Integration of single-cell transcriptome of female early gonadal development in bovine, goats, and pigs

Shiyao Han; Qianhui Zou; Yifei Fang; Junmei Zhang; Yue Su; Shengcan Xie; Zhen Yang; Yiyu Zhao; Ningxiao Li; Wenjing Wan; Linxiu Yue; Heshuangyi Xie; Yulei Wei; Ellie Duan; Young Tang

doi:10.1016/j.isci.2026.116074

. 2026 May 22;29(6):116074. doi: 10.1016/j.isci.2026.116074

Integration of single-cell transcriptome of female early gonadal development in bovine, goats, and pigs

Shiyao Han ^1,⁵, Qianhui Zou ^2,⁵, Yifei Fang ^3,⁵, Junmei Zhang ⁴, Yue Su ¹, Shengcan Xie ¹, Zhen Yang ¹, Yiyu Zhao ¹, Ningxiao Li ¹, Wenjing Wan ¹, Linxiu Yue ¹, Heshuangyi Xie ¹, Yulei Wei ^4,^∗, Ellie Duan ^3,^∗∗, Young Tang ^1,^6,^∗∗∗

PMCID: PMC13224005 PMID: 42231951

Summary

The molecular programs governing early female gonadal development in livestock remain incompletely characterized. Here, we generated a single-cell transcriptomic atlas of bovine fetal ovaries spanning sex determination to early folliculogenesis and performed an integrated cross-species comparison with goats and pigs. We identified major germline and somatic cell populations and reconstructed germ cell differentiation trajectories, revealing conserved stages of pluripotency, retinoic acid (RA) response, and meiotic initiation, alongside species-specific developmental dynamics. Notably, goats exhibited delayed meiotic progression compared with bovine and pigs. Transcription factor analysis uncovered both conserved and bovine-specific regulators in granulosa cells. Cell-cell communication analysis further highlighted prominent RA-responsive MDK/PTN-NCL signaling and increased network interactions during meiotic entry in bovine and porcine but absent in pre-meiotic goat gonads. These findings provide a cross-species framework for early ovarian development in livestock and offer novel insights into mammalian gametogenesis and reproduction.

Subject areas: developmental anatomy, animals, transcriptomics

Graphical abstract

Highlights

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A single-cell atlas of early bovine ovarian development
•
Cross-species analysis reveals conserved and species-specific germ cell differentiation
•
Goats exhibit delayed meiotic progression relative to cattle and pigs
•
RA-responsive MDK/PTN-NCL signaling shapes the microenvironment for meiotic entry

Developmental anatomy; Animals; Transcriptomics

Introduction

Sexual reproduction in mammals relies on the precise development of male and female gonads, a process initiated from the bipotential embryonic genital ridge.¹ The fate of this primordium is determined by a complex cascade of genetic and cellular events, leading to the differentiation of somatic support cells (Sertoli in males and granulosa in females) and the establishment of a niche for germ cell development.² In females, primordial germ cells (PGCs) enter meiosis shortly after the differentiation of granulosa cells and subsequently arrest at the diplotene stage.³ This process is cooperatively promoted by the activation of the RSPO1/WNT4/β-catenin pathway⁴^,⁵^,⁶^,⁷^,⁸^,⁹ and FOXL2.¹⁰^,¹¹ In contrast, in male gonads, expression of SRY followed by SOX9 and CITED4 drives the differentiation of Sertoli cells,¹²^,¹³^,¹⁴ and germ cells become mitotically arrested after sex determination.¹⁵ While the core principles of sex determination are established, the complete regulatory landscape, particularly the intricate crosstalk between germ cells and somatic cells, remains an area of active investigation.

Our understanding of these processes is largely derived from studies in mice and humans. These models have revealed conserved regulators of PGC specification like PRDM1, PRDM14, and TFAP2C.¹⁶^,¹⁷^,¹⁸ However, critical species differences also exist. For example, SOX2 is expressed in mouse but repressed in human PGCs, while SOX17 is essential only for the specification of human PGCs.¹⁹^,²⁰ These species-specific regulations indicate that a truly comprehensive view of mammalian gametogenesis requires a broader phylogenetic perspective. Particularly, major livestock species, such as goats, pigs, and cattle, represent distinct evolutionary lineages and are vital for global agriculture. Despite their importance, the molecular choreography of early gonadal development in these species remains poorly characterized at single-cell resolution.²¹ While recent single-cell RNA sequencing (scRNA-seq) studies have provided valuable insights into the early gonadal development of goats and pigs,²² comprehensive comparative analyses across these species are lacking. Cattle, in particular, have been notably absent from such studies, despite their significant role in agriculture and unique reproductive characteristics. Moreover, a systematic, integrated cross-species comparison is lacking, leaving a gap in our knowledge of both conserved and species-specific early gonadal developmental programs. For instance, while some transcriptional regulators and signaling pathways, such as FOXL2²³ and WNT/β-catenin, are conserved across species, the regulation of gonadal development can vary substantially between livestock species due to differences in reproduction strategies, gestational length, and embryonic development.²⁴

Here, we present a single-cell transcriptomic atlas of fetal bovine ovarian development across key gestational stages and integrate these data with existing dataset from goats and pigs. This study aims to (1) define the cellular composition and transcriptional trajectories of germ and somatic cells during early female gonadogenesis; (2) identify conserved and species-specific transcriptional regulators; and (3) decipher the cell-cell communication networks that orchestrate these key developmental processes. Our work provides a foundational resource that not only elucidates the fundamental biology of gonadal development in ruminants and monogastric but also opens new avenues for advancing precision breeding and in vitro gametogenesis technologies.

