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Single-cell multi-omics sequencing of human spermatogenesis reveals a DNA demethylation event associated with male meiotic recombination

Nature Cell Biology volume 25, pages 1520–1534 (2023)Cite this article

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Abstract

Human spermatogenesis is a highly ordered process; however, the roles of DNA methylation and chromatin accessibility in this process remain largely unknown. Here by simultaneously investigating the chromatin accessibility, DNA methylome and transcriptome landscapes using the modified single-cell chromatin overall omic-scale landscape sequencing approach, we revealed that the transcriptional changes throughout human spermatogenesis were correlated with chromatin accessibility changes. In particular, we identified a set of transcription factors and cis elements with potential functions. A round of DNA demethylation was uncovered upon meiosis initiation in human spermatogenesis, which was associated with male meiotic recombination and conserved between human and mouse. Aberrant DNA hypermethylation could be detected in leptotene spermatocytes of certain nonobstructive azoospermia patients. Functionally, the intervention of DNA demethylation affected male meiotic recombination and fertility. Our work provides multi-omics landscapes of human spermatogenesis at single-cell resolution and offers insights into the association between DNA demethylation and male meiotic recombination.

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Fig. 1: Overview of chromatin accessibility, DNA methylation and transcriptome of human testicular germ cells.
Fig. 2: Defining epigenetic regulatory networks underlying human spermatogenesis.
Fig. 3: Identification of potential regulators for cell-fate transition during human spermatogenesis.
Fig. 4: A round of DNA demethylation occurs upon human male meiosis initiation.
Fig. 5: DNA demethylation upon human male meiosis initiation is associated with meiotic recombination.
Fig. 6: deMRs exhibit enrichment of human PRDM9 motif and higher recombination rate.
Fig. 7: Aberrant DNA methylation status in nonobstructive azoospermia patients.
Fig. 8: The intervention of DNA demethylation affects male meiotic recombination and fertility.

Data availability

All raw sequence data reported in this study have been deposited in the Genome Sequence Archive of the National Genomics Data Center, China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences. The accession numbers are listed as below: the single-cell multi-omics sequencing raw data are under HRA000148 (https://ngdc.cncb.ac.cn/gsa-human/browse/HRA000148), the scRNA-seq raw data of testicular cells from NOA3-NOA8 patients are under HRA004917 (https://ngdc.cncb.ac.cn/gsa-human/browse/HRA004917), the HEK293T cell line sequencing raw data are under HRA004922 (https://ngdc.cncb.ac.cn/gsa-human/browse/HRA004922) and the Uhrf1-cKO and control mice sequencing raw data are under CRA011561 (https://ngdc.cncb.ac.cn/gsa/browse/CRA011561). All processed data reported in this study have been deposited in the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo) under accession number GSE235324.

Human reference genome hg38, mouse reference genome mm10 and genomic-region annotations were obtained from UCSC genome browser (https://genome.ucsc.edu/). The union of H3K27ac and H3K4me1 ChIP-seq peaks from GSE143117 was performed to identify human enhancers96. The datasets of previous publication are publicly available under accession numbers: scRNA-seq data of testicular cells from human normal samples (GSE106487 and GSE109037)8,10 and NOA9 patient (GSE157421)64; scCOOL-seq data (GSE100272)22; DNA methylation and chromatin accessibility data of hFGCs (GSE79552)28 and scRNA-seq data of hFGCs (GSE86146)27; DNA methylation data of spermatogenic cells from spermatogenesis-synchronized mice (GSE132446)17; mouse DSB hotspots (SPO11 hotspots, GSE84689; DMC1 hotspots, GSE35498)52,53; mouse PRDM9 binding sites (GSE61613)54; human meiotic DSB hotspots (GSE59836)45. Human recombination hotspots are from ref. 46,47. Source data are provided with this paper.

Code availability

The code used in this study is deposited at: https://github.com/YangXinyan/HumanSperm_MultiOmics (https://doi.org/10.5281/zenodo.8214258).

