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Neurodegeneration pp 417–439Cite as

Designing, Performing, and Interpreting a Microarray-Based Gene Expression Study

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 793))

Abstract

Microarray-based assays have significantly expanded their scope and range of applications over the last 10 years, and – at least for gene expression – can be considered mainstream applications. High-throughput, microarray-based gene expression studies have proven particularly useful in the study of neurodegenerative diseases, for which they have provided key insights in understanding disease pathogenesis, regional and cellular specificity, and identification of therapeutic targets. Even though many experimental steps are currently performed in specialized core facilities, the key steps of a microarray study – experimental design, and data analysis and interpretation – are performed by the primary investigator. Knowledge of the issues related to these key steps is essential to properly perform and interpret a microarray experiment and constitutes the main focus of the present chapter. The basic analytical steps are covered, and annotated R code for the analysis of a published dataset is provided.

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References

  1. Schena, M., Shalon, D., Davis, R. W., and Brown, P. O. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science. 270, 467–470.

    Google Scholar 

  2. Shi, L., Reid, L. H., Jones, W. D., Shippy, R., Warrington, J. A., Baker, S. C., Collins, P. J., de Longueville, F., Kawasaki, E. S., Lee, K. Y., Luo, Y., Sun, Y. A., Willey, J. C., Setterquist, R. A., Fischer, G. M., Tong, W., Dragan, Y. P., Dix, D. J., Frueh, F. W., Goodsaid, F. M., Herman, D., Jensen, R. V., Johnson, C. D., Lobenhofer, E. K., Puri, R. K., Schrf, U., Thierry-Mieg, J., Wang, C., Wilson, M., Wolber, P. K., Zhang, L., Amur, S., Bao, W., Barbacioru, C. C., Lucas, A. B., Bertholet, V., Boysen, C., Bromley, B., Brown, D., Brunner, A., Canales, R., Cao, X. M., Cebula, T. A., Chen, J. J., Cheng, J., Chu, T. M., Chudin, E., Corson, J., Corton, J. C., Croner, L. J., Davies, C., Davison, T. S., Delenstarr, G., Deng, X., Dorris, D., Eklund, A. C., Fan, X. H., Fang, H., Fulmer-Smentek, S., Fuscoe, J. C., Gallagher, K., Ge, W., Guo, L., Guo, X., Hager, J., Haje, P. K., Han, J., Han, T., Harbottle, H. C., Harris, S. C., Hatchwell, E., Hauser, C. A., Hester, S., Hong, H., Hurban, P., Jackson, S. A., Ji, H., Knight, C. R., Kuo, W. P., LeClerc, J. E., Levy, S., Li, Q. Z., Liu, C., Liu, Y., Lombardi, M. J., Ma, Y., Magnuson, S. R., Maqsodi, B., McDaniel, T., Mei, N., Myklebost, O., Ning, B., Novoradovskaya, N., Orr, M. S., Osborn, T. W., Papallo, A., Patterson, T. A., Perkins, R. G., Peters, E. H., Peterson, R., Philips, K. L., Pine, P. S., Pusztai, L., Qian, F., Ren, H., Rosen, M., Rosenzweig, B. A., Samaha, R. R., Schena, M., Schroth, G. P., Shchegrova, S., Smith, D. D., Staedtler, F., Su, Z., Sun, H., Szallasi, Z., Tezak, Z., Thierry-Mieg, D., Thompson, K. L., Tikhonova, I., Turpaz, Y., Vallanat, B., Van, C., Walker, S. J., Wang, S. J., Wang, Y., Wolfinger, R., Wong, A., Wu, J., Xiao, C., Xie, Q., Xu, J., Yang, W., Zhong, S., Zong, Y., and Slikker, W., Jr. (2006) The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat Biotechnol. 24, 1151–1161.

