CoChat
Sign Up
Cited by 479Single-cell and spatial transcriptomicsGene Regulatory Network AnalysisGenomics and Chromatin Dynamics

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

Open access
Olsson, Andre, Venkatasubramanian, Meenakshi, Chaudhri, Viren K., Aronow, Bruce J., Salomonis, Nathan, Singh, Harinder, Grimes, H. Leighton·2016·Nature
DOI 10.1038/nature19348PMC PMC5161694
Open this paper in CoChat — free account

Abstract

Delineating hierarchical cellular states, including rare intermediates and the networks of regulatory genes that orchestrate cell-type specification, are continuing challenges for developmental biology. Single-cell RNA sequencing is greatly accelerating such research, given its power to provide comprehensive descriptions of genomic states and their presumptive regulators. Haematopoietic multipotential progenitor cells, as well as bipotential intermediates, manifest mixed-lineage patterns of gene expression at a single-cell level. Such mixed-lineage states may reflect the molecular priming of different developmental potentials by co-expressed alternative-lineage determinants, namely transcription factors. Although a bistable gene regulatory network has been proposed to regulate the specification of either neutrophils or macrophages, the nature of the transition states manifested in vivo, and the underlying dynamics of the cell-fate determinants, have remained elusive. Here we use single-cell RNA sequencing coupled with a new analytic tool, iterative clustering and guide-gene selection, and clonogenic assays to delineate hierarchical genomic and regulatory states that culminate in neutrophil or macrophage specification in mice. We show that this analysis captured prevalent mixed-lineage intermediates that manifested concurrent expression of haematopoietic stem cell/progenitor and myeloid progenitor cell genes. It also revealed rare metastable intermediates that had collapsed the haematopoietic stem cell/progenitor gene expression programme, instead expressing low levels of the myeloid determinants, Irf8 and Gfi1 (refs 9, 10, 11, 12, 13). Genetic perturbations and chromatin immunoprecipitation followed by sequencing revealed Irf8 and Gfi1 as key components of counteracting myeloid-gene-regulatory networks. Combined loss of these two determinants ‘trapped’ the metastable intermediate. We propose that mixed-lineage states are obligatory during cell-fate specification, manifest differing frequencies because of their dynamic instability and are dictated by counteracting gene-regulatory networks.

AI snapshot

Written from the paper’s full text.

TL;DR

Single-cell RNA-Seq and ICGS resolved nine hierarchical myeloid states and identified prevalent and rare mixed-lineage intermediates during neutrophil-versus-macrophage specification. Irf8 and Gfi1 act as counteracting determinants of a metastable transition state that can be “trapped” by combined loss of both factors.

Key findings

  • ICGS resolved nine hierarchically ordered cellular states—HSCP-1, HSCP-2, Meg, Eryth, Multi-Lin*, MDP, Mono, Gran, and Myelocyte—whose inferred developmental order agreed with the experimentally determined hematopoietic sequence.
  • A prevalent Multi-Lin* state co-expressed HSCP and myeloid progenitor genes (Ctsg, Mpo, Elane) and the TFs Gata2, Meis1, PU.1, and C/EBPα, with variable priming of megakaryocytic, erythroid, granulocytic, and monocytic genes.
  • Rare metastable intermediates expressed low levels of both Irf8 and Gfi1; Irf8hi GMPs were specified monocytic progenitors (CFU-M), Irf8− GMPs contained specified granulocytes (CFU-G) and bipotential progenitors (CFU-GM), and IG2s gave equal proportions of monocytic and granulocytic colonies.
  • ChIP-Seq showed Irf8 peaks enriched for EICE motifs co-bound by PU.1, shared Gfi1/Irf8 regions accessible in GMPs, and increased H3K4me2 at shared regions upon Gfi1 loss or Lsd1 inhibition, correlating with enhanced monocytic potential.

Methods

  • scRNA-Seq was performed on mouse LSK, CMP, GMP, and LKCD34+ cells using the C1 Single-Cell Auto Prep System; 96 LSK, 96 CMP, 136 GMP, and 66 LKCD34+ libraries were sequenced, with QC failures in 3 LSK, 2 CMP, 4 GMP, and 3 LKCD34+ samples. Additional scRNA-Seq was performed on GG1s, IG2s, and Irf8−/−Gfi1−/− GMP-like cells.
  • ICGS used pairwise correlation of dynamically expressed genes and iterative clustering with pattern-specific guide genes, excluding cell-cycle genes; results were compared with six independent computational approaches and annotated using GO-Elite/ImmGen enrichment.
  • ChIP-Seq for Gfi1, Irf8, and H3K4me2 was performed in GMPs, with external Cebpα ChIP-Seq and ATAC-Seq data; functional assays included CFU assays, flow cytometry, RT-PCR, and an inducible Gfi1 allele.

