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Genotype-by-age interaction and identification of longevity-associated genes from microarray data.

ABSTRACT: Microarray-based comparisons of long-lived and normal mouse strains represent a promising approach for dissecting the basis of lifespan extension in higher organisms. Recently, Boylston et al. (2006) generated a genome-wide data set that allowed expression levels of Snell (Pit1 (dw/dw)) and Ames (Prop1 (df/df)) long-lived mice to be compared with age-matched control mice across different ages (6-24 months). Longevity-associated genes were identified as those genes exhibiting differential expression between long-lived and normal mice at every age examined. In this communication, an alternative approach to identifying longevity-associated genes is suggested and applied to the data sets considered by Boylston et al. (2006). Longevity-associated genes are defined as those exhibiting significant genotype-by-age interaction with respect to expression levels of long-lived and normal mice, and a total of 63 longevity-associated genes are identified. This approach may lend greater confidence to the inference that expression of identified genes specifically underlies aging differences between long-lived and normal genotypes.

SUBMITTER: Swindell WR

PROVIDER: S-EPMC2267658 | biostudies-literature | 2007 Sep

REPOSITORIES: biostudies-literature

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Genotype-by-age interaction and identification of longevity-associated genes from microarray data.

Swindell William R WR

Age (Dordrecht, Netherlands) 20070621 2-3

Microarray-based comparisons of long-lived and normal mouse strains represent a promising approach for dissecting the basis of lifespan extension in higher organisms. Recently, Boylston et al. (2006) generated a genome-wide data set that allowed expression levels of Snell (Pit1 (dw/dw)) and Ames (Prop1 (df/df)) long-lived mice to be compared with age-matched control mice across different ages (6-24 months). Longevity-associated genes were identified as those genes exhibiting differential express ...[more]

PMID: 19424835

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Project description:To identify candidate key genes and miRNAs associated with esophageal squamous cell carcinoma (ESCC) development and prognosis, the gene expression profiles and miRNA microarray data including GSE20347, GSE38129, GSE23400, and GSE55856 were downloaded from the Gene Expression Omnibus (GEO) database. Clinical and survival data were retrieved from The Cancer Genome Atlas (TCGA). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes (DEGs) was analyzed via DAVID, while the DEG-associated protein-protein interaction network (PPI) was constructed using the STRING database. Additionally, the miRNA target gene regulatory network and miRNA coregulatory network were constructed, using the Cytoscape software. Survival analysis and prognostic model construction were performed via the survival (version 2.42-6) and rbsurv R packages, respectively. The results showed a total of 2575, 2111, and 1205 DEGs, and 226 differentially expressed miRNAs (DEMs) were identified. Pathway enrichment analyses revealed that DEGs were mainly enriched in 36 pathways, such as the proteasome, p53, and beta-alanine metabolism pathways. Furthermore, 448 nodes and 1144 interactions were identified in the PPI network, with MYC having the highest random walk score. In addition, 7 DEMs in the microarray data, including miR-196a, miR-21, miR-205, miR-194, miR-103, miR-223, and miR-375, were found in the regulatory network. Moreover, several reported disease-related miRNAs, including miR-198a, miR-103, miR-223, miR-21, miR-194, and miR-375, were found to have common target genes with other DEMs. Survival analysis revealed that 85 DEMs were related to prognosis, among which hsa-miR-1248, hsa-miR-1291, hsa-miR-421, and hsa-miR-7-5p were used for a prognostic survival model. Taken together, this study revealed the important roles of DEGs and DEMs in ESCC development, as well as DEMs in the prognosis of ESCC. This will provide potential therapeutic targets and prognostic predictors for ESCC.

Dataset Information

Genotype-by-age interaction and identification of longevity-associated genes from microarray data.

Publications

Genotype-by-age interaction and identification of longevity-associated genes from microarray data.

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