Distinct waves of ovarian follicles contribute to mouse oocyte production

Reviewer #1 (Public review):

Multiple waves of follicles have been proven to exist in multiple species, and different waves of follicles contribute differently to oogenesis and fertility. This work characterizes the wave 1 follicles in mouse comprehensively and compares different waves of follicles regarding their cellular and molecular features. Elegant mouse genetics methods are applied to provide lineage tracing of the wave 1 folliculogenesis, together with sophisticated microscopic imaging and analyses. Single-cell RNA-seq is further applied to profile the molecular features of cells in mouse ovaries from week 2 until week 6. While extensive details about the wave 1 follicles, especially the atresia process, are provided, the authors also identified another group of follicles located in the medullary-cortical boundary, which could also be labeled by the FoxL2-mediated lineage tracing method. The "boundary" or "wave 1.5" follicles are proposed by the authors to be the earliest wave 2 follicles, which contribute to the early fertility of puberty mice, instead of the wave 1 follicles, which undergo atresia with very few oocytes generated. The wave 1 follicle atresia, which degrades most oocytes, on the other hand, expands the number of theca cells and generates the interstitial gland cells in the medulla, where the wave 1 follicles are located. These gland cells likely contribute to the generation of androgen and estrogen, which shape oogenesis and animal development. By comparing scRNA-seq data from cells collected from week 2 until week 6 ovaries, the author profiled the changes in numbers of different cells and identified key genes that differ between wave 1 and wave 2 follicles, which could potentially be another driver of different waves of folliculogenesis. In summary, the authors provide a high amount of new results with good quality that illustrate the molecular and cellular features of different waves of mouse follicles, which could be further reused by other researchers in related fields. The findings related to the boundary follicles could potentially bring many new findings related to oogenesis.

This paper is overall well-written with solid and intriguing conclusions that are well supported. The reviewer only has some minor comments for the authors' consideration that could potentially help with the readability of the paper.

(1) The authors identify the wave 1.5 follicles at the medullary-cortex boundary, which begin to develop shortly after 2 weeks. Since the authors already collected scRNA-seq data from week 2 until week 6, could any special gene expression patterns be identified that make wave 1.5 follicle cells different from wave 1 and wave 2?

(2) Are Figures 1C and 1E Z projections from multiple IF slices? If so, please provide representative IF slice(s) from Figures 1C and 1E and clearly label wave 1 and wave 2 follicles to better illustrate how the wave 1 follicles are clarified and quantified.

(3) For Figure 3D, please also provide an image showing the whole ovary section, like in Figures 3A and 3C, to better illustrate the localization and abundance of different cells.

(4) In Figure 4H, expressions of HSD3B1 and PLIN1 seem to be detected in almost all medulla cells. Does this mean all medulla cells gain gland cell features? Or there is only a subset of the medulla cells that are actively expressing these 2 proteins. Please provide image(s) with higher magnification to show more clearly how the expression of these 2 proteins differs among different cells.

(5) Figure 5: The authors discussed cell number changes for different types of cells from week 2 to week 6. A table, or some plots, visualizing numbers of different cell types, instead of just providing original clusters in Dataset S6, at different time points, would make the changes easier to observe.

(6) Figure S7: It would be more helpful to directly show the number of wave 1 follicles.

(7) Did the fluorescence cryosection staining (Line 587 - 595) use the same buffers as in the whole-mount staining (Line 575 - 586)? Please clarify.

(8) In Line 618, what tissue samples were collected? Please point out clearly.

Reviewer #2 (Public review):

Summary:

This study explores an important question concerning the developmental trajectory of wave 1 ovarian follicles, leveraging valuable tools such as lineage tracing and single-cell RNA sequencing. These approaches position the authors well to dissect early follicle dynamics. The study would benefit from more in-depth analysis, including quantification using the lineage-traced ovaries, and comparison of wave 1 and 2 follicular cells per stage within the single cell dataset.

Strengths:

This study aims to address an important question regarding the developmental trajectories of wave 1 ovarian follicles and how they differ from wave 2 follicles that contribute to long-term fertility. This is an important topic, as many studies on ovarian follicle development rely on samples collected at perinatal timepoints in the mouse, which primarily represent wave 1 follicles, to infer later fertility. The research group has the tools and expertise necessary to tackle these questions.

Weaknesses:

Wave 1 follicles are quantified based on the criteria of oocytes larger than 20 µm located within the medullary region, using whole-mount staining. However, the boundary between the medulla and cortex appears somewhat arbitrary. Quantification using FOXL2-lineage-traced ovaries provides a more reliable method for identifying wave 1 follicles. As the developmental trajectory of wave 1 follicles has been well described in Zhang et al. 2013, it would be valuable to provide a more detailed quantification of both labeled and unlabeled follicles by specific follicle stages. In fact, in Zhang et al. 2013, the authors demonstrated that lineage-labeled primordial follicles can be found at the cortex-medulla boundary, suggesting that the observation of labeled "border follicles" is not unexpected. Quantification by follicle stage would provide greater insight into the timing and development of these follicles.

Similarly, the analysis of wave 1 follicle loss should be performed on lineage-traced ovaries using cell death markers to demonstrate the loss of oocytes and granulosa cells, while confirming the preservation of theca and interstitial cells. In particular, granulosa cell loss should be assessed directly with cell death markers in lineage-traced ovaries, rather than from the loss of tamoxifen-labeled cells, as labeling efficiency varies between follicles (Figure 2G).

Single-cell RNA sequencing presents a valuable dataset capturing the development of first-wave follicles. The use of a 40µm cell strainer during cell collection for the 10x platform may explain the exclusion of larger oocytes. However, it is still surprising that no oocytes were captured at all. The central question, how wave 1 follicular cells differ from wave 2 cells, should be investigated in more depth, with results validated on FOXL2-lineage-traced ovaries (i.e., Wnt4 staining in wave 1 antral follicles versus wave 2 using lineage-traced ovaries). This analysis should span all stages of follicle development. It also appears to be a missed opportunity that the single-cell sequencing analysis was not performed on lineage-traced ovaries, which would have enabled more definitive identification of wave 1-derived cells.

Finally, this study does not directly assess fertility outcomes and should therefore refrain from drawing conclusions about the fertility potential of wave 1 follicles.