BMP4 drives primed to naïve transition through PGC-like state

Yu, Shengyong; Zhou, Chunhua; He, Jiangping; Yao, Zhaokai; Huang, Xingnan; Rong, Bowen; Zhu, Hong; Wang, Shijie; Chen, Shuyan; Wang, Xialian; Cai, Baomei; Zhao, Guoqing; Chen, Yuhan; Xiao, Lizhan; Liu, He; Qin, Yue; Guo, Jing; Wu, Haokaifeng; Zhang, Zhen; Zhang, Man; Zhao, Xiaoyang; Lan, Fei; Wang, Yixuan; Chen, Jiekai; Cao, Shangtao; Pei, Duanqing; Liu, Jing

doi:10.1038/s41467-022-30325-4

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Published: 19 May 2022

BMP4 drives primed to naïve transition through PGC-like state

Nature Communications volume 13, Article number: 2756 (2022) Cite this article

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Abstract

Multiple pluripotent states have been described in mouse and human stem cells. Here, we apply single-cell RNA-seq to a newly established BMP4 induced mouse primed to naïve transition (BiPNT) system and show that the reset is not a direct reversal of cell fate but goes through a primordial germ cell-like cells (PGCLCs) state. We first show that epiblast stem cells bifurcate into c-Kit⁺ naïve and c-Kit⁻ trophoblast-like cells, among which, the naïve branch undergoes further transition through a PGCLCs intermediate capable of spermatogenesis in vivo. Mechanistically, we show that DOT1L inhibition permits the transition from primed pluripotency to PGCLCs in part by facilitating the loss of H3K79me2 from Gata3/6. In addition, Prdm1/Blimp1 is required for PGCLCs and naïve cells, while Gata2 inhibits PGC-like state by promoting trophoblast-like fate. Our work not only reveals an alternative route for primed to naïve transition, but also gains insight into germ cell development.

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Introduction

Pluripotency is defined as the ability to generate all cell types in an individual by a single cell. In mice, it has been well established that two distinct, yet interconvertible, states exist, namely naïve and primed pluripotency represented by ESCs (Embryonic Stem Cells) and EpiSCs (Epiblast Stem Cells)^1,2,3. Despite both referred to pluripotency, they differ markedly in morphology, gene expression profile, conditions for maintenance, epigenetic state, chimeric competence, and germline contribution¹. From an embryological perspective, naïve and primed pluripotency represent the developmental potentials of pre- and post- implantation embryos, respectively¹. Therefore, a detailed investigation of both states may deepen our understanding of early embryo development.

The interconvertibility between naïve and primed states has been well documented^4,5,6,7,8. For example, naïve ESCs can be differentiated into primed state closely resembling EpiSCs^9,10. Likewise, EpiSCs have been converted to the naïve state similar to ESCs^4,5. Unlike the differentiation of ESCs to the primed state, the reprogramming of EpiSCs towards naïve state has been largely accomplished by over-expressing transcription factors (TFs)^{5,11,12,13,14,15,16}, similar to the iPSCs (Induced Pluripotent Stem Cells) pioneered by Yamanaka and colleagues¹⁷. Recently, we have established a BMP4 induced primed to naïve transition (BiPNT) system without any exogenous TF expression, and show that a 3-day exposure of EpiSCs in BMP4, DOT1L inhibitor and EZH2 inhibitor followed by a 5-day culture in 2iL can convert the majority (~80%) of the primed cells into chimera-competent naïve colonies¹⁸. Through RNA-seq and ATAC-seq bulk analyses, we demonstrated that many downstream targets of BMP4, including the previously unrecognized Zbtb7 family members, are activated through chromatin remodeling events for the resetting of primed to naïve states¹⁸. Even though it is still unclear if there are intermediates governing the resetting of primed into naïve state by BMP4 or the precise cell dynamics during this resetting process, as distinct molecular routes have been shown to mediate the acquisition of naïve pluripotency with different TFs and signals¹⁹.

Here we report the cell fate continuum between primed and naïve states generated by BMP4 with intermediate states previously masked in bulk analysis. Specifically, our data reveal a Prdm1-dependent PGCLCs intermediate governing BiPNT.

Results

Single-cell atlas of BMP4 induced primed to naïve transition

We have established a robust BMP4 induced primed to naïve transition (BiPNT) system¹⁸, that can convert ~80% EpiSCs to chimera-competent naïve colonies. To map the cell fate continuum, we performed scRNA-seq from cells that are at D0, 1, 2, 3, 5, and 8 (Fig. 1a). Analysis with t-SNE methods yielded well segregated clusters for cells at each day (Fig. 1b), indicating distinct stages of cell fate transition during BiPNT. Indeed, distinct gene expression profiles can be observed from D0 to D8 using representative genes from primed to naïve state (Fig. 1c).

**Fig. 1: Single-cell analysis for BiPNT.**

To further identify the cell populations at two stages, we analyzed single cells from D0–3 at stage 1 in detail and identified that many cells emerged at D3 have naïve pluripotency program genes (Fig. 1d). Among those genes, Klf2, Dppa5a, and Dppa3 are almost exclusively expressed in D3 cluster (Fig. 1d, lower panels). Interestingly, we also found cells in D3 expressing some trophoblast marker genes, such as Plac1, Gata2, Krt8, and Peg10 (Fig. 1d, middle panels). These results suggest that EpiSCs undergo fate transitions towards trophoblast-like and naïve-like pluripotency cells at stage 1.

2iL is a well-known condition for maintaining naïve pluripotent state²⁰. When the BMP4-treated cells were switched to 2iL condition, it is expected that they can be further matured into naïve pluripotency. Indeed, scRNA-seq confirms naïve pluripotent cells between D5 and D8 (Fig. 1e), suggesting that 2iL has further reprogrammed the cells in D3 into naïve state. We can also observe minor populations in both D5 and D8 cultures as trophoblast-like (Fig. 1e).

We then plotted the cells with naïve- and trophoblast-like programs to show that BMP4 induces almost equal numbers for each fate up to D2, but the naïve fate continues to increase while the trophoblast-like fate levels off (Fig. 1f). Apparently that 2iL continues to support the increase of the naïve fate as expected while the trophoblast-like ones begin to diminish at D5 (Fig. 1f). Thus, we can conclude that two primary fates emerge in BMP4-treated EpiSCs and 2iL favors the naïve fate while partially suppressing the trophoblast-like program (Fig. 1f). Gata2, which is highly expressed in trophoblast but not in naïve pluripotent stem cells, plays an important role in trophoblast development^21,22. To further trace the generation of these two cell fates in vitro, EpiSC cell line carrying both ΔPE-Pou5f1 (also known as Oct4) -GFP²³/Gata2-tdTomato reporters was constructed and then undergoes BiPNT (Supplementary Fig. 1a). Results from both fluorescence microscope in situ (Fig. 1g) and FACS (Supplementary Fig. 1b) show that, the naïve signal (ΔPE-Oct4-GFP) and trophoblast signal (Gata2-tdTomato) are incompatible and mutually exclusive to each other, confirming two discrete cell types at the end of BiPNT.

