Agricultural Reviews

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Agricultural Reviews, volume 38 issue 4 (december 2017) : 271-281

Transcriptome profiling: methods and applications- A review

Bibha Rani, V.K. Sharma
1Rajendra Agricultural University, Pusa, Samastipur-848 125, Bihar, India.
Cite article:- Rani Bibha, Sharma V.K. (2017). Transcriptome profiling: methods and applications- A review. Agricultural Reviews. 38(4): 271-281. doi: 10.18805/ag.R-1549.
Global transcriptional profiling is a powerful tool that can expose expression patterns to define cellular states or to identify genes with similar expression patterns. In recent years, transcriptome profiling has been widely used to understand the genetic regulation of a particular cell type. Transcriptome is defined as a full range of messenger Ribonucleic acid (RNA) molecule expressed by an organism. In other words a transcriptome represents the small percentage of genetic code that is transcribed into RNA molecules. It can offer valuable information on the significant biological processes behind the maintenance of the functionality of the cell. Transcriptomics provides fundaments for more definitively designed studies and guidance to select the genes for functional studies. The technology for the study of the transcriptome is not dependent on any prior knowledge of the genes expressed in the cells. However, with regards to the administration and interpretation of the enormous data provided by transcriptome profiling challenges remain.. Four methods have been reviewed here that is, Microarray technology, Serial Analysis of Gene Expression (SAGE), RNA sequencing (RNA-Seq) and Massively Parallel Signature Sequencing (MPSS). The use of these technologies to analyse the expressed transcripts in several prokaryotic and eukaryotic genomes has revealed the high complexity of transcriptomes.
  1. Barbazuk, W.B., Emrich, S.J., Chen, L.L., Schnable, P.S. (2007). SNP discovery via 454 transcriptome sequencing. Plant Journal, 51: 910–918.
  2. Berget, S.M., Moore, C., Sharp, P.A. (1977).Spliced segments at the 52 terminus of adenovirus 2 late mRNA. Proceedings of Natural Acadamic Science, 74:3171–3175.
  3. Bradford, J.R., Hey, Y., Yates, T., Li, Y., Pepper, S.D., Miller, C.J. (2010). A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling. BMC Genomics, 11: 282-294.
  4. Brenner, S., Johnson, M., Bridgham, J., Golda, G., Lloyd, D.H., Johnson, D., Luo, S., et al. (2000). Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays. Nature Biotechnology. 18: 630-634.
  5. Brett, D., Pospisil, H., Valcarcel, J., Reich, J., Bork, P. (2002).Alternative splicing and genome complexity. Nature Genetics, 30:29–30.
  6. Byers, R.J., Hoyland, J.A., Dixon, J., Freemont, A.J. (2002). Subtractive hybridization -genetic takeaways and the search for meaning. International Journal of Experimental Pathology, 81: 391-404.
  7. Cloonan, N., Forrest, A.R.R., Kolle, G., Gardiner, B.B.A., Faulkner, G.J., Brown, M.K., et al. (2008). Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nature Methods, 5 (7): 613 – 619.
  8. Danila, A.L., Laborde, L., Legrand, S., Huot, L., Hot, D., Lemoine, Y., Hilbert, J.L., et al. (2010). (Identification of novel genes potentially involved in somatic embryogenesis in chicory (Cichorium intybus L.). BMC Plant Biology, 10: 122-137.
  9. Dubey, A., Farmer, A., Schlueter, J., Cannon, S.B., Abernathy, B., Tuteja, R., Woodward, J., Shah, T., et al. (2011). Defining the transcriptome assembly and its use for genome dynamics and transcriptome profiling studies in pigeonpea (Cajanus cajan L.). DNA Research, 18: 153–164.
  10. Early, P., Rogers, J., Davis, M., Calame, K., Bond, M., Wall, R., Hood, L. (1980). Two mRNAs can be produced from a single immunoglobulin mu gene by alternative RNA processing pathways. Cell, 20:313–319.
  11. Eisen, M.B., Spellman, P.T., Brown, P.O., Botstein, D. (1998). Cluster analysis and display of genome-wide expression patterns. Proceeding of Natural Acadamy of Science, 95: 14863–14868.
  12. Eveland AL, McCarty DR, Koch KE (2008) Transcript profiling by 32 -untranslated region sequencing resolves expression of gene families. Plant Physiol. 146:32–44.
  13. Gopalakrishnan S, Upadhyaya HD, Vadlamudi S, Humayun P, Vidya MS, Alekhya G, et al. (2012) Plant growth-promoting traits of biocontrol potential bacteria isolated from rice rhizosphere. Springerplus 1:71.
  14. Harrington, C.A., Rosenow, C., Retief, J. (2000).Monitoring gene expression using DNA microarrays.Current Opinion in Microbiology, 3:285–291.
  15. He, Y., Vogelstein, B., Velculescu, V.E., Papadopoulos, N., Kinzler, K.W. (2008). The antisense transcriptomes of human cells. Science, 322:1855–1857.
