jin-Xia (Laboratory of Biomedical Engineering, Chongqing Medical University) ;
  • Ran, Long-Ke (Department of Bioinformatics, Chongqing Medical University)
  • Published : 2014.11.28

Abstract

Purpose: To identify prostate cancer lncRNAs using a pipeline proposed in this study, which is applicable for the identification of lncRNAs that are differentially expressed in prostate cancer tissues but have a negligible potential to encode proteins. Materials and Methods: We used two publicly available RNA-Seq datasets from normal prostate tissue and prostate cancer. Putative lncRNAs were predicted using the biological technology, then specific lncRNAs of prostate cancer were found by differential expression analysis and co-expression network was constructed by the weighted gene co-expression network analysis. Results: A total of 1,080 lncRNA transcripts were obtained in the RNA-Seq datasets. Three genes (PCA3, C20orf166-AS1 and RP11-267A15.1) showed a significant differential expression in the prostate cancer tissues, and were thus identified as prostate cancer specific lncRNAs. Brown and black modules had significant negative and positive correlations with prostate cancer, respectively. Conclusions: The pipeline proposed in this study is useful for the prediction of prostate cancer specific lncRNAs. Three genes (PCA3, C20orf166-AS1, and RP11-267A15.1) were identified to have a significant differential expression in prostate cancer tissues. However, there have been no published studies to demonstrate the specificity of RP11-267A15.1 in prostate cancer tissues. Thus, the results of this study can provide a new theoretic insight into the identification of prostate cancer specific genes.