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Acknowledgements

We thank M. Tong from the Shanghai Institute of Biochemistry and Cell Biology for providing the Prdm9–/– (Prdm9tm1Ymat) mice, Q. Shi from the University of Science and Technology of China for kindly providing the Top6bl–/– mice and S. Yuan’s laboratory at Huazhong University of Science and Technology for providing the Uhrf1flox/flox mice. We thank F. Tang from Peking University and S. Rao from Nanfang Hospital for helpful discussion and suggestions regarding the paper. This work was supported by grants from the National Key R&D Programme of China (2022YFA0806303 and 2022YFC2702603 to X.-Y.Z., 2021YFA1102700 to L.L., 2020YFA0113300 and 2019YFA0801802 to M.W., and 2019YFE0109500 to G.A.), the National Natural Science Foundation of China (U22A20278 and 82071711 to X.-Y.Z., 31970814 to S.G., 31970787 and 32170869 to G.C., 32070833 and 82101745 to L.L., and 32170866 to M.W.), the Natural Science Funds for Distinguished Young Scholar of Guangdong Province (2022B1515020110 to L.L), the Natural Science Foundation of Shenzhen (JCYJ20210324120212033 to G.C.) and the Key-Area Research and Development Programme of Guangdong Province Modernization of Chinese medicine in Lingnan (2020B1111100011 to L.L.).

Author information

Author notes

  1. These authors contributed equally: Yaping Huang, Lin Li, Geng An, Xinyan Yang, Manman Cui.

Authors and Affiliations

  1. State Key Laboratory of Organ Failure Research, Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P. R. China

    Yaping Huang, Xinyan Yang, Manman Cui, Xiuling Song, Jing Lin, Xiaoling Zhang, Zhaokai Yao, Cong Wan, Cai Zhou, Jiexiang Zhao, Ke Song, Shaofang Ren, Xinyu Xia, Xuesong Hu, Wen Wang, Mei Wang, Yi Zheng, Xiaochun Bai & Xiao-Yang Zhao

  2. Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P. R. China

    Lin Li

  3. Department of Reproductive Medicine Center, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China

    Geng An, Xin Fu & Yu Lan

  4. Centre for Precision Medicine Research and Training, Faculty of Health Sciences, University of Macau, Macau, P. R. China

    Kai Miao

  5. Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, P. R. China

    Andrew P. Hutchins

  6. Department of Biochemistry and Molecular Biology, Shenzhen University Medical School, Shenzhen, P. R. China

    Gang Chang

  7. State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of the MARA, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, P. R. China

    Shuai Gao

  8. Guangdong Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou, P. R. China

    Xiao-Yang Zhao

  9. Key Laboratory of Mental Health of the Ministry of Education, Guangzhou, P. R. China

    Xiao-Yang Zhao

  10. Department of Gynecology, Zhujiang Hospital, Southern Medical University, Guangzhou, P. R. China

    Xiao-Yang Zhao

  11. National Clinical Research Center for Kidney Disease, Guangzhou, P. R. China

    Xiao-Yang Zhao

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  1. Yaping Huang
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Contributions

X.-Y.Z., S.G. and G.C. conceived and supervised the project. X.-Y.Z., G.C. and Y.H. designed the experiments. Y.H., S.G., G.A., M.C., J.L., X.Z., Z.Y., C.W., C.Z., K.S., S.R., and X.X. carried out the experiments. J.Z., X.F., Y.L., X.H., W.W., M.W. and Y.Z. helped with sample collection. With the help of A.P.H., X.B. and K.M., L.L., X.Y. and X.S. performed bioinformatics analyses. X.Z., S.G., G.C., Y.H., L.L., X.Y. and M.C. wrote the paper with help from all authors.

Corresponding authors

Correspondence to Gang Chang, Shuai Gao or Xiao-Yang Zhao.