    Article  PubMed  CAS  Google Scholar 

  3. Shi, L., Campbell, G., Jones, W., Campagne, F., Wen, Z., Walker, S., Su, Z., Chu, T.-M., Goodsaid, F., Pusztai, L., Shaughnessy, J., Oberthuer, A., Thomas, R., Paules, R., Fielden, M., Barlogie, B., Chen, W., Du, P., Fischer, M., Furlanello, C., Gallas, B., Ge, X., Megherbi, D., Symmans, F., Wang, M., Zhang, J., Bitter, H., Brors, B., Bushel, P., Bylesjo, M., Chen, M., Cheng, J., Cheng, J., Chou, J., Davison, T., Delorenzi, M., Deng, Y., Devanarayan, V., Dix, D., Dopazo, J., Dorff, K., Elloumi, F., Fan, J., Fan, S., Fan, X., Fang, H., Gonzaludo, N., Hess, K., Hong, H., Huan, J., Irizarry, R., Judson, R., Juraeva, D., Lababidi, S., Lambert, C., Li, L., Li, Y., Li, Z., Lin, S., Liu, G., Lobenhofer, E., Luo, J., Luo, W., McCall, M., Nikolsky, Y., Pennello, G., Perkins, R., Philip, R., Popovici, V., Price, N., Qian, F., Scherer, A., Shi, T., Shi, W., Sung, J., Thierry-Mieg, D., Thierry-Mieg, J., Thodima, V., Trygg, J., Vishnuvajjala, L., Wang, S. J., Wu, J., Wu, Y., Xie, Q., Yousef, W., Zhang, L., Zhang, X., Zhong, S., Zhou, Y., Zhu, S., Arasappan, D., Bao, W., Lucas, A. B., Berthold, F., Brennan, R., Buness, A., Catalano, J., Chang, C., Chen, R., Cheng, Y., Cui, J., Czika, W., Demichelis, F., Deng, X., Dosymbekov, D., Eils, R., Feng, Y., Fostel, J., Fulmer-Smentek, S., Fuscoe, J., Gatto, L., Ge, W., Goldstein, D., Guo, L., Halbert, D., Han, J., Harris, S., Hatzis, C., Herman, D., Huang, J., Jensen, R., Jiang, R., Johnson, C., Jurman, G., Kahlert, Y., Khuder, S., Kohl, M., Li, J., Li, M., Li, Q.-Z., Li, S., Li, Z., Liu, J., Liu, Y., Liu, Z., Meng, L., Madera, M., Martinez-Murillo, F., Medina, I., Meehan, J., Miclaus, K., Moffitt, R., Montaner, D., Mukherjee, P., Mulligan, G., Neville, P., Nikolskaya, T., Ning, B., Page, G., Parker, J., Parry, M., Peng, X., Peterson, R., Phan, J., Quanz, B., Ren, Y., Riccadonna, S., Roter, A., Samuelson, F., Schumacher, M., Shambaugh, J., Shi, Q., Shippy, R., Si, S., Smalter, A., Sotiriou, C., Soukup, M., Staedtler, F., Steiner, G., Stokes, T., Sun, Q., Tan, P.-Y., Tang, R., Tezak, Z., Thorn, B., Tsyganova, M., Turpaz, Y., Vega, S., Visintainer, R., von Frese, J., Wang, C., Wang, E., Wang, J., Wang, W., Westermann, F., Willey, J., Woods, M., Wu, S., Xiao, N., Xu, J., Xu, L., Yang, L., Zeng, X., Zhang, J., Zhang, L., Zhang, M., Zhao, C., Puri, R., Scherf, U., Tong, W., and Wolfinger, R. (2010) The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nat Biotechnol. 28, 827–838.

    Google Scholar 

  4. Edgar, R., Domrachev, M., and Lash, A. E. (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30, 207–210.

    Article  PubMed  CAS  Google Scholar 

  5. Lange, P. S., Chavez, J. C., Pinto, J. T., Coppola, G., Sun, C. W., Townes, T. M., Geschwind, D. H., and Ratan, R. R. (2008) ATF4 is an oxidative stress-inducible, prodeath transcription factor in neurons in vitro and in vivo. J Exp Med. 205, 1227–1242.

    Article  PubMed  CAS  Google Scholar 

  6. R Development Core Team (2008) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.

  7. Gentleman, R., Carey, V., Bates, D., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., Hornik, K., Hothorn, T., Huber, W., Iacus, S., Irizarry, R., Leisch, F., Li, C., Maechler, M., Rossini, A., Sawitzki, G., Smith, C., Smyth, G., Tierney, L., Yang, J., and Zhang, J. (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80.

    Article  PubMed  Google Scholar 

  8. Lee, M. L., and Whitmore, G. A. (2002) Power and sample size for DNA microarray studies. Stat Med. 21, 3543–3570.

    Article  PubMed  Google Scholar 

  9. Klur, S., Toy, K., Williams, M., and Certa, U. (2004) Evaluation of procedures for amplification of small-size samples for hybridization on microarrays. Genomics. 83, 508–517.