Results

A single-cell atlas of early bovine ovarian development

To define the cellular landscape of early female gonadal development in cattle, we performed scRNA-seq on fetal bovine ovaries across six gestational stages (E38, E46, E73, E83, E92, and E112) together with the data for an E50 female bovine gonad,²⁵ these samples cover several key events including sex determination, pre-granulosa differentiation, meiosis initiation, and folliculogenesis (Figure 1A). By integrating the sequencing data from all seven stages, 54,268 high-quality cells were retained for analysis. Germ cells and gonadal somatic cells were first identified by automated marker-based annotation and then manually curated based on the enrichment of marker genes previously established in mouse²⁶ and human²⁷ studies, resulting in 8,221 germ cells and 46,047 somatic cells.

Unsupervised clustering identified seven major cell types (Figure 1B; Table S1). Germ cells are annotated by established markers, such as POU5F1, NANOG, and DAZL (Figures 1C and S1A). The somatic compartments consisted of granulosa cells expressing TRIB2 and WNT6, stromal cells with PDGFRA and TCF21, endothelial cells expressing PECAM1, undifferentiated gonadal somatic cells with LHX9 and WT1, and immune cells expressing PTPRC and CD14 (Figures 1C and S1A). The “Other cells” refers to a cluster expressing kidney-related genes (OSR1, PAX2/8) most likely from cells of mesonephros tissue.

Our analysis reveals that bovine female PGC development shares considerable conservation with humans and mice, including core pluripotency factors for early PGCs (POU5F1, NANOG, and NANOS3), germ cell-specific markers such as DDX4 and DAZL, meiotic markers SYCP1, SYCP3, and primary oocyte marker FIGLA (Figures 1C and S1A). Bovine granulosa cells exhibited significant enrichment of TRIB2 (Figure 1C), which was known as a critical regulator for bovine ovarian folliculogenesis,²⁸^,²⁹ and was also detected in porcine and goat granulosa cells.²²^,³⁰ Another granulosa fate determinant, RUNX1,³¹ was also detected in bovine granulosa cells (Figure S1A). Similar to humans,²⁰ SOX17 is expressed in bovine germ cells (Figure S1A), indicating a conserved role for SOX17 in bovine PGC development.

Cross-species germ cell developmental trajectories reveal conserved programs and divergent meiotic timing

We next integrated our bovine data with public scRNA-seq datasets from female goat (E32, E34, E36, and E40) and porcine (E27, E30, and E35) gonads²² to conduct a cross-species comparative analysis (Figure 2A; Table S2). Integrated clustering of all three species robustly separated germ cells from somatic populations (Figure 2B). Germ cells were further separated into a mitotic PGC group, characterized by POU5F1 and NANOG, and a retinoic acid (RA)-responsive/meiotic PGC group that expressed STRA8 and SYCP1. Interestingly, both DDX4 and DAZL were detected in both mitotic and RA-responsive/meiotic groups (Figure 2C).

Cross-species germ cell trajectories reveal conserved programs and divergent meiotic timing

(A) Schematic diagram of experimental work flow for female bovine, porcine, and goat gonad analysis.

(B) t-stochastic neighborhood embedding (t-SNE) visualization of female gonadal cell clusters from bovine, pigs, and goats. Cells are color-coded according to different cell types.

(C) Left: t-SNE visualization of female germ cells from bovine, pigs, and goats. Cells are color-coded according to different cell types and species. Right: the expression levels of representative markers for relevant cell types.

(D–F) Top: pseudotime trajectories of female germ cells in bovine, pigs, and goats. Bottom: heatmap for gene expression levels along the pseudotime trajectories. Representative genes were listed (right).

(G) Left: heatmap for DEGs identified among female bovine, porcine, and goat gonadal germ cells. Right: GO analysis based on these DEGs.

To further define the dynamics of transcriptional regulation in female gonadal germ cell development, we reconstructed pseudotime trajectories for germ cells of each species (Figures 2D–2F). Early stages across all species were marked by high expression of pluripotency factors (POU5F1, NANOG, and TFAP2C), and the cell migration and homing receptor CD9³² (Figures 2D–2F). Bovine and goat early trajectories express cytoskeleton gene KRT7, lysosomal protease gene CTSV,³³ lipid and steroidogenesis metabolism gene APOE,³⁴ and AKR1B1—encoding the rate-limiting enzyme in polyol pathway³⁵ (Figures 2D and 2E). In bovine and porcine early trajectories, the lysosome/autophagy-related gene LAMP2³⁶ was highly expressed (Figures 2D and 2F), whereas in goat and porcine early trajectories, PGC marker KIT and ubiquitin ligase HERC5 were highly expressed (Figures 2E and 2F). A key divergence was the timing of meiotic entry: STRA8 and SYCP1 were highly expressed in the middle-to-late stages of bovine and porcine trajectories but were not detected in goats (Figures 2E and 2F), indicating uninitiated meiosis up to the sampling stage (E40). This observation was consistent with the proposed onset of meiosis (∼E56) in female goat gonads.³⁷^,³⁸

Various differentiation genes are expressed across early, middle, to late developmental stages in each species, such as CTSD,³⁹ CDH16,⁴⁰^,⁴¹ and CSMD3.1⁴² in bovine (Figure 2D), DPYSL3,⁴³ RELN, DAB2,⁴⁴ PECAM1, LYVE1, and SOX18⁴⁵ in goats (Figure 2E), and COX1/2,⁴⁶^,⁴⁷ BBX,⁴⁸ NCAM1, PLD6,⁴⁹ RDX,⁵⁰ and KRT18 in pigs (Figure 2F). These data indicate that early female germ cell differentiation in livestock follows a broadly conserved trajectory including early PGC marker expression, lysosomal activity regulation, RA-responsive and meiosis onset, yet with species-specific dynamics for the expression of differentiation regulators.

To further investigate the conservation and divergence of germ cell development in livestock, we identified differentially expressed genes (DEGs) across female bovine, goat, and porcine germ cells (Figure 2G; Table S3). Gene Ontology (GO) analysis on upregulated DEGs revealed enrichment on biological process (BP) for “proteasome-mediated ubiquitin-dependent protein catabolic process” across all three species, while “organelle fission” and “mitotic cell cycle phase transition” were shared between bovine and goats, and “establishment of protein localization to organelle” was common to bovine and pigs (Figure 2G). These findings suggest that while DEGs vary by species, some of their regulatory roles in PGC development may be evolutionarily conserved. On the other hand, species-unique terms were identified, such as “stem cell population maintenance” and “ribonucleotide metabolic process” in goats; and “ribosome biogenesis”, “rRNA metabolic process”, and “establishment of organelle organization” in pigs, suggesting distinct regulatory emphases during PGC development.

Cross-species comparative analysis of female gonadal somatic cells in livestock

Integrating female gonadal scRNA-seq data from bovine, goats, and pigs identified 5 gonadal somatic cell clusters: granulosa cells, stromal cells, endothelial cells, immune cells, and undifferentiated somatic cells (Figure 2A). The cellular architecture was conserved across species, with granulosa (47.4%–57.7%) and stromal cells (33.7%–35.7%) constituting the majority population (Figure 3A).

Expression of key granulosa cell markers varied significantly by species (Figures 3B and S1B). For example, TRIB2 was highly expressed in bovine and goats, WNT6 in bovine and pigs, and AMHR2 was predominantly porcine. NR5A1 expression was markedly weaker in goats, in line with its low expression compared to humans, macaques, and pigs²² (Figure 3B). Interestingly, FOXL2, a critical granulosa cell determinant in humans and mice,²⁷ was only weakly detected in bovine and pigs and not detected in goats for the sampled stages (Figure S1B), in contrast to its robust expression in adult bovine follicular granulosa cells (Figure S1C). These results indicate species-specific and temporally regulated role of FOXL2 for early ovarian development in livestock.

To assess functional conservation and divergence in granulosa cells development across the three species, we performed GO analysis on upregulated DEGs enriched in each species (Figure 3C; Table S4). In cattle, enrichments for “small GTPase-mediated signal transduction” and “Wnt signaling pathway” highlight the importance of these signals in granulosa cell development. In goat, “mitochondria inner membrane” and “energy derivation by oxidation of organic compounds” were enriched, implicating a unique role for energy metabolism in goat granulosa cells. In pigs, “in utero embryonic development” was enriched, suggesting a species-specific developmental regulation (Figure 3C). Overall, these results showed shared somatic cell composition with divergent, species-specific regulatory programs during granulosa cell differentiation in livestock species.

Conserved and species-specific transcriptional networks govern germ and somatic cell fate

To further define the transcriptional regulatory networks underlying gonad developmental programs, we performed transcription factor (TF) network analysis using pySCENIC (Table S6). In germ cells, 145 conserved TFs were identified across the three species (Figure 4A), including pluripotency regulators such as STAT3 and TFAP2C,⁵¹^,⁵² the cell cycle regulators such as E2F6, E2F8, MYC, MYB, MYBL1, TP53, and FOXO1,⁵³^,⁵⁴^,⁵⁵^,⁵⁶ and the RA-responsive factors RARA and RARG (Figure 4A; Table S5). GO analysis for the conserved TFs identified enrichment terms for multi-organ, tissue, and cell type development, RA receptor signaling pathway, growth hormone/cell surface receptor signaling pathways via JAK-STAT3, and transforming growth factor beta (TGFβ) receptor signaling pathway (Figure 4B; Table S6). GO terms related to in utero embryonic development and mammary gland development were also enriched (Figure 4B; Table S6).

We next compared the expression of TFs across three livestock species. Several TFs shared high expression among all female germ cells were identified, including PGC regulator PRDM1, mitosis/meiosis regulators RAD21, CHD1, the stress-response and translational control factor ATF4,⁵⁷^,⁵⁸ cell proliferation factor YY1, the epigenetic regulators KAT7, MLL10, the critical oocyte regulator HDAC2,⁵⁹ the PRC2 component MTF2, the genome organizer CTCF, and the SWI/SNF component HITF (Figure 4C; Table S7). These common TF enrichments highlight the central role of chromatin remodeling in livestock PGC development.

Another SWI/SNF family member, SMARCA5, which is essential for meiotic progression in mouse germ cells,⁶⁰^,⁶¹ was expressed only in meiotic-progressing bovine and porcine germ cells but absent in pre-meiotic goats, consistent with the developmental timing (Figure 4C). In addition, the H3K4me2 reader PHF20 was highly expressed in bovine and goats, whereas expression of chromatin organizer SATB2 was higher in goats and pigs (Figure 4C). These data revealed conserved as well as species-specific epigenetic reprogramming regulators for female germ cell development in livestock.

Similarly, we performed pySCENIC analysis to identify TFs involved in granulosa cell development across species (Table S9). We identified 128 conserved TFs in granulosa cells, including gonadal somatic determinants, such as GATA4, WT1, NR2F1, LHX9, and FOXO1, the cell cycle and differentiation regulators, such as FOS, FOSL1, ETS1, RA-receptors RARA, RARG, RXRG, and the lipid metabolism regulator PPARG (Figure 4D; Table S8) GO enrichment analysis revealed pathways closely associated with gonadal development, including cell fate determination, BMP signaling, TGF-β receptor signaling, and RA receptor signaling (Figure 4E). Additionally, SMAD protein signal transduction and in utero embryonic development were also enriched, highlighting key regulatory networks involved in sex differentiation. (Figure 4E; Table S9).

We further compared the expression of the identified TFs in granulosa cells. Across the three species, highly expressed TFs included key genital ridge and gonadal somatic determinants WT1 and EMX2,⁶²^,⁶³^,⁶⁴ BMP signal mediator SMAD1, WNT signal mediators LEF1 and TCF3, cell survival and stress-response gene ATF4, cell proliferation factor SMC3, SP3, the epigenetic regulators HDAC2 and HITF (Figure 4F; Table S10). In contrast, SMAD2, WNT6, MXI1, and PBX1 were expressed strongly in bovine and pigs, whereas SOX4 and JUN were expressed more in bovine and goats, and HOXD9, TBX3, and HES1 were expressed more in pigs and goats. Interestingly, NPAS2, PBX3, and SOX5 were only highly expressed in bovine granulosa cells (Figure 4F). Among these bovine-specific TFs, PBX3 is associated with primate granulosa cell development,²⁷ and SOX5 is expressed in mouse gonadal somatic cells and germ cells, with loss-of-function causing female-to-male reversal in Medaka fish.⁶⁵ Together, these data suggest potential regulatory roles of these TFs in cattle ovary development.

A retinoic acid-responsive signaling axis defines the meiotic microenvironment

We used CellChat⁶⁶ to map conserved and species-specific cell-cell communication networks in bovine, goats, and pigs (Figures S2A and S2B). Within each species, cell-cell communications appear stronger among the three somatic populations (stromal cells, endothelial cells, and immune cells) and also between germ cells and non-granulosa somatic cells than between granulosa and germ cells (Figure 5A). To identify pivotal ligand-receptor interacting pairs, we further compared the signals sent from three gonadal somatic populations to germ cells (Figure 5B), and from germ cells to each of the somatic cell population (Figure 5C). Across all species, two pairs of interactions were conserved: the canonical germ cell development KITL-KIT⁶⁷ (Figure 5B) signaling from granulosa to germ cells and the extracellular matrix (ECM)-integrin signal LAMC1-(ITGA6+ITGB1) (Figure 5C) from germ cells to granulosa. Additionally, the KITL-KIT interaction was found to also initiate from endothelial cells to germ cells in pigs and from stromal cells to germ cells in pigs and goats (Figure 5B).

The ECM components, laminin and collagen, play critical roles in supporting spermatogenesis in testis, and reduction of LAMA1 correlates with the loss of spermatogenesis in humans.⁶⁸^,⁶⁹ We identified that between germ cells and granulosa cells, different species showed distinct ECM ligand and receptor pairs: in cattle, LAMA1/2-(ITGA6+ITGB1) and COLA4A1-ADGRG1; in goats, LAMB1-(ITGA6+ITGB1), COLA4A1/4-(ITGA10+ITGB1), and FN1-(ITGAV+ITGB1); and in pigs, LAMC1-DAG1 (Figures 5B and 5C). These data indicate conserved as well as species-specific ECM signals for germ cell/granulosa communication, potentially regulating cell survival and differentiation for female livestock gonad development, similarly as they do in human male gonads.

Intriguingly, a robust Midikine-Nucleolin (MDK-NCL) interaction consistently presents in female bovine and pigs that is initiated from all three somatic cell populations to germ cells (Figure 5B). Pleiotrophin (PTN) also exhibited a strong PTN-NCL interaction that initiates from granulosa and stromal cells to germ cells in bovine and pigs (Figure 5B). MDK and PTN are retinoic acid (RA)-responsive heparin-binding growth factors abundantly expressed during mouse urogenital development⁷⁰^,⁷¹ and in human amniotic fluids.⁷² MDK was also identified in human granulosa cells, follicular fluid, and medulla of adult ovaries.⁷³ In contrast, the MDK-NCL or PTN-NCL axis was absent in pre-meiotic goat gonads (Figure 5B). These data thus implicate a critical role of RA-responsive MDK/PTN-NCL signaling axis for the establishment of meiotic microenvironment in female gonads.

We further analyzed the interactions among gonadal somatic cells (granulosa, stromal, and endothelial cells) across species (Figures S3A–S3C). Although the overall numbers of germ cell-somatic interactions appear similar across the three species (Figures 5B and 5C), there are obviously more extensive inter-somatic cell communications in bovine and porcine gonads than in goats (Figures S3A and S3B), and no cell-cell interaction was identified from goat endothelial to the other two somatic cell populations for the sampled stages (Figure S3C). Furthermore, in bovine and pigs, extensive interactions were identified between granulosa and endothelial cells for ECM-mediated laminin/collagen and their receptor pairs (Figures S3A and S3C), and between stromal and endothelial cells (Figures S3B and S3C), while these interactions are sparse in goats. Together, these data strongly support the model for a surge of intercellular signaling at the onset of meiosis, prominently the ECM-mediated cues and the RA-responsive MDK/PTN-NCL axis that functions on creating the niche in early female gonads to support proper development of primordial follicles.

Discussion

While mammalian gonadal development has been extensively characterized in mice and humans, analogous processes in livestock remain poorly defined. This study provides the first single-cell transcriptomic atlas of fetal bovine ovarian development and integrates these data with goat and pig gonads to uncover conserved and species-specific regulatory programs governing early female gametogenesis in livestock.

In addition to the pluripotent markers such as POU5F1 or NANOG, our analysis revealed a conserved network of germ line regulators, such as PRDM1, STAT3, and TFAP2C across all species, underscoring their essential roles in PGC development and identity. The consistent expression of CD9 in early PGCs across livestock identifies a practical surface marker for isolating germline populations in non-model organisms for downstream research and applications. Beyond classical markers, we identified additional transcriptional regulators, such as YY1, FOXO1, MYC, ATF4, RAD21, and CHD1 across all three species, suggesting broader transcriptional circuitry coupling stress response and mitotic cell-cycle control to germ cell specification and differentiation.

A particularly exciting finding was the high expression of a suite of epigenetic regulators, such as KAT7, MLL10, HDAC2, MTF2, CTCF, and HITF, in germ cells across livestock species. As PGCs undergo extensive epigenomic reprogramming, such as DNA demethylation, imprinting, and X chromosome inactivation to reset the developmental clock,⁷⁴^,⁷⁵ the conserved expression of these genes strongly implies a critical and previously underappreciated role for their regulatory network in livestock germ cell development. Species-specific features further refine this picture. For example, SMARCA5, an SWI/SNF chromatin remodeler essential for meiotic progression in mice,⁶⁰^,⁶¹ expressed exclusively in bovine and porcine germ cells, consistent with their progression into meiosis during their sampled stages, whereas goat gonads remained pre-meiotic. These findings highlight both the conservation and evolutionary divergence of meiotic initiation mechanisms across mammals.

Our analysis of the somatic compartment also revealed a core of conserved regulators. In addition to WT1, TFs, such as EMX2, SMAD1, LEF1, and TCF3 are highly expressed in granulosa cells across livestock species, reaffirming the pivotal roles of BMP and WNT/β-catenin signaling in granulosa cell proliferation, differentiation, and primordial follicle activation,⁷⁶^,⁷⁷^,⁷⁸ as well as the potential importance of EMX2, a key regulator of mouse gonadal and urogenital morphogenesis,⁶²^,⁶³ in livestock ovarian development. Interestingly, bovine granulosa cells displayed specific enrichment of PBX3 and SOX5, factors previously linked to primate granulosa cell function and vertebrate sex determination,²⁷^,⁶⁵ suggesting potential ruminant-specific adaptations in granulosa differentiation and follicle assembly.

A defining feature of this study is the identification of the robust MDK/PTN-NCL signaling axis from somatic cells to germ cells in bovine and pigs, which was conspicuously absent in goats. As a pleiotropic heparin-binding growth factor, MDK and its homolog PTN are known to be crucial in embryogenesis, tissue repair, and cancer progression through receptors such as ALK and LRP1. Previous studies have highlighted the importance of MDK/PTN signaling in a variety of biological processes. For example, Jiang⁷⁹ demonstrated that MDK promotes angiogenesis and tumor growth by activating ALK and LRP1 in cancer cells. In reproduction, MDK has been implicated in supporting primordial follicle assembly in mice.⁸⁰ As MDK is a known retinoic acid-responsive factor, the timing of this signaling correlates with the onset of meiosis, suggesting that MDK/PTN-NCL interactions form part of a conserved meiotic microenvironment that orchestrates germ-somatic communication and primordial follicle assembly, with its expression known to be regulated by retinoic acid, linking the timing of MDK signaling to the onset of meiosis.⁸¹ These findings suggest that MDK/PTN-NCL interactions are part of a conserved meiotic microenvironment that orchestrates germ-somatic communication and primordial follicle assembly. Moreover, MDK is overexpressed in various human malignancies, including ovarian cancer, and regulates cancer cell growth, survival, migration, and angiogenesis.⁸² The absence of this pathway in goat samples, which have yet to enter meiosis at comparable developmental stages, reinforces its likely role in coordinating meiotic initiation and gonadal microenvironmental remodeling. This spatial-temporal activation pattern, coupled with the extensive ECM-mediated signaling in bovine and porcine gonads, points to a coordinated surge in intercellular crosstalk at the onset of meiosis, which may be a crucial event for constructing proper cellular architecture and providing necessary signals to support the formation of follicle pool in gonads. This is the first identification of the MDK/PTN-NCL axis as a meiotic niche signal in mammals.

Our findings support a working model in which the comparatively delayed meiotic initiation observed in the fetal goat ovary arises from coordinated temporal regulation of germ cell-intrinsic and somatic niche-derived signals. In mammals, RA signaling licenses meiotic entry through activation of STRA8 and associated regulators.⁸³ We propose that species-specific differences in RA dynamics or tissue responsiveness shift the window of meiotic competence in goats. Critically, meiotic entry is not solely germ cell-autonomous but depends on a permissive somatic microenvironment. Delayed maturation of pre-granulosa cells and gradual establishment of WNT/BMP-mediated paracrine signaling may transiently constrain germ cell sensitivity to RA, thereby postponing meiotic onset.⁸⁴ Within this framework, FOXL2 upregulation marks the progressive stabilization of granulosa cell identity and ovarian fate,⁸⁵ reinforcing somatic support necessary for follicle assembly rather than directly triggering meiosis. Concurrently, MDK signaling may modulate germ cell survival and extracellular matrix remodeling during cyst breakdown,⁸¹ integrating survival and differentiation cues. Together, these processes form a temporally coordinated regulatory network that delays meiotic entry while optimizing primordial follicle establishment, ultimately shaping the slower developmental tempo of the goat ovary.

In conclusion, our comparative single-cell analyses delineate both universal and species-specific gene expression programs, transcriptional regulators, and cell-cell communication events underlying early ovarian development in livestock. This work establishes a valuable resource for the reproductive biology community and offers a framework for future functional and translational studies, ranging from fertility optimization and genetic improvement in breeding programs to advances in in vitro gametogenesis.

Limitations of the study

Despite providing a comprehensive single-cell atlas of bovine fetal ovarian development and cross-species comparisons, several limitations should be acknowledged.

First, this study is primarily based on transcriptomic data, and the inferred cellular states, developmental trajectories, and regulatory networks lack direct functional validation. Future studies integrating genetic or in vitro functional assays will be necessary to confirm the roles of identified key regulators and signaling pathways. Second, although cross-species integration was performed using orthologous genes, potential biases arising from differences in genome annotation, sequencing depth, and sample collection stages across species may influence the comparative analyses. Therefore, some species-specific differences observed in this study should be interpreted with caution. Third, the developmental stages analyzed in this study, while covering key transitions from sex determination to early folliculogenesis, may not fully capture the complete dynamics of germ cell maturation, particularly later stages of meiosis and follicle development. Finally, cell-cell communication analysis was inferred computationally based on ligand-receptor expression and does not directly measure physical interactions or signaling activity. Experimental validation will be required to confirm the predicted signaling pathways, including RA-responsive and MDK/PTN-NCL signaling.

Resource availability

Lead contact

Further information and requests for resources should be directed to the lead contact, Young Tang (youngtang@nwafu.edu.cn).

Materials availability

This study did not generate new unique reagents.

Data and code availability

Data: Single-cell RNA-seq data have been deposited in CNCB under accession OMIX012725 and are publicly available.
Code: Code is available from the corresponding author upon reasonable request.
Additional Information: Any additional information required is available from the lead contact.

Acknowledgments

This work was supported by the Biological Breeding-National Science and Technology Major Project (2023ZD0407504) and the Chinese Universities Scientific Fund (245-2023-F2010123001 and 245-2025-Z1090224009). Additional support was provided by the National Science Foundation (grant #2213824).

Author contributions

S.H., conceptualization, methodology, software, validation, investigation, writing – original draft, and review and editing; Q.Z., software, investigation, formal analysis, data curation, and visualization; Y.F., software, resources, investigation, and writing – review and editing; J.Z., validation and formal analysis; Y.S., investigation; S.X., data curation and formal analysis; Z.Y., investigation and visualization; Y.Z., resources; N.L., investigation; W.W., visualization; L.Y., resources; H.X., investigation; Y.W., supervision, project administration, and writing – review and editing; E.D., supervision, funding acquisition, and writing – review and editing; Y.T., supervision, conceptualization, formal analysis, funding acquisition, and writing – original draft; all authors have read and agreed to the published version of the manuscript.

Declaration of interests

The authors declare no competing interests.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Biological samples

Bovine female embryonic tissues (E46, E73, E83, E92and E112)	local slaughterhouse	N/A

Critical commercial assays

Single Cell 3' RNA-Seq Kit (v2.1)	MobiDrop	cat. no. S050200201
microfluidic chip of Chip A Single Cell Kit	MobiDrop	cat. no. S050100201

Deposited data

Single-cell RNA Sequencing - raw data	This paper	CNCB: OMIX012725

Software and algorithms

Cell Ranger(3.1)	10x Genomics	https://support.10xgenomics.com/single-cell-gene-expression/software/overview/welcome
Seurat package (v5.2.0)	Hao & Hao et al., 2021	https://satijalab.org/seurat/
pySCENIC (v0.11.2)	Van de Sande et al.⁸⁶	https://pyscenic.readthedocs.io/en/latest/scenic.readthedocs.io/en/latest/
Monocle3	Trapnell Lab	https://cole-trapnell-lab.github.io/monocle3/
CellChat package (v1.6.1)	Jin et al., 2021;	https://github.com/sqjin/CellChat
org.Hs.eg.db (v3.13.0)	Wu et al., 2021	https://bioconductor.org/packages/release/data/annotation/html/org.Hs.eg.db.html
CellPhoneDB (v2.14.0)	Efremova et al., 2020	https://www.cellphonedb.org/

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Experimental model and study participant details

Animal models

Bovine fetal gonads were collected from female embryos at stages E38, E46, E73, E83, E92, and E112. Single-cell RNA sequencing data for fetal bovine (E38, E46, E73, E83, E92, E112) are available in the China National Center for Bioinformation (CNCB) database under accession number CNCB: OMIX012725.

Single-cell RNA sequencing data for pig and goat used in this study are publicly available in the Zenodo database (hosted by CERN) under accession number:zenodo.6918355.

Single-cell RNA sequencing data for bovine (E50) used in this study are publicly available in GEO (hosted by NCBI) under accession number: GSE162952.

Ethics statement

All animal experimental procedures were performed in accordance with the National Research Council's Guide for the Care and Use of Laboratory Animals and were approved by the Institutional Animal Care and Use Committee (IACUC) of Northwest A&F University (protocol code: IACUC2024-1204).

Method details

Fetal bovine gonad collection

Estrus signs of donor cows raised under natural conditions were observed daily to confirm pregnancy. Artificial insemination was performed once at the onset of detected estrus. Uteri were collected from cows slaughtered in a local slaughterhouse and transferred to a sterile laboratory for disinfection. Embryos were then dissected, and gonads were isolated. Morphologically intact fetal gonads with adequate cell viability were collected from both female embryos at stages E38, E46, E73, E83, E92and E112.

Sample information for single-cell RNA sequencing of bovine fetal gonads.

Sample ID	Breed	Sex	Gestational Age (days)	body weight(g)	Crown-Rump Length(cm)
F1	Simmental	Famale	112	638.26	24.5
F2	Simmental	Famale	92	339.24	18.1
F3	Simmental	Famale	83	170.97	15.4
F4	Simmental	Famale	73	91,89	12.6
F6	Simmental	Famale	46	9.72	2.9
F7	Simmental	Famale	38	3.47	1.7

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Single-cell suspension preparation of fetal gonads

To collect Primordial Germ Cells (PGCs) and gonadal somatic cells, gonads were dissected under a stereomicroscope and transferred to a 1.5 mL tube containing a digestion mix of 1 mg/mL Collagenase IV, 1 mg/mL Hyaluronidase, 0.25% Trypsin, and 1 mg/mL DNase I, followed by incubation at 37°C for 30 minutes. After digestion, serum was added to neutralize the enzymes. The cell suspension was pipetted repeatedly, filtered through a 40 μm cell strainer, and resuspended in 0.1% serum/PBS to prepare single-cell suspensions for 10x Genomics single-cell RNA-seq.

Single-cell RNA sequencing

The viability of the single-cell suspension exceeded 80%, and the cell concentration was adjusted to 700-1200 cells/μL. The cells of each sample were then processed with the MobiCube® High Throughput Single Cell 3' RNA-Seq Kit (v2.1) as per manufacturer' s instruction in Novogene Bioinformatics Technology Co., Ltd (Tianjing,China). The cells/nuclei were loaded into microfluidic chip of Chip A Single Cell Kit (MobiDrop, cat. no. S050100201) to generate droplets with MobiNova-100 (MobiDrop, cat. no.A1A40001). Each cell/nuclus was involved into a droplet which contained a gel bead linked with up to millions oligos (cell unique barcode). After encapsulation, droplets suffer light cut by MobiNovaSP-100 (MobiDrop, cat. no.A2A40001) while oligos diffuse into reaction mix. The mRNAs were captured by gel beads containing oligo(dT) in droplets. Following reverse transcription, cDNAs with barcodes were amplified, and a library was constructed using the High Throughput Single Cell 3’RNA-Seq Kit v2.0 (MobiDrop (Zhejiang) Co., Ltd., cat. no. S050200201) and the 3' Single Index Kit (MobiDrop (Zhejiang) Co., Ltd., cat. no. S050300201). Libraries were sequenced by the Illumina NovaSeq sequencer with 150-bp paired-end reads in Novogene Bioinformatics Technology Co. Ltd (Tianjing,China).

RNA-seq library preparation and sequencing

Total RNA was isolated using the miRNeasy Mini Kit (Qiagen, 217004), with integrity verified on an Agilent Bioanalyzer 2100 system. The RNA was then fragmented in First-Strand Synthesis Reaction Buffer (5X) using divalent cations at elevated temperature. First-strand cDNA was synthesized with random hexamer primers and M-MuLV Reverse Transcriptase (RNase H-), followed by second-strand synthesis using DNA Polymerase I and RNase H. Subsequent library fragments were purified and PCR-amplified with Phusion High-Fidelity DNA polymerase, universal PCR primers, and a unique index primer. The final PCR products were purified using the AMPure XP system, and library quality was assessed on the Bioanalyzer. Sequencing was performed by Novogene on an Illumina NovaSeq 6000 platform, generating approximately 50 million paired-end 150 bp reads per sample.

Single-cell RNA sequencing data processing

Raw sequencing data were processed using Cell Ranger (v3.1, 10x Genomics). Sequencing reads were aligned to the respective reference genomes. The reference genomes for cattle (ARS1), pig (Sscrofa11.1), and goat (ARS1) were built according to Cell Ranger instructions, with genome sequences and annotations obtained from Ensemble (release 98). The filtered feature-barcode matrices generated by Cell Ranger were used for subsequent analysis.

Cell identification

Based on differential expression analysis of this dataset and referenced published mammalian ovarian scRNA-seq studies²²

Cell clustering and annotation

Preliminary analysis of the single-cell data was performed using the Seurat package (v5.2.0). Low-quality cells expressing fewer than 300 genes and genes detected in fewer than 3 cells were filtered out. Cells with a mitochondrial gene count percentage exceeding 10% were also removed from the dataset. Data were normalized based on the top 2000 highly variable genes. Batch effects were corrected with Harmony. The Harmony-corrected data were subsequently used for dimensionality reduction, clustering, and manual cell type annotation based on the identification of cluster-specific marker genes in accordance following Seurat guidelines.

Differential expression gene (DEG) analysis and Gene Ontology (GO) enrichment

For each cell type, differential expression genes (DEGs) were identified using the Wilcoxon rank-sum test. Significance for both differential expression analysis and GO enrichment analysis was corrected for multiple testing using the Benjamini-Hochberg method, with an adjusted p-value (adj. p-val) < 0.05 considered statistically significant. For significant DEGs identified in specific cell types, Gene Ontology (GO) and KEGG pathway enrichment analyses were performed using the clusterProfiler package (v4.2.1) to identify enriched biological processes and pathways.⁸⁷

Transcriptional regulatory network analysis (SCENIC)

Gene regulatory network analysis was conducted using the Python package pySCENIC (v0.11.2). The analysis comprised three main steps: 1) Identification of co-expression modules between transcription factors (TFs) and potential target genes based on correlation; 2) Formulation and refinement of these modules, followed by motif enrichment analysis to define regulons (a TF and its direct target genes); 3) Evaluation of regulon activity in individual cells. Transcription factors with high weights and confidence were retained for downstream analyses, with correlation thresholds adjusted flexibly based on the number of pairs.⁸⁶

Pseudotime and cell trajectory inference

Pseudotime analysis and cell differentiation trajectory inference were performed using the Monocle3 package.⁸⁸ Cells were ordered along pseudotime, and UMAP was applied for dimensionality reduction. Following quality control and preliminary cell subtype annotation, which revealed a basic developmental hierarchy, cells with a progenitor state were manually specified as the trajectory starting point based on the expression of canonical marker genes and biological knowledge. The graph_test function in Monocle3 was used to identify genes correlated with the reconstructed developmental trajectory, allowing for the assessment of dynamic gene expression changes along the path.

Cell-cell communication analysis

Cell-cell communication analysis was performed using the CellChat package (v1.6.1).⁶⁶ Based on a comprehensive database of known ligand-receptor interactions and integrated with cell type annotations, signaling relationships between different cell types were systematically inferred. By calculating communication probabilities and signal strength, intercellular interaction differences during early PGC development across species were explored. Then, the overall interaction network and specific signaling pathways were visualized.

