4.5 Article

Development and application of a rat ovarian gene expression database

Journal

ENDOCRINOLOGY
Volume 145, Issue 11, Pages 5384-5396

Publisher

ENDOCRINE SOC
DOI: 10.1210/en.2004-0407

Keywords

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Funding

  1. NCRR NIH HHS [P20 RR15592] Funding Source: Medline
  2. NIA NIH HHS [AG17164] Funding Source: Medline

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The pituitary gonadotropins play a key role in follicular development and ovulation through the induction of specific genes. To identify these genes, we have constructed a genome-wide rat ovarian gene expression database (rOGED). The database was constructed from total RNA isolated from intact ovaries, granulosa cells, or residual ovarian tissues collected from immature pregnant mare serum gonadotropin (PMSG)/human chorionic gonadotropin-treated rats at 0 h (no PMSG), 12 h, and 48 h post PMSG, as well as 6 and 12 h post human chorionic gonadotropin. The total RNA was used for DNA microarray analysis using Affymetrix Rat Expression Arrays 230A and 230B (Affymetrix, Santa Clara, CA). The microarray data were compiled and used for display of individual gene expression profiles through specially developed software. The final rOGED provides immediate analysis of temporal gene expression profiles for over 28,000 genes in intact ovaries, granulosa cells, and residual ovarian tissue during follicular growth and the preovulatory period. The accuracy of the rOGED was validated against the gene profiles for over 20 known genes. The utility of the rOGED was demonstrated by identifying six genes that have not been described in the rat periovulatory ovary. The mRNA expression patterns and cellular localization for each of these six genes (estrogen sulfotransferase, synaptosomal-associated protein 25 kDa, runt-related transcription factor, calgranulin B,alpha1-macroglobulin, and MAPK phosphotase-3) were confirmed by Northern blot analyses and in situ hybridization, respectively. The current findings demonstrate that the rOGED can be used as an instant reference for ovarian gene expression profiles, as well as a reliable resource for identifying important yet, to date, unknown ovarian genes.

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