The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index; none of the 19 sources its claims cite is checked for support yet.
Polylox barcoding reveals haematopoietic stem cell fates realized in vivo
Open accessAbstract
Developmental deconvolution of complex organs and tissues at the level of individual cells remains challenging. Non-invasive genetic fate mapping has been widely used, but the low number of distinct fluorescent marker proteins limits its resolution. Much higher numbers of cell markers have been generated using viral integration sites, viral barcodes, and strategies based on transposons and CRISPR-Cas9 genome editing; however, temporal and tissue-specific induction of barcodes in situ has not been achieved. Here we report the development of an artificial DNA recombination locus (termed Polylox) that enables broadly applicable endogenous barcoding based on the Cre-loxP recombination system. Polylox recombination in situ reaches a practical diversity of several hundred thousand barcodes, allowing tagging of single cells. We have used this experimental system, combined with fate mapping, to assess haematopoietic stem cell (HSC) fates in vivo. Classical models of haematopoietic lineage specification assume a tree with few major branches. More recently, driven in part by the development of more efficient single-cell assays and improved transplantation efficiencies, different models have been proposed, in which unilineage priming may occur in mice and humans at the level of HSCs. We have introduced barcodes into HSC progenitors in embryonic mice, and found that the adult HSC compartment is a mosaic of embryo-derived HSC clones, some of which are unexpectedly large. Most HSC clones gave rise to multilineage or oligolineage fates, arguing against unilineage priming, and suggesting coherent usage of the potential of cells in a clone. The spreading of barcodes, both after induction in embryos and in adult mice, revealed a basic split between common myeloid-erythroid development and common lymphocyte development, supporting the long-held but contested view of a tree-like haematopoietic structure.
Overview
CoChat Summary
Written by AI from the paper’s full text.
TL;DR
The authors developed Polylox, an artificial Cre-loxP recombination cassette that enables endogenous DNA barcoding with a practical diversity of several hundred thousand barcodes in situ. Using Polylox to fate-map haematopoietic stem cells in mice, they found that adult HSC clones are often multilineage or oligolineage and that haematopoiesis follows a bifurcating myelo-erythroid versus common lymphoid structure.
Key findings
- Polylox recombination can generate 1,866,868 distinct codes in silico, with all codes reachable by 10 recombination events; experimentally, 52% of reads from 30,000 splenic B cells were recombined and 849 different barcodes were identified.
- Adult bone marrow HSC were a mosaic of embryo-derived clones: >95% of adult HSC had recombined barcodes after E9.5 tamoxifen induction, and 14 high-confidence single-progenitor barcodes gave adult clone sizes from 0.2% to 3.8%, including clones above 1.5%.
- Most HSC clones gave multilineage or oligolineage fates, arguing against unilineage priming; among 117 peripheral barcodes, 54 were represented in all assayed lineages and 44 in several lineages.
- Barcode concordance revealed a basic split between common myeloid-erythroid development and common lymphocyte development, with B1a as a distinct lineage within the lymphoid branch; CMP barcodes were found in both EryP and granulocytes with highly correlated frequencies, but about 1/3 of EryP and granulocyte barcodes were undetected in CMP.
Methods
- Polylox consists of ten loxP sites in alternating orientations spaced 178 bp apart, flanking nine unique DNA segments derived from the Arabidopsis thaliana AT2G21770 gene; it was targeted into the Rosa26 locus in ES cells and mice.
- In vivo barcoding used Rosa26Polylox/CreERT2 or Rosa26PolyloxTie2MCM mice, with tamoxifen induction in embryos at E9.5 or in adult mice; sorted cell populations were analyzed by PCR and single molecule real time (SMRT) sequencing across the Polylox locus.
- Barcodes were decoded by aligning the nine forward and reverse-complement segments to circular consensus reads; barcode generation probabilities (Pgen) were computed with a Markov chain model over all possible excisions and inversions.
Limitations
- The paper states that barcodes may be missed in samples, so the range of fates acquired by particular clones may sometimes be underestimated; it also states that it cannot formally conclude that individual cells within a clone underwent multilineage differentiation.
- The paper notes that the quantitative output of adult HSC is controversial, that adult sampling repeats showed lower overlap indicating overall smaller clone sizes, and that paucity of barcodes in CLP precluded robust correlation analysis.
- The Methods state that no randomization was done, no blinding was done, no animals were excluded, and no statistical methods were used to predetermine sample size.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
58 Own result · 24 Own interpretation · 10 Own method · 5 No full text of the sources · 3 Check pending · 2 Not checked yet · 1 Sources not found · 1 No basis given
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The spreading of barcodes, both after induction in embryos and in adult mice, revealed a basic split between common myeloid-erythroid development and common lymphocyte development, supporting the long-held but contested view of a tree-like haematopoietic structure.”