We further analyzed the identity of those trophoblast-like cells by comparing the gene expression profiles of D5/D8 trophoblast-like cells to the published reference dataset²⁴, and show by Sankey plot that the majority (87.53%) of D5/D8 trophoblast-like cells can be classified into ExE (extra-embryonic) ectoderm, while 7.97% cells are difficult to be classified (5.14%, Rejected; 2.83%, Ambiguous), with very few cells can be classified as ExE endoderm, ExE mesoderm, or other cell types (Supplementary Fig. 1c). Noteworthily, the amnion markers such as Isl1 and Igfbp3 are exclusively expressed in those D5/D8 Elf5 positive trophoblast-like cells (Supplementary Fig. 1d), which can distinguish them from the amnion cells.

c-Kit marks the naïve branch

To further resolve the apparent naïve versus trophoblast-like fate choices in D2 and D3, we re-analyzed the scRNA-seq data with Harmony²⁵, a program designed to resolve branches or trajectories along cell fate continuum. Harmony resolves the cells into two main branches, the trophoblast branch (TB) and naïve branch (NB) as expected (Fig. 2a, b). While the TB is enriched with imprinted genes such as Igf2, Peg10, H19 and trophoblast genes Gata2, Tead3, the NB expresses Dppa5a, Klf2, and Nanog, mostly naïve-related genes (Fig. 2b). Consistent with the naïve- and trophoblast-dichotomy, the TB is enriched with genes from trophoblast-like fate while the NB with those from the naïve-like fate (Fig. 2c).

**Fig. 2: c-Kit is a key marker for successful BiPNT.**

We then searched for cell surface markers that may distinguish the NB from the TB. Among a group of cell surface markers (Supplementary Fig. 2a), we found that Kit (also known as c-Kit) is a good candidate (Fig. 2d). c-Kit begins to be expressed at D1 and persists in the NB significantly (Fig. 2d). When plotted along the pseudotime, it becomes very clear that c-Kit begins to diverge at early phase of PNT that the NB maintains its expression while the TB diminishes (Fig. 2e), suggesting that c-Kit may help mark the NB. To test this idea, we sorted D3 cells with c-Kit-APC and show that ~50% of D3 cells are c-Kit positive (c-Kit ⁺) (Fig. 2f). By replating the sorted c-Kit⁺ and c-Kit⁻ cells separately and culturing them in 2iL, we show that almost all (94.2%) of c-Kit⁺ cells become GFP positive compared to 0.7% for c-Kit⁻ cells (Fig. 2g).

We further performed RNA-seq to investigate the difference between Day 3 c-Kit⁺ and c-Kit⁻ population (Fig. 2h), and show that 1102 genes are highly expressed in c-Kit^– cells, including the trophoblast markers Plac1, Gata2, and Krt8, while 1065 genes are specifically expressed in c-Kit⁺ cells including pluripotency genes Pou5f1, Sox2, Nanog, Esrrb, Klf2, and more interestingly, T and Prdm1 (also known as Blimp1) (Fig. 2h). GO (gene ontology) analysis reveal that programs such as embryonic placenta development, endothelial cell migration, and placenta development are highly enriched in c-Kit⁻ cells, while those involved in gastrulation, BMP signaling pathway, non-canonical Wnt signaling pathway are highly enriched in c-Kit⁺ cells (Fig. 2i).

Given c-Kit and Prdm1 are well-known primordial germ cell (PGC) markers²⁶, we then detected the expression of other PGC markers in Day3 sorted c-Kit⁺ cells by RT-qPCR. PGC genes such as Dppa3 (also known as Stella), Nanos3 and Ifitm1/3 are also highly expressed in c-Kit⁺ cells, while trophoblast genes such as Plac1 and Gata2 are highly expressed in c-Kit⁻ cells (Fig. 2j). Consistently, we also detected stronger ATAC-seq signaling in loci for PGC genes such as Nanog, Prdm1, and Prdm14 in c-Kit⁺ cells, as well as for trophoblast genes such as Plac1, Gata2, and Elf5 in c-Kit⁻ cells (Supplementary Fig. 2b). Together, these results suggest that c-Kit marks the naïve branch quite early among BMP4-treated cells.

Activation of a PGC-like program during BiPNT

The enrichment of PGC markers in Day 3 c-Kit⁺ cells (Fig. 2h, j) warrants further analysis. We then generated a pseudotime plot of NB during PNT and found it can be generally divided into four distinct phases (I–IV) (Fig. 3a). The first phase (I) is mainly cells expressing genes enriched in the primed fate, such as Otx2, Dnmt3b, and Fgf5. The second phase (II) includes cells that appear to express genes enriched for mesoderm like PGC precursor²⁷, such as Msx1/2, Cdx2, T, and Prdm1. The third phase (III) are cells expressing genes enriched in early PGC, such as Prdm14, Tfap2c, Dppa3, Nanos3, and Dnd1. And the last phase (IV) contains cells with naïve pluripotency features, such as Klf4 and Tbx3 (Fig. 3a). Consistently, heatmap generated with Harmony also indicates a continuous cell fate transition from primed pluripotency, PGC precursor, early PGC, then end with naïve pluripotency along the NB (Fig. 3b).

**Fig. 3: Activation of PGC-like program during successful BiPNT.**

To distinguish the putative early PGC-like cells (PGCLCs) from naïve pluripotent cells, we detected the expression of KLF4 in ΔPE-Oct4-GFP positive cells by immunofluorescence (IF) at Day 6 and Day 8 during BiPNT²⁸. Since PGC and naïve pluripotent cells are both positive for ΔPE-Oct4-GFP^4,23, the emergence of GFP⁺ /KLF4⁻ cells suggest the existence of a PGCLCs fate before reaching to naïve pluripotency during BiPNT (Supplementary Fig. 3a, b). We then quantified the putative PGCLC population with two documented PGC cell surface markers SSEA1 and CD61 by fluorescence-activated cell sorting (FACS) and show that 16.1% cells are SSEA1⁺/CD61⁺ at Day 6 BiPNT (Supplementary Fig. 3c).

To further investigate the PGCLCs emerged in BiPNT, we generated EpiSC cell line from ESC bearing Blimp1-mVenus (BV) and Stella-ECFP (SC) transgenes to monitor the PGCLCs fate²⁹. Data from FACS and fluorescence microscope show that, Prdm1/Blimp1-mVenus is activated significantly when stimulated with Stage 1 medium, and reaches to a peak at 89% at Day 1, while the expression of Stella-ECFP is upregulated specifically when changed to 2iL medium, and the percentage of double positive for BVSC (BV⁺SC⁺) cells reaches to a peak at 13% at Day 6 (Fig. 3c and Supplementary Fig. 3d). In addition, the higher expression of Prdm1, Prdm14, Tfap2c, and Dppa3 while the lower expression of naïve genes Klf4 and Tbx3 in Day 6 BV⁺SC⁺ cells distinguish them from naïve pluripotent cells (Fig. 3d). These data indicate an efficient Primed-PGCLC transition (PP_GT) before reaching to naïve pluripotency during BiPNT.

We further tested the GK15 or GK15 + cytokines (BMP4/SCF/EGF/LIF) culture conditions, which were used for PGC specification from ESCs previously^30,31, for their ability in PGCLCs induction at stage 2, and show by FACS that, BV⁺SC⁺ cells can be generated in both conditions (GK15 ~ 4.81%, GK15 + cytokines ~ 10.2%) (Supplementary Fig. 3e). These data suggest that the Day3 BiPNT cells have acquired the potential for germline specification.

To further capture the process of PGCLC-Naïve transition (P_GNT), we performed immunostaining for naïve pluripotent marker KLF4, and show that the sorted Day 6 BV⁺SC⁺ cells, when re-plated in 2iL medium, convert from KLF4⁻ cells to KLF4⁺ colonies gradually (Fig. 3e, f), suggesting a clear cell fate transition from PGCLCs to Naïve pluripotency.

Together, these results suggest a PGCLCs state along the NB branch during BiPNT.

Characteristics of BV⁺SC⁺ PGCLCs

To further characterize the Day6 BV⁺SC⁺ cells, we performed RNA-seq and compared our data to the published datasets which containing Day 4/Day 6 PGCLCs from ESCs in vitro or primary PGCs (E9.5,11.5,13.5) in vivo^32,33. PCA analysis reveals that the transcriptomes of the BV⁺SC⁺ cells are similar to D4 and D6 in vitro PGCLCs, and to a less extent to in vivo E9.5 PGCs (Fig. 4a). We then evaluated the epigenetic profiles of Day6 BV⁺SC⁺ cells. IF analysis reveals a reduced H3K9me2 and increased H3K27me3 in Day 6 BV⁺ cells (Fig. 4b), which are further confirmed by western blot (Fig. 4c), and consist with previous report³¹. We further determined the methylation states of maternally (H19) and paternally (Snrpn) imprinted genes in Day 6 BV⁺SC⁺ cells and show that whereas the DNA methylation in Snrpn loci is retained, the methylation states of H19 loci reduced significantly, suggesting that Day 6 BV⁺SC⁺ cells may undergo a process of imprint erasure (Fig. 4d). Consistently, RT-qPCR analysis also shows the downregulation of de novo DNA methyltransferases Dnmt3a/b as well as Uhrf1, a critical regulator which recruits Dnmt1 to hemi-methylated DNA (Supplementary Fig. 4a). Notably, BV⁺SC⁺ cells cultured in 2iL medium for one passage show a quick loss of Blimp1 and can further form naïve-like colonies (Supplementary Fig. 4b). We further performed blastocysts microinjection experiments for the sorted BV⁺SC⁺ cells to determine their chimera formation ability (Supplementary Fig. 4c). Comparing with these naïve-like cells, Day 6 sorted BV⁺SC⁺ cells showed a poor chimera ability (12.5% versus 66.7%) (Supplementary Fig. 4c), consist with previous observations that PGCs cannot contribute to chimera, despite expressing naïve pluripotency genes^28,34,35.

**Fig. 4: Characterization of PGC-like cells.**

To further determine the capacity of the Day 6 sorted BV⁺SC⁺ cells in spermatogenesis, we transplanted them into the seminiferous tubules of neonatal W/W^v mice lacking endogenous germ cells^31,36,37. Notably, 3 months after transplantation, tubules with normal spermatogenesis, which express the spermatogonia markers (DDX4 and PLZF), spermatocytes markers (SYCP3 and γH2AX), and spermatids markers (DDX4 and PNA) can be detected in two out of six testes sections transplanted with BV⁺SC⁺ cells, while only Sertoli cells in the tubules of control group (Fig. 4e, f and Supplementary Fig. 4d). These results confirm that Day 6 BV⁺SC⁺ cells are PGCLCs.

Prdm1-KO blocks the generation of PGCLCs and naïve pluripotency

To test whether PGCLCs are intermediates for the acquisition of naïve pluripotency, we knocked out Prdm1, a factor which is obligatory for PGC specification but not for pluripotency maintenance^38,39, in ΔPE-Oct4-GFP EpiSCs by CRISPR/Cas9 (Supplementary Fig. 5a–c). The Prdm1^−/− EpiSCs exhibited indistinguishable morphology from wild-type (WT) EpiSCs and expressed comparable levels of primed pluripotency markers such as Oct4, Sox2, and Otx2 (Fig. 5a and Supplementary Fig. 5d). However, when undergoing BiPNT, no GFP⁺ cells can be observed from Prdm1^−/− cells, while the lentivirus-mediated overexpression of exogenous Prdm1 can rescue this defect (Fig. 5b and Supplementary Fig. 5e, f). These data indicate that Prdm1 is essential for the generation of PGCLC or naïve cells during BiPNT.

**Fig. 5: PGCLCs mediate the successful BiPNT.**

To further investigate the role of Prdm1 in the cell trajectories during BiPNT, we performed single-cell analysis. To this end, we collected scRNA-seq data for Prdm1^−/− EpiSCs undergoing BiPNT at corresponding time point same with WT EpiSCs (Fig. 5c). By comparing WT and Prdm1^−/− samples using UMAP, we show that the separation between WT and Prdm1^−/− populations occurs initially on Day1, and obviously on Day2 and Day3 (D2–3) (Fig. 5d). We further compared the expression pattern of selected genes between WT and Prdm1^−/− scRNA-seq data, and show by heatmap that Prdm1-KO almost totally abolishes the activation of Nanos3, Dppa3, Dppa5a, and Zfp42, and also blocks, in varying degrees, the expression of Snrpn, Ifitm1, Klf2, and Sox2, while significantly increases the expression of the trophoblast genes, such as Plac1, Igf2, and Ahnak (Fig. 5e). RT-qPCR analysis further confirmed the expression pattern of these indicated genes (Fig. 5f).

The derived naïve cells in BiPNT show a distinctive methylation state from the EpiSCs and ESCs in loci of Mest (also known as Peg1), Peg3 and Snrpn (Supplementary Fig. 5g), which may suggest their embryonic germ cell (EGC)-like feature. Furthermore, although the addition of JAK inhibitor in second stage of BiPNT can induce ΔPE-Oct4-GFP⁺ cells, they are almost negative for KLF4 (Supplementary Fig. 5h, i), indicating the block for the formation of naïve cells/EGC from PGCLCs, which is consistent with previous report that LIF/Stat3 signal is indispensable for PGC to EGC transition⁴⁰. Together, these results suggest that Prdm1-dependent PGCLCs are the essential intermediates for naïve branch in BiPNT.

DOT1Li restores PGCLC competence for primed pluripotency

Developmentally, primed EpiSCs have lost the PGC competence³¹. The emergence of PGCLCs during BiPNT offers an ideal model in vitro to investigate the epigenetic barrier(s) established during PGC development in vivo. To this end, we performed dropout assay to compounds in stage 1 (S1) medium for identifying the critical factor(s) for PP_GT, and show that, the withdrawal of EPZ5676, a DOT1L inhibitor, blocks the induction of BV⁺SC⁺ PGCLCs significantly, while the addition of SGC0946, another specific DOT1L inhibitor, can rescue this defect, and seems even more potent than EPZ5676 (Fig. 6a). RT-qPCR analysis further validates the activation of PGC markers such as Prdm1, Dppa3, Nanos3, and Prdm14 by DOT1L inhibitors (DOT1Li) (Fig. 6b and Supplementary Fig. 6a). Notably, DOT1L inhibition leads a significant repression for trophoblast markers such as Gata2 or Plac1 in late stage (Day 6) (Supplementary Fig. 6a), but not in early stage (Day 3) during BiPNT (Fig. 6b). These data indicate that DOT1L inhibition is critical for restoring PGCLC competence from EpiSCs and hinders trophoblast fate in late stage of BiPNT.

**Fig. 6: DOT1L inhibitor is responsible for the induction of PGCLCs from EpiSCs.**

To gain any insight on how DOT1Li helps the restoring of PGCLC competence from EpiSCs, we performed RNA-seq in samples with or without DOT1Li (SGC0946) at Day3 BiPNT to probe the downstream targets and show that 330 genes, including the PGC markers Prdm1 or PGC/Naïve pluripotency markersTfap2c, Nanos3, Nanog and Klf2 are upregulated, while 128 genes, including the HOX/GATA family members, such as Hoxa5/6/7/10, Hoxb2/3/4/6, Hoxc4/6/8/10/11, Hoxd9 and Gata3/6, are downregulated, by DOT1Li treatment, respectively (Fig. 6c). GO analysis shows that terms enriched in DOT1Li upregulated genes are involved in Wnt and BMP signaling pathway (Supplementary Fig. 6b), both of which are necessary for PGC specification as reported previously^27,41, while for terms enriched in DOT1Li downregulated genes are largely associated with lineage differentiation, such as embryonic skeletal system morphogenesis and limb morphogenesis (Supplementary Fig. 6b).

As chromatin accessibility dynamics (CAD) plays critical roles in gene expression regulation, we performed ATAC-seq, as done before¹⁸, to investigate the effect of DOT1L inhibition on CAD at Day3 BiPNT, and show by heatmap that DOT1Li leads to chromatin OC (Open to Close) in 4831 loci (Fig. 6d), among which binding motif for TFs such as GATA1/2/3/4/6, HOXA9, HOXB4, HOXC9, HOXB13, and CDX2, could be enriched (Fig. 6e), while leads to chromatin CO (close to open) in 3251 loci(Fig. 6d), among which binding motif of PGC regulators or pluripotency factors such as NANOG, TFAP2C, OCT2/4/6 and ZIC1/3, could be enriched (Fig. 6e).

Based on the RNA-seq and ATAC-Seq data, we further tested a set of candidate transcriptional factors for their effect on BV⁺SC⁺ cells induction, and show that the BV⁺SC⁺ cell induction efficiency is promoted by overexpression of Nanog or Tfap2c separately (Nanog, 1.11–15.7%; Tfap2c, 1.11–11.2%) (Fig. 6f), and can be further increased up to 22.8% by Nanog and Tfap2c co-expression when DOT1Li withdrawing (Fig. 6f and Supplementary Fig. 6c). In addition, when DOT1Li is present, the overexpression of Nanog or Tfap2c, separately or together, can further increase the BV⁺SV⁺ cells induction efficiency (Supplementary Fig. 6c). In contrast, the overexpression of Gata3 or Gata6, two genes downregulated by DOT1Li, reduces the induction efficiency of BV⁺SV⁺ cells (Fig. 6f and Supplementary Fig. 6d). RT-qPCR analysis further confirmed the repression of PGC-related genes such as Nanog, Prdm1, Dppa3 and Nanos3 at Day3 BiPNT by the overexpression of Gata3 or Gata6 (Supplementary Fig. 6e).

DOT1L is a highly conserved histone methyltransferase that catalyzes H3K79 methylation⁴², which is mainly found in active genes⁴³. To gain insight into the relationship between H3K79 methylation and PGCLCs induction, we first performed western blot and show a significant decrease in global H3K79me2 at Day3 BiPNT upon DOT1Li (both EPZ5676 and SGC0946) treatment (Supplementary Fig. 6f). We then performed H3K79me2/H3K27me3 ChIP-seq for Day3 Cells with or without DOT1Li (SGC0946) treatment, and show that DOT1L inhibition leads a global loss of H3K79me2 (Fig. 6g). When analyzing the correlation between H3K79me2 and gene expression, we found that 30.6% upregulated genes, 58.0% downregulated genes, and 79.1% genes without change are marked by H3K79me2, respectively (Fig. 6h). Specifically, for genes such as Gata3 and Gata6, the loss of H3K79me2 is associated with increased deposition of H3K27me3, and downregulation in mRNA (Fig. 6i), consistent with a role of H3K79me2 for active transcription⁴³. For PGC genes such as Nanog, Prdm1, Tfap2c, and Nanos3, the loss of H3K79me2 is independent to H3K27me3, and associated with an upregulation in mRNA upon DOT1L inhibition (Fig. 6i). Since downregulated genes seem more sensitive to H3K79me2 (Fig. 6h), we further performed loss of function test for Gata3/6 in BV⁺SV⁺ cells induction, and show that Gata3 or Gata6 knockout (KO) can facilitate the induction of BV⁺SV⁺ cells in the absence of DOT1Li (Fig.6j, k and Supplementary Fig. 6g–j). RT-qPCR further confirmed the upregulation of PGC-related genes such as Nanog, Prdm1, Nanos3, and Dppa3 in Gata3- or Gata6-KO Cells (Supplementary Fig. 6k). In addition, DOT1Li can enhance the efficiency of BV⁺SC⁺ cell induction in Gata3- or Gata6-KO EpiSCs, comparing with WT EpiSCs (Fig. 6k).

Taken together, these data suggest that DOT1L inhibition promotes PP_GT in part by facilitating the loss of H3K79 methylation from Gata3/6 and repressing their expression.

Gata2 gates trophoblast-like whereas hampers PGCLC program

To further determine the key events for early cell fate choice during BiPNT, we reanalyzed the scRNA-seq data at D0, D1, and D2 by UMAP. We found a significant cell diversity at D2 (Fig. 7a). Heatmap for representative genes show an activation of trophoblast signal (Gata2, Plac1) as early as Day 1 (Fig. 7b), and a diversity of pluripotent signal (Dppa3, Nanog) at Day 2 (Fig. 7b), suggesting an early cell fate choice. To further investigate the key factor(s) regulate this cell fate choice, we use pySCENIC⁴⁴ to predict the regulon of each cell subgroup and heatmap illustrated a widely activation of early BMP4 response regulons, such as Id1, Cdx2, Tfap2c, and a separate pattern for regulons Prdm1 (PGC) and Gata2 (Trophoblast) at D2 populations (Fig. 7c and Supplementary Fig. 7a). The Prdm1-KO almost abolished PNT, indicating Prdm1 as a key regulon for PGC-Naïve trajectory. To test whether Gata2 is a regulon specific for trophoblast trajectory, we generated two independent Gata2-KO EpiSC cell lines in BVSC EpiSCs by CRISPR/Cas9 (Supplementary Fig. 7b, c). These two cell lines express comparable levels of primed pluripotency markers (Supplementary Fig. 7d). Comparing with WT, Gata2-KO shows a significant increase of BV⁺ cells at Day3 and BV⁺SC⁺ cells at Day6 during BiPNT (Fig. 7d). Consistently, RT-qPCR analysis shows almost abolishment in trophoblast signal such as Plac1, Peg10, and Phlda2, and a significant increase in PGC-like signal such as Prdm1, Prdm14, Dppa3, and Nanos3 in Gata2-KO cells during BiPNT (Fig. 7e). We further sorted c-Kit for WT and two Gata2-KO cell lines and show that Gata2-KO leads to a significant increase of c-Kit⁺ population at Day3 BiPNT (WT ~ 53%, KO1# ~ 76.2%, KO2# ~ 75.4%) (Supplementary Fig. 7e). RT-qPCR analysis further confirmed the loss of trophoblast markers in Gata2-KO c-Kit⁻ cells (Supplementary Fig. 7f). These data suggest that Gata2-KO results in an early alteration of lineage trajectories during BiPNT, which turns off the trophoblast-like program while facilitates the PGC-like program.

**Fig. 7: Deficiency of Gata2 hinders trophoblast fate but promotes PGCLCs.**

Discussion

In this report, by performing scRNA-seq to a previous well-established PNT process driven by BMP4 (BiPNT)¹⁸, we generated a cell fate continuum between primed and naïve pluripotency states and show that the trajectories of BiPNT can bifurcate into c-Kit⁺ naïve and c-Kit⁻ trophoblast-like branches. Surprisingly, the naïve branch, as shown here (Fig. 8), in single-cell level, goes through a PGC-like intermediate, which links PNT with two distinctive while continuous cell fate transitions, here they were termed as Primed to PGCLC transition or PP_GT, and PGCLC to Naïve transition or P_GNT, respectively. Our finding shows a unique landscape for resetting the stable mouse primed pluripotent state into a naïve pluripotent one by linking an important developmental intermediate state therefore sheds light on the mechanism of cell reprogramming and differentiation.

**Fig. 8: Schematic diagram of cell fate trajectories during BiPNT.**

Prdm1 and PGC-like cells have been demonstrated to be dispensable for the derivation and maintenance of ESCs as well as the reprogramming of EpiSCs into rESCs^39,45. The obligatory role of Prdm1 in our study may be due to the differences of induction systems, e.g., BMP4, a key growth factor known for driving PGC/PGCLC specification. In addition, we previously showed that BMP4 is able to activate naïve or PGC-related genes such as Klf2, Esrrb, Tfap2c, and Dppa3¹⁸, which further underlines the PGCLC intermediates for recapturing naïve pluripotency in BiPNT. Actually, the BV⁺SC⁺ cells induced during BiPNT exhibited PGC features, including upregulation of early PGC markers, increase of H3K27me3 and reduction of H3K9me2, erasure of imprinting, poor contribution to blastocyst chimeras and contribution to spermatogenesis, indicating their PGCLCs fate. It’s of great interest to test the function of the sperm/spermatids generated from those BV⁺SC⁺ cells in future.

In mice, permissiveness for PGC specification is unique to formative epiblast cells (i.e., E5.0–E6.0 epiblast, EpiLCs) or PSCs with formative pluripotency^31,41,46,47. The primed EpiSCs, which corresponding to E6.5 epiblast, have lost the competence of PGC responsiveness^31,41. Nevertheless, in BiPNT system, a PGC-like program is robustly activated from the primed EpiSCs. The critical role of DOT1Li identified here indicates H3K79 methylation may act as an epigenetic barrier for PP_GT. Mechanistically, DOT1Li promotes the generation of PGCLC partially through removing H3K79me2 from lineage genes such as Gata3 and Gata6, leading to their repression (Fig. 8). Interestingly, DOT1Li mediated loss of H3K79me2 is also observed at chromatin loci of upregulated genes, such as PGC genes Tfap2c, Prdm1, Nanos3, etc. Indeed, H3K79 methylation has been linked to transcriptional repression in some cases^48,49,50,51, suggesting a context dependent manner for H3K79 methylation on transcriptional regulation. However, as a secondary effect of DOT1Li on activation of PGC genes may exist, future study is needed to investigate whether H3K79me2 also play a repressive role in BiPNT as well as the underlying mechanism.

Methods

Mice

129 Sv/Jae and ICR mice were purchased from Beijing Vital River Laboratory, and ΔPE-Oct4-GFP (OG2) transgenic allele-carrying mice (CBA/CaJ X C57BL/6 J) were purchased from The Jackson Laboratory. W/W^v mice were provided by Dr. Xiaoyang Zhao. All animal experiments were operated under the Animal Protection Guidelines of Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.

EpiSCs derivation and cell culture

Mouse EpiSCs were derived from E5.5 mouse embryos by crossing male homozygous ΔPE-Oct4-GFP transgenic allele-carrying (CBA/CaJ X C57BL/6 J) with 129 Sv/Jae female mice, following the described protocols^3,52. After culturing on feeder for the first 4–8 passages, stable EpiSCs were maintained feeder-free on fetal bovine serum (FBS)-coated dishes in N2B27 + bFGF (15 ng/ml, PeproTech) + Activin A (20 ng/ml, PeproTech) + XAV939 (1 μM, Selleck) (FAX) medium. N2B27 medium comprised equal volume of DMEM/F12 (GIBCO) and Neurobasal (GIBCO), 0.5% N2 (GIBCO), 1% B27 (GIBCO), 1% GlutaMAX (GIBCO), 1% non-essential amino acids (NEAA) (GIBCO) and 0.1 mM β-mercaptoethanol (GIBCO). EpiSCs were dissociated with Accutase (Sigma) and passaged as singular cell with FAX medium in the presence of 5 μM Y27632 (Selleck) at ~20,000 cells in a well of 12-well plate every 3 days. The medium was refreshed daily.

