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Symmetric inheritance of parental histones contributes to safeguarding the fate of mouse embryonic stem cells during differentiation

Nature Genetics volume 55, pages 1555–1566 (2023)Cite this article

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Abstract

Parental histones, the carriers of posttranslational modifications, are deposited evenly onto the replicating DNA of sister chromatids in a process dependent on the Mcm2 subunit of DNA helicase and the Pole3 subunit of leading-strand DNA polymerase. The biological significance of parental histone propagation remains unclear. Here we show that Mcm2-mutated or Pole3-deleted mouse embryonic stem cells (ESCs) display aberrant histone landscapes and impaired neural differentiation. Mutation of the Mcm2 histone-binding domain causes defects in pre-implantation development and embryonic lethality. ESCs with biased parental histone transfer exhibit increased epigenetic heterogeneity, showing altered histone variant H3.3 and H3K27me3 patterning at genomic sites regulating differentiation genes. Our results indicate that the lagging strand pattern of H3.3 leads to the redistribution of H3K27me3 in Mcm2-2A ESCs. We demonstrate that symmetric parental histone deposition to sister chromatids contributes to cellular differentiation and development.

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Fig. 1: Mcm2-2A mutation alters the H3K27me3 landscape of ESCs.
Fig. 2: Mcm2-2A mutation impairs ESC differentiation and mouse development.
Fig. 3: Single-cell lineage and transcriptome sequencing maps distinct fate of NPCs differentiated from WT versus Mcm2-2A ESCs.
Fig. 4: Mcm2-2A mutation increases histone H3K27me3 heterogeneity.
Fig. 5: Mcm2-2A mutation increases cellular transcriptional heterogeneity.
Fig. 6: Mcm2-2A mutation forms superclones.
Fig. 7: H3.3 coordinates with H3K27me3 to impair Mcm2-2A ESC differentiation.

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Data availability

The datasets generated during and/or analyzed during the current study are available in the Expression Omnibus data base repository (GEO). The next-generation sequencing datasets (RNA-seq, scRNA-seq, CUT&Tag, scCUT&Tag, eSPAN, CUT&RUN, MINCE-seq, ATAC-seq and Repli-ATAC-seq) have been deposited in the GEO with accession GSE185271 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?&acc=GSE185271). Publication ChIP-seq datasets used for comparison were downloaded from GEO (https://www.ncbi.nlm.nih.gov/geo/) under accession numbers GSM3267572 (H3.3, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM3267572), GSM2345017 (H3.3, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM2345017), GSM1555116 (H3.3, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM1555116), GSM1207789 (Hira, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM1207789), GSM4774514 (Ezh2, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM4774514), GSM4774522 (Jarid2, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM4774522), GSM3483858 (Suz12, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM3483858), GSM3483878 (H2AK119ub1, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM3483878) and GSM3483853 (Ring1B, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM3483853). Several ESC marker TF peak location files according published ChIP-seq data were downloaded from ENCODE (https://www.encodeproject.org/) under accession number ENCSR392DGA (Pou5f1 of ESCs, https://www.encodeproject.org/experiments/ENCSR392DGA/). The published E14TG2a datasets were downloaded from GEO under accession number GSE66582 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE66582). Primers for genotyping and qPCR can be found in Supplementary Table 1. Summary of mouse genotypes can be found in Supplementary Tables 2–7. The gRNA and donor sequences for the CRISPR–Cas9 can be found in Supplementary Table 8. The antibody information used for CUT&Tag, scCUT&Tag, eSPAN, CUT&RUN, immunofluorescence, fluorescent activated cell sorting and western blot can be found in Supplementary Table 9.

Code availability

We have made use of publicly available software, tools and code. The public pipeline used to calculate bias via eSPAN analysis is available with the following link: https://github.com/clouds-drift/eSPAN-bias. The published scripts used to call lineage barcodes are available with the following link: https://github.com/AllonKleinLab/LARRY. All other codes used to generate the analysis in this study have been placed in Zenodo through the following link: https://doi.org/10.5281/zenodo.7866527.