§ Polylox barcoding reveals haematopoietic stem cell fates realized in vivo > Abstract
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We then focused on barcodes induced with high confidence in single embryonic HSC progenitors (Pgen < 10−4), obtaining 14 such barcodes (Fig. 4b).”
§ Polylox barcoding reveals haematopoietic stem cell fates realized in vivo > Abstract
plainn = 2 ·- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The dichotomy of myelo-erythroid and lymphoid branches was not disturbed when all barcodes were analyzed, hence it remained evident even in the presence of non-clonal barcode ‘background’ (Extended Data Fig. 7e).”
§ Polylox barcoding reveals haematopoietic stem cell fates realized in vivo > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper states — it cites no source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Polylox recombination in situ reaches a practical diversity of several hundred thousand barcodes, allowing tagging of single cells.”
§ Polylox barcoding reveals haematopoietic stem cell fates realized in vivo > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we induced Polylox recombination in a Rosa26Polylox/CreERT2 mouse, and 18 hours later analyzed the acutely generated barcodes in 30,000 splenic B cells. 52% of the recovered reads were recombined, indicating recombination in about half of the cells.”
§ Polylox barcoding reveals haematopoietic stem cell fates realized in vivo > Abstract
hedgedSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 28
- Probably not a substantial claim. 17
- The quote only partly states this claim. 1
Create a free account to see these claims.
Create a free account to see these assumptions.
61 more claims
Create a free account to see all 104 claims and to verify the 6 references still open.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In contrast to the transplantation setting, native haematopoiesis has been described as polyclonal32,33, whereby several thousand clones contribute to blood formation.”
From Clonal tracing with somatic epimutations reveals dynamics of blood ageing (2025) · cites this paper as [32]
Citations
Cites
Generalized lacZ expression with the ROSA26 Cre reporter strain
Soriano, P. (1999) · Nature Genetics · doi:10.1038/5007 · Cited by 5,237
A clonogenic common myeloid progenitor that gives rise to all myeloid lineages
Akashi, K., Traver, D., Miyamoto, T., & Weissman, I. L. (2000) · Nature · doi:10.1038/35004599 · Cited by 2,617
Restoration of p53 function leads to tumour regression in vivo
Ventura, A., Kirsch, D. G., McLaughlin, M. E., Tuveson, D. A., Grimm, J., Lintault, L., Newman, J., Reczek, E. E., Weissleder, R., & Jacks, T. (2007) · Nature · doi:10.1038/nature05541 · Cited by 1,820
HPRT-deficient (Lesch–Nyhan) mouse embryos derived from germline colonization by cultured cells
Hooper, M., Hardy, K., Handyside, A. H., Hunter, S., & Monk, M. (1987) · Nature · doi:10.1038/326292a0 · Cited by 1,218
Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors
Paul, F., Arkin, Y., Giladi, A., Jaitin, D. A., Kenigsberg, E., Keren-Shaul, H., Winter, D., Lara-Astiaso, D., Gury, M., Weiner, A., et al. (2015) · Cell · doi:10.1016/j.cell.2015.11.013 · Cited by 1,082
Human haematopoietic stem cell lineage commitment is a continuous process
Velten, L., Haas, S. F., Raffel, S., Blaszkiewicz, S., Islam, S., Hennig, B. P., Hirche, C., Lutz, C., Buss, E. C., Nowak, D., et al. (2017) · Nature Cell Biology · doi:10.1038/ncb3493 · Cited by 925
Clonal dynamics of native haematopoiesis
Sun, J., Ramos, A., Chapman, B., Johnnidis, J. B., Le, L., Ho, Y.-J., Klein, A., Hofmann, O., & Camargo, F. D. (2014) · Nature · doi:10.1038/nature13824 · Cited by 821
Yamamoto, R., Morita, Y., Ooehara, J., Hamanaka, S., Onodera, M., Rudolph, K. L., Ema, H., & Nakauchi, H. (2013) · Cell · doi:10.1016/j.cell.2013.08.007 · Cited by 819
