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# Maternal vitamin C regulates reprogramming of DNA methylation and germline development

Stephanie P Ditroia, Michelle Percharde, Marie-Justine Guerquin, Estelle Wall, Evelyne Collignon, Kevin T Ebata, Kathryn Mesh, Swetha Mahesula, Michalis Agathocleous, Diana J Laird, et al.

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## To cite this version:

Stephanie P Ditroia, Michelle Percharde, Marie-Justine Guerquin, Estelle Wall, Evelyne Collignon, et al.. Maternal vitamin C regulates reprogramming of DNA methylation and germline development. Nature, 2019, 573 (7773), pp.271-275. 10.1038/s41586-019-1536-1. hal-04516361

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https://hal.science/hal-04516361

Submitted on 22 Mar 2024

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# Maternal vitamin C regulates reprogramming of DNA methylation and germline development

Stephanie P Ditroia, Michelle Percharde, Marie-Justine Guerquin, Estelle Wall, Evelyne Collignon, Kevin T Ebata, Kathryn Mesh, Swetha Mahesula, Michalis Agathocleous, Diana J Laird, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Stephanie P Ditroia, Michelle Percharde, Marie-Justine Guerquin, Estelle Wall, Evelyne Collignon, et al.. Maternal vitamin C regulates reprogramming of DNA methylation and germline development. Nature, 2019, 573 (7773), pp.271-275. 10.1038/s41586-019-1536-1. hal-04516361

HAL Id: hal-04516361

https://hal.science/hal-04516361v1

Submitted on 22 Mar 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Maternal vitamin C regulates reprogramming of DNA methylation and germline development

Stephanie P. DiTroia<fnref n="1" />,²,⁸, Michelle Percharde<fnref n="1" />,²,³,⁴, Marie-Justine Guerquin⁵, Estelle Wall<fnref n="1" />,², Evelyne Collignon⁶, Kevin T. Ebata<fnref n="1" />,², Kathryn Mesh<fnref n="1" />,², Swetha Mahesula⁷, Michalis Agathocleous⁷, Diana J. Laird<fnref n="1" />,², Gabriel Rivera⁵ & Miguel Ramalho-Santos<fnref n="1" />,²,⁶*

Development is often assumed to be hardwired in the genome, but several lines of evidence indicate that it is susceptible to environmental modulation with potential long-term consequences, including in mammals<fnref n="1" />,². The embryonic germline is of particular interest because of the potential for intergenerational epigenetic effects. The mammalian germline undergoes extensive DNA demethylation³⁻⁷ that occurs in large part by passive dilution of methylation over successive cell divisions, accompanied by active DNA demethylation by TET enzymes³,⁸⁻¹⁰. TET activity has been shown to be modulated by nutrients and metabolites, such as vitamin C¹¹⁻¹⁵. Here we show that maternal vitamin C is required for proper DNA demethylation and the development of female fetal germ cells in a mouse model. Maternal vitamin C deficiency does not affect overall embryonic development but leads to reduced numbers of germ cells, delayed meiosis and reduced fecundity in adult offspring. The transcriptome of germ cells from vitamin-C-deficient embryos is remarkably similar to that of embryos carrying a null mutation in *Tet1*. Vitamin C deficiency leads to an aberrant DNA methylation profile that includes incomplete demethylation of key regulators of meiosis and transposable elements. These findings reveal that deficiency in vitamin C during gestation partially recapitulates loss of TET1, and provide a potential intergenerational mechanism for adjusting fecundity to environmental conditions.

We sought to determine the role of vitamin C (also known as ascorbic acid) in the developing germline, which expresses high levels of vitamin C transporters (Extended Data Fig. 1a). We used *Gulo*⁻<fnref n="1" />/⁻<fnref n="1" />; *Oct4-eGFP* mice¹⁶,¹⁷ (*Oct4* is also known as *Pou5f1*) to test the role of vitamin C in germline development (see Methods). Vitamin C was removed from the drinking water of female mice from before mating to embryonic day (E)13.5. We chose E13.5 because it represents the lowest point of global DNA methylation during germline reprogramming³. We focused on female germ cells because they enter meiosis at E13.5, whereas in male cells this only occurs postnatally. In all our analyses, female progeny of vitamin-C-depleted mothers were compared with genetically identical control mice supplied with physiological levels of vitamin C throughout development (Fig. 1a). The withdrawal of vitamin C in this model is compatible with normal development to E13.5 (Fig. 1b–d). However, there is a significant reduction in the number of primordial germ cells (PGCs) in vitamin C-deficient female embryos compared with controls (Fig. 1e and Extended Data Fig. 1d, e).

When added to embryonic stem (ES) cells in culture, vitamin C induces DNA demethylation and the expression of a set of key germline genes in a TET1/TET2-dependent manner¹¹, and these genes also depend on TET1 for expression in PGCs in vivo⁸,¹⁸. Notably, we found that those same germline genes are consistently downregulated in female PGCs developed under vitamin-C-deficient conditions (Extended Data Fig. 1f–i). Vitamin C deficiency has no overall effect

on the developmental progression of fetal gonads, as assessed by RNA sequencing (RNA-seq) (Fig. 1f and Extended Data Fig. 1j), quantitative PCR with reverse transcription (qRT-PCR) of select somatic markers that are sharply induced between E11.5 and E13.5, and immunohistochemistry (Extended Data Fig. 2a–c). Thus, vitamin C deficiency during gestation up to E13.5 is compatible with embryonic and gonadal development, but leads to a reduced number of germ cells and defective expression of TET1-dependent germline regulators.

Several of the germline genes identified as vitamin-C-responsive in vivo (Extended Data Fig. 1f) are important regulators of meiotic initiation and progression. We confirmed significant reductions in STRA8 and SYCP3 at the RNA and protein levels in vitamin-C-deficient germ cells (Extended Data Figs. 1f, 3a–e). Vitamin-C-deficient ovaries from E14.5 mice display a significant enrichment in the proportion of germ cells in meiotic S phase (preleptotene) compared with controls (Fig. 1g). Although changes in individual post-S-phase stages are not significant (Fig. 1g), their aggregate proportion is reduced in vitamin-C-deficient ovaries (Extended Data Fig. 3f, g). This delay in meiotic progression persists at E18.5 (Fig. 1g). The successful pairing of chromosomes during meiosis in mouse germ cells leads to approximately 20 centromeric foci per cells; however, vitamin-C-deficient embryos have a significant increase in germ cells, with more than 25 centromeric foci per cell (Fig. 1h and Extended Data Fig. 3h). Notably, fetal testes, in which meiosis does not take place until puberty, display no apparent defects in germ cell number, morphology, or marker protein expression after vitamin C deficiency (Extended Data Figs. 2b–d, 4). Together, these data indicate that maternal deficiency of vitamin C induces considerable deficits in meiotic initiation and progression in fetal female germ cells.

We next investigated the potential postnatal effects of gestational vitamin C deficiency on ovarian reserve and fecundity. Pregnant female mice (F₀) were depleted of vitamin C as before, returned to a vitamin-C-containing diet from E13.5 onwards and allowed to give birth (Fig. 2a). There is an abnormally variable ovarian reserve in postnatal day 7 (P7) pups that had been depleted of vitamin C in utero, with several having very low numbers of developing oocytes compared with control P7 pups (Fig. 2b, c). There are no significant changes in ovary volume (Fig. 2d) or the overall distribution of oocyte sizes (Extended Data Fig. 3i). After mating, vitamin-C-deficient F₁ female mice have a significantly reduced number of implanted embryos per mating, with a high incidence of entirely failed pregnancies (that lack implantation sites) relative to control F₁ mice (Fig. 2e, f). Even within the successful pregnancies of vitamin-C-deficient F₁ female mice, there is an abnormally high frequency of embryo resorption (Fig. 2g, h). Thus, although vitamin-C-deficient F₁ female mice can be fertile, they have significantly reduced fecundity.

Our results indicate that resupply of vitamin C to the maternal diet at E13.5 does not erase the defects in germline function induced by

<footnote n="1">¹Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA. ²Center for Reproductive Sciences, University of California, San Francisco, San Francisco, CA, USA. ³MRC London Institute of Medical Sciences (LMS), London, UK. ⁴Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, London, UK. ⁵UMR967 INSERM, CEA/DRF/iRCM/SCSR/LDG, Université Paris Diderot, Sorbonne Paris Cité, Université Paris-Sud, Université Paris-Saclay, Laboratory of Development of the Gonads, Fontenay aux Roses, France. ⁶Lunenfeld-Tanenbaum Research Institute and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada. ⁷Children's Research Institute and the Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA. ⁸Present address: Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. *e-mail: mrsantos@lunenfeld.ca</footnote>
# Maternal vitamin C regulates reprogramming of DNA methylation and germline development

Stephanie P. DiTroia<fnref n="1" />,²,⁸, Michelle Percharde<fnref n="1" />,²,³,⁴, Marie-Justine Guerquin⁵, Estelle Wall<fnref n="1" />,², Evelyne Collignon⁶, Kevin T. Ebata<fnref n="1" />,², Kathryn Mesh<fnref n="1" />,², Swetha Mahesula⁷, Michalis Agathocleous⁷, Diana J. Laird<fnref n="1" />,², Gabriel Rivera⁵ & Miguel Ramalho-Santos<fnref n="1" />,²,⁶*

Development is often assumed to be hardwired in the genome, but several lines of evidence indicate that it is susceptible to environmental modulation with potential long-term consequences, including in mammals<fnref n="1" />,². The embryonic germline is of particular interest because of the potential for intergenerational epigenetic effects. The mammalian germline undergoes extensive DNA demethylation³⁻⁷ that occurs in large part by passive dilution of methylation over successive cell divisions, accompanied by active DNA demethylation by TET enzymes³,⁸⁻¹⁰. TET activity has been shown to be modulated by nutrients and metabolites, such as vitamin C¹¹⁻¹⁵. Here we show that maternal vitamin C is required for proper DNA demethylation and the development of female fetal germ cells in a mouse model. Maternal vitamin C deficiency does not affect overall embryonic development but leads to reduced numbers of germ cells, delayed meiosis and reduced fecundity in adult offspring. The transcriptome of germ cells from vitamin-C-deficient embryos is remarkably similar to that of embryos carrying a null mutation in *Tet1*. Vitamin C deficiency leads to an aberrant DNA methylation profile that includes incomplete demethylation of key regulators of meiosis and transposable elements. These findings reveal that deficiency in vitamin C during gestation partially recapitulates loss of TET1, and provide a potential intergenerational mechanism for adjusting fecundity to environmental conditions.

We sought to determine the role of vitamin C (also known as ascorbic acid) in the developing germline, which expresses high levels of vitamin C transporters (Extended Data Fig. 1a). We used *Gulo*⁻<fnref n="1" />/⁻<fnref n="1" />; *Oct4-eGFP* mice¹⁶,¹⁷ (*Oct4* is also known as *Pou5f1*) to test the role of vitamin C in germline development (see Methods). Vitamin C was removed from the drinking water of female mice from before mating to embryonic day (E)13.5. We chose E13.5 because it represents the lowest point of global DNA methylation during germline reprogramming³. We focused on female germ cells because they enter meiosis at E13.5, whereas in male cells this only occurs postnatally. In all our analyses, female progeny of vitamin-C-depleted mothers were compared with genetically identical control mice supplied with physiological levels of vitamin C throughout development (Fig. 1a). The withdrawal of vitamin C in this model is compatible with normal development to E13.5 (Fig. 1b–d). However, there is a significant reduction in the number of primordial germ cells (PGCs) in vitamin C-deficient female embryos compared with controls (Fig. 1e and Extended Data Fig. 1d, e).

When added to embryonic stem (ES) cells in culture, vitamin C induces DNA demethylation and the expression of a set of key germline genes in a TET1/TET2-dependent manner¹¹, and these genes also depend on TET1 for expression in PGCs in vivo⁸,¹⁸. Notably, we found that those same germline genes are consistently downregulated in female PGCs developed under vitamin-C-deficient conditions (Extended Data Fig. 1f–i). Vitamin C deficiency has no overall effect

on the developmental progression of fetal gonads, as assessed by RNA sequencing (RNA-seq) (Fig. 1f and Extended Data Fig. 1j), quantitative PCR with reverse transcription (qRT-PCR) of select somatic markers that are sharply induced between E11.5 and E13.5, and immunohistochemistry (Extended Data Fig. 2a-c). Thus, vitamin C deficiency during gestation up to E13.5 is compatible with embryonic and gonadal development, but leads to a reduced number of germ cells and defective expression of TET1-dependent germline regulators.

Several of the germline genes identified as vitamin-C-responsive in vivo (Extended Data Fig. 1f) are important regulators of meiotic initiation and progression. We confirmed significant reductions in STRA8 and SYCP3 at the RNA and protein levels in vitamin-C-deficient germ cells (Extended Data Figs. 1f, 3a-e). Vitamin-C-deficient ovaries from E14.5 mice display a significant enrichment in the proportion of germ cells in meiotic S phase (preleptotene) compared with controls (Fig. 1g). Although changes in individual post-S-phase stages are not significant (Fig. 1g), their aggregate proportion is reduced in vitamin-C-deficient ovaries (Extended Data Fig. 3f, g). This delay in meiotic progression persists at E18.5 (Fig. 1g). The successful pairing of chromosomes during meiosis in mouse germ cells leads to approximately 20 centromeric foci per cells; however, vitamin-C-deficient embryos have a significant increase in germ cells, with more than 25 centromeric foci per cell (Fig. 1h and Extended Data Fig. 3h). Notably, fetal testes, in which meiosis does not take place until puberty, display no apparent defects in germ cell number, morphology, or marker protein expression after vitamin C deficiency (Extended Data Figs. 2b-d, 4). Together, these data indicate that maternal deficiency of vitamin C induces considerable deficits in meiotic initiation and progression in fetal female germ cells.

We next investigated the potential postnatal effects of gestational vitamin C deficiency on ovarian reserve and fecundity. Pregnant female mice (F₀) were depleted of vitamin C as before, returned to a vitamin-C-containing diet from E13.5 onwards and allowed to give birth (Fig. 2a). There is an abnormally variable ovarian reserve in postnatal day 7 (P7) pups that had been depleted of vitamin C in utero, with several having very low numbers of developing oocytes compared with control P7 pups (Fig. 2b, c). There are no significant changes in ovary volume (Fig. 2d) or the overall distribution of oocyte sizes (Extended Data Fig. 3i). After mating, vitamin-C-deficient F₁ female mice have a significantly reduced number of implanted embryos per mating, with a high incidence of entirely failed pregnancies (that lack implantation sites) relative to control F₁ mice (Fig. 2e, f). Even within the successful pregnancies of vitamin-C-deficient F₁ female mice, there is an abnormally high frequency of embryo resorption (Fig. 2g, h). Thus, although vitamin-C-deficient F₁ female mice can be fertile, they have significantly reduced fecundity.

Our results indicate that resupply of vitamin C to the maternal diet at E13.5 does not erase the defects in germline function induced by

<footnote n="1">¹Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA. ²Center for Reproductive Sciences, University of California, San Francisco, San Francisco, CA, USA. ³MRC London Institute of Medical Sciences (LMS), London, UK. ⁴Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, London, UK. ⁵UMR967 INSERM, CEA/DRF/iRCM/SCSR/LDG, Université Paris Diderot, Sorbonne Paris Cité, Université Paris-Sud, Université Paris-Saclay, Laboratory of Development of the Gonads, Fontenay aux Roses, France. ⁶Lunenfeld-Tanenbaum Research Institute and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada. ⁷Children's Research Institute and the Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA. ⁸Present address: Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. *e-mail: mrsantos@lunenfeld.ca</footnote>
<figure><img src="image_4.png" /><figcaption>**Fig. 1** | Maternal vitamin C promotes female germ-cell development. **a,** Diagram of vitamin C withdrawal during gestation. Control (ctrl) litters are genetically identical to vitamin-C-deficient (–VitC) litters. Control female mice are provided with physiological levels of vitamin C in the drinking water. Vitamin C is withdrawn from the deficient female mice 3–7 days before mating, up until E13.5. **b,** Vitamin C deficiency does not affect embryonic development up to E13.5, as determined by morphological assessment of the embryos and hand-plate staging. Embryos were compared across 13 control and 11 vitamin-C-deficient litters. **c,** Gestational deficiency of vitamin C does not affect litter size. **d,** Gestational vitamin C deficiency does not affect the resorption rate. **e,** Reduction in the number of Oct4-eGFP+ germ cells (in which the expression of enhanced green fluorescent protein (eGFP) is driven by the Oct4 promoter) in vitamin-C-deficient E13.5 female embryos. **f,** MA plot reveals no significant changes in the transcription profile of vitamin-C-deficient E13.5 somatic cells of the female gonad (log₂-transformed fold change > |1| and FDR < 0.05). **g,** Staging of meiosis reveals a delay in meiosis progression in vitamin-C-deficient ovaries. See also Extended Data Fig. 3f, **h,** CREST staining reveals unpaired chromosomes in vitamin-C-deficient E18.5 female germ cells. CREST foci were counted in 100 cells across 4 biological replicates. See images in Extended Data Fig. 3h. Data are mean ± s.d. (c–e, **g**) or mean ± s.e.m. (h). **P** values determined by two-sided Welch's *t*-test (c–e, **h**) or Sidak's multiple comparison test (**g**). NS, not significant.</figcaption></figure>

vitamin C deficiency earlier in gestation. We therefore characterized the transcriptome of E13.5 germ cells (Fig. 3a and Extended Data Fig. 5a). Germ cells depleted of vitamin C are overall transcriptionally distinguishable from controls (Fig. 3b and Extended Data Fig. 5b). In total, 412 genes were identified as differentially expressed in germ cells after vitamin C deficiency during gestation (false discovery rate (FDR) < 0.05, log₂-transformed fold change > |0.7|), with a preponderance of downregulated genes (314 genes downregulated versus 98 upregulated; Fig. 3c, d and Supplementary Data 1). Notably, the set of genes downregulated in vitamin-C-depleted germ cells is enriched for functions in meiosis and sexual reproduction (Supplementary Data 3). Several key regulators of meiosis are among the top downregulated genes in vitamin-C-depleted germ cells (Fig. 3c).

Similar to vitamin-C-deficient embryos, *Tet1*<sup>-/-</sup> female embryos are fully viable but display a reduced number of germ cells, reduced expression of meiotic regulators, defective meiosis and reduced fecundity<sup>8,9</sup>. We found that vitamin C deficiency recapitulates the transcriptional

<figure><img src="image_5.png" /><figcaption>**Fig. 2** | Gestational vitamin C deficiency has a long-term effect on female fecundity. **a,** Diagram of experiments to address female fecundity (see Fig. 1a). From E13.5 onwards, vitamin C was resupplied in the drinking water. After birth, F₁ female mice were assessed for ovarian reserve at postnatal day 7 (P7), or fecundity at 20–25 weeks. All vitamin-C-deficient and control mice are of the same genotype, *Gulo*<sup>-/-</sup>; *Oct4-eGFP*, **b,** Representative whole-mount images of P7 ovaries from vitamin-C-deficient or control female mice. Oocyte nuclei identified by NOBOX (red) staining are segmented and sorted by volume to quantify primordial and primary follicles. *n* = 9 ovaries per condition. Scale bars, 100 µm. **c,** Quantification of oocytes in P7 ovaries by whole-mount imaging of NOBOX staining. Geometric shapes represent individual female embryos; identical shapes indicate ovary pairs. Control female embryos contain 3,000–4,500 NOBOX⁺ oocytes per ovary (*n* = 9). Vitamin-C-deficient female embryos contain 1,000–4,500 NOBOX⁺ oocytes per ovary (*n* = 9). **d,** Normal numbers and variance in P7 ovary volume from females that had developed in the absence of vitamin C. *n* = 9 ovaries per condition were measured, matched with data in Fig. 2c. **e,** Vitamin-C-deficient or control F₁ female mice were mated to wild-type males, and the number of implantation sites per female displaying a vaginal plug was counted between E9.5 and E18.5. Control F₁ female mice average 6.5 implants per pregnancy, whereas vitamin-C-deficient F₁ female mice average 4 implants. **f,** There is a significant reduction in the number of successful matings in vitamin-C-deficient F₁ female mice. A successful mating is defined as the observation of at least one implanted embryo per female that had displayed a vaginal plug after mating. *n* = 14 vitamin-C-deficient and *n* = 17 control mated female mice. **g,** Within successful matings only, there is a higher number of resorptions in vitamin-C-deficient F₁ female mice, relative to controls. **h,** The number of pregnancies containing at least one resorbed embryo is significantly higher in vitamin-C-deficient F₁ female mice, relative to controls. *n* = 5 vitamin-C-deficient and *n* = 12 control pregnant female mice. *P* values determined by two-tailed Student's *t*-test (c–e, **g**), χ² test (f, **h**), and variance ratio determined by *F*-test (c, **d**). Data are mean (c, **d**) or mean ± s.e.m. (e, **g**).</figcaption></figure>

defects of *Tet1*<sup>-/-</sup> germ cells, with regards to both upregulated and downregulated genes (Fig. 3d and Extended Data Fig. 5c), as well as Gene Ontology terms (Supplementary Data 3). Vitamin C deficiency does not affect the expression of TET, DNMT or other potentially vitamin-C-sensitive enzymes in PGCs (Extended Data Fig. 5d–f). Together, these data indicate that, although vitamin C and TET1 are likely to have unique functions in the fetal female germline, vitamin C is required for the execution of a transcriptional program that is orchestrated by TET1 and is essential for normal fecundity.
<figure><img src="image_3.png" /><figcaption>**Fig. 1** | Maternal vitamin C promotes female germ-cell development. **a**, Diagram of vitamin C withdrawal during gestation. Control (ctrl) litters are genetically identical to vitamin-C-deficient (–VitC) litters. Control female mice are provided with physiological levels of vitamin C in the drinking water. Vitamin C is withdrawn from the deficient female mice 3–7 days before mating, up until E13.5. **b**, Vitamin C deficiency does not affect embryonic development up to E13.5, as determined by morphological assessment of the embryos and hand-plate staging. Embryos were compared across 13 control and 11 vitamin-C-deficient litters. **c**, Gestational deficiency of vitamin C does not affect litter size. **d**, Gestational vitamin C deficiency does not affect the resorption rate. **e**, Reduction in the number of Oct4-eGFP+ germ cells (in which the expression of enhanced green fluorescent protein (eGFP) is driven by the Oct4 promoter) in vitamin-C-deficient E13.5 female embryos. **f**, MA plot reveals no significant changes in the transcription profile of vitamin-C-deficient E13.5 somatic cells of the female gonad (log₂-transformed fold change > |1| and FDR < 0.05). **g**, Staging of meiosis reveals a delay in meiosis progression in vitamin-C-deficient ovaries. See also Extended Data Fig. 3f, **h**, CREST staining reveals unpaired chromosomes in vitamin-C-deficient E18.5 female germ cells. CREST foci were counted in 100 cells across 4 biological replicates. See images in Extended Data Fig. 3h. Data are mean ± s.d. (c–e, **g**) or mean ± s.e.m. (h). *P* values determined by two-sided Welch's *t*-test (c–e, **h**) or Sidak's multiple comparison test (**g**). NS, not significant.</figcaption></figure>

vitamin C deficiency earlier in gestation. We therefore characterized the transcriptome of E13.5 germ cells (Fig. 3a and Extended Data Fig. 5a). Germ cells depleted of vitamin C are overall transcriptionally distinguishable from controls (Fig. 3b and Extended Data Fig. 5b). In total, 412 genes were identified as differentially expressed in germ cells after vitamin C deficiency during gestation (false discovery rate (FDR) < 0.05, log₂-transformed fold change > |0.7|), with a preponderance of downregulated genes (314 genes downregulated versus 98 upregulated; Fig. 3c, d and Supplementary Data 1). Notably, the set of genes downregulated in vitamin-C-depleted germ cells is enriched for functions in meiosis and sexual reproduction (Supplementary Data 3). Several key regulators of meiosis are among the top downregulated genes in vitamin-C-depleted germ cells (Fig. 3c).

