Translational Medicine of AgingGeneticsPeer-reviewed journal article
Lack of accelerated ovarian aging in a follicle-stimulating hormone receptor haploinsufficiency model
Kristen MehalkoiD, Minhoo KimiD, Sanjana M. PayeiD, Kelly KohiD, Ryan J. LuiD, Bérénice Anath BenayouniD
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Abstract
Follicle-stimulation hormone (FSH) and FSH receptor (FSHR) signaling is essential for lifelong ovarian and endocrine functions in females. Previous studies have reported that Fshr haploinsufficiency in female mice led to accelerated ovarian aging, including anticipated progressive fertility decline, irregular estrus cycles, increased follicular atresia and premature ovarian failure at 7 to 9 months of age. Interestingly, these phenotypes resemble key characteristics of human menopause and thus Fshr haploinsufficiency was proposed as a promising research mouse model of menopause. However, the Fshr haploinsufficiency model had not been fully explored, especially at the molecular level. In this study, we characterized the ovarian and endocrine functions of a Fshr heterozygous knockout allele that was generated on the C57BL/6 genetic background as part of the Knockout Mouse Project (KOMP). Based on our analyses of these mice using a breeding assay, ovarian tissue histology and serum hormone quantifications (i.e. FSH, AMH, INHA) analyses, the KOMP Fshr heterozygous knockout female mice do not show the anticipated phenotypes of ovarian aging in terms of fertility and endocrine function. We further confirmed that the expression of Fshr is unaltered in the ovaries of the KOMP Fshr heterozygous knockout animals compared to wild-type. Together, our data suggests that the KOMP Fshr heterozygous knockout strain does not recapitulate the previously reported ovarian aging phenotypes associated to another model of Fshr haploinsufficiency.
- organism: mouse
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
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