Distinct routes of lineage development reshape the human blood hierarchy across ontogeny
Notta, F., Zandi, S., Takayama, N., Dobson, S., Gan, O. I., Wilson, G., Kaufmann, K. B., McLeod, J., Laurenti, E., Dunant, C. F., et al. (2016) · Science · doi:10.1126/science.aab2116 · Cited by 780
Fundamental properties of unperturbed haematopoiesis from stem cells in vivo
Busch, K., Klapproth, K., Barile, M., Flossdorf, M., Holland-Letz, T., Schlenner, S. M., Reth, M., Höfer, T., & Rodewald, H.-R. (2015) · Nature · doi:10.1038/nature14242 · Cited by 769
Self-citation
Cited by
Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)
Cossarizza, A., Chang, H., Radbruch, A., Acs, A., Adam, D., Adam‐Klages, S., Agace, W. W., Aghaeepour, N., Akdiş, M., Allez, M., et al. (2019) · European Journal of Immunology · doi:10.1002/eji.201970107 · Cited by 1,011
From haematopoietic stem cells to complex differentiation landscapes
Laurenti, E., & Göttgens, B. (2018) · Nature · doi:10.1038/nature25022 · Cited by 949
Wound healing, fibroblast heterogeneity, and fibrosis
desJardins-Park, H. E., Mascharak, S., Griffin, M., Wan, D. C., & Longaker, M. T. (2022) · Cell stem cell · doi:10.1016/j.stem.2022.07.006 · Cited by 856
Characterization of cell fate probabilities in single-cell data with Palantir
Setty, M., Kiseliovas, V., Levine, J., Gayoso, A., Mazutis, L., & Pe’er, D. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0068-4 · Cited by 833
MDSC: Markers, development, states, and unaddressed complexity
Hegde, S., Leader, A. M., & Mérad, M. (2021) · Immunity · doi:10.1016/j.immuni.2021.04.004 · Cited by 706
Buenrostro, J. D., Corces, M. R., Lareau, C. A., Wu, B., Schep, A. N., Aryee, M. J., Majeti, R., Chang, H. Y., & Greenleaf, W. J. (2018) · Cell · doi:10.1016/j.cell.2018.03.074 · Cited by 670
Lineage tracing meets single-cell omics: opportunities and challenges
Wagner, D. E., & Klein, A. M. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0223-2 · Cited by 646
Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain
Raj, B., Wagner, D. E., McKenna, A., Pandey, S., Klein, A. M., Shendure, J., Gagnon, J. A., & Schier, A. F. (2018) · Nature Biotechnology · doi:10.1038/nbt.4103 · Cited by 614
Population dynamics of normal human blood inferred from somatic mutations
Lee-Six, H., Øbro, N. F., Shepherd, M. S., Grossmann, S., Dawson, K., Belmonte, M., Osborne, R. J., Huntly, B. J. P., Martincorena, I., Anderson, E., et al. (2018) · Nature · doi:10.1038/s41586-018-0497-0 · Cited by 604
Physiology and diseases of tissue-resident macrophages
Lazarov, T., Juarez-Carreño, S., Cox, N., & Geissmann, F. (2023) · Nature · doi:10.1038/s41586-023-06002-x · Cited by 579
Lineage Tracing in Humans Enabled by Mitochondrial Mutations and Single-Cell Genomics
Ludwig, L. S., Lareau, C. A., Ulirsch, J. C., Christian, E., Muus, C., Li, L. H., Pelka, K., Ge, W., Oren, Y., Brack, A., et al. (2019) · Cell · doi:10.1016/j.cell.2019.01.022 · Cited by 567
Simultaneous lineage tracing and cell-type identification using CRISPR–Cas9-induced genetic scars
Spanjaard, B., Hu, B., Mitic, N., Olivares-Chauvet, P., Janjuha, S., Ninov, N., & Junker, J. P. (2018) · Nature Biotechnology · doi:10.1038/nbt.4124 · Cited by 531
Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)
Cossarizza, A., Chang, H., Radbruch, A., Abrignani, S., Addo, R., Akdis, M., Andrä, I., Andreata, F., Annunziato, F., Arranz, E., et al. (2021) · European Journal of Immunology · doi:10.1002/eji.202170126 · Cited by 531
Whole-organism clone tracing using single-cell sequencing
Alemany, A., Florescu, M., Baron, C. S., Peterson-Maduro, J., & van Oudenaarden, A. (2018) · Nature · doi:10.1038/nature25969 · Cited by 450
Hierarchically related lineage-restricted fates of multipotent haematopoietic stem cells
Carrelha, J., Meng, Y., Kettyle, L. M., Luis, T. C., Norfo, R., Alcolea, V., Boukarabila, H., Grasso, F., Gambardella, A. R., Grover, A., et al. (2018) · Nature · doi:10.1038/nature25455 · Cited by 426
Single-Cell Transcriptomics Meets Lineage Tracing
Kester, L., & van Oudenaarden, A. (2018) · Cell Stem Cell · doi:10.1016/j.stem.2018.04.014 · Cited by 375
Tissue macrophages: origin, heterogenity, biological functions, diseases and therapeutic targets
Guan, F., Wang, R., Yi, Z., Luo, P., Liu, W., Xie, Y., Liu, Z., Xia, Z., Zhang, H., & Cheng, Q. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02124-y · Cited by 371
Causes and Consequences of Hematopoietic Stem Cell Heterogeneity
Haas, S. F., Trumpp, A., & Milsom, M. D. (2018) · Cell stem cell · doi:10.1016/j.stem.2018.04.003 · Cited by 365
A comprehensive single cell transcriptional landscape of human hematopoietic progenitors
Pellin, D., Loperfido, M., Baricordi, C., Wolock, S. L., Montepeloso, A., Weinberg, O. K., Biffi, A., Klein, A. M., & Biasco, L. (2019) · Nature Communications · doi:10.1038/s41467-019-10291-0 · Cited by 360
Bowling, S., Sritharan, D., Osorio, F. G., Nguyen, M., Cheung, P., Rodriguez-Fraticelli, A., Patel, S., Yuan, W.-C., Fujiwara, Y., Li, B. E., et al. (2020) · Cell · doi:10.1016/j.cell.2020.04.048 · Cited by 326
Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution
Yang, D., Jones, M. G., Naranjo, S., Rideout, W. M., Min, K. H., Ho, R., Wu, W., Replogle, J. M., Page, J. L., Quinn, J. J., et al. (2022) · Cell · doi:10.1016/j.cell.2022.04.015 · Cited by 354
New paradigms on hematopoietic stem cell differentiation
Cheng, H., Zheng, Z., & Cheng, T. (2019) · Protein & Cell · doi:10.1007/s13238-019-0633-0 · Cited by 353
Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics
Gulati, G. S., D'Silva, J. P., Liu, Y., Wang, L., & Newman, A. M. (2024) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-024-00768-2 · Cited by 351
Massively parallel single-cell mitochondrial DNA genotyping and chromatin profiling
Lareau, C. A., Ludwig, L. S., Muus, C., Gohil, S. H., Zhao, T., Chiang, Z., Pelka, K., Verboon, J. M., Luo, W., Christian, E., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-0645-6 · Cited by 315
Liao, J., Lu, X., Shao, X., Zhu, L., & Fan, X. (2020) · Trends in biotechnology · doi:10.1016/j.tibtech.2020.05.006 · Cited by 286
Haematopoietic stem cell self-renewal in vivo and ex vivo
Wilkinson, A. C., Igarashi, K. J., & Nakauchi, H. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0241-0 · Cited by 226
Multiplex recording of cellular events over time on CRISPR biological tape
Sheth, R. U., Yim, S. S., Wu, F. L., & Wang, H. H. (2017) · Science · doi:10.1126/science.aao0958 · Cited by 204
Hematopoietic Hierarchy – An Updated Roadmap
Zhang, Y., Gao, S., Xia, J., & Liu, F. (2018) · Trends in Cell Biology · doi:10.1016/j.tcb.2018.06.001 · Cited by 204
Triana, S., Vonficht, D., Jopp-Saile, L., Raffel, S., Lutz, R., Leonce, D., Antes, M., Hernández-Malmierca, P., Ordoñez-Rueda, D., Ramasz, B., et al. (2021) · Nature Immunology · doi:10.1038/s41590-021-01059-0 · Cited by 195
Hematopoietic lineage distribution and evolutionary dynamics of clonal hematopoiesis
Arends, C. M., Galan-Sousa, J., Hoyer, K., Chan, W., Jäger, M., Yoshida, K., Seemann, R., Noerenberg, D., Waldhueter, N., Fleischer-Notter, H., et al. (2018) · Leukemia · doi:10.1038/s41375-018-0047-7 · Cited by 194
Cellular barcoding: lineage tracing, screening and beyond
Kebschull, J. M., & Zador, A. M. (2018) · Nature Methods · doi:10.1038/s41592-018-0185-x · Cited by 190
Pei, W., Shang, F., Wang, X., Fanti, A.-K., Greco, A., Busch, K., Klapproth, K., Zhang, Q., Quedenau, C., Sauer, S., et al. (2020) · Cell Stem Cell · doi:10.1016/j.stem.2020.07.018 · Cited by 181
Self-citationUnravelling cellular relationships during development and regeneration using genetic lineage tracing
Baron, C. S., & van Oudenaarden, A. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0186-3 · Cited by 183
DNA-based memory devices for recording cellular events
Sheth, R. U., & Wang, H. H. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0052-8 · Cited by 180
Lifelong multilineage contribution by embryonic-born blood progenitors
Patel, S. H., Christodoulou, C., Weinreb, C., Yu, Q., da Rocha, E. L., Pepe-Mooney, B. J., Bowling, S., Li, L., Osorio, F. G., Daley, G. Q., et al. (2022) · Nature · doi:10.1038/s41586-022-04804-z · Cited by 180
Emerging Principles in Myelopoiesis at Homeostasis and during Infection and Inflammation
Schultze, J. L., Mass, E., & Schlitzer, A. (2019) · Immunity · doi:10.1016/j.immuni.2019.01.019 · Cited by 174
Stretching the limits: from homeostasis to stem cell plasticity in wound healing and cancer
Ge, Y., & Fuchs, E. V. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2018.9 · Cited by 172
Recording development with single cell dynamic lineage tracing
McKenna, A., & Gagnon, J. A. (2019) · Development · doi:10.1242/dev.169730 · Cited by 170
Diverse mechanisms for endogenous regeneration and repair in mammalian organs
Wells, J. M., & Watt, F. M. (2018) · Nature · doi:10.1038/s41586-018-0073-7 · Cited by 169
Li, L., Bowling, S., McGeary, S. E., Yu, Q., Lemke, B., Alcedo, K., Jia, Y., Liu, X., Ferreira, M., Klein, A. M., et al. (2023) · Cell · doi:10.1016/j.cell.2023.09.019 · Cited by 167
Deciphering cell states and genealogies of human haematopoiesis
Weng, C., Yu, F., Yang, D., Poeschla, M., Liggett, L. A., Jones, M. G., Qiu, X., Wahlster, L., Caulier, A., Hussmann, J. A., et al. (2024) · Nature · doi:10.1038/s41586-024-07066-z · Cited by 171
Molecular transitions in early progenitors during human cord blood hematopoiesis
Zheng, S., Papalexi, E., Butler, A., Stephenson, W., & Satija, R. (2018) · Molecular Systems Biology · doi:10.15252/msb.20178041 · Cited by 155
Early lineage specification defines alveolar epithelial ontogeny in the murine lung
Frank, D. B., Penkala, I. J., Zepp, J. A., Sivakumar, A., Linares-Saldana, R., Zacharias, W. J., Stolz, K., Pankin, J., Lu, M., Wang, Q., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1813952116 · Cited by 155
What Makes a pDC: Recent Advances in Understanding Plasmacytoid DC Development and Heterogeneity
Musumeci, A. G., Lutz, K., Winheim, E., & Krug, A. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.01222 · Cited by 154
Imaging cell lineage with a synthetic digital recording system
Chow, K.-H. K., Budde, M. W., Granados, A. A., Cabrera, M., Yoon, S., Cho, S., Huang, T.-H., Koulena, N., Frieda, K. L., Cai, L., et al. (2021) · Science · doi:10.1126/science.abb3099 · Cited by 149
Haematopoiesis in the era of advanced single-cell technologies
Jacobsen, S. E. W., & Nerlov, C. (2018) · Nature Cell Biology · doi:10.1038/s41556-018-0227-8 · Cited by 143
Next-Generation Lineage Tracing and Fate Mapping to Interrogate Development
VanHorn, S., & Morris, S. A. (2020) · Developmental Cell · doi:10.1016/j.devcel.2020.10.021 · Cited by 142
Single-cell omics in ageing: a young and growing field
He, X., Memczak, S., Qu, J. T., Belmonte, J. C. I., & Liu, G. (2020) · Nature Metabolism · doi:10.1038/s42255-020-0196-7 · Cited by 130
Feng, D., Zhu, W., Wang, J., Li, D., Shi, X., Xiong, Q., You, J., Han, P., Qiu, S., Wei, Q., et al. (2024) · Military Medical Research · doi:10.1186/s40779-024-00526-7 · Cited by 126
Power in Numbers: Single-Cell RNA-Seq Strategies to Dissect Complex Tissues
Birnbaum, K. D. (2018) · Annual Review of Genetics · doi:10.1146/annurev-genet-120417-031247 · Cited by 117
Gutierrez, C., Al’Khafaji, A. M., Brenner, E. A., Johnson, K. E., Gohil, S. H., Lin, Z., Knisbacher, B. A., Durrett, R., Li, S., Parvin, S., et al. (2021) · Nature Cancer · doi:10.1038/s43018-021-00222-8 · Cited by 110
Clonal lineage tracing reveals shared origin of conventional and plasmacytoid dendritic cells
Feng, J., Pucella, J. N., Jang, G., Alcántara‐Hernández, M., Upadhaya, S., Adams, N. M., Khodadadi‐Jamayran, A., Lau, C. M., Stoeckius, M., Hao, S. P., et al. (2022) · Immunity · doi:10.1016/j.immuni.2022.01.016 · Cited by 110
Made to order: emergency myelopoiesis and demand-adapted innate immune cell production
Swann, J. W., Olson, O. C., & Passegue, E. A. (2024) · Nature reviews. Immunology · doi:10.1038/s41577-024-00998-7 · Cited by 110
BCR-dependent lineage plasticity in mature B cells
Graf, R., Seagal, J., Otipoby, K. L., Lam, K., Ayoub, S., Zhang, B., Sander, S., Chu, V. T., & Rajewsky, K. (2019) · Science · doi:10.1126/science.aau8475 · Cited by 108
The Intestinal Epithelium – Fluid Fate and Rigid Structure From Crypt Bottom to Villus Tip
Bonis, V., Rossell, C., & Gehart, H. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.661931 · Cited by 107
A red light–responsive photoswitch for deep tissue optogenetics
Kuwasaki, Y., Suzuki, K., Yu, G., Yamamoto, S., Otabe, T., Kakihara, Y., Nishiwaki, M., Miyake, K., Fushimi, K., Bekdash, R., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01351-w · Cited by 103
Epigenetic Regulators as the Gatekeepers of Hematopoiesis
Rodrigues, C. P., Shvedunova, M., & Akhtar, A. (2020) · Trends in Genetics · doi:10.1016/j.tig.2020.09.015 · Cited by 102
Connecting past and present: single-cell lineage tracing
Chen, C., Liao, Y., & Peng, G. (2022) · Protein & Cell · doi:10.1007/s13238-022-00913-7 · Cited by 100
Differentiation-based model of hematopoietic stem cell functions and lineage pathways
Höfer, T., & Rodewald, H.-R. (2018) · Blood · doi:10.1182/blood-2018-03-791517 · Cited by 98
Self-citationReview of Single-Cell RNA Sequencing in the Heart
Yamada, S., & Nomura, S. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21218345 · Cited by 98
Akinduro, O., Weber, T., Ang, H. Y.-K., Haltalli, M. L. R., Ruivo, N., Duarte, D., Rashidi, N. M., Hawkins, E. D., Duffy, K. R., & Celso, C. L. (2018) · Nature Communications · doi:10.1038/s41467-017-02376-5 · Cited by 98
Stem cell bioengineering: building from stem cell biology
Tewary, M., Shakiba, N., & Zandstra, P. W. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0040-z · Cited by 97
Kong, W., Biddy, B. A., Kamimoto, K., Amrute, J., Butka, E. G., & Morris, S. A. (2020) · Nature Protocols · doi:10.1038/s41596-019-0247-2 · Cited by 97
Do haematopoietic stem cells age?
Dorshkind, K. A., Höfer, T., Montecino‐Rodriguez, E., Pioli, P. D., & Rodewald, H.-R. (2019) · Nature reviews. Immunology · doi:10.1038/s41577-019-0236-2 · Cited by 94
Self-citationPhylodynamics for cell biologists
Stadler, T., Pybus, O. G., & Stumpf, M. P. H. (2021) · Science · doi:10.1126/science.aah6266 · Cited by 94
Chapple, R. H., Tseng, Y.-J., Hu, T., Kitano, A., Takeichi, M., Hoegenauer, K. A., & Nakada, D. (2018) · Blood Advances · doi:10.1182/bloodadvances.2018016295 · Cited by 90
Clonal tracing with somatic epimutations reveals dynamics of blood ageing
Scherer, M., Singh, I., Braun, M. M., Szu-Tu, C., Sanchez Sanchez, P., Lindenhofer, D., Jakobsen, N. A., Körber, V., Kardorff, M., Nitsch, L., et al. (2025) · Nature · doi:10.1038/s41586-025-09041-8 · Cited by 89
Kinetics of adult hematopoietic stem cell differentiation in vivo
Upadhaya, S., Sawai, C. M., Papalexi, E., Rashidfarrokhi, A., Jang, G., Chattopadhyay, P. K., Satija, R., & Reizis, B. (2018) · The Journal of Experimental Medicine · doi:10.1084/jem.20180136 · Cited by 89
Normal Hematopoiesis Is a Balancing Act of Self-Renewal and RegenerationPreprint
Olson, O. C., Kang, Y.-A., & Passegue, E. A. (2020) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a035519 · Cited by 89
New insights into hematopoietic differentiation landscapes from single-cell RNA sequencing
Watcham, S., Kuciński, I., & Göttgens, B. (2019) · Blood · doi:10.1182/blood-2018-08-835355 · Cited by 88
A time- and single-cell-resolved model of murine bone marrow hematopoiesis
Kuciński, I., Campos, J., Barile, M., Severi, F., Bohin, N., Moreira, P. N., Allen, L., Lawson, H., Haltalli, M. L. R., Kinston, S., et al. (2024) · Cell stem cell · doi:10.1016/j.stem.2023.12.001 · Cited by 88
In situ readout of DNA barcodes and single base edits facilitated by in vitro transcription
Askary, A., Sánchez-Guardado, L. Ó., Linton, J. M., Chadly, D. M., Budde, M. W., Cai, L., Lois, C., & Elowitz, M. B. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0299-4 · Cited by 87
Testing thousands of nanoparticles in vivo using DNA barcodes
Lokugamage, M. P., Sago, C. D., & Dahlman, J. E. (2018) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2018.08.001 · Cited by 87
Raj, B., Gagnon, J. A., & Schier, A. F. (2018) · Nature Protocols · doi:10.1038/s41596-018-0058-x · Cited by 87
Developmental dynamics of two bipotent thymic epithelial progenitor types
Nusser, A., Sagar, Swann, J. B., Krauth, B., Diekhoff, D., Calderón, L., Happe, C., Grün, D., & Boehm, T. L. J. (2022) · Nature · doi:10.1038/s41586-022-04752-8 · Cited by 86
Single-cell lineage tracing by integrating CRISPR-Cas9 mutations with transcriptomic data
Zafar, H., Lin, C. H., & Bar‐Joseph, Z. (2020) · Nature Communications · doi:10.1038/s41467-020-16821-5 · Cited by 85
Murine foetal liver supports limited detectable expansion of life‐long haematopoietic progenitors
Ganuza, M., Hall, T., Myers, J., Nevitt, C., Sánchez-Lanzas, R., Chabot, A., Ding, J., Kooienga, E., Caprio, C., Finkelstein, D., et al. (2022) · Nature Cell Biology · doi:10.1038/s41556-022-00999-5 · Cited by 83
Untangling the web of intratumour heterogeneity
Li, Z., Seehawer, M., & Polyák, K. (2022) · Nature Cell Biology · doi:10.1038/s41556-022-00969-x · Cited by 83
Molecular and cellular mechanisms of aging in hematopoietic stem cells and their niches
Zhang, L., Mack, R. M., Breslin, P., & Zhang, J. (2020) · Journal of Hematology & Oncology · doi:10.1186/s13045-020-00994-z · Cited by 82
How oxygenation shapes immune responses: emerging roles for physioxia and pathological hypoxia
Mirchandani, A. S., Sánchez-García, M. A., & Walmsley, S. R. (2024) · Nature reviews. Immunology · doi:10.1038/s41577-024-01087-5 · Cited by 79
Hematopoietic stem cell-independent hematopoiesis and the origins of innate-like B lymphocytes
Ghosn, E., Yoshimoto, M., Nakauchi, H., Weissman, I. L., & Herzenberg, L. A. (2019) · Development · doi:10.1242/dev.170571 · Cited by 75
Bowling, S., Sritharan, D., Osorio, F. G., Nguyen, M., Cheung, P., Rodriguez-Fraticelli, A., Patel, S. H., Yuan, W.-C., Fujiwara, Y., Li, B. E., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.018 · Cited by 73
Fate mapping of hematopoietic stem cells reveals two pathways of native thrombopoiesis
Morcos, M. N. F., Li, C., Munz, C. M., Greco, A., Dressel, N., Reinhardt, S., Sameith, K., Dahl, A., Becker, N. B., Roers, A., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-31914-z · Cited by 70
Self-citationSymbolic recording of signalling and cis-regulatory element activity to DNA
Chen, W., Choi, J., Li, X., Nathans, J. F., Martin, B., Yang, W., Hamazaki, N., Qiu, C., Lalanne, J., Regalado, S. G., et al. (2024) · Nature · doi:10.1038/s41586-024-07706-4 · Cited by 69
Self-citationQuantitative immunology for physicists
Altan-Bonnet, G. Y., Mora, T., & Walczak, A. M. (2020) · Physics Reports · doi:10.1016/j.physrep.2020.01.001 · Cited by 69
Deep learning-based enhancement of epigenomics data with AtacWorks
Lal, A., Chiang, Z., Yakovenko, N., Duarte, F. M., Israeli, J., & Buenrostro, J. D. (2021) · Nature Communications · doi:10.1038/s41467-021-21765-5 · Cited by 68
Six, E. M., Guilloux, A., Denis, A., Lecoules, A., Magnani, A., Vilette, R., Male, F., Cagnard, N., Delville, M., Magrin, E., et al. (2020) · Blood · doi:10.1182/blood.2019002350 · Cited by 68
Lineage tracing using a Cas9-deaminase barcoding system targeting endogenous L1 elements
