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
14 of 23 cited sources checked · 6 supported · 0 flagged · 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)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- 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
Load-bearingStrength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA 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
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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
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA 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
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA 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
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA 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
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA 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
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA 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
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA 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
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- 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)
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- 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)
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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)
Strength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably 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.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably 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)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably 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
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt 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
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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
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably 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
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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
Strength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably 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?
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt 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?
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“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
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“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
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
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
“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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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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?
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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
“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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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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
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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
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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
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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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
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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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
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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
“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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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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
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably 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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably 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
Tests✗ Asserted: fails✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably 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
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably 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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“A common goal of scSeq is to order gene expression along dynamic trajectories by defining a “pseudotime” coordinate that orders transcriptomes (24).”
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“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-citation
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Martinez, T. C., Jotte, M. R. M., Khan, S. S., Stoddart, A., Blaylock, H. Z., Malik, A., & McNerney, M. E. (2025) · Blood · doi:10.1182/blood.2024026815 · Cited by 4
Mathematical Framework for Hierarchical Cell Identity Control by Collective Enhancer Dynamics
Grishechkin, A., Mukherjee, A., & Karin, O. (2025) · PRX Life · doi:10.1103/dkmq-h4d9 · Cited by 5
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“The pre-dominance of EMPs and the absence of lymphoid lineages in our HEMO model are consistent with the profile of very early embryonic hematopoiesis, prior to the emergence of definitive HSCs [ 4 ].”
InfluentialHematopoiesis in High Definition: Combining State and Fate Mapping
Chahi, A. K., & Hope, K. J. (2020) · Cell stem cell · doi:10.1016/j.stem.2020.08.010 · Cited by 2
Gotzhein, F., Aranyossy, T., Thielecke, L., Sonntag, T., Thaden, V., Fehse, B., Müller, I., Glauche, I., & Cornils, K. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23063160 · Cited by 2
Hematopoietic stem cells depend on HIM and HER
Kent, D. G. (2022) · Experimental Hematology · doi:10.1016/j.exphem.2022.10.004 · Cited by 3
“Single-cell transcriptional profiling, lineage tracing, and cellular barcoding efforts, in particular [9 − 15], although numerous other -omics datasets have reinforced this (reviewed in Bode et al. [16]), have focused people ’ s attention on global molecular states being far more fluid than the…”
Dong, F., Cheng, H., Ema, H., & Cheng, T. (2020) · Science China Life Sciences · doi:10.1007/s11427-020-1786-4 · Cited by 2
Three-dimensional mapping identifies distinct vascular niches for myelopoiesisPreprint
Zhang, J., Wu, Q., Johnson, C. B., Olsson, A., Slaughter, A., May, M. L., Weinhaus, B., D’Alessandro, A., Engel, J. D., Jiang, J. X., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.02.014548 · Cited by 2
Genomic context sensitivity of insulator functionPreprint
Ribeiro-dos-Santos, A. M., Hogan, M. S., Luther, R. D., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.16.444030 · Cited by 2
Quantifying Cellular Pluripotency and Pathway Robustness through Forman-Ricci CurvaturePreprint
Murgas, K. A., Saucan, E., & Sandhu, R. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.03.462918 · Cited by 2
“However, the mathematical quantification of this landscape in regards to cellular trajectories and pluripotency in general has only been recently investigated [3, 4, 10] and to a large part, remains an open problem.”
BackgroundGene Expression Noise Dynamics Unveil Functional Heterogeneity of Ageing Hematopoietic Stem CellsPreprint
Rosales-Alvarez, R. E., Rettkowski, J., Herman, J. S., Dumbović, G., Cabezas‐Wallscheid, N., & Grün, D. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4197395 · Cited by 3
A time and single-cell resolved model of hematopoiesisPreprint
Kuciński, I., Campos, J., Barile, M., Severi, F., Bohin, N., Moreira, P. N., Allen, L., Lawson, H., Haltalli, M. L. R., Kinston, S., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.07.506735 · Cited by 2
A multi-kingdom genetic barcoding system for precise target clone isolationPreprint
Ishiguro, S., Ishida, K., Sakata, R. C., Mori, H., Takana, M., King, S. B., Bashth, O. S., Ichiraku, M., Masuyama, N., Takimoto, R., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.01.18.524633 · Cited by 2
“Furthermore, the combination of barcode transcription and single-cell 78 RNA sequencing (scRNA-seq) allows clonal lineages to be analyzed alongside cell states, revealing cell 79 lineage-restricted state trajectories (9, 17-23).”