    Article  PubMed  CAS  Google Scholar 

  10. Wilson, C. L., Pepper, S. D., Hey, Y., and Miller, C. J. (2004) Amplification protocols introduce systematic but reproducible errors into gene expression studies. Biotechniques. 36, 498–506.

    PubMed  CAS  Google Scholar 

  11. Jones, L., Yue, S., Cheung, C.-Y., and Singer, V. (1998) RNA Quantitation by Fluorescence-Based Solution Assay: RiboGreen Reagent Characterization. Analytical Biochemistry. 265, 368–374.

    Article  PubMed  CAS  Google Scholar 

  12. Fan, J.-B., Gunderson, K., Bibikova, M., Yeakley, J., Chen, J., Wickham Garcia, E., Lebruska, L., Laurent, M., Shen, R., and Barker, D. (2006) Illumina universal bead arrays. Methods Enzymol. 410, 57–73.

    Article  PubMed  CAS  Google Scholar 

  13. Yang, Y. H., Dudoit, S., Luu, P., Lin, D. M., Peng, V., Ngai, J., and Speed, T. P. (2002) Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 30, e15.

    Google Scholar 

  14. Stafford, P. (2008) Methods in Microarray Normalization, Vol. 10, Taylor & Francis.

    Google Scholar 

  15. Bolstad, B. M., Irizarry, R. A., Astrand, M., and Speed, T. P. (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 19, 185–193.

    Google Scholar 

  16. Bourgon, R., Gentleman, R., and Huber, W. (2010) Independent filtering increases detection power for high-throughput experiments. Proc Natl Acad Sci USA. 107, 9546–9551.

    Article  CAS  Google Scholar 

  17. Smyth, G. K., Gentleman, R., Carey, V., Dudoit, S., Irizarry, R., and Huber, W. (2005) Limma: linear models for microarray data, In Bioinformatics and Computational Biology Solutions using R and Bioconductor, pp 397–420, Springer.

    Google Scholar 

  18. Hochberg, Y., and Benjamini, Y. (1990) More powerful procedures for multiple significance testing. Stat Med. 9, 811–818.

    Article  PubMed  CAS  Google Scholar 

  19. Mootha, V. K., Lindgren, C. M., Eriksson, K. F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstrale, M., Laurila, E., Houstis, N., Daly, M. J., Patterson, N., Mesirov, J. P., Golub, T. R., Tamayo, P., Spiegelman, B., Lander, E. S., Hirschhorn, J. N., Altshuler, D., and Groop, L. C. (2003) PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet. 34, 267–273.

    Article  PubMed  CAS  Google Scholar 

  20. Oldham, M., Horvath, S., and Geschwind, D. (2006) Conservation and evolution of gene coexpression networks in human and chimpanzee brains. Proc Natl Acad Sci USA. 103, 17973–17978.

    Article  PubMed  CAS  Google Scholar 

  21. Miller, J. A., Horvath, S., and Geschwind, D. H. (2010) Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways. Proc Natl Acad Sci USA. 107, 12698–12703.

    Article  PubMed  CAS  Google Scholar 

  22. Johnson, M., Kawasawa, Y., Mason, C., Krsnik, Z., Coppola, G., Bogdanovi, D., Geschwind, D., Mane, S., State, M., and Sestan, N. (2009) Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis. Neuron. 62, 494–509.

    Google Scholar 

  23. Oldham, M. C., Konopka, G., Iwamoto, K., Langfelder, P., Kato, T., Horvath, S., and Geschwind, D. H. (2008) Functional organization of the transcriptome in human brain. Nat Neurosci. 11, 1271–1282.

    Article  PubMed  CAS  Google Scholar 

  24. Winden, K. D., Oldham, M. C., Mirnics, K., Ebert, P. J., Swan, C. H., Levitt, P., Rubenstein, J. L., Horvath, S., and Geschwind, D. H. (2009) The organization of the transcriptional network in specific neuronal classes. Mol Syst Biol. 5, 291.