Similar to vitamin-C-deficient embryos, *Tet1*<sup>-/-</sup> female embryos are fully viable but display a reduced number of germ cells, reduced expression of meiotic regulators, defective meiosis and reduced fecundity<sup>8,9</sup>. We found that vitamin C deficiency recapitulates the transcriptional

<figure><img src="image_4.png" /><figcaption>**Fig. 2** | Gestational vitamin C deficiency has a long-term effect on female fecundity. **a**, Diagram of experiments to address female fecundity (see Fig. 1a). From E13.5 onwards, vitamin C was resupplied in the drinking water. After birth, F₁ female mice were assessed for ovarian reserve at postnatal day 7 (P7), or fecundity at 20–25 weeks. All vitamin-C-deficient and control mice are of the same genotype, *Gulo*<sup>-/-</sup>;*Oct4-eGFP*, **b**, Representative whole-mount images of P7 ovaries from vitamin-C-deficient or control female mice. Oocyte nuclei identified by NOBOX (red) staining are segmented and sorted by volume to quantify primordial and primary follicles. *n* = 9 ovaries per condition. Scale bars, 100 µm. **c**, Quantification of oocytes in P7 ovaries by whole-mount imaging of NOBOX staining. Geometric shapes represent individual female embryos; identical shapes indicate ovary pairs. Control female embryos contain 3,000–4,500 NOBOX⁺ oocytes per ovary (*n* = 9). Vitamin-C-deficient female embryos contain 1,000–4,500 NOBOX⁺ oocytes per ovary (*n* = 9). **d**, Normal numbers and variance in P7 ovary volume from females that had developed in the absence of vitamin C. *n* = 9 ovaries per condition were measured, matched with data in Fig. 2c. **e**, Vitamin-C-deficient or control F₁ female mice were mated to wild-type males, and the number of implantation sites per female displaying a vaginal plug was counted between E9.5 and E18.5. Control F₁ female mice average 6.5 implants per pregnancy, whereas vitamin-C-deficient F₁ female mice average 4 implants. **f**, There is a significant reduction in the number of successful matings in vitamin-C-deficient F₁ female mice. A successful mating is defined as the observation of at least one implanted embryo per female that had displayed a vaginal plug after mating. *n* = 14 vitamin-C-deficient and *n* = 17 control mated female mice. **g**, Within successful matings only, there is a higher number of resorptions in vitamin-C-deficient F₁ female mice, relative to controls. **h**, The number of pregnancies containing at least one resorbed embryo is significantly higher in vitamin-C-deficient F₁ female mice, relative to controls. *n* = 5 vitamin-C-deficient and *n* = 12 control pregnant female mice. *P* values determined by two-tailed Student's *t*-test (c–e, **g**), χ² test (f, **h**), and variance ratio determined by *F*-test (c, **d**). Data are mean (c, **d**) or mean ± s.e.m. (e, **g**).</figcaption></figure>

defects of *Tet1*<sup>-/-</sup> germ cells, with regards to both upregulated and downregulated genes (Fig. 3d and Extended Data Fig. 5c), as well as Gene Ontology terms (Supplementary Data 3). Vitamin C deficiency does not affect the expression of TET, DNMT or other potentially vitamin-C-sensitive enzymes in PGCs (Extended Data Fig. 5d–f). Together, these data indicate that, although vitamin C and TET1 are likely to have unique functions in the fetal female germline, vitamin C is required for the execution of a transcriptional program that is orchestrated by TET1 and is essential for normal fecundity.
<figure><img src="image_6.png" /><figcaption>**Fig. 3** | Vitamin C deficiency induces a *Tet1*−/−-like expression profile in the developing germline. **a**, Diagram of experiments to determine the molecular effect of vitamin C deficiency in the embryonic germline. Pregnant mice were deprived of vitamin C as before, and *Oct4*-eGFP+ germ cells were isolated from single E13.5 embryos. **b**, Principle component analysis (PCA) of the transcriptional profile of E13.5 germ cells identifies a clear separation of samples according to vitamin C availability along principal component 1 (PC1). Each grey or red dot represents the germ cell transcriptome from a single control or vitamin-C-deficient female embryo, respectively. C1F1 denotes control litter 1, female embryo 1; V4F2 denotes vitamin-C-deficient litter 4, female embryo 2. *n* = 6 biological replicates per condition were measured. The control sample closest to the vitamin C samples in the PCA plot clusters with them in hierarchical clustering (see Extended Data Fig. 5b). This</figcaption></figure>

sample is transcriptionally intermediate between control and vitamin-C-deficient samples, for reasons unknown. **c**, MA plot of the differential expression between control and vitamin-C-deficient samples. The 98 gold and 314 blue dots represent genes significantly upregulated and downregulated in vitamin-C-deficient germ cells, respectively. Select germline genes previously identified as TET1-dependent in female germ cells<sup>8</sup>, induced by vitamin C in ES cell culture<sup>11</sup> and validated by qRT-PCR (see Extended Data Fig. 1f-i) are highlighted in pink. **d**, Gene set enrichment analysis (GSEA) highlights the similarities between vitamin-C-deficient (this study) and *Tet1*−/− female E13.5 germ cells<sup>8</sup>. Genes that are upregulated or downregulated in *Tet1*−/− germ cells are highly biased to be upregulated or downregulated, respectively, in vitamin-C-deficient E13.5 germ cells. *P* values determined by a weighted Kolmogorov-Smirnov-like statistic and adjusted for multiple hypothesis testing.

Re-supplementation of vitamin C at E3.5, after the pre-implantation window of DNA methylation reprogramming, rescues to a large extent the transcriptional defects and the reduction in germ cell numbers induced by vitamin C deficiency (Extended Data Fig. 6). These results suggest that vitamin C is required for proper germline gene expression and germ cell development between E3.5 and E13.5, overlapping with the window of DNA demethylation in the embryonic germline.

We next used reduced representation bisulfite sequencing (RRBS) analysis to compare the DNA methylome of vitamin-C-depleted and control E13.5 germ cells on a genome-wide scale. As previously reported<sup>3,19</sup>, E13.5 female germ cells are globally demethylated, and the presence or absence of vitamin C does not affect the global abundance of modified cytosine residues (Extended Data Fig. 7a, b). These results are in agreement with the idea that global DNA demethylation in the germline occurs primarily by passive dilution, with TET1 having a secondary role<sup>3,8,20</sup>. We identified 460 differentially methylated regions (DMRs) across the genome (*P* < 0.05, 5% minimum change). Two-thirds of the DMRs gain methylation after vitamin C deficiency (285 hypermethylated DMRs versus 175 hypomethylated DMRs; Fig. 4a and Extended Data Fig. 7c), indicating that vitamin C is primarily required for DNA demethylation.

Notably, hypermethylated DMRs induced by vitamin C deficiency are enriched for proximity to sequences associated with abnormal ovary development and female infertility (Fig. 4b). Most of the DMRs are located distal from transcription start sites (TSSs; Fig. 4c). The 55 genes with hypermethylation within 5 kb of their TSSs after vitamin C deficiency are enriched for germline regulators. Examples include

genes expressed in E13.5 germ cells and dependent on vitamin C for their proper expression, such as *Dazl* or *Sycp1*, as well as regulators of meiosis not expressed robustly until later in development, such as *Spo11* or *Sohlh2* (Fig. 4d). These vitamin-C-dependent germline regulators are classified as loci targeted for active demethylation<sup>3</sup> (Fig. 4d). Distal DMRs are enriched for transposable elements, specifically of the LINE1, IAP and ERVK families, which display methylation gains (Fig. 4e and Extended Data Fig. 7d). An unbiased analysis of the DNA methylation status in transposable elements, regardless of whether they are called differentially methylated or not, revealed mild but significant trends towards gains of DNA methylation (Extended Data Fig. 7e). These results indicate that vitamin C deficiency leads to accumulation of DNA methylation at meiosis regulators and transposable elements in the embryonic germline, in both cases mimicking the defects observed in *Tet1*−/− germ cells<sup>8,18</sup>. A recent study documented that TET1 is required for maintaining, rather than driving, DNA demethylation in the germline<sup>18</sup>. A crucial set of germline and meiosis regulators, known as germline reprogramming-responsive (GRR) genes, were defined that undergo DNA demethylation in the embryonic germline and depend on TET1 for maintenance of their DNA demethylated state and proper induction<sup>18</sup>. In agreement, we found that this set of GRR genes displays significantly increased levels of promoter DNA methylation and lower expression levels in vitamin-C-deficient female germ cells (Fig. 4f, g). Further corroborating the requirement of vitamin C for optimal TET activity in vivo, levels of 5-hydroxymethylcytosine (hmC) are sharply reduced in brain and liver samples from vitamin-C-deficient E13.5 embryos, relative to controls (Extended Data Fig. 7f, g).
<figure><img src="image_5.png" /><figcaption>**Fig. 3** | Vitamin C deficiency induces a *Tet1*−/−-like expression profile in the developing germline. **a**, Diagram of experiments to determine the molecular effect of vitamin C deficiency in the embryonic germline. Pregnant mice were deprived of vitamin C as before, and *Oct4*-eGFP+ germ cells were isolated from single E13.5 embryos. **b**, Principle component analysis (PCA) of the transcriptional profile of E13.5 germ cells identifies a clear separation of samples according to vitamin C availability along principal component 1 (PC1). Each grey or red dot represents the germ cell transcriptome from a single control or vitamin-C-deficient female embryo, respectively. C1F1 denotes control litter 1, female embryo 1; V4F2 denotes vitamin-C-deficient litter 4, female embryo 2. *n* = 6 biological replicates per condition were measured. The control sample closest to the vitamin C samples in the PCA plot clusters with them in hierarchical clustering (see Extended Data Fig. 5b). This</figcaption></figure>

sample is transcriptionally intermediate between control and vitamin-C-deficient samples, for reasons unknown. **c**, MA plot of the differential expression between control and vitamin-C-deficient samples. The 98 gold and 314 blue dots represent genes significantly upregulated and downregulated in vitamin-C-deficient germ cells, respectively. Select germline genes previously identified as TET1-dependent in female germ cells<sup>8</sup>, induced by vitamin C in ES cell culture<sup>11</sup> and validated by qRT-PCR (see Extended Data Fig. 1f-i) are highlighted in pink. **d**, Gene set enrichment analysis (GSEA) highlights the similarities between vitamin-C-deficient (this study) and *Tet1*−/− female E13.5 germ cells<sup>8</sup>. Genes that are upregulated or downregulated in *Tet1*−/− germ cells are highly biased to be upregulated or downregulated, respectively, in vitamin-C-deficient E13.5 germ cells. *P* values determined by a weighted Kolmogorov-Smirnov-like statistic and adjusted for multiple hypothesis testing.

Re-supplementation of vitamin C at E3.5, after the pre-implantation window of DNA methylation reprogramming, rescues to a large extent the transcriptional defects and the reduction in germ cell numbers induced by vitamin C deficiency (Extended Data Fig. 6). These results suggest that vitamin C is required for proper germline gene expression and germ cell development between E3.5 and E13.5, overlapping with the window of DNA demethylation in the embryonic germline.

We next used reduced representation bisulfite sequencing (RRBS) analysis to compare the DNA methylome of vitamin-C-depleted and control E13.5 germ cells on a genome-wide scale. As previously reported<sup>3,19</sup>, E13.5 female germ cells are globally demethylated, and the presence or absence of vitamin C does not affect the global abundance of modified cytosine residues (Extended Data Fig. 7a, b). These results are in agreement with the idea that global DNA demethylation in the germline occurs primarily by passive dilution, with TET1 having a secondary role<sup>3,8,20</sup>. We identified 460 differentially methylated regions (DMRs) across the genome (*P* < 0.05, 5% minimum change). Two-thirds of the DMRs gain methylation after vitamin C deficiency (285 hypermethylated DMRs versus 175 hypomethylated DMRs; Fig. 4a and Extended Data Fig. 7c), indicating that vitamin C is primarily required for DNA demethylation.

Notably, hypermethylated DMRs induced by vitamin C deficiency are enriched for proximity to sequences associated with abnormal ovary development and female infertility (Fig. 4b). Most of the DMRs are located distal from transcription start sites (TSSs; Fig. 4c). The 55 genes with hypermethylation within 5 kb of their TSSs after vitamin C deficiency are enriched for germline regulators. Examples include

genes expressed in E13.5 germ cells and dependent on vitamin C for their proper expression, such as *Dazl* or *Sycp1*, as well as regulators of meiosis not expressed robustly until later in development, such as *Spo11* or *Sohlh2* (Fig. 4d). These vitamin-C-dependent germline regulators are classified as loci targeted for active demethylation<sup>3</sup> (Fig. 4d). Distal DMRs are enriched for transposable elements, specifically of the LINE1, IAP and ERVK families, which display methylation gains (Fig. 4e and Extended Data Fig. 7d). An unbiased analysis of the DNA methylation status in transposable elements, regardless of whether they are called differentially methylated or not, revealed mild but significant trends towards gains of DNA methylation (Extended Data Fig. 7e). These results indicate that vitamin C deficiency leads to accumulation of DNA methylation at meiosis regulators and transposable elements in the embryonic germline, in both cases mimicking the defects observed in *Tet1*−/− germ cells<sup>8,18</sup>. A recent study documented that TET1 is required for maintaining, rather than driving, DNA demethylation in the germline<sup>18</sup>. A crucial set of germline and meiosis regulators, known as germline reprogramming-responsive (GRR) genes, were defined that undergo DNA demethylation in the embryonic germline and depend on TET1 for maintenance of their DNA demethylated state and proper induction<sup>18</sup>. In agreement, we found that this set of GRR genes displays significantly increased levels of promoter DNA methylation and lower expression levels in vitamin-C-deficient female germ cells (Fig. 4f, g). Further corroborating the requirement of vitamin C for optimal TET activity in vivo, levels of 5-hydroxymethylcytosine (hmC) are sharply reduced in brain and liver samples from vitamin-C-deficient E13.5 embryos, relative to controls (Extended Data Fig. 7f, g).
<figure><img src="image_7.png" /></figure>

**Fig. 4** | Vitamin C deficiency leads to incomplete loss of DNA methylation at meiosis regulators and transposable elements in the embryonic germline. **a**, Average methylation per CpG across the germ cells of six biologically independent control and vitamin-C-deficient E13.5 female embryos. DMRs were defined by hierarchical testing and size-weighted FDR. Blue and red dots represent 285 hypermethylated and 175 hypomethylated DMRs, respectively. **b**, Genomic regions enrichment of annotations tool (GREAT) analysis of 285 hypermethylated DMRs induced by vitamin C deficiency identifies an enrichment for annotations associated with abnormal ovary development and female infertility (red arrows). **c**, Distance of 285 hypermethylated DMRs to gene TSSs compared with the RRBS background of genomic regions covered by RRBS. DMRs are found primarily at a distance from TSSs. This trend is similar in hypomethylated DMRs. **d**, *Dazl* and *Spo11* are both examples of hyper-

DMRs at the promoter of germline regulators. The reduced expression of *Dazl* at E13.5 is correlated with a gain in promoter methylation. Purple bars denote late demethylating region defined previously³. **e**, DMR transposable element analyses reveals that 460 DMRs (hyper- and hypo-) are enriched at LINE, long-terminal repeat (LTR) and SINE elements relative to the RRBS background. **f**, Increased CpG methylation is found surrounding the TSS of GRR genes with vitamin C deficiency. The average GRR gene TSS methylation across six biological replicates per condition was determined. **g**, GRR genes display reduced gene expression after vitamin C deficiency compared with all genes profiled. **P** values determined by paired two-sided Wilcoxon test (**f**) or two-sided unpaired Welch's *t*-test (**g**). Box plot hinges in **f** and **g** correspond to Tukey plot quartiles, with median centre line.

Finally, we explored the potential effect of vitamin C deficiency on the genome-wide pattern of H3K9me2, because vitamin C promotes KDM3A/B-mediated demethylation of H3K9me2 in ES cells²¹, and the overall levels of this histone modification are sharply lost specifically in PGCs within the same time frame as DNA demethylation²². Vitamin C deficiency induces upregulation of H3K9me2 in E13.5 gonadal soma at both genes and transposable elements (Extended Data Fig. 8a–c), although this does not lead to any changes in their transcriptome (Fig. 1g). By contrast, the loss of vitamin C does not detectably affect the globally demethylated state of germ cells for this mark (Extended Data Fig. 8c, e, f).

The present study documents the extensive parallels between ges-
tational vitamin C deficiency and the *Tet1* mutation with regards to
germline reprogramming, transcriptional profile, meiosis and fecundity
(Extended Data Fig. 9). Vitamin-C-deficient embryos display germ
cell loss earlier than *Tet1* mutants⁸. It is possible that vitamin C also
regulates the activity of TET2, which is also expressed in PGCs, albeit at
lower levels than TET1 (Extended Data Fig. 5b). In addition, vitamin C
deficiency may affect other intercellular processes and epigenetic layers
in germ cells, although no detectable defects were found in H3K9me2.
Our results highlight that a nutritional deficit can, to a large extent,
recapitulate a genetic mutation with a central role in epigenetic repro-
gramming and mammalian reproduction.

Errors in meiosis are the leading cause of miscarriage in human
reproduction. It is notable that TET enzymes receive a diversity of
inputs from the cell's metabolic state<sup>11-15</sup>. We propose that the inter-
connectivity of TET1 with metabolism and maternal nutrition during
germline development, rather than being a liability, provides a mecha-
nism for adjusting the investment on reproduction across generations
to the abundance of key nutrients in the environment. Of potential
evolutionary interest is the fact that most animals can synthesize their
own vitamin C, but certain vertebrate species, including humans, have
lost that ability<sup>23</sup>. Moreover, oxidative stress induced by environmental
contaminants can lead to oxidation of vitamin C<sup>24-29</sup>. Given the sensi-
tivity of TET1 and vitamin C to metabolic and environmental inputs, it
will be important to determine the epigenetic effect of climate change
and environmental contamination on reproduction.

Online content

Any methods, additional references, Nature Research reporting summaries, source
data, extended data, supplementary information, acknowledgements, peer review
information; details of author contributions and competing interests; and state-
ments of data and code availability are available at https://doi.org/10.1038/s41586-
019-1536-1.

Received: 2 February 2018; Accepted: 2 August 2019;
Published online 4 September 2019.
<figure><img src="image_6.png" /></figure>

**Fig. 4** | Vitamin C deficiency leads to incomplete loss of DNA methylation at meiosis regulators and transposable elements in the embryonic germline. **a**, Average methylation per CpG across the germ cells of six biologically independent control and vitamin-C-deficient E13.5 female embryos. DMRs were defined by hierarchical testing and size-weighted FDR. Blue and red dots represent 285 hypermethylated and 175 hypomethylated DMRs, respectively. **b**, Genomic regions enrichment of annotations tool (GREAT) analysis of 285 hypermethylated DMRs induced by vitamin C deficiency identifies an enrichment for annotations associated with abnormal ovary development and female infertility (red arrows). **c**, Distance of 285 hypermethylated DMRs to gene TSSs compared with the RRBS background of genomic regions covered by RRBS. DMRs are found primarily at a distance from TSSs. This trend is similar in hypomethylated DMRs. **d**, *Dazl* and *Spo11* are both examples of hyper-

DMRs at the promoter of germline regulators. The reduced expression of *Dazl* at E13.5 is correlated with a gain in promoter methylation. Purple bars denote late demethylating region defined previously³. **e**, DMR transposable element analyses reveals that 460 DMRs (hyper- and hypo-) are enriched at LINE, long-terminal repeat (LTR) and SINE elements relative to the RRBS background. **f**, Increased CpG methylation is found surrounding the TSS of GRR genes with vitamin C deficiency. The average GRR gene TSS methylation across six biological replicates per condition was determined. **g**, GRR genes display reduced gene expression after vitamin C deficiency compared with all genes profiled. **P** values determined by paired two-sided Wilcoxon test (**f**) or two-sided unpaired Welch's *t*-test (**g**). Box plot hinges in **f** and **g** correspond to Tukey plot quartiles, with median centre line.

Finally, we explored the potential effect of vitamin C deficiency on the genome-wide pattern of H3K9me2, because vitamin C promotes KDM3A/B-mediated demethylation of H3K9me2 in ES cells²¹, and the overall levels of this histone modification are sharply lost specifically in PGCs within the same time frame as DNA demethylation²². Vitamin C deficiency induces upregulation of H3K9me2 in E13.5 gonadal soma at both genes and transposable elements (Extended Data Fig. 8a–c), although this does not lead to any changes in their transcriptome (Fig. 1g). By contrast, the loss of vitamin C does not detectably affect the globally demethylated state of germ cells for this mark (Extended Data Fig. 8c, e, f).

