The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index; 14 of the 23 sources its claims cite were checked for support.
Lineage tracing on transcriptional landscapes links state to fate during differentiation
Open accessPublished version of a preprint
Abstract
Mapping cell fate during hematopoiesis: Biologists have long attempted to understand how stem and progenitor cells in regenerating and embryonic tissues differentiate into mature cell types. Through the use of recent technical advances to sequence the genes expressed in thousands of individual cells, differentiation mechanisms are being revealed. Weinreb et al. extended these methods to track clones of cells (cell families) across time. Their approach reveals differences in cellular gene expression as cells progress through hematopoiesis, which is the process of blood production. Using machine learning, they tested how well gene expression measurements account for the choices that cells make. This work reveals that a considerable gap still exists in understanding differentiation mechanisms, and future methods are needed to fully understand—and ultimately control—cell differentiation. Science , this issue p. eaaw3381
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Claims the paper makes
64 Own result · 29 Own interpretation · 7 Own method · 5 No full text of the sources · 4 Supported · 4 Partly supported · 3 No basis given · 2 Not checked yet · accuracy not yet measured
Every source the paper cites for this claim was checked and supports it.
In the paper
“The strategy differs from CRISPR-based lineage tracing approaches (27, 28) in that it links states across time, not only at a single end-point.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > DISCUSSION
What the sources say
- Supportedcites [27] source
In Results > Tracing cell lineages during development (page unavailable), the authors say they isolated embryos at E8.5 or E9.5 for analysis and collected single-cell RNA-seq data from them. The Abstract and Discussion describe continuous CRISPR-based recording of lineage history, while Results > Simultaneous scRNA-seq to assign state describes assigning states to the sampled cells. This supports the contrast between recording lineage over time and measuring cellular states at an endpoint; the paper does not assess LARRY itself. (LLM, conf=0.85)
- Supportedcites [28] source
The Main text describes LINNAEUS as creating scars early in development, then sequencing scars and transcriptomes from dissociated cells at a later stage. Its reported single-cell analysis uses larvae at 5 days post fertilization, supporting the contrast with a method that links measured cell states across time. The source does not itself describe LARRY. (LLM, conf=0.88)
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
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
“Visualizing cells from uni-lineage clones revealed well-delineated domains of fate potential (Fig 2c).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
boosted- Asserted: passes — The authors put it forward as true.
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- 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
“In vitro, the cells defined a continuous state map spanning from multipotent progenitors (MPPs) to nine mature cell types that appeared in culture (Fig 1e,f): erythrocytes (Er), megakaryocytes (Mk), basophils (Ba), mast cells (Ma), eosinophils (Eos), neutrophils (Neu), monocytes (Mo), dendritic cells (plasmocytoid pDC; Ccr7+ migratory migDC) and lymphoid precursors (Ly).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“Many of these cell types were internally heterogeneous, with several types of DCs including CD11+, CD8+, migDC and pDC, as well as Ly6C+ classical and Ly6C- non-classical monocytes (Fig 1j; Supp Fig 3).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
plain- Asserted: passes — The authors put it forward as true.
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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
“After profiling by scSeq, one or more barcodes could be robustly detected in 93% of GFP+ cells (Supp Fig 1a–c).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
hedged- Asserted: passes — The authors put it forward as true.
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- 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 retrieved 130,887 scSeq transcriptomes from culture and 182,173 single cells after transplantation (see Table 1 and Supp Methods 3 for details of analysis).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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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
“After transplantation, the cells again defined a continuous landscape spanning from MPPs through several stages of neutrophil maturation, as well as DCs, Mo, Er, B, T and Ba cells.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
plain- Asserted: passes — The authors put it forward as true.
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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
“Specific barcode sequences overlapped rarely between replicate transduction experiments, at a frequency expected by chance for the library size (0.3% of 5000 barcodes appeared more than once).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
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 retrieved 130,887 scSeq transcriptomes from culture and 182,173 single cells after transplantation (see Table 1 and Supp Methods 3 for details of analysis).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether 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
“they shared the same dominant fate 71% of the time (23% by chance).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Functional purity of scSeq-defined cell states
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- 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. 36
- Probably not a substantial claim. 16
Every source the paper cites for this claim was checked and supports it.