Hwang, B., Lee, W., Yum, S.-Y., Jeon, Y., Cho, N., Jang, G., & Bang, D. (2019) · Nature Communications · doi:10.1038/s41467-019-09203-z · Cited by 65
Fanti, A.-K., Busch, K., Greco, A., Wang, X., Cirovic, B., Shang, F., Nizharadze, T., Frank, L., Barile, M., Feyerabend, T. B., et al. (2023) · Cell stem cell · doi:10.1016/j.stem.2022.12.014 · Cited by 65
Self-citationVink, C. S., Calero‐Nieto, F. J., Wang, X., Maglitto, A., Mariani, S. A., Jawaid, W., Göttgens, B., & Dzierzak, E. A. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107627 · Cited by 64
Self-citationLiu, K., Deng, S., Ye, C., Yao, Z., Wang, J., Gong, H., Liu, L., & He, X. (2021) · Nature Methods · doi:10.1038/s41592-021-01325-x · Cited by 63
Ortmann, C. A., Dorsheimer, L., Abou‐El‐Ardat, K., Hoffrichter, J., Aßmus, B., Bonig, H. B., Scholz, A., Pfeifer, H., Martin, H., Schmid, T., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.04.064 · Cited by 62
Bone marrow lympho-myeloid malfunction in obesity requires precursor cell-autonomous TLR4
Liu, A., Chen, M., Kumar, R. J., Stefanović-Račić, M., O'Doherty, R. M., Ding, Y., Jahnen‐Dechent, W., & Borghesi, L. (2018) · Nature Communications · doi:10.1038/s41467-018-03145-8 · Cited by 61
Clonal dynamics after allogeneic haematopoietic cell transplantation
Spencer Chapman, M., Wilk, C. M., Boettcher, S., Mitchell, E., Dawson, K., Williams, N., Müller, J., Kovtonyuk, L., Jung, H., Caiado, F., et al. (2024) · Nature · doi:10.1038/s41586-024-08128-y · Cited by 60
Chen, M., Fu, R., Chen, Y., Li, L., & Wang, S.-W. (2025) · Nature Methods · doi:10.1038/s41592-024-02567-1 · Cited by 58
Cheng, J., Liao, J., Shao, X., Lu, X., & Fan, X. (2021) · Advanced Science · doi:10.1002/advs.202101229 · Cited by 58
Inflammation and Aging of Hematopoietic Stem Cells in Their Niche
Yang, D., & de Haan, G. (2021) · Cells · doi:10.3390/cells10081849 · Cited by 57
Changing concepts in hematopoietic stem cells
Yamamoto, R., Wilkinson, A. C., & Nakauchi, H. (2018) · Science · doi:10.1126/science.aat7873 · Cited by 57
Single cell transcriptomics: moving towards multi-omics
Song, Y., Xu, X., Wang, W., Tian, T., Zhu, Z., & Yang, C. J. (2019) · The Analyst · doi:10.1039/c8an01852a · Cited by 56
Epigenetic regulation of hematopoietic stem cell fate
Meng, Y., & Nerlov, C. (2024) · Trends in Cell Biology · doi:10.1016/j.tcb.2024.08.005 · Cited by 55
Metadata
- Authors
- Pei, W., Feyerabend, T. B., Rössler, J., Wang, X., Postrach, D., Busch, K., Rode, I., Klapproth, K., Dietlein, N., Quedenau, C., Chen, W., Sauer, S., Wolf, S., Höfer, T., & Rodewald, H.-R.
- Affiliations
- German Cancer Research Center (DE)
- Max Delbrück Center (DE)
- Corresponding author
- Höfer, Thomas
- Rodewald, Hans-Reimer
- ORCID
- Venue
- Nature
- Published
- 2017-08-16
- Volume
- 548
- Issue
- 7668
- Pages
- 456-460
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5905670
- OpenAlex
- W2747263575
- Semantic Scholar
- 34620783d9c8f0e9f5a2eba79e0a3d5e90a074c4
- Cited by
- 443
- References
- 34
- Citations by year
- 2026: 43 · 2025: 47 · 2024: 49 · 2023: 41 · 2022: 41 · 2021: 45 · 2020: 68 · 2019: 47 · 2018: 54 · 2017: 8
- FWCI
- 37.59
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (submittedVersion)
- Topics
- Health Sciences › Medicine › Hematology › Hematopoietic Stem Cell Transplantation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Keywords
- hematopoietic stem cells, Cre-loxP recombination, hematopoiesis
- MeSH terms
- Animals, Attachment Sites, Microbiological, Clone Cells, Embryo, Mammalian, Female, Hematopoietic Stem Cells, Lymphocytes, Male, Mosaicism, Recombination, Genetic, Cell Lineage, Integrases, Myeloid Cells, Erythroid Cells, Mice, DNA Barcoding, Taxonomic, Cell Tracking, Single-Cell Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-11-12, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-11-12 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
