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A statistical method for quantifying progenitor cells reveals incipient cell fate commitments

Nature Methods volume 21, pages 597–608 (2024)Cite this article

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Abstract

Quantifying the number of progenitor cells that found an organ, tissue or cell population is of fundamental importance for understanding the development and homeostasis of a multicellular organism. Previous efforts rely on marker genes that are specifically expressed in progenitors. This strategy is, however, often hindered by the lack of ideal markers. Here we propose a general statistical method to quantify the progenitors of any tissues or cell populations in an organism, even in the absence of progenitor-specific markers, by exploring the cell phylogenetic tree that records the cell division history during development. The method, termed targeting coalescent analysis (TarCA), computes the probability that two randomly sampled cells of a tissue coalesce within the tissue-specific monophyletic clades. The inverse of this probability then serves as a measure of the progenitor number of the tissue. Both mathematic modeling and computer simulations demonstrated the high accuracy of TarCA, which was then validated using real data from nematode, fruit fly and mouse, all with related cell phylogenetic trees. We further showed that TarCA can be used to identify lineage-specific upregulated genes during embryogenesis, revealing incipient cell fate commitments in mouse embryos.

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Fig. 1: Theory for TarCA.
Fig. 2: Validating the robustness of TarCA with in silico phylogenies.
Fig. 3: Testing TarCA in D. melanogaster.
Fig. 4: Testing TarCA in mouse embryos.
Fig. 5: TarCA informs incipient cell fate commitments by identifying LUGs.

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Data availability

The Yuan et al. dataset of C. elegans and P. marina is available at https://github.com/helloicyvodka/DELTA_code. Cell phylogenies of D. melanogaster can be found in source data files of Liu et al. (https://doi.org/10.1038/s41592-021-01325-x). The data about cell phylogenies of mouse embryogenesis are available in the Gene Expression Omnibus database under accession number GSE117542 and data of annotation from Pijuan-Sala et al. are available via http://tome.gs.washington.edu. Simulated phylogenies constructed by Fang et al. are available at https://doi.org/10.5281/zenodo.7112097. The data of hematopoiesis can be accessed at https://cospar.readthedocs.io/. All source data supporting the findings of the present study are available at https://github.com/shadowdeng1994/TarCA_sourcedata. Source data are provided with this paper.

Code availability

All custom codes for processing the data are available at https://github.com/shadowdeng1994/TarCA.

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Acknowledgements

We are grateful to W. Zhai, Z. Hu, J. Yang and Y. Zhang for comments. This work was supported by the National Key R&D Program of China (2021YFA1302500 and 2021YFA1302501), the National Natural Science Foundation of China (32293190, 32293191, 31970570 and 32200492).

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  1. These authors contributed equally: Shanjun Deng, Han Gong.

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  1. MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China

    Shanjun Deng, Han Gong, Di Zhang, Mengdong Zhang & Xionglei He

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Contributions

X.H. and S.D. conceived the study. S.D. and H.G. did the simulation and analyzed the data. D.Z. and M.Z. analyzed the third-party data. X.H. supervised the study. X.H., S.D. and H.G. wrote the manuscript with contribution from all authors.

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Correspondence to Xionglei He.

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Nature Methods thanks Manu Setty, Michael Stumpf and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Madhura Mukhopadhyay, in collaboration with the Nature Methods team. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 The comparison between of TarCA and counting the sheer number of monophyletic clades.

Each dot in the figure represents the average estimation accuracy from 1,000 repeats, and the error bar indicates the interquartile range. The dots are colored based on the two inference strategies being compared. Specifically, the results obtained under a 0.1% sampling rate are highlighted in a grey shadow.

Source data

Extended Data Fig. 2 The impact of insufficient informative sites on Np estimation.

a. The schematic diagram shows the reconstructed error introduced by insufficient informative sites. When there is a loss of bifurcating nodes in the phylogenetic tree, it can lead to the overestimation of Np. b. In each panel, the performance of Np estimation is assessed for a specific number of informative sites, ranging from 10 to 1,000 sites. The x-axis represents the average Np obtained from 100 repeats, while the y-axis denotes the actual number of progenitors. The horizontal error bar indicates the interquartile range of Np estimates and the trendline fitted with a linear model (LM) is shown in blue. The Pearson′s correlation coefficients and the corresponding P-values obtained from two-sided t-tests are shown on the top-left corner of each panel.

Source data

Extended Data Fig. 3 The impact of lineage invasions on Np estimation.

a. Schematic plot of impact of lineage invasion. b. In each panel, the performance of Np estimation is assessed for a specific proportion of lineage invasions, ranging from 0.1% to 90%. The x-axis represents the average Np obtained from 1,000 repeats, while the y-axis denotes the actual number of progenitors. The horizontal error bars indicate the interquartile range of Np estimates and the trendline fitted with a linear model (LM) is shown in blue. The Pearson′s correlation coefficients and the corresponding P-values obtained from two-sided t-tests are shown on the top-left corner of each panel.

Source data

Extended Data Fig. 4 Examining the impact of reconstruction errors on the estimation of the number of progenitors for a focal cell type.

a. The diagram illustrates the process of dense sampling of the focal cell type (O1 in this case) under different levels of error rates. b. Each panel in the figure presents a comparison between two inference methods: TarCA and counting of the sheer number of monophyletic clades. The x-axis represents the sampling rate of the focal cell type within all its descendants. The y-axis displays the estimated number of progenitor cells and the corresponding estimation accuracy. The given error rate is indicated on the top of each panel. The results inferred using the sheer number of monophyletic clades are depicted with blue dots, while those inferred using TarCA are represented by orange dots. Each dot denotes the average level of the data. The error bars indicate the lower and upper quartiles of the data. Additionally, the red dashed line in each panel represents the actual number of progenitors of the focal cell type (O1 in this case). This line serves as a reference for assessing the accuracy of the estimation methods.

Source data

Extended Data Fig. 5 Testing TarCA in nematodes.

a. The Np estimated by TarCA matches well the actual progenitor number for the eight cell types examined in C. elegans, including blast cells (Bla, n = 39), epidermal cells (Epi, n = 93), germ cells (Ger, n = 2), gland cells (Gla, n = 13), intestinal cells (Int, n = 20), muscle cells (Mus, n = 122), neuron cells (Neu, n = 226) and structural cells (Str, n = 46). The Pearson′s correlation and Spearman′s correlation are shown on the left-top, with P-value obtained from two-side correlation test. b. A similar performance of TarCA is shown in P. marina. The seven cell types included are neuron (Neu, n = 173), epidermal (Epi, n = 103), pharynx (Pha, n = 93), muscle (Mus, n = 80), germ cells (Ger, n = 2), intestine (Int, n = 20), and unknown (Unknown, n = 30), respectively. The Pearson′s correlation and Spearman′s correlation are shown on the left-top, with P-value obtained from two-side correlation test.

Source data

Extended Data Fig. 6 Inference of the number of progenitors for different cell populations in the early stage of mouse embryogenesis.

a. Each dot in panel a represents the Np corresponding to one of the 10 artificially defined cell populations in Embryo-3. The size of the dot indicates the exact value of Np, which is shown on the left side of the figure. b. The estimated Np values for the 10 cell populations are shown to be consistent between two embryos. The color of each dot represents the identity of the corresponding cell population as depicted in panel a. The Pearson′s correlation is shown on the left-top, with P-value obtained from two-side correlation test.

Source data

Extended Data Fig. 7 Ten representative LUGs on the cell phylogeny of gut endoderm cells in Embryo-3.

The cell phylogeny of gut endoderm cells is shown, and two types of dots are depicted: i) dots in pink represent the cell population with expression upregulation of the focal gene; ii) dots in red show the clades on which the focal cell population with upregulated expression is concentrated.

Source data

Extended Data Fig. 8 Examining the distribution of the clusters derived from the whole transcriptome of gut endoderm cells on the cell phylogeny in Embryo-6.

a. UMAP projection of the gut endoderm cells in Embryo-6 are shown colored by clusters derived from Leiden clustering, along with the same projection showing the expression level of five extraembryonic marker genes. b. Each panel considers an individual cluster in the UMAP projection of gut endoderm cells in Embryo-6. The red line represents the observed Np for the cluster, and the histogram shows the expected Np based on 1,000 repeats of random shuffling. The one-sided empirical P-value in these 1,000 repeats is also shown. c. The phylogenetic tree of the gut endoderm cells of Embryo-6, with cell annotations referring to the UMAP projection in panel b.

Source data

Extended Data Fig. 9 Comparison between LUGs and genes predicted by CoSpar in hematopoiesis.

The Venn plot shows the relationship between 1,825 LUGs and 377 genes predicted by CoSpar, with TarCA-specific genes shown in red, overlapped genes shown in purple and CoSpar-specific genes shown in sky blue. Specifically, the four classic genes selected by Weinreb et al.61 are highlighted in orange.

Source data

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Deng, S., Gong, H., Zhang, D. et al. A statistical method for quantifying progenitor cells reveals incipient cell fate commitments. Nat Methods 21, 597–608 (2024). https://doi.org/10.1038/s41592-024-02189-7

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