The present study documents the extensive parallels between ges-
tational vitamin C deficiency and the *Tet1* mutation with regards to
germline reprogramming, transcriptional profile, meiosis and fecundity
(Extended Data Fig. 9). Vitamin-C-deficient embryos display germ
cell loss earlier than *Tet1* mutants⁸. It is possible that vitamin C also
regulates the activity of TET2, which is also expressed in PGCs, albeit at
lower levels than TET1 (Extended Data Fig. 5b). In addition, vitamin C
deficiency may affect other intercellular processes and epigenetic layers
in germ cells, although no detectable defects were found in H3K9me2.
Our results highlight that a nutritional deficit can, to a large extent,
recapitulate a genetic mutation with a central role in epigenetic repro-
gramming and mammalian reproduction.

Errors in meiosis are the leading cause of miscarriage in human
reproduction. It is notable that TET enzymes receive a diversity of
inputs from the cell's metabolic state<sup>11-15</sup>. We propose that the inter-
connectivity of TET1 with metabolism and maternal nutrition during
germline development, rather than being a liability, provides a mecha-
nism for adjusting the investment on reproduction across generations
to the abundance of key nutrients in the environment. Of potential
evolutionary interest is the fact that most animals can synthesize their
own vitamin C, but certain vertebrate species, including humans, have
lost that ability<sup>23</sup>. Moreover, oxidative stress induced by environmental
contaminants can lead to oxidation of vitamin C<sup>24-29</sup>. Given the sensi-
tivity of TET1 and vitamin C to metabolic and environmental inputs, it
will be important to determine the epigenetic effect of climate change
and environmental contamination on reproduction.

Online content

Any methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-019-1536-1.

Received: 2 February 2018; Accepted: 2 August 2019;
Published online 4 September 2019.
1. Barker, D. J. P. The developmental origins of adult disease. *J. Am. Coll. Nutr.* **23**, 588S–595S (2004).

2. Boekelheide, K. et al. Predicting later-life outcomes of early-life exposures. *Environ. Health Perspect.* **120**, 1353–1361 (2012).

3. Seisenberger, S. et al. The dynamics of genome-wide DNA methylation reprogramming in mouse primordial germ cells. *Mol. Cell* **48**, 849–862 (2012).

4. Hackett, J. A. et al. Germline DNA demethylation dynamics and imprint erasure through 5-hydroxymethylcytosine. *Science* **339**, 448–452 (2013).

5. Gkountela, S. et al. DNA demethylation dynamics in the human prenatal germline. *Cell* **161**, 1425–1436 (2015).

6. Guo, F. et al. The transcriptome and DNA methylome landscapes of human primordial germ cells. *Cell* **161**, 1437–1452 (2015).

7. Tang, W. W. C. et al. A unique gene regulatory network resets the human germline epigenome for development. *Cell* **161**, 1453–1467 (2015).

8. Yamaguchi, S. et al. Tet1 controls meiosis by regulating meiotic gene expression. *Nature* **492**, 443–447 (2012).

9. Yamaguchi, S., Shen, L., Liu, Y., Sendler, D. & Zhang, Y. Role of Tet1 in erasure of genomic imprinting. *Nature* **504**, 460–464 (2013).

10. Hajkova, P. et al. Chromatin dynamics during epigenetic reprogramming in the mouse germ line. *Nature* **452**, 877–881 (2008).

11. Blaschke, K. et al. Vitamin C induces Tet-dependent DNA demethylation and a blastocyst-like state in ES cells. *Nature* **500**, 222–226 (2013).

12. Carey, B. W., Finley, L. W. S., Cross, J. R., Allis, C. D. & Thompson, C. B. Intracellular α-ketoglutarate maintains the pluripotency of embryonic stem cells. *Nature* **518**, 413–416 (2014).

13. Zhang, Q. et al. Differential regulation of the ten-eleven translocation (TET) family of dioxygenases by O-linked β-N-acetylglucosamine transferase (OGT). *J. Biol. Chem.* **289**, 5986–5996 (2014).

14. Yin, R. et al. Ascorbic acid enhances Tet-mediated 5-methylcytosine oxidation and promotes DNA demethylation in mammals. *J. Am. Chem. Soc.* **135**, 10396–10403 (2013).

15. Wu, H. & Zhang, Y. Mechanisms and functions of Tet protein-mediated 5-methylcytosine oxidation. *Genes Dev.* **25**, 2436–2452 (2011).

16. Maeda, N. et al. Aortic wall damage in mice unable to synthesize ascorbic acid. *Proc. Natl Acad. Sci. USA* **97**, 841–846 (2000).

17. Szabó, P. E., Hübner, K., Schöler, H. & Mann, J. R. Allele-specific expression of imprinted genes in mouse migratory primordial germ cells. *Mech. Dev.* **115**, 157–160 (2002).

18. Hill, P. W. S. et al. Epigenetic reprogramming enables the transition from primordial germ cell to gonocyte. *Nature* **555**, 392–396 (2018).

19. Kobayashi, H. et al. High-resolution DNA methylome analysis of primordial germ cells identifies gender-specific reprogramming in mice. *Genome Res.* **23**, 616–627 (2013).

20. Ohno, R. et al. A replication-dependent passive mechanism modulates DNA demethylation in mouse primordial germ cells. *Development* **140**, 2892–2903 (2013).

21. Ebata, K. T. et al. Vitamin C induces specific demethylation of H3K9me2 in mouse embryonic stem cells via Kdm3a/b. *Epigenetics Chromatin* **10**, 36 (2017).

22. Seki, Y. et al. Cellular dynamics associated with the genome-wide epigenetic reprogramming in migrating primordial germ cells in mice. *Development* **134**, 2627–2638 (2007).

23. Drouin, G., Godin, J.-R. & Pagé, B. The genetics of vitamin C loss in vertebrates. *Curr. Genomics* **12**, 371–378 (2011).

24. Salnikow, K. & Zhitkovich, A. Genetic and epigenetic mechanisms in metal carcinogenesis and cocarcinogenesis: nickel, arsenic, and chromium. *Chem. Res. Toxicol.* **21**, 28–44 (2008).

25. Ercal, N., Gurer-Orhan, H. & Aykin-Burns, N. Toxic metals and oxidative stress part I: mechanisms involved in metal-induced oxidative damage. *Curr. Top. Med. Chem.* **1**, 529–539 (2001).

26. Cross, C. E., Traber, M., Eiserich, J. & van der Vliet, A. Micronutrient antioxidants and smoking. *Br. Med. Bull.* **55**, 691–704 (1999).

27. Alsharif, N. Z., Lawson, T. & Stohs, S. J. Oxidative stress induced by 2,3,7,8-tetrachlorodibenzo-p-dioxin is mediated by the aryl hydrocarbon (Ah) receptor complex. *Toxicology* **92**, 39–51 (1994).

28. Matsumura, F. On the significance of the role of cellular stress response reactions in the toxic actions of dioxin. *Biochem. Pharmacol.* **66**, 527–540 (2003).

29. Cyr, A. R. & Domann, F. E. The redox basis of epigenetic modifications: from mechanisms to functional consequences. *Antioxid. Redox Signal.* **15**, 551–589 (2011).

**Publisher's note:** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

© The Author(s), under exclusive licence to Springer Nature Limited 2019
1. Barker, D. J. P. The developmental origins of adult disease. *J. Am. Coll. Nutr.* **23**, 588S–595S (2004).

2. Boekelheide, K. et al. Predicting later-life outcomes of early-life exposures. *Environ. Health Perspect.* **120**, 1353–1361 (2012).

3. Seisenberger, S. et al. The dynamics of genome-wide DNA methylation reprogramming in mouse primordial germ cells. *Mol. Cell* **48**, 849–862 (2012).

4. Hackett, J. A. et al. Germline DNA demethylation dynamics and imprint erasure through 5-hydroxymethylcytosine. *Science* **339**, 448–452 (2013).

5. Gkountela, S. et al. DNA demethylation dynamics in the human prenatal germline. *Cell* **161**, 1425–1436 (2015).

6. Guo, F. et al. The transcriptome and DNA methylome landscapes of human primordial germ cells. *Cell* **161**, 1437–1452 (2015).

7. Tang, W. W. C. et al. A unique gene regulatory network resets the human germline epigenome for development. *Cell* **161**, 1453–1467 (2015).

8. Yamaguchi, S. et al. Tet1 controls meiosis by regulating meiotic gene expression. *Nature* **492**, 443–447 (2012).

9. Yamaguchi, S., Shen, L., Liu, Y., Sendler, D. & Zhang, Y. Role of Tet1 in erasure of genomic imprinting. *Nature* **504**, 460–464 (2013).

10. Hajkova, P. et al. Chromatin dynamics during epigenetic reprogramming in the mouse germ line. *Nature* **452**, 877–881 (2008).

11. Blaschke, K. et al. Vitamin C induces Tet-dependent DNA demethylation and a blastocyst-like state in ES cells. *Nature* **500**, 222–226 (2013).

12. Carey, B. W., Finley, L. W. S., Cross, J. R., Allis, C. D. & Thompson, C. B. Intracellular α-ketoglutarate maintains the pluripotency of embryonic stem cells. *Nature* **518**, 413–416 (2014).

13. Zhang, Q. et al. Differential regulation of the ten-eleven translocation (TET) family of dioxygenases by O-linked β-N-acetylglucosamine transferase (OGT). *J. Biol. Chem.* **289**, 5986–5996 (2014).

14. Yin, R. et al. Ascorbic acid enhances Tet-mediated 5-methylcytosine oxidation and promotes DNA demethylation in mammals. *J. Am. Chem. Soc.* **135**, 10396–10403 (2013).

15. Wu, H. & Zhang, Y. Mechanisms and functions of Tet protein-mediated 5-methylcytosine oxidation. *Genes Dev.* **25**, 2436–2452 (2011).

16. Maeda, N. et al. Aortic wall damage in mice unable to synthesize ascorbic acid. *Proc. Natl Acad. Sci. USA* **97**, 841–846 (2000).

17. Szabó, P. E., Hübner, K., Schöler, H. & Mann, J. R. Allele-specific expression of imprinted genes in mouse migratory primordial germ cells. *Mech. Dev.* **115**, 157–160 (2002).

18. Hill, P. W. S. et al. Epigenetic reprogramming enables the transition from primordial germ cell to gonocyte. *Nature* **555**, 392–396 (2018).

19. Kobayashi, H. et al. High-resolution DNA methylome analysis of primordial germ cells identifies gender-specific reprogramming in mice. *Genome Res.* **23**, 616–627 (2013).

20. Ohno, R. et al. A replication-dependent passive mechanism modulates DNA demethylation in mouse primordial germ cells. *Development* **140**, 2892–2903 (2013).

21. Ebata, K. T. et al. Vitamin C induces specific demethylation of H3K9me2 in mouse embryonic stem cells via Kdm3a/b. *Epigenetics Chromatin* **10**, 36 (2017).

22. Seki, Y. et al. Cellular dynamics associated with the genome-wide epigenetic reprogramming in migrating primordial germ cells in mice. *Development* **134**, 2627–2638 (2007).

23. Drouin, G., Godin, J.-R. & Pagé, B. The genetics of vitamin C loss in vertebrates. *Curr. Genomics* **12**, 371–378 (2011).

24. Salnikow, K. & Zhitkovich, A. Genetic and epigenetic mechanisms in metal carcinogenesis and cocarcinogenesis: nickel, arsenic, and chromium. *Chem. Res. Toxicol.* **21**, 28–44 (2008).

25. Ercal, N., Gurer-Orhan, H. & Aykin-Burns, N. Toxic metals and oxidative stress part I: mechanisms involved in metal-induced oxidative damage. *Curr. Top. Med. Chem.* **1**, 529–539 (2001).

26. Cross, C. E., Traber, M., Eiserich, J. & van der Vliet, A. Micronutrient antioxidants and smoking. *Br. Med. Bull.* **55**, 691–704 (1999).

27. Alsharif, N. Z., Lawson, T. & Stohs, S. J. Oxidative stress induced by 2,3,7,8-tetrachlorodibenzo-p-dioxin is mediated by the aryl hydrocarbon (Ah) receptor complex. *Toxicology* **92**, 39–51 (1994).

28. Matsumura, F. On the significance of the role of cellular stress response reactions in the toxic actions of dioxin. *Biochem. Pharmacol.* **66**, 527–540 (2003).

29. Cyr, A. R. & Domann, F. E. The redox basis of epigenetic modifications: from mechanisms to functional consequences. *Antioxid. Redox Signal.* **15**, 551–589 (2011).

**Publisher's note:** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

© The Author(s), under exclusive licence to Springer Nature Limited 2019
## METHODS

**Mouse model for gestational vitamin C deficiency.** *Gulo*⁻¹⁻¹ mice¹⁶ were obtained from the UC Davis Mutant Mouse Resource & Research Center (strain B6.129P2-*Gulo*¹¹Mae/Mmucl, RRID:MMRRC_000015-UCD) and bred with *Oct4-eGFP* mice¹⁷ to establish a homozygous *Gulo*⁻¹⁻¹;*Oct4-eGFP* colony on a C57BL/6 background. All mice were supplemented with 3.3 g l⁻¹ L-ascorbic acid (Sigma-Aldrich A92902) in their drinking water, refreshed weekly. Experimental (vitamin-C-depleted and control) female mice were maintained on a custom mouse chow devoid of vitamin C (Teklad Custom Rodent Diet TD.130707). Like humans, *Gulo*⁻¹⁻¹ mice are fully dependent on the diet for vitamin C owing to a mutation in the L-gulonolactone oxidase (*Gulo*) gene. With proper supplementation of vitamin C in the drinking water, these mice are viable, fertile and indistinguishable from their heterozygous or wild-type littermates¹⁶,³⁰. In agreement with previous reports³⁰, we found that it takes about 7 days of withdrawal for vitamin C to become essentially undetectable in the blood plasma of pregnant *Gulo*⁻¹⁻¹ mice (Extended Data Fig. 1b). To obtain sufficient mice for analysis, female mice were depleted of vitamin C for 3 days before exposure to a male, and the plugging was allowed to happen between days 3 and 7 (mice were separated the morning of plug detection or at day 7 if no plug was detected). This was to ensure that, at the time of fertilization, female mice have at least a 50% reduction in their serum levels of vitamin C, which become undetectable after 7 days (Extended Data Fig. 1b). We do not detect differences that correlate with the timing of depletion before fertilization, perhaps because the key effect of vitamin C deficiency in this context is post-implantation (Extended Data Fig. 6). Information on the specific days of depletion for the RNA-seq and RRBS sequencing samples is provided in Supplementary Data 4. Pregnant female mice remained on non-supplemented water through E13.5, with the morning of observed vaginal plug denoted as E0.5. All pregnant mice (control and vitamin-C-depleted) were supplied with fresh vitamin-C-supplemented water at E13.5 and were visually indistinguishable. Vitamin C is undetectable in E13.5 vitamin-C-deficient embryos, whereas it is robustly detected in controls (Extended Data Fig. 1c). In the case of the vitamin C re-dition model described in Extended Data Fig. 6, the goal was specifically to test the role of vitamin C availability in the first wave of DNA demethylation during pre-implantation as it pertains to PGC development. To this end, a longer removal window, 7–10 days, was carried out to ensure full depletion of vitamin C by the time of fertilization and vitamin C was re-supplied at the end of the first wave of DNA demethylation (blastocyst stage, E3.5). In all our analyses, female progeny of vitamin-C-depleted mothers were compared with genetically identical controls supplied with physiological levels of vitamin C throughout development (Fig. 1a). For fecundity tests, we then crossed wild-type males to vitamin-C-depleted or control F₁ female mice at 20–25 weeks of age—the period of peak female fertility in the C57BL/6 strain³¹. Experiments were performed in accordance with the guidelines of the UCSF Institutional Animal Care and Use Committee. We have complied with all relevant ethical regulations. Sample size choice was not pre-determined but was based on previous experience in the laboratories involved. Randomization or blinding was not performed.

**Measurement of circulating maternal vitamin C.** After deep isoflurane anaesthesia, blood was collected from the vena cava of pregnant female mice using a syringe. Approximately 1 ml of blood was allowed to clot for 30 min at room temperature in a 1.5-ml Eppendorf tube. Clotted blood was centrifuged at 10,000 r.p.m. for 10 min. Serum was collected and immediately stored at -80°C or processed using a colorimetric Ascorbic Acid Assay Kit (Sigma-Aldrich MAK074-1KT) according to the manufacturer's protocol.

**Measurement of vitamin C in embryonic tissue.** Tissue concentrations of vitamin C were quantified according to a previously published method³². In brief, extraction buffer containing 1 mM EDTA and 5 nmol ¹³C-labelled vitamin C (ascorbate) standard (Cambridge Isotope Laboratories CLM 3085-0.05) in 80% methanol was prepared on dry ice. E13.5 embryonic fore Ireurs and livers were dissected and weighed, taking 5–20 mg of tissues for the extraction and kept immediately on dry ice. Cold extraction buffer (500 µl) was quickly added to each sample, which was then crushed with a small pestle. The suspension was vortexed for 1 min to lyse the cells and centrifuged at 13,000 r.p.m. for 15 min at 4°C. The supernatant was dried in a speedvac (Thermo), resuspended in 0.03% formic acid plus 1 mM EDTA in water and centrifuged at 13,000 r.p.m. for 15 min at 4°C. The supernatant was analysed using liquid chromatography–tandem mass spectrometry (LC–MS/MS). A Nexera Ultra High Performance Liquid Chromatograph (UHPLC) system (Shimadzu) was used with a Scherzo SM-C18 column (Imtakt). Mobile phase A was 0.03% formic acid in water. Mobile phase B was 0.03% formic acid in acetonitrile. The flow rate was 0.5 ml min⁻¹, the column was at 35°C and the samples in the autosampler were at 4°C. Mass spectrometry was performed with a triple quadrupole mass spectrometer (AB Sciex QTRAP 5500) in multiple reaction monitoring (MRM) mode. Chromatogram peak areas were integrated using Multiquant (AB Sciex).

**Isolation of germ cells.** Dissections were performed at E11.5, E13.5, E14.5 or E18.5, depending on the experiment, after euthanasia of pregnant female mice under deep isoflurane anaesthesia. Embryonic gonads were dissected in sterile cold PBS and immediately fixed or dissociated for further analyses. Embryonic ovaries were enzymatically digested in 0.5% trypsin and 0.8 mg ml⁻¹ DNase I (Worthington) at 37°C for 3–5 min, then manually dissociated by pipetting. PGCs and matched somatic cells were isolated by FACS on an AriaII instrument (BD Biosciences) based on GFP and SSEA1 expression. PGCs and soma were sorted directly into RLT lysis buffer or PBS, for downstream RNA or DNA extraction respectively, and immediately frozen on dry ice.

**qRT–PCR.** RNA was extracted using RNeasy micro columns (Qiagen) and cDNA generated using a High Capacity cDNA Reverse Transcription kit (ABI) according to the manufacturer's protocol. qRT–PCR was performed on an ABI-Prism PCR machine with primers listed in Supplementary Data 2. The relative amount of each gene was normalized using two housekeeping genes (*Rpl7* and *Ubb*).

**Histology and immunohistochemistry.** E14.5 ovaries were fixed with Bouin's fluid (for haematoxylin and eosin staining) or 4% formaldehyde (for immunohistochemistry) for 45 min and dehydrated through an ethanol series, embedded in paraffin and cut into 5-µm-thick sections. Sections were mounted on glass, dewaxed, rehydrated and stained with haematoxylin and eosin. Meiotic staging was based on nuclear shape and chromatin compaction as previously described³³⁻³⁵. The Histolab analysis software (Microvision Instruments) was used for counting.

For immunohistochemistry, tissue sections were mounted on glass slides, dewaxed, rehydrated and submitted to antigen retrieval by boiling for 20 min in citrate buffer (pH 6). Endogenous peroxidase activity was blocked by a 10-min incubation with 3% hydrogen peroxide. Slides were then washed in PBS and blocked for 30 min in 2% horse serum in PBS. Slides were incubated overnight at 4°C with primary antibody diluted in PBS with 20% blocking buffer containing 2.5% of horse serum. Peroxidase-conjugated secondary antibodies (ImmPRESS reagent kit, Vector Laboratories) were incubated for 30 min, followed by 3,3'-diaminobenzidine (DAB substrate reagent kit, Vector Laboratories) or VIP (Vector VIP substrate reagent kit, Vector Laboratories) reactions. Three sections were randomly chosen from each gonad to quantify the percentage of DDX4⁺ (also known as VASA⁺) (Abcam Ab13840 rabbit 1:200 or Ab27591 mouse 1:500) germ cells co-stained for STRA8 (Abcam Ab49602 rabbit 1:400) or SYCP3 (Abcam Ab97672 mouse 1:500). At least 200 DDX4⁺ germ cells were scored per section. Additional immunohistochemistry staining experiments represented in Extended Data Figs. 2 and 4 include FOXL2 (ThermoFisher PA1-802 1:200), AMH (SantaCruz SC-6858 1:200) and Ki67 (550609 BD Pharmingen 1:200) antibodies.

**Centromere staining in meiotic spreads.** Glass slides were prepared by submerging in 70% ethanol while E18.5 ovaries were dissected and prepared. Freshly dissected E18.5 ovary pairs were dissociated in 200 µl of enzymatic solution (0.025% trypsin; 2.5 mg ml⁻¹ collagenase; 0.1 mg ml⁻¹ DNase I) at 37°C for 30 min, pipetting every 10 min. Trypsin was quenched with 50 µl fetal bovine serum (FBS) and 250 µl hypotonic buffer (30 mM Tris pH 8.2; 50 mM sucrose; 17 mM sodium citrate; 5 mM EDTA; 0.5 mM dithiothreitol (DTT); 0.5 mM phenylmethanesulfonyl fluoride (PMSF)) was added to each sample for 30 min at room temperature. The cell suspension was centrifuged at 1,000 r.p.m. for 10 min. The pellet was resuspended in 90 µl 100 mM sucrose. At this point, slides were dried of ethanol and prepared with fixative solution (1% paraformaldehyde (PFA); 0.15% Triton X-100; 3 mM DTT). Aliquots of cell suspension (20 µl) were added to each drop of fixative solution per slide and allowed to dry at room temperature. Dried slides were quickly submerged in 0.4% Kodak Photo-Flo 200 and air dried. Meiotic spreads were stored at -80°C until staining.

Slides containing E18.5 female germ cell spreads were allowed to thaw for 15 min at room temperature before staining. Thawed slides were washed twice in PBS then permeabilized in PBS plus 0.2% Triton X-100 for 20 min at room temperature. Next, spreads were blocked in a buffer containing PBS plus 5% BSA and 0.1% Tween (PBSST) for 45 min. The primary antibodies for Sypc1 (Abcam Ab15090) and CREST (Antibodies Incorporated 15-234-0001) were incubated at a 1:400 dilution overnight in a 4°C humidity chamber. On day two, slides were washed in PBSST three times for 10 min each and blocked in PBSST plus 10% donkey serum for 30 min. The slides were incubated in secondary antibodies (Alexa Fluor 488 donkey anti-rabbit IgG, Alexa Fluor 647 AffiniPure donkey anti-human IgG 709-605-149) for 1 h in the dark. Slides containing immunofluorescent stained meiotic spreads were then washed for a final time (PBSST 3 × 10 min at room temperature in the dark) before mounting with Vectashield plus DAPI and imaging on a Leica confocal.

**Whole-mount imaging.** Whole-mount immunostaining and confocal imaging of P7 ovaries were previously described³⁶. The primary antibody used was NOBOW (1:100, a gift from A. Rajkovic) and the stain Hoechst (1:100, Fisher H3569). The secondary antibody used was Alexa-555 Donkey anti-Goat from Fisher and used at 1:200. Whole-mount ovaries were imaged using the Leica DMi8 confocal microscope, using a 20× objective. Imaris software (Bitplane) was used to quantify
METHODS

**Mouse model for gestational vitamin C deficiency.** *Gulo*⁻¹⁻¹ mice¹⁶ were obtained from the UC Davis Mutant Mouse Resource & Research Center (strain B6.129P2-*Gulo*¹¹Mae/Mmucl, RRID:MMRRC_000015-UCD) and bred with *Oct4-eGFP* mice¹⁷ to establish a homozygous *Gulo*⁻¹⁻¹;*Oct4-eGFP* colony on a C57BL/6 background. All mice were supplemented with 3.3 g l⁻¹ L-ascorbic acid (Sigma-Aldrich A92902) in their drinking water, refreshed weekly. Experimental (vitamin-C-depleted and control) female mice were maintained on a custom mouse chow devoid of vitamin C (Teklad Custom Rodent Diet TD.130707). Like humans, *Gulo*⁻¹⁻¹ mice are fully dependent on the diet for vitamin C owing to a mutation in the L-gulonolactone oxidase (*Gulo*) gene. With proper supplementation of vitamin C in the drinking water, these mice are viable, fertile and indistinguishable from their heterozygous or wild-type littermates¹⁶,³⁰. In agreement with previous reports³⁰, we found that it takes about 7 days of withdrawal for vitamin C to become essentially undetectable in the blood plasma of pregnant *Gulo*⁻¹⁻¹ mice (Extended Data Fig. 1b). To obtain sufficient mice for analysis, female mice were depleted of vitamin C for 3 days before exposure to a male, and the plugging was allowed to happen between days 3 and 7 (mice were separated the morning of plug detection or at day 7 if no plug was detected). This was to ensure that, at the time of fertilization, female mice have at least a 50% reduction in their serum levels of vitamin C, which become undetectable after 7 days (Extended Data Fig. 1b). We do not detect differences that correlate with the timing of depletion before fertilization, perhaps because the key effect of vitamin C deficiency in this context is post-implantation (Extended Data Fig. 6). Information on the specific days of depletion for the RNA-seq and RRBS sequencing samples is provided in Supplementary Data 4. Pregnant female mice remained on non-supplemented water through E13.5, with the morning of observed vaginal plug denoted as E0.5. All pregnant mice (control and vitamin-C-depleted) were supplied with fresh vitamin-C-supplemented water at E13.5 and were visually indistinguishable. Vitamin C is undetectable in E13.5 vitamin-C-deficient embryos, whereas it is robustly detected in controls (Extended Data Fig. 1c). In the case of the vitamin C re-dition model described in Extended Data Fig. 6, the goal was specifically to test the role of vitamin C availability in the first wave of DNA demethylation during pre-implantation as it pertains to PGC development. To this end, a longer removal window, 7–10 days, was carried out to ensure full depletion of vitamin C by the time of fertilization and vitamin C was re-supplied at the end of the first wave of DNA demethylation (blastocyst stage, E3.5). In all our analyses, female progeny of vitamin-C-depleted mothers were compared with genetically identical controls supplied with physiological levels of vitamin C throughout development (Fig. 1a). For fecundity tests, we then crossed wild-type males to vitamin-C-depleted or control F₁ female mice at 20–25 weeks of age—the period of peak female fertility in the C57BL/6 strain³¹. Experiments were performed in accordance with the guidelines of the UCSF Institutional Animal Care and Use Committee. We have complied with all relevant ethical regulations. Sample size choice was not pre-determined but was based on previous experience in the laboratories involved. Randomization or blinding was not performed.

**Measurement of circulating maternal vitamin C.** After deep isoflurane anaesthesia, blood was collected from the vena cava of pregnant female mice using a syringe. Approximately 1 ml of blood was allowed to clot for 30 min at room temperature in a 1.5-ml Eppendorf tube. Clotted blood was centrifuged at 10,000 r.p.m. for 10 min. Serum was collected and immediately stored at -80°C or processed using a colorimetric Ascorbic Acid Assay Kit (Sigma-Aldrich MAK074-1KT) according to the manufacturer's protocol.

**Measurement of vitamin C in embryonic tissue.** Tissue concentrations of vitamin C were quantified according to a previously published method³². In brief, extraction buffer containing 1 mM EDTA and 5 nmol ¹³C-labelled vitamin C (ascorbate) standard (Cambridge Isotope Laboratories CLM 3085-0.05) in 80% methanol was prepared on dry ice. E13.5 embryonic fore Ireurs and livers were dissected and weighed, taking 5–20 mg of tissues for the extraction and kept immediately on dry ice. Cold extraction buffer (500 µl) was quickly added to each sample, which was then crushed with a small pestle. The suspension was vortexed for 1 min to lyse the cells and centrifuged at 13,000 r.p.m. for 15 min at 4°C. The supernatant was dried in a speedvac (Thermo), resuspended in 0.03% formic acid plus 1 mM EDTA in water and centrifuged at 13,000 r.p.m. for 15 min at 4°C. The supernatant was analysed using liquid chromatography–tandem mass spectrometry (LC–MS/MS). A Nexera Ultra High Performance Liquid Chromatograph (UHPLC) system (Shimadzu) was used with a Scherzo SM-C18 column (Imtakt). Mobile phase A was 0.03% formic acid in water. Mobile phase B was 0.03% formic acid in acetonitrile. The flow rate was 0.5 ml min⁻¹, the column was at 35°C and the samples in the autosampler were at 4°C. Mass spectrometry was performed with a triple quadrupole mass spectrometer (AB Sciex QTRAP 5500) in multiple reaction monitoring (MRM) mode. Chromatogram peak areas were integrated using Multiquant (AB Sciex).

**Isolation of germ cells.** Dissections were performed at E11.5, E13.5, E14.5 or E18.5, depending on the experiment, after euthanasia of pregnant female mice under deep isoflurane anaesthesia. Embryonic gonads were dissected in sterile cold PBS and immediately fixed or dissociated for further analyses. Embryonic ovaries were enzymatically digested in 0.5% trypsin and 0.8 mg ml⁻¹ DNase I (Worthington) at 37°C for 3–5 min, then manually dissociated by pipetting. PGCs and matched somatic cells were isolated by FACS on an AriaII instrument (BD Biosciences) based on GFP and SSEA1 expression. PGCs and soma were sorted directly into RLT lysis buffer or PBS, for downstream RNA or DNA extraction respectively, and immediately frozen on dry ice.

**qRT–PCR.** RNA was extracted using RNeasy micro columns (Qiagen) and cDNA generated using a High Capacity cDNA Reverse Transcription kit (ABI) according to the manufacturer's protocol. qRT–PCR was performed on an ABI-Prism PCR machine with primers listed in Supplementary Data 2. The relative amount of each gene was normalized using two housekeeping genes (*Rpl7* and *Ubb*).

**Histology and immunohistochemistry.** E14.5 ovaries were fixed with Bouin's fluid (for haematoxylin and eosin staining) or 4% formaldehyde (for immunohistochemistry) for 45 min and dehydrated through an ethanol series, embedded in paraffin and cut into 5-µm-thick sections. Sections were mounted on glass, dewaxed, rehydrated and stained with haematoxylin and eosin. Meiotic staging was based on nuclear shape and chromatin compaction as previously described³³⁻³⁵. The Histolab analysis software (Microvision Instruments) was used for counting.

For immunohistochemistry, tissue sections were mounted on glass slides, dewaxed, rehydrated and submitted to antigen retrieval by boiling for 20 min in citrate buffer (pH 6). Endogenous peroxidase activity was blocked by a 10-min incubation with 3% hydrogen peroxide. Slides were then washed in PBS and blocked for 30 min in 2% horse serum in PBS. Slides were incubated overnight at 4°C with primary antibody diluted in PBS with 20% blocking buffer containing 2.5% of horse serum. Peroxidase-conjugated secondary antibodies (ImmPRESS reagent kit, Vector Laboratories) were incubated for 30 min, followed by 3,3'-diaminobenzidine (DAB substrate reagent kit, Vector Laboratories) or VIP (Vector VIP substrate reagent kit, Vector Laboratories) reactions. Three sections were randomly chosen from each gonad to quantify the percentage of DDX4⁺ (also known as VASA⁺) (Abcam Ab13840 rabbit 1:200 or Ab27591 mouse 1:500) germ cells co-stained for STRA8 (Abcam Ab49602 rabbit 1:400) or SYCP3 (Abcam Ab97672 mouse 1:500). At least 200 DDX4⁺ germ cells were scored per section. Additional immunohistochemistry staining experiments represented in Extended Data Figs. 2 and 4 include FOXL2 (ThermoFisher PA1-802 1:200), AMH (SantaCruz SC-6858 1:200) and Ki67 (550609 BD Pharmingen 1:200) antibodies.

**Centromere staining in meiotic spreads.** Glass slides were prepared by submerging in 70% ethanol while E18.5 ovaries were dissected and prepared. Freshly dissected E18.5 ovary pairs were dissociated in 200 µl of enzymatic solution (0.025% trypsin; 2.5 mg ml⁻¹ collagenase; 0.1 mg ml⁻¹ DNase I) at 37°C for 30 min, pipetting every 10 min. Trypsin was quenched with 50 µl fetal bovine serum (FBS) and 250 µl hypotonic buffer (30 mM Tris pH 8.2; 50 mM sucrose; 17 mM sodium citrate; 5 mM EDTA; 0.5 mM dithiothreitol (DTT); 0.5 mM phenylmethanesulfonyl fluoride (PMSF)) was added to each sample for 30 min at room temperature. The cell suspension was centrifuged at 1,000 r.p.m. for 10 min. The pellet was resuspended in 90 µl 100 mM sucrose. At this point, slides were dried of ethanol and prepared with fixative solution (1% paraformaldehyde (PFA); 0.15% Triton X-100; 3 mM DTT). Aliquots of cell suspension (20 µl) were added to each drop of fixative solution per slide and allowed to dry at room temperature. Dried slides were quickly submerged in 0.4% Kodak Photo-Flo 200 and air dried. Meiotic spreads were stored at -80°C until staining.

Slides containing E18.5 female germ cell spreads were allowed to thaw for 15 min at room temperature before staining. Thawed slides were washed twice in PBS then permeabilized in PBS plus 0.2% Triton X-100 for 20 min at room temperature. Next, spreads were blocked in a buffer containing PBS plus 5% BSA and 0.1% Tween (PBSST) for 45 min. The primary antibodies for Sypc1 (Abcam Ab15090) and CREST (Antibodies Incorporated 15-234-0001) were incubated at a 1:400 dilution overnight in a 4°C humidity chamber. On day two, slides were washed in PBSST three times for 10 min each and blocked in PBSST plus 10% donkey serum for 30 min. The slides were incubated in secondary antibodies (Alexa Fluor 488 donkey anti-rabbit IgG, Alexa Fluor 647 AffiniPure donkey anti-human IgG 709-605-149) for 1 h in the dark. Slides containing immunofluorescent stained meiotic spreads were then washed for a final time (PBSST 3 × 10 min at room temperature in the dark) before mounting with Vectashield plus DAPI and imaging on a Leica confocal.

**Whole-mount imaging.** Whole-mount immunostaining and confocal imaging of P7 ovaries were previously described³⁶. The primary antibody used was NOBOW (1:100, a gift from A. Rajkovic) and the stain Hoechst (1:100, Fisher H3569). The secondary antibody used was Alexa-555 Donkey anti-Goat from Fisher and used at 1:200. Whole-mount ovaries were imaged using the Leica DMi8 confocal microscope, using a 20× objective. Imaris software (Bitplane) was used to quantify
NOBOX objects. An Imaris surface was created around entire ovary to exclude oviposition and surrounding tissue and channels were masked to this surface for analysis. The ovary volume was generated from this Imaris surface contour. Images were filtered using Background Subtraction with a 30-µm filter and Gaussian Filter 1 voxel size. NOBOX objects were quantified using the Imaris spot module with a diameter of 8 µm and all spot objects were selected.

**Statistical analyses.** All statistical calculations were performed with GraphPad Prism 7.0 software or within R studio. Details of individual tests are outlined within each figure legend.

**RNA-seq.** Germ-cell RNA isolated from single embryos was quantified using an Agilent Bioanalyzer RNA Pico Kit. Barcoded libraries were created from 1.5 ng DNaseI-treated total RNA using Clonetech SMARTR-seq RNA library prep kit according to the manufacturer's recommendations. Successful libraries were bioanalyzed for quality and size distribution and then quantified using the Qubit dsDNA HS Assay Kit. Diluted libraries were pooled at equal 5 nM concentrations for sequencing. Final product was sequenced as 50-bp single-end reads on one lane of an Illumina HiSeq4000 at the UCSF Center for Advanced Technology. Six embryos were sequenced per condition, totalling 12 libraries in all. Approximately 25–40 million reads were obtained and analysed per sample. Single-end reads were quality-controlled and adaptor-trimmed using Trim Galore! (Babraham Bioinformatics). Filtered reads were mapped to the mm9 mouse genome using Tophat²³⁷. Reads mapping uniquely to known genes were counted using hseq-count³⁸. Count data were subsequently imported into R with Bioconductor³⁹ and filtered to remove non-expressed genes. For read-depth normalization, filtered gene count data were analysed using the R package DESeq²⁴⁰. Data were input into a DESeq object and normalized according to package recommendations. Gene Ontology term enrichment was analysed using DAVID⁴¹, and comparisons to the data from *Tet1*⁻/⁻ E13.5 germ cells⁸ were carried out using GSEA⁴².

**Reduced RRBS on single embryo PGCs.** We modified previously published protocols for RRBS and single-cell RRBS⁴³,⁴⁴ to create a streamlined single-tube workflow for low-input. Each RRBS library was created from 2 ng of genomic DNA collected from PGCs isolated by FACS from single E13.5 embryos. Initially, gDNA was extracted from *Oct4-eGFP* PGCs using Purelink Genomic DNA kit (K1820-00 Invitrogen) according to the manufacturer's instructions. Genomic DNA (2 ng) and 0.25% lambda DNA were then digested with 10 U of MspI enzyme (Fermentas) in a total reaction volume of 18 µl at 37°C for 3 h, followed by heat inactivation at 80°C for 20 min. End repair and A-addition was then carried out to repair and tail the 3' end of each digested fragment. This reaction was done immediately following MspI digestion by adding 2 µl of 5 U Klenow exo- with additional dNTPs (0.04 mM dATP, 0.004 mM dGTP, 0.004 mM dCTP) directly to the 18 µl digest. This reaction was incubated at 37°C for 40 min followed by heat inactivation at 75°C for 15 min. After repair, NEBNext USER methylated adaptors were ligated onto the DNA by adding 25 U of T4 DNA Ligase, 1.5 mM ATP, and 25 nM NEB Adaptors directly to the 20 µl reaction, giving a final reaction volume of 30 µl. Adaptor ligation was performed at 16°C for 30 min and then left at 4°C overnight. The following day, 1 µl of NEB USER enzyme was added to each reaction, followed by an incubation at 37°C for 15 min and then inactivation at 65°C for 20 min. Per the manufacturer's protocol, NEB USER enzyme is required for NEBNext adaptor cleavage.

Bisulfit conversion was performed on each 30 µl sample containing DNA fragments with methylated sequencing adapters. We used the low-concentration protocol of the EpiTect Fast Bisulphite Conversion Kit (Qiagen), eluting in 15 µl. Converted DNA (13 µl) was used directly in a library amplification PCR, which was optimized for 2 ng input, including 1 µl NEBNext Primer F, 1 µl NEBNext R, and 15 µl of 2× HiFi Uracil+ Mix (KAPA). This reaction was incubated at 95°C for 2 min, followed by 15 cycles of 95°C for 20 s; 60°C for 30 s; 72°C for 1 min, with a final step of 72°C for 5 min and a hold at 4°C. At this point, all samples were quantified using the Qubit dsDNA HS Assay Kit.

Successfully amplified libraries were completed with size selection and clean up. Size selection of 200–600-bp fragments was performed using Axygen Fragment Select-I beads. First, 0.5 volume of beads (15 µl) was added to the 30 µl sample, pipetted to mix, and incubated at room temperature for 5 min. The bead-sample solution was then magnetically separated and 45 µl of supernatant was placed in a clean strip-tube. An additional 10 µl of beads was then added to each 45 µl sample for collection. After a 5-min incubation, beads were magnetically recovered and washed twice in 80% ethanol. Size-selected libraries were eluted off the beads with 20 µl double-distilled water. Completed libraries were then quantified in an Agilent Bioanalyzer using the High Sensitivity DNA Assay, and diluted to 10 nM. Libraries were pooled and sequenced at the UCSF Center for Advanced Technology on an Illumina HiSeq4000 sequencer with adequate PhiX spike-in DNA (~30%). Approximately 13–20 million reads were obtained and analysed per sample.

**RRBS data analysis.** RRBS fastq files were first trimmed for quality and MspI-induced overhangs using Trim Galore! (Babraham Bioinformatics) with RRBS-specific settings. Trimmed files were then aligned to the mouse mm9 genome and methylation extracted using Bismark, a program specific for alignment of

bisulphite-treated DNA⁴⁵. Given the very low genome-wide methylation in E13.5 PGCs (<5% total methylation, Extended Data Fig. 5a), the R program BiSeq⁴⁶ was determined to be the most appropriate to detect differential methylation. BiSeq is a DMR-detecting method that enables testing within target regions, like with RRBS, and allows calculation of FDR. Coverage and methylation calls per CpG calculated with Bismark were imported into RStudio, and these files were then used to build the BiSeq data-frame, accounting for replicates. Coverage data were filtered with requirements of more than 5× coverage in a minimum of 9 out of 12 samples per CpG. Each sample contained 1.3 million–1.6 million CpGs passing this coverage threshold. CpGs were categorized into clusters, with a cluster defined as a string of >5 CpGs with a maximum of 20 bp distance between adjacent CpGs. In total, 52,707 clusters were defined across the mouse genome ranging from 10 to 370 bp per cluster (53 bp average cluster size). Functional annotation of DMRs was done using GREAT⁴⁷. TET1-binding sites in ES cells⁴⁸ and DNMT1-targeting sites in ES cells⁴⁹ were previously described. Transposable element genomic locations were downloaded from UCSC RepeatMasker for transposable element-methylation analysis.

**hmC quantification.** E13.5 forebrain and liver were dissected and DNA was extracted using the DNeasy Blood and Tissue kit (Qiagen). DNA hydroxymethylation was measured by ELISA using the Global 5-hmC DNA Quantification Kit (Active Motif) according to the manufacturer's protocol. In total, 50 ng were used for the quantification.

For hmC quantification by dot blot, 30 ng of DNA extracted from tissues was spotted onto a nylon membrane (GE Healthcare Hybond-N+). The membrane was dried and baked at 80°C for 2 h, before being blocked in 5% (w/v) non-fat dry milk in PBS plus 0.1% Tween-20 for 1 h. The membrane was then transferred into blocking solution supplemented with rabbit anti-hmC antibody (Active Motif 39791) diluted 1:1,000 and incubated overnight at 4°C. Thereafter, it was washed three times with PBS plus 0.1% Tween-20 for a total of 30 min. The membrane was transferred into blocking solution supplemented with horseradish peroxidase (HRP)-linked anti-rabbit IgG (Jackson ImmunoResearch 111-035-144) diluted 1:10,000 before incubation for 1 h at room temperature followed by three washing steps with PBS plus 0.1% Tween-20. Peroxidase activity was detected with Pierce ECL Western Blotting Substrate (Thermo Fisher Scientific) using the ChemiDoc MP Imaging Syste (Bio-Rad). Specificity of the anti-hmC antibody was assessed using amplicons produced by PCR with the DreamTaq DNA Polymerase (Thermo Fisher Scientific), according to the manufacturer's protocol, using dNTPs with unmodified cytosine residues (Zymo Research, D1000-1), methylated cytosines (Zymo Research, D1030), or hydroxymethylated cytosine residues (Zymo Research, D1040).

**Low input CUT&RUN.** CUT&RUN experiments were performed on samples of 1,000 nuclei isolated from FACS-purified E13.5 gonadal PGCs and soma as previously described⁵⁰ and originally developed⁵¹. Maintenance of pregnant *Gulo*⁻/⁻ female mice and E13.5 gonadal dissections were performed as described above. Flow cytometry (FACS) was used to isolate 2,000 PGCs or soma from control or vitamin-C-deprived E13.5 female embryos per sample, sorting directly into chilled PGC media (DMEM, 15% FBS, 100 U ml⁻¹ leukaemia inhibitory factor (LIF), 5 µM forskolin, 1 ng ml⁻¹ stem cell factor (SCF)). For vitamin-C-deprived PGC samples, several embryos were pooled if needed at sorting, owing to an overall lower PGC number per embryo, to allow collection of sufficient PGCs per sample. After FACS, dimethylsulfoxide (DMSO) was added to cells in PGC media at a final concentration of 1:100 in 200 µl wash buffer (as blocking buffer, without EDTA) and rotated for 2 h at 4°C, washed twice in wash buffer, then incubated with pA-MN fusion protein for 1 h at 4°C at a final dilution of 1:200 in wash buffer. Samples were next equilibrated to 0°C in a metal hot-block, which was pre-chilled by submersion in wet ice, then the pA-MN was activated by addition of 2 mM CaCl₂. Cleavage was allowed to proceed for exactly 30 min at 0°C before stopping with an equal volume of 2XSTOP buffer (200 mM NaCl, 20 mM EDTA, 4 mM EGTA, 50 µg ml⁻¹ RNase A, 40 µg ml⁻¹ glycogen, 10 pg ml⁻¹ yeast MNase-treated nucleosomal spike-in DNA). The same 2XSTOP solution minus RNase A was used for both PGC and
NOBOX objects. An Imaris surface was created around entire ovary to exclude oviposition and surrounding tissue and channels were masked to this surface for analysis. The ovary volume was generated from this Imaris surface contour. Images were filtered using Background Subtraction with a 30-µm filter and Gaussian Filter 1 voxel size. NOBOX objects were quantified using the Imaris spot module with a diameter of 8 µm and all spot objects were selected.

**Statistical analyses.** All statistical calculations were performed with GraphPad Prism 7.0 software or within R studio. Details of individual tests are outlined within each figure legend.

**RNA-seq.** Germ-cell RNA isolated from single embryos was quantified using an Agilent Bioanalyzer RNA Pico Kit. Barcoded libraries were created from 1.5 ng DNaseI-treated total RNA using Clonetech SMARTR-seq RNA library prep kit according to the manufacturer's recommendations. Successful libraries were bioanalyzed for quality and size distribution and then quantified using the Qubit dsDNA HS Assay Kit. Diluted libraries were pooled at equal 5 nM concentrations for sequencing. Final product was sequenced as 50-bp single-end reads on one lane of an Illumina HiSeq4000 at the UCSF Center for Advanced Technology. Six embryos were sequenced per condition, totalling 12 libraries in all. Approximately 25–40 million reads were obtained and analysed per sample. Single-end reads were quality-controlled and adaptor-trimmed using Trim Galore! (Babraham Bioinformatics). Filtered reads were mapped to the mm9 mouse genome using Tophat²³⁷. Reads mapping uniquely to known genes were counted using hseq-count³⁸. Count data were subsequently imported into R with Bioconductor³⁹ and filtered to remove non-expressed genes. For read-depth normalization, filtered gene count data were analysed using the R package DESeq²⁴⁰. Data were input into a DESeq object and normalized according to package recommendations. Gene Ontology term enrichment was analysed using DAVID⁴¹, and comparisons to the data from *Tet1*⁻/⁻ E13.5 germ cells⁸ were carried out using GSEA⁴².

**Reduced RRBS on single embryo PGCs.** We modified previously published protocols for RRBS and single-cell RRBS⁴³,⁴⁴ to create a streamlined single-tube workflow for low-input. Each RRBS library was created from 2 ng of genomic DNA collected from PGCs isolated by FACS from single E13.5 embryos. Initially, gDNA was extracted from *Oct4-eGFP* PGCs using Purelink Genomic DNA kit (K1820-00 Invitrogen) according to the manufacturer's instructions. Genomic DNA (2 ng) and 0.25% lambda DNA were then digested with 10 U of MspI enzyme (Fermentas) in a total reaction volume of 18 µl at 37°C for 3 h, followed by heat inactivation at 80°C for 20 min. End repair and A-addition was then carried out to repair and tail the 3' end of each digested fragment. This reaction was done immediately following MspI digestion by adding 2 µl of 5 U Klenow exo- with additional dNTPs (0.04 mM dATP, 0.004 mM dGTP, 0.004 mM dCTP) directly to the 18 µl digest. This reaction was incubated at 37°C for 40 min followed by heat inactivation at 75°C for 15 min. After repair, NEBNext USER methylated adaptors were ligated onto the DNA by adding 25 U of T4 DNA Ligase, 1.5 mM ATP, and 25 nM NEB Adaptors directly to the 20 µl reaction, giving a final reaction volume of 30 µl. Adaptor ligation was performed at 16°C for 30 min and then left at 4°C overnight. The following day, 1 µl of NEB USER enzyme was added to each reaction, followed by an incubation at 37°C for 15 min and then inactivation at 65°C for 20 min. Per the manufacturer's protocol, NEB USER enzyme is required for NEBNext adaptor cleavage.

Bisulphite conversion was performed on each 30 µl sample containing DNA fragments with methylated sequencing adapters. We used the low-concentration protocol of the EpiTect Fast Bisulphite Conversion Kit (Qiagen), eluting in 15 µl. Converted DNA (13 µl) was used directly in a library amplification PCR, which was optimized for 2 ng input, including 1 µl NEBNext Primer F, 1 µl NEBNext R, and 15 µl of 2× HiFi Uracil+ Mix (KAPA). This reaction was incubated at 95°C for 2 min, followed by 15 cycles of 95°C for 20 s; 60°C for 30 s; 72°C for 1 min, with a final step of 72°C for 5 min and a hold at 4°C. At this point, all samples were quantified using the Qubit dsDNA HS Assay Kit.

Successfully amplified libraries were completed with size selection and clean up. Size selection of 200–600-bp fragments was performed using Axygen Fragment Select-I beads. First, 0.5 volume of beads (15 µl) was added to the 30 µl sample, pipetted to mix, and incubated at room temperature for 5 min. The bead-sample solution was then magnetically separated and 45 µl of supernatant was placed in a clean strip-tube. An additional 10 µl of beads was then added to each 45 µl sample for collection. After a 5-min incubation, beads were magnetically recovered and washed twice in 80% ethanol. Size-selected libraries were eluted off the beads with 20 µl double-distilled water. Completed libraries were then quantified in an Agilent Bioanalyzer using the High Sensitivity DNA Assay, and diluted to 10 nM. Libraries were pooled and sequenced at the UCSF Center for Advanced Technology on an Illumina HiSeq4000 sequencer with adequate PhiX spike-in DNA (~30%). Approximately 13–20 million reads were obtained and analysed per sample.

**RRBS data analysis.** RRBS fastq files were first trimmed for quality and MspI-induced overhangs using Trim Galore! (Babraham Bioinformatics) with RRBS-specific settings. Trimmed files were then aligned to the mouse mm9 genome and methylation extracted using Bismark, a program specific for alignment of

bisulphite-treated DNA⁴⁵. Given the very low genome-wide methylation in E13.5 PGCs (<5% total methylation, Extended Data Fig. 5a), the R program BiSeq⁴⁶ was determined to be the most appropriate to detect differential methylation. BiSeq is a DMR-detecting method that enables testing within target regions, like with RRBS, and allows calculation of FDR. Coverage and methylation calls per CpG calculated with Bismark were imported into RStudio, and these files were then used to build the BiSeq data-frame, accounting for replicates. Coverage data were filtered with requirements of more than 5× coverage in a minimum of 9 out of 12 samples per CpG. Each sample contained 1.3 million–1.6 million CpGs passing this coverage threshold. CpGs were categorized into clusters, with a cluster defined as a string of >5 CpGs with a maximum of 20 bp distance between adjacent CpGs. In total, 52,707 clusters were defined across the mouse genome ranging from 10 to 370 bp per cluster (53 bp average cluster size). Functional annotation of DMRs was done using GREAT⁴⁷. TET1-binding sites in ES cells⁴⁸ and DNMT1-targeting sites in ES cells⁴⁹ were previously described. Transposable element genomic locations were downloaded from UCSC RepeatMasker for transposable element-methylation analysis.

**hmC quantification.** E13.5 forebrain and liver were dissected and DNA was extracted using the DNeasy Blood and Tissue kit (Qiagen). DNA hydroxymethylation was measured by ELISA using the Global 5-hmC DNA Quantification Kit (Active Motif) according to the manufacturer's protocol. In total, 50 ng were used for the quantification.

For hmC quantification by dot blot, 30 ng of DNA extracted from tissues was spotted onto a nylon membrane (GE Healthcare Hybond-N+). The membrane was dried and baked at 80°C for 2 h, before being blocked in 5% (w/v) non-fat dry milk in PBS plus 0.1% Tween-20 for 1 h. The membrane was then transferred into blocking solution supplemented with rabbit anti-hmC antibody (Active Motif 39791) diluted 1:1,000 and incubated overnight at 4°C. Thereafter, it was washed three times with PBS plus 0.1% Tween-20 for a total of 30 min. The membrane was transferred into blocking solution supplemented with horseradish peroxidase (HRP)-linked anti-rabbit IgG (Jackson ImmunoResearch 111-035-144) diluted 1:10,000 before incubation for 1 h at room temperature followed by three washing steps with PBS plus 0.1% Tween-20. Peroxidase activity was detected with Pierce ECL Western Blotting Substrate (Thermo Fisher Scientific) using the ChemiDoc MP Imaging Syste (Bio-Rad). Specificity of the anti-hmC antibody was assessed using amplicons produced by PCR with the DreamTaq DNA Polymerase (Thermo Fisher Scientific), according to the manufacturer's protocol, using dNTPs with unmodified cytosine residues (Zymo Research, D1000-1), methylated cytosines (Zymo Research, D1030), or hydroxymethylated cytosine residues (Zymo Research, D1040).

**Low input CUT&RUN.** CUT&RUN experiments were performed on samples of 1,000 nuclei isolated from FACS-purified E13.5 gonadal PGCs and soma as previously described⁵⁰ and originally developed⁵¹. Maintenance of pregnant *Gulo*⁻/⁻ female mice and E13.5 gonadal dissections were performed as described above. Flow cytometry (FACS) was used to isolate 2,000 PGCs or soma from control or vitamin-C-deprived E13.5 female embryos per sample, sorting directly into chilled PGC media (DMEM, 15% FBS, 100 U ml⁻¹ leukaemia inhibitory factor (LIF), 5 µM forskolin, 1 ng ml⁻¹ stem cell factor (SCF)). For vitamin-C-deprived PGC samples, several embryos were pooled if needed at sorting, owing to an overall lower PGC number per embryo, to allow collection of sufficient PGCs per sample. After FACS, dimethylsulfoxide (DMSO) was added to cells in PGC media at a final concentration of 1:100 in 200 µl wash buffer (as blocking buffer, without EDTA) and rotated for 2 h at 4°C, washed twice in wash buffer, then incubated with pA-MN fusion protein for 1 h at 4°C at a final dilution of 1:200 in wash buffer. Samples were next equilibrated to 0°C in a metal hot-block, which was pre-chilled by submersion in wet ice, then the pA-MN was activated by addition of 2 mM CaCl₂. Cleavage was allowed to proceed for exactly 30 min at 0°C before stopping with an equal volume of 2XSTOP buffer (200 mM NaCl, 20 mM EDTA, 4 mM EGTA, 50 µg ml⁻¹ RNase A, 40 µg ml⁻¹ glycogen, 10 pg ml⁻¹ yeast MNase-treated nucleosomal spike-in DNA). The same 2XSTOP solution minus RNase A was used for both PGC and
soma CUT&RUN experiments, to allow direct comparison between cell types and antibodies. Finally, cleaved DNA fragments were released by incubation at 37°C for 20 min, followed by centrifugation and collection of the supernatant containing released DNA fragments to new tubes. DNA was isolated using QIAGEN PCR Purification kits, eluting the purified DNA twice in the same 30 µl 0.1 × TE buffer. The entire eluate was used for library generation with the Hyper Prep Kit (KAPA), according to the manufacturer's instructions for inputs <1 ng, and 18 cycles of PCR amplification. At the end of the library generation protocol, excess adaptor dimers were removed via an extra 0.85–0.9 × Ampure XP bead clean-up step. All libraries were verified for quality and concentration with Bioanalyzer DNA HS assays, before pooling all PGC and soma samples for sequencing.

**CUT&RUN sequencing and bioinformatics.** Paired-end sequencing (PE150) was performed at the UCSF CAT core, and reads were processed and normalized as previously described⁵¹. Raw fastq reads were quality-controlled and adaptor-trimmed using Trim Galore! (Babraham Bioinformatics), using standard settings, then mapped to mm10 with Bowtie2 and settings --local --very-sensitive-local --no-unal --no-mixed --no-discordant --phred33 -I 10 -X 1000, or to the yeast (Saccharomyces cerevisiae) genome with settings --local --very-sensitive-local --no-unal --no-mixed --no-discordant --phred33 -I 10 -X 700 --no-overlap --no-dovetail. We noted lower than expected mapping efficiencies especially for PGC samples, which may have arisen from an overall very low H3K9me2 abundance in these cells (Extended Data Fig. 8b). Successfully mapped mouse and yeast reads were deduplicated with Picard MarkDuplicates as recommended for low input numbers, before downstream analyses. For comparison between distinct conditions and cell types, total mapped reads were normalized to the number of mapped, deduplicated spike-in reads per sample. To compare and quantify H3K9me2 enrichment across samples and conditions at individual loci, reads were summarized across gene bodies or transposable element families using RSubread package, FeatureCounts in R/Bioconductor, normalized to spike-in reads, and presented as 1,000 × normalized coverage/spike-in. For determination of differentially H3K9me2-enriched genes or transposable elements, we used our previously described spike-in normalization method⁵² and the Limma Voom package⁵³, where we used mapped deduplicated yeast read counts as normalization factors. Differential genes or transposable elements were called as those exceeding log2-transformed fold change > |1| and FDR <0.05. For correlation analyses between H3K9me2 enrichment and gene expression, we used female E13.5 control PGC and soma normalized RNA-seq expression values generated in this study.

**Reporting Summary.** Further information on research design is available in the Nature Research Reporting Summary linked to this paper.

## Code availability

Custom codes used for data analysis were deposited in Github (https://github.com/Santosi/VitC-PGCs) and are also available upon request.

## Data availability

RNA-seq, RRBS and CUT&RUN data have been deposited in Gene Expression Omnibus (GEO) under accession number GSE109747.

30. Kim, H. et al. The analysis of vitamin C concentration in organs of *Gulo*⁻/⁻ mice upon vitamin C withdrawal. *Immune Netw.* **12**, 18–26 (2012).

31. Franks, L. M. & Payne, J. The influence of age on reproductive capacity in C57BL mice. *J. Reprod. Fertil.* **21**, 563–565 (1970).

32. Agathocleous, M. et al. Ascorbate regulates haematopoietic stem cell function and leukaemogenesis. *Nature* **549**, 476–481 (2017).

33. Guerquin, M.-J. et al. New testicular mechanisms involved in the prevention of fetal meiotic initiation in mice. *Dev. Biol.* **346**, 320–330 (2010).

34. Arora, R. et al. Meiotic onset is reliant on spatial distribution but independent of germ cell number in the mouse ovary. *J. Cell Sci.* **129**, 2493–2499 (2016).

35. Abby, E. et al. Implementation of meiosis prophase I programme requires a conserved retinoid-independent stabilizer of meiotic transcripts. *Nat. Commun.* **7**, 10324 (2016).

36. Faire, M. et al. Follicle dynamics and global organization in the intact mouse ovary. *Dev. Biol.* **403**, 69–79 (2015).

37. Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. *Genome Biol.* **14**, R36 (2013).

38. Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. *Bioinformatics* **31**, 166–169 (2015).

39. Huber, W. et al. Orchestrating high-throughput genomic analysis with Bioconductor. *Nat. Methods* **12**, 115–121 (2015).

40. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. *Genome Biol.* **15**, 550 (2014).

41. Huang, W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. *Nat. Protocols* **4**, 44–57 (2009).

42. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. *Proc. Natl Acad. Sci. USA* **102**, 15545–15550 (2005).

43. Meissner, A. et al. Genome-scale DNA methylation maps of pluripotent and differentiated cells. *Nature* **454**, 766–770 (2008).

44. Guo, H. et al. Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing. *Genome Res.* **23**, 2126–2135 (2013).

45. Krueger, F. & Andrews, S. R. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. *Bioinformatics* **27**, 1571–1572 (2011).

46. Hebestreit, K., Dugas, M. & Klein, H.-U. Detection of significantly differentially methylated regions in targeted bisulfite sequencing data. *Bioinformatics* **29**, 1647–1653 (2013).

47. McLean, C. Y. et al. GREAT improves functional interpretation of cis-regulatory regions. *Nat. Biotechnol.* **28**, 495–501 (2010).

48. Wu, H. et al. Dual functions of Tet1 in transcriptional regulation in mouse embryonic stem cells. *Nature* **473**, 389–393 (2011).

49. Li, Z. et al. Distinct roles of DNMT1-dependent and DNMT1-independent methylation patterns in the genome of mouse embryonic stem cells. *Genome Biol.* **16**, 115 (2015).

50. Hainer, S. J., Bošković, A., McCannel, K. N., Rando, O. J. & Fazzio, T. G. Profiling of pluripotency factors in stem cells and early embryos. *Cell* **177**, 1319–1329 (2019).

51. Skene, P. J., Henikoff, J. G. & Henikoff, S. Targeted in situ genome-wide profiling with high efficiency for low cell numbers. *Nat. Protocols* **13**, 1006–1019 (2018).

52. Perchardé, M., Wong, P. & Ramalho-Santos, M. Global hypertranscription in the mouse embryonic germline. *Cell Reports* **19**, 1987–1996 (2017).

53. Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. *Nucleic Acids Res.* **43**, e47 (2015).

**Acknowledgements** We thank M. Conti, R. Blelloch, P. Rinaudo, M. Lorinzc, S. Fisher, L. Selleri and members of the Santos laboratory for input and critical reading of the manuscript. We thank E. Chow and members of the UCSF Center for Advanced Technology for assistance with sequencing; B. Soygur for meiotic spread protocol and reagents; Y. Zhang and L. Shen for technical advice on RRBS. We are grateful to S. Henikoff for providing the pA-MN and yeast tRNA spike-ins, and to S. Henikoff and T. Fazzio for providing technical help with performing CUT&RUN experiments. Flow cytometry data were generated in the UCSF Parnassus Flow Cytometry Core, which is supported by a Diabetes Research Center grant and NIH grant P30 DK063720. S.P.D. was supported by the National Science Foundation Graduate Research Fellowship Program under grant no. 1650113. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. G.L. was partly supported by Institut Universitaire de France. This work was supported by National Institutes of Health (NIH) grants R21ES023297 and R01ES028212 to D.J.L., and NIH grants R01OD012204 and R01GM123556, and a Canada 150 Research Chair to M.R.-S.

**Author contributions** S.P.D. and M.R.-S. conceived the project. S.P.D. designed, performed and analysed most experiments with following exceptions. M.P. performed and analysed CUT&RUN experiments and somatic cell RNA-seq. M.P. collaborated with E.C., S.M. and M.A. to quantify vitamin C levels in embryos. M.-J.G. performed histology, immunohistochemistry and meiosis analysis on E14.5 fetal ovaries and testes under the supervision of G.L. E.W. performed and analysed whole-mount imaging on day 7 ovaries under the supervision of D.J.L. E.C. performed hmC quantifications. K.T.E. and K.M. set up the initial conditions for analysis of the mouse gestational vitamin C deficiency model. M.R.-S. supervised the project. S.P.D. and M.R.-S. wrote the manuscript with feedback from all authors.

**Competing interests** The authors declare no competing interests.

### Additional information

**Supplementary information** is available for this paper at https://doi.org/10.1038/s41586-019-1536-1.

**Correspondence and requests for materials** should be addressed to M.R.

**Reprints and permissions information** is available at http://www.nature.com/reprints.
soma CUT&RUN experiments, to allow direct comparison between cell types and antibodies. Finally, cleaved DNA fragments were released by incubation at 37°C for 20 min, followed by centrifugation and collection of the supernatant containing released DNA fragments to new tubes. DNA was isolated using QIAGEN PCR Purification kits, eluting the purified DNA twice in the same 30 µl 0.1 × TE buffer. The entire eluate was used for library generation with the Hyper Prep Kit (KAPA), according to the manufacturer's instructions for inputs <1 ng, and 18 cycles of PCR amplification. At the end of the library generation protocol, excess adaptor dimers were removed via an extra 0.85–0.9 × Ampure XP bead clean-up step. All libraries were verified for quality and concentration with Bioanalyzer DNA HS assays, before pooling all PGC and soma samples for sequencing.

**CUT&RUN sequencing and bioinformatics.** Paired-end sequencing (PE150) was performed at the UCSF CAT core, and reads were processed and normalized as previously described⁵¹. Raw fastq reads were quality-controlled and adaptor-trimmed using Trim Galore! (Babraham Bioinformatics), using standard settings, then mapped to mm10 with Bowtie2 and settings --local --very-sensitive-local --no-unal --no-mixed --no-discordant --phred33 -I 10 -X 1000, or to the yeast (Saccharomyces cerevisiae) genome with settings --local --very-sensitive-local --no-unal --no-mixed --no-discordant --phred33 -I 10 -X 700 --no-overlap --no-dovetail. We noted lower than expected mapping efficiencies especially for PGC samples, which may have arisen from an overall very low H3K9me2 abundance in these cells (Extended Data Fig. 8b). Successfully mapped mouse and yeast reads were deduplicated with Picard MarkDuplicates as recommended for low input numbers, before downstream analyses. For comparison between distinct conditions and cell types, total mapped reads were normalized to the number of mapped, deduplicated spike-in reads per sample. To compare and quantify H3K9me2 enrichment across samples and conditions at individual loci, reads were summarized across gene bodies or transposable element families using RSubread package, FeatureCounts in R/Bioconductor, normalized to spike-in reads, and presented as 1,000 × normalized coverage/spike-in. For determination of differentially H3K9me2-enriched genes or transposable elements, we used our previously described spike-in normalization method⁵² and the Limma Voom package⁵³, where we used mapped deduplicated yeast read counts as normalization factors. Differential genes or transposable elements were called as those exceeding log2-transformed fold change > |1| and FDR <0.05. For correlation analyses between H3K9me2 enrichment and gene expression, we used female E13.5 control PGC and soma normalized RNA-seq expression values generated in this study.

**Reporting Summary.** Further information on research design is available in the Nature Research Reporting Summary linked to this paper.

## Code availability

Custom codes used for data analysis were deposited in Github (https://github.com/Santosi/VitC-PGCs) and are also available upon request.

## Data availability

RNA-seq, RRBS and CUT&RUN data have been deposited in Gene Expression Omnibus (GEO) under accession number GSE109747.

30. Kim, H. et al. The analysis of vitamin C concentration in organs of *Gulo*⁻/⁻ mice upon vitamin C withdrawal. *Immune Netw.* **12**, 18–26 (2012).

31. Franks, L. M. & Payne, J. The influence of age on reproductive capacity in C57BL mice. *J. Reprod. Fertil.* **21**, 563–565 (1970).

32. Agathocleous, M. et al. Ascorbate regulates haematopoietic stem cell function and leukaemogenesis. *Nature* **549**, 476–481 (2017).

33. Guerquin, M.-J. et al. New testicular mechanisms involved in the prevention of fetal meiotic initiation in mice. *Dev. Biol.* **346**, 320–330 (2010).

34. Arora, R. et al. Meiotic onset is reliant on spatial distribution but independent of germ cell number in the mouse ovary. *J. Cell Sci.* **129**, 2493–2499 (2016).

35. Abby, E. et al. Implementation of meiosis prophase I programme requires a conserved retinoid-independent stabilizer of meiotic transcripts. *Nat. Commun.* **7**, 10324 (2016).

36. Faire, M. et al. Follicle dynamics and global organization in the intact mouse ovary. *Dev. Biol.* **403**, 69–79 (2015).

37. Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. *Genome Biol.* **14**, R36 (2013).

38. Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. *Bioinformatics* **31**, 166–169 (2015).

39. Huber, W. et al. Orchestrating high-throughput genomic analysis with Bioconductor. *Nat. Methods* **12**, 115–121 (2015).

40. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. *Genome Biol.* **15**, 550 (2014).

41. Huang, W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. *Nat. Protocols* **4**, 44–57 (2009).

42. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. *Proc. Natl Acad. Sci. USA* **102**, 15545–15550 (2005).

43. Meissner, A. et al. Genome-scale DNA methylation maps of pluripotent and differentiated cells. *Nature* **454**, 766–770 (2008).

44. Guo, H. et al. Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing. *Genome Res.* **23**, 2126–2135 (2013).

45. Krueger, F. & Andrews, S. R. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. *Bioinformatics* **27**, 1571–1572 (2011).

46. Hebestreit, K., Dugas, M. & Klein, H.-U. Detection of significantly differentially methylated regions in targeted bisulfite sequencing data. *Bioinformatics* **29**, 1647–1653 (2013).

47. McLean, C. Y. et al. GREAT improves functional interpretation of cis-regulatory regions. *Nat. Biotechnol.* **28**, 495–501 (2010).

48. Wu, H. et al. Dual functions of Tet1 in transcriptional regulation in mouse embryonic stem cells. *Nature* **473**, 389–393 (2011).

49. Li, Z. et al. Distinct roles of DNMT1-dependent and DNMT1-independent methylation patterns in the genome of mouse embryonic stem cells. *Genome Biol.* **16**, 115 (2015).

50. Hainer, S. J., Bošković, A., McCannel, K. N., Rando, O. J. & Fazzio, T. G. Profiling of pluripotency factors in stem cells and early embryos. *Cell* **177**, 1319–1329 (2019).

51. Skene, P. J., Henikoff, J. G. & Henikoff, S. Targeted in situ genome-wide profiling with high efficiency for low cell numbers. *Nat. Protocols* **13**, 1006–1019 (2018).

52. Perchardé, M., Wong, P. & Ramalho-Santos, M. Global hypertranscription in the mouse embryonic germline. *Cell Reports* **19**, 1987–1996 (2017).

53. Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. *Nucleic Acids Res.* **43**, e47 (2015).

**Acknowledgements** We thank M. Conti, R. Blelloch, P. Rinaudo, M. Lorinzc, S. Fisher, L. Selleri and members of the Santos laboratory for input and critical reading of the manuscript. We thank E. Chow and members of the UCSF Center for Advanced Technology for assistance with sequencing; B. Soygur for meiotic spread protocol and reagents; Y. Zhang and L. Shen for technical advice on RRBS. We are grateful to S. Henikoff for providing the pA-MN and yeast tRNA spike-ins, and to S. Henikoff and T. Fazzio for providing technical help with performing CUT&RUN experiments. Flow cytometry data were generated in the UCSF Parnassus Flow Cytometry Core, which is supported by a Diabetes Research Center grant and NIH grant P30 DK063720. S.P.D. was supported by the National Science Foundation Graduate Research Fellowship Program under grant no. 1650113. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. G.L. was partly supported by Institut Universitaire de France. This work was supported by National Institutes of Health (NIH) grants R21ES023297 and R01ES028212 to D.J.L., and NIH grants R01OD012204 and R01GM123556, and a Canada 150 Research Chair to M.R.-S.

**Author contributions** S.P.D. and M.R.-S. conceived the project. S.P.D. designed, performed and analysed most experiments with following exceptions. M.P. performed and analysed CUT&RUN experiments and somatic cell RNA-seq. M.P. collaborated with E.C., S.M. and M.A. to quantify vitamin C levels in embryos. M.-J.G. performed histology, immunohistochemistry and meiosis analysis on E14.5 fetal ovaries and testes under the supervision of G.L. E.W. performed and analysed whole-mount imaging on day 7 ovaries under the supervision of D.J.L. E.C. performed hmC quantifications. K.T.E. and K.M. set up the initial conditions for analysis of the mouse gestational vitamin C deficiency model. M.R.-S. supervised the project. S.P.D. and M.R.-S. wrote the manuscript with feedback from all authors.

**Competing interests** The authors declare no competing interests.

## Additional information

**Supplementary information** is available for this paper at https://doi.org/10.1038/s41586-019-1536-1.

**Correspondence and requests for materials** should be addressed to M.R.

**Reprints and permissions information** is available at http://www.nature.com/reprints.
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<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /><figcaption>Extended Data Fig. 1 | See next page for caption.</figcaption></figure>
**Extended Data Fig. 1** | Validation of vitamin C depletion and the downregulation of TET1-dependent germline genes in a mouse model of gestational vitamin C deficiency. **a**, Expression of vitamin C transporters (SVCT1, SVCT2 and GLUT8, encoded by *Slc23a1*, *Slc23a2* and *Glut8*, respectively) in developing female (F) germ cells. Data are from Seisenberger et al.³. **b**, Kinetics of vitamin C depletion from the serum of pregnant *Gulo*⁻¹⁻²⁻ mice after withdrawal from their drinking water. Pregnant female mice were removed from vitamin C supplementation at E3.5 and circulating blood serum was tested over the time course indicated. It takes five days of withdrawal for the circulating vitamin C levels to be <25%, and seven days to be essentially undetectable. Line plot connects the average blood serum values of three biological replicates. **c**, Vitamin C levels measured by mass spectrometry in E13.5 embryonic tissue with and without gestational vitamin C removal. E13.5 female head or liver were normalized by tissue weight. Samples with non-detectable levels of vitamin C were set to zero. *n* = 5 biological replicates per condition. **d**, The reduction in E13.5 female germ cells numbers after vitamin C deficiency is confirmed using both *Oct4*⁻eGFP and SSEA1 positivity. *n* = 6 matched biological replicates per condition. **e**, Gestational vitamin C deficiency does not affect average somatic cell number. *n* = 13 control and *n* = 10 vitamin-C-depleted biological replicates. **f**, Vitamin-C-deficient E13.5 female germ cells express lower levels of key germline

genes, as measured by qRT-PCR. *n* = 3 control and *n* = 4 vitamin-C-depleted biological replicates. The variability in *Stra8* expression in controls as assessed by qRT-PCR at E13.5 is because it is just being induced at this stage; RNA-seq and immunofluorescence data further document the significant reduction in *Stra8* RNA and protein levels in vitamin-C-deficient PGCs (Extended Data Fig. 3b, c). **g**, Expression of select germline genes are induced in a TET1/2-dependent manner after the addition of vitamin to cultured mouse ES cells¹¹. Gene expression was measured by qRT-PCR, plotted as mean of technical triplicates. Data are from Blaschke et al.¹¹. **h**, Decreased expression of select germline genes in *Tet1*⁻¹⁻²⁻ E13.5 germ cells as measured by RNA-seq. Data are from Yamaguchi et al.⁸, and denote averages of three controls and two *Tet1*⁻¹⁻²⁻ samples. **i**, Select germline genes induced by vitamin C in cultured ES cells (c) and downregulated in *Tet1*⁻¹⁻²⁻ germ cells (d) are also downregulated in vitamin-C-deficient E13.5 germ cells. Gene expression was measured by RNA-seq. *n* = 6 biological replicates. **j**, Gestational vitamin C deficiency does not affect transcription in the somatic cells of E13.5 female gonads as shown by unsupervised clustering of RNA-seq analysis. Clustering performed on *n* = 6 biological replicates per condition. Data are single values per stage (a), mean values (b, h), mean ± s.e.m. (c, i) or mean ± s.d. (d-g). *P* values determined by two-tailed *t*-test with Welch's correction (c, d, e), two-tailed Student's *t*-test (f).
**Extended Data Fig. 1** | Validation of vitamin C depletion and the downregulation of TET1-dependent germline genes in a mouse model of gestational vitamin C deficiency. **a**, Expression of vitamin C transporters (SVCT1, SVCT2 and GLUT8, encoded by *Slc23a1*, *Slc23a2* and *Glut8*, respectively) in developing female (F) germ cells. Data are from Seisenberger et al.³. **b**, Kinetics of vitamin C depletion from the serum of pregnant *Gulo*⁻¹⁻²⁻ mice after withdrawal from their drinking water. Pregnant female mice were removed from vitamin C supplementation at E3.5 and circulating blood serum was tested over the time course indicated. It takes five days of withdrawal for the circulating vitamin C levels to be <25%, and seven days to be essentially undetectable. Line plot connects the average blood serum values of three biological replicates. **c**, Vitamin C levels measured by mass spectrometry in E13.5 embryonic tissue with and without gestational vitamin C removal. E13.5 female head or liver were normalized by tissue weight. Samples with non-detectable levels of vitamin C were set to zero. *n* = 5 biological replicates per condition. **d**, The reduction in E13.5 female germ cells numbers after vitamin C deficiency is confirmed using both *Oct4*⁻eGFP and SSEA1 positivity. *n* = 6 matched biological replicates per condition. **e**, Gestational vitamin C deficiency does not affect average somatic cell number. *n* = 13 control and *n* = 10 vitamin-C-depleted biological replicates. **f**, Vitamin-C-deficient E13.5 female germ cells express lower levels of key germline

genes, as measured by qRT-PCR. *n* = 3 control and *n* = 4 vitamin-C-depleted biological replicates. The variability in *Stra8* expression in controls as assessed by qRT-PCR at E13.5 is because it is just being induced at this stage; RNA-seq and immunofluorescence data further document the significant reduction in *Stra8* RNA and protein levels in vitamin-C-deficient PGCs (Extended Data Fig. 3b, c). **g**, Expression of select germline genes are induced in a TET1/2-dependent manner after the addition of vitamin to cultured mouse ES cells¹¹. Gene expression was measured by qRT-PCR, plotted as mean of technical triplicates. Data are from Blaschke et al.¹¹. **h**, Decreased expression of select germline genes in *Tet1*⁻¹⁻²⁻ E13.5 germ cells as measured by RNA-seq. Data are from Yamaguchi et al.⁸, and denote averages of three controls and two *Tet1*⁻¹⁻²⁻ samples. **i**, Select germline genes induced by vitamin C in cultured ES cells (c) and downregulated in *Tet1*⁻¹⁻²⁻ germ cells (d) are also downregulated in vitamin-C-deficient E13.5 germ cells. Gene expression was measured by RNA-seq. *n* = 6 biological replicates. **j**, Gestational vitamin C deficiency does not affect transcription in the somatic cells of E13.5 female gonads as shown by unsupervised clustering of RNA-seq analysis. Clustering performed on *n* = 6 biological replicates per condition. Data are single values per stage (a), mean values (b, h), mean ± s.e.m. (c, i) or mean ± s.d. (d-g). *P* values determined by two-tailed *t*-test with Welch's correction (c, d, e), two-tailed Student's *t*-test (f).
<figure><img src="image_18.png" /><figcaption>b</figcaption></figure>

Ctrl **FOXL2** -VitC

<figure><img src="image_19.png" /></figure>

Bar: 10 µM

<caption>c</caption>

Ctrl **AMH** -VitC

<figure><img src="image_20.png" /></figure>

Bar: 10 µM

<caption>d</caption>

Ctrl **3BHSD** -VitC

<figure><img src="image_21.png" /></figure>

Bar: 10 µM
<figure><img src="image_17.png" /><figcaption>b</figcaption></figure>

<figure><img src="image_18.png" /><figcaption>Ctrl **FOXL2** -VitC</figcaption></figure>

Bar: 10 µM

<caption>c</caption>

<figure><img src="image_19.png" /><figcaption>Ctrl **AMH** -VitC</figcaption></figure>

Bar: 10 µM

<caption>d</caption>

<figure><img src="image_20.png" /><figcaption>Ctrl **3BHSD** -VitC</figcaption></figure>

Bar: 10 µM
**Extended Data Fig. 2 | Analyses of gonad development upon vitamin

**C deficiency.** a, There is an overall normal induction of key markers of developmental progression of somatic cells of the ovaries between E11.5 and E13.5 in vitamin-C-deficient embryos, as measured by qRT-PCR. E13.5 somatic ovary cells are matched with PGCs in Extended Data Fig. 1f. In this analysis, *Foxl2* expression is strongly induced after vitamin C deficiency, but to a slightly lower extent than in control samples. However, no significant changes in *Foxl2* were detected by RNA-seq (Fig. 1f) or immunofluorescence (b). Error bars of E13.5 samples depict mean ± s.d. of four biological replicates; E11.5 data are from two biological replicates. b, Sexual differentiation is controlled by a balance between SOX9 (leading to expression of anti-Müllerian hormone (AMH)) in male and FOXL2 in female mice. Expression of FOXL2 in E14 and E18 ovaries (O14 and

O18, respectively) does not change after vitamin C depletion as measured by immunohistochemistry. As expected, FOXL2 was not detected in E14 testes (T14). Images are representative of *n* = 5 control and *n* = 4 vitamin-C-deficient ovaries, and *n* = 2 control and *n* = 3 vitamin-C-deficient testes. c, Expression of AMH in E14 testis does not change after vitamin C depletion as measured by immunohistochemistry. As expected, AMH was not detected in E14 or E18 ovaries. Images are representative of *n* = 5 control and *n* = 4 vitamin-C-deficient ovaries, and *n* = 2 control and *n* = 3 vitamin-C-deficient testes. d, Gestational vitamin C deficiency does not affect the presence of Leydig cells (3BHSD) in developing testes or the absence of Leydig cells in developing ovaries. Images are representative of *n* = 5 control and *n* = 4 vitamin-C-deficient ovaries, and *n* = 2 control and *n* = 3 vitamin-C-deficient testes.
**Extended Data Fig. 2 | Analyses of gonad development upon vitamin

**C deficiency.** a, There is an overall normal induction of key markers of developmental progression of somatic cells of the ovaries between E11.5 and E13.5 in vitamin-C-deficient embryos, as measured by qRT-PCR. E13.5 somatic ovary cells are matched with PGCs in Extended Data Fig. 1f. In this analysis, *Foxl2* expression is strongly induced after vitamin C deficiency, but to a slightly lower extent than in control samples. However, no significant changes in *Foxl2* were detected by RNA-seq (Fig. 1f) or immunofluorescence (b). Error bars of E13.5 samples depict mean ± s.d. of four biological replicates; E11.5 data are from two biological replicates. b, Sexual differentiation is controlled by a balance between SOX9 (leading to expression of anti-Müllerian hormone (AMH)) in male and FOXL2 in female mice. Expression of FOXL2 in E14 and E18 ovaries (O14 and

O18, respectively) does not change after vitamin C depletion as measured by immunohistochemistry. As expected, FOXL2 was not detected in E14 testes (T14). Images are representative of *n* = 5 control and *n* = 4 vitamin-C-deficient ovaries, and *n* = 2 control and *n* = 3 vitamin-C-deficient testes. c, Expression of AMH in E14 testis does not change after vitamin C depletion as measured by immunohistochemistry. As expected, AMH was not detected in E14 or E18 ovaries. Images are representative of *n* = 5 control and *n* = 4 vitamin-C-deficient ovaries, and *n* = 2 control and *n* = 3 vitamin-C-deficient testes. d, Gestational vitamin C deficiency does not affect the presence of Leydig cells (3BHSD) in developing testes or the absence of Leydig cells in developing ovaries. Images are representative of *n* = 5 control and *n* = 4 vitamin-C-deficient ovaries, and *n* = 2 control and *n* = 3 vitamin-C-deficient testes.
<figure><img src="image_22.png" /></figure>

<figure><img src="image_23.png" /></figure>

<figure><img src="image_24.png" /></figure>

<figure><img src="image_25.png" /></figure>

<figure><img src="image_26.png" /></figure>

<figure><img src="image_27.png" /></figure>

<figure><img src="image_28.png" /></figure>

Black arrowhead indicates meiocyte. pL: meiotic S phase; I: leptotene; z:zygotene; p:pachytene; d:diplotene

<figure><img src="image_29.png" /></figure>

<figure><img src="image_30.png" /></figure>

<figure><img src="image_31.png" /><figcaption>Extended Data Fig. 3 | See next page for caption.</figcaption></figure>
<figure><img src="image_21.png" /></figure>

<figure><img src="image_22.png" /></figure>

<figure><img src="image_23.png" /></figure>

<figure><img src="image_24.png" /></figure>

<figure><img src="image_25.png" /></figure>

<figure><img src="image_26.png" /></figure>

<figure><img src="image_27.png" /></figure>

Black arrowhead indicates meiocyte. pL: meiotic S phase; I: leptotene; z:zygotene; p:pachytene; d:diplotene

<figure><img src="image_28.png" /></figure>

<figure><img src="image_29.png" /></figure>

<figure><img src="image_30.png" /></figure>
**Extended Data Fig. 3** | Detailed analyses of meiotic staging in germ cells of E14.5 vitamin-C-deficient ovaries. **a**, Representative images of STRA8 and SYCP3 abundance in E14.5 control or vitamin-C-deficient female germ cells. Images are representative of *n* = 7 STRA8 and *n* = 8 SYCP3 biologically independent experiments, as indicated in **b** and **d**. **b**, Significant reduction in the percentage of DDX4⁺ germ cells that are STRA8⁺ after vitamin C deficiency. **c**, *Stra8* mRNA abundance is significantly reduced at E13.5 as measured by RNA-seq. *n* = 6 biological replicates. **d**, There was a non-significant reduction in the average percentage of DDX4⁺ germ cells that are SYCP3⁺ in vitamin-C-deficient E14.5 female germ cells compared with controls. **e**, Abundance of *Sycp3* mRNA is significantly reduced at E13.5 as measured by RNA-seq. *n* = 6 biological replicates. **f**, Representative haematoxylin and eosin staining of E14.5 embryonic ovaries for data quantified in Fig. 1h. Black

arrowheads indicate germ cells at the indicated stage of meiosis. Images are representative of *n* = 8 biologically independent experiments.
**g**, The percentage of germ cells in meiotic S phase versus post-S phase is significantly higher in vitamin-C-deficient E14.5 female mice, relative to controls. Additional analysis of data from meiosis staging is shown in Fig. 1h. *n* = 8 biologically independent experiments. **h**, Representative images of CREST and SYCP1 staining in E18.5 germ cells, as in Fig. 1h. **i**, Ovarian follicle volume and frequency are not significantly different in P7 female mice deprived of vitamin C in utero (*P* = 0.206). Ovarian follicles were stained by NOBOX and quantified using whole-mount imaging. *n* = 6 control and *n* = 9 vitamin-C-depleted ovaries per condition. Data are mean (**c**, **e**), mean ± s.e.m. (**b**, **d**) or mean ± s.d. (**i**). *P* values determined by two-sided Mann-Whitney *U*-test (**b**, **d**), Wald χ² test (**c**, **e**, **g**) or paired two-sided homoscedastic Student's *t*-test (**i**).
**Extended Data Fig. 3** | Detailed analyses of meiotic staging in germ cells of E14.5 vitamin-C-deficient ovaries. **a**, Representative images of STRA8 and SYCP3 abundance in E14.5 control or vitamin-C-deficient female germ cells. Images are representative of *n* = 7 STRA8 and *n* = 8 SYCP3 biologically independent experiments, as indicated in **b** and **d**. **b**, Significant reduction in the percentage of DDX4⁺ germ cells that are STRA8⁺ after vitamin C deficiency. **c**, *Stra8* mRNA abundance is significantly reduced at E13.5 as measured by RNA-seq. *n* = 6 biological replicates. **d**, There was a non-significant reduction in the average percentage of DDX4⁺ germ cells that are SYCP3⁺ in vitamin-C-deficient E14.5 female germ cells compared with controls. **e**, Abundance of *Sycp3* mRNA is significantly reduced at E13.5 as measured by RNA-seq. *n* = 6 biological replicates. **f**, Representative haematoxylin and eosin staining of E14.5 embryonic ovaries for data quantified in Fig. 1h. Black

arrowheads indicate germ cells at the indicated stage of meiosis. Images are representative of *n* = 8 biologically independent experiments.
**g**, The percentage of germ cells in meiotic S phase versus post-S phase is significantly higher in vitamin-C-deficient E14.5 female mice, relative to controls. Additional analysis of data from meiosis staging is shown in Fig. 1h. *n* = 8 biologically independent experiments. **h**, Representative images of CREST and SYCP1 staining in E18.5 germ cells, as in Fig. 1h. **i**, Ovarian follicle volume and frequency are not significantly different in P7 female mice deprived of vitamin C in utero (*P* = 0.206). Ovarian follicles were stained by NOBOX and quantified using whole-mount imaging. *n* = 6 control and *n* = 9 vitamin-C-depleted ovaries per condition. Data are mean (**c**, **e**), mean ± s.e.m. (**b**, **d**) or mean ± s.d. (**i**). *P* values determined by two-sided Mann-Whitney *U*-test (**b**, **d**), Wald χ² test (**c**, **e**, **g**) or paired two-sided homoscedastic Student's *t*-test (**i**).
<figure><img src="image_32.png" /></figure>