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Extended data

Extended Data Fig. 1 Cell identity assignment and quality control of single-cell multi-omics sequencing datasets.

a, UMAP plots showing transcriptome data of adult human testicular cells in this study (1,097 cells) integrated with the cells (2,854 cells) from Wang et al.10. Cells are coloured by the origin (donors, left) or cluster (right). b, The expression patterns of representative marker genes on the UMAP plots of this study. A gradient of grey to purple indicates gene expression level from low to high. SPG, spermatogonia; SPC, spermatocytes. c, Box plot showing the number of genes detected in transcriptome data in each individual cell of Wang et al.10 and this study. The cell number at each stage of this study is indicated above each box. d,e, Box plots showing the number of WCG sites (d) and GCH sites (e) covered in a single cell at the indicated stage at 1× depth. f, Box plot showing the mapping rate of DNA data (chromatin accessibility and DNA methylation) at each stage. In c-f, each box represents the median and the 25% and 75% quartiles, and the whiskers indicate 1.5 times the interquartile range. All the data of this study represented in this figure are from four biologically independent samples (integration of all samples).

Source data

Extended Data Fig. 2 The relationship between DNA methylation, chromatin accessibility and RNA expression of the corresponding genes during cell-fate transition in human spermatogenesis.

a, Volcano plots showing the relationship between RNA expression and chromatin accessibility of proximal NDRs as cell fate transitioning during human spermatogenesis. The x axis represents the differential RNA expression (log(fold change)) between Undiff.SPGs and Diff.ing SPG (left), Diff.ing SPG and preL-2 (middle), S1 and S2 (right), respectively. Positive values indicate higher expression in the latter stage. The y axis represents the significance of differential RNA expression (two-sided Wilcoxon rank sum test with Bonferroni correction). Number of DEGs in these three groups are shown at the top of each panel. Red dots represent genes whose RNA expression are significantly higher and the proximal NDRs are significantly more open in the latter stage (two-sided multiple t test with Benjamini-Hochberg adjustment for chromatin accessibility). Blue dots are vice versa. b, Violin plots showing the distribution of gene expression, chromatin accessibility and DNA methylation level of correlated proximal NDRs at the indicated stages. Genomic track is shown on top, and the location of correlated proximal NDRs is labelled with red box. Each box within violin plots represents the median and the 25% and 75% quartiles, and the whiskers indicate 1.5 times the interquartile range. Each dot corresponds to a single cell. c, Genome browser views of chromatin accessibility at the ID4 locus in spermatogonia. Heatmap showing RNA expression level of ID4 at each stage (left). Coloured bars indicate methylation level at GCH sites calculated based on single-cell multi-omics data. Red boxes under each track indicate the location of NDRs. The shadow region represents the specific proximal NDR and its mean level of chromatin accessibility at the indicated stage is shown as heatmap on the right of IGV. d, Heatmap showing the K-means clustering (expected clusters = 3) of DNA methylation level (mean WCG methylation) at the promoter regions (1 kb upstream and 0.5 kb downstream of the TSS). All the data represented in this figure are from four biologically independent samples (integration of all samples).

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Extended Data Fig. 3 The epigenetic modification differences between hFGCs and adult spermatogenic cells.

a, Heatmaps showing DNA methylation, chromatin accessibility of promoters and corresponding relative RNA expression level of representative pluripotency genes throughout human male germline development. White indicates missing values (undetected). b, Genome browser views showing DNA methylation levels of representative pluripotency genes loci in hFGCs and spermatogonia. Coloured bars indicate the DNA methylation level of WCG sites calculated based on the NOMe-seq data from ref. 28 (hFGCs) and single-cell multi-omics data in this study (adult testicular cells). Colour bars above the horizontal line indicate the DNA methylation level (higher than 0.1) at individual WCG site, and the black bars indicate the horizontal line denote WCG site with DNA methylation level lower than 0.1, to discriminate from undetected WCG sites. The shadow region represents the promoter of each gene and its mean DNA methylation level at the indicated stage is shown as heatmap on the right of IGV. c, Heatmaps showing DNA methylation and chromatin accessibility of promoters as well as corresponding relative RNA expression of representative meiosis-specific genes throughout human male germline development. d, Genome browser views of DNA methylation and chromatin accessibility at the representative meiosis-specific gene (SPO11) locus in hFGCs and spermatogenic cells. The shadow region represents the promoter of SPO11 and the mean levels of DNA methylation and chromatin accessibility at the indicated stage are shown as heatmaps on the right of IGV, respectively. The DNA methylation and chromatin accessibility data of hFGCs are from ref. 28 and scRNA-seq data of hFGCs are from ref. 27. All the data of this study represented in this figure are from four biologically independent samples (integration of all samples).