In the paper
“Consistent with recent scSeq studies (19), progenitors with different fate potentials did not partition into discrete cell states, but instead formed a structured continuum.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
What the sources say
- Supportedcites [19] source
The Results section ('Early haematopoiesis is a continuous process'; page unavailable) describes primitive HSCs and their immediate progeny as a continuum rather than discrete populations. The Discussion says these cells gradually acquire lineage priming in multiple directions, supporting the description of a structured continuum. The finding concerns early HSPCs; the paper says more differentiated progenitors form discrete populations. (LLM, conf=0.88)
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“In addition, the high-dimensional nature of scSeq allows more than one approach to constructing cell state trajectories from the same data (4).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > Introduction
What the sources say
- Supportedcites [4] source
The introduction describes multiple methods for reconstructing trajectories from high-dimensional single-cell snapshots. The section “Multiple Dynamic Trajectories Can Generate the Same High-Dimensional” says that dynamic inference has no unique solution, supporting the claim that the same data can yield more than one trajectory. Page numbers are unavailable in our copy. (LLM, conf=0.90)
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“scSeq captures mature cell types alongside all stages of cell differentiation, revealing a ‘state map’ in gene expression space.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > Introduction
What the sources say
- Partly supportedcites [3] sourceExperimental — accuracy not yet measured
In “Single-Cell Experimental Technologies to Interrogate Cell States From Tissues” (page unavailable), the paper says scRNA-seq measures gene expression and describes cell states as positions in a molecular-marker data space. It also says transitional states can be sampled to infer a continuum, but they are often rare and require dense sampling; it does not support the claim that sequencing captures every differentiation stage. (LLM, conf=0.85)
- Partly supportedcites [4] sourceExperimental — accuracy not yet measured
The paper’s discussion of genome-scale single-cell measurements says scRNA-seq can generate an atlas of tissue cell states, and its hematopoiesis analysis describes a continuum of expression states at various stages of maturity. It does not say scRNA-seq captures every differentiation stage or necessarily includes mature cell types; the mapped endpoints in that analysis are identified as progenitors. No page numbers are available in our copy. (LLM, conf=0.87)
- Not checked — no full text of the sourcecites [5] source
- Partly supportedcites [6] sourceExperimental — accuracy not yet measured
Figure 3 (Abstract; page unavailable) shows a gene-expression embedding containing major transient and mature cell subpopulations, supporting the idea of a state map. The paper does not establish that single-cell RNA sequencing captures *all* stages of differentiation; its abstract also describes each measurement as a static snapshot. (LLM, conf=0.84)
- Not checked — no full text of the sourcecites [7] source
plaindirect- 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.
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It may state two separate claims as one.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“The gold standard for inferring the relationship between progenitors and their offspring is lineage tracing, where a subset of progenitors is labeled, typically using genetic approaches that mark cells expressing defined marker genes, and their fate is profiled at a later time point (1).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > Introduction
What the sources say
- Partly supportedcites [1] sourceExperimental — accuracy not yet measured
The Abstract describes fate maps as important tools for defining relationships between embryonic and later tissue structure, and Section 2 explains how genetic labeling tracks descendants over time. The paper supports the use of lineage tracing for this purpose, but does not establish the citing sentence’s stronger claim that it is the gold standard. (LLM, conf=0.82)
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“But recent state maps from scSeq (9), as well as clonal studies using barcodes (10) and single cell culture (11), suggest that the traditional intermediate cell types are internally heterogeneous in state and fate potential, with HSPCs lying along a continuum of states rather than a stepwise hierarchy.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > Introduction
What the sources say
- Supportedcites [9] source
Split into 2 atoms — 2 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
- Partly supportedcites [10] sourceExperimental — accuracy not yet measured
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
- Partly supportedcites [11] sourceExperimental — accuracy not yet measured
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
hedgedcorrelational- 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.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“For cells undergoing multi-lineage fate choice, scSeq has been used to estimate lineage hierarchy based on the assumption that cell types with transcriptionally similar differentiation pathways are clonally related (3–5, 7).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Agreement of state and clonal differentiation hierarchies
What the sources say
- Partly supportedcites [3] sourceExperimental — accuracy not yet measured
The ‘Downstream Analysis of Reconstructed Trajectories’ section (page unavailable) says that single-cell trajectories can indicate branching cell-fate decisions and hierarchical relationships. But ‘Notes on Using and Evaluating Trajectory Reconstruction Algorithms’ (page unavailable) distinguishes inferred cell-state transitions from parent–child lineage, which requires experimental validation; it does not establish that transcriptionally similar pathways imply clonal origin. (LLM, conf=0.85)
- Partly supportedcites [4] sourceExperimental — accuracy not yet measured
The introduction says earlier single-cell methods fitted curves or trees to cell-state distributions to reconstruct differentiation trajectories, including branching ones. It does not say those studies assumed transcriptionally similar pathways imply clonal relatedness; that specific assumption is unsupported by our copy. (LLM, conf=0.82)
- Not checked — no full text of the sourcecites [5] source
- Not checked — no full text of the sourcecites [7] source
plaincorrelational- 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.
Probably not a substantial claim.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“This reasoning reflects a formal result known as the Data Processing Inequality (20) (Supp Methods 10.1).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Functional purity of scSeq-defined cell states
What the sources say
- Supportedcites [20] source
The Self-consistent equitability section (p. 6) defines the Data Processing Inequality as a formal condition and explains that it captures the intuition that information is lost, not gained, through a noisy channel. This supports the cited sentence’s characterization of the reasoning as reflecting DPI. (LLM, conf=0.91)
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
- Supported
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
“On this landscape clones exhibited a range of behaviors including uni-lineage and multi-lineage differentiation, and self-renewal of early progenitors (Fig 1g).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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It may state two separate claims as one.
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
“In these two experiments, 38% and 63% of cells respectively belonged to a clone of two or more cells (5864 and 7751 clones), with 1,816 and 817 clones in total spanning early and late timepoints (Fig 1d,i).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether 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.
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 found that pairs of sisters profiled on day 2 localized in the SPRING graph, had correlated gene expression (median R=0.846) and that a majority (70%) fell in the same or nearest neighbor cluster (Fig 2a,b; Supp Fig 4a–d; Supp Methods section 5).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
plaincorrelational- 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.
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
“In these two experiments, 38% and 63% of cells respectively belonged to a clone of two or more cells (5864 and 7751 clones), with 1,816 and 817 clones in total spanning early and late timepoints (Fig 1d,i).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether 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.
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
“Where the progenitors for different fates overlapped, we observed bi-potent or oligopotent clones, indicating the location of fate commitment boundaries (Fig 2d).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
hedgedcorrelational- 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.
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
“In these two experiments, 38% and 63% of cells respectively belonged to a clone of two or more cells (5864 and 7751 clones), with 1,816 and 817 clones in total spanning early and late timepoints (Fig 1d,i).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether 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.
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
“A minority of cells, however, were more diverged, with 10% falling outside a four-cluster radius (compared to 80% for random cell pairs).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“We did not detect megakaryocytes, possibly because they did not survive bone marrow harvest, flow-sorting and single-cell encapsulation intact.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > A simultaneous assay of clonal states and fates
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
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
“In the data, monocytes appeared to form a spectrum from neutrophil-like to DC-like, expressing alternatively neutrophil elastase (Elane) and other neutrophil markers, or MHC class II components (Cd74 and H2-Aa) (Fig 4a).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Distinct routes of monocyte differentiation
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“We demonstrated that this strategy can be simply extended to paired perturbation experiments that compare sister cells treated in different states.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > DISCUSSION
boosted- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
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
“Across all conditions, the highest overall predictive accuracy from transcriptional state was 60% in vitro and 51% in vivo.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > How predictable is cell fate from gene expression?
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- 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.
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
“As in vitro, the DC-related monocytes were enriched for DC marker genes, whereas neutrophil-related monocytes were enriched for neutrophil markers (Fig 4g,h).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Distinct routes of monocyte differentiation
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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It may state two separate claims as one.
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
“with the most accurate algorithms achieving late prediction accuracy of 76% in vitro and 70% in vivo, compared to 60% and 52% respectively for early prediction.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Functional purity of scSeq-defined cell states
plaincorrelational- 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.
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 multipotent progenitor (CD34+) fraction of day 2 cells (Fig 2e) contained several broad domains, including a restricted central domain of stem cell marker (Procr) expression, a wing expressing Gata2 – an erythroid and stem cell marker – and an opposing wing expressing Flt3 indicative of lymphoid priming.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
plain- Asserted: passes — The authors put it forward as true.
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- 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.
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
“For example, Ikaros family zinc finger 2 (Ikzf2) – a myeloid leukemia gene not previously associated with fate choice – was enriched in eosinophil and mast cell progenitors, but not basophil or megakaryocyte.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether 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.
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
“Transcription factors were only marginally more informative than random size-matched gene sets (10% more informative in vitro; 3% more informative in vivo), whereas differentially expressed genes were substantially more informative (38% more informative in vitro; 20% more informative in vivo).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > How predictable is cell fate from gene expression?
plaincorrelational- 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.
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
“Second, we analyzed classical monocytes (Supp Fig 10g) and human peripheral blood monocytes (Supp Fig 10h) by scSeq. Principal component analysis shows that in both cases a spectrum exists of neutrophil-like to DC-like gene expression (see Table 8 for differentially expressed genes), which is also evident in the expression of marker genes (Fig 4i).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Distinct routes of monocyte differentiation
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- 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.
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
“Megakaryocyte, basophil, mast cell and eosinophil potential were all restricted to the Gata2+ region, yet derived from separate subsets within this region.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“As before the cells spanned a continuous landscape with domains of primed gene expression, including a central domain of stem cell (Procr) and opposing wings of Gata2 and Flt3 expression (Fig 2h), that correlated with output into the nine respective post-transplant fates (Fig 2i).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“but in the early progenitor (Cd34+) region, clonal tracking revealed a bifurcation of monocyte and neutrophil potential that was generally not detected by the prediction algorithms, although FateID performed slightly better (Fig 5c,d; R < 0.26 for all methods).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > scSeq-based models do not fully predict fate choice
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“Cell culture and transplantation studies over several decades have led to the prevailing model of hematopoiesis as a branching hierarchy with defined fate-restricted intermediates (8).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > Introduction
What the sources say
- Not checked — no full text of the sourcecites [8] source
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In the paper
“These tests justified approximating single-cell trajectories by clonal trajectories, though with some loss in resolution of fate boundaries expected due to ~10% diverged sister pairs.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“scSeq data does not directly report the stages at which progenitor cells become committed to one or more fates or how many distinct paths might lead cells to the same end states.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > Introduction
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“LARRY defines a scSeq-compatible lineage tracing approach that links cell states to clonal fates simultaneously from multiple initial conditions, without needing to target each specific progenitor state.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > DISCUSSION
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“This analysis agrees with earlier observations (21).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Distinct routes of monocyte differentiation
What the sources say
- Not checked — no full text of the sourcecites [21] source
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In the paper
“These results are consistent with a recent finding that immunophenotypically-defined monocyte-dendritic progenitors (MDPs) and granulocyte-monocyte progenitors (GMPs) give rise to monocytes with DC-like and neutrophil-like characteristics, respectively (21).”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Distinct routes of monocyte differentiation
What the sources say
- Not checked — no full text of the sourcecites [21] source
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“and that cells differentiate via a continuous, structured fate hierarchy that differs from classical tree-like depictions of hematopoiesis in its clonal structure.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > DISCUSSION
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“These results suggest that the predictive content of our gene expression measurements in HSPCs is almost entirely contained within several hundred differentially expressed genes, and only marginally enriched in transcription factors.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > How predictable is cell fate from gene expression?
