A Comprehensive Analysis of the Microarray Gene Expression Protocol and Results Using the Mouse T-cell Gene Expression Profile

Main Article Content

Onoriode Oyiborhoro
Oriakhi Kelly
Esosa S. Uhunmwangho
Kingsley A. Iteire
Enoh F. Akpojotor

Abstract

The microarray technology is a very powerful technology that combines molecular biology and computer technology to analyze the gene expression levels for most or all of the genes in a whole genome simultaneously, at very high resolutions. This technology has wide applications, including gene interaction studies for discovery of genes responsible for different diseases; classification of cancers and other diseases; prediction of clinical outcomes or prognosis for different diseases; response to therapy and development of new therapeutic agents, including gene therapy. It is therefore a very potent, unbiased and sensitive technology for the discovery of novel genes involved in the pathogenesis or control of diseases including cancers and autoimmune diseases. In the present study, we seek to give a clear and detailed account of the microarray gene expression protocol using the mouse T-cell gene expression profile, including challenges involved and how to overcome them, as well as detailed analysis of results obtained.

Keywords:
cDNA, GeneChip microarray, single stranded oligonucleotide.

Article Details

How to Cite
Oyiborhoro, O., Kelly, O., Uhunmwangho, E. S., A. Iteire, K., & F. Akpojotor, E. (2019). A Comprehensive Analysis of the Microarray Gene Expression Protocol and Results Using the Mouse T-cell Gene Expression Profile. Asian Journal of Biochemistry, Genetics and Molecular Biology, 2(4), 1-15. https://doi.org/10.9734/ajbgmb/2019/v2i430069
Section
Method Article

References

Wolf-Karsten H. Gene expression profiling by microarray 1st ed. Cambridge University Press, New York. 2006;2-3.

Bradley AB Comparative environmental genomics in non-model species: Using heterologous hybridization to DNA-based microarrays. Journal of Experimental Biology. 2007;210:1602-1606.

Fryer MR, Randall J, Yoshida T, Hsiao L, Blumenstock J, Jensen KE. Global analysis of gene expressions: Methods, interpretations and pitfalls. Experimental Nephrology. 2002;10:64-74.

Beixue G, Qingfei K, Kyeorda K, Yuan-Si Z, Deyu F. Analysis of sirtium 1 expression reveals a molecular explanation of IL-2 mediated reversal of T-cell tolerance. PNAS, 2012;109(3):899 – 904.

Keiko M, Yuta K, Kenichi S, Keishi F, Tomohisa O, Yukinori O et al. Regulatory polymorphisms in Egr2 are associated with susceptibility to Systemic Lupus Erythematosus. Hum. Mol. Genet. 2010; 19(11):2313-2320.

Stephanie EC, Dirk H. Cellular, Molecular and Clinical Immunology. 2011;1.

Available:www.ucdenver.edu/academics/colleges. 24-12-2012.

Liu J, Li F, Wang L, Chen X, Wang d, Cao L, Ping Y, et al. CTL vs Treg lymphocyte-attracting chemokines, CCL4 and CCL20 are strong reciprocal predictive markers for survival of patients with oesophageal squamous cell carcinoma. British Journal of Cancer. 2015;113:747-755.

Zhao J, Zhang Z, Luan Y, Zou Z, Sun Y, Li Y, et al. Pathological functions of interleukin-22 in chronic liver inflammation and fibrosis with hepatitis B virus infection by promoting T-helper 17 cell recruitment. Hepatology. 2014;59(4):1331- 1342.

Joanna S, Ewa T, Jakub C, Katarzyna G and Angnieszka B. A potential contribution of chemokine network dysfunction to the depressive disorders. Curr Neuro-pharmacol. 2016;14(7):705-720.

Zhang W, Ferguson J, Ng SM, Hui K, Lin A, Esplugues E, et al. Effector CD4+ T-cell expression signatures and immune-mediated disease associated genes. PLos One. 2012;7(6):e38501.

DOI:10.1371/Journal pone. 0038510

Roberta M, Clemens Z, Marco A, Samanta T, Massimo R, Antonio G, Antonello M. The emerging role of epigenetics in human autoimmune disorders. Clinical Epige-netics. 2019;11:34.

Jeffries M, Sawalha A Autoimmune disease in the epigenetic era: how has epigenetics changed our understanding of disease and how can we expect the field to evolve? Expert Rev. Clin. Immunol. 2015; 11(1):45 –58.

Wang Y, Shu Y, Xiao Y, Wang Q, Kanekura T, Li Y et al. Hypomethylation and overexpression of ITGAL (CD11a) in CD4+ T cells in systemic sclerosis. Clin. Epigenetics. 2014;6(1):25.

Limbach M, Saare M, Tserel L, Kisand K, Eglit T, Sauer S et al. Epigenetic profiling in CD4+ and CD8+ T cells from Grave’s disease patients reveals changes in genes associated with T-cell receptor signalling. J. Autoimmune. 2016;67:46–56.

Chia-Chen Kuo, Shih-Chang Lin. Altered FOXO1 transcript levels in peripheral blood mononuclear cells of SLE and rheumatoid arthritis patients. Mol Med. 2007;13(11-12):561-566.

Wang S, Xia P, Huang G, Zhu P, Liu J, Ye B et al. FOXO1-mediated autophagy is required for NK cell development and innate immunity. Nature Communications, 2016;7:11023.

Kim YI, Lee BR, Cheon JH, Kwon BE, Kweon MN, Ko HJ, Chang SY. Compensatory roles of CD8+ T cells and plasmacytoid dendritic cells in gut immune regulation for reduced function of CD4+ Treg. Oncotarget. 2016;7(10):10947–10961.

Seong-il O, Jeong HH, Byung WC, Ki-Wook O, Chan KP, Min-Jun K et al. A novel F455 SOD1 mutation in Amyotrophic Lateral Sclerosis coexisting with Bullous Pemphigoid. Journal of Clinical Neurology. 2015;11(4):390-394.

Papadimitriou D, Le VV, Jacquier A, Ikiz B, Przedborski S, Re DB. Inflammation in ALS and SMA: Sorting the good from the evil. Neurobiological Diseases. 2010;37: 493-502.

McCombe PA, Henderson RA. The Role of immune and inflammatory mechanisms in ALS. Curr Mol Med. 2011;11(3):246-254.

Cheung VG, Morley M, Aguilar F, Massimi A, Kucherlapati R, Childs G. Making and reading microarrays. Nature Genetics. 1999;21:15-19.