    Article  PubMed  Google Scholar 

  25. Horvath, S., Zhang, B., Carlson, M., Lu, K. V., Zhu, S., Felciano, R. M., Laurance, M. F., Zhao, W., Qi, S., Chen, Z., Lee, Y., Scheck, A. C., Liau, L. M., Wu, H., Geschwind, D. H., Febbo, P. G., Kornblum, H. I., Cloughesy, T. F., Nelson, S. F., and Mischel, P. S. (2006) Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target. Proc Natl Acad Sci USA. 103, 17402–17407.

    Article  PubMed  CAS  Google Scholar 

  26. Day, A., Carlson, M. R., Dong, J., O’Connor, B. D., and Nelson, S. F. (2007) Celsius: a community resource for Affymetrix microarray data. Genome Biol. 8, R112.

    Article  PubMed  Google Scholar 

  27. Chesler, E. J., Lu, L., Shou, S., Qu, Y., Gu, J., Wang, J., Hsu, H. C., Mountz, J. D., Baldwin, N. E., Langston, M. A., Threadgill, D. W., Manly, K. F., and Williams, R. W. (2005) Complex trait analysis of gene expression uncovers polygenic and pleiotropic networks that modulate nervous system function. Nat Genet. 37, 233–242.

    Article  PubMed  CAS  Google Scholar 

  28. Cox, J., and Mann, M. (2007) Is proteomics the new genomics? Cell. 130, 395–398.

    Article  PubMed  CAS  Google Scholar 

  29. Metzker, M. L. (2010) Sequencing technologies – the next generation. Nat Rev Genet. 11, 31–46.

    Article  PubMed  CAS  Google Scholar 

  30. Ng, S., Turner, E., Robertson, P., Flygare, S., Bigham, A., Lee, C., Shaffer, T., Wong, M., Bhattacharjee, A., Eichler, E., Bamshad, M., Nickerson, D., and Shendure, J. (2009) Targeted capture and massively parallel sequencing of 12 human exomes. Nature. 461, 272–276.

    Article  PubMed  CAS  Google Scholar 

  31. Biesecker, L., Mullikin, J., Facio, F., Turner, C., Cherukuri, P., Blakesley, R., Bouffard, G., Chines, P., Cruz, P., Hansen, N., Teer, J., Maskeri, B., Young, A., Manolio, T., Wilson, A., Finkel, T., Hwang, P., Arai, A., Remaley, A., Sachdev, V., Shamburek, R., Cannon, R., and Green, E. (2009) The ClinSeq Project: Piloting large-scale genome sequencing for research in genomic medicine. Genome Res. 19, 1665–1674.

    Article  PubMed  CAS  Google Scholar 

  32. Wang, Z., Gerstein, M., and Snyder, M. (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 10, 57–63.

    Article  PubMed  CAS  Google Scholar 

  33. Mortazavi, A., Williams, B., McCue, K., Schaeffer, L., and Wold, B. (2008) Mapping and quantifying mammalian transcriptomes by (RNA)-Seq. Nat Methods. 5, 621–628.

    Article  CAS  Google Scholar 

  34. Pan, Q., Shai, O., Lee, L., Frey, B., and Blencowe, B. (2008) Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet. 40, 1413–1415.

    Article  PubMed  CAS  Google Scholar 

  35. Leek, J., Scharpf, R., Bravo, H. É. c., Simcha, D., Langmead, B., Johnson, E., Geman, D., Baggerly, K., and Irizarry, R. Tackling the widespread and critical impact of batch effects in high-throughput data. Nat Rev Genet. 11, 733–739.

    Google Scholar 

  36. Verdugo, R., Deschepper, C., Munoz, G., Pomp, D., and Churchill, G. (2009) Importance of randomization in microarray experimental designs with Illumina platforms. Nucleic Acids Res. 37, 5610–5618.

    Google Scholar 

  37. Shi, W., Banerjee, A., Ritchie, M., Gerondakis, S., and Smyth, G. (2009) Illumina WG-6 BeadChip strips should be normalized separately. BMC Bioinformatics. 10, 372.

    Article  PubMed  Google Scholar 

  38. Johnson, E., Li, C., and Rabinovic, A. (2007) Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostat. 8, 118–127.

    Article  Google Scholar 

  39. Rebhan, M., Chalifa-Caspi, V., Prilusky, J., and Lancet, D. (1997) GeneCards: integrating information about genes, proteins and diseases. Trends Genet. 13, 163.

    Google Scholar 

  40. Huang, D. W., Sherman, B., and Lempicki, R. (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protocols. 4, 44–57.