BackgroundConsequences of training data composition for deep learning models in single-cell biologyPreprint
Nadig, A., Thoutam, A., Hughes, M., Gupta, A., Navia, A. W., Fusi, N., Raghavan, S., Winter, P. S., Amini, A. P., & Crawford, L. A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.19.639127 · Cited by 5
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“For this, we have explored the feasibility of using VISIBLE system for patient-derived cancer organoids pipelines that require DNA barcoding of cells using lentiviral delivery enabling lineage tracing and single-cell RNA sequencing to allow tracing of clones through phenotypic space 40 .”
Deciphering Cell Fate and Clonal Dynamics via Integrative Single-Cell Lineage ModelingPreprint
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“Examples of this are hematopoiesis, 14–18 homeostasis of the small intestinal epithelium, 19 and axolotl limb regeneration.”
BackgroundLeading Edge Techniques in the Quest for Characterizing Rare Hematopoietic Stem Cells
Patel, S. B., Franceski, A. M., Crown, B. L., & Welner, R. S. (2024) · Current Stem Cell Reports · doi:10.1007/s40778-024-00240-z · Cited by 1
Transcriptional landscape of direct reprogramming toward the hematopoietic lineage
Cwycyshyn, J., Stansbury, C. M., Golts, S., Lee, H., Pickard, J., Meixner, W., Rajapakse, I., & Muir, L. A. (2026) · iScience · doi:10.1016/j.isci.2026.117266 · Cited by 1
Reconstructing Progenitor State Hierarchy and Dynamics Using Lineage Barcoding Data
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Lineage Recording in Human Brain Organoids with iTracer
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“Innovations like single-cell long read-sequencing, for example, ONT and PacBio, and genetic barcoding techniques, for example, cell-tag indexing [23] and LARRY [24], provide unprecedented opportunities.”
The landscape of cell lineage tracing
Ye, F., Guang, L., Li, H., & Cheng, L. (2025) · Science China Life Sciences · doi:10.1007/s11427-024-2751-6 · Cited by 2
“These include Polylox (Cre/loxP combining unique DNA elements) with 1.8 million barcodes, LARRY (lineage and RNA recovery) with a library of approximately 0.5 million barcodes and TracerSeq (a transposon-based barcoding approach) with 1 trillion barcodes, (Pei et al., 2017; Weinreb et al., 2020).”
InfluentialCell Lineage Affiliation During Hematopoiesis
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Limitations and optimizations of cellular lineages tracking
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Physical Modeling of Embryonic Transcriptomes Identifies Collective Modes of Gene Expression
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IFNγ signaling drives resistance to FLT3 inhibition in acute myeloid leukemia
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Lineage-tracing technology for decoding cell evolution in pathophysiology: a bibliometric analysis
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Exploiting tumor lineage features for precision cancer therapy
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Interactive analysis of single-cell trajectories in 3D space with Cell Journey
Panas, D., & Tabaka, M. (2026) · GigaScience · doi:10.1093/gigascience/giag021
“Furthermore, we demonstrated Cell Journey’s utility for clonal data analysis using the dataset from Weinreb et al. [ 52 ] (GSE140802, Fig.”
Jin, L., Han, Z., Hannah, R., Shao, H., Huang, J., Wang, S., Zhang, W., Lin, J., Sun, K., & Yu, Y. (2026) · Briefings in Bioinformatics · doi:10.1093/bib/bbag114 · Cited by 1
“However, identifying lineage-committed precursors in vivo remains technically difficult due to their sparse distribution within complex tissue environments [10], which impedes further elucidation of the molecular mechanisms driving lineage commitment.”
The evolution of hematopoietic models through a clonal lens
Tomei, S., Weber, T., & Naik, S. H. (2026) · Blood · doi:10.1182/blood.2024028189 · Cited by 1
Multiscale learning of gene network-driven phenotypic dynamics of single cells
Zhang, D., Li, J., Nie, Q. H., & (493308), X. S. (2026) · Molecular Systems Biology · doi:10.1038/s44320-026-00220-x · Cited by 2
“For the lineage tracing data (Weinreb et al, 2020a; Data ref: Weinreb et al, 2020b), following the original study, we select a total of 15,007 cells from D2, D4, and D6, which belong to clones that differentiate into neutrophils (Neu) and monocytes (Mo).”
InfluentialSPACE-seq integrates spatial transcriptomics and lineage tracing in native tissues
Jia, Y., Sun, D., Weir, J. A., Liu, X., Russell, A. J. C., Kim, Y., Thom, N., Marrero, G. J., Kumar, V., Chen, F., et al. (2026) · Cell stem cell · doi:10.1016/j.stem.2026.05.017 · Cited by 5
Self-citationDNMT3A/TET2-mediated epigenetic alteration in Type-1 diabetes dysregulates the haematopoiesis
Mallick, S. (2026) · Molecular Biology Reports · doi:10.1007/s11033-026-12293-w · Cited by 1
“Research indicated that HSCs from T1D patients maintain hypermethylation at Foxp3 loci, hindering Treg development, and hypomethyl - ation at Ifng promotes Th1 polarization [46, 47].”
