Array Analysis Manager-An automated DNA microarray analysis tool simplifying microarray data filtering, bias recognition, normalization, and expression analysis

We show that the intraclass correlation coefficient (ICC) can be used as a relatively simple statistical measure to assess methodological and biological variation in DNA microarray analysis. The ICC is a measure that determines the reproducibility of a variable, which can easily be calculated from an ANOVA table. It is based on the assessment of both systematic deviation and random variation, and it facilitates comparison of multiple samples at once. We used the ICC first to optimize our microarray data normalization method and found that the use of median values instead of mean values improves data correction. Then the reproducibility of different labeling methods was evaluated, and labeling by indirect fluorescent dye incorporation appeared to be more reproducible than direct labeling. Finally, we determined optimal biopsy sampling by analyzing overall variation in gene expression. The variation in gene expression of rectal biopsies within persons decreased when two biopsies were taken instead of one, but it did not considerably improve when more than two biopsies were taken from one person, indicating that it is sufficient to use two biopsies per person for DNA microarray analysis under our experimental conditions. To optimize the accuracy of the microarray data, biopsies from at least six different persons should be used per group.

Download Full-text

Expression analysis of ginsenoside biosynthesis-related genes in methyl jasmonate-treated adventitious roots of Panax ginseng via DNA microarray analysis

Horticulture Environment and Biotechnology ◽

10.1007/s13580-017-0041-4 ◽

2017 ◽

Vol 58 (4) ◽

pp. 376-383 ◽

Cited By ~ 3

Author(s):

Yurry Um ◽

Yi Lee ◽

Seong-Cheol Kim ◽

Yeon-Ju Jeong ◽

Geum-Soog Kim ◽

...

Keyword(s):

Methyl Jasmonate ◽

Panax Ginseng ◽

Microarray Analysis ◽

Dna Microarray ◽

Expression Analysis ◽

Adventitious Roots ◽

Ginsenoside Biosynthesis ◽

Dna Microarray Analysis ◽

Analysis Of Ginsenoside

Download Full-text

The Potential of 2-aza-8-Oxohypoxanthine as a Cosmetic Ingredient

Cosmetics ◽

10.3390/cosmetics8030060 ◽

2021 ◽

Vol 8 (3) ◽

pp. 60

Author(s):

Hisae Aoshima ◽

Masayuki Ito ◽

Rinta Ibuki ◽

Hirokazu Kawagishi

Keyword(s):

Gene Expression ◽

Cell Proliferation ◽

Microarray Analysis ◽

Dna Microarray ◽

Cell Activation ◽

Skin Barrier ◽

Efficacy Evaluation ◽

Activation Effect ◽

Expression Levels ◽

Dna Microarray Analysis

In this study, we verified the effects of 2-aza-8-oxohypoxanthine (AOH) on human epidermal cell proliferation by performing DNA microarray analysis. Cell proliferation was assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, which measures mitochondrial respiration in normal human epidermal keratinocyte (NHEK) cells. Gene expression levels were determined by DNA microarray analysis of 177 genes involved in skin aging and disease. AOH showed a significant increase in cell viability at concentrations between 7.8 and 31.3 μg/mL and a significant decrease at concentrations above 250 μg/mL. DNA microarray analysis showed that AOH significantly increased the gene expression of CLDN1, DSC1, DSG1, and CDH1 (E-cadherin), which are involved in intercellular adhesion and skin barrier functioning. AOH also up-regulated the expression of KLK5, KLK7, and SPIMK5, which are proteases involved in stratum corneum detachment. Furthermore, AOH significantly stimulated the expression of KRT1, KRT10, TGM1, and IVL, which are considered general differentiation indicators, and that of SPRR1B, a cornified envelope component protein. AOH exerted a cell activation effect on human epidermal cells. Since AOH did not cause cytotoxicity, it was considered that the compound had no adverse effects on the skin. In addition, it was found that AOH stimulated the expression levels of genes involved in skin barrier functioning by DNA microarray analysis. Therefore, AOH has the potential for practical use as a cosmetic ingredient. This is the first report of efficacy evaluation tests performed for AOH.

Download Full-text

DNA Microarray Analysis Identifies CKS2 and LEPR as Potential Markers of Meningioma Recurrence

The Oncologist ◽

10.1634/theoncologist.2010-0249 ◽

2011 ◽

Vol 16 (10) ◽

pp. 1440-1450 ◽

Cited By ~ 13

Author(s):

Francesca Menghi ◽

Francesca N. Orzan ◽

Marica Eoli ◽

Mariangela Farinotti ◽

Emanuela Maderna ◽

...

Keyword(s):

Microarray Analysis ◽

Dna Microarray ◽

Dna Microarray Analysis ◽

Meningioma Recurrence

Download Full-text

DNA microarray analysis of global gene regulation by A-factor in Streptomyces griseus

Microbiology ◽

10.1099/mic.0.027862-0 ◽

2009 ◽

Vol 155 (7) ◽

pp. 2197-2210 ◽

Cited By ~ 37

Author(s):

Hirofumi Hara ◽

Yasuo Ohnishi ◽

Sueharu Horinouchi

Keyword(s):

Gene Expression ◽

Microarray Analysis ◽

Dna Microarray ◽

Streptomyces Griseus ◽

Exponential Growth Phase ◽

Mobility Shift ◽

Dna Microarray Analysis ◽

Regulatory Cascade ◽

Transcriptional Units ◽

Inducible Genes

A-factor (2-isocapryloyl-3R-hydroxymethyl-γ-butyrolactone) is a microbial hormone that triggers morphological differentiation and secondary metabolism in Streptomyces griseus. The effects of A-factor on global gene expression were determined by DNA microarray analysis of transcriptomes obtained with the A-factor-deficient mutant ΔafsA. A-factor was added at a concentration of 25 ng ml−1 to mutant ΔafsA at the middle of the exponential growth phase, and RNA samples were prepared from the cells grown after A-factor addition for a further 5, 15 and 30 min, and 1, 2, 4, 8 and 12 h. The effects of A-factor on transcription of all protein-coding genes of S. griseus were evaluated by comparison of the transcriptomes with those obtained from cells grown in the absence of A-factor. Analysis of variance among the transcriptomes revealed that 477 genes, which were dispersed throughout the chromosome, were differentially expressed during the 12 h after addition of A-factor, when evaluated by specific criteria. Quality threshold clustering analysis with regard to putative polycistronic transcriptional units and levels of upregulation predicted that 152 genes belonging to 74 transcriptional units were probable A-factor-inducible genes. Competitive electrophoretic mobility shift assays using DNA fragments including putative promoter regions of these 74 transcriptional units suggested that AdpA bound 37 regions to activate 72 genes in total. Many of these A-factor-inducible genes encoded proteins of unknown function, suggesting that the A-factor regulatory cascade of S. griseus affects gene expression at a specific time point more profoundly than expected.

Download Full-text