Quantifying growing versus non-growing ovarian follicles in the mouse.

BACKGROUND: A standard histomorphometric approach has been used for nearly 40 years that identifies atretic (e.g., dying) follicles by counting the number of pyknotic granulosa cells (GC) in the largest follicle cross-section. This method holds that if one pyknotic granulosa nucleus is seen in the largest cross section of a primary follicle, or three pyknotic cells are found in a larger follicle, it should be categorized as atretic. Many studies have used these criteria to estimate the fraction of atretic follicles that result from genetic manipulation or environmental insult. During an analysis of follicle development in a mouse model of Fragile X premutation, we asked whether these 'historical' criteria could correctly identify follicles that were not growing (and could thus confirmed to be dying).

METHODS: Reasoning that the fraction of mitotic GC reveals whether the GC population was increasing at the time of sample fixation, we compared the number of pyknotic nuclei to the number of mitotic figures in follicles within a set of age-matched ovaries.

RESULTS: We found that, by itself, pyknotic nuclei quantification resulted in high numbers of false positives (improperly categorized as atretic) and false negatives (improperly categorized intact). For preantral follicles, scoring mitotic and pyknotic GC nuclei allowed rapid, accurate identification of non-growing follicles with 98% accuracy. This method most often required the evaluation of one follicle section, and at most two serial follicle sections to correctly categorize follicle status. For antral follicles, we show that a rapid evaluation of follicle shape reveals which are intact and likely to survive to ovulation.

CONCLUSIONS: Combined, these improved, non-arbitrary methods will greatly improve our ability to estimate the fractions of growing/intact and non-growing/atretic follicles in mouse ovaries.