Mouse ESCs were maintained feeder-free on 0.1% gelatin-coated dishes in N2B27 medium supplemented with 2i/LIF medium as described¹⁸.

Derivation of EpiSCs from mouse BVSC-ESCs

Mouse BVSC-ESCs were dissociated into single cells using 0.05% Trypsin-EDTA and were plated at a density of 2–5 × 10⁴ in a well of 12-well plate coated with FBS in N2B27-2iL medium. The next day, medium was changed to FAX medium for 3 days and then re-plated at a ratio of 1:10. Cells were passaged with Accutase every 3 days. Experiments were performed between P8 and P20.

BMP4 induction of EpiSCs into naïve state

Reprogramming of EpiSCs into naïve state was performed with our protocol published previously with minor modification¹⁸.

Reagents setup

Stage 1 medium: iCD1 medium⁵³ comprised Vitamin C (50 μg/ml, Sigma), bFGF (10 ng/ml), LiCl (5 mM, Sigma), LIF (1000 U/ml, Millipore) and CHIR99021 (1 μM, synthesized in GIBH), with the addition of BMP4 (5–10 ng/ml, R&D Systems), EPZ6438 (1 μM, TargetMol) and EPZ5676 (2.5 μM, TargetMol) or SGC0946 (1 μM, TargetMol). In some experiments, we also added 2 μM Parnate (Selleck).

Stage 2 medium: N2B27-2iL medium comprised N2B27 medium with the supplement of 50 μg/ml Vitamin C, 1 μM PD0325901, 3 μM CHIR99021 and 1000 U/ml LIF.

2. EpiSCs were passaged with Accutase into singular cell and seeded at a density of 5,000 cells per well of 24-well plate coated with FBS in N2B27 + FAX medium with the addition of 5 μM Y27632. Next day, the medium was replaced with Stage 1 medium and changed daily for the first 3 days. The Stage 2 medium was refreshed daily for the last 5 days.

Flow cytometry

Cells were dissociated with 0.05% Trypsin-EDTA and neutralized with DMEM containing 10% FBS. After the dissociation, cells were collected by centrifugation and resuspended with flow cytometry buffer (DPBS with 0.1% BSA and 1 mM EDTA) at a density of 1 × 10⁶ cells per 100 μl buffer. Cells were then incubated with fluorophore-conjugated antibodies for 30 min at 4 °C. After incubation, cells were washed with DPBS for three times, resuspended with flow cytometry buffer, and filtered with 40 μm cell strainer to remove large clumps of cells. Cells were then analyzed with LSR Fortessa X-20 (BD Biosciences) or sorted with BD FACSAria III (BD Biosciences). The FACS data were analyzed with FlowJo 10.4 software.

The following antibodies were used: APC anti-c-Kit (eBioscience, 17-1171-83,1:200), Alexa Fluor 647 anti-mouse/human CD15 (SSEA-1) (BioLegend, 125607, 1:200), PE anti-mouse/rat CD61 (BioLegend, 104307, 1:500).

Immunofluorescence

The cells were seeded on coverslips and the fixed with 4% paraformaldehyde for 30 min at room temperature. The cells were washed with PBS once and subsequently soaked in the mixing buffer of equal volume of 0.1% Triton X-100 and 3% BSA for 1 h at room temperature. The cells were washed with PBS once, then incubated with primary antibody at 4 °C for overnight. The cells were washed with PBS five times next day, then incubated with appropriate secondary antibody for 1 h at room temperature. The cells were washed with PBS five times to remove the secondary antibody and counterstained with DAPI for 3 min and washed with PBS once. In the end, the coverslips were mounted on the slide for observation under the confocal microscope (Zeiss 710 NLO). Primary antibodies and secondary antibodies were diluted in 3% BSA. Primary antibodies used in this study were anti-KLF4 (R&D system, AF3158, 1:100), anti-H3K9me2 (Abcam, ab1220, 1:100), anti-H3K27me3 (Merck, 17–622, 1:200), anti-PRDM1 (Invitrogen, 14–5963–82, 1:50), anti-DDX4 (Abcam, ab13840, 1:400), anti-SOX9 (EMD Millipore, AB5535, 1:400), anti-PLZF (Santa Cruz, sc-28319, 1:100), anti-SYCP3 (Abcam, ab15093, 1:400), and anti-γH2AX (Abcam, ab26350, 1:400), anti-PNA (ThermoFisher, L21409, 10 μg/ml).

Western blot

1 × 10⁶ cells were harvested and lysed with 100 μL lysis buffer which containing 62.5 mM Tris-HCl (pH 6.8), 2% SDS, 10% glycerol, 0.025% bromophenol blue and 50 mM DTT with protease inhibitor cocktail (Roche) on ice for 5 min and boiled for 10 min at 100 °C. The samples were separated by 10–12.5% SDS-PAGE and transferred to a PVDF membrane (Millipore) using a wet transfer system, and then incubated with the primary antibodies and secondary antibodies. The following antibodies were used: anti-H3K9me2 (Abcam, ab1220,1:500), anti-H3K27me3 (Merck,17–622,1:2000), anti-H3 (Abcam, ab1791, 1:2000), anti-H3K79me2 (Active Motif, 39143, 1:1000), anti-PRDM1 (Invitrogen, 14–5963–82, 1:100) and anti-ACTIN (Sigma, A5441, 1:4000).

Transplantation of the BV⁺SC⁺ cells into Seminiferous Tubules of Neonatal W/W ^v Mice

Recipient animals (neonatal [10- to 15-day-old] W/W^v male mice lacking endogenous spermatogenesis) were induced into hypothermic anesthesia on ice. The glass needle with a 40 μm inner diameter was filled with 2 × 10⁵ cell/μL sorted BV + SC + cells and the donor cell suspension (~2 μl) was injected into the efferent duct of recipient W/W^v mice testis. Then the recipient animals were returned to their littermates after surgery and they were sacrificed by anesthesia at 2 months after transplantation and testicular tissue were fixed in 4% paraformaldehyde overnight at 4 °C for Immunofluorescence staining.

