Blastoid·verse

Author

Affiliation

Jialei Duan

UT Southwestern Medical Center

Abstract

We now report an optimized protocol for the efficient generation of large quantities of high-fidelity human blastoids from naive pluripotent stem cells. Side-by-side single-cell RNA sequencing revealed similarities and differences in transcriptome profiles between pre-implantation blastoids and blastocysts, as well as post-implantation cultures, and uncovered a population resembling early migratory trophoblasts during co-culture with endometrial stromal cells. This optimized protocol will facilitate broader use of human blastoids as an accessible, perturbable, scalable, and tractable model for human blastocysts.

Schematic Summary

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Large-scale production of human blastoids amenable to modeling blastocyst development and maternal-fetal cross talk

Citation

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Leqian Yu#, Deirdre Logsdon#, Carlos A. Pinzon-Arteaga#, Jialei Duan#, Toshihiko Ezashi#, Yulei Wei#, Ana Elisa Ribeiro Orsi, Seiya Oura, Lizhong Liu, Lei Wang, Kun Liu, Xiaoyun Ding, Linfeng Zhan, Junfei Zhang, Asrafun Nahar, Caitlen Stobbe, Mandy Katz-Jaffe, William B. Schoolcraft, Tao Tan, Gary C. Hon*, Ye Yuan*, Jun Wu*. (2023). Large-scale production of human blastoids amenable to modeling blastocyst development and maternal-fetal cross talk. Cell Stem Cell 30, 1246–1261.e9.
DOI: 10.1016/10.1016/j.stem.2023.08.002

Leqian Yu#, Toshihiko Ezashi#, Yulei Wei#, Jialei Duan#, Deirdre Logsdon, Linfeng Zhan, Asrafun Nahar, Carlos A. Pinzon Arteaga, Lizhong Liu, Caitlen Stobbe, Mandy Katz-Jaffe, William B Schoolcraft, Lei Wang, Tao Tan, Gary C. Hon*, Ye Yuan*, Jun Wu*. (2022). Large scale production of human blastoids amenable to modeling blastocyst development and maternal-fetal crosstalk. bioRxiv, 2022.09.14.507946.
DOI: 10.1101/2022.09.14.507946

Datasets

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In this manuscript, several human transcriptome data sets generated by different technologies were included. To minimize platform and processing differences, raw fastq files of public datasets were downloaded and re-processed.

• Yu, L., Wei, Y., Duan, J., Schmitz, D.A., Sakurai, M., Wang, L., Wang, K., Zhao, S., Hon, G.C., and Wu, J. (2021). Blastocyst-like structures generated from human pluripotent stem cells. Nature 591, 620–626.
• Petropoulos, S., Edsgärd, D., Reinius, B., Deng, Q., Panula, S.P., Codeluppi, S., Plaza Reyes, A., Linnarsson, S., Sandberg, R., and Lanner, F. (2016). Single-cell RNA-Seq reveals lineage and X chromosome dynamics in human preimplantation embryos. Cell 165, 1012–1026.
• Zheng, Y., Xue, X., Shao, Y., Wang, S., Esfahani, S.N., Li, Z., Muncie, J.M., Lakins, J.N., Weaver, V.M., Gumucio, D.L., et al. (2019). Controlled modelling of human epiblast and amnion development using stem cells. Nature 573, 421–425.
• Xiang, L., Yin, Y., Zheng, Y., Ma, Y., Li, Y., Zhao, Z., Guo, J., Ai, Z., Niu, Y., Duan, K., et al. (2020). A developmental landscape of 3D-cultured human pre-gastrulation embryos. Nature 577, 537–542.
• Yanagida, A., Spindlow, D., Nichols, J., Dattani, A., Smith, A., and Guo, G. (2021). Naive stem cell blastocyst model captures human embryo lineage segregation. Cell Stem Cell 28, 1016–1022.e4.
• Tyser, R.C.V., Mahammadov, E., Nakanoh, S., Vallier, L., Scialdone, A., and Srinivas, S. (2021). Single-cell transcriptomic characterization of a gastrulating human embryo. Nature 600, 285–289.

Code

embedding |>
    dplyr::mutate(num_umis = Matrix::colSums(matrix_readcount_use[, cell])) |>
    dplyr::group_by(study, batch) |>
    dplyr::summarise(
        num_cells = dplyr::n(),
        median_umis = median(num_umis)
    ) |>
    gt::gt(groupname_col = "study") |>
    gt::row_group_order(
        groups = c(
            "This study",
            "Yu et al. 2021",
            "Petropoulos et al. 2016",
            "Zheng et al. 2019",
            "Xiang et al. 2020",
            "Yanagida et al. 2021",
            "Tyser et al. 2021"
        )
    ) |>
    gt::data_color(
        columns = c(median_umis),
        fn = scales::col_numeric(
            palette = c(
                "green", "orange", "red"
            ),
            domain = NULL
        )
    ) |>
    gt::fmt_number(
        columns = c(median_umis),
        sep_mark = ",",
        decimals = 1,
        use_seps = TRUE,
        suffixing = FALSE
    ) |>
    gt::fmt_number(
        columns = c(num_cells),
        sep_mark = ",",
        decimals = 0,
        use_seps = TRUE,
        suffixing = FALSE
    ) |>
    gt::grand_summary_rows(
        columns = c(num_cells),
        fns = list(
            Sum = ~ sum(.)
        ),
        fmt = ~ gt::fmt_number(., decimals = 0, use_seps = TRUE)
    ) |>
    gt::tab_header(
        title = gt::md("**Dataset Summary**"),
        subtitle = gt::md("Human single-cell datasets used in this study")
    ) |>
    gt::cols_label(
        "batch" = gt::md("**Batch**"),
        "num_cells" = gt::md("**Num of cells**"),
        "median_umis" = gt::md("**Median UMIs**")
    )

Dataset Summary
Human single-cell datasets used in this study
	Batch	Num of cells	Median UMIs
This study
	LW119	2,236	2,956.5
	LW120	435	17,392.0
	LW121	5,130	12,536.0
	LW122	287	100,092.0
	LW186	10,977	3,026.0
	LW187	3,690	4,980.0
	LW188	6,838	3,738.0
	LW189	3,250	5,344.0
	LW202	4,833	3,834.0
	LW203	2,571	5,254.0
	LW204	7,596	2,405.0
Yu et al. 2021
	LW60	4,497	14,421.0
	LW61	5,156	7,625.0
Petropoulos et al. 2016
	PRJEB11202	1,529	1,551,093.0
Zheng et al. 2019
	GSM3956280	5,454	23,322.0
	GSM3956281	4,512	27,887.0
Xiang et al. 2020
	PRJNA562548	555	10,165,004.0
Yanagida et al. 2021
	PRJNA720968	495	7,690,661.0
Tyser et al. 2021
	PRJEB40781	1,195	899,241.0
Sum	—	71,236	—

Location

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