Limitations

  • The paper does not state a formal limitations section.
  • Evident from the text: the study is based on mouse bone marrow populations, and human relevance is not tested.
  • Evident from the text: rare intermediates are inferred partly from population frequencies, and the Gfi1-GFP reporter expresses stable GFP, which the authors note can over-estimate Gfi1 expression and likely accounts for higher GFP in GG3s despite very low Gfi1 transcripts.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1038/nature19348

Cites

50 of 50 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 15 cited sources checked · 0 supported · 0 flagged

  • Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Clustering of LKCD34+ cells recreated the entire developmental ordering with granulocytic precursors at one end of the continuum.

    “Similarly, clustering of LKCD34+ cells recreated the entire developmental ordering with granulocytic precursors at one end of the continuum (Extended Data Fig. 6b).”
    Quote in the paperNot a substantial claim
  • Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Genetic perturbations and ChIP-Seq revealed Irf8 and Gfi1 as key components of counteracting myeloid-gene-regulatory networks.

    “Genetic perturbations and ChIP-Seq revealed Irf8 and Gfi1 as key components of counteracting myeloid-gene-regulatory networks.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    During steady-state myelopoiesis a prevalent mixed-lineage state expresses HSCP and myeloid progenitor genes (Ctsg, Mpo, Elane) while displaying molecular priming of erythrocytic, megakaryocytic, granulocytic and monocytic potentials.

    “Thus, during steady-state myelopoiesis a prevalent mixed-lineage state is encountered that expresses HSCP and myeloid progenitor genes (Ctsg, Mpo, and Elane), while displaying molecular priming of erythrocytic, megakaryocytic, granulocytic and monocytic potentials.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Similar binding patterns for Gfi1 and Irf8 were seen on the Irf8, Klf4 and Zeb2 genes.

    “Strikingly, similar binding patterns for Gfi1 and Irf8 were seen on the Irf8, Klf4 and Zeb2 genes (Extended Data Fig. 8a).”
    Quote in the paperSubstantial claim
  • Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Gfi1 and Irf8 displayed strong partitioning within granulocyte- versus monocyte-specified cells.

    “Notably, Gfi1 and Irf8, which are required for normal granulopoiesis and monopoiesis, respectively9,11,12,24,25, displayed strong partitioning within granulocyte- versus monocyte-specified cells (Fig. 1f).”
    Quote in the paperSubstantial claim
  • May combine two claims. 29
  • Classified as probably not a substantial claim. 17

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    In Csf1r+ GMP, inducing Gfi1 repressed monocytic genes including Irf8 and induced neutrophil genes in a dose-dependent manner.

    “In Csf1r+ GMP, inducing Gfi1 repressed monocytic genes (including Irf8), and induced neutrophil genes in a dose-dependent manner (Fig. 2d).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Pairwise expression correlation confirmed the Irf8-Klf4 regulatory relationship and suggested new regulatory interactions Irf8-Zeb2 and Gfi1-Per3.

    “This confirmed an established regulatory relationship (e.g. Irf8-Klf423), and suggested new regulatory interactions (Irf8-Zeb2 and Gfi1-Per3).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [23] Kurotaki, D. et al. Essential role of the IRF8-KLF4 transcription factor cascade in murine monocyte differentiation. Blood 121, 1839–1849 (2013) source

      Not checked in the free run.

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    GG2 cells expressed highest levels of Gfi1 and represented specified granulocytic progenitors.

    “GG2 cells expressed highest levels of Gfi1 and represented specified granulocytic progenitors, while GG3 cells, which expressed highest levels of Irf8 were oppositely specified as monocytic progenitors (Fig. 3f–h).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Genes near shared genomic regions were associated with monocytic-dendritic-precursors or abnormal mononuclear cell morphology and were reciprocally dysregulated in Irf8−/− or Gfi1−/− GMPs.

