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
plain- Asserted: passes — The authors put it forward as true.
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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
plain- Asserted: passes — The authors put it forward as true.
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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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Probably not a substantial claim.
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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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It 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
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
Finding the missing heritability of complex diseases
Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336 · cited 1×
“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
Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells
Klein, A. M., Mazutis, L., Akartuna, I., Tallapragada, N., Veres, A., Li, V., Peshkin, L., Weitz, D. A., & Kirschner, M. W. (2015) · Cell · doi:10.1016/j.cell.2015.04.044 · Cited by 3,356
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).”
BackgroundMi, H., Muruganujan, A., & Thomas, P. D. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1118 · Cited by 1,739
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-citation
Cited by
Sorted by citations
Items 201–300 of 723
Tracing back primed resistance in cancer via sister cells
Dai, J., Zheng, S., Falco, M. M., Bao, J., Eriksson, J., Pikkusaari, S., Forstén, S., Jiang, J., Wang, W., Gao, L., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-45478-7 · Cited by 24
“However, transcriptional patterns of pre-treatment cells do not fully capture their future fate 9 , and cells with extreme fates, such as high-dose drug persistence, may not display evident gene expression fea-turespriortreatment 11 .”
BackgroundMethodFan, D., Cong, Y., Liu, J., Zhang, H., & Du, Z. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113928 · Cited by 21
Re-defining synthetic lethality by phenotypic profiling for precision oncology
Akimov, Y. A., & Aittokallio, T. A. (2021) · Cell chemical biology · doi:10.1016/j.chembiol.2021.01.026 · Cited by 20
Dual recombinases-based genetic lineage tracing for stem cell research with enhanced precision
Jin, H., Liu, K., & Zhou, B. (2021) · Science China Life Sciences · doi:10.1007/s11427-020-1889-9 · Cited by 22
Cell Tracking for Organoids: Lessons From Developmental Biology
Betjes, M. A., Zheng, X., Kok, R. N. U., van Zon, J. S., & Tans, S. J. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.675013 · Cited by 20
“, 2017) or lentiviral transduction (Weber et al., 2011; Mohme et al., 2017; Weinreb et al., 2020).”
Heterogeneity and origins of myeloid cells
Yáñez, A., Bono, C., & Goodridge, H. S. (2022) · Current Opinion in Hematology · doi:10.1097/moh.0000000000000716 · Cited by 22
“Moreover, two independent pathways originating from GMPs and monocyte-DC progenitors (MDPs) yield classical monocytes with distinct neutrophil-like and DC-like gene expression signatures (NeuMo and DCMo, respectively) in steady-state mouse bone marrow [32,33].”
BackgroundMonocyte regulation by gut microbial signals
Kolypetri, P., & Weiner, H. L. (2023) · Trends in Microbiology · doi:10.1016/j.tim.2023.05.006 · Cited by 21
Adameyko, I. I., Bakken, T. E., Bhaduri, A., Chhatbar, C., Filbin, M. G., Gate, D., Hochgerner, H., Kim, C. N., Krull, J. E., Manno, G. L., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01827-9 · Cited by 26
“Regulon analysis can be combined with clonal analysis using DNA recombination or virally delivered barcodes to link pre-bifurcation states to future cell fates 58 .”
Dendritic cell development at a clonal level within a revised ‘continuous’ model of haematopoiesis
Naik, S. H. (2020) · Molecular Immunology · doi:10.1016/j.molimm.2020.06.012 · Cited by 19
Engineering Brain Organoids: Toward Mature Neural Circuitry with an Intact Cytoarchitecture
Jang, H., Kim, S. H., Koh, Y., & Yoon, K. (2022) · International Journal of Stem Cells · doi:10.15283/ijsc22004 · Cited by 22
“Transposonbased recording usually inserts a fluorescent reporter cassette whose 3’ UTR carries a short sequence working as a barcode (103-106).”
BackgroundApplication of single-cell RNA sequencing in embryonic development
Shangguan, Y., Li, C., Lin, H., Ou, M., Tang, D., Dai, Y., & Yan, Q. (2020) · Genomics · doi:10.1016/j.ygeno.2020.08.007 · Cited by 21
Rodrigues, C. P., & Akhtar, A. (2021) · Science Advances · doi:10.1126/sciadv.abi5987 · Cited by 21
“Those subtypes can have different functional properties, including differences in repopulation kinetics (2–5), cell cycle status (6), self-renewal abilities (7), and multilineage differentiation output (8, 9).”
BackgroundLaise, P., Turunen, M. M., Garcia, A. C., Tomassoni, L., Maurer, H. C., Elyada, E., Schmierer, B., Worley, J., Kesner, J. S., Tan, X., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.10.27.357269 · Cited by 21
“To address this question, we performed barcode-based lineage-tracing assays (Weinreb et al., 2020) in cell lines representative of the GLS and MOS PDLs (we could not identify cell lines with a sufficient ALS fraction for analysis).”
Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets
Eisele, A. S., Tarbier, M., Dormann, A. A., Pelechano, V., & Suter, D. M. (2024) · Nature Communications · doi:10.1038/s41467-024-47158-y · Cited by 29
“Data from Weinreb et al. 12 was down-loaded from (https://github.com/AllonKleinLab/paper-data/blob/ master/Lineage_tracing_on_transcriptional_landscapes_links_state_to_ fate_during_differentiation/README.md).”
InfluentialNew frameworks for hematopoiesis derived from single-cell genomics
Safina, K. R., & van Galen, P. (2024) · Blood · doi:10.1182/blood.2024024006 · Cited by 23
Bury, L. A. D., Fu, S., & Wynshaw-Boris, A. J. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114862 · Cited by 19
Li, K., Yu, P.-L., Zheng, Q.-Q., Wang, X., Fang, X., Li, L., & Xu, C. (2025) · Cell · doi:10.1016/j.cell.2024.12.012 · Cited by 20
Single-cell fate decisions of bipotential hematopoietic progenitors
Brand, M., & Morrissey, E. R. (2020) · Current Opinion in Hematology · doi:10.1097/moh.0000000000000592 · Cited by 19
A Novel GATA2 Protein Reporter Mouse Reveals Hematopoietic Progenitor Cell Types
Ahmed, N., Kunz, L., Hoppe, P. S., Loeffler, D., Etzrodt, M., Ortega, G. C., Hilsenbeck, O., Anastassiadis, K., & Schroeder, T. (2020) · Stem Cell Reports · doi:10.1016/j.stemcr.2020.06.008 · Cited by 18
“This is in agreement with recent single-cell RNA sequencing analysis confirming heterogeneousMPPGata2 expression at themRNA level (Weinreb et al., 2020).”
ResultSingle-Cell Toolkits Opening a New Era for Cell Engineering
Lee, S., Kim, J., & Park, J.-E. (2021) · Molecules and Cells · doi:10.14348/molcells.2021.0002 · Cited by 20
“For example, iTracer (He et al., 2020b) is a novel technique that takes advantage of previously developed complex barcode libraries (Weinreb et al., 2020) and an inducible Cas9 scarring system similar to the one used in the lineage tracing by nuclease-activated editing of ubiquitous sequences…”
MethodSingle-Cell Epigenomics Reveals Mechanisms of Cancer Progression
LaFave, L. M., Savage, R. E., & Buenrostro, J. D. (2022) · Annual Review of Cancer Biology · doi:10.1146/annurev-cancerbio-070620-094453 · Cited by 20
Concurrent stem- and lineage-affiliated chromatin programs precede hematopoietic lineage restriction
Safi, F., Dhapola, P., Warsi, S., Sommarin, M. N. E., Erlandsson, E., Ungerbäck, J., Warfvinge, R., Sitnicka, E., Bryder, D., Böiers, C., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110798 · Cited by 17
Mukherjee, P., Park, S. H., Pathak, N., Patino, C. A., Bao, G., & Espinosa, H. D. (2022) · ACS Nano · doi:10.1021/acsnano.2c05494 · Cited by 20
Parmentier, R., Racine, L., Moussy, A., Chantalat, S., Ravi, S., Gao, N. P., Stockholm, D., Corre, G., Fourel, G., Deleuze, J., et al. (2022) · PLoS Biology · doi:10.1371/journal.pbio.3001849 · Cited by 19
“Recently, Weinreb and colleagues [34] also found that the list of expressed genes defining the subtypes in HSPCs is almost entirely composed by highly expressed and highly variable genes, and only marginally enriched in TFs.”
BackgroundA robust and accurate single-cell data trajectory inference method using ensemble pseudotime
Zhang, Y., Tran, D., Nguyen, T., Dascalu, S. M., & Harris, F. C. (2023) · BMC Bioinformatics · doi:10.1186/s12859-023-05179-2 · Cited by 23
Therapeutic targeting of leukemia stem cells in acute myeloid leukemia
Barbosa, K., & Deshpande, A. J. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1204895 · Cited by 20
Linking cell cycle to hematopoietic stem cell fate decisions
Treichel, S., & Filippi, M. (2023) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2023.1231735 · Cited by 20
“Other studies using single cell RNA-seq have shown that HSC priming is associated with cell cycle entry (Weinreb et al., 2020).”
BackgroundHarnessing the power of proteomics in precision diabetes medicine
Kurgan, N., Larsen, J. K., & Deshmukh, A. S. (2024) · Diabetologia · doi:10.1007/s00125-024-06097-5 · Cited by 22
“Evidence from the single-cell field has highlighted the fact that transcrip-tomics is unable to predict cell fate [40] and that genetic variation in single cells appears to mostly influence the proteