# Temporal and regional X-linked gene reactivation in the mouse germline reveals site-specific retention of epigenetic silencing

Clara Roidor, Laurène Syx, Emmanuelle Beyne, Peggy Raynaud, Dina Zielinski, Aurélie Teissandier, Caroline Lee, Marius Walter, Nicolas Servant,

Karim Chebli, et al.

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► To cite this version:

Clara Roidor, Laurène Syx, Emmanuelle Beyne, Peggy Raynaud, Dina Zielinski, et al. Temporal and regional X-linked gene reactivation in the mouse germline reveals site-specific retention of epigenetic silencing. Nature Structural and Molecular Biology, 2025, 32, pp.926-939. 10.1038/s41594-024-01469-2. hal-04907746

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https://hal.science/hal-04907746v1

Submitted on 25 Jul 2025

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1 **a. Title**

2 Temporal and regional X-linked gene reactivation in the mouse germline reveals site-specific

3 retention of epigenetic silencing.

4 **b. Author list**

5 Clara Roidor ¹*, Laurène Syx ²*, Emmanuelle Beyne ¹, Peggy Raynaud ³, Dina Zielinski ⁴, Aurélie

6 Teissandier ⁴, Caroline Lee ⁵,⁶, Marius Walter ⁴, Nicolas Servant ², Karim Chebli ¹, Déborah Bourc’his ⁴,

7 M. Azim Surani⁵,⁶, Maud Borensztein ¹,⁵±

8 **c. Affiliations**

9 ¹IGMM, University of Montpellier, CNRS, Montpellier, France

10 ²Institut Curie, PSL Research University, INSERM U900, Mines ParisTech, Paris, France

11 ³CRBM, University of Montpellier, CNRS, Montpellier, France

12 ⁴Institut Curie, Paris Sciences et Lettres Research University, INSERM U934, CNRS UMR3215, Paris,

13 France

14 ⁵Wellcome/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, UK.

15 ⁶Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.

16

17 * These authors contributed equally

18 ± Correspondence should be sent to maud.borensztein@igmm.cnrs.fr

19

20 **Keywords:** X-chromosome inactivation, primordial germ cells, reprogramming, scRNA-seq, WGBS,

21 CUT&RUN

22

23 **GEO Reviewer Tokens:**

24 All scRNA-seq and WGBS, and CUT&RUN datasets are deposited in Gene Expression Omnibus under the

25 numbers GSE243943 (token: yxwbuaagnnubzch) and GSE243464 (token: idelsmqstdqrzkt).
26 **d. Abstract**

27

28 Random X-chromosome inactivation is a hallmark of female mammalian somatic cells. This epigenetic
29 mechanism, mediated by the long non-coding RNA Xist, occurs in the early embryo and is stably
30 maintained throughout life, though inactivation is lost during primordial germ cell (PGC) development.
31 Using a combination of single-cell allele-specific RNA sequencing and low-input chromatin profiling on
32 developing mouse PGCs, we provide a detailed map of X-linked gene reactivation. Despite the absence of
33 Xist expression, PGCs still harbour a fully silent X chromosome at embryonic day (E) 9.5. Subsequently,
34 X-linked genes undergo gradual and distinct regional reactivation. At E12.5, a substantial part of the
35 inactive X chromosome resists reactivation, retaining an epigenetic memory of its silencing. Our findings
36 define the orchestration of reactivation of the inactive X chromosome, a key event in female PGC
37 reprogramming with direct implications for reproduction.
38

38

39 **e. Main text**

40

41 **Introduction**

42

43 Difference in sex chromosome content between males and females leads to gene dosage imbalance. This
44 imbalance is compensated in mammals by transcriptional inactivation of one of the two X chromosomes in
45 female somatic cells¹,². This epigenetic mechanism, called X-chromosome inactivation (XCI), represents
46 an important paradigm for chromosome-wide epigenetic regulation. The long non-coding RNA *Xist* plays
47 a crucial role in the initiation of XCI ³⁻⁵. The absence of *Xist* in early female embryos is lethal owing to
48 impaired dosage compensation and extraembryonic tissue development ⁴,⁵. Once expressed, *Xist* coats in
49 *cis* the most accessible regions of the future inactive X chromosome (Xi), in 3D spatial proximity, the *Xist*
50 RNA entry sites, before spreading along the chromosome ⁶⁻⁸. Transposons, particularly LINE-1 elements,
51 have been proposed to facilitate this heterochromatinization process ⁹⁻¹¹. *Xist* then triggers the recruitment
52 of specific factors involved in gene silencing, which in turn induces the removal of active chromatin marks,
53 the earliest event being the erasure of H3K27 acetylation, followed by the recruitment of repressive histone
54 marks, such as H3K27me3, H3K9me2, and H2AK119ub ¹². Finally, DNA methylation is enriched at the
55 promoters of inactivated genes to further lock the silent state of these genes and maintain them over
56 hundreds of cell divisions ¹³. The kinetics of X-linked gene inactivation follow different speeds of silencing
57 in the pre-implantation ⁴ and post-implantation mouse embryos ¹⁴, and during *in vitro* differentiation of
58 mouse embryonic stem cells <sup>15,16</sup>. The inactivation occurs chromosome-wide, with an exception of the
59 pseudo-autosomal regions and the escapee genes (~7% of the genes in mice). Early-inactivated genes may
60 be more likely to lie inside the *Xist* RNA entry sites and close to the X-inactivation centre (Xic) <sup>4</sup> from
61 which *Xist* is transcribed, in gene-rich regions, prebound by Polycomb <sup>12</sup> and close to LINE-1 elements <sup>16</sup>.

62

63 Although XCI has been extensively studied, much less is known about how Xi reactivation occurs and
64 whether it mirrors key XCI events. Reactivation has been observed *in vitro* during female induced
65 pluripotent stem cell derivation (iPSC) <sup>17,18</sup>. During development, Xi reactivation occurs after imprinted
66 XCI in the inner cell mass (ICM) of the blastocyst <sup>19,20</sup> (a rodent-specific event) and after random XCI in
67 PGCs <sup>21,22</sup>.

68 While commitment and homeostasis of somatic lineages are central to survival, establishment of the
69 germline is crucial for functional gamete and species survival. In mice, specification of the germ cell lineage
70 is initiated during embryonic post-implantation development at the onset of gastrulation. Approximately
71 30-40 PGCs become specified and are found at the base of the allantois bud at E7.25 <sup>23,24</sup>. After E8.5, PGCs
72 undergo migration and proliferation and reach the genital ridges between E10 and E11. Throughout this
73 period, germ cell proliferation and colonization continue until PGCs enter meiotic prophase at E13.5 in
74 female embryos, a process that occurs only after birth in males <sup>25</sup>. Establishment of the germline determines
75 the production of oocytes and spermatozoa and therefore their competency to accomplish fertilization and
76 transmit genetic and epigenetic information to the next generation <sup>26</sup>. PGC differentiation is accompanied
77 by repression of the somatic program, expression of germline-specific genes, and extensive genome-wide
78 epigenetic reprogramming, including DNA demethylation, loss of genomic imprints, and redistribution of
79 histone marks <sup>23,27</sup>. Epigenetic reprogramming occurs when PGCs proliferate and migrate to colonize the
80 future gonads. At the time of gonadal sex determination, PGC epigenetic reprogramming displays striking
81 differences between XX females and XY males, with reactivation of the Xi chromosome <sup>21,22,28,29</sup>. This
82 biallelic expression of X-linked genes leads to an imbalance between sex, with the X:autosome ratio
83 exceeding 1 in female PGCs compared to males <sup>30,31</sup>. Excess X-linked genes could promote sexual
84 dimorphism and meiosis progression through the direct or indirect involvement of some X-linked genes in
85 the process of sex-specific gonadal formation and could reinforce the Xi reactivation process itself <sup>32,33</sup>.

86

87 A combination of immunofluorescence, RNA-FISH, and RT-PCR in the germline, has been used to show
88 that early PGCs carry an inactive X chromosome, coated by *Xist*, enriched in H3K27me3<sup>22,28,34</sup>, with silent
89 X-linked genes on the Xi <sup>21</sup>. Reactivation is initiated by the transcriptional extinction of *Xist* RNA (from
90 E7.5, prior to and upon PGC migration), loss of repressive H3K27me3 chromatin marks (from E9.5, during
91 PGC migration and proliferation), and re-expression of inactivated X-linked genes (from E10.5, when
92 PGCs start to colonize the future gonads) ²¹,²²,²⁸,³⁴. *Xist* repression is the earliest known feature of Xi
93 reactivation in PGCs and has been linked to pluripotency factors such as NANOG and PRDM14 in
94 pluripotent mouse embryonic stem cells ³⁵, ICM ²⁰,³⁶ and germline ²⁸.
95 Importantly, a recent study in *in vitro* PGC-like cells demonstrated the significance of proper XCI, followed
96 by Xi reactivation, in ensuring the adequate meiotic potential of female PGCs ³². However, the study
97 suggested that Xi could only be moderately silenced in early PGCs before full reactivation and raised the
98 question of X reactivation in the germline. The events underlying X-linked gene reactivation in the germline
99 remain unclear, particularly at the level of the entire chromosome. The extent of XCI in early *in vivo* PGCs
100 and the subsequent kinetics of gene reactivation are still unknown. To shed light on these issues, we
101 explored the precise kinetics of X-linked gene expression and Xi chromatin changes in developing mouse
102 PGCs. To that aim, we used interspecific mouse crosses and combined gene expression analyses by scRNA-
103 seq, patterns of DNA methylation by whole-genome bisulfite sequencing (WGBS), allele-specific DNA
104 methylation assays, and H3K27me3 histone mark profiling using low-input allele-specific CUT&RUN. By
105 investigating transcriptional changes from E9.5 to E12.5 PGCs, we show that, as described for the ICM of
106 the blastocyst, X-linked genes are sequentially activated but with different dynamics and requirements ²⁰.
107 We provide chromosome-wide cartography of X-chromosome reactivation in the *in vivo* germline and
108 determine that the earliest-inactivated genes are more resistant to reactivation. These late-reactivated genes
109 lie in close proximity to the *Xist* locus, and at a distance from escapee loci, exhibit high H3K27me3
110 enrichment, and, to a certain extent, DNA methylation at their Xi promoters. Therefore, this study
111 contributes important insights into the transcriptional, allelic, and chromatin dynamics of Xi reactivation in
112 germline cells. Our results emphasize the importance of studying epigenetic reprogramming of the inactive
113 X chromosome in the peculiar context of the germline, which is the most relevant for developmental
114 syndromes and human reproductive medicine.
115
116

115

116

117 **Results**

118

119 Transcriptional analysis of PGCs and soma cells by scRNA-seq

120 To address the X-chromosome reactivation kinetics in PGCs, at the chromosome-wide scale, we produced
121 scRNA-seq for female and male PGCs, as well as surrounding female somatic cells, as a control for
122 maintenance of XCI. F1 interspecific embryos were obtained by mating common inbred laboratory strain
123 129S1/SvImJ (129) and inbred *Mus musculus castaneus* (Cast) mice and collected every day between E9.5
and E12.5 (Figure 1A). These subspecies have evolved for more than 3 million years and carry an important number of well-characterized single nucleotide polymorphisms (SNPs) (mean of ~1 SNP/650 bp on the X chromosome between 129 and Cast, Mouse Genomes project) ³⁷,³⁸. To visualize PGCs in our embryos, we utilized a green fluorescent protein (GFP) transgene in a 129 genetic background under the control of the *Oct4* promoter ³⁹. *Pou5f1* gene, also known as *Oct4*, encodes a pluripotency transcription factor present in PGCs but not in surrounding somatic cells. From E9.5 to E10.5, PGCs were collected with the assistance of fluorescent active cell sorting based on GFP expression. From E11.5, soma and PGCs were collected after gonad dissection based on their size and confirmed based on the presence of GFP under a microscope. Each single cell was then manually picked, and polyadenylated mRNA was amplified ⁴⁰. We produced scRNA-seq libraries from 154 samples. Since we were interested in allelic expression, we decided to use a scRNA-seq method allowing high-depth high-throughput sequencing for each single cell ⁴¹ (Source Data 1). In total, we obtained 1 116 million reads, with a median of 5.6 million reads per cell. Only single cells that passed the quality controls (see Methods) were used for downstream analysis (n=122 libraries). We used principal component analysis (PCA) to cluster single cells (Figure 1B). The cells are first associated based on their lineage, followed by their embryonic stage. Next, we performed a correlation analysis based on the expression status of pluripotency, soma, and Y-linked genes (Figures 1C and D; genes listed in Figure 1D). We classified the cells according to their developmental stage and pluripotency/soma factor status. This clearly supports a strong repression of the somatic program in PGCs and confirms the expression of well-known factors in PGCs, such as STELLA, BLIMP1, OCT4, NANOG, and DAZL ²³,⁴². The PCA clustering provides a clear separation between PGC and somatic lineages. We investigated the identity of the factors driving this segregation. The weight of these factors in segregating the soma and PGC lineages is shown in Extended Data Fig. 1A. The length of the arrows is proportional to the implication of the factor in PCA association. Markers of soma point towards somatic cells and germline towards PGCs. While some well-known factors, such as OCT4, TFAP2C, STELLA, ESRRB and DND1 ²³,⁴³,⁴⁴, are found to push towards PGC fate, other less studied genes in the context of PGCs were also identified, such as *Esrp1* (*Epithelial Splicing Regulatory Protein*), known to be crucial for oocyte meiosis ⁴⁵.

We then studied the sex of our single-cell samples to focus on sex specificities, X-chromosome reactivation, and transcriptional changes during female PGC development. After clustering PGC and soma cells based on the expression of well-known markers and confirmation by clustering analysis, we sexed all single cells based on the expression of *Xist* (in XX females) and Y-linked genes (in XY male) (Figures 1C and D). Each single cell was attributed a lineage and a sex (Figure 2A, Supplementary Data 1). Sex was also confirmed by the absence of SNPs from the X chromosomes in XY cells. By serendipity, an XO female embryo was found at E12.5 and was used in the analysis (n= 3 PGCs and 1 soma cell sequenced from the
same embryo). We first studied the differentially expressed genes (DEGs) in migratory and colonizing female PGCs by comparing E9.5 versus E10.5, E11.5 versus E10.5 and E12.5 versus E11.5 **(Extended Data Fig. 1B, 1C and 1D)**. Strikingly, very few DEGs are found in migratory PGCs (E10.5 versus E9.5). This is in accordance with a previously published large scRNA-seq dataset of mouse male and female PGCs <sup>42</sup>. From E11.5, there is a strong increase in DEG in female PGCs, with the expected upregulation of PGC genes such as *Dazl* and *Stella/Dppa3*. In accordance with previous reports, there is significant gene repression and upregulation at E12.5 compared to E11.5 <sup>29,42</sup>. Most DEGs from the X-chromosome are upregulated, which is consistent with X-chromosome reactivation occurring in female PGCs (111 upregulated genes on 148 DEG from the X, **Extended Data Fig. 1D**). They show a statistically greater enrichment in upregulated genes at E12.5 compared to E11.5, owing to X reactivation.

Furthermore, when soma cells and PGCs strongly cluster on PCA by lineage and then more modestly by developmental stage (1st axis, **Figure 1B**), they do not cluster by sex until E12.5. Very similar transcriptomes in early XX and XY PGCs were reported previously <sup>42</sup>. We confirm that the clustering by sex only occurs from E12.5 for XX, XY and XO PGCs.

172

## X-reactivation initiates progressively upon PGC development

To study X-chromosome reactivation, we analysed scRNA-seq in an allele-specific manner to determine the parental origin of the transcripts. SNPs from F1 hybrid embryos were used to map informative reads to either the 129 or Cast genomes (see Methods). Each gene with informative SNPs and expressed more than 4 reads per retro-transcribed length per million mapped reads (RPRT) was provided with an allelic expression ratio (reads from Cast divided by total informative reads). The parental origin of Xi was then determined in each single cell based on the allelic ratio of all informative X-linked genes and the Xa allelic ratio calculated as reads mapped on active X (Xa) divided by total reads in the following analysis (**Supplementary Data 1**, see Methods). On the 91 female scRNA-seq, 59 cells carry an active X chromosome of Cast origin (65%), and 32 cells of 129 origin (35%). Despite the random choice of Xi, we observe strongly skewed silencing towards the 129 chromosome. This confirms the X-chromosome controlling element (Xce) effect in F1 hybrid female mice. Indeed, it has been well documented that an F1 hybrid background could lead to skewed XCI depending on their Xce strength (Xce<sup>a</sup>Xce<sup>b</sup>Xce<sup>c</sup>Xce<sup>d</sup>Xce<sup>e</sup>, with the strongest Xce allele being the most resistant to silencing) <sup>46</sup>. Using 129 and Cast strains associated with Xce<sup>a</sup> and Xce<sup>c</sup> respectively, we confirm that the 129 chromosome is preferentially chosen to be silent in the expected proportions <sup>47</sup>.

189
We then studied allelic expression of autosomal and X-linked genes during PGC development (Figure 2B). Autosomal genes are biallelically expressed (0.15< allelic ratio <0.85), with parity between 129 and Cast reads, in both males and females E9.5-E12.5 PGCs and in somatic gonadal cells used as controls. On the other hand, X-linked genes are strictly expressed from the Xa (allelic ratio ≥ 0.85) in E9.5 female PGCs, except for a few genes, known as escapees (see Supplementary Data 2 for their identity). The distribution of the X-linked gene allelic ratios is very similar in female and male PGCs, highlighting complete XCI in E9.5 PGCs. From E10.5, X-chromosome reactivation is initiated in female PGCs (ratio<0.85) and progresses during PGC development.

Because PGCs could be heterogeneous in terms of developmental timing, even inside the same embryo, we decided to order the female PGCs by pseudotime ordering (Figure 2C). We used the 1st principal component of our PCA (Figure 2A) to order female PGCs by pseudotime ordering. Despite some lagging cells, mainly at E11.5 and E12.5, most of the cells at the same developmental stage cluster together, without a clear distinction of sex (Figure 2C and Extended Data Fig. 2A). We then studied the percentage of reactivated X-linked genes in each female PGC (Figure 2D). Lagging cells at E11.5 and E12.5 on the pseudotime axis are also delayed in terms of percentage of X-linked gene reactivation compared to more developmentally advanced PGCs, collected at the same stage. We show that Xi reactivation is progressive from fully inactivated E9.5 PGCs to highly reactivated E12.5 PGCs, and strongly correlates with PGC development (r=0.76).

Since the loss of Xist enrichment on Xi is the earliest known event during reactivation in the germline (based on IF/RNA-FISH) 21,30, Xist expression levels were extracted from our scRNA-seq data (Extended Data Fig. 2B). We confirm that Xist is not expressed in most PGCs compared to female somatic cells, which retain Xist expression and inactivate the X chromosome. In migratory E9.5 female PGCs, X-chromosome reactivation has been initiated, although X-linked genes subject to XCI are still silenced.

Finally, to explore which pathways could drive Xi reactivation in the germline, we studied the correlation between genome-wide gene expression and the percentage of reactivated genes (allelic ratio < 0.85) per female single cell (PGC and soma) (Supplementary Data 3). We show that X-chromosome reactivation occurs concomitantly with PGC development. In accordance, we find that the best correlated genes are markers of late PGCs, including *Dazl* (ranked 1st, r=0.78, adj.pval < 10⁻¹⁴), a well-known late germ cell marker, and *Ddx4/Vasa*, ranked 4th (r=0.73, adj.pval < 10⁻¹¹) 23. It is not surprising to find well-known markers of late PGCs as X-chromosome reactivation highly correlates with PGC developmental progression. Gene ontology analysis of the top correlated genes (p < 0.001) reveals that factors involved in
histone modification, DNA methylation, RNA and DNA metabolism, and meiosis are overrepresented (Extended Data Fig. 3A). This suggests that they may play a role in both PGC and Xi reprogramming.

224

225 **Different genes reactivate at different rates along the Xi**

Next, we investigated the kinetics of X-linked gene reactivation along the entire X chromosome. Heatmaps of X-linked gene activity were generated for E9.5 to E12.5 female PGCs (Figure 3 and Supplementary Data 2). We focused on genes expressed at more than 4 RPRT to avoid confounding effects due to PCR bias and molecular loss in the scRNA-seq method, which would negatively impact SNP analysis. This expression cut-off to access allelic information from scRNA-seq has already been validated in our previous studies 4,20,40. Thus, polymorphic genes expressed at RPRT > 4 in at least 3 developmental stages are included in the heatmap and ordered by genomic position (Figure 3). E9.5 PGCs display 89% (157 out of 176) of monoallelically-expressed genes from the active X (allelic ratio ≥ 0.85) and 11% of biallelically expressed genes (0.15 < allelic ratio < 0.85), 9 of which are known escapees, i.e. *Kdm6a*, *Kdm5c*, *Ddx3x*, *Eif2s3x*, *Utp14a*, *1810030007Rik*, *Fundc1*, *Cdk16*, and *Pqbp1* (Supplementary Data 2) 48. Interestingly, the proportion of biallelically expressed genes greatly increases during the development of female PGCs, reaching 70% (132 out of 188) at E12.5. This indicates strong reactivation of X-linked genes during PGC development. However, a surprisingly large portion of the X-linked genes remains inactivated at E12.5.

We then classified the genes into different groups with respect to the timing of reactivation (Figure 4A and Method, Figure 3 right). At E9.5, all genes are silenced, except for the escapee class (n = 11 out of 197 genes). Early genes (n = 33 out of 197) are reactivated from E10.5, intermediate genes (n = 53 out of 197 genes) from E11.5, and late genes (28 out of 197) from E12.5. At E12.5, 59 out of 197 genes are still silenced (monoallelically expressed from the Xa) and belong to the very late-reactivated class. We termed these silent genes very late-reactivated, as we expect their reactivation after E12.5, based on a recent preprint 49. The reactivation speed of few X-linked genes was previously tested by single cell RT-PCR digested by restriction enzymes in F1 hybrid *Mus musculus molossinus x Mus musculus domesticus*. PGCs 21. We compared these previously published results to our reactivation classes and found excellent correlation, corroborating the validity of our analysis (Extended Data Fig. 3B).

We then questioned whether the level of expression of X-linked genes could influence their reactivation kinetics. Just prior (E9.5) or at the time of (E10.5) early reactivation, no difference in global expression levels is observed (Figure 4B). At E11.5, early and escapee genes tend to be more highly expressed, compared to still-silent genes (p < 0.01 by Kruskal-Wallis (KW) test). This could be explained by the fact that the Xi allele is also transcribed for early reactivated and escapee genes, compared to the other classes of genes. Consistently, at E12.5, very late reactivated genes tend to be less expressed than those in the other
classes ($p$ = 0.01, KW test). When plotting the mean allelic expression of Xa and Xi in each reactivation classes, it is striking to observe that the expression is indeed only coming from the Xa for inactivated genes, and that expression from the Xa is only progressively acquired as a class of genes is reactivated (pink dots: Xa, yellow dots: Xi, **Figure 4B** at E12.5). Furthermore, the mean allelic expression of the female Xa compared to the male Xa (blue dots) is very similar at E9.5, due to the combined presence of XCI and X-chromosome upregulation. Escapees are also more highly expressed from the Xa, as expected from previous work in mice<sup>48,50</sup>. However, focusing on early-reactivated genes, we observe that the female Xa tends to be less expressed than the male Xa as the genes become reactivated. This could suggest that upregulation from the Xa may be lost as the Xi begins to be transcribed, depending on the XCI status of the gene. Another argument that does not support the idea of an excess of expression of early-reactivated genes specifically in females is the absence of overrepresentation of early genes in the differentially expressed genes (DEG) between XX versus XY E12.5 PGCs (5/232 DEGs, adj.<i>p</i>-value < 0.05, **Supplementary Data 4**) and XX versus XO E12.5 PGCs (2/17 DEGs, <i>p</i>-value < 0.05, **Supplementary Data 4**), however the important question of X-chromosome upregulation in PGCs merits further investigation.

269

## Consistency of X-linked gene reactivation kinetics

Then, we aimed to test the consistency of the reactivation kinetics of X-linked genes in different developmental contexts (ICM vs. PGCs). We compared the classes of reactivation that include common X-linked genes during imprinted Xi reactivation in ICM and random Xi reactivation in PGCs (**Figure 4D**) <sup>20</sup>. 50% of the genes belong to the same reactivation class between ICM and PGCs (non-significant by Fisher's Exact test, <i>p</i>-value = 0.0885, n = 57 genes). However clear similarities are found with the first reactivated genes. Indeed, 90% of the early-reactivated genes in PGCs are early or intermediate in ICM (63% and 27% respectively). We then compared the reactivation classes in PGCs to a recent study on PGC-like cells (PGCLC) (**Extended Data Fig. 3D**) <sup>32</sup>. The *in vitro* PGCLC model recapitulates PGC specification, including Xi reactivation in female cells and entry into meiosis. Most of our genes are ranked as early-reactivated genes *in vitro*, showing no consistency by Fisher's exact test (non-significant <i>p</i>-value =0.3). This could be due to the more advanced developmental stage of the PGCLC and / or partial inactivation of these genes *in vitro*. Overall, these results show that, despite differences in the different cellular contexts, genes more prone to be early reactivated seem to be conserved in ICM and PGC.

284

## Early-inactivated genes, close to Xist, resist reactivation

A closer examination of the reactivation heatmap, ordered by genomic position, shows several regions of early-reactivation along the entire X chromosome. Because close genomic proximity to escapees could
favour an early reactivation in mouse iPSCs<sup>18,51</sup>, we tested the distance of our different reactivation class genes to their closest escapee (<strong>Extended Data Fig. 3C</strong>). In our *in vivo* female PGCs, there is also a tendency for first and last-reactivated genes to localise the closest and furthest respectively from escapees. We indeed find that early-reactivated genes lie in close proximity to escapees compared to very late-reactivated genes (*p*-value = 0.02 by Mann-Whitney, MW). We then tested whether distance to the *Xist* locus could be a significant parameter for reactivation kinetics (<strong>Figure 4C</strong>). Pioneering work in the field of X-chromosome reactivation in PGCs had suggested a relationship between the reactivation kinetics and distance to *Xist* locus, with reactivation starting from the centromeres and moving towards the *Xist* locus<sup>21,22</sup>. We find a strong bias for very late-reactivated genes to be localised closer to the *Xist* genomic locus compared to intermediate (*p* =0.0058, KW test) and early (*p* = 0.0051, KW test) reactivated genes. Escapees are also found further from the *Xist* locus compared to very late-reactivated genes (*p* = 0.0039, KW test). We conclude that there is a strong correlation between close proximity to the *Xist* locus and longer germline silencing<sup>21</sup>.

We then wondered if the X-chromosome reactivation event could mirror the XCI. We tested this hypothesis by studying the correlation between XCI and X-chromosome reactivation, and comparing the kinetics of reactivation in PGCs to inactivation in differentiating mouse embryonic stem cells (*p*-value = 0.0236 by Fisher's Exact test, **Figure 4E**) <sup>15</sup>. We find that the early-inactivated genes mostly belong to the very late reactivation class in PGCs (correlation r = 0.78, *p* = 0.001 by hypergeometrical test). Indeed, being an early-inactivated gene can influence the speed of reactivation a few days later. On the other hand, late inactivation does not impact the speed of reactivation: late-inactivated genes are represented in all classes of reactivation without preference (**Figure 4E**).

Because the genes that resisted reactivation at E12.5 are closer to the *Xist* locus (**Figure 4C**) and could be the first silenced genes during random XCI (**Figure 4E**), this prompted us to question the relationship between X-linked gene reactivation and the 3D accessibility of the future Xi, by studying the Xist RNA entry sites. Xist RNA entry sites are genomic regions of the chromosome that are the first to be bound by Xist RNA upon initiation of XCI<sup>6,8</sup>. It is believed that Xist exploits the 3D conformation of the chromosome to first bind the regions in 3D spatial proximity to its transcription site and then initiate silencing before spreading across the entire chromosome<sup>8,52</sup>. Furthermore, we have previously shown that the genes lying inside these 3D accessible regions were more prone to early silencing *in vivo*<sup>4</sup>. Although there is a tendency for genes with transcription start site (TSS) located within the predicted Xist RNA entry sites to show more resistance to early reactivation at E10.5, this observation is not statistically significant, likely due to the low number of informative genes within Xist RNA entry sites (**Extended Data Fig. 3E**). Genes outside the *Xist* RNA entry sites show the earliest reactivation and strongest allelic expression from Xi until E11.5. We hypothesize that the genes within the Xist RNA entry sites may correspond to genes that are more resistant
322 to reactivation, carrying a stronger epigenetic memory of their silencing *in vivo*. However only a very
323 limited number of genes were both mapped to Xist RNA entry sites and categorised in a reactivation class,
324 which makes it difficult to confidently draw a conclusion.

325

326 Chromatin repressive marks may explain resistance to reactivation

327 Very late-reactivated genes appear to correlate with the first inactivated regions of Xi. Because repeated
328 sequences of the genome, mainly LINE-1 elements, have been proposed to help with silencing propagation
329 and facultative heterochromatinisation of Xi, we tested the enrichment of transposons inside and outside
330 Xist RNA entry sites (Figure 5A)⁹,¹¹. We confirm that the X chromosome is highly enriched in LINE-1s
331 compared to control autosomal regions. However, we do not observe any significant enrichment of repeats
332 inside Xist RNA entry sites compared with the rest of the X chromosome, except for a slight enrichment of
333 short interspersed nuclear elements (SINEs), as expected from previous work⁶,⁵³.

334

335 Different chromatin environments could explain the differential kinetics of reactivation of X-linked genes
336 in the PGCs, as previously demonstrated in the ICM of blastocysts²⁰. Both repressive histone marks, such
337 as H3K27me3, and DNA methylation, are enriched on the Xi chromosome upon random XCI ¹⁴. We studied
338 DNA methylation by WGBS in female E6.5 epiblasts, when XCI takes place, and in publicly available
339 datasets of female E10.5 ⁵⁴ and E12.5 ⁵⁵ PGCs (Figure 5B). WGBS shows that very late reactivated genes
340 display a small enrichment in DNA methylation at their TSS compared to early-reactivated genes at E6.5
341 (*p*-value < 0.001, by t-test). At E10.5, DNA methylation erasure is nearly complete for TSS, as expected,
342 with TSS being known to undergo faster DNA reprogramming than the rest of the genome in PGCs. Yet,
343 very-late reactivated genes still display a small enrichment in DNA methylation at their promoters
344 compared to early-reactivation genes (*p*-value = 0.0134, by t-test). At 12.5, all differences are lost (Figure
345 5B).

346 Because XCI is random, our populations of PGCs were heterogeneous in terms of the parental origin of Xi
347 (i.e., 50% of the cells silence the paternal X chromosome and 50% the maternal chromosome), and our cell
348 population-based assays on mosaic female embryos are not informative for distinguishing between Xa and
349 Xi. Here, we consider that the enrichment of DNA methylation at X-linked gene promoters has a higher
350 probability of coming from Xi rather than Xa as TSS are generally hypomethylated in autosomes and Xa,
351 in contrast to hypermethylated TSS on Xi⁵⁶. However, we decided to directly assess the parental origin of
352 DNA methylation observed in 3 X-linked genes. First, to overcome the mosaicism in the PGC population
353 and distinguish between Xa and Xi, we used triple transgenic female mice (*Xist flox/flox*: Zp3-Cre;
354 Oct4(*ΔPE*)eGFP, on a C57Bl6/J genetic background) crossed with Cast males (Figure 5C). This allows us
to collect F1 polymorphic female embryos and sort pure PGC populations based on GFP (under the promoter control of the pluripotency factor OCT4) with non-random XCI. The *Xist* deletion occurs in the maternal germline and allows the transmission of a *Xist*<sup>KO</sup> B6 allele, which cannot be inactivated; Xi is then always the Cast allele. Thus, we collected genomic DNA from female PGCs with a non-random paternal Xi and digested it with methylation-sensitive HpaII enzyme, followed by PCR amplification and Sanger sequencing of the promoter region of 3 X-linked genes and an imprinted control region, *H19*-ICR, as a control (**Figure 5D**). We chose our candidate genes based on their DNA methylation level in WGBS (**Figure 5B**), the presence of SNPs (B6/Cast) close to the promoter region, and the combined presence of HpaII digestion site and absence of EcoRI digestion site in the PCR amplicon. We tested our allele-specific DNA methylation assays on the *H19/Igf2* Imprinted Control Region (ICR), which is paternally methylated in somatic cells and E10.5 PGCs, before being erased <sup>57</sup>. We show that the DNA methylation is only detectable from the paternal allele (**Figure 5E** and **Supplementary Figure 1**). We then tested one early-reactivated gene (*Rps4x*) and two very-late reactivated genes (*Mtmr1* and *Xlr3a*) in E10.5 female PGCs, digested by HpaII (**Figure 5F**). We provide evidence that DNA methylation at the promoters of these 3 candidate genes is exclusively coming from the Xi, even when a very low level of DNA methylation is detectable for the early-reactivated gene by WGBS (**Figure 5B**). Very late reactivated genes are initially more enriched in DNA methylation than early-reactivated genes on the Xi; however, it is not clear why these late-reactivated genes still resist reactivation at E12.5, when DNA demethylation is complete.

Thus, we decided to study another repressive mark, the histone mark H3K27me3, which is enriched on the inactive X chromosome and confers resistance to the early reactivation for X-linked genes in the ICM <sup>20</sup>. To study X-chromosome reactivation at the population level, we took advantage of our F1 transgenic female embryos (**Figure 5C**) to collect PGCs with non-random XCI and allelic information. Low-input allele-specific CUT&RUN against H3K27me3 marks was performed on sorted GFP+ female PGCs at E11.5 and E12.5. Statistically enriched broad domains of H3K27me3 are identified by MACS2 compared to IgG conditions, with 2 replicates per developmental stage (**Figure 6A**, see Methods). When tested for Pearson correlation, replicates are highly similar genome-wide and for active and inactive X chromosomes. We then merged biological replicates per developmental stage to call broad domains of H3K27me3 and determine the allelic origin of the domain (d-score: Cast counts/total counts) (**Figure 6A**). Well-known H3K27me3 repressed loci in PGCs, *HoxC*, and *Sox9*, are also highly enriched in H3K27me3 marks in our CUT&RUN, with signals coming equally from both alleles (each replicate is provided in **Extended Data Fig. 4**). This confirms the quality of our low-input and allele-specific CUT&RUN.
387 Screenshots of the entire X chromosomes are then provided (Figure 6B). We observe fewer global
388 H3K27me3 marks on the Xa compared to Xi as expected by XCI. However, some mirroring of the Xi seems
389 to exist on the Xa and could be due to genes silenced on both X chromosomes, independently of XCI. We
390 then decided to include this new class of genes in our follow-up analysis. The silent genes class includes
391 consistently silent genes on both Xa and Xi in PGCs, based on our scRNA-seq data (n = 344 genes).

392 We then wondered if H3K27me3 enrichment could be different between our different classes of genes.
393 Tracks showing global and allele-specific H3K27me3 counts for representatives of each reactivation class
394 and silent genes were provided (Figure 6C, Extended Data Fig. 5 and 6). *Kdm5c* (escapee), and *Smc1a*,
395 *Med14* and *Kif4* (early genes) are fully depleted of H3K27me3 from both Xi and Xa, in accordance with
396 their biallelic expression. The early-reactivated gene, *Nono*, presents a slight enrichment in H3K27me3,
397 which could be explained by its allelic ratio being very close to the cut-off (E9.5 = 1; E10.5 = 0.84; E11.5
398 = 0.83 and E12.5 = 0.61). Yet, it is clear that *Nono*'s enrichment in repressive marks is lower than its
399 neighbouring genes: the very-late reactivated *Zmym3*, strongly enriched from the Xi exclusively, and the
400 silent gene *Gjb1*, strongly enriched from both X chromosomes (Figure 6C and with each replicate shown
401 in Extended Data Fig. 6A). *Cacna1f*, another example of a silent gene, is even more striking, with strong
402 enrichment of H3K27me3 coming equally from both X chromosomes (Extended Data Fig. 6D). When
403 measuring the signal from the Xi compared to Xa for silent genes, we find that 51% of the signal at E11.5
404 and 66% at E12.5 originates from the Xi, confirming the biallelic origin of H3K27me3 domains. However,
405 it is important to note that most silent genes do not appear to be primarily silenced by H3K27me3, as only
406 30-40% of the 344 silent genes show H3K27me3 domains (Figure 6D). Additionally, no significant
407 H3K27me3 enrichment is observed compared to early-reactivated genes for those that are enriched (Figure
408 6E). This suggests that other repressive marks are responsible for maintaining the silenced state of these
409 genes, independently of XCI, during PGC development.

410 Next, we quantified the allelic origin of H3K27me3 domains for late and very late reactivated genes. We
411 provide data for both Xa and Xi at E11.5 and E12.5 (Figure 6E) and a direct comparison between Xa and
412 Xi (Figure 6F). Surprisingly, a slight enrichment of H3K27me3 is observed on the Xa. However, the
413 majority of the signal originates from the inactive X chromosome (Figure 6F, p < 0.001 by Wilcoxon
414 matched-pairs signed rank test, with 84% and 89% of the H3K27me3 signal coming from Xi at E11.5 and
415 E12.5 respectively in very late genes). Very-late reactivated genes, which are still inactivated at E12.5,
416 present the strongest score of H3K27me3 enrichment on the Xi compared to other reactivation classes
417 (Figure 6E). In accordance with the transcriptional repression of H3K27me3 mostly observed when the
418 mark is located at the promoters, we observe a higher percentage of promoters enriched in H3K27me3 in
419 late and very late reactivated classes (Figure 6D). Furthermore, a higher number of genes exhibit an
420 H3K27me3 domain at E12.5 compared to E11.5, which could be seen as counterintuitive given the ongoing
421 X-chromosome reactivation. One hypothesis is that the increased number of genes coated by H3K27me3
422 at E12.5 could be attributed to genome-wide enrichment of H3K27me3 occurring simultaneously in male
423 and female PGCs<sup>24</sup>.

424 To have a more global view of the X chromosome, we generated the heatmaps of H3K27me3 count +/- 3kb
425 of the TSS in E11.5 and E12.5 female PGCs (Extended Data Fig. 7A). We then clustered the datasets into
426 5 classes based on the global H3K27me3 enrichment at E11.5 (k-mean 5). While H3K27me3 score for TSS
427 in clusters 1 and 2 is equivalent between both Xa and Xi, H3K27me3 score at TSS in clusters 3-4-5 is
428 always stronger from the Xi than the Xa (Top Extended Data Fig. 7A) at both E11.5 and E12.5. Only
429 some silent genes belong to clusters 1 and 2, while all escapees and most of early reactivated genes lie in
430 cluster 5. Late and Very Late genes are found in clusters 3, 4 and 5 (Extended Data Fig. 7B). Early-
431 reactivated genes resemble escapees in terms of chromatin environment, which could explain their
432 promptness to reactivate. On the other hand, last reactivated genes could carry an epigenetic memory of
433 their silencing, with H3K27me3, and better resist reactivation upon PGC development.
434

434

435 Discussion

436

437 In this study, we performed an allele-specific single-cell transcriptomic analysis of migratory and
438 colonizing female PGCs, combined with low-input epigenomics. We demonstrated that early female PGCs
439 carry a nearly fully inactive X chromosome (89%), which progressively reactivates during PGC
440 development, reaching 70% reactivation by E12.5. Our study provides a detailed *in vivo* map of X-
441 chromosome activities throughout this process. We show that the kinetics of gene reactivation varies across
442 the chromosome, with early and very late reactivated genes. Our data supports that spatial proximity to the
443 *Xist* locus, distance from escapees, being early-inactivated during XCI, and enriched in H3K27me3
444 chromatin marks and initially enriched in DNA methylation at promoters are important factors in the
445 dynamic process of X-chromosome reactivation in female PGCs.

446 Our scRNA-seq dataset, spanning PGC development from E9.5 to E12.5, confirmed minimal
447 transcriptional changes during PGC migration, and a significant increase in differentially expressed genes
448 (DEGs) in gonadal PGCs <sup>42</sup>. We identify well-known germline and somatic genes, that influence the
449 clustering of PGC versus somatic lineages. Transcriptomic differences between XX and XY PGCs only
450 emerge from E11.5, in our dataset, consistent with previous report <sup>42</sup>.

451 Over the past 40 years, several studies of female PGCs have begun to uncover the dynamics of X
452 chromosome in the germline. The presence of an inactivated X chromosome in early PGCs was first
453 demonstrated by studying a single X-linked gene, which dated the reactivation to the entrance of meiosis
58. It was later challenged by studies showing an earlier onset of reactivation through transgene activity on the X chromosome 59, by visualisation of Xist RNA cloud, loss of H3K27me3 enrichment on the Xi 22, and the reactivation kinetics of eight genes using single-cell RT-PCR 21, which revealed highly variable profiles. Until now, a clear mapping of X-linked gene behaviour during X-chromosome reactivation in PGCs remained unknown. Taking advantage of our allele-specific scRNA-seq, we show that E9.5 PGCs carry a mostly inactive X chromosome, with the exception of known escapees. The Xi then undergoes progressive reactivation as the cells differentiate, highlighted by the strong correlation between developmental progression and the degree of reactivation (r=0.76). This finding corroborates previous work, with the importance of reprogramming for X-reactivation in iPSCs 18,60. We then classified each informative X-linked gene (n = 197 genes) based on its reactivation speed. We found that 70 % of the studied X-linked genes were reactivated by E12.5, showing a surprisingly high percentage of genes that remained inactivated just before the onset of female meiosis. This observation was corroborated by a recent preprint, which reported a similar degree of reactivation in E12.5 PGCs (61%, 172/281) from non-random female embryos 49. Interestingly, it is only at E16.5 that Xi reactivation appears nearly complete (~90%, 250/281 genes). While this late reactivation was known for few examples 21,61, the extent observed in our study was unexpected. Our work highlights the strong resistance to reactivation of very late-reactivated genes, which lasts up to 7 days following the loss of Xist RNA coating 21.

A progressive reactivation of X-linked genes occurs not only in female PGCs but also in *in vitro* models, such as iPSCs and PGCLCs (days) and *in vivo* in the ICM (hours) 18,20,32,49. Notably, genes that reactivate early in PGCs are often associated with facultative escape in somatic tissues (25/33 genes, **Supplementary Data 2**) 48. This observation suggests that these genes may share a similar chromatin environment, with early reactivated genes located far from the *Xist* locus, and closer to regions of active escape in PGCs, as previously proposed for *in vitro* reactivation 18,51.

Some of those escapees and early-reactivated genes may directly influence the reactivation mechanism or the female gametogenesis, potentially contributing to sexual dimorphism. The X chromosome contains several genes important for germline function and transcriptional regulation. For instance, *Fmr1* and *Zfx* are important for oogenesis and are early-reactivated in PGCs. Histone demethylases KDM6A and KDM5C (escapees), along with the mediator complex co-factor MED14 (early-reactivated) may play roles in X-linked gene reactivation. The *Med14* gene is also prone to early reactivation in mouse iPSCs 18 and human breast cancer cells depleted of XIST 62. Similarly, the *Smc1a* gene, also an early-reactivated gene, has recently been involved in the remodelling and reactivation of Xi in mouse iPSCs 63. Notably, we have previously shown that *Kdm6a* is implicated in the proper reactivation of some late-reactivated genes on the imprinted Xi in the mouse ICM 20. This raises questions about whether these biallelically expressed genes have a functional impact on the female germline. However, it is well known that XO female mice are viable
and fertile without obvious phenotypes, in contrast to Turner syndrome (45, XO) patients, a syndrome often associated with high prenatal mortality, infertility, hypogonadism and anatomical defects <sup>64</sup>. In the mice germline, two active X chromosomes are not strictly required for female gametogenesis, although some reports suggest subfertility in these aneuploid female mice <sup>33,65</sup>.

As discussed, X-chromosome reactivation occurs during the reprogramming of female PGCs, potentially leading to an excess of X-linked gene products in female PGCs compared to males <sup>30,31</sup>. In mice, this female-specific excess of X-linked genes has been shown to occur transiently at the onset of sex-specific gonadal differentiation (E9.5-E15.5). From our datasets, the expression level from the Xa seemed to decrease as the Xi was getting reactivated, suggesting a close relationship between X-chromosome inactivation and X-chromosome upregulation. However, the extent and timing of X-upregulation remain debated in the germline. Further studies combining allele-specific scRNA-seq and chromatin accessibility, as suggested by recent work on upregulation, would be important to elucidate the dynamics of X-chromosome upregulation during X-reactivation *in vivo* <sup>31,66</sup>.

Understanding the resistance to early reactivation and its underlying mechanisms is essential for elucidating how epigenetic reprogramming occurs both on the X chromosome and at the genome-wide level. Here, we demonstrated the significant role of genomic location, with genes located near *Xist* locus and Xist RNA entry sites being the last to undergo reactivation. We proposed that these genes could be the first targets of *Xist*, and exhibit repressive chromatin marks, suggesting an epigenetic basis for their silencing, which needs to be erased prior to reactivation. Supporting this hypothesis, genes that are inactivated early in random XCI process (differentiated mouse embryonic stem cells) display strong resistance to reactivation. This resistance is likely dependent on chromatin marks rather than *Xist* itself, as *Xist* coating is lost early from the Xi. By examining DNA methylation at promoters of late and very late reactivated genes, we found that these genes acquire slightly more methylation during XCI process compared to early-reactivate genes (at E6.5), and this little difference persists in E10.5 PGCs despite the global hypomethylation already occurring at TSS. However, by E12.5, all X-linked TSS are fully hypomethylated, yet only the very-late reactivated genes remain silenced.

Other repressive marks play an important role during the XCI process, such as H3K27me3, which is already known to be preferentially enriched at late reactivated genes in the ICM <sup>20</sup>. Our analysis of H3K27me3 repressive marks confirmed that these marks are indeed preferentially found on late and very late genes compared to early-reactivated genes. In absence of DNA methylation, H3K27me3 could serve as the primary repressive mark in PGCs, especially since H3K9 methylation is lost during PGC reprogramming while H3K27 methylation is gained genome-wide <sup>24,27,55,67</sup>. However, it remains untested whether the loss of H3K27me3 alone is sufficient to trigger earlier reactivation of the late genes. For instance, PRC2
inhibition does not enhance X-chromosome reactivation in iPSCs<sup>18</sup> and this observation still needs to be investigated in PGCs. From our analysis of H3K27me3, we were surprised to observe that more late and very late reactivated genes were enriched for this repressive marks at E12.5 compared to E11.5, which seems counterintuitive given the simultaneous X-chromosome reactivation. One hypothesis is that the increased number of genes coated by H3K27me3 at E12.5 could be attributed to a genome-wide enrichment of H3K27me3 occurring simultaneously in both male and female PGCs<sup>24</sup>. More quantitative and spiked allele-specific CUT&RUN experiments in males and females PGCs at earlier and later stages would be necessary to fully understand this observation. Finally, other chromatin marks may also be involved in regulating the reactivation kinetics. H3K27 acetylation is the first mark to be lost when the Xi becomes silenced. We could envisage a strict duality between the acquisition of acetylation at H3K27 for early-reactivated genes and methylation for late-reactivated genes respectively.

In conclusion, in PGCs, we observed that resistance to reactivation depends on the proximity of X-linked genes to the *Xist* locus, their tendency to be inside the first regions coated by the long non-coding RNA in 3D space, their distance to actively transcribed regions (escapee loci), and their enriched in repressive chromatin marks such as H3K27me3, and to a lesser extent, DNA methylation. Together, these findings provide a better understanding of the *in vivo* requirements for female epigenetic reprogramming and are widely relevant to stem cell biology and reproduction.

538

f. Acknowledgments

We acknowledge the Surani and Bourc'his laboratories for insightful discussions, Kay Harnish, Cambridge Stem Cell Institute Genomics Facility, and the MGX-Montpellier GenomiX platform for advice and deep sequencing of the libraries. We thank the pathogen-free barrier animal facility of Gurdon Institute, and the PCEA and ZEFI of IGMM, UMR5535, in Montpellier. We are grateful to Joan Barau, Dominique Helmlinger, and Lorraine Bonneville for their advice and reagents regarding the low-input CUT&RUN. We thank Yolanda Moyano Rodriguez, Thierry Forné and Eric J. Kremer for proofreading the manuscript. This work was supported by a Centre National de la Recherche Scientifique et Institut National de la Santé et de la Recherche Médicale (CNRS-INSERM ATIP-Avenir grant, the Amorçage Jeune Equipe from Fondation Recherche Médicale (FRM -AJE202005011598) and Agence National de la Recherche under the "Investissements d'avenir" programme with the reference ANR-16-IDEX-0006 » to M.B. ; by the Wellcome Trust funding 096738 and 092096 and Cancer Research UK program C6946/A14492 to M.A.S., by a PhD fellowship from La Ligue nationale contre le cancer to C. R; by a FRM SPE20150331826 and a Marie Sklodowska-Curie Individual (H2020-MSCA-IF-2015—no. 706144) fellowships to M.B. MGX acknowledges financial support from France Génomique National infrastructure, funded as part of the
554 "Investissement d'Avenir" program managed by Agence Nationale pour la Recherche (contract ANR-10-INBS-09).

556

557 **g. Author Contributions Statement**

558 M.B. conceived the study with M.A.S. and performed scRNA-seq experiments. C.R. performed chromatin 559 analysis, handled mouse colonies, and collected embryos with the help and supervision of K.C. L.S., E.B., 560 P.R. and D.Z. performed bioinformatics analysis, supervised by N.S. and M.B. A.T. performed the repeats 561 and WGBS bioinformatics analysis. C.L. contributed to animal husbandry and sample collection. M.W. and 562 D.B. conducted WGBS experiments. M.B., M.A.S., and D.B. secured the funding. M.B. wrote the original 563 draft, C.R. and L.S. reviewed and edited the manuscript, with inputs from co-authors.

564

565 **h. Competing Interests Statement**

566 Authors declare no competing interests.

567

568 **i. Tables**

569 N/A

570

571 **j. Figure Legends/Captions**

572 **Figure 1**

573 **Single-cell RNA sequencing of polymorphic primordial germ cells during embryonic development.**
574 (A) Schematic illustration of single-cell transcriptomic experiments, including mouse breeding (129 × Cast), harvested embryonic stages, and single-cell collection. In embryos from E9.5 to E12.5, the *Oct4-GFP* (GOF-ΔPE-18 line) <sup>39</sup> marker was used to differentiate between PGCs and soma. PGC, primordial germ cells; FACS, fluorescence-activated cell sorting. (B) PCA of single PGC and soma based on the 1 000 most variable genes in the transcriptomic datasets. The different stages are denoted by different colours. The rounds represent PGC, and triangles represent GFP-negative somatic cells in the proximity of the PGCs. The number of cells analysed per stage and further details of the scRNA-seq samples are shown in **Supplementary Data (C)** Hierarchical clustering and two-sided Pearson's distance of scRNA-seq samples based on germline, soma, and sex-specific gene expression variation using Pearson's correlation. Cells were clustered first by lineage (PGC and soma), then by stage (E9.5–E12.5), and then by sex for the E11.5 and E12.5 stages. n = 122 single-cell samples. (D) Expression levels of 25 known genes expressed in developing
585 PGCs or soma and sex-specific genes (*Xist* and *Y*-linked genes) in the 122 single-cell samples were used to classify cells according to their lineage, as shown. The cells were ordered according to hierarchical clustering in *C*. PGCs primordial germ cells.
586
587

588

589 **Figure 2**

590 **Progression of X-chromosome reactivation in developing PGCs.** (A) PCA of scRNA-seq datasets from
591 PGCs and soma between E9.5-E12.5. The X-chromosome composition of each single cell is represented
592 on the PCA, such as the XY male, XX female, and XO female cells. The XO cells originate from a single
593 embryo and found by serendipity. PCA is based on the 1 000 most variable genes, as described in **Figure
594 1B**. The details of each cell are listed in **Supplementary Data (B)** Allele-specific expression ratios for
595 genes on autosomes and X chromosomes in female (pink) and male (dark blue) single PGCs from E9.5 to
596 E12.5, and in female (pink) and male (dark blue) single somatic cells collected alongside the PGCs. For
597 autosomes, the allelic ratio represents the number of reads mapped to the Cast genome divided by the total
598 number of 129 and Cast reads. For X-linked genes, we measured the allelic ratio as the parental genome
599 from which Xi originated, divided by the total number of 129 and Cast reads mapped for each gene (Xa
600 counts/total Xa + Xi counts). A gene was considered biallelically expressed when 0.15< allelic ratio <0.85.

601 Box plots represent medians (centre lines) with lower and upper quartiles (box limits). Whiskers represent
602 1.5× the interquartile range. Outliers are represented by dots. The number of cells analysed per stage and
603 the parental origin of Xi are shown in **Supplementary Data. (C) and (D)** Pseudotime representation of
604 scRNA-seq data based on the first principal component for female PGCs between E9.5 and E12.5. (C) Each
605 dot represents a single cell. The percentage of reactivation is calculated for each PGC from the number of
606 biallelically expressed X-linked genes. In (D), single female PGCs are ordered by pseudotime as a function
607 of the percentage of biallelic X-linked genes per cell, provided by a colour gradient as shown in the key. A
608 gene is called reactivated if its allelic ratio is >0.15 and <0.85, which represents an expression from the Xi
609 of at least 15%. A strong positive (r=0.76) correlation was observed between the pseudo-developmental
610 time of the PGCs and their reactivation.
611

611

612 **Figure 3**

613
614
615
616
617

**Kinetics of reactivation of X-linked genes over the entire X chromosome in developing PGCs during reversal of random XCI.** The mean of the allele-specific expression ratios per embryonic stage for each informative and expressed X-linked gene in female PGCs are represented as heatmaps from E9.5 to E12.5, with strict monoallelic Xa expression (ratio >0.85) in red and strict monoallelic Xi expression (ratio <0.15) in blue. Color gradients are used between these two values, as indicated in the key. Genes are ordered by
618 genomic position (A) and reactivation kinetics class (B). Xist expression was always below RPRT < 4, and
619 its genomic location has been added to the heatmap for information (black arrow). n = 197 informative X-
620 linked genes, with a RPRT expression ≥4, expressed in at least 3 out of 4 developmental stages. White box,
621 data not available (below threshold).
622

623 **Figure 4**

624 **Differential timing of X-linked gene reactivation is associated with timing of silencing and** 625 **chromosomal location.** (A) Genes are clustered by reactivation kinetics as early (re-expressed from the Xi 626 from E10.5), intermediate (from E11.5), late (from E12.5), very late (not reactivated at E12.5), and escapee 627 (not subject to XCI). The allelic ratio of each gene represents the fraction of Xa expression, with the number 628 of reads mapped on the Xa genome divided by the total number of reads mapped. This is shown for stages 629 E9.5 to E12.5 for all female PGCs. n = 197 X-linked genes. Further information is provided in 630 **Supplementary Data 2.** For PGC reactivation classes: early (n=33 genes), intermediate (n=53 genes), late 631 (n=28 genes), very late (n=59 genes), and escapee (n=11 genes). (B) Mean expression level of X-linked 632 genes in female PGCs (total number of reads mapped, normalized by the covered gene length) is represented 633 at E9.5, E10.5, E11.5 and E12.5. KW tests followed by post-hoc Dunn's were performed with * p- 634 value<0.05; ** p-value<0.01. n = 197 X-linked genes. (C) Pink and yellow dots represent the mean of 635 expression from the Xa and Xi respectively in female PGCs. Blue dots represent the mean of expression of 636 the Xa in male PGCs. n = 197 X-linked genes. (D) Distance to the *Xist* genomic locus. Distribution of 637 genomic distances (Mb) for different X-linked gene reactivation classes (p=0.01, KW test). The 638 transcription start site (TSS) of each gene was used to measure the distance from the *Xist* locus. Very late 639 reactivated genes were significantly closer to the *Xist* locus than early reactivated (p=0.0051), intermediate- 640 reactivated (p=0.0039), and escapee (p=0.0058) genes, according to the KW test followed by post-hoc 641 Dunn's test. ** p<0.01. (E) Comparison of reactivation classes in female PGCs and in the ICM of female 642 blastocysts 20. (F) Silencing classes of X-linked genes in mouse embryonic stem cells (ESC) compared with 643 their reactivation classes in PGCs 15. 644

644 Box plots: (centre lines), lower and upper quartiles (box limits) and whiskers (1.5× the interquartile range).
645 Outliers are represented by dots.
646

647 **Figure 5**

648 **Enrichment of repeats and DNA methylation correlates with the latest reactivated loci of the inactive** 649 **X chromosome (A)** Number of total transposons, LINEs, and SINES overlapping with Xist RNA entry 650 sites 6. A set of control regions was generated randomly 1 000 times. A two-sided t test was performed to
compare the number of repeats in Xist RNA entry sites compared to controls. * *p*-value<0.05; ** *p*-value<0.01; *** *p*-value<0.005. (B) WGBS of E6.5 female epiblast cells compared to public datasets of female PGCs at E10.5<sup>54</sup> and E12.5<sup>55</sup>. A two-sided *t* test was performed for each developmental stage to compare mean DNA methylation level of genes annotated as early in comparison to genes annotated in the other classes: * *p*-value<0.05; ** *p*-value<0.01; *** *p*-value<0.0001 by *t*-test. (C) Scheme of mouse breeding between C57Bl6/J Xist<sup>flox/flox</sup>; Zp3-Cre; Oct4-eGFP females and Castaneus males to obtain female polymorphic embryos with non-random XCI and fluorescent PGCs. PGCs were isolated by FACS (Oct4-eGFP reporter). (D) Following PGC sorting, gDNA was extracted and HpaII DNA methylation-sensitive restriction enzyme treatment completed, followed by PCR amplification and Sanger sequencing. Two independent PCR were performed per loci and per stage and sequenced independently. However, only one digestion was performed per stage due to the scarcity of material. Empty microtube-closed icon is credited to DBCLS licensed under CC-BY 4.0 Unported https://creativecommons.org/licenses/by/4.0, with small adaptations. (E) Allele-specific DNA methylation assay with methylation-sensitive HpaII was performed for the paternally imprinted *H19*-ICR. Top: agarose gel electrophoresis in E13.5 embryo and E10.5 PGCs. Bottom: Sanger sequencing results indicate the paternal allele-specificity of methylation at the *H19*-ICR in E13.5 embryo and PGCs. The arrow indicates the SNP used to distinguish between the maternal (M) and paternal (P) alleles. (F) Allele-specific DNA methylation assay for three X-linked genes. Sanger sequencing profiles indicate methylation enrichment from Xi for *Rps4x* (early-reactivated), *Mtmr1* (very late-reactivated), and *Xlr3a* (very-late reactivated) in E10.5 female PGCs. The arrow indicates the SNP used to distinguish between Xa and Xi chromosomes.

Box plots: (centre lines), lower and upper quartiles (box limits) and whiskers (1.5× the interquartile range).
Outliers are represented by dots.

673

674 **Figure 6**

675 **Repressive histone mark contributes to resistance to early gene reactivation.** (A) Two-sided Pearson 676 correlation between each H3K27me3 samples (2 replicates at E11.5 and 2 at E12.5) and the IgG control of 677 CUT&RUN. From left to right: genome-wide analysis, Xa only, and Xi only. (B) Integrative Genomics 678 Viewer tracks for total H3K27me3 normalised reads (dark blue) and allele-specific reads (light blue: 679 Xi/CAST; red: Xa/B6) on the entire X chromosome. Orange blocks are statistically called broad domains. 680 (C) Tracks of H3K27me3 from E11.5 female PGCs (2 pooled replicates) and E12.5 female PGCs (2 pooled 681 replicates), compared to IgG (E13.5 female PGCs). Dark blue tracks represent total H3K27me3 normalised 682 reads, and light blue and red represent allele-specific Xi and Xa reads respectively, for chosen examplps of 683 X-linked genes. Orange blocks are statistically called H3K27me3 broad domains by MACS2, compared to
684 IgG. (D) Percentage of early (n = 33), intermediate (n = 53), late (n = 28), very late (n = 59), and escapee (n = 11), silent (n=344) genes showing an occupancy by at least one significantly-called broad domain of
685 H3K27me3. A Two-way Anova has been performed to compare percentage per reactivation class. (E-F)
686 Violin plots represent H3K27me3 sum score for all reactivation classes and silent genes from the Xa (left)
687 and Xi (right) at E11.5 (top) and E12.5 (below) in female PGCs. Silent class has been characterised as genes
688 silenced from both X chromosomes in all female PGC scRNA-seq. Each dot represents one gene, yellow
689 dotted lines the median, and the red dotted lines the quartiles. Early (n=33), intermediate (n = 53), late (n =
690 28), very late (n = 59), and escapee (n = 11), silent (n = 344) (E) KW test followed by post-hoc Dunn's test
691 (versus Early) show significantly different enrichment from Xi at E11.5 (p-value < 0.0001) and E12.5 (p-
692 value < 0.0001). (F) A two-sided Wilcoxon matched-pairs signed rank test was performed to compare each
693 gene on the Xa versus Xi at E11.5 and E12.5 with * p-value < 0.05 and**** p-value < 0.0001.
694

695 Location is in mm10, with gene location and isoforms extracted from IGV and UCSC.

696

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839

840

841 **1. Methods**

842

843 **Mouse husbandry**

844 The care and use of animals strictly apply the European and National Regulation for the Protection of
845 Vertebrate Animals used for Experimental and other Scientific Purposes (Directive 2010/63/EU and French
846 decree R.214-103). All husbandry and experiments involving mouse scRNA-seq were authorized by the
847 UK Home Office Project Licences PPL80/2637 and PE596D1FE and were carried out in a Home Office
848 designated facility (Welcome Trust Cancer Research Gurdon Institute). Chromatin experiments were
849 authorized by the French ethics committee number 36 under agreement F3417216 and carried out in the
850 pathogen-free Animal Care Facility of IGMM (facility licence #G34-172-16). Researchers carrying out
851 regulated procedures on living mice held a personal licence from either the UK (C.L., M.B., and M.A.S.)
852 or France (C.R., M.B., K.C., and D.B.).

853 Mice were housed under a 12 h light/12 h dark cycle at 22 ± 2 °C ambient temperature, with free access to
854 food and water. All embryos were derived from natural mating. Noon on the day of observation of the
855 vaginal plugs was scored as embryonic day (E) 0.5. Embryos were harvested every 24 h between E9.5 and
856 E12.5. Collected embryos were included in the analyses only if they showed normal morphology according
857 to their developmental stages. No statistical method was used to pre-determine sample sizes but our sample
858 sizes are similar to those reported in previous publications ⁴,²⁰. Randomization was not performed: embryos
859 were allocated based on their sex (PCR or analysis of transcripts) and their developmental timing
860 (embryonic day at collection). Data collection and analysis were neither performed blind to the conditions
861 of the experiments.

862 Male and female hybrid embryos were obtained by breeding GOF-ΔPE-18 transgenic line on a common
863 laboratory strain 129S1/SvImJ (129) background<sup>39</sup> with *Mus musculus castaneus* (Cast) for scRNA-seq
864 experiments (**Figure 1A**). *Xist*<sup>-/+</sup> *Zp3-CRE; Oct4-eGFP* female embryos (**Figure 5C**) were obtained by
865 mating *Mus musculus*. *domesticus* C57Bl6/J *Xist*<sup>flox/flox</sup>; *Zp3-CRE; Oct4-eGFP* females<sup>5,68,69</sup> with *Mus
866 musculus castaneus* males.

867

868 Sexing of the embryos

869 The sex of the embryos was characterized based on the morphology of the gonads at E11.5 and E12.5. Prior
870 E11.5, sex was characterized in single-cell RNA-seq datasets by studying the expression of *Xist* and Y-
871 linked genes, as well as the presence or absence of polymorphisms (SNPs) on the X chromosome. For the
872 WGBS and CUT&RUN experiments, the sex of the embryos was determined by PCR using genomic DNA
873 and *Ube1* primers (Ube1-Forward *TGGATGGTGTGGCCAATG*; Ube1-Reverse
874 CACCTGCACGTTGCCCTT, 252 bp for the X and 334 bp for the Y).

875

876 Collection of PGCs

877 After dissection of embryos at the location of the PGCs, according to embryonic stage, and sexing of the
878 embryos, samples were resuspended in 200 µL of 0.25% trypsin and incubated at 37 °C for 3 min. Trypsin
879 was inactivated with serum, and a single-cell solution was obtained by vigorous up-and-down. For scRNA-
880 seq experiments from E10.5, cells were manually picked based on their GFP and size and washed in PBS-
881 acetylated BSA (**Figure 1A**). For the other stages, allele-specific DNA methylation assays and all
882 CUT&RUN experiments, cells were collected by fluorescence-associated cell sorting (FACS ARIA© and
883 S3e Cell Sorter Bio-Rad©) and processed quickly for scRNA-seq or low-input CUT&RUN. For genomic
884 DNA extraction, cells were frozen in TRIzol™ and kept at -80°C for weeks. Flow cytometry was analysed
885 using FlowJo (v10.7.1) or BD FACSDiva (Becton-Dickinson) software, see **Supplementary Figures 2-4**
886 for gating strategies.

887

888 Single-cell RNA sequencing and bioinformatic analysis

889 Single PGC and soma cells were washed thrice with PBS/acetylated BSA (Sigma) before being manually
890 transferred within the minimum amount of liquid into PCR tubes. We either directly prepared the cDNA
amplifications or kept the single cells at – 80 °C (less than 2 months) for future preparation. Poly(A)⁺
mRNA extracted from each single cell was reverse-transcribed from 3'-UTRs and amplified according to
a previously described protocol <sup>40,41</sup>. Care was taken to process only embryos and PGCs of the highest
quality based on morphology and amplification yield. A total of 150 single cells were processed, and quality
control (QC) was performed as described in <sup>4</sup>, meaning that sequencing reads characterized by at least one
of the following criteria were discarded from the analysis: more than 50% low-quality bases (Phred score
<5); more than 5% N bases; more than 80% A/T bases; at least 30% (15 bases) of continuous A and/or T.

Single-cell libraries were analysed from 122 samples that passed QC, according to the manufacturer's
protocol (Illumina). Sequencing to produce single-end 50-bp reads was then performed on an Illumina
HiSeq 4000 instrument (<strong>Supplementary Data 1</strong>).

Quality controls, filtering of raw data, mapping, and SNP calling have been described previously <sup>28,32</sup>.
Briefly, the mouse mm10 genome was downloaded from the Sanger database. To study allele-specific gene
expression, reads were processed according to Borensztein et al <sup>4</sup>. SNPs between the 129 and Cast strains
were extracted from the VCF file and used to reconstruct the Cast genome. After the removal of the common
exonic SNPs between *Xist* and *Tsix*, 20,220,776 SNPs were retained. The number of paternal and maternal
reads was counted at each SNP position. The threshold used to call a gene informative was five reads
mapped per single SNP, with a minimum of eight reads mapped on SNPs per gene, to minimize disparity
with low-polymorphic genes. The allele-specific origin of the transcripts (allelic ratio) was calculated as
the total number of reads mapped to the Cast genome divided by the total number of reads for each gene:
allelic ratio = Cast reads/(Cast + 129) reads. For the X-linked genes, we modified the allelic ratio to allelic
ratio = Xa reads/(Xa + Xi) reads. In the case of 129 Xi, the allelic ratio became 1-[Cast reads/(Cast+129)
reads]. Genes were thus classified into two categories: inactivated genes: allelic-ratio value ≤0.15 or ≥0.85,
and biallelically expressed genes: allelic-ratio value >0.15 or <0.85.

914

*Estimation of gene expression levels.* Given that our RNA reverse transcription allowed sequencing only up to an average of 3 kb from the 3' UTR, half of the expressed genes were only partially covered (less than 50% of the gene size on average). To estimate transcript abundance, read counts were normalized based on the amplification size of each transcript (RPRT) rather than the size of each gene (RPKM) (see details in Borensztein *et al.*<sup>40</sup>).

920

PCA and hierarchical clustering. Count tables of gene expression were generated using RefFlat annotation
and HTSeq software (v0.7.2). Only genes with at least one read in one cell were retained for these analyses.
The VST method from the DESeq2 R package (v1.34.0, R software v.4.1.2) was applied to the raw count
data. PCA and hierarchical clustering were then used to determine how single cells were clustered with the others although their gene expression profiles, depending on their stage, sex and lineage. PCA on normalized data was performed using the DESeq2 R package. Hierarchical clustering analysis was based on Pearson correlation distance and the Ward method using the hclust function implemented in the gplots R package (v3.1.3).

*Differential analysis.* Expressed genes (RPRT ≥ 1 in at least three cells) were then selected for differential analysis. The raw count table was normalized using the TMM method (weighted trimmed mean of the log expression ratios) from the edgeR R package (v3.36.0), and the limma-voom (v3.50.3) functions were applied to detect genes with differential expression between the different conditions. With Benjamini-Hochberg correction, genes with an adjusted P value < 0.05 were considered significant.

*Heatmap generation for X-chromosome allelic gene expression.* For allelic ratio heatmaps, data from informative genes were analysed at each developmental stage only if the gene was expressed (RPRT ≥4) in at least two cells. To follow the kinetics of expression, we focused only on genes expressed in at least three different stages. The mean allelic ratio of each gene is represented for the different stages of the female PGCs.

*Global gene expression correlation with X-chromosome reactivation.* Correlation and anti-correlation between gene expression levels (autosomes and X chromosomes) and the percentage of X-linked gene reactivation (0.15< allelic ratio <0.85 for X-linked genes) were measured using two-sided Pearson's correlation and Benjamini-Hochberg correction. Gene ontology analysis was performed for the top-correlated genes (adj.pval≤0.05) using the clusterProfiler R package (v.4.2.2). Genes with RPRT < 4 were excluded from the allelic analysis (allelic ratio = NA) (Supplementary Data 3).

*Definition of X-linked gene reactivation classes.* We automatically assigned X-linked genes to the reactivation classes.

951 - Early reactivation: expressed on both chromosomes at stage E10.5. Allelic ratio ≥ 0.85 or NA at E9.5; allelic ratio < 0.85 at E10.5; allelic ratio < 0.85 at E11.5; allelic ratio < 0.85 or NA at E12.5.

953 - Intermediate reactivation: expressed on both chromosomes at stage E11.5. Allelic ratio ≥ 0.85 or NA at E9.5; allelic ratio ≥ 0.85 or NA at E10.5; allelic ratio < 0.85 at E11.5; allelic ratio < 0.85 or NA at E12.5.
956 - Late reactivation: expressed on both chromosomes at stage E12.5. Allelic ratio ≥ 0.85 or NA at E10.5;
957 allelic ratio ≥ 0.85 at E11.5; allelic ratio < 0.85 at E12.5.

958 - Very Late reactivation: silenced at stage E12.5. Allelic ratio ≥ 0.85 or NA at E10.5; allelic ratio ≥ 0.85
959 at E11.5 and E12.5 OR allelic ratio < 0.85 at E11.5 and ≥ 0.85 at E12.5.

960 - Escapees: always biallelic. Allelic ratio < 0.85 at all stages, or NA at E10.5

961

962 Low-input CUT&RUN

963 After PGCs were collected, the cells were directly pelleted at 4 °C for 5 min. The CUT&RUN protocol was
964 modified from Skene et al ⁷⁰ and Dura et al ⁷¹to accommodate to a low number of PGCs (5 000- 15 000
965 per sample). Briefly, cells were split according to the number of required antibody profiles, and nuclear
966 extraction buffer (20 mM HEPES-KOH, 10 mM KCl, 0.5 mM spermidine, 0.1% Triton X-100, 20%
967 glycerol, complete EDTA-free protease inhibitor cocktail) was gently added to the cell solution and
968 incubated on ice for 5 min. Cells and concanavalin A beads were incubated for 10 min at room temperature
969 (RT) on a rotating wheel. Cells were then collected on magnets, resuspended in blocking buffer (20 mM
970 HEPES-KOH, 150 mM NaCl, 0.5 mM spermidine, 0.1% BSA), 2 mM EDTA, and 1× Complete EDTA-
971 free protease inhibitor cocktail), and incubated at RT for 5 min. Cells were then washed and incubated with
972 H3K27me3 antibody (1:200 dilution, Cell Signaling 36B11#9733, control with IgG rabbit Sigma) for 2 h
973 at 4 °C on a rotating wheel and washed twice. Samples were then incubated with 1:400 Protein A-MNase
974 fusion protein (gift from the Dominique Helmlinger lab, CRBM France) for 1 h at 4 °C followed by two
975 washes. Cells were then resuspended in 150 µL of wash buffer and cooled in an ice-water bath for 5 min
976 before the addition of a final concentration of 100 mM CaCl₂. Targeted digestion was performed for 30 min
977 on ice. The samples were then incubated for 20 min at 37 °C to release the cleaved chromatin fragments.
978 After centrifugation at 16,000 × g for 5 min, supernatants were transferred to new low-binding tubes.
979 Following the addition of 20% SDS and 20 mg ml⁻¹ proteinase K, the samples were incubated for 30 min
980 at 70 °C. DNA was purified using phenol/chloroform, followed by chloroform extraction and precipitation
981 with 20 mg.ml⁻¹ glycogen and three volumes of 100% ethanol at 20 °C. The DNA pellet was washed with
982 85% ethanol, centrifuged, and resuspended in low Tris-EDTA.

983 Library preparation was performed according to the manufacturer's instructions (NEBNext® Ultra™ II
984 DNA Library Prep Kit for Illumina) using the following modified library amplification program: 98 °C for
985 30 s, (98 °C for 10 s, 65 °C for 15 s) × 15 cycles, 65 °C for 5 min, hold at 4 °C. Average library size and
986 quality control were performed using a Fragment Analyser (High Sensitivity NGS kit) and qPCR (Roche
987 Light Cycler 480). CUT&RUN libraries were sequenced on a NovaSeq 6000 (Illumina) from Biocampus,
988 MGX platform, using a paired-end 150-bp run. We obtained 9-15 million mapped reads per CUT&RUN
replicates and 35 million mapped read for the IgG control used in the analyses. 2 other IgG have been produced, tested for reproducibility and are provided in GEO. All CUT&RUN replicates were performed on 10 000 to 14 000 PGCs from two to five-pooled female embryos. IgG was performed on 20 000 PGCs from 4 female embryos. Replicates were from different litters.

993

994 Allele-specific CUT&RUN bioinformatic analysis

995 FastQC (v0.11.9) and MultiQC (v1.13)⁶⁷ were used to assess CUT&RUN data quality. Paired-end reads 996 with at least one undefined UMI were discarded using Cutadapt (v4.1) ⁷² and seqkit (v2.3) ⁷³. The reads 997 were then trimmed using Trim Galore (v0.6.6) ⁴ (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/⁷⁴; options "--length 20 -illumina - 998 2color 20"). Trimmed reads were mapped with Bowtie2 (v2.4.2) ⁷⁵ (options "--end-to-end -very-sensitive 999 -reorder") to the mm10 reference genome, modified as follows: autosomal, sexual and mitochondrial 1000 chromosomes are kept, and 20 668 274 SNP positions (0.76% of genome size) related to *Mus musculus* 1001 *Castaneus* strain are N-masked using SNPsplit (v0.6) ⁷⁶ (https://ftp.ebi.ac.uk/pub/databases/mousegenomes/REL-1505- 1002 1003 SNPs_Indels/strain Specific vcfS/CAST_EiJ.mgp.v5.snps.dbSNP142.vcf). SAMtools (v1.11) ⁷⁷ was used 1004 to sort and convert the data formats. PCR duplicates were removed using GATK MarkDuplicates, and 1005 unmapped reads with or without primary alignment discarded (SAMtools options "-F 0x04 -F 0x100 -F 1006 0x800"). The coverage for each developmental stage was calculated from the bam file using the deepTools 1007 bamCoverage tool (v3.5.1, normalization by scale factor, bin=10 nt) ⁷⁸. Scale factor was Count per Million 1008 (CPM) based on filtered mapped reads. 1009

1010 Peak calling of H3K27me3 histone marks for E11.5 and E12.5 female samples, using immunoglobulin G 1011 (IgG) (E13.5 female PGCs) as input for each stage, was performed with MACS2 (v2.2.7.1, options "-f 1012 BAMPE -broad -broad-cutoff 0.1") ⁷⁹ on total mapped reads (including both allelic and non-allele 1013 sequencing reads).

1014 Allele-specific reads (i.e., reads from B6: Xa and Cast: Xi) were sorted using SNPsplit. The d-score 1015 parameter (reads Cast/[reads B6 + reads Cast]) was calculated using featureCounts from the Rsubread R 1016 package (v2.12.3) ⁸⁰. H3K27me3 enrichment heatmaps show the log2-fold change in the coverage 1017 difference between the H3K27me3 mark and the IgG control for each developmental stage, normalized by 1018 the sequencing depth using deepTools bamCompare (bin= 10 nt). computeMatrix and plotHeatmap.

1019 Integrative Genomics Viewer tracks for total H3K27me3 normalised reads and allele-specific reads are in 1020 Count Per Million mapped reads (CPM, bin 10). All provided locations are in mm10 genome, with gene 1021 location extracted from IGV and UCSC. A gene was considered with H3K27me3 promoter occupancy if at
1022

least one broad domain was mapped +/- 1kb from TSS. Genes with only domains outside this window were
considered enriched at the gene body.

1023

1024

1025

Whole-genome bisulfite sequencing of female epiblasts

1026

C57Bl6/J epiblasts were manually dissected from extraembryonic tissues of E6.5 embryos, followed by sex
determination by PCR on the extraembryonic tissue (see section sexing of the embryos). WGBS libraries
from 2 E6.5 female replicates were prepared as described by Smallwood et al ⁸¹. The WGBS was analysed
as described previously ⁸². Briefly, reads generated in this study or recovered from the available datasets
were treated as follows: the first eight base pairs of the reads were trimmed using the FASTX-Toolkit
v0.0.13 (hannonlab.cshl.edu/fastx_toolkit/index.html). Adapter sequences were removed with Cutadapt
v1.3 (code.google.com/p/cutadapt/) ⁷², and reads shorter than 16 bp were discarded. The cleaned sequences
were aligned to the mouse reference genome (mm10) using the default parameters for Bismark v0.12.5 70
with Bowtie2-2.1.0 ⁷⁵. Only the reads that mapped uniquely to the genome were conserved. Sequencing t-
test statistics can be found in the figure legend and/or the main text. Methylation calls were extracted after
duplicate removal. Only CG dinucleotides covered by a minimum of ten reads were retained for the
subsequent analysis.

1027

1028

1029

1030

1031

1032

1033

1034

1035

1036

1037

1038

1039

DNA methylation and transposon data analysis

1040

DNA methylation data at E10.5 and E12.5 were downloaded from DRA000607 ⁵⁴ and GSE76971⁵⁵,
respectively. The raw data were cleaned using Trim Galore v0.4.4 ⁷⁴. The cleaned reads were aligned to the
mouse reference genome assembly (GRCm38/mm10) using Bismark v0.18.2 ⁸³ with Bowtie2-2.2.9 ⁷⁵,
allowing for one mismatch in the seed alignment. Only reads that mapped uniquely to the genome were
retained, and methylation calls were extracted after duplicate removal, considering only CpG dinucleotides
covered by a minimum of five reads.

1041

1042

1043

1044

1045

1046

For the control regions of transposon enrichment, a set of 25 random regions (number of Xist RNA entry
sites), with the same length as the median Xist RNA entry sites, was bootstrapped 1 000 times either
genome-wide or on the X chromosome using the R package regioneR (v1.10.0 ⁸⁴). The number of
retrotransposons overlapping Xist RNA entry sites and random regions was calculated and normalized to a
10 kb window. DNA methylation levels were estimated using a window of -1 kb to +100 bp from the
transcriptional start site (TSS) for each gene. In all cases, a permutation test was performed using the
RegioneR package.

1047

1048

1049

1050

1051

1052

1053
1054 Allele-specific DNA methylation assays

1055 Genomic DNA was directly extracted from the interphase and lower-phase of TRIzol™ in stored PGCs,
1056 following the manufacturer's protocol (TRI REAGENT® - RNA / DNA / PROTEIN ISOLATION
1057 REAGENT). Briefly, gDNA from E10.5 PGCs (12 500 cells from 9 female embryos) was extracted.
1058 Genomic DNA of an entire E13.5 female embryo was also extracted as control by classic proteinase K,
1059 phenol-chloroform protocol. 700 ng of gDNA from each sample was first digested EcoRI (Cutsmart NEB
1060 buffer) for 3 hours at 37°C. Half of digested samples was then digested again by HpaII (Cutsmart NEB
1061 buffer) overnight at 37°C, followed by 20 mins of inactivation at 65 °C. Finally, specific loci were amplified
1062 by PCR (92 °C for 2 min, (94 °C for 30 s, 57-59 °C for 30 s, 72 °C for 30 s) x 30-40 cycles, 72 °C for 2min,
1063 hold at 10 °C). PCR products were run on a 1.5% agarose gel, excised, and column-purified (Qiagen,
1064 #28506), followed by Sanger sequencing to distinguish the parental alleles using SNPs. PCR primer
1065 sequences are given in **Supplementary Data 5**.

1066

1067 Statistics

1068 Statistical significance was evaluated using the Kruskal-Wallis (KW) test followed by Dunn's correction
1069 and Mann-Whitney (MW) for two samples comparison. To compare same gene between Xa and Xi, we
1070 used Wilcoxon matched-pairs signed rank test. The statistical test is mentioned in the figure caption and/or
1071 result section. P-values are provided in the figure legends and/or the main text.

1072

1073 **m. Data availability**

1074 All scRNA-seq and WGBS, and CUT&RUN datasets are deposited in Gene Expression Omnibus under the
1075 numbers GSE243943 and GSE243464. WGBS of E10.5 PGCs and E12.5 PGCs were respectively extracted
1076 from the Japan (DDBJ) Sequence Read Archive (under accession number DRA000607) 54 and from GEO,
1077 under accession number GSE76973 55. Other data are available from the corresponding author upon request.

1078

1079 **n. Code Availability**

1080 No code has been developed for this study. Details and specificities (tools, version and options) to replicate
1081 the bioinformatic pipelines are provided in the Methods.

1082

1083 **o. Methods-only references**
68. Lan, Z. J., Xu, X. & Cooney, A. J. Differential oocyte-specific expression of Cre recombinase activity in GDF-9-iCre, Zp3cre, and Msx2Cre transgenic mice. Biol Reprod 71, 1469-1474 (2004).

69. Szabo, P. E., Hübner, K., Schöler, H. & Mann, J. R. Allele-specific expression of imprinted genes in mouse migratory primordial germ cells. Mechanisms of development 115, 157-160 (2002).

70. Skene, P. J. & Henikoff, S. An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites. eLife 6, 1-35 (2017).

71. Dura, M. et al. DNMT3A-dependent DNA methylation is required for spermatogonial stem cells to commit to spermatogenesis. Nat Genet 54, 469-480 (2022).

72. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10-12 (2011).

73. Shen, W., Le, S., Li, Y. & Hu, F. SeqKit: A Cross-Platform and Ultrafast Toolkit for FASTA/Q File Manipulation. PLOS ONE 11, e0163962 (2016).

74. Krueger, F., James, F., Ewels, P., Afyounian, E. & Schuster-Boeckler, B. FelixKrueger/TrimGalore: v0.6.7 - DOI via Zenodo. Zenodo https://doi.org/10.5281/zenodo.5127899 (2021).

75. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat Methods 9, 357-359 (2012).

76. Krueger, F. & Andrews, S. R. SNPsplit: Allele-specific splitting of alignments between genomes with known SNP genotypes. F1000Res 5, 1479 (2016).

77. Danecek, P. et al. Twelve years of SAMtools and BCFtools. Gigascience 10, giab008 (2021).

78. Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res 44, W160-W165 (2016).

79. Zhang, Y. et al. Model-based Analysis of ChIP-Seq (MACS). Genome Biology 9, R137 (2008).

80. Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923-930 (2014).

81. Smallwood, S. a et al. Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nature Methods 11, 817-820 (2014).

82. Walter, M., Teissandier, A., Pérez-Palacios, R. & Bourc'his, D. An epigenetic switch ensures transposon repression upon dynamic loss of DNA methylation in embryonic stem cells. eLife 5, e11418 (2016).
1114

83. Krueger, F. & Andrews, S. R. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq

1115

applications. Bioinformatics 27, 1571–1572 (2011).

1116

84. Gel, B. et al. regioneR: an R/Bioconductor package for the association analysis of genomic regions

1117

based on permutation tests. Bioinformatics 32, 289–291 (2016).

1118

1119
<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

**Lineage**
* PGC
▲ Soma

**Stage**
* E9.5
* E10.5
* E11.5
* E12.5

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /><figcaption>Figure 1</figcaption></figure>
<figure><img src="image_8.png" /></figure>
<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /><figcaption>Figure 2</figcaption></figure>
<figure><img src="image_14.png" /></figure>
<figure><img src="image_15.png" /><figcaption>B Ordered by reactivation classes</figcaption></figure>

<figure><img src="image_16.png" /><figcaption>Figure 3</figcaption></figure>
<figure><img src="image_17.png" /></figure>
<figure><img src="image_18.png" /><figcaption>Figure 4</figcaption></figure>
<figure><img src="image_19.png" /></figure>
<figure><img src="image_20.png" /></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" /><figcaption>Figure 5</figcaption></figure>
<figure><img src="image_27.png" /></figure>
<figure><img src="image_28.png" /></figure>

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

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

<figure><img src="image_31.png" /></figure>

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

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

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

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

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

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

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

<figure><img src="image_39.png" /><figcaption>Figure 6</figcaption></figure>
<figure><img src="image_40.png" /></figure>
<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" /></figure>
<figure><img src="image_45.png" /><figcaption>Extended Data Fig. 2</figcaption></figure>
<figure><img src="image_46.png" /><figcaption>B</figcaption></figure>

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

Reactivation timing
(Sugimoto and Abe, 2007)

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

Reactivation classes

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

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

Xist RNA entry sites

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

Xist RNA entry sites

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

Xist RNA entry sites

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

Xist RNA entry sites
<figure><img src="image_54.png" /><figcaption>B</figcaption></figure>

<figure><img src="image_55.png" /></figure>

Extended Data Fig. 4
<figure><img src="image_56.png" /><figcaption>B</figcaption></figure>

<figure><img src="image_57.png" /></figure>
<figure><img src="image_58.png" /><figcaption>B</figcaption></figure>

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

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

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

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

B

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