Beyond static biomarkers: systems biology and AI for decoding cancer dynamics
Dutta, S., & Goli, A. (2026) · Frontiers in Systems Biology · doi:10.3389/fsysb.2026.1855016 · Cited by 3
“Lineage-tracing technologies (Weinreb et al., 2020; Rodriguez-Fraticelli et al., 2018) now offer direct fate measurement that can calibrate computational models.”
CFM-GP: unified conditional flow matching to learn gene perturbation across cell types
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“Similarly Similarly, scPRAM [ 43 ] emphasizes probabilistic regulatory activity modeling, and PerturBench (Wu et al. , 2024, arXiv) provides a standardized benchmarking framework for perturbation prediction models [ 44 ][ 45 ][ 46 ].”
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“The basic principle for lineage tracing experiments was similar to that described in previous work 65 .”
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A DNA Typewriter records the cell lineage history of a mouse, from zygote to late organogenesis
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“Moreover, several references have reported successful allele-specific single-cell analysis and lineage tracing in mammalians, which may be capable of studying the sexual reproduction in microbes and reveal some unexpected phenomena and mechanisms in the life cycle of microorganisms (Zhang et al., 2018; Collombet et al…”
BackgroundTowards ‘end-to-end’ analysis and understanding of biological timecourse data
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“…to characterise complex, continuous biological systems with transitional cell states such as hematological differentiation (Velten et al., 2017; Weinreb et al., 2020), cellular reprogramming (Kong et al., 2022), as well as tumor development and plasticity (Kinker et al., 2020; Nadeu et al.,…”
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Multi-lineage Differentiation from Hematopoietic Stem Cells
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Cell cycle expression heterogeneity predicts degree of differentiation
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“…lineage tracing analysis of a hematopoietic cell differentiation dataset from Weinreb et al. in which undifferentiated cells are allowed to progress towards one of several terminal states and heritable DNA barcodes identify cells across three time points which share a common ancestor [38] (Fig.”
BackgroundMethodInfluentialRecording Lineage History with Cellular Barcodes in the Mammary Epithelium and in Breast Cancer
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HemAtlas: A Multi-omics Hematopoiesis Database
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Barcodes based on nucleic acid sequences: Applications and challenges (Review)
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“In the same year, Weinreb et al (118) employed expressed DNA barcodes to perform clonal tracing of tran‑ scriptomes over time, applying this approach to investigate fate determination during hematopoiesis.”
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“Advancesintranscriptomicsnowenable cellular diversity within organisms to be characterised at an unprecedented resolution 1 – 3 .”
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Single-Cell RNA Sequencing Technologies
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“26,27 Another conceptual consideration for development of synthetic models of lymphoid differentiation is to accommodate phenotype/function and transcriptional approaches with recently developed chromatin conformation analyses that allow for dissection of enhancer/promoter interactions at the…”
BackgroundThe EHA Research Roadmap: Normal Hematopoiesis.
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“19 published lentiviral barcoding over time that might be employed to more precisely quantify lineage bias at each stage in our protocol (Biddy et al., 2018; Weinreb et al., 2019).”
BackgroundMethodInfluentialSelf-citationOptimal Transport using GANs for Lineage TracingPreprint
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“We apply this framework to perform lineage tracing on the dataset of Weinreb et al. (2020).”
BackgroundMethodInfluentialSingle-cell Bayesian deconvolutionPreprint
Torregrosa-Cortés, G., Oriola, D., Trivedi, V., & García‐Ojalvo, J. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.02.13.480250 · Cited by 1
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“The other clusters (c1, 7, 9, 15, 16) expressed highest levels of LILRB1, LILRB2 and POU2F2 (Figure 2b, Table S4), features associated with differentiated monocytes (Weinreb et al., 2020).”
BackgroundMuVEH and mitoMuVEH improve discovery of genetic variation from single cellsPreprint
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“an expressed traceable tag) is made to an original cell to leave a heritable mark that can be followed through development [9, 10].”
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PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genesPreprint
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“We also provide important improvements to the nascent field of transcribed lineage barcoding 17 .”