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“Further, bipotent domains formed extended fate boundaries, indicating that differentiation progression can occur independently of fate commitment over some time.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
hedgedconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“Overall, these observations support the view that functional lineage priming varies across a continuous hematopoietic progenitor landscape and covaries with the heterogenous expression of genes, including transcription factors and a wide array of other functional gene categories.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“Thus, the DC-like and neutrophil-like trajectories observed here likely represent MDP and GMP pathways of monocyte differentiation, and they clarify the location of these states in a gene expression continuum.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Distinct routes of monocyte differentiation
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“As with CRISPR-based approaches, the method cannot study processes faster than one cell cycle.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > DISCUSSION
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“which could be explained by cells remaining in the MPP state for a variable duration before initiating neutrophil differentiation.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Temporal progression is captured by pseudotime
hedgedconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“Our data therefore contains two different pathways of monocyte differentiation with distinct clonal relationships and gene expression dynamics.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Distinct routes of monocyte differentiation
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“Despite the less mature state of these cells, each fate outcome correlated with unique enriched genes prior to transplantation (Fig 2j; n=190 [173 unique] differentially expressed genes at FDR=0.05; Table 3), indicating a surprising degree of specific priming at this early stage of differentiation.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Clonal dynamics identify early transcriptional fate boundaries
hedgedcorrelationaln = 190- Asserted: passes — The authors put it forward as true.
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In the paper
“and it does not require delivering multiple components.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > DISCUSSION
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“These results provide a framework for comparing computational models of differentiation, and may serve as a useful benchmark for improving them.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > scSeq-based models do not fully predict fate choice
hedgedconditional- Asserted: passes — The authors put it forward as true.
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- Rests on an assumption: A shortage of ground-truth data has made it difficult to compare and validate current methods for modeling cell-state dynamics.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These improvements in accuracy for late prediction reflect the high rate of concordance between sisters cell fates, and hold for clones of all potencies (Fig 3d)”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Functional purity of scSeq-defined cell states
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“Yet this assumption may not always hold: similar end states could also arise from non-overlapping clones (26) and distant end states could share lineage through asymmetric division.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Agreement of state and clonal differentiation hierarchies
What the sources say
- Not checked — no full text of the sourcecites [26] source
hedged- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — 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 distinct clonal origins of monocytes suggested that they arise from progenitors with different fate potentials, and possibly different gene expression.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Distinct routes of monocyte differentiation
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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None of the sources cited for this claim have been checked yet.
In the paper
“If there were no hidden variables, we reasoned that the information shared between separated sister cells could only decrease as time passes.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Functional purity of scSeq-defined cell states
hedgeddirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the paper
“Conversely, if there are stable properties that influence cell fate but are hidden from scSeq, then the mutual information between sisters could increase over time as these properties manifest in cell fate.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Functional purity of scSeq-defined cell states
hedgedconditional- Asserted: fails — The authors may not put it forward as true.
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Probably not a substantial claim. The authors may not put it forward as true.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These results support the use of pseudotime methods for mapping differentiation progression.”
§ Lineage tracing on transcriptional landscapes links state to fate during differentiation > RESULTS > Temporal progression is captured by pseudotime
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
The authors state this as an assumption.
If no hidden variables exist, the two day-6 fates are independent once the day-2 state is conditioned on.
“Without hidden variables, the two fates observed at day 6 should be statistically independent after conditioning on the day 2 state.”
The paper relies on this without support.
A shortage of ground-truth data has made it difficult to compare and validate current methods for modeling cell-state dynamics.
“Due to a lack of ground truth data, existing methods have been hard to compare and validate.”
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“We adapted culture conditions37,39 that permit the parallel differentiation of primary mouse HSCs into red blood cells, megakaryocytes, neutrophils, eosinophils, basophils, monocytes and dendritic cells.”
From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [37]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“all primary hematopoietic cells activate Trp53 upon lentiviral infection87 without affecting the differentiation of cells in the ex vivo system used here.37,39”
From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [37]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Advanced primary cell models of hematopoietic differentiation37,38,39 provide a unique opportunity to study this broadly relevant question, as they allow for measuring the activity of a large number of synthetic DNA constructs in a complex model of stemness and differentiation.”
From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [37]
In the citing paper
“PCA-batch-correction was performed using Patient 4 as a reference, as previously described (93).”
From Non-neuronal expression of SARS-CoV-2 entry genes in the olfactory system suggests mechanisms underlying COVID-19-associated anosmia (2020) · cites this paper as [93]
In the citing paper
“Further complicating the picture of hematopoiesis, it appears that there are multiple differentiation paths that cells can follow to produce the same lineage, such as is observed for monocyte differentiation (Figure 2) (Weinreb et al., 2020).”
From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Weinreb et al., 2020
In the citing paper
“While cell-sorting based methods often show a multipotent HSC and progenitor compartment that gives rise to unipotent lineage-committed cells (Notta et al., 2016), the combination of scRNA-seq and cell barcoding has now directly demonstrated that the early fate biases in hematopoietic stem and progenitor cells (HSPCs) significantly impact eventual fate (Weinreb et al., 2020).”
From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Weinreb et al., 2020
Citations
Cites
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“Missing information of this type is akin to the notion of “missing heritability” in population genetics 29 .”
BackgroundTrapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314 · cited 1×
“A common goal of scSeq is to order gene expression along dynamic trajectories by defining a “pseudotime” coordinate that orders transcriptomes (24).”
BackgroundLa Manno, G., Soldatov, R., Zeisel, A., Braun, E., Hochgerner, H., Petukhov, V., Lidschreiber, K., Kastriti, M. E., Lönnerberg, P., Furlan, A., et al. (2018) · Nature · doi:10.1038/s41586-018-0414-6 · Cited by 4,118
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Self-citationA 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 · cited 1×
“Cell culture and transplantation studies over several decades have led to the prevailing model of hematopoiesis as a branching hierarchy with defined faterestricted intermediates (8).”
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A revised airway epithelial hierarchy includes CFTR-expressing ionocytes
Montoro, D. T., Haber, A. L., Biton, M., Vinarsky, V., Lin, B., Birket, S. E., Yuan, F., Chen, S., Leung, H. M., Villoria, J., et al. (2018) · Nature · doi:10.1038/s41586-018-0393-7 · Cited by 1,206 · cited 1×
“This approach can map the fate of cells from a continuous landscape of starting states and does not require isolation or labeling of specific prospective progenitor populations (2, 14).”
BackgroundA single-cell atlas of the airway epithelium reveals the CFTR-rich pulmonary ionocyte
Plasschaert, L. W., Žilionis, R., Choo-Wing, R., Savova, V., Knehr, J., Roma, G., Klein, A. M., & Jaffe, A. B. (2018) · Nature · doi:10.1038/s41586-018-0394-6 · Cited by 1,047
Self-citationHuman 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 · cited 1×
“Consistent with recent scSeq studies (19), progenitors with different fate potentials did not partition into discrete cell states, but instead formed a structured continuum.”
BackgroundSingle-cell mapping of gene expression landscapes and lineage in the zebrafish embryo
Wagner, D. E., Weinreb, C., Collins, Z. M., Briggs, J. A., Megason, S. G., & Klein, A. M. (2018) · Science · doi:10.1126/science.aar4362 · Cited by 849 · cited 1×
“However, this assumption may not always hold: Similar end states could also arise from nonoverlapping clones (26), and distant end states could share lineage through asymmetric division.”
BackgroundSelf-citationSchiebinger, G., Shu, J., Tabaka, M., Cleary, B., Subramanian, V., Solomon, A., Gould, J., Liu, S., Lin, S., Berube, P., et al. (2019) · Cell · doi:10.1016/j.cell.2019.01.006 · Cited by 829 · cited 3×
“We tested three recent approaches, Population Balance Analysis (PBA) 4 , WaddingtonOT (WOT) 5 , and FateID 7 for their ability to predict the fate of a cell choosing between neutrophil and monocyte fates.”
Clonal dynamics of native haematopoiesis
Sun, J., Ramos, A., Chapman, B., Johnnidis, J. B., Le, L., Ho, Y.-J., Klein, A. M., Hofmann, O., & Camargo, F. D. (2014) · Nature · doi:10.1038/nature13824 · Cited by 803 · cited 1×
“Third, in native hematopoiesis, we examined the clonal cooccurrence of Mos with DCs and Neus after genetically barcoding HPC clones in a nonperturbativemanner using a transposase-based strategy (22) (materials and methods, section 12.”
MethodSelf-citationDistinct 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 · cited 1×
“However, recent state maps from scSeq (9), as well as clonal studies using barcodes (10) and single-cell culture (11), suggest that the traditional intermediate cell types are internally heterogeneous in state and fate potential, with HSPCs lying along a continuum of states rather than a stepwise hierarchy.”
BackgroundA single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation
Nestorowa, S., Hamey, F. K., Pijuan Sala, B., Diamanti, E., Shepherd, M., Laurenti, E., Wilson, N. K., Kent, D. G., & Göttgens, B. (2016) · Blood · doi:10.1182/blood-2016-05-716480 · Cited by 768 · cited 1×
“However, recent state maps from scSeq (9), as well as clonal studies using barcodes (10) and single-cell culture (11), suggest that the traditional intermediate cell types are internally heterogeneous in state and fate potential, with HSPCs lying along a continuum of states rather than a stepwise hierarchy.”
BackgroundPietras, E. M., Reynaud, D., Kang, Y.-A., Carlin, D., Calero-Nieto, F. J., Leavitt, A. D., Stuart, J. M., Göttgens, B., & Passegué, E. (2015) · Cell stem cell · doi:10.1016/j.stem.2015.05.003 · Cited by 723 · cited 1×
“In hematopoiesis, clonal tracing studies have shown evidence of functional lineage priming of multipotent progenitor cells (MPPs) 32 .”
BackgroundEquitability, mutual information, and the maximal information coefficient
Kinney, J. B., & Atwal, G. S. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1309933111 · Cited by 667 · cited 1×
“This reasoning reflects a formal result knownas data-processing inequality (20) (materials and methods, section 10.”
MethodClonal analysis of lineage fate in native haematopoiesis
Rodriguez-Fraticelli, A. E., Wolock, S. L., Weinreb, C. S., Panero, R., Patel, S. H., Jankovic, M., Sun, J., Calogero, R. A., Klein, A. M., & Camargo, F. D. (2018) · Nature · doi:10.1038/nature25168 · Cited by 596
Self-citationSimultaneous 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 · cited 1×
“The strategy differs from CRISPR-based lineage-tracing approaches (27, 28) in that it links states across time, not only at a single end point.”
MethodYáñez, A., Coetzee, S. G., Olsson, A., Muench, D. E., Berman, B. P., Hazelett, D. J., Salomonis, N., Grimes, H. L., & Goodridge, H. S. (2017) · Immunity · doi:10.1016/j.immuni.2017.10.021 · Cited by 470 · cited 4×
“This analysis agrees with earlier observations (21).”
BackgroundResultInfluentialLu, R., Neff, N. F., Quake, S. R., & Weissman, I. L. (2011) · Nature Biotechnology · doi:10.1038/nbt.1977 · Cited by 451 · cited 1×
“We modified a classical strategy for clonal labeling by lentiviral delivery of inherited DNA barcodes (15, 16) to allow barcode detection using scSeq (17).”
MethodSingle-cell mapping of lineage and identity in direct reprogramming
Biddy, B. A., Kong, W., Kamimoto, K., Guo, C., Waye, S. E., Sun, T., & Morris, S. A. (2018) · Nature · doi:10.1038/s41586-018-0744-4 · Cited by 390 · cited 1×
“We modified a classical strategy for clonal labeling by lentiviral delivery of inherited DNA barcodes (15, 16) to allow barcode detection using scSeq (17).”
MethodPopulation snapshots predict early haematopoietic and erythroid hierarchies
Tusi, B. K., Wolock, S. L., Weinreb, C., Hwang, Y., Hidalgo, D., Zilionis, R., Waisman, A., Huh, J. R., Klein, A. M., & Socolovsky, M. (2018) · Nature · doi:10.1038/nature25741 · Cited by 384 · cited 1×
“To understand hematopoietic fate control, we and others have been interested in developing data-drivenmodels of gene expression dynamics constrained by scSeq data (3, 4, 5, 7, 23).”
MethodSelf-citationSingle-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 · cited 1×
“Reconciling these views requires tracking the dynamics of individual lineages on the continuous landscape of HSPC states defined by scSeq (12).”
BackgroundMolecular recording of mammalian embryogenesis
Chan, M. M., Smith, Z. D., Grosswendt, S., Kretzmer, H., Norman, T. M., Adamson, B., Jost, M., Quinn, J. J., Yang, D., Jones, M. G., et al. (2019) · Nature · doi:10.1038/s41586-019-1184-5 · Cited by 364 · cited 1×
“The strategy differs from CRISPR-based lineage-tracing approaches (27, 28) in that it links states across time, not only at a single end point.”
MethodFateID infers cell fate bias in multipotent progenitors from single-cell RNA-seq data
Herman, J. S., Sagar, & Grün, D. (2018) · Nature Methods · doi:10.1038/nmeth.4662 · Cited by 363
Fundamental limits on dynamic inference from single-cell snapshots
Weinreb, C., Wolock, S., Tusi, B. K., Socolovsky, M., & Klein, A. M. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1714723115 · Cited by 341 · cited 6×
“At present, it is unknown how single cells traverse these trajectories, including whether they progress at different rates or even reverse their dynamics (4).”
BackgroundMethodInfluentialSelf-citationSPRING: a kinetic interface for visualizing high dimensional single-cell expression data
Weinreb, C., Wolock, S., & Klein, A. M. (2018) · Bioinformatics · doi:10.1093/bioinformatics/btx792 · Cited by 298
Self-citationCellular barcoding tool for clonal analysis in the hematopoietic system
Gerrits, A., Dykstra, B. J., Kalmykowa, O. J., Klauke, K., Verovskaya, E. V., Broekhuis, M., de Haan, G., & Bystrykh, L. V. (2010) · Blood · doi:10.1182/blood-2009-06-229757 · Cited by 253
Essential role of the IRF8-KLF4 transcription factor cascade in murine monocyte differentiation
Kurotaki, D., Osato, N., Nishiyama, A., Yamamoto, M., Ban, T., Sato, H., Nakabayashi, J., Umehara, M., Miyake, N., Matsumoto, N., et al. (2013) · Blood · doi:10.1182/blood-2012-06-437863 · Cited by 252 · cited 3×
“…and focusing on the earliest progenitors (Fig 2h; region identified by high expression of Cd34), we observed that the regions of bias toward each lineage overlapped closely with the expression of known hematopoietic transcription factors (Fig 2i) (e.g. Gata2 20 , Gfi1 21 , Irf8 22 and Satb1 23 ).”