    “Genes located near the shared genomic regions were associated with monocytic-dendritic-precursors (ImmGen) or abnormal mononuclear cell morphology (Mouse Phenotype Ontology), and were reciprocally dysregulated in Irf8−/− or Gfi1−/− GMPs (Extended Data Fig. 7f).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    IG2s expressed low levels of Irf8 and Gfi1 and gave rise to equal proportions of monocytic and granulocytic colonies.

    “Intriguingly, the IG2s, which expressed low levels of Irf8 and Gfi1 (Fig. 3b, c), appeared to represent cells poised to undergo specification as they gave rise to equal proportion of monocytic and granulocytic colonies.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Increased Gfi1 expression reciprocally altered key transcription factors: Klf4, Zeb2 and Irf5 were repressed whereas Ets1 and Per3 were induced.

    “In agreement with regulatory state (Fig. 1e) and loss-of-function analyses (Fig. 2a), key TFs were reciprocally altered by increased expression of Gfi1; Klf4, Zeb2 and Irf5 were repressed whereas Ets1 and Per3 were induced.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Irf8 peaks were enriched for EICE motifs, which are co-bound by PU.1.

    “Notably, Irf8 peaks were enriched for EICE motifs, which are co-bound by PU.126.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [26] Brass, A. L., Zhu, A. Q. & Singh, H. Assembly requirements of PU.1-Pip (IRF-4) activator complexes: inhibiting function in vivo using fused dimers. EMBO J. 18, 977–991 (1999) source

      Not checked in the free run.

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Gfi1 induction in GMP increased granulocytic and diminished monocytic potential.

    “Gfi1 induction in GMP increased granulocytic and diminished monocytic potential (Extended Data Fig. 8c, d).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    CFU assays demonstrated Irf8hi GMPs (IG3) were specified monocytic progenitors (CFU-M); Irf8− GMPs with highest Gfi1 comprised specified granulocytes (CFU-G) and bipotential progenitors (CFU-GM).

    “Colony forming unit (CFU) assays demonstrated that Irf8hi GMPs (IG3) were specified monocytic progenitors (CFU-M); whereas Irf8− GMPs (that expressed highest levels of Gfi1) comprised of specified granulocytes (CFU-G) as well as bipotential progenitors (CFU-GM) (Fig. 3d).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    The remaining two GG1 groups expressed low levels of Gfi1 and Irf8 along with myeloid genes Etv6, Mpo, Elane, Hax1; a subset expressed higher Irf8 along with Cybb and Ly6a.

    “The remaining two groups of cells expressed low levels of Gfi1 and Irf8 along with the myeloid genes Etv6, Mpo, Elane, Hax1, a subset of these expressed higher levels of Irf8 along with Cybb and Ly6a (Fig. 4a).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    ICGS generated HOPACH clusters for mouse intestinal organoids for discovery of rare cell populations.

    “HOPACH generated clusters using ICGS for mouse intestinal organoids1 for the discovery of rare cell populations.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Seurat hierarchical relationships between predicted cell states are based on 161 differentially expressed genes.

    “Seurat hierarchical relationships between the predicted cell states, based on 161 differentially expressed genes.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Significant changes in expression of key genes occur between Irf8−/− versus Irf8-high WT GMP, and between Gfi1−/− versus Gfi1-high WT GMP.

    “Significant changes in expression of key genes between Irf8−/− versus Irf8-high WT GMP, or Gfi1−/− versus Gfi1-high WT GMP are noted (* p<0.05, ** p<0.01, *** p<0.001 Benjamini-Hochberg adjusted).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Seurat predicted 9 cell states.

    “Seurat t-SNE displayed output for the 9 predicted cell states.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Low-level Irf8 induction is associated with loss of the multipotential program but is not accompanied by monocyte specification.

    “We note induction of Irf8 at low levels is associated with loss of the multipotential program but is not accompanied by specification of monocytes.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    HSCP gene expression waned in IG2s and they co-expressed Gfi1 and Irf8.

    “HSCP gene expression waned in IG2s and they co-expressed Gfi1 and Irf8.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    ICGS generated HOPACH clusters for human myoblast differentiation without cell cycle associated genes.

    “HOPACH generated clusters using ICGS for human myoblast differentiation, without inclusion of cell cycle associated genes.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Of the sequenced single-cell libraries, 3 LSK, 2 CMP, 4 GMP and 3 LKCD34+ samples failed QC analysis.

    “Of the 96 LSK, 96 CMP, 136 GMP and 66 LKCD34+ libraries that were sequenced, 3 LSK, 2 CMP, 4 GMP and 3 LKCD34+ samples failed the QC analysis.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    GG3 cells expressed highest levels of Irf8 and were specified as monocytic progenitors.

    “GG2 cells expressed highest levels of Gfi1 and represented specified granulocytic progenitors, while GG3 cells, which expressed highest levels of Irf8 were oppositely specified as monocytic progenitors (Fig. 3f–h).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    IG2s lack bipotential progenitors (CFU-GM) and are highly enriched for cells undergoing lineage specification, resulting in CFU-G and CFU-M.

    “To test this, we analyzed IG2s (Fig. 4a, Extended Data Fig. 10i), which lack bipotential progenitors (CFU-GM) and are highly enriched for cells undergoing lineage specification, resulting in CFU-G and CFU-M.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    Irf8−/− and Gfi1−/− GMP continue to express non-productive transcripts emanating from the mutant Gfi1 and Irf8 alleles.

    “Note that Irf8−/− and Gfi1−/− GMP continue to express non-productive transcripts emanating from the mutant Gfi1 and Irf8 alleles.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    The second GG1 cluster down regulated most HSCP genes except Gata1 and expressed Gfi1, Il5ra, Prg2 and Epx.

    “The second cluster down regulated most HSCP genes except Gata1 and expressed Gfi1, Il5ra, Prg2 and Epx.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    RaceID identified 14 k-means cell clusters.

    “Heatmap of the t-SNE based cell-state ordering and the top 150 most significant RaceID genes associated with each of the 14 k-means clusters.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Intermediate Gfi1 expression is associated with loss of the multipotential program, but a further increase coincides with neutrophil specification.

    “Similarly, an intermediate level of Gfi1 expression is associated with loss of the multipotential program, but a further increase in its expression coincides with neutrophil specification.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    The HSCP-enriched GG1 cells were not contaminants as they expressed CD16/32 and CD34, and corresponded to bipotential cells (CFU-GM) within the GG1 population.

    “These cells were not contaminants as they expressed CD16/32 and CD34 (Extended Data Fig. 9e, f), and corresponded to the bipotential cells (CFU-GM) within the GG1 population (see below).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Cell cycle associated genes were enriched (z-score>1.96) in Gfi1−/− and depleted (z-score <−1.96) in Irf8−/− GMPs.

    “Cell cycle associated genes were enriched (z-score>1.96) in Gfi1−/− and depleted (z-score <−1.96) in the Irf8−/− GMPs.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    ICGS generated HOPACH clusters for human pre-implantation embryos and embryonic stem cells.

    “HOPACH generated clusters derived using ICGS for human scRNA-Seq data for pre-implantation embryos and embryonic stem cells.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Optimization of single-cell RNA-Seq library preparation increased the fraction of reads mapping to a single genomic/transcriptomic location from 61.8% to 83.5%.

    “Single-cell RNA-Seq library fragment distribution before and after optimization reveals an increase in reads that can be mapped to the genome (reads mapping to a single genomic/transcriptomic location using BowTie2/TopHat2; 61.8% before and 83.5% after optimization).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Lsd1 inhibition results in monocytic colony formation and increased Irf8 expression.

    “Lsd1 inhibition results monocytic colony formation and increased Irf8 expression.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Mixed-lineage states are obligatory during cell-fate specification and manifest differing frequencies because of their dynamic instability, dictated by counteracting gene-regulatory networks.

    “We propose that mixed-lineage states are obligatory during cell-fate specification and manifest differing frequencies because of their “dynamic instability”, dictated by counteracting gene-regulatory networks.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Mixed-lineage states reflect molecular priming of developmental potentials by co-expressed alternate-lineage determinants, namely transcription factors.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Mouse manipulations were reviewed and approved by the Children's Hospital Research Foundation Institutional Animal Care and Use Committee.

    “mouse manipulations were reviewed and approved by the Children's Hospital Research Foundation Institutional Animal Care and Use Committee (Protocol Number IACUC2013-0090).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    IG2s manifest dynamic instability because of the counteracting functions of Irf8 and Gfi1, and this metastable state is trapped by elimination of both developmental determinants.

    “Accordingly, we propose that IG2s manifest “dynamic instability” because of the counter acting functions of Irf8 and Gfi1 and that this metastable state is “trapped” by the elimination of both developmental determinants.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Mixed-lineage states reflect molecular priming of developmental potentials by co-expressed alternate-lineage determinants, namely transcription factors.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Differentially expressed genes were identified using AltAnalyze using a FDR adjusted empirical Bayes moderated t-test p<0.05.

    “Differentially expressed genes were identified using AltAnalyze using a FDR adjusted empirical Bayes moderated t-test p<0.05.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    For flow cytometric statistics, a t-test was performed from at least 3 independent experiments.

    “For flow cytometric statistics, a t-test was performed from at least 3 independent experiments.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Oscillatory behavior may be a reflection of partial assembly of counteracting regulatory states or a lack of their stabilization.

    “The oscillatory behavior may be a reflection of partial assembly of counter acting regulatory states or a lack of their stabilization.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductreasoning
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    The Gfi1-GFP reporter expresses a stable GFP, which can over-estimate Gfi1 expression, likely accounting for higher GFP expression in GG3s despite very low levels of Gfi1 transcripts.

    “The Gfi1-GFP reporter expresses a stable GFP, which can over-estimate Gfi1 expression, likely accounting for higher GFP expression in GG3s (Fig. 3f) in spite of very low levels of Gfi1 transcripts (Fig. 3g).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    Based on its frequency, this state is inferred to be metastable, but could be trapped by elimination of counter-acting determinants.

    “Based on its frequency, this state is inferred to be metastable, but could be “trapped” by elimination of counter-acting determinants.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    The concept of trapping rare developmental intermediates by genetic perturbation is based on analogy with trapping unstable transition states in chemical reactions using physico-chemical strategies.

    “The concept of “trapping” of rare developmental intermediates by genetic perturbation is based on the analogy with trapping of unstable transition states in chemical reactions using physico-chemical strategies33.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [33] Mitchison, T. & Kirschner, M. Dynamic instability of microtubule growth. Nature 312, 237–242 (1984) source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Expression of Flt3, Csf1r and Cx3CR1 identifies MDP, while expression of Batf3 and Ifi205 suggests dendritic cell differentiation.

    “Expression of Flt3, Csf1r and Cx3CR1 identifies MDP, while expression of Batf3 and Ifi205 suggests dendritic cell differentiation.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Bulk RNA-Seq expression for each sorted population correlates with average single-cell gene expression values from the same sort.

    “Correlation between bulk RNA-Seq (TRUseq Stranded mRNA HT kit) for each sorted population compared to average single-cell gene expression values from the same sort (e.g. LSK, CMP, or GMP).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Study design and conductnone given

    In order to identify sub-populations of 3 cells present at 10%, a minimum of 30 cells was required; for primary discovery analyses n>90 was required.

    “In order to identify sub-populations of 3 cells, present at 10%, a minimum of 30 cells was required. For primary discovery analyses n>90 was required.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Gfi1 controls two genetically separable programs: granulopoiesis and Hox-based myeloid progenitor proliferation.

    “In agreement with our previous report that Gfi1 controls two genetically separable programs; granulopoiesis and Hox-based myeloid progenitor proliferation25”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [25] Holtschke, T. et al. Immunodeficiency and chronic myelogenous leukemia-like syndrome in mice with a targeted mutation of the ICSBP gene. Cell 87, 307–317 (1996) source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning
    § Single-cell analysis of mixed-lineage states leading to a binary cell fate choice

    This may generate oscillations in the regulatory states of multi- or bi-potential intermediates, resulting in bursts of alternate lineage gene expression.

    “This may generate oscillations in the regulatory states of multi- or bi-potential intermediates, resulting in bursts of alternate lineage gene expression.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationown data

    Re-clustering with HOPACH delineates relationships between monocytic and granulocytic programming among different indicated cell populations.

    “Genes and cells outlined in the dotted box were re-clustered with HOPACH to delineate relationships between monocytic and granulocytic programming among the different indicated cell populations (Fig. 4c).”
    Quote in the paperNot a substantial claim
44 of 44

  • The paper relies on this without support.

    The nature of the transition states manifested in vivo and the underlying dynamics of the cell-fate determinants have remained elusive.

    “Although a bistable-gene-regulatory network has been proposed to regulate the specification of neutrophils versus macrophages7,8, the nature of the transition states manifested in vivo and the underlying dynamics of the cell-fate determinants have remained elusive.”

