Dataset Information

Genomewide discovery and classification of candidate ovarian fertility genes in the mouse.

ABSTRACT: Female infertility syndromes are among the most prevalent chronic health disorders in women, but their genetic basis remains unknown because of uncertainty regarding the number and identity of ovarian factors controlling the assembly, preservation, and maturation of ovarian follicles. To systematically discover ovarian fertility genes en masse, we employed a mouse model (Foxo3) in which follicles are assembled normally but then undergo synchronous activation. We developed a microarray-based approach for the systematic discovery of tissue-specific genes and, by applying it to Foxo3 ovaries and other samples, defined a surprisingly large set of ovarian factors (n = 348, approximately 1% of the mouse genome). This set included the vast majority of known ovarian factors, 44% of which when mutated produce female sterility phenotypes, but most were novel. Comparative profiling of other tissues, including microdissected oocytes and somatic cells, revealed distinct gene classes and provided new insights into oogenesis and ovarian function, demonstrating the utility of our approach for tissue-specific gene discovery. This study will thus facilitate comprehensive analyses of follicle development, ovarian function, and female infertility.

SUBMITTER: Gallardo TD

PROVIDER: S-EPMC2013718 | biostudies-literature | 2007 Sep

REPOSITORIES: biostudies-literature

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Genomewide discovery and classification of candidate ovarian fertility genes in the mouse.

Gallardo Teresa D TD John George B GB Shirley Lane L Contreras Cristina M CM Akbay Esra A EA Haynie J Marshall JM Ward Samuel E SE Shidler Meredith J MJ Castrillon Diego H DH

Genetics 20070729 1

Female infertility syndromes are among the most prevalent chronic health disorders in women, but their genetic basis remains unknown because of uncertainty regarding the number and identity of ovarian factors controlling the assembly, preservation, and maturation of ovarian follicles. To systematically discover ovarian fertility genes en masse, we employed a mouse model (Foxo3) in which follicles are assembled normally but then undergo synchronous activation. We developed a microarray-based appr ...[more]

PMID: 17660561

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Project description:BackgroundIdentification of single nucleotide polymorphisms (SNPs) for specific genes involved in reproduction might improve reliability of genomic estimates for these low-heritability traits. Semen from 550 Holstein bulls of high (≥ 1.7; n = 288) or low (≤ -2; n = 262) daughter pregnancy rate (DPR) was genotyped for 434 candidate SNPs using the Sequenom MassARRAY® system. Three types of SNPs were evaluated: SNPs previously reported to be associated with reproductive traits or physically close to genetic markers for reproduction, SNPs in genes that are well known to be involved in reproductive processes, and SNPs in genes that are differentially expressed between physiological conditions in a variety of tissues associated in reproductive function. Eleven reproduction and production traits were analyzed.ResultsA total of 40 SNPs were associated (P < 0.05) with DPR. Among these were genes involved in the endocrine system, cell signaling, immune function and inhibition of apoptosis. A total of 10 genes were regulated by estradiol. In addition, 22 SNPs were associated with heifer conception rate, 33 with cow conception rate, 36 with productive life, 34 with net merit, 23 with milk yield, 19 with fat yield, 13 with fat percent, 19 with protein yield, 22 with protein percent, and 13 with somatic cell score. The allele substitution effect for SNPs associated with heifer conception rate, cow conception rate, productive life and net merit were in the same direction as for DPR. Allele substitution effects for several SNPs associated with production traits were in the opposite direction as DPR. Nonetheless, there were 29 SNPs associated with DPR that were not negatively associated with production traits.ConclusionSNPs in a total of 40 genes associated with DPR were identified as well as SNPs for other traits. It might be feasible to include these SNPs into genomic tests of reproduction and other traits. The genes associated with DPR are likely to be important for understanding the physiology of reproduction. Given the large number of SNPs associated with DPR that were not negatively associated with production traits, it should be possible to select for DPR without compromising production.

Dataset Information

Genomewide discovery and classification of candidate ovarian fertility genes in the mouse.

Publications

Genomewide discovery and classification of candidate ovarian fertility genes in the mouse.

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