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Acknowledgements

We thank Q. Li (Center for Energy Metabolism and Reproduction, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences) for his suggestions and help with embryonic staining, and K. Harper of Harper Health & Science Communications, LLC, for editorial assistance. This work was supported by the following funding: National Key R&D Program of China (grant no. 2019YFA0903800 to H.G.), the Major Program of the National Natural Science Foundation of China (32090031 to H.G.), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB0480000 to H.G.), the General Program of the National Natural Science Foundation of China (32070610 to H.G.), the National Natural Science Foundation of China for Young Scholars (32000580 to Q.W., 32001043 to Y.S., 32100460 to J.Z. and 32101178 to Y.Y.), the Guangdong Province Fund for Distinguished Young Scholars (2021B1515020109 to H.G.), Guangdong Basic and Applied Basic Research Foundation (2021A1515110377 to X.K.), Shenzhen Institute of Synthetic Biology Scientific Research Program (JCHZ20200005, ZTXM20190019 to H.G.) and National Institutes of Health Grant (R01GM130588 to C.Y.).

Author information

Author notes

  1. These authors contributed equally: Qing Wen, Jiaqi Zhou, Congcong Tian, Xinran Li, Guibing Song.

Authors and Affiliations

  1. CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics and Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Qing Wen, Jiaqi Zhou, Congcong Tian, Xinran Li, Guibing Song, Yaping Sun, Sitong Yao, Xiaoyan Liang, Xing Kang, Nan Wang, Yuan Yao & Haiyun Gan

  2. College of Animal Science and Technology, Northwest A&F University, Yangling, China

    Guibing Song & Hongbao Wang

  3. Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA

    Yuan Gao

  4. Center for Energy Metabolism and Reproduction, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Chiyuan Ma & Xiaohua Lei

  5. College of Veterinary Medicine, South China Agricultural University, Guangzhou, China

    Sitong Yao & Xiaohuan Liang

  6. Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, International Cancer Center, Marshall Laboratory of Biomedical Engineering, Shenzhen University Health Science Center, Shenzhen, China

    Jialin Tang & Xiangyu Liu

  7. Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA

    Steven M. Offer

  8. Hormel Institute, University of Minnesota, Austin, MN, USA

    Chuanhe Yu

  9. Department of Hematology, The Second People’s Hospital of Shenzhen, Shenzhen, China

    Xiangyu Liu

  10. School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China

    Zichuan Liu

  11. Tianjin University and Health-Biotech United Group Joint Laboratory of Innovative Drug Development and Translational Medicine, Tianjin University, Tianjin, China

    Zichuan Liu

  12. Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA

    Zhiquan Wang

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  1. Qing Wen
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Contributions

H.G. supervised the research. H.G. and Q.W. conceived and designed the experiments. Q.W., C.T., G.S., Y.S., C.M., S.Y., Xiaoyan Liang and X. Lei performed the experiments. H.G., Q.W., J.Z., C.T., X. Li, G.S., C.M., S.Y., Xiaoyan Liang and X. Lei performed statistical analysis. H.G., Q.W., J.Z., C.T., X.L., G.S., Y.G., C.M., S.Y., Xiaoyan Liang, X. Lei., Z.L. and Z.W. analyzed the data. H.G., Q.W., J.Z., Y.S., X.K., N.W., Y.Y., H.W., Xiaohuan Liang, J.T., S.M.O., X. Lei, X. Liu and Z.L. contributed materials. H.G., Q.W., Y.G., S.M.O., C.Y., X. Liu, Z.L. and Z.W. wrote the paper.

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Correspondence to Haiyun Gan.

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Supplementary Figs. 1–28 (unprocessed immunoblots), Tables 1–9, Notes 1–11 and references.

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Supplementary Data

Exact P values of Supplementary Figs. 2d (H3K27me3, H3K4me3 and H3K9me3); 6a,b; 12a–e,i and 23a.

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Wen, Q., Zhou, J., Tian, C. et al. Symmetric inheritance of parental histones contributes to safeguarding the fate of mouse embryonic stem cells during differentiation. Nat Genet 55, 1555–1566 (2023). https://doi.org/10.1038/s41588-023-01477-w

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