BackgroundBuilding a lineage from single cells: genetic techniques for cell lineage tracking
Woodworth, M. B., Girskis, K. M., & Walsh, C. A. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2016.159 · Cited by 236 · cited 3×
“Lineage maps are key to understanding and controlling differentiation (2).”
BackgroundThe Branching Point in Erythro-Myeloid Differentiation
Perié, L., Duffy, K. R., Kok, L., de Boer, R. J., & Schumacher, T. N. (2015) · Cell · doi:10.1016/j.cell.2015.11.059 · Cited by 185 · cited 3×
“3D), consistent with recent observations of clonal fate restriction among HSPCs (10).”
BackgroundMethodGörgens, A., Radtke, S., Möllmann, M., Cross, M. A., Dürig, J., Horn, P. A., & Giebel, B. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.04.025 · Cited by 174 · cited 2×
“From these biased states, cells differentiate via a structured fate hierarchy that differs from classical tree-like depictions of hematopoiesis in its clonal structure and confirms recently-established ontogenies of granulocytes 25,33 and monocytes 27 .”
BackgroundSchiebinger, G., Shu, J., Tabaka, M., Cleary, B., Subramanian, V., Solomon, A., Gould, J., Liu, S., Lin, S., Berube, P., et al. (2019) · Cell · doi:10.1016/j.cell.2019.02.026 · Cited by 139
A genome-wide and nonredundant mouse transcription factor database
Kanamori, M., Konno, H., Osato, N., Kawai, J., Hayashizaki, Y., & Suzuki, H. (2004) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2004.07.179 · Cited by 122
Differentiation and Characterization of Myeloid Cells
Gupta, D., Shah, H. P., Malu, K., et al. (2014) · Current Protocols in Immunology · doi:10.1002/0471142735.im22f05s104 · Cited by 116 · cited 1×
“The time for an MPP to differentiate into a myelocyte was 10 days, consistent with previous results (25).”
ResultThe Satb1 Protein Directs Hematopoietic Stem Cell Differentiation toward Lymphoid Lineages
Satoh, Y., Yokota, T., Sudo, T., Kondo, M., Lai, A. Y., Kincade, P. W., Kouro, T., Iida, R., Kokame, K., Miyata, T., et al. (2013) · Immunity · doi:10.1016/j.immuni.2013.05.014 · Cited by 115 · cited 2×
“…and focusing on the earliest progenitors (Fig 2h; region identified by high expression of Cd34), we observed that the regions of bias toward each lineage overlapped closely with the expression of known hematopoietic transcription factors (Fig 2i) (e.g. Gata2 20 , Gfi1 21 , Irf8 22 and Satb1 23 ).”
BackgroundThe STAT5-GATA2 Pathway Is Critical in Basophil and Mast Cell Differentiation and Maintenance
Li, Y.-P., Qi, X.-P., Liu, B., & Huang, H. (2015) · Journal of Immunology · doi:10.4049/jimmunol.1500018 · Cited by 113 · cited 1×
“…and focusing on the earliest progenitors (Fig 2h; region identified by high expression of Cd34), we observed that the regions of bias toward each lineage overlapped closely with the expression of known hematopoietic transcription factors (Fig 2i) (e.g. Gata2 20 , Gfi1 21 , Irf8 22 and Satb1 23 ).”
BackgroundCellular barcoding: A technical appraisal
Naik, S. H., Schumacher, T. N., & Perié, L. (2014) · Experimental Hematology · doi:10.1016/j.exphem.2014.05.003 · Cited by 80 · cited 1×
“The pLARRY vector was constructed by DNA synthesis and Gateway cloning (Vectorbuilder) using a protocol loosely adapted from (Naik, Schumacher et al. 2014) and (Gerrits, Dykstra et al. 2010).”
MethodSierra, M. D. L. L., Sakakibara, S., Gasperini, P., Salvucci, O., Jiang, K., McCormick, P. J., Segarra, M., Stone, J., Maric, D., Zhu, J., et al. (2010) · Blood · doi:10.1182/blood-2009-10-246967 · Cited by 57
Essentials of Recombinase-Based Genetic Fate Mapping in Mice
Jensen, P., & Dymecki, S. M. (2014) · Methods in Molecular Biology · doi:10.1007/978-1-60327-292-6_26 · Cited by 54 · cited 1×
“The gold standard for inferring the relationship between progenitors and their offspring is lineage tracing, in which a subset of progenitors is labeled, typically using genetic approaches that mark cells expressing defined marker genes, and their fate is profiled at a later time point (1).”