  • The paper relies on this without support.

    Each ICGS-delineated cellular state has an underlying regulatory state characterized by distinct combinations of transcription factors.

    “Each ICGS delineated cellular state is expected to have an underlying regulatory state characterized by distinct combinations of TFs.”

  • The paper relies on this without support.

    Mixed-lineage states reflect molecular priming of developmental potentials by co-expressed alternate-lineage determinants, namely transcription factors.

    “Such mixed-lineage states may reflect molecular priming of developmental potentials by co-expressed alternate-lineage determinants, namely transcription factors.”
3 of 3

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?

  • Deep sequencing and cell tracking have revealed hematopoiesis to be more continuous and less discrete and punctuated than originally envisioned.

    “As part of the genomics revolution, increasingly accurate deep sequencing and novel methods of cell tracking have revealed hematopoiesis to be more of a continuous and less of a discrete and punctuated process than originally envisioned.”

    From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Olsson et al., 2016

  • Gene expression alone may be insufficient to distinguish discrete cell populations and may miss other relevant aspects of biology.

    “Thus, while the continuum model clearly addresses some of the oversimplifications of the classic model of hematopoiesis, gene expression alone may be insufficient to distinguish discrete cell populations and may miss other relevant aspects of biology (Olsson et al., 2016).”

    From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Olsson et al., 2016

  • scRNA-seq profiling of the mammalian hematopoietic system typically produces a largely continuous distribution of cells from the earliest HSCs through the characteristic hematopoietic lineages.

    “When computationally reconstructed, single-cell RNA sequencing (scRNA-seq) profiling of the mammalian hematopoietic system typically produces a largely continuous distribution of cells from the earliest HSCs through the characteristic hematopoietic lineages (Nestorowa et al., 2016; Olsson et al., 2016; Paul et al., 2015; Pellin et al., 2019; Tusi et al., 2018; Weinreb et al., 2020).”

    From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Olsson et al., 2016

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Extended Data Figure 10 identifies panel i as both a CFU assay and an ICGS analysis

    Minor

    The caption says the cytospin examines CFU from panel i, but describes panel i as an ICGS analysis rather than a CFU assay.

  • Extended Data Figure 7 assigns two different contents to panel c

    Minor

    The caption labels both a gene-expression comparison and ChIP-Seq/RNA-Seq tracks as panel c.

2 of 2

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Olsson, A., Venkatasubramanian, M., Chaudhri, V. K., Aronow, B. J., Salomonis, N., Singh, H., & Grimes, H. L.
Affiliations
Cincinnati Children's Hospital Medical Center (US)
Corresponding author
  • Salomonis, Nathan
  • Singh, Harinder
  • Grimes, H. Leighton
ORCID
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2016-08-31
Volume
537
Issue
7622
Pages
698-702
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
DOI
10.1038/nature19348
PMC
PMC5161694
OpenAlex
W2515907404
Semantic Scholar
f4cfb99ea0ea2e73c36ba3b1cd57e59bd22bd1d3
Cited by
476
References
50
Citations by year
2026: 11 · 2025: 24 · 2024: 42 · 2023: 44 · 2022: 38 · 2021: 55 · 2020: 78 · 2019: 64 · 2018: 58 · 2017: 59 · 2016: 3
FWCI
31.89
Type
journal article
Language
en
Update notices
correction (2019-04-24)
Open access
Licence
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health (UL1TR001425)
  • National Heart, Lung, and Blood Institute (R01HL122661)
  • National Institute of Diabetes and Digestive and Kidney Diseases (P30DK090971, P30DK078392)
  • National Institute of Arthritis and Musculoskeletal and Skin Diseases (P30AR047363)
  • National Center for Advancing Translational Sciences
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
Keywords
cell fate determination, hematopoiesis, single-cell RNA sequencing, IRF8, GFI1, hematopoietic stem cells, myeloid progenitor cells, chromatin accessibility
MeSH terms
Interferon Regulatory Factor-8, Animals, Cell Differentiation, DNA-Binding Proteins, Female, Macrophages, Male, Mice, Inbred C57BL, Models, Biological, Neutrophils, Transcription Factors, Sequence Analysis, RNA, Cell Lineage, Gene Expression Profiling, Myeloid Progenitor Cells, Chromatin Immunoprecipitation, Interferon Regulatory Factors, Mice, Gene Regulatory Networks, 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.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.

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