Quantitative RT-PCR

Total RNA was extracted using the TRIzol. cDNA was reversed transcribed by HiScript II Reverse Transcriptase (Vazyme biotech R222-01) from 2 μg of total RNA. Real-time quantitative PCR was performed with ChamQ^TM SYBR^® qPCR Master Mix (Vazyme biotech Q311-02). Relative expression values were normalized to Gapdh and analyzed with Microsoft Excel 2019. Each experiment was operated in technical triplicate. Primers for RT-qPCR were listed in Supplementary Data 1.

Gene editing in EpiSCs

Knockout EpiSCs lines were obtained by the CRISPR/Cas9 system. Guide RNAs (gRNAs) were designed in website: crispr.mit.edu., and cloned downstream of human U6 promoter of pX330 and pXP (modified from pX330, with the resistance of puromycin). For Prdm1, Gata2, Gata3 and Gata6 knockout, two pairs of gRNAs were designed to delete the critical exons. For establishing Gata2-tdTomato reporter, two pairs of gRNAs were used to make cleavages and a tdTomato cassette was targeted into exon1 of Gata2 by homologous recombination. The gRNAs and linearized donor plasmids were transfected with Lipofectamine 3000 (Thermo Fisher Scientific) in EpiSCs followed the guidance of manufacturer. 1 × 10⁵ cells were resuspended in FAX medium with Y27632 in one plate of the 12-well plate. After 8–10 h, the medium was changed with fresh FAX medium. Forty-eight hour post transfection, the cells were selected with puromycin for 3 days and 1000 cells were seeded on one well of the 6-well plate for colony formation. Singular colony were picked up and evaluated by genotyping. Primers for gRNAs were listed in Supplementary Data 2.

Bisulfite sequencing

The genomic purification kit (Promega) was used to isolate genomic DNAs, and EpiTect Bisulfite Kit (QIAGEN) was used to perform the bisulfite reactions. LA Taq (TaKaRa) was used to amplify differentially methylated regions of Snrpn, H19, Peg1, and Peg3. The PCR products were subcloned into the pMD-18T vector (TaKaRa), and then sequenced. The results were analyzed in quma.cdb.riken.jp. Primers were listed in Supplementary Data 3.

RNA-seq and data analysis

Total RNA was isolated. Sequencing libraries were prepared according to the VAHTS^TM mRNA-seq V3 Library Prep Kit for Illumina® (NR611-01/02, Vazyme) and sequenced using a NextSeq 500 High Output Kit V2 (75 cycles) (FC-404–1005, Illumina).

RNA-seq was proceeded as previously described¹⁸. Briefly, sequenced reads were aligned to the GENCODE annotations transcriptome (M13) using Bowtie2 (version 2.2.5)⁵⁴ and RSEM (version 2.4.1)⁵⁵, and normalized using EDASeq (version 2.4.1)⁵⁶. Differentially expressed genes were obtained using DESeq2 (version 1.22.1)⁵⁷ with P-value < 0.05 and fold change > 2 as a threshold. Gene ontology analysis was performed using goseq (version 1.22.0). PCA was performed using function prcomp.

ATAC-seq

ATAC-seq was executed as previously described¹⁸. Briefly, a total of 50,000 cells were washed with 50 μL cold PBS once, then centrifuged for 5 min at 500 g at 4 °C, then resuspended in 50 μL lysis buffer (10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl₂, 0.2% (v/v) IGEPAL CA-630) and incubated at 4 °C for 10 min. The suspension of nuclei was centrifuged for 5 min at 500 g at 4 °C, followed by the addition of 50 μL transcription reaction mix (10 μL 5X TTBL, 5 μL TTE Mix V50, and 35 μL nuclease-free H₂O) of TruePrep ^TM DNA Library Prep Kit V2 for Illumina® (TD501–503, Vazyme biotech) and incubated at 37 °C for 30 min. DNA fragments were purified by MinElute Kit (QIAGEN). ATAC-seq libraries were amplified by 13 cycles of amplification according to the TruePrep ^TM DNA Library Prep Kit V2 for Illumina® (TD501–503, Vazyme biotech), then the libraries were purified by a Qiaquick PCR (QIAGEN) column. Library concentration was detected by a VAHTS ^TM Human Genomic DNA Quantification and QC Kit (NQ201, Vazyme biotech) according to the manufacturer’s instructions. The concentration of ATAC library peaks was measured with Real-Time Quantitative PCR by detecting the differential expression of housekeeping gene (GAPDH) and negative genes. In the end, the ATAC library was sequenced on a NextSeq 500 using a NextSeq 500 High Output Kit V2 (150 cycles) (FC-404–2002, Illumina) according to the manufacturer’s instructions.

ChIP-seq and data analysis

ChIP assay was carried out as previously described⁵⁸. The cells were crosslinked with 1% formaldehyde for 10 min and then quenched by adding 125 mM glycine. Chromatin samples were lysed with lysis buffer (20 mM Tris-HCl, pH 8.0, 500 mM NaCl, 1 mM EDTA, 1% Triton X-100 and 0.1% SDS) and sonicated with Qsonica. Histone specific antibody was incubated with chromatin samples overnight at 4 °C. Antibodies used were as follows: H3K79me2 (Active motif, 39143), H3K27me3 (CST, 9733 S). About 5 × 10⁵ cells were used for each ChIP. We used 0.5 µg spike-in antibody (Active motif, 61686) and 25 ng spike-in chromatin (Active motif, 53083) in this ChIP assay according to the manufacturer’s guidelines. The protein-DNA complexes were immobilized on 15 µl protein A/G beads (Smart lifesciences, SA032005) and then washed three times with lysis buffer, twice with low salt buffer (10 mM Tris-HCl, 250 mM LiCl, 1 mM EDTA, 0.5% NP40, 0.5% Na-deoxylcholate) and once with TE buffer (10 mM Tris-HCl, pH 8.0). Decrosslinking was carried out in elution buffer (50 mM Tris-HCl, pH8.0, 10 mM EDTA, and 1% SDS) at 65 °C for at least 5 h. Proteinase K and RNase A digestions were performed at 55 °C for 1 h. DNA samples were purified with PCR extraction kit (QIAGEN, 28006). DNA samples were analyzed using real-time PCR and prepared for deep sequencing according to the manufacturer’s guidelines (Vazyme, ND607). Finally, libraries were pooled and sequenced on the Illumina NovaSeq 6000 sequencer with paired-end sequencing.

ChIP-seq data analysis were performed as previously described¹⁸. In brief, Sequenced reads were aligned to the mouse reference genome (mm10) using Bowtie2⁵⁴ with default parameters. Reads that mapped to mitochondrial DNA or unassigned sequences were discarded. For paired-end sequencing data, only concordantly aligned pairs were retained. Peaks were called using MACS2 (version 2.1.2)⁵⁹ with the default parameters. Alignment BAM files were transformed into read coverage files (bigWig format) using deepTools (version 2.5.4)⁶⁰ using the RPKM normalization method.