Keywords

References

  1. Birney E, Stamatoyannopoulos JA, Dutta A, et al (2007). Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature, 447, 799-16. https://doi.org/10.1038/nature05874
  2. Bussemakers MJ, Van Bokhoven A, Verhaegh GW, et al (1999). DD3: a new prostate-specific gene highly overexpressed in prostate cancer. Cancer Res, 59, 5975-9.
  3. Cabili MN, Trapnell C, Goff L, et al (2011). Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses. Genes Dev, 25, 1915-27. https://doi.org/10.1101/gad.17446611
  4. Eeles RA, Olama AA, Benlloch S, et al (2013). Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array. Nat Genet, 45, 385-91. https://doi.org/10.1038/ng.2560
  5. Engreitz JM, Pandya-Jones A, McDonel P, et al (2013). The Xist lncRNA Exploits Three-Dimensional Genome Architecture to Spread Across the X Chromosome. Science, 341, 1237973. https://doi.org/10.1126/science.1237973
  6. Finn RD, Tate J, Mistry J, et al (2008). The Pfam protein families database. Nucleic Acids Res, 36, 281-8. https://doi.org/10.1093/nar/gkn226
  7. Furuno M, Kasukawa T, Saito R, et al (2003). CDS Annotation in Full-Length cDNA Sequence. Genome Research, 13, 1478-87. https://doi.org/10.1101/gr.1060303
  8. Garber M, Grabherr MG, Guttman M, et al (2011). Computational methods for transcriptome annotation and quantification using RNA-seq. Nat Meth, 8, 469-77. https://doi.org/10.1038/nmeth.1613
  9. Guttman M, Amit I, Garber M, et al (2009). Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature, 458, 223-7. https://doi.org/10.1038/nature07672
  10. Guttman M, Garber M, Levin JZ, Donaghey J, et al (2010). Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multiexonic structure of lincRNAs. Nat Biotechnol, 28, 503-10. https://doi.org/10.1038/nbt.1633
  11. Hung T, Chang HY (2010). Long noncoding RNA in genome regulation: prospects and mechanisms. RNA Biol, 7, 582-5. https://doi.org/10.4161/rna.7.5.13216
  12. Kanduri C (2008). Functional insights into long antisense noncoding RNA Kcnq1ot1 mediated bidirectional silencing. RNA Biol, 5, 208-11. https://doi.org/10.4161/rna.7113
  13. Kimura K, Wakamatsu A, Suzuki Y, et al (2006). Diversification of transcriptional modulation: large-scale identification and characterization of putative alternative promoters of human genes. Genome Res, 16, 55-65.
  14. Kong L, Zhang Y, Ye ZQ, et al (2007). CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine. Nucleic Acids Research, 35, 345-9. https://doi.org/10.1093/nar/gkm391
  15. Korostowski L, Sedlak N, Engel N (2012). The Kcnq1ot1 long non-coding RNA affects chromatin conformation and expression of Kcnq1, but does not regulate its imprinting in the developing heart. PLoS Genet, 8, 1002956. https://doi.org/10.1371/journal.pgen.1002956
  16. Landers KA, Burger MJ, Tebay MA, et al (2005). Use of multiple biomarkers for amolecular diagnosis of prostate cancer. Int J Cancer, 114, 950-6. https://doi.org/10.1002/ijc.20760
  17. Langfelder P, Horvath S (2008). WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics, 9, 559. https://doi.org/10.1186/1471-2105-9-559
  18. Lee JT (2012). Epigenetic regulation by long noncoding RNAs. Science, 338, 1435-9. https://doi.org/10.1126/science.1231776
  19. Li T, Wang S, Wu R, Zhou X, Zhu D, Zhang Y (2012). Identification of long non-protein coding RNAs in chicken skeletal muscle using next generation sequencing. Genomics, 99, 292-8. https://doi.org/10.1016/j.ygeno.2012.02.003
  20. Lin MF, Jungreis I, Kellis M (2011). PhyloCSF: a comparative genomics method to distinguish protein coding and non-coding regions. Bioinformatics, 27, 275-82. https://doi.org/10.1093/bioinformatics/btq632
  21. Liu JH, Chen G, Dang YW, Li CJ, Luo DZ (2014). Expression and prognostic significance of lncRNA MALAT1 in pancreatic cancer tissues. Asian Pac J Cancer Prev, 15, 2971-7. https://doi.org/10.7314/APJCP.2014.15.7.2971
  22. Lv J, Cui W, Liu H, et al (2013).Identification and characterization of long non-coding RNAs related to mouse embryonic brain development fromavailable transcriptomic data. PLoS One, 8, 71152. https://doi.org/10.1371/journal.pone.0071152
  23. Marioni JC, Mason CE, Mane SM, Stephens M, Gilad Y (2008). RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays. Genome Res, 18, 1509-17. https://doi.org/10.1101/gr.079558.108
  24. Martin JA, Wang Z (2011). Next-generation transcriptome assembly. Nat Rev Genet, 12, 671-82. https://doi.org/10.1038/nrg3068
  25. Mercer TR, Dinger ME, Mattick JS (2009). Long non-coding RNAs: insights into functions. Nat Rev Genet, 10, 155-9. https://doi.org/10.1038/nrg2521
  26. Nagano T, Mitchell JA, Sanz LA, et al (2008). The Air noncoding RNA epigenetically silences transcription by targeting G9a to chromatin. Science, 322, 1717-20. https://doi.org/10.1126/science.1163802
  27. Orom UA, Derrien T, Beringer M, et al (2010). Long noncoding RNAs with enhancer-like function in human cells. Cell, 143, 46-58. https://doi.org/10.1016/j.cell.2010.09.001
  28. Pauli A, Rinn JL, Schier AF (2011). Non-coding RNAs as regulators of embryogenesis. Nat Rev Genet, 12, 136-49.
  29. Ponjavic J, Ponting CP, Lunter G (2007). Functionality or transcriptional noise? Evidence for selection within long noncoding RNAs. Genome Res, 17, 556-65. https://doi.org/10.1101/gr.6036807
  30. Ponting CP, Oliver L, Reik W (2009). Evolution and functions of long noncoding RNAs. Cell, 136, 629-41. https://doi.org/10.1016/j.cell.2009.02.006
  31. Qiao HP, Gao WS, Huo JX, Yang ZS (2013). Long non-coding RNA GAS5 functions as a tumor suppressor in renal cell carcinoma. Asian Pac J Cancer Prev, 14, 1077-82. https://doi.org/10.7314/APJCP.2013.14.2.1077
  32. Trapnell C, Pachter L, Salzberg SL (2009). TopHat: discovering splice junctions with RNA-Seq. Bioinformatics, 25, 1105-11. https://doi.org/10.1093/bioinformatics/btp120
  33. Trapnell C, Roberts A, Goff L, et al (2012). Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc, 7, 562-78. https://doi.org/10.1038/nprot.2012.016
  34. Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, et al (2010). Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol, 28, 511-5. https://doi.org/10.1038/nbt.1621
  35. Wang Z, Gerstein M, Snyder M (2009). RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet, 10, 57-63. https://doi.org/10.1038/nrg2484
  36. Ye N, Wang B, Quan ZF, et al (2014). Functional Roles of Long Non-coding RNA in Human Breast Cancer. Asian Pac J Cancer Prev, 15, 5993-7. https://doi.org/10.7314/APJCP.2014.15.15.5993
  37. Zhang Q, Geng PL, Yin P, et al (2013). Down-regulation of long non-coding RNA TUG1 inhibits osteosarcoma cell proliferation and promotes apoptosis. Asian Pac J Cancer Prev, 14, 2311-5. https://doi.org/10.7314/APJCP.2013.14.4.2311

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