BackgroundSchiebinger, G. R., Shu, J., Tabaka, M., Cleary, B., Subramanian, V., Solomon, A., Liu, S., Lin, S. L., Berube, P., Lee, L., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/191056 · Cited by 54
Lin, D. S. Y., Kan, A., Gao, J., Crampin, E. J., Hodgkin, P. D., & Naik, S. H. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.02.046 · Cited by 44 · cited 1×
“We modified a classical strategy for clonal labeling by lentiviral delivery of inherited DNA barcodes (15, 16) to allow barcode detection using scSeq (17).”
MethodSingle-Cell Computational Strategies for Lineage Reconstruction in Tissue Systems
Herring, C. A., Chen, B., McKinley, E. T., & Lau, K. S. (2018) · Cellular and Molecular Gastroenterology and Hepatology · doi:10.1016/j.jcmgh.2018.01.023 · Cited by 35 · cited 2×
“To understand hematopoietic fate control, we and others have been interested in developing data-drivenmodels of gene expression dynamics constrained by scSeq data (3, 4, 5, 7, 23).”
BackgroundMethodGónzalez-Murillo, Á., Lozano, M. L., Montini, E., Bueren, J., & Guenechea, G. (2008) · Blood · doi:10.1182/blood-2008-03-142661 · Cited by 33 · cited 1×
“Virally transduced HPCs underwent transient aggregation but showed little difference in gene expression or lineage distribution compared to controls when analyzed by scSeq (Supp Fig 1d,e), consistent with previous reports 18 .”
ResultSIS-seq, a molecular ‘time machine’, connects single cell fate with gene programs
Tian, L., Schreuder, J., Zalcenstein, D., Tran, J., Kocovski, N., Su, S., Diakumis, P., Bahlo, M., Sargeant, T., Hodgkin, P. D., et al. (2018) · doi:10.1101/403113 · Cited by 10 · cited 1×
“Our strategy for simultaneously capturing transcriptional cell state and fate is to genetically barcode a heterogeneous progenitor population, allow cell division, sample some cells immediately for scSeq profiling, and then sample the remaining cells later (13).”
Method
Cited by
Sorted by citations
Brann, D. H., Tsukahara, T., Weinreb, C., Lipovsek, M., Van den Berge, K., Gong, B., Chance, R., Macaulay, I. C., Chou, H.-J., Fletcher, R. B., et al. (2020) · Science Advances · doi:10.1126/sciadv.abc5801 · Cited by 1,198
Self-citationCellRank for directed single-cell fate mapping
Lange, M., Bergen, V., Klein, M., Setty, M. N., Reuter, B., Bakhti, M., Lickert, H., Ansari, M., Gote-Schniering, J., Schiller, H. B., et al. (2022) · Nature Methods · doi:10.1038/s41592-021-01346-6 · Cited by 783
“To overcome the deficiencies of splicing data, it may be possible to extend the CellRank model to epigenetic information such as chromatin accessibility, leveraging the directional information coded by the typical delay between epigenetic and transcriptional changes 61,62 .”
Xu, C., Lopez, R., Mehlman, E., Regier, J., Jordan, M. I., & Yosef, N. (2021) · Molecular Systems Biology · doi:10.15252/msb.20209620 · Cited by 691
“In the simplest scenario, we have access to one dataset where states have been annotated either ab initio , or using additional experimental measurements (e.g., protein expression (Zheng et al , 2017; Stoeck-ius et al , 2017) or lineage tracing (Weinreb et al , 2020)) and another, unannotated…”
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 684
Non-genetic mechanisms of therapeutic resistance in cancer
Marine, J., Dawson, S., & Dawson, M. A. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-020-00302-4 · Cited by 698
Metadata
- Authors
- Weinreb, C., Rodriguez-Fraticelli, A., Camargo, F. D., & Klein, A. M.
- Affiliations
- Harvard University (US)
- Boston Children's Hospital (US)
- Corresponding author
- Klein, Allon M.
- Venue
- Science
- Published
- 2020-02-14
- Volume
- 367
- Issue
- 6479
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC7608074
- OpenAlex
- W3002219094
- Semantic Scholar
- 572846affc0d995127aa26185ad9dadb30744381
- Cited by
- 759
- References
- 36
- Citations by year
- 2026: 166 · 2025: 121 · 2024: 110 · 2023: 92 · 2022: 90 · 2021: 101 · 2020: 71
- FWCI
- 25.30
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc
- Locations
- Science (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (submittedVersion, cc-by-nc)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (K99HL146983)
- NIH Office of the Director (R33CA212697-01, 1R01HL14102-01, HL128850-01A1, P01HL13147)
- American Society of Hematology (3391-19)
- Chan Zuckerberg Initiative (2018-182714)
- Harvard Stem Cell Institute (DP-0174-18-00)
- EMBO (ALTF 675-2015)
- 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 › Developmental Biology and Gene Regulation
- Keywords
- lineage tracing, clonal tracing, single-cell transcriptomics, hematopoiesis, cell fate determination, transcriptional landscape, hematopoietic hierarchy, granulopoiesis, monocyte differentiation, developmental hierarchy, stem cell differentiation
- MeSH terms
- RNA-Seq, Algorithms, Animals, Hematopoiesis, Monocytes, Gene Expression, Cell Lineage, Mice, DNA Barcoding, Taxonomic, Single-Cell Analysis, Transcriptome
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