Source data

Extended Data Fig. 4 The potential distal cis-regulatory elements and transcription factors involved in the human spermatogenesis.

a, Heatmap showing the pairwise correlations of cells from P to S1 based on the transcriptome data. Unsupervised hierarchical clustering indicates that SPC7 are more similar to S1. b, Chromatin accessibility of the distal cis-regulatory elements of SPC7 and spermatids (S1-S3). The number of cis-regulatory element at the indicated stages is shown on the left of the heatmap. Representative GO terms (GREAT analysis) and genes corresponding to the distal cis-regulatory elements of each cluster are shown on the right of the heatmap. GO terms are coloured by membership of sub-group (early round spermatids: SPC7 and S1; late round spermatids: S2 and S3). c, Immunofluorescence of KLF6 co-staining with germ cells marker DDX4 in adult human testicular paraffin sections from normal sample. White triangles indicate SPG and yellow arrows indicate Sertoli cells. Scale bar, 10 μm. d,e, The relative expression of KLF6 (d) or representative hSSC marker genes (e) after transfection with the negative control (NC) siRNA or KLF6 siRNA (1/2) into the sorted human undifferentiated spermatogonia. Data are represented as mean with data points (n = 3 biologically independent replicates obtained from two healthy donors with normal fertility). f, Immunofluorescence of KLF4 co-staining with spermatid marker PNA in adult human testicular paraffin sections from normal samples. White arrows indicate S1, yellow arrows indicate S2 and white triangles indicate elongating spermatids. Scale bar, 20 μm. g, Transcription factor motif enrichment at all cis-regulatory elements. The size of circle represents P value (-log10(P value)) of the motif-enrichment and the colour represents the RNA expression level. Only motifs with P ≤ 1×10-10 and TPM ≥ 10 in at least one stage are shown. Significance is calculated with one-sided binomial test using HOMER. Cis-regulatory elements are combined for motif enrichment by sub-groups, including Undiff.SPG (Undiff.SPG-1/2), Diff.ing SPG, early primary spermatocytes (Early SPC; preL-Z), late primary spermatocytes (Late SPC; preP-D), early round spermatids (Early SPD; SPC7-S1) and late round spermatids (Late SPC; S2-S3). Data in a,b and g are from four biologically independent samples (integration of all samples).

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Extended Data Fig. 5 DNA methylation changes in human spermatogenesis and the expression patterns of DNA demethylation related genes.

a, Quantification of the relative fluorescence intensity of 5mC to Hoechst at the indicated stages from normal samples (Donor 1: 28, 36, 32 cells; Donor 2: 29, 38, 39 cells; Donor 3: 25, 38, 35 cells; Donor 4: 24, 36, 32 cells at Diff.ing SPG, preL/L and P stage). Data are represented as mean with data points. b, PCA analysis of stages from Diff.ing SPG to L1/2 based on tiles’ DNA methylation level. c, Box plots showing the expression dynamics of DNA methylation-related genes during human spermatogenesis. d, Negative controls (no primary antibody) of immunofluorescence in adult human testicular paraffin sections from normal sample. Scale bar, 10 μm. e, Immunofluorescence of 5hmC and DDX4 in adult human testicular paraffin sections from normal sample. Scale bar, 10 μm. f, Boxplots showing the expression levels of G1/S phase specific genes at the indicated stages. Each box in c and f represents the median and the 25% and 75% quartiles, and the whiskers indicate 1.5 times the interquartile range. Data in b,c and f are from four biologically independent samples (integration of all samples).

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Extended Data Fig. 6 Cell type annotation and characterization in NOA patients.

a, Immunofluorescence of SYCP3 co-staining with γH2AX and PNA in adult human testicular paraffin sections from normal sample (top), NOA1 (middle) and NOA2 patients (bottom). Scale bar, 10 μm. b,c, UMAP plots showing the transcriptome data of NOA1 (176 cells, b) and NOA2 (130 cells, c) in this study integrated with the data from Wang et al. (2,854 cells from nine biologically independent samples; integration of all samples)10. Cells are coloured by sample origins (left) or clusters (right). d,e, UMAP plots showing the cell types detected in NOA1 (d) and NOA2 (e) patients. The number of each cell type is indicated in the parenthesis. f,g, UMAP plots showing the expression patterns of representative marker genes of NOA1 (f) and NOA2 (g) patients. A gradient of grey to purple indicates expression level from low to high.

Extended Data Fig. 7 Abnormal DNA methylation patterns in the testicular germ cells of NOA patients.

a, Dimensionality reduction of the DNA methylation on 500-bp non-overlapping tiles by PCA analysis. Cells are coloured by stage. b, Bar plot showing the number of DEGs with or without differentially methylated promoters at the indicated stages of NOA1 or NOA2 compared with normal samples. c, Enrichment analysis (-log10(P value), one-sided hypergeometric test) for the hypo-DMRs at Undiff.SPG-1 (left), L3 (middle) and preP (right) stages of NOA1/NOA2 patient compared with the normal control. d, Relative expression levels of SVA, ERV1 and ERVK at the indicated stages of NOA patients and normal samples (1,097, 176, 130 cells in normal, NOA1, NOA2 samples). e, Global pattern of DNA methylation level in NOA patients and normal samples at the indicated stages before (left) and after (right) down-sampling (1,097, 176, 130 cells in normal, NOA1, NOA2 samples). In b-e, Undiff.SPG-out1/2 of NOA1 patient is compared with the Undiff.SPG-1 of normal samples. Normal samples in this figure are the integration of four biologically independent samples.

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Extended Data Fig. 8 The DNA demethylation at the onset of meiosis is conserved between human and mouse.

a, Immunofluorescence performed in testicular sections from PND 15 mice. White triangles indicate epL (STRA8− dispersed SYCP3), yellow arrows indicate mpL (STRA8+ dispersed SYCP3) and white arrows indicate P (threads SYCP3). Scale bar, 10 μm. b, Quantification of the relative fluorescence density of 5mC to Hoechst at the indicated stages from PND 15 mice (174, 162, 159 cells from left to right). c, Quantification of fluorescence density of UHRF1 at the indicated stages from PND 15 mice (120, 185, 140 cells from left to right). Statistics of b and c are performed in three independent mice and data are represented as mean ± SD; unpaired two-sided Student’s t test. d,e, ECDF plots showing the differential DNA methylation level of mouse hotspots (d) or PRDM9 binding sites (e) or random regions between the stage when demethylation occurs and the previous stage in mice (mpL versus type B of spermatogonia (BS)). Random regions are randomly selected genomic regions with equal GC content, number of CpG sites and sequence length distribution as that of hotspots (d) and PRDM9 binding sites (e). DMC1 hotspots: 18,291 regions; SPO11 hotspots: 9,714 regions; PRDM9 binding sites: 32,406 regions. f,g, DNA methylation dynamics of known crossover hotspots during mouse (f) and human (g) spermatogenesis. The bottom three hotspots (A1, A2, A4) are previously identified by pedigree analysis and others are identified by sperm typing53. * indicates the locus selected for bisulfite genomic PCR-based Sanger sequencing assay in this study. In d-f, the DNA methylation dataset of spermatogenic cells from spermatogenesis-synchronized mice is from ref. 17 (n = 2 independent replicates). h, COBRA analysis of the representative crossover hotspots in the sorted cell populations of juvenile, adult and spermatogenesis-synchronized mice. P/D, pachytene/diplotene spermatocytes; BS, type B of spermatogonia; mP, middle pachytene spermatocytes; U, uncut; C, cut.

