Microarray-based gene expression analysis of an animal model for closed head injury

被引:20
|
作者
Colak, T. [1 ]
Cine, N.
Bamac, B. [1 ]
Kurtas, O.
Ozbek, A. [1 ]
Bicer, U.
Sunnetci, D.
Savli, H.
机构
[1] Kocaeli Univ, Sch Med, Dept Anat, TR-41380 Kocaeli, Turkey
关键词
Rats; Craniocerebral trauma; Microarray; TRAUMATIC BRAIN-INJURY; C1Q FAMILY PROTEINS; MATRIX METALLOPROTEINASES; ENDOTHELIAL-CELLS; GROWTH-FACTOR; ANGIOGENESIS; ISCHEMIA; DEATH; PATHOPHYSIOLOGY; MECHANISMS;
D O I
10.1016/j.injury.2012.01.021
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Objective: Traumatic brain injury (TBI) is a major cause of death and disability in both children and the elderly. Mortality from TBI is said account for 1-2% of all deaths. One-third to one-half of all traumatic deaths is due to head injury. Of those who survive, the majority is left with significant disabilities, including 3% who remain in a vegetative state and only approximately 30% who make a good recovery. Microarray studies and other genomic techniques facilitate the discovery of new targets for the treatment of diseases, which aids in drug development, immunotherapeutics and gene therapy. Gene expression profiling or microarray analysis enables the measurement of thousands of genes in a single RNA sample. Methods: In this study, adult Wistar-albino rats underwent TBI using a trauma device. Brain tissues and blood samples were taken for gene expression at 1, 12 and 48 h post-trauma and were then analysed via microarray. Total RNA was isolated using an RNeasy Mini Kit (QIAGEN-Sample & Assay Technologies, Hilden, Germany) and tested using a 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA). Overall changes in gene expression were evaluated using Agilent Whole Rat Genome 4 x 44 K oligonucleotide arrays and analysed with GeneSpring (GeneSpring 6.1, Silicon Genetics, Redwood City, CA) software. Only genes with a signal-to-noise ratio of above 2 in the experiments were included in the statistical analysis. Results: ANOVA (p < 0.05) was performed to identify differentially expressed probe sets. Additional filtering (minimum 2-fold change) was applied to extract the most differentially expressed genes based on the study groups (Control vs. 1st hour, Control vs. 12th hour, Control vs. 48th hour). Differentially expressed genes were detected via microarray analysis. A gene interaction-based network investigation of the genes that were identified via traditional microarray data analysis describes a significantly relevant gene network that includes the C1ql2, Cbnl, Sdc1, Bdnf, MMP9, and Cd47 genes, which were differentially expressed compared with the controls. Conclusions: In this study, we will review the current understanding of the genetic susceptibility of TBI with microarrays. Our results highlight the importance of genes that control the response of the brain to injury as well as the suitability of microarrays for identifying specific targets for further study. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1264 / 1270
页数:7
相关论文
共 50 条
  • [1] Microarray-Based Gene Expression Analysis of Hepatocellular Carcinoma
    Maass, Thorsten
    Sfakianakis, Ioannis
    Staib, Frank
    Krupp, Markus
    Galle, Peter R.
    Teufel, Andreas
    CURRENT GENOMICS, 2010, 11 (04) : 261 - 268
  • [2] Microarray-based analysis of micro-ribonucleic acid expression in an animal model of mania
    Rong, H.
    Liu, T. B.
    Yang, H. C.
    Zhang, J.
    Yang, H. Z.
    Bi, J. Q.
    Shen, Q. J.
    BIPOLAR DISORDERS, 2014, 16 : 48 - 48
  • [3] Automated target preparation for microarray-based gene expression analysis
    Raymond, Frederic
    Metairon, Sylviane
    Borner, Roland
    Hofmann, Markus
    Kussmann, Martin
    ANALYTICAL CHEMISTRY, 2006, 78 (18) : 6299 - 6305
  • [4] Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review
    Raddatz, Barbara B.
    Spitzbarth, Ingo
    Matheis, Katja A.
    Kalkuhl, Arno
    Deschl, Ulrich
    Baumgaertner, Wolfgang
    Ulrich, Reiner
    VETERINARY PATHOLOGY, 2017, 54 (05) : 734 - 755
  • [5] The effects of globin on microarray-based gene expression analysis of mouse blood
    Mary E. Winn
    Matthew A. Zapala
    Iiris Hovatta
    Victoria B. Risbrough
    Elizabeth Lillie
    Nicholas J. Schork
    Mammalian Genome, 2010, 21 : 268 - 275
  • [6] The effects of globin on microarray-based gene expression analysis of mouse blood
    Winn, Mary E.
    Zapala, Matthew A.
    Hovatta, Iiris
    Risbrough, Victoria B.
    Lillie, Elizabeth
    Schork, Nicholas J.
    MAMMALIAN GENOME, 2010, 21 (5-6) : 268 - 275
  • [7] A fisheye viewer for microarray-based gene expression data
    Min Wu
    Cheng Thao
    Xiangming Mu
    Ethan V Munson
    BMC Bioinformatics, 7
  • [8] Microarray-based gene expression profiles of silkworm brains
    Gan, Ling
    Liu, Xilong
    Xiang, Zhonghuai
    He, Ningjia
    BMC NEUROSCIENCE, 2011, 12
  • [9] A fisheye viewer for microarray-based gene expression data
    Wu, Min
    Thao, Cheng
    Mu, Xiangming
    Munson, Ethan V.
    BMC BIOINFORMATICS, 2006, 7 (1)
  • [10] Microarray-based gene expression profiles of silkworm brains
    Ling Gan
    Xilong Liu
    Zhonghuai Xiang
    Ningjia He
    BMC Neuroscience, 12