Dataset Information

Identification of Genes Expressed in Hyperpigmented Skin Using Meta-Analysis of Microarray Data Sets.

ABSTRACT: More than 375 genes have been identified that are involved in regulating skin pigmentation and these act during development, survival, differentiation, and/or responses of melanocytes to the environment. Many of these genes have been cloned, and disruptions of their functions are associated with various pigmentary diseases; however, many remain to be identified. We have performed a series of microarray analyses of hyperpigmented compared with less pigmented skin to identify genes responsible for these differences. The rationale and goal for this study was to perform a meta-analysis on these microarray databases to identify genes that may be significantly involved in regulating skin phenotype either directly or indirectly that might not have been identified due to subtle differences by any of these individual studies alone. The meta-analysis demonstrates that 1,271 probes representing 921 genes are differentially expressed at significant levels in the 5 microarray data sets compared, providing new insights into the variety of genes involved in determining skin phenotype. Immunohistochemistry was used to validate two of these markers at the protein level (TRIM63 and QPCT), and we discuss the possible functions of these genes in regulating skin physiology.

SUBMITTER: Yin L

PROVIDER: S-EPMC4567955 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Identification of Genes Expressed in Hyperpigmented Skin Using Meta-Analysis of Microarray Data Sets.

Yin Lanlan L Coelho Sergio G SG Valencia Julio C JC Ebsen Dominik D Mahns Andre A Smuda Christoph C Miller Sharon A SA Beer Janusz Z JZ Kolbe Ludger L Hearing Vincent J VJ

The Journal of investigative dermatology 20150607 10

More than 375 genes have been identified that are involved in regulating skin pigmentation and these act during development, survival, differentiation, and/or responses of melanocytes to the environment. Many of these genes have been cloned, and disruptions of their functions are associated with various pigmentary diseases; however, many remain to be identified. We have performed a series of microarray analyses of hyperpigmented compared with less pigmented skin to identify genes responsible for ...[more]

PMID: 25950827

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Project description:BackgroundMicroarrays have been widely used for the analysis of gene expression and several commercial platforms are available. The combined use of multiple platforms can overcome the inherent biases of each approach, and may represent an alternative that is complementary to RT-PCR for identification of the more robust changes in gene expression profiles. In this paper, we combined statistical and functional analysis for the cross platform validation of two oligonucleotide-based technologies, Affymetrix (AFFX) and Applied Biosystems (ABI), and for the identification of differentially expressed genes.ResultsIn this study, we analysed differentially expressed genes after treatment of an ovarian carcinoma cell line with a cell cycle inhibitor. Treated versus control RNA was analysed for expression of 16425 genes represented on both platforms. We assessed reproducibility between replicates for each platform using CAT plots, and we found it high for both, with better scores for AFFX. We then applied integrative correlation analysis to assess reproducibility of gene expression patterns across studies, bypassing the need for normalizing expression measurements across platforms. We identified 930 genes as differentially expressed on AFFX and 908 on ABI, with approximately 80% common to both platforms. Despite the different absolute values, the range of intensities of the differentially expressed genes detected by each platform was similar. ABI showed a slightly higher dynamic range in FC values, which might be associated with its detection system. 62/66 genes identified as differentially expressed by Microarray were confirmed by RT-PCR.ConclusionIn this study we present a cross-platform validation of two oligonucleotide-based technologies, AFFX and ABI. We found good reproducibility between replicates, and showed that both platforms can be used to select differentially expressed genes with substantial agreement. Pathway analysis of the affected functions identified themes well in agreement with those expected for a cell cycle inhibitor, suggesting that this procedure is appropriate to facilitate the identification of biologically relevant signatures associated with compound treatment. The high rate of confirmation found for both common and platform-specific genes suggests that the combination of platforms may overcome biases related to probe design and technical features, thereby accelerating the identification of trustworthy differentially expressed genes.

Dataset Information

Identification of Genes Expressed in Hyperpigmented Skin Using Meta-Analysis of Microarray Data Sets.

Publications

Identification of Genes Expressed in Hyperpigmented Skin Using Meta-Analysis of Microarray Data Sets.

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