  16. Henry RJ, Edwards M, Waters DLE, GopalaKrishnan S, Bundock P, Sexton TR, Masouleh AK, Nock CJ, Pattemore J (2012) Application of large-scale sequencing to marker discovery in plants. Biosciences J. 37(5): 829-841.
  17. Hiremath, P.J., Farmer, A., Cannon, S.B., Woodward, J., Kudapa, H., Tuteja, R., Kumar, A., BhanuPrakash, A., et al. (2011). Large-    scale transcriptome analysis of chickpea ( Cicer arietinum L.) an orphan legume crop of the semi-arid tropics of Asia and Africa. Journal of Plant Biotechnology, 9:922–931.
  18. Ingolia NT, Ghaemmaghami S, Newman JRS, Weissman JS (2009) Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324:218–223.
  19. Jiang, H., and Wong, W.H. (2009). Statistical inferences for isoform expression in RNA-Seq. Bioinfo. 25(8): 1026-1032
  20. Jiang, Y., Harlocker, S.L., Molesh, D.A., Dillon, D.C., Houghton, R.L., Repasky, E.A. et al. (2002). Discovery of differentially expressed genes in human breast cancer using subtracted cDNA libraries and cDNA microarrays. Oncogene, 21:2270 – 2282.
  21. Kim, E., Magen, A., Ast, G. (2007). Different levels of alternative splicing among eukaryotes. Nucleic Acids Reearch, 35:125–131.
  22. Lee, J.Y., Lee, D.H. (2003). Use of serial analysis of gene expression technology to reveal changes in gene expression in Arabidopsis pollen undergoing cold stress. Plant Physiology, 132: 517-529.
  23. Levin, J.Z., Yassour, M., Adiconis, X., Nusbaum, C., Thompson, D.A., Friedman, N., Gnirke, A., Regev, A. (2010). Comprehensive comparative analysis of strand-specific RNA sequencing methods. Nature Methods 7(9): 709–715.
  24. Lievens S, Goormachtig S, Holsters M (2001) A critical evaluation of differential display as a tool to identify genes involved in legume nodulation: looking back and looking forward. Nucleic Acids Res 17: 3459–3468.
  25. Meyers, B.C., Lee, D.K., Vu, T.H., Tej, S.S., Edberg, S.B., Matvienko, M. ,Tindell, L.D. (2004). Arabidopsis MPSS: An online resource for quantitative expression analysis. Plant Physiology, 135: 801–813.
  26. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5:621–628.
  27. Nagalakshmi U, Wang Z, Waern K, Shou C, Raha D, Gerstein M, Snyder M (2008). The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320(5881):1344-1349.
  28. Patino, W.D., Mian, O.Y., Hwang, P.M. (2002). Serial analysis of gene expression technical considerations and applications to cardiovascular biology. Circular research, 91: 565-569.
  29. Reddy, A.S. (2007). Alternative splicing of pre-messenger RNAs in plants in the genomic era. Annu. Rev. Plant Biol. 58:267–294.
  30. Rosenfeld, M.G., Lin, C.R., Amara, S.G., Stolarsky, L., Roos, B.A., Ong, E.S., Evans, R.M. (1982). Calcitonin mRNA polymorphism: Peptide switching associated with alternative RNA splicing events. Proceedings of Natural and Academic Science, 79:1717–1721.
  31. Sharp, P.A. (1994). Split genes and RNA splicing. Cell, 77: 805–815.
  32. Sorek, R., Ast, G. (2003). Intronic sequences flanking alternatively spliced exons are conserved between human and mouse. Genome Research, 13:1631–1637.
  33. Staley,J.P., Guthrie, C. (1998). Mechanical devices of the spliceosome: Motors, clocks, springs, and things. Cell, 92:315–326.
  34. Sultan, M., Schulz, M.H., Richard, H., et. al. (2008). A Global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science, 321(5891): 956-960.
  35. Trick, M., Long, Y., Meng, J., Bancroft, I. (2009). Single nucleotide polymorphism (SNP) discovery in the polyploidy Brassica napus using Solexa transcriptome sequencing. Journal of Plant Biotechnology, 7:334–346.
  36. Virlon, B., Cheval, L., Buhler, J.M., Billon, E., Doucet, A.J., Elalouf, J.M. (1999). Serial microanalysis of renal transcriptomes. Proceedings of Natural and Academic Science, 96:5286–15291.
  37. Wang, B.B. and Brendel, V. (2006). Genomewide comparative analysis of alternative splicing in plants. PNAS. 103(18):7175-7180.
  38. Wang, Z., Gerstein, M., Snyder, M. (2009). RNA-Seq: a revolutionary tool for transcriptomics. Nature Review Genetics, 10(1):57–63.
  39. Wu, M., Tu, T., Huang, Y., Wu, Y.C. (2013). Suppression subtractive hybridization identified differentially expressed genes in lung adenocarcinoma: ERGIC3 as a novel lung cancerrelated gene. BMC Cancer, 13:44-54.
  40. Wu, X., Ren, C., Joshi, T., Vuong, T., Xu, D., Nguyen, H.T. (2010). SNP discovery by high-throughput sequencing in soybean. BMC Genomics, 11: 469.
  41. Xing, Y. and Lee, C. (2006). Alternative splicing and RNA selection pressure - evolutionary consequences for eukaryotic genomes. Nature Review Genetics, 7:499–509.

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