<figure><img src="image_33.png" /></figure>

<figure><img src="image_34.png" /></figure>

**Extended Data Fig. 4** | Analyses of the effects of vitamin C deficiency on the development of male germ cells. a, Unlike the consistent reduction of female germ cells (top), vitamin C (VC) deficiency does not decrease the number of germ cells in E13.5 male gonads (bottom). ns, not significant. The number of biological replicates is indicated. b, The meiotic germ-cell marker SYCP3 was not identified in *n* = 2 or *n* = 3 male gonads with or without vitamin C depletion, respectively. *n* = 6 control and *n* = 5 vitamin-C-deficient biological replicates. c, The meiotic germ-cell marker

STRA8 was not identified in *n* = 2 or *n* = 3 male gonads with or without vitamin C depletion, respectively. Female graph includes *n* = 6 biological replicates. **d**, Most germ cells in developing testis are proliferative (Ki67+), with a few quiescent (Ki67−) germ cells, and no deviations from this pattern are detected with vitamin C deficiency. Images are representative of *n* = 2 control and *n* = 3 vitamin-C-deficient biological replicates. Data are mean ± s.d. (a) or mean ± s.e.m. (b, c). P values determined by two-sided Welch's t-test (a) or two-tailed Mann-Whitney U-test (b-d).
<figure><img src="image_31.png" /></figure>

<figure><img src="image_32.png" /></figure>

<figure><img src="image_33.png" /></figure>

**Extended Data Fig. 4** | Analyses of the effects of vitamin C deficiency on the development of male germ cells. a, Unlike the consistent reduction of female germ cells (top), vitamin C (VC) deficiency does not decrease the number of germ cells in E13.5 male gonads (bottom). ns, not significant. The number of biological replicates is indicated. b, The meiotic germ-cell marker SYCP3 was not identified in *n* = 2 or *n* = 3 male gonads with or without vitamin C depletion, respectively. *n* = 6 control and *n* = 5 vitamin-C-deficient biological replicates. c, The meiotic germ-cell marker

STRA8 was not identified in *n* = 2 or *n* = 3 male gonads with or without vitamin C depletion, respectively. Female graph includes *n* = 6 biological replicates. **d**, Most germ cells in developing testis are proliferative (Ki67+), with a few quiescent (Ki67−) germ cells, and no deviations from this pattern are detected with vitamin C deficiency. Images are representative of *n* = 2 control and *n* = 3 vitamin-C-deficient biological replicates. Data are mean ± s.d. (a) or mean ± s.e.m. (b, c). P values determined by two-sided Welch's t-test (a) or two-tailed Mann-Whitney U-test (b-d).
<table><caption>a</caption><thead><tr><th>sample</th><th>Litter #</th><th># of PGCs</th><th>Days off VitC before plug</th></tr></thead><tbody><tr><td>1C F1</td><td>Ctrl 1</td><td>1482</td><td>0</td></tr><tr><td>1C F2</td><td>Ctrl 1</td><td>804</td><td>0</td></tr><tr><td>2C F2</td><td>Ctrl 2</td><td>651</td><td>0</td></tr><tr><td>3C F2</td><td>Ctrl 3</td><td>531</td><td>0</td></tr><tr><td>4C F1</td><td>Ctrl 4</td><td>1850</td><td>0</td></tr><tr><td>4C F2</td><td>Ctrl 4</td><td>839</td><td>0</td></tr></tbody></table><table><tbody><tr><td>1V F1</td><td>-VitC 1</td><td>729</td><td>7</td></tr><tr><td>1V F2</td><td>-VitC 1</td><td>674</td><td>7</td></tr><tr><td>2V F1</td><td>-VitC 2</td><td>480</td><td>7</td></tr><tr><td>3V F1</td><td>-VitC 3</td><td>852</td><td>4</td></tr><tr><td>4V F1</td><td>-VitC 4</td><td>142</td><td>7</td></tr><tr><td>4V F2</td><td>-VitC 4</td><td>488</td><td>7</td></tr></tbody></table>

<figure><img src="image_35.png" /><figcaption>c</figcaption></figure>

<figure><img src="image_36.png" /><figcaption>d</figcaption></figure>

<figure><img src="image_37.png" /><figcaption>e</figcaption></figure>

<figure><img src="image_38.png" /><figcaption>f</figcaption></figure>

<figure><img src="image_39.png" /></figure>

Extended Data Fig. 5 | See next page for caption.
<table><caption>a</caption><thead><tr><th>sample</th><th>Litter #</th><th># of PGCs</th><th>Days off VitC before plug</th></tr></thead><tbody><tr><td>1C F1</td><td>Ctrl 1</td><td>1482</td><td>0</td></tr><tr><td>1C F2</td><td>Ctrl 1</td><td>804</td><td>0</td></tr><tr><td>2C F2</td><td>Ctrl 2</td><td>651</td><td>0</td></tr><tr><td>3C F2</td><td>Ctrl 3</td><td>531</td><td>0</td></tr><tr><td>4C F1</td><td>Ctrl 4</td><td>1850</td><td>0</td></tr><tr><td>4C F2</td><td>Ctrl 4</td><td>839</td><td>0</td></tr></tbody></table><table><tbody><tr><td>1V F1</td><td>-VitC 1</td><td>729</td><td>7</td></tr><tr><td>1V F2</td><td>-VitC 1</td><td>674</td><td>7</td></tr><tr><td>2V F1</td><td>-VitC 2</td><td>480</td><td>7</td></tr><tr><td>3V F1</td><td>-VitC 3</td><td>852</td><td>4</td></tr><tr><td>4V F1</td><td>-VitC 4</td><td>142</td><td>7</td></tr><tr><td>4V F2</td><td>-VitC 4</td><td>488</td><td>7</td></tr></tbody></table>

<figure><img src="image_34.png" /><figcaption>c</figcaption></figure>

<figure><img src="image_35.png" /><figcaption>d</figcaption></figure>

<figure><img src="image_36.png" /><figcaption>e</figcaption></figure>

<figure><img src="image_37.png" /><figcaption>f</figcaption></figure>

<figure><img src="image_38.png" /></figure>

Extended Data Fig. 5 | See next page for caption.
**Extended Data Fig. 5** | **Further analyses of RNA-seq data from vitamin-C-deficient E13.5 female germ cells.** a, Table of RNA-seq samples and number of germ cells per sample. Each sample represents germ cells from a single E13.5 female. b, Unsupervised hierarchical clustering of *n* = 6 biological replicates in each condition documents the overall separation between control and vitamin-C-deficient samples (columns) and relative gene expression (rows). 1CF1 denotes control litter 1, female embryo 1; 4VF2 denotes vitamin-C-deficient litter 4, female embryo 2. c, Scatterplot of differential gene expression in vitamin-C-deficient E13.5 female PGCs of genes differentially expressed in E13.5 *Tet1*⁻/⁻ female PGCs⁸. Spearman's rho statistic is used to estimate a rank-based measure of association. d, Expression of Dnmt and Tet genes in vitamin-C-deficient samples is similar to control samples. *n* = 6 biological replicates per condition. e, Heat map documenting the consistent expression of Tet and Dnmt genes across the six control and six vitamin-C-deficient samples. f, Expression of other genes belonging to families of enzymes with the potential to be vitamin C-sensitive (such as Kdm genes, collagen hydroxylases (P4h genes), prolyl hydroxylases (Lepre genes), HIF hydroxylases (Egln genes)). *Lepre1* is also known as *P3h1*; *Leprel1* is also known as *P3h2*; *Leprel2* is also known as *P3h3*; and *Leprel4* is also known as *P3h4*. None of these displays differential expression in vitamin-C-deficient female germ cells. *n* = 6 biological replicates per condition. Data are mean ± s.d. (d, f). Statistical significance assessed by two-tailed Student's *t*-test (d, f). n.d., not determined.
**Extended Data Fig. 5** | Further analyses of RNA-seq data from vitamin-C-deficient E13.5 female germ cells. **a**, Table of RNA-seq samples and number of germ cells per sample. Each sample represents germ cells from a single E13.5 female. **b**, Unsupervised hierarchical clustering of *n* = 6 biological replicates in each condition documents the overall separation between control and vitamin-C-deficient samples (columns) and relative gene expression (rows). 1CF1 denotes control litter 1, female embryo 1; 4VF2 denotes vitamin-C-deficient litter 4, female embryo 2.

c, Scatterplot of differential gene expression in vitamin-C-deficient E13.5 female PGCs of genes differentially expressed in E13.5 *Tet1*⁻/⁻ female PGCs⁸. Spearman's rho statistic is used to estimate a rank-based measure of association. **d**, Expression of Dnmt and Tet genes in vitamin-C-deficient samples is similar to control samples. *n* = 6 biological replicates per condition.

e, Heat map documenting the consistent expression of Tet and Dnmt genes across the six control and six vitamin-C-deficient samples. **f**, Expression of other genes belonging to families of enzymes with the potential to be vitamin C-sensitive (such as Kdm genes, collagen hydroxylases (P4h genes), prolyl hydroxylases (Lepre genes), HIF hydroxylases (Egln genes)). *Lepre1* is also known as *P3h1*; *Leprel1* is also known as *P3h2*; *Leprel2* is also known as *P3h3*; and *Leprel4* is also known as *P3h4*. None of these displays differential expression in vitamin-C-deficient female germ cells. *n* = 6 biological replicates per condition. Data are mean ± s.d. (d, f). Statistical significance assessed by two-tailed Student's *t*-test (d, f). n.d., not determined.
<figure><img src="image_40.png" /></figure>

**Extended Data Fig. 6** | Identification of the window of susceptibility to vitamin C deficiency between E3.5 and E13.5. a, Pregnant female mice mated in vitamin-C-deficient conditions were either maintained without vitamin C (–VitC) or returned to vitamin-C-containing water at E3.5 (3.5 return). b, Adding back vitamin C from E3.5 to E13.5 tends to rescue the defects in the expression of key germline regulators induced with full vitamin C deficiency. Gene expression was measured by qRT-PCR

in E13.5 female germ cells. *n* = 4 biological replicates. c, The numbers of E13.5 *Oct4*–eGFP+ germ cells are mostly recovered after the return of vitamin C at E3.5. Data are normalized to the germ-cell count of the control embryos. *n* = 11–22 biological replicates of each condition as indicated. Data are mean ± s.e.m. (b, c). \*P < 0.05; \*\*P < 0.01; two-tailed Student's *t*-test (b, c).
<figure><img src="image_39.png" /></figure>

**Extended Data Fig. 6** | Identification of the window of susceptibility to vitamin C deficiency between E3.5 and E13.5. a, Pregnant female mice mated in vitamin-C-deficient conditions were either maintained without vitamin C (–VitC) or returned to vitamin-C-containing water at E3.5 (3.5 return). b, Adding back vitamin C from E3.5 to E13.5 tends to rescue the defects in the expression of key germline regulators induced with full vitamin C deficiency. Gene expression was measured by qRT-PCR

in E13.5 female germ cells. *n* = 4 biological replicates. c, The numbers of E13.5 *Oct4*–eGFP+ germ cells are mostly recovered after the return of vitamin C at E3.5. Data are normalized to the germ-cell count of the control embryos. *n* = 11–22 biological replicates of each condition as indicated. Data are mean ± s.e.m. (b, c). \*P < 0.05; \*\*P < 0.01; two-tailed Student's *t*-test (b, c).
<figure><img src="image_41.png" /><figcaption>b</figcaption></figure>

<figure><img src="image_42.png" /><figcaption>c</figcaption></figure>

<figure><img src="image_43.png" /><figcaption>d</figcaption></figure>

<figure><img src="image_44.png" /><figcaption>e</figcaption></figure>

<figure><img src="image_45.png" /><figcaption>ERVK</figcaption></figure>

<figure><img src="image_46.png" /><figcaption>ERVK- IAP</figcaption></figure>

<caption>Satellite</caption>

<figure><img src="image_47.png" /><figcaption>g</figcaption></figure>

<figure><img src="image_48.png" /></figure>
<figure><img src="image_40.png" /><figcaption>b</figcaption></figure>

<figure><img src="image_41.png" /><figcaption>c</figcaption></figure>

<figure><img src="image_42.png" /><figcaption>d</figcaption></figure>

<figure><img src="image_43.png" /><figcaption>e</figcaption></figure>

<figure><img src="image_44.png" /><figcaption>Full-length LINE1</figcaption></figure>

<figure><img src="image_45.png" /><figcaption>SINE</figcaption></figure>

<figure><img src="image_46.png" /><figcaption>f</figcaption></figure>

<figure><img src="image_47.png" /><figcaption>g</figcaption></figure>

<figure><img src="image_48.png" /></figure>
**Extended Data Fig. 7** | DNA methylation defects in E13.5 vitamin-C-deficient female germ cells. **a**, Average methylation of cytosine according to sequence context. Genome-wide CpG methylation is 3–6% regardless of vitamin C supplementation. Methylation of cytosine in a CHG or CHH context (in which H correspond to A, T or C) is below 1%. **b**, Average methylation according to genomic context in control and vitamin-C-deficient samples. Box plots indicate minimum to maximum measurements of *n* = 6 biological replicates, with centre line denoting the mean. **c**, Top, density plot of 460 DMRs with a >5% methylation change reveals an overall increase in the number and magnitude of methylation gains over losses after vitamin C deficiency. Bottom, GREAT analysis of 175 hypomethylated DMRs (hypermethylated DMRs are in Fig. 4b). **d**, Transposable elements of the LINE1, LTR, ERVK and IAP families that are associated with DMRs show a consistent pattern of hypermethylation after vitamin C deficiency. *n* = 6 biological replicates. **e**, Average methylation in control or vitamin-C-deficient samples in different transposable element families across the genome. Data are from uniquely

mapped transposable elements annotated by RepeatMasker and captured by RRBS, regardless of the DMR calls, based on 558 elements and 3,180 CpGs (LINE1), 185 elements and 1,065 CpGs (full-length LINE1; >6 kb), 384 elements and 1,724 CpGs (SINE), 568 elements and 2,691 CpGs (ERVK), 226 elements and 1,057 CpGs (ERVK-IAP), 10 elements and 73 CpGs (satellite). The box extends to 25th and 75th percentiles, with centre line indicating the median transposable element methylation across *n* = 6 biological replicates. Error bars extend to 5th and 95th percentiles. **f**, hmC quantification by dot blot in E13.5 brain and liver indicate that hmC abundance is higher in brain and reduced with vitamin C depletion. Each group represents three biological replicates (across) and two technical replicates (vertical pairs). **g**, hmC quantification by ELISA (Active Motif) confirmed a significant decrease of hmC in both E13.5 brain and liver. Quantification was performed using 50 ng of DNA. *n* = 5 biological replicates. Data are mean ± s.e.m. (d, g). *P* values were determined by two-tailed Student's *t*-tests (d), two-tailed Wilcoxon matched-pairs signed-rank test (e) or two-sided Welch's *t*-test (g).
**Extended Data Fig. 7** | DNA methylation defects in E13.5 vitamin-C-deficient female germ cells. **a**, Average methylation of cytosine according to sequence context. Genome-wide CpG methylation is 3–6% regardless of vitamin C supplementation. Methylation of cytosine in a CHG or CHH context (in which H correspond to A, T or C) is below 1%. **b**, Average methylation according to genomic context in control and vitamin-C-deficient samples. Box plots indicate minimum to maximum measurements of *n* = 6 biological replicates, with centre line denoting the mean. **c**, Top, density plot of 460 DMRs with a >5% methylation change reveals an overall increase in the number and magnitude of methylation gains over losses after vitamin C deficiency. Bottom, GREAT analysis of 175 hypomethylated DMRs (hypermethylated DMRs are in Fig. 4b).

**d**, Transposable elements of the LINE1, LTR, ERVK and IAP families that are associated with DMRs show a consistent pattern of hypermethylation after vitamin C deficiency. *n* = 6 biological replicates. **e**, Average methylation in control or vitamin-C-deficient samples in different transposable element families across the genome. Data are from uniquely

mapped transposable elements annotated by RepeatMasker and captured by RRBS, regardless of the DMR calls, based on 558 elements and 3,180 CpGs (LINE1), 185 elements and 1,065 CpGs (full-length LINE1; >6 kb), 384 elements and 1,724 CpGs (SINE), 568 elements and 2,691 CpGs (ERVK), 226 elements and 1,057 CpGs (ERVK-IAP), 10 elements and 73 CpGs (satellite). The box extends to 25th and 75th percentiles, with centre line indicating the median transposable element methylation across *n* = 6 biological replicates. Error bars extend to 5th and 95th percentiles.

**f**, hmC quantification by dot blot in E13.5 brain and liver indicate that hmC abundance is higher in brain and reduced with vitamin C depletion. Each group represents three biological replicates (across) and two technical replicates (vertical pairs). **g**, hmC quantification by ELISA (Active Motif) confirmed a significant decrease of hmC in both E13.5 brain and liver. Quantification was performed using 50 ng of DNA.

*n* = 5 biological replicates. Data are mean ± s.e.m. (d, g). P values were determined by two-tailed Student's *t*-tests (d), two-tailed Wilcoxon matched-pairs signed-rank test (e) or two-sided Welch's *t*-test (g).
<figure><img src="image_49.png" /><figcaption>b</figcaption></figure>

<figure><img src="image_50.png" /></figure>

<figure><img src="image_51.png" /><figcaption>c</figcaption></figure>

<figure><img src="image_52.png" /><figcaption>d</figcaption></figure>

<figure><img src="image_53.png" /><figcaption>e</figcaption></figure>

<figure><img src="image_54.png" /><figcaption>f</figcaption></figure>

<figure><img src="image_55.png" /></figure>
<figure><img src="image_49.png" /><figcaption>b</figcaption></figure>

<figure><img src="image_50.png" /></figure>

<figure><img src="image_51.png" /><figcaption>c</figcaption></figure>

<figure><img src="image_52.png" /><figcaption>d</figcaption></figure>

<figure><img src="image_53.png" /><figcaption>e</figcaption></figure>

<figure><img src="image_54.png" /><figcaption>f</figcaption></figure>

<figure><img src="image_55.png" /></figure>
**Extended Data Fig. 8** | CUT&RUN analysis of H3K9me2 abundance in E13.5 female gonads. **a**, Diagram of CUT&RUN experiments. E13.5 control or vitamin-C-deficient gonads were dissociated and the PGCs and soma were separated by FACS for cryopreservation and CUT&RUN analysis. PGCs and soma from 3–5 independent embryos per condition were subjected to H3K9me2 (K9me2) or control (IgG) CUT&RUN. **b**, K9me2 enrichment is highest at non- or low-expressed genes. Box plots of average K9me2 coverage at genes in control soma or PGC samples, separated into quartiles from lowest (quartile 1) to highest (quartile 4) expression level in control E13.5 soma. Coverage is calculated from average (K9me2/IgG + 0.001) of *n* = 4 control and *n* = 3 vitamin-C-depleted soma replicates, and *n* = 5 PGC replicates per condition. **c**, Scatter plots of average K9me2 coverage at genes or transposable element families in control or vitamin-C-deficient E13.5 female soma and PGCs. *n* = 4 control and *n* = 3 vitamin-C-depleted soma replicates, and *n* = 5 PGC replicates per condition. Significantly upregulated (yellow) or

downregulated (blue) genes or transposable element families are indicated (log₂-transformed fold change > |1|, FDR < 0.05). **d**, Increases in soma K9me2 levels are highest at already K9me2-marked genes. Box plot showing K9me2 log₂-transformed fold change after vitamin C depletion in soma in groups of genes ranked according to K9me2 enrichment in control (lowest and highest quartile of K9me2 enrichment, and all genes). *n* = 4 control and *n* = 3 vitamin-C-depleted soma replicates, and *n* = 5 PGC replicates per condition. **e, f**, Histograms of K9me2 or IgG coverage at selected transposable element families in E13.5 female soma (e) or PGCs (f). *n* = 4 control and *n* = 3 vitamin-C-depleted soma replicates, and *n* = 5 PGC replicates per condition. Box plots in **b** and **d** indicate 25th and 75th percentiles, with centre lines marking the median values. Data are mean ± s.e.m. (e, f). *P* values were determined by two-sided Wilcoxon rank-sum test (**b, d**) or are the FDR from Limma analysis (**c, e, f**). See Supplementary Data 5 and Methods for details.
**Extended Data Fig. 8** | CUT&RUN analysis of H3K9me2 abundance in E13.5 female gonads. **a**, Diagram of CUT&RUN experiments. E13.5 control or vitamin-C-deficient gonads were dissociated and the PGCs and soma were separated by FACS for cryopreservation and CUT&RUN analysis. PGCs and soma from 3–5 independent embryos per condition were subjected to H3K9me2 (K9me2) or control (IgG) CUT&RUN. **b**, K9me2 enrichment is highest at non- or low-expressed genes. Box plots of average K9me2 coverage at genes in control soma or PGC samples, separated into quartiles from lowest (quartile 1) to highest (quartile 4) expression level in control E13.5 soma. Coverage is calculated from average (K9me2/IgG + 0.001) of *n* = 4 control and *n* = 3 vitamin-C-depleted soma replicates, and *n* = 5 PGC replicates per condition. **c**, Scatter plots of average K9me2 coverage at genes or transposable element families in control or vitamin-C-deficient E13.5 female soma and PGCs. *n* = 4 control and *n* = 3 vitamin-C-depleted soma replicates, and *n* = 5 PGC replicates per condition. Significantly upregulated (yellow) or

downregulated (blue) genes or transposable element families are indicated (log₂-transformed fold change > |1|, FDR < 0.05). **d**, Increases in soma K9me2 levels are highest at already K9me2-marked genes. Box plot showing K9me2 log₂-transformed fold change after vitamin C depletion in soma in groups of genes ranked according to K9me2 enrichment in control (lowest and highest quartile of K9me2 enrichment, and all genes). *n* = 4 control and *n* = 3 vitamin-C-depleted soma replicates, and *n* = 5 PGC replicates per condition. **e, f**, Histograms of K9me2 or IgG coverage at selected transposable element families in E13.5 female soma (e) or PGCs (f). *n* = 4 control and *n* = 3 vitamin-C-depleted soma replicates, and *n* = 5 PGC replicates per condition. Box plots in **b** and **d** indicate 25th and 75th percentiles, with centre lines marking the median values. Data are mean ± s.e.m. (e, f). *P* values were determined by two-sided Wilcoxon rank-sum test (**b, d**) or are the FDR from Limma analysis (**c, e, f**). See Supplementary Data 5 and Methods for details.
<figure><img src="image_56.png" /></figure>

**Extended Data Fig. 9** | **Model for the role of vitamin C in DNA methylation reprogramming and development of the embryonic germline.** Embryonic germline cells require vitamin C for proper DNA demethylation of key regulators of meiosis and transposable elements (TEs). Gestational vitamin C deficiency is compatible with development to

term and adulthood, but induces a phenotype akin to a TET1 hypomorph, with incomplete DNA demethylation and downregulation of germline genes, reduced numbers of germ cell, meiosis defects and decreased fecundity. Vitamin C deficiency may also affect other enzymatic reactions in the germline.

