Characterization of preantral follicle clustering and neighborhood patterns in the equine ovary.

Abstract

Understanding the transition from quiescent primordial follicles to activated primary follicles is vital for characterizing ovarian folliculogenesis and improving assisted reproductive techniques. To date, no study has investigated preantral follicle crowding in the ovaries of livestock or characterized these crowds according to follicular morphology and ovarian location (portions and regions) in any species. Therefore, the present study aimed to assess the crowding (clustering and neighborhood) patterns of preantral follicles in the equine ovary according to mare age, follicular morphology and developmental stage, and spatial location in the ovary. Ovaries from mares (n = 8) were collected at an abattoir and processed histologically for evaluation of follicular clustering using the Morisita Index and follicular neighborhoods in ovarian sections. Young mares were found to have a large number of preantral follicles with neighbors (n = 2,626), while old mares had a small number (n = 305). Moreover, young mares had a higher number of neighbors per follicle (2.6 ± 0.0) than old mares (1.2 ± 0.1). Follicle clustering was shown to be present in all areas of the ovary, with young mares having more clustering overall than old mares and a tendency for higher clustering in the ventral region when ages were combined. Furthermore, follicles with neighbors were more likely to be morphologically normal (76.5 ± 6.5%) than abnormal (23.5 ± 6.5%). Additionally, morphologically normal activated follicles had increased odds of having neighbors than normal resting follicles, and these normal activated follicles had more neighbors (2.6 ± 0.1) than normal resting follicles (2.3 ± 0.1 neighbors). In the present study, it was demonstrated that preantral follicles do crowd in the mare ovary and that clustering/neighborhood patterns are dynamic and differ depending on mare age, follicular morphology, and follicular developmental stage.