Quantification and statistical analysis

All statistical analyses were performed using R (version 4.2.0) unless otherwise specified. For single-cell RNA-seq data, differential gene expression analysis was conducted using the Wilcoxon rank-sum test implemented in the Seurat package. P values were adjusted for multiple testing using the Benjamini–Hochberg method, and genes with an adjusted P value (FDR) < 0.05 were considered statistically significant.

For Gene Ontology (GO) and pathway enrichment analyses, adjusted P values (false discovery rate, FDR) were calculated to control for multiple comparisons. Only significantly enriched terms with FDR < 0.05 were retained for downstream interpretation.

In cell–cell communication analysis using CellChat, communication probabilities were inferred based on the expression of ligand–receptor pairs, and statistical significance was determined using permutation tests implemented in the package.

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.isci.2026.116074.

Contributor Information

Yulei Wei, Email: yulei.wei@cau.edu.cn.

Ellie Duan, Email: jd774@cornell.edu.

Young Tang, Email: youngtang@nwafu.edu.cn.

Supplemental information

Document S1. Figures S1–S3

mmc1.pdf^{(681.7KB, pdf)}

Table S1. Summary of cell-type-specific marker genes identified across all bovine gonadal cell clusters

mmc2.csv^{(208KB, csv)}

Table S2. Integrated cluster marker genes across bovine, goat, and pig gonadal single-cell datasets

mmc3.csv^{(443.6KB, csv)}

Table S3. Differentially expressed genes in germ cells across developmental stages

mmc4.csv^{(17.2KB, csv)}

Table S4. Differentially expressed genes in granulosa cells during ovarian development

mmc5.csv^{(17.2KB, csv)}

Table S5. Shared and unique gene sets identified in germ cells based on Venn analysis

mmc6.csv^{(11.3KB, csv)}

Table S6. Gene Ontology (GO) enrichment analysis of transcription factors in germ cells

mmc7.xlsx^{(22.1KB, xlsx)}

Table S7. Transcription factor analysis in germ cells

mmc8.csv^{(50.5KB, csv)}

Table S8. Shared and unique gene sets in granulosa cells identified by Venn analysis

mmc9.csv^{(9.6KB, csv)}

Table S9. Gene Ontology (GO) enrichment analysis of transcription factors in granulosa cells

mmc10.xlsx^{(22.1KB, xlsx)}

Table S10. Transcription factor analysis in granulosa cells

mmc11.csv^{(122.1KB, csv)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Figures S1–S3

mmc1.pdf^{(681.7KB, pdf)}

Table S1. Summary of cell-type-specific marker genes identified across all bovine gonadal cell clusters

mmc2.csv^{(208KB, csv)}

Table S2. Integrated cluster marker genes across bovine, goat, and pig gonadal single-cell datasets

mmc3.csv^{(443.6KB, csv)}

Table S3. Differentially expressed genes in germ cells across developmental stages

mmc4.csv^{(17.2KB, csv)}

Table S4. Differentially expressed genes in granulosa cells during ovarian development

mmc5.csv^{(17.2KB, csv)}

Table S5. Shared and unique gene sets identified in germ cells based on Venn analysis

mmc6.csv^{(11.3KB, csv)}

Table S6. Gene Ontology (GO) enrichment analysis of transcription factors in germ cells

mmc7.xlsx^{(22.1KB, xlsx)}

Table S7. Transcription factor analysis in germ cells

mmc8.csv^{(50.5KB, csv)}

Table S8. Shared and unique gene sets in granulosa cells identified by Venn analysis

mmc9.csv^{(9.6KB, csv)}

Table S9. Gene Ontology (GO) enrichment analysis of transcription factors in granulosa cells

mmc10.xlsx^{(22.1KB, xlsx)}

Table S10. Transcription factor analysis in granulosa cells

mmc11.csv^{(122.1KB, csv)}

Data Availability Statement

Data: Single-cell RNA-seq data have been deposited in CNCB under accession OMIX012725 and are publicly available.
Code: Code is available from the corresponding author upon reasonable request.
Additional Information: Any additional information required is available from the lead contact.

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PERMALINK

Integration of single-cell transcriptome of female early gonadal development in bovine, goats, and pigs

Shiyao Han

Qianhui Zou

Yifei Fang

Junmei Zhang

Yue Su

Shengcan Xie

Zhen Yang

Yiyu Zhao

Ningxiao Li

Wenjing Wan

Linxiu Yue

Heshuangyi Xie

Yulei Wei

Ellie Duan

Young Tang

Summary

Graphical abstract

Highlights

Introduction

Results

A single-cell atlas of early bovine ovarian development

Figure 1.

Cross-species germ cell developmental trajectories reveal conserved programs and divergent meiotic timing

Figure 2.

Cross-species comparative analysis of female gonadal somatic cells in livestock

Figure 3.

Conserved and species-specific transcriptional networks govern germ and somatic cell fate

Figure 4.

A retinoic acid-responsive signaling axis defines the meiotic microenvironment

Figure 5.

Discussion

Limitations of the study

Resource availability

Lead contact

Materials availability

Data and code availability

Acknowledgments

Author contributions

Declaration of interests

STAR★Methods

Key resources table

Experimental model and study participant details

Animal models

Ethics statement

Method details

Fetal bovine gonad collection

Single-cell suspension preparation of fetal gonads

Single-cell RNA sequencing

RNA-seq library preparation and sequencing

Single-cell RNA sequencing data processing

Cell identification

Cell clustering and annotation

Differential expression gene (DEG) analysis and Gene Ontology (GO) enrichment

Transcriptional regulatory network analysis (SCENIC)

Pseudotime and cell trajectory inference

Cell-cell communication analysis

Quantification and statistical analysis

Footnotes

Contributor Information

Supplemental information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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