E13.5 female germline:

* Aberrant DNA methylation

* Tet1KO-like transcriptome

Long-term consequences:

* Defective meiosis

* Reduced fecundity
<figure><img src="image_56.png" /></figure>

**Extended Data Fig. 9** | **Model for the role of vitamin C in DNA methylation reprogramming and development of the embryonic germline.** Embryonic germline cells require vitamin C for proper DNA demethylation of key regulators of meiosis and transposable elements (TEs). Gestational vitamin C deficiency is compatible with development to

term and adulthood, but induces a phenotype akin to a TET1 hypomorph, with incomplete DNA demethylation and downregulation of germline genes, reduced numbers of germ cell, meiosis defects and decreased fecundity. Vitamin C deficiency may also affect other enzymatic reactions in the germline.

E13.5 female germline:

* Aberrant DNA methylation

* Tet1KO-like transcriptome

Long-term consequences:

* Defective meiosis

* Reduced fecundity
# Reporting Summary

Nature Research wishes to improve the reproducibility of the work that we publish. This form provides structure for consistency and transparency in reporting. For further information on Nature Research policies, see *Authors & Referees* and the *Editorial Policy Checklist*.

## Statistics

For all statistical analyses, confirm that the following items are present in the figure legend, table legend, main text, or Methods section.

n/a | Confirmed

☐ ☑ The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement

☐ ☑ A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly

☐ ☑ The statistical test(s) used AND whether they are one- or two-sided

*Only common tests should be described solely by name; describe more complex techniques in the Methods section.*

☑ ☐ A description of all covariates tested

☐ ☑ A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons

☐ ☑ A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals)

☐ ☑ For null hypothesis testing, the test statistic (e.g. *F*, *t*, *r*) with confidence intervals, effect sizes, degrees of freedom and *P* value noted
*Give *P* values as exact values whenever suitable.*

☑ ☐ For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings

☑ ☐ For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes

☑ ☐ Estimates of effect sizes (e.g. Cohen's *d*, Pearson's *r*), indicating how they were calculated

*Our web collection on *statistics for biologists* contains articles on many of the points above.*

## Software and code

Policy information about *availability of computer code*

**Data collection** Sequencing data collection was done by proprietary Illumina software.

Histolab analysis software (Microvision Instruments, Evry, France) was used for counting meiotic germ cells. Imaris (Oxford Instruments) spot module was used for counting NOBOX objects in whole-mount imaging analysis. TrimGalore, Tophat2, htseq-count, Bioconductor, DESeq2, DAVID, and GSEA programs and code were used in RNAseq analysis. TrimGalore, Bismark, BiSeq, and GREAT programs and code were used in RRBS analysis. Cut&Run-seq analysis is listed under ChIP-seq. GraphPad Prism 7.0 was used to perform statistical tests of qRT-PCR, flow cytometry and imaging data. Multiquant (AB Sciex) was used to integrate chromatogram peak areas of data from mass spectrometry (AB Sciex QTRAP 5500) analysis of vitamin C levels.

For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors/reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research *guidelines for submitting code & software* for further information.

## Data

Policy information about *availability of data*

All manuscripts must include a *data availability statement*. This statement should provide the following information, where applicable:

- Accession codes, unique identifiers, or web links for publicly available datasets

- A list of figures that have associated raw data

- A description of any restrictions on data availability

RNA-seq, Cut&Run and RRBS data have been deposited in Gene Expression Omnibus (GEO) under accession number GSE109747.
# Reporting Summary

Nature Research wishes to improve the reproducibility of the work that we publish. This form provides structure for consistency and transparency in reporting. For further information on Nature Research policies, see *Authors & Referees* and the *Editorial Policy Checklist*.

## Statistics

For all statistical analyses, confirm that the following items are present in the figure legend, table legend, main text, or Methods section.

n/a | Confirmed

☐ ☑ The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement

☐ ☑ A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly

☐ ☑ The statistical test(s) used AND whether they are one- or two-sided

*Only common tests should be described solely by name; describe more complex techniques in the Methods section.*

☑ ☐ A description of all covariates tested

☐ ☑ A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons

☐ ☑ A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals)

☐ ☑ For null hypothesis testing, the test statistic (e.g. *F*, *t*, *r*) with confidence intervals, effect sizes, degrees of freedom and *P* value noted
*Give *P* values as exact values whenever suitable.*

☑ ☐ For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings

☑ ☐ For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes

☑ ☐ Estimates of effect sizes (e.g. Cohen's *d*, Pearson's *r*), indicating how they were calculated

*Our web collection on statistics for biologists contains articles on many of the points above.*

## Software and code

Policy information about [availability of computer code](#)

**Data collection** Sequencing data collection was done by proprietary Illumina software.

Histolab analysis software (Microvision Instruments, Evry, France) was used for counting meiotic germ cells. Imaris (Oxford Instruments) spot module was used for counting NOBOX objects in whole-mount imaging analysis. TrimGalore, Tophat2, htseq-count, Bioconductor, DESeq2, DAVID, and GSEA programs and code were used in RNAseq analysis. TrimGalore, Bismark, BiSeq, and GREAT programs and code were used in RRBS analysis. Cut&Run-seq analysis is listed under ChIP-seq. GraphPad Prism 7.0 was used to perform statistical tests of qRT-PCR, flow cytometry and imaging data. Multiquant (AB Sciex) was used to integrate chromatogram peak areas of data from mass spectrometry (AB Sciex QTRAP 5500) analysis of vitamin C levels.

For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors/reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.

## Data

Policy information about [availability of data](#)

All manuscripts must include a [data availability statement](#). This statement should provide the following information, where applicable:

- Accession codes, unique identifiers, or web links for publicly available datasets

- A list of figures that have associated raw data

- A description of any restrictions on data availability

RNA-seq, Cut&Run and RRBS data have been deposited in Gene Expression Omnibus (GEO) under accession number GSE109747.
# Field-specific reporting

Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

<figure><img src="image_57.png" /></figure>

Life sciences

<figure><img src="image_58.png" /></figure>

Behavioural & social sciences

<figure><img src="image_59.png" /></figure>

Ecological, evolutionary & environmental sciences

For a reference copy of the document with all sections, see [nature.com/documents/nr-reporting-summary-flat.pdf](https://nature.com/documents/nr-reporting-summary-flat.pdf)

# Life sciences study design

All studies must disclose on these points even when the disclosure is negative.

Sample size

No statistical methods were used to predetermine sample size estimate. Samples were collected in numbers estimated from previous studies to allow statistical significance, which was confirmed after data analysis.

Data exclusions

Cut&Run-seq samples siggv2 and sk9v3 were excluded due to failing sequencing, which was pre-established as an exclusion criterion.

Replication

All experiments were replicated a minimum of 3 times and up to 20 times, with the exception of E11.5 PGCs in Ext. Data Fig. 2a and control testis samples in Ext. Data Fig. 4b-d (n=2). All attempts at reproduction were successful, within the level of variation reported in each case.

Randomization

Mice were randomly allocated to Vitamin C-deficient or -containing drinking water.

Blinding

Investigators were not blinded during data collection/analysis because of precedent in

the lab to ensure collection of appropriate numbers of samples from each condition by a single individual.

# Reporting for specific materials, systems and methods

We require information from authors about some types of materials, experimental systems and methods used in many studies. Here, indicate whether each material, system or method listed is relevant to your study. If you are not sure if a list item applies to your research, read the appropriate section before selecting a response.

## Materials & experimental systems

<table><thead><tr><th>n/a</th><th>Involved in the study</th></tr></thead><tbody><tr><td>☐</td><td>Antibodies</td></tr><tr><td>☑</td><td>Eukaryotic cell lines</td></tr><tr><td>☑</td><td>Palaeontology</td></tr><tr><td>☐</td><td>Animals and other organisms</td></tr><tr><td>☑</td><td>Human research participants</td></tr><tr><td>☑</td><td>Clinical data</td></tr></tbody></table>

## Methods

<table><thead><tr><th>n/a</th><th>Involved in the study</th></tr></thead><tbody><tr><td>☐</td><td>ChIP-seq</td></tr><tr><td>☑</td><td>Flow cytometry</td></tr><tr><td>☑</td><td>MRI-based neuroimaging</td></tr></tbody></table>

## Antibodies

Antibodies used

Commercially available antibodies were: DDX4 (Abcam Ab13840 1:200 or Ab27591 1:500), Stra8 (Abcam Ab49602 1:400), Sycp3 (Abcam Ab97672 1:500), Foxl2 (ThermoFisher PA1-802 1:200), AMH (SantaCruz SC-6858 1:200), Sycp1 (Abcam Ab15090 1:400), CREST (Antibodies Incorporated 15-234-0001 1:400) and ki67 (550609 BD pharmingen 1:200). Anti-Nobox (1:100) was a gift from Aleksandar Rajkovic (U. Pittsburgh and UCSF).

Validation

Commercial antibodies were used per their manufacturer's information and instructions. Validation information is provided at the manufacturers' websites from Abcam (abcam.com), Santa Cruz (scbt.com), BD (bdbioscience.com), Antibodies Incorporated (antibodiesinc.com) and ThermoFisher (thermofisher.com/antibodies). Antibodies were tested and validated in-house by observing the expected, tissue- and stage-specific staining pattern, as shown in ED Figs. 2, 3 and 4. Similarly, the non-commercial anti-Nobox antibody was validated by the specific staining of oocytes and not somatic cells in the ovary.

## Animals and other organisms

Policy information about studies involving animals; ARRIVE guidelines recommended for reporting animal research

Laboratory animals

Gulo/- mice were obtained from the UC Davis Mutant Mouse Resource & Research Center (strain B6.129P2-Gulotm1Mae/ Mmucd, RRID:MMRRC_000015-UCD) and bred with Oct4/EGFP mice to establish a homozygous Gulo/-;Oct4/EGFP colony on a C57BL/6 background. Maternal mice were mated at 8-12 weeks of age. Samples were collected from female progeny at various stages of embryo development, postnatal day 7, and 20-25 weeks of age.

Wild animals

This study did not involve wild animals.

Field-collected samples

This study did not involve any samples collected in the field.

Ethics oversight

Experiments were performed in accordance with the guidelines of the UCSF Institutional Animal Care and Use Committee.
# Field-specific reporting

Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

<figure><img src="image_57.png" /></figure>

Life sciences

<figure><img src="image_58.png" /></figure>

Behavioural & social sciences

<figure><img src="image_59.png" /></figure>

Ecological, evolutionary & environmental sciences

For a reference copy of the document with all sections, see [nature.com/documents/nr-reporting-summary-flat.pdf](https://nature.com/documents/nr-reporting-summary-flat.pdf)

# Life sciences study design

All studies must disclose on these points even when the disclosure is negative.

Sample size

No statistical methods were used to predetermine sample size estimate. Samples were collected in numbers estimated from previous studies to allow statistical significance, which was confirmed after data analysis.

Data exclusions

Cut&Run-seq samples siggv2 and sk9v3 were excluded due to failing sequencing, which was pre-established as an exclusion criterion.

Replication

All experiments were replicated a minimum of 3 times and up to 20 times, with the exception of E11.5 PGCs in Ext. Data Fig. 2a and control testis samples in Ext. Data Fig. 4b-d (n=2). All attempts at reproduction were successful, within the level of variation reported in each case.

Randomization

Mice were randomly allocated to Vitamin C-deficient or -containing drinking water.

Blinding

Investigators were not blinded during data collection/analysis because of precedent in

the lab to ensure collection of appropriate numbers of samples from each condition by a single individual.

# Reporting for specific materials, systems and methods

We require information from authors about some types of materials, experimental systems and methods used in many studies. Here, indicate whether each material, system or method listed is relevant to your study. If you are not sure if a list item applies to your research, read the appropriate section before selecting a response.

## Materials & experimental systems

<table><thead><tr><th>n/a</th><th>Involved in the study</th></tr></thead><tbody><tr><td>☐</td><td>Antibodies</td></tr><tr><td>☑</td><td>Eukaryotic cell lines</td></tr><tr><td>☑</td><td>Palaeontology</td></tr><tr><td>☐</td><td>Animals and other organisms</td></tr><tr><td>☑</td><td>Human research participants</td></tr><tr><td>☑</td><td>Clinical data</td></tr></tbody></table>

## Methods

<table><thead><tr><th>n/a</th><th>Involved in the study</th></tr></thead><tbody><tr><td>☐</td><td>ChIP-seq</td></tr><tr><td>☑</td><td>Flow cytometry</td></tr><tr><td>☑</td><td>MRI-based neuroimaging</td></tr></tbody></table>

## Antibodies

Antibodies used

Commercially available antibodies were: DDX4 (Abcam Ab13840 1:200 or Ab27591 1:500), Stra8 (Abcam Ab49602 1:400), Sycp3 (Abcam Ab97672 1:500), Foxl2 (ThermoFisher PA1-802 1:200), AMH (SantaCruz SC-6858 1:200), Sycp1 (Abcam Ab15090 1:400), CREST (Antibodies Incorporated 15-234-0001 1:400) and ki67 (550609 BD pharmingen 1:200). Anti-Nobox (1:100) was a gift from Aleksandar Rajkovic (U. Pittsburgh and UCSF).

Validation

Commercial antibodies were used per their manufacturer's information and instructions. Validation information is provided at the manufacturers' websites from Abcam (abcam.com), Santa Cruz (scbt.com), BD (bdbioscience.com), Antibodies Incorporated (antibodiesinc.com) and ThermoFisher (thermofisher.com/antibodies). Antibodies were tested and validated in-house by observing the expected, tissue- and stage-specific staining pattern, as shown in ED Figs. 2, 3 and 4. Similarly, the non-commercial anti-Nobox antibody was validated by the specific staining of oocytes and not somatic cells in the ovary.

## Animals and other organisms

Policy information about studies involving animals; ARRIVE guidelines recommended for reporting animal research

Laboratory animals

Gulo/- mice were obtained from the UC Davis Mutant Mouse Resource & Research Center (strain B6.129P2-Gulotm1Mae/ Mmucd, RRID:MMRRC_000015-UCD) and bred with Oct4/EGFP mice to establish a homozygous Gulo/-;Oct4/EGFP colony on a C57BL/6 background. Maternal mice were mated at 8-12 weeks of age. Samples were collected from female progeny at various stages of embryo development, postnatal day 7, and 20-25 weeks of age.

Wild animals

This study did not involve wild animals.

Field-collected samples

This study did not involve any samples collected in the field.

Ethics oversight

Experiments were performed in accordance with the guidelines of the UCSF Institutional Animal Care and Use Committee.
# ChIP-seq

## Data deposition

<figure><img src="image_60.png" /></figure>

Confirm that both raw and final processed data have been deposited in a public database such as GEO.

<figure><img src="image_61.png" /></figure>

Confirm that you have deposited or provided access to graph files (e.g. BED files) for the called peaks.

Data access links

May remain private before publication.

NB Cut and Run peaks not called - no files uploaded.

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE109747. Reviewer token uvmnswyaltenxmb

Files in database submission

piggc1-5.fq, piggv1-5.fq, siggc1-3.fq, siggv1,3,4.fq, sk9c1-4.fq, sk9v1,2,4.fq

Genome browser session
(e.g. UCSC)

N/A - browser shots not produced

## Methodology

Replicates

Individual replicates consisted of 2000 PGCs or soma from a single (control) or up to three pooled (-VitC) E13.5 independent embryos taken from at least 3 different litters

Sequencing depth

PE reads of 150bp length, with K9me2-generated unique deduplicated reads of mean 8e6 for soma and 3e6 for PGCs

Antibodies

Samples were resuspended with H3K9me2 (Active motif Cat# 39239) or Rabbit IgG antibodies (Cell Signaling Cat# 2729)

Peak calling parameters

N/A

Data quality

Reads were quality and adapter trimmed by Trim_Galore! (Babraham) according to default recommended parameters, aligned to mm10 or s.cerevisiae, and duplicated reads removed with Picard MarkDuplicates.

Software

trim_galore 0.4.0, Bowtie2 v 2.2.5, picard MarkDuplicates 2.18.14, R version 3.5.1

# Flow Cytometry

## Plots

Confirm that:

<figure><img src="image_62.png" /></figure>

The axis labels state the marker and fluorochrome used (e.g. CD4-FITC).

<figure><img src="image_63.png" /></figure>

The axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of identical markers).

<figure><img src="image_64.png" /></figure>

All plots are contour plots with outliers or pseudocolor plots.

<figure><img src="image_65.png" /></figure>

A numerical value for number of cells or percentage (with statistics) is provided.

## Methodology

Sample preparation

Embryonic gonads were dissected in sterile cold PBS and dissociated via enzymatically digestion in 0.5% Trypsin and 0.8 mg/mL DNAse I (Worthington) at 37°C for 3-5 minutes with manual dissociation by pipetting. Dissociated samples were diluted in FACS buffer (PBS containing 3% FBS and 3mM EDTA) and filtered prior to sorting.

Instrument

Aria II FACS instrument (BD Biosciences)

Software

FlowJo v 9-10 was used to analyze FACS data

Cell population abundance

Embryonic E13.5 PGCs were approximately 8% (female) or 3% (male) of total sorted live gonadal cells in control embryos, as determined by Oct4GFP positive protein expression. Purity was confirmed post-sorting during initial flow cytometry setup. Gene expression analyses (RNA-seq) confirmed PGC or soma-specific gene expression for relevant samples.

Gating strategy

Samples were gated by FSC-A/SSC-A, then FSC-W/FSC-A and SSC-A/SSC-W followed by Sytox Blue/SSC-A to obtain live single cells. PGCs were identified by positive Oct4GFP protein expression (488nm). Embryonic dissociated limb was used to select gates for negative populations.

<figure><img src="image_66.png" /></figure>

Tick this box to confirm that a figure exemplifying the gating strategy is provided in the Supplementary Information.
# ChIP-seq

## Data deposition

<figure><img src="image_60.png" /></figure>

Confirm that both raw and final processed data have been deposited in a public database such as GEO.

<figure><img src="image_61.png" /></figure>

Confirm that you have deposited or provided access to graph files (e.g. BED files) for the called peaks.

Data access links

May remain private before publication.

NB Cut and Run peaks not called - no files uploaded.

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE109747. Reviewer token uvmnswyaltenxmb

Files in database submission

piggc1-5.fq, piggv1-5.fq, siggc1-3.fq, siggv1,3,4.fq, sk9c1-4.fq, sk9v1,2,4.fq

Genome browser session
(e.g. UCSC)

N/A - browser shots not produced

## Methodology

Replicates

Individual replicates consisted of 2000 PGCs or soma from a single (control) or up to three pooled (-VitC) E13.5 independent embryos taken from at least 3 different litters

Sequencing depth

PE reads of 150bp length, with K9me2-generated unique deduplicated reads of mean 8e6 for soma and 3e6 for PGCs

Antibodies

Samples were resuspended with H3K9me2 (Active motif Cat# 39239) or Rabbit IgG antibodies (Cell Signaling Cat# 2729)

Peak calling parameters

N/A

Data quality

Reads were quality and adapter trimmed by Trim_Galore! (Babraham) according to default recommended parameters, aligned to mm10 or s.cerevisiae, and duplicated reads removed with Picard MarkDuplicates.

Software

trim_galore 0.4.0, Bowtie2 v 2.2.5, picard MarkDuplicates 2.18.14, R version 3.5.1

# Flow Cytometry

## Plots

Confirm that:

<figure><img src="image_62.png" /></figure>

The axis labels state the marker and fluorochrome used (e.g. CD4-FITC).

<figure><img src="image_63.png" /></figure>

The axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of identical markers).

<figure><img src="image_64.png" /></figure>

All plots are contour plots with outliers or pseudocolor plots.

<figure><img src="image_65.png" /></figure>

A numerical value for number of cells or percentage (with statistics) is provided.

## Methodology

Sample preparation

Embryonic gonads were dissected in sterile cold PBS and dissociated via enzymatically digestion in 0.5% Trypsin and 0.8 mg/mL DNAse I (Worthington) at 37°C for 3-5 minutes with manual dissociation by pipetting. Dissociated samples were diluted in FACS buffer (PBS containing 3% FBS and 3mM EDTA) and filtered prior to sorting.

Instrument

Aria II FACS instrument (BD Biosciences)

Software

FlowJo v 9-10 was used to analyze FACS data

Cell population abundance

Embryonic E13.5 PGCs were approximately 8% (female) or 3% (male) of total sorted live gonadal cells in control embryos, as determined by Oct4GFP positive protein expression. Purity was confirmed post-sorting during initial flow cytometry setup. Gene expression analyses (RNA-seq) confirmed PGC or soma-specific gene expression for relevant samples.

Gating strategy

Samples were gated by FSC-A/SSC-A, then FSC-W/FSC-A and SSC-A/SSC-W followed by Sytox Blue/SSC-A to obtain live single cells. PGCs were identified by positive Oct4GFP protein expression (488nm). Embryonic dissociated limb was used to select gates for negative populations.

<figure><img src="image_66.png" /></figure>

Tick this box to confirm that a figure exemplifying the gating strategy is provided in the Supplementary Information.