Single-cell sequencing

Cells at different induction time points of BiPNT were collected and resuspended in DPBS with 0.04% BSA. Then, cells suspensions (500–1000 cells per microliter) were loaded on a Chromium Single Cell Controller (10x Genomics) to obtain single-cell gel beads in emulsion (GEMs) by using Single Cell 3' Library and Gel Bead Kit V2 (10x genomics, 120237). Captured cDNAs were lysed and the released RNA were barcoded through reverse transcription in singular GEMs. Barcoded cDNAs were pooled and cleaned by DynaBeads® MyOne Silane Beads (Invitrogen, 37002D). Single-cell RNA-seq libraries were prepared by Single Cell 3' Library Gel Bead Kit V2 (10x Genomics, 120237) following the manufacturer’s instruction. Sequencing was operated on an Illumina HiSeq X Ten with pair end 150 bp (PE150).

Single-cell RNA-seq data analysis

Fastq reads were aligned to the genome using STARsolo⁶¹ with the setting '--outSAMattributes NH HI AS nM CR CY UR UY --readFilesCommand zcat --outFilterMultimapNmax 100 --winAnchorMultimapNmax 100 --outMultimapperOrder Random --runRNGseed 777 --outSAMmultNmax 1'. The count matrix was lightly filtered to exclude cell barcodes with low numbers of counts: Cells with <1000 UMIs, <500 genes or >20% fraction of mitochondrial counts were removed. The filtered matrix was normalized using scran⁶². The top 4000 most highly variable genes were used for PCA, and the first 50 PCs (principle components) were used for downstream analysis with SCANPY⁶³. Single-cell trajectory was analyzed by Harmony²⁵ and the top 1000 highly variable genes were used for PCA, and the force-directed layout was computed using first 150 PCs. The genes expression trajectories on pseudotemporal orderings of cells (Fig. 3a) were analyzed by LineagePulse (https://github.com/YosefLab/LineagePulse) according to the pseudotime generate from Harmony. The Prmd1 KO and WT scRNA-seq data batch effect was corrected by Seurat⁶⁴.

Statistics and reproducibility

No statistical method was used to predetermine the sample size. The experiments were not randomized. The investigators were not blinded to allocation during the experiment and outcome assessment. Data are presented as mean ± s.d. P-values were calculated using two-tailed unpaired Student’s t-tests with GraphPad Prism 6. P < 0.05 was considered to be statistically significant; *P < 0.05, **P < 0.01, ***P < 0.001. The exact P-values are indicated in relevant figures. The statistical test, numbers for sample sizes, and independent experiments are indicated in the figure legends.

Reporting summary

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

Data availability

The scRNA-seq, RNA-seq, ATAC-seq, and ChIP-seq data generated in this study have been deposited in the Gene Expression Omnibus (GEO) database under accession code GSE147088 Source data are provided with this paper. The source data underlying Figs. 2j, 3d, f, 4c, 5f, 6a, b, k, 7e and Supplementary Figs. 3b, 4a, 5d, i, 6a, c–e, k, 7d, f are provided as a Source Data file. The authors declare that all data supporting the findings of this study are available within the article and its supplementary information files or from the corresponding author upon reasonable request.

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Acknowledgements

We thank Dr. Mitinori Saitou for BVSC ESC cell lines. This work was supported by grants from National Natural Science Foundation of China (U20A2013 [C.Z.], 31970681 [J.L.], 32022019 [J.L.], 32100594 [C.Z.], 31421004 [D.P.], 31530038 [D.P.], 21907095 [S.C.]), The National Key Research and Development Program of China, (2016YFA0101800 [J.L.], 2017YFA0105001 [X.Z.], 2018YFE0204800 [J.L.]), Natural Science Foundation of Guangdong Province, China (2021A1515111156 [S.Y.]), Science and Technology Planning Project of Guangdong Province (2020B1212060052 [D.P.], 2019A1515011024 [S.C.]). Frontier Research Program of Bioland Laboratory (2018GZR110105012 [J.L.]). China Postdoctoral Science Foundation (2021000184 [C.Z.])

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These authors contributed equally: Shengyong Yu, Chunhua Zhou, Jiangping He.

Authors and Affiliations

Center for Cell Lineage and Development, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
Shengyong Yu, Chunhua Zhou, Hong Zhu, Shuyan Chen, Yue Qin, Jing Guo, Haokaifeng Wu, Zhen Zhang, Yixuan Wang, Jiekai Chen & Jing Liu
Center for Cell Lineage and Atlas, Bioland Laboratory, 510005, Guangzhou, China
Jiangping He, Baomei Cai, Guoqing Zhao, Lizhan Xiao, He Liu, Man Zhang, Jiekai Chen, Shangtao Cao & Jing Liu
State Key Laboratory of Organ Failure Research, Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
Zhaokai Yao, Yuhan Chen & Xiaoyang Zhao
Laboratory of Cell Fate Control, School of Life Sciences, Westlake University, Hangzhou, 310024, China
Xingnan Huang & Duanqing Pei
Shanghai Key Laboratory of Medical Epigenetics, State International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, and Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
Bowen Rong & Fei Lan
University of Chinese Academy of Sciences, Beijing, 100049, China
Hong Zhu, Shuyan Chen & Yue Qin
GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, 511436, China
Shijie Wang & Xialian Wang
School of Life Sciences, University of Science and Technology of China, Hefei, 230026, China
Yixuan Wang

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Shengyong Yu
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Chunhua Zhou
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Jiangping He
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He Liu
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Contributions

S.Y. and J.L. designed the project; S.Y. and C.Z. performed the most experiments; J.H. performed the bioinformatics analysis with X.H., S.Ch., and G.Z.; S.Y., C.Z., and S.W. isolated the primary EpiSC cell lines; S.Ca. and J.G. performed the blastocyst injection; H.L. and Y.Q. performed the scRNA-seq experiments; H.Z., X.W., B.C., L.X., and Y.W. performed the gene editing and RT-qPCR experiments; B.R. performed the ChIP-seq experiments; Z.Y. and Y.C. performed the PGCLC transplantation experiments; H.W. and Z.Z. provide suggestions to revise the manuscript; M.Z. and X.Z. supervised the germ cell experiments; F.L. and J.C. supervised the data analysis; J.L., D.P., and S.Ca. supervised the whole study, J.L., S.Y., and D.P. wrote the manuscript, J.L. approved the final version.

Corresponding authors

Correspondence to Shangtao Cao, Duanqing Pei or Jing Liu.

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Yu, S., Zhou, C., He, J. et al. BMP4 drives primed to naïve transition through PGC-like state. Nat Commun 13, 2756 (2022). https://doi.org/10.1038/s41467-022-30325-4

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Received: 27 January 2021
Accepted: 26 April 2022
Published: 19 May 2022
DOI: https://doi.org/10.1038/s41467-022-30325-4

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