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Natural and age-related variation in circulating human hematopoietic stem cellsPreprint
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CC-Tempo: A cell-cell communication aware temporal model of cellular dynamicsPreprint
Jony, S. S. R., Rahman, M. S., & Samee, M. A. H. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.04.569835 · Cited by 1
“In a similar fashion, the top 15 most important genes for the neutrophil lineage showed three of the previous neutrophil markers reported by Weinreb et al. ( Lcn2, S100a9, S100a8 ; Fig.”
BackgroundMethodInfluentialCharting Single Cell Lineage Dynamics and Mutation Networks via Homing CRISPRPreprint
Wang, L., Dong, W., Yin, Z., Sheng, J., Ezeana, C. F., Li, Y., Yu, X., Wong, S. S. Y., Wan, Z., Danforth, R. L., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.05.574236 · Cited by 1
Unveiling Clonal Cell Fate and Differentiation Dynamics: A Hybrid NeuralODE-Gillespie ApproachPreprint
Gao, M., Barile, M., Chabra, S., Haltalli, M. L. R., Calderbank, E. F., Chao, Y., Laurenti, E., Göttgens, B., & Huang, Y. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.08.602444 · Cited by 1
“We applied CLADES to a publicly available mouse hematopoietic dataset that was introduced by Weinreb, et al. 18 and also used to benchmark CoSpar 32 .”
BackgroundMethodInfluentialYang, S. J., Wang, Z., & Lin, K. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.28.620670 · Cited by 1
“• Hematopoietic Differentiation (Weinreb et al., 2020): The authors designed the LARRY protocol to barcode hematopoietic stem cells in mice over a 6-day experiment to study how cells commit to differentiating into certain cell types.”
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“To strengthen our understanding of the developmental trajectory and transcriptional maturity of Vgat +Esr1+clusters, we employed a support vector machine (SVM) classifier to predict the developmental state of single cells based solely on HA-DEGs ( Weinreb et al., 2020 ).”
Denstaedt, S. J., McBean, B. N., Boyle, A. P., Arenberg, B. C., Mack, M., Moore, B. B., Newstead, M. W., Deng, Y., Nesvizhskii, A. I., Singer, B. H., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.16.654442 · Cited by 1
Differentiation hierarchy in adult B cell acute lymphoblastic leukemia at clonal resolutionPreprint
Geßner, A., Jolly, A., Sijmonsma, T., Matthess, Y., Kaulich, M., Günther, S., Lang, F., Buettner, F., & Rieger, M. A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.10.674954 · Cited by 1
“By combining the information from cell barcodes expressed at the RNA level that are transferred to progeny throughout generations, scRNA-Seq can infer lineage development in embryogenesis and in adult stem cell systems 26–28 .”
Palii, C. G., Tur, S., Yan, S., Longabaugh, W. J. R., Solano, R., Dilworth, F. J., Ranish, J. A., & Brand, M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.11.675740 · Cited by 1
Blood Originates in Hypoblasts During Embryonic DevelopmentPreprint
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“Recent advances in transcriptomic and epigenomic profiles in single cells and molecular barcoding technology 16 17 has further enabled tracking the hematopoiesis in human stem cell-based models to address the origin of the earliest population of blood cells.”
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Multiplexed enrichment and tracking of lineages with CloneSweeperPreprint
Velde, R. V., Ng, R. W. S., Cote, C. J., & Shaffer, S. M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.30.700779 · Cited by 1
“Updated technologies, such as CellTag 10 and LARRY 11 , allow researchers to detect lineages in single-cell RNA sequencing (scRNA-seq) data by expressing their barcodes as RNA.”
Leukemia stem cell expansion cultures reveal clonal drivers of leukemogenesis and therapy responsePreprint
Singh, I., Polazzi, A., Pombo, A. M., López-Osias, M., Bauer, C., Guarini, M., Sánchez-Sánchez, P., Goulet, L., Gallardo, C., Fernández-Pérez, D., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.24.707683 · Cited by 1
“Lineage-associated transcriptional signatures were quantified curating gene lists from our previous analyses 36,38 .”
InfluentialSelf-citationClonal embeddings allow exploratory analysis of lineage-resolved single-cell dataPreprint
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“The expected neutrophil axis described earlier was captured by the second component, with the top genes matching neutrophil-biasing genes described by Weinreb et al. (Supplementary Fig.”
InfluentialMassively multiplex multimodal chemical screens at single-cell resolutionPreprint
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A DNA Typewriter records the cell lineage history of a mouse, from zygote to late organogenesisPreprint
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Skipping adolescence to become super-inflammatory monocytes
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“cells (HSPC) gradually pass through a continuum of differentiation states(Karamitros et al., 2017; Laurenti and Göttgens, 2018; Velten et al., 2017; Weinreb et al., 2020).”
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“Genomics and proteomics on emergent properties, clonal fate, and protein types [6]–[8].”
Background
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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