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Extended Data Fig. 9 The binding sites of PRDM9 in HEK293T cells with DNA methylation inhibitor treatment.

a, Bisulfite genomic PCR-based Sanger sequencing showing the DNA methylation patterns from the representative crossover hotspots in the sorted cell populations of juvenile, adult and spermatogenesis-synchronized mice. Top genome browser view showing the DNA methylation level of each locus in the indicated cell populations from spermatogenesis-synchronized mice17. b, Whole-genome bisulfite sequencing showing the DNA methylation level of HEK293T cells treated with dimethylsulfoxide (DMSO, control) or Decitabine for 60 h. Data are represented as mean ± SD; unpaired two-sided Student’s t test. c, Venn diagram showing the overlap of the hypo-DMRs in Decitabine-treated HKE293T cells (Deci hypo-DMRs) with human recombination hotspots. hypo Hotspots represent the human recombination hotspots overlapped with Deci hypo-DMRs; Hotspot_DMRs represent the Deci hypo-DMRs overlapped with human recombination hotspots. d, Genome browser views of the hPRDM9 signal level and DNA methylation level around human recombination hotspots in Decitabine-treated HEK293T cells and the control group. The mean DNA methylation levels of crossover regions (shadow regions) are shown as heatmaps on the right. Data in b-d are from three biologically independent replicates in each group; integration of all samples.

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Extended Data Fig. 10 Male meiotic recombination and fertility are affected by the intervention of DNA methylation.

a, Immunofluorescence of RAD51 co-staining with SYCP3 for surface-spread spermatocytes from Uhrf1 cKO and control mice. Scale bar, 10 μm. b, The foci number of RAD51 per spermatocyte from Uhrf1 cKO and control mice (30, 43, 49, 68, 45, 53 cells from left to right). c, Schematic illustration of the donor constructs for knocking the CAG-the indicated genes’ coding sequence (CDS)-P2A-Tdtomato cassette into the Rosa26 locus. d, The relative expression of Uhrf1 or Dnmt1 in the control, Uhrf1-TG and UD-TG EGFP-labelled mSSCs. e, Representative cell morphology of the control, Uhrf1-TG and UD-TG EGFP-mSSCs. Scale bar, 100 μm. f, Growth curves of the control, Uhrf1-TG and UD-TG EGFP-mSSCs. In d and f, data are represented as mean ± SD (n = 3 independent mice per group). g, Immunofluorescence of mouse spermatogonial markers PLZF, OCT4 and ID4 in the control, Uhrf1-TG and UD-TG EGFP-mSSCs, respectively. Scale bar, 20 μm. h, Immunofluorescence of RAD51 co-staining with SYCP3 and GFP for surface-spread spermatocytes from recipient testes transplanted with the control, Uhrf1-TG and UD-TG EGFP-mSSCs. Scale bar, 5 μm. i, The foci number of RAD51 per spermatocyte from recipient testes transplanted with the control, Uhrf1-TG and UD-TG EGFP-mSSCs (54, 46, 60, 70, 44, 45 cells from left to right). j, Immunofluorescence of SYCP3 co-staining with the spermatid marker PNA on the testicular sections from Uhrf1 cKO and control mice at PND 30. Scale bar, 50 μm. k, Flow cytometry analysis of DNA content revealing the ratio of haploid spermatid (1 C) in the testes of Uhrf1 cKO and control mice at PND 30. Statistics of b (n = 3) and i (n = 5) are performed in at least three independent mice per group and data are represented as mean ± SD; unpaired two-sided Student’s t test.

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Huang, Y., Li, L., An, G. et al. Single-cell multi-omics sequencing of human spermatogenesis reveals a DNA demethylation event associated with male meiotic recombination. Nat Cell Biol 25, 1520–1534 (2023). https://doi.org/10.1038/s41556-023-01232-7

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