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DNA Microarray Analysis of Estrogen-Responsive Genes

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Estrogen Receptors

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1366))

Abstract

DNA microarray is a powerful, non-biased discovery technology that allows the analysis of the expression of thousands of genes at a time. The technology can be used for the identification of differential gene expression, genetic mutations associated with diseases, DNA methylation, single-nucleotide polymorphisms, and microRNA expression, to name a few. This chapter describes microarray technology for the analysis of differential gene expression in response to estrogen treatment.

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References

  1. Eyster KM, Mark-Kappeler CJ, Appt S, Register T, Clarkson T (2014) Effects of estradiol on transcriptional profiles in atherosclerotic iliac arteries in ovariectomized cynomolgus macaques. Menopause 21(2):143–152

    Article  Google Scholar 

  2. Mark-Kappeler CJ, Martin DS, Eyster KM (2011) Estrogens and selective estrogen receptor modulators (SERMs) regulate gene and protein expression in the mesenteric arteries. Vascul Pharmacol 55:42–49

    Article  CAS  Google Scholar 

  3. Kiyama R, Zhu Y (2014) DNA microarray-based gene expression profiling of estrogenic chemicals. Cell Mol Life Sci 71:2065–2082

    Article  CAS  Google Scholar 

  4. Weaver DD, Norby AR, Rosenfeld JA et al (2015) Chromosome 1p36.22p36.21 duplications/triplication causes Setleis syndrome (focal facial dermal dysplasia type III). Am J Med Genet A 167:1061–1070

    Article  CAS  Google Scholar 

  5. Zhu CQ, Tsao MS (2014) Prognostic markers in lung cancer: is it ready for prime time? Transl Lung Cancer Res 3:149–158

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Kadioglu O, Efferth T (2015) Pharmacogenomic characterization of cytotoxic compounds from Salvia officinalis in cancer cells. J Nat Prod 78(4):762–775

    Article  CAS  Google Scholar 

  7. Ding X, Zheng D, Fan C et al (2015) Genome-wide screen of DNA methylation identifies novel markers in childhood obesity. Gene 566(1):74–83, pii, S0378-1119(15)00441-2

    Article  CAS  Google Scholar 

  8. Valencia-Morales MP, Zaina S, Heyn H et al (2015) The DNA methylation drift of the atherosclerotic aorta increases with lesion progression. BMC Med Genomics 8:7

    Article  Google Scholar 

  9. Goitia V, Oquendo M, Stratton R (2015) Case of 7p22.1 microduplication detected by whole genome microarray (REVEAL) in workup of child diagnosed with autism. Case Rep Genet 2015:212436

    PubMed  PubMed Central  Google Scholar 

  10. Palta P, Kaplinski L, Nagirnaja L et al (2015) Haplotype phasing and inheritance of copy number variants in nuclear families. PLoS One 10(4), e0122713

    Article  Google Scholar 

  11. Schaefer JS, Attumi T, Opekun AR et al (2015) MicroRNA signatures differentiate Crohn’s disease from ulcerative colitis. BMC Immunol 16:5

    Article  Google Scholar 

  12. Gui Z, Li S, Liu X, Xu B, Xu J (2015) Oridonin alters the expression profiles of MicroRNAs in BxPC-3 human pancreatic cancer cells. BMC Complement Altern Med 15:117

    Article  Google Scholar 

  13. Yamashita K, Kuno A, Matsuda A, et al (2015) Lectin microarray technology identifies specific lectins related to lymph node metastasis of advanced gastric cancer. Gastric Cancer, epub ahead of print

    Google Scholar 

  14. Gibson UE, Heid CA, Williams PM (1996) A novel method for real time quantitative RT-PCR. Genome Res 6(10):995–1001

    Article  CAS  Google Scholar 

  15. Cassidy A, Jones J (2014) Developments in in situ hybridization. Methods 70:39–45

    Article  CAS  Google Scholar 

  16. Stempel AJ, Morgans CW, Stout JT, Appukuttan B (2014) Simultaneous visualization and cell-specific confirmation of RNA and protein in the mouse retina. Mol Vis 20:1366–1373

    PubMed  PubMed Central  Google Scholar 

  17. Mahmood T, Yang PC (2012) Western blot: technique, theory, and trouble shooting. N Am J Med Sci 4:429–434

    Article  Google Scholar 

  18. Kurien BT, Dorri Y, Dillon S, Dsouza A, Scofield RH (2011) An overview of Western blotting for determining antibody specificities for immunohistochemistry. Methods Mol Biol 717:55–67

    Article  CAS  Google Scholar 

  19. Aydin S (2015) A short history, principles, and types of ELISA, and our laboratory experience with peptide/protein analyses using ELISA. Peptides pii, S0196-9781(15)00131-X

    Google Scholar 

  20. Shan WC, Cui YL, He X, Zhang L, Liu J, Wang JP (2015) Production of monoclonal antibody against clonazepam for immunoassay of benzodiazepine drugs in swine tissues. J Environ Sci Health B 50:15–22

    Article  CAS  Google Scholar 

  21. Nielsen S (2015) External quality assessment for immunohistochemistry: experiences from NordiQC. Biotech Histochem 22:1–10

    Google Scholar 

  22. Grabinski TM, Kneynsberg A, Manfredsson FP, Kanaan NM (2015) A method for combining RNAscope in situ hybridization with immunohistochemistry in thick free-floating brain sections and primary neuronal cultures. PLoS One 10(3):e0120120

    Article  Google Scholar 

  23. Brazma A, Hingamp P, Quackenbush J et al (2001) Minimum information about a microarray experiment (MIAME)—toward standards for microarray data. Nat Genet 29:365–371

    Article  CAS  Google Scholar 

  24. Rodrigo MC, Martin DS, Redetzke RA, Eyster KM (2002) A method for the extraction of high-quality RNA and protein from single small samples of arteries and veins preserved in RNAlater. J Pharmacol Toxicol Methods 47:87–92

    Article  CAS  Google Scholar 

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Acknowledgements

Research reported in this publication was supported, in part, by an Institutional Development Award (IDeA) grant P20GM103443. Its contents are solely the responsibility of the authors and do not necessarily represent official views of NIGMS or NIH.

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Authors and Affiliations

  1. Division of Basic Biomedical Sciences, Sanford School of Medicine, University of South Dakota, 414 E. Clark St., Vermillion, SD, 57069, USA

    Kathleen M. Eyster

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  1. Kathleen M. Eyster
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Corresponding author

Correspondence to Kathleen M. Eyster .

Editor information

Editors and Affiliations

  1. University of South Dakota Sanford School of Medicine, Vermillion, South Dakota, USA

    Kathleen M. Eyster

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Eyster, K.M. (2016). DNA Microarray Analysis of Estrogen-Responsive Genes. In: Eyster, K.M. (eds) Estrogen Receptors. Methods in Molecular Biology, vol 1366. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3127-9_10

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  • DOI: https://doi.org/10.1007/978-1-4939-3127-9_10

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3126-2

  • Online ISBN: 978-1-4939-3127-9

  • eBook Packages: Springer Protocols

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