Abstract
During the last years the technology used for gene expression analysis has changed dramatically. The old mainstay, DNA microarray, has served its due course and will soon be replaced by next-generation sequencing (NGS), the Swiss army knife of modern high-throughput nucleic acid-based analysis. Therefore preparation technologies have to adapt to suit the emerging NGS technology platform. Moreover, interpretation of the results is still time consuming and employs the use of high-end computers usually not found in molecular biology laboratories. Alternatively, cloud computing might solve this problem. Nevertheless, these new challenges have to be embraced for gene expression analysis in general.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Grützmann R, Boriss H, Ammerpohl O, Lüttges J, Kalthoff H, Schackert HK, Klöppel G, Saeger HD, Pilarsky C (2005) Meta-analysis of microarray data on pancreatic cancer defines a set of commonly dysregulated genes. Oncogene 24(32):5079–5088. doi:10.1038/sj.onc.1208696
Alldinger I, Dittert D, Peiper M, Fusco A, Chiappetta G, Staub E, Lohr M, Jesnowski R, Baretton G, Ockert D, Saeger HD, Grutzmann R, Pilarsky C (2005) Gene expression analysis of pancreatic cell lines reveals genes overexpressed in pancreatic cancer. Pancreatology 5(4–5):370–379. doi:10.1159/000086537
Grutzmann R, Pilarsky C, Ammerpohl O, Luttges J, Bohme A, Sipos B, Foerder M, Alldinger I, Jahnke B, Schackert HK, Kalthoff H, Kremer B, Kloppel G, Saeger HD (2004) Gene expression profiling of microdissected pancreatic ductal carcinomas using high-density DNA microarrays. Neoplasia 6(5):611–622. doi:10.1593/neo.04295
Volinia S, Calin GA, Liu C-G, Ambs S, Cimmino A, Petrocca F, Visone R, Iorio M, Roldo C, Ferracin M, Prueitt RL, Yanaihara N, Lanza G, Scarpa A, Vecchione A, Negrini M, Harris CC, Croce CM (2006) A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci U S A 103(7):2257–2261. doi:10.1073/pnas.0510565103
Okoniewski MJ, Miller CJ (2006) Hybridization interactions between probesets in short oligo microarrays lead to spurious correlations. BMC Bioinformatics 7:276. doi:10.1186/1471-2105-7-276
Royce TE, Rozowsky JS, Gerstein MB (2007) Toward a universal microarray: prediction of gene expression through nearest-neighbor probe sequence identification. Nucleic Acids Res 35(15):e99. doi:10.1093/nar/gkm549
Klebanov L, Yakovlev A (2007) How high is the level of technical noise in microarray data? Biol Direct 2:9. doi:10.1186/1745-6150-2-9
Kedes L, Campany G (2011) The new date, new format, new goals and new sponsor of the Archon Genomics X PRIZE competition. Nat Genet 43(11):1055–1058. doi:10.1038/ng.988
Ledford H (2015) End of cancer-genome project prompts rethink. Nature 517(7533):128–129. doi:10.1038/517128a
Adams MD, Dubnick M, Kerlavage AR, Moreno R, Kelley JM, Utterback TR, Nagle JW, Fields C, Venter JC (1992) Sequence identification of 2,375 human brain genes. Nature 355(6361):632–634. doi:10.1038/355632a0
Shah SP, Köbel M, Senz J, Morin RD, Clarke BA, Wiegand KC, Leung G, Zayed A, Mehl E, Kalloger SE, Sun M, Giuliany R, Yorida E, Jones S, Varhol R, Swenerton KD, Miller D, Clement PB, Crane C, Madore J, Provencher D, Leung P, DeFazio A, Khattra J, Turashvili G, Zhao Y, Zeng T, Glover JNM, Vanderhyden B, Zhao C, Parkinson CA, Jimenez-Linan M, Bowtell DDL, Mes-Masson A-M, Brenton JD, Aparicio SA, Boyd N, Hirst M, Gilks CB, Marra M, Huntsman DG (2009) Mutation of FOXL2 in granulosa-cell tumors of the ovary. N Engl J Med 360(26):2719–2729. doi:10.1056/NEJMoa0902542
Mastrokolias A, Dunnen JT, Ommen GB, Hoen PAC, Roon-Mom WMC (2012) Increased sensitivity of next generation sequencing-based expression profiling after globin reduction in human blood RNA. BMC Genomics 13(1):28. doi:10.1186/1471-2164-13-28
Mooney M, Bond J, Monks N, Eugster E, Cherba D, Berlinski P, Kamerling S, Marotti K, Simpson H, Rusk T, Tembe W, Legendre C, Benson H, Liang W, Webb CP (2013) Comparative RNA-Seq and microarray analysis of gene expression changes in B-cell lymphomas of Canis familiaris. PLoS One 8(4):e61088. doi:10.1371/journal.pone.0061088
Edgren H, Murumagi A, Kangaspeska S, Nicorici D, Hongisto V, Kleivi K, Rye IH, Nyberg S, Wolf M, Borresen-Dale A-L (2011) Identification of fusion genes in breast cancer by paired-end RNA-sequencing. Genome Biol 12(1)
Kulis M, Esteller M (2010) DNA methylation and cancer. Adv Genet 70:27–56. doi:10.1016/B978-0-12-380866-0.60002-2, B978-0-12-380866-0.60002-2 [pii]
Nakhasi HL, Lynch KR, Dolan KP, Unterman RD, Feigelson P (1981) Covalent modification and repressed transcription of a gene in hepatoma cells. Proc Natl Acad Sci U S A 78(2):834–837
Wissmann C, Wild PJ, Kaiser S, Roepcke S, Stoehr R, Woenckhaus M, Kristiansen G, Hsieh J-C, Hofstaedter F, Hartmann A, Knuechel R, Rosenthal A, Pilarsky C (2003) WIF1, a component of the Wnt pathway, is down-regulated in prostate, breast, lung, and bladder cancer. J Pathol 201(2):204–212. doi:10.1002/path.1449
Slieker RC, Bos SD, Goeman JJ, Bovée JV, Talens RP, van der Breggen R, Suchiman HED, Lameijer E-W, Putter H, van den Akker EB, Zhang Y, Jukema JW, Slagboom PE, Meulenbelt I, Heijmans BT (2013) Identification and systematic annotation of tissue-specific differentially methylated regions using the Illumina 450k array. Epigenetics Chromatin 6(1):26. doi:10.1186/1756-8935-6-26
Sánchez-Vega F, Gotea V, Petrykowska HM, Margolin G, Krivak TC, Deloia JA, Bell DW, Elnitski L (2013) Recurrent patterns of DNA methylation in the ZNF154, CASP8, and VHL promoters across a wide spectrum of human solid epithelial tumors and cancer cell lines. Epigenetics 8(12)
Morris TJ, Butcher LM, Feber A, Teschendorff AE, Chakravarthy AR, Wojdacz TK, Beck S (2013) ChAMP: 450k Chip Analysis Methylation Pipeline. Bioinformatics. doi:10.1093/bioinformatics/btt684
Murphy PJ, Cipriany BR, Wallin CB, Ju CY, Szeto K, Hagarman JA, Benitez JJ, Craighead HG, Soloway PD (2013) Single-molecule analysis of combinatorial epigenomic states in normal and tumor cells. Proc Natl Acad Sci U S A 110(19):7772–7777. doi:10.1073/pnas.1218495110
Lister R, Pelizzola M, Dowen RH, Hawkins RD, Hon G, Tonti-Filippini J, Nery JR, Lee L, Ye Z, Ngo QM, Edsall L, Antosiewicz-Bourget J, Stewart R, Ruotti V, Millar AH, Thomson JA, Ren B, Ecker JR (2009) Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 462(7271):315–322. doi:10.1038/nature08514
Stirzaker C, Taberlay PC, Statham AL, Clark SJ (2013) Mining cancer methylomes: prospects and challenges. Trends Genet 30:75–84. doi:10.1016/j.tig.2013.11.004
Vandewoestyne M, Goossens K, Burvenich C, Van Soom A, Peelman L, Deforce D (2013) Laser capture microdissection: should an ultraviolet or infrared laser be used? Anal Biochem 439(2):88–98. doi:10.1016/j.ab.2013.04.023
Kristiansen G (2010) Manual microdissection. Methods Mol Biol 576:31–38. doi:10.1007/978-1-59745-545-9_2
Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, Martinez P, Matthews N, Stewart A, Tarpey P (2012) Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 366(10):883–892
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media New York
About this protocol
Cite this protocol
Pilarsky, C., Nanduri, L.K., Roy, J. (2016). Gene Expression Analysis in the Age of Mass Sequencing: An Introduction. In: Grützmann, R., Pilarsky, C. (eds) Cancer Gene Profiling. Methods in Molecular Biology, vol 1381. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3204-7_4
Download citation
DOI: https://doi.org/10.1007/978-1-4939-3204-7_4
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-3203-0
Online ISBN: 978-1-4939-3204-7
eBook Packages: Springer Protocols