    Article  CAS  Google Scholar 

  41. Zhang, B., Kirov, S., and Snoddy, J. (2005) WebGestalt: an integrated system for exploring gene sets in various biological contexts. Nucleic Acids Res. 33, W741-W748.

    Article  PubMed  CAS  Google Scholar 

  42. Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., and Kanehisa, M. (1999) KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 27, 29–34.

    Article  PubMed  CAS  Google Scholar 

  43. Chen, H., and Sharp, B. (2004) Content-rich biological network constructed by mining PubMed abstracts. BMC Bioinformatics. 5, 147.

    Article  PubMed  Google Scholar 

  44. Becker, K., Hosack, D., Dennis, G., Lempicki, R., Bright, T., Cheadle, C., and Engel, J. (2003) PubMatrix: a tool for multiplex literature mining. BMC Bioinformatics. 4, 61.

    Article  PubMed  Google Scholar 

  45. Hoffmann, R., and Valencia, A. (2004) A gene network for navigating the literature. Nat Genet. 36.

    Google Scholar 

  46. Chang, J., and Nevins, J. (2006) GATHER: a systems approach to interpreting genomic signatures. Bioinformatics. 22, 2926–2933.

    Google Scholar 

  47. Matys, V., Fricke, E., Geffers, R., Gössling, E., Haubrock, M., Hehl, R., Hornischer, K., Karas, D., Kel, A. E., Kel-Margoulis, O. V., Kloos, D. U., Land, S., Lewicki-Potapov, B., Michael, H., Münch, R., Reuter, I., Rotert, S., Saxel, H., Scheer, M., Thiele, S., and Wingender, E. (2003) TRANSFAC: transcriptional regulation, from patterns to profiles. Nucleic Acids Res. 31, 374–378.

    Google Scholar 

  48. Bailey, T. L., and Elkan, C. (1994) Fitting a mixture model by expectation maximization to discover motifs in biopolymers. Proceedings/International Conference on Intelligent Systems for Molecular Biology; ISMB. International Conference on Intelligent Systems for Molecular Biology. 2, 28–36.

    CAS  Google Scholar 

  49. Kent, J. (2002) BLAT – the BLAST-like alignment tool. Genome res. 12, 656–664.

    PubMed  CAS  Google Scholar 

  50. Parkinson, H., Sarkans, U., Kolesnikov, N., Abeygunawardena, N., Burdett, T., Dylag, M., Emam, I., Farne, A., Hastings, E., Holloway, E., Kurbatova, N., Lukk, M., Malone, J., Mani, R., Pilicheva, E., Rustici, G., Sharma, A., Williams, E., Adamusiak, T., Brandizi, M., Sklyar, N., and Brazma, A. (2010) Array Express update – an archive of microarray and high-throughput sequencing-based functional genomics experiments. Nucleic Acids Res. 39, D1002–4.

    Google Scholar 

  51. Wang, J., Williams, R., and Manly, K. (2003) WebQTL: web-based complex trait analysis. Neuroinformatics. 1, 299–308.

    Article  PubMed  Google Scholar 

  52. Obayashi, T., and Kinoshita, K. (2011) COXPRESdb: a database to compare gene coexpression in seven model animals. Nucleic Acids Res. in press.

    Google Scholar 

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Acknowledgments

The author would like to thank Fuying Gao and Jeremy Davis-Turak for technical assistance, and Drs. Michael Oldham and Daniel Geschwind for critically reading the manuscript.

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Authors and Affiliations

  1. Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, #1524 Gonda Neuroscience and Genetics Research Center, University of California Los Angeles, Los Angeles, CA, USA

    Giovanni Coppola

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  1. Giovanni Coppola
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Correspondence to Giovanni Coppola .

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  1. Weill Medical College, Dept. Neurology & Neuroscience, Cornell University, East 68th St. 525, New York, 10065, New York, USA

    Giovanni Manfredi

  2. York Avenue 1300, New York, 10065, New York, USA

    Hibiki Kawamata

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Coppola, G. (2011). Designing, Performing, and Interpreting a Microarray-Based Gene Expression Study. In: Manfredi, G., Kawamata, H. (eds) Neurodegeneration. Methods in Molecular Biology, vol 793. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-328-8_28

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  • DOI: https://doi.org/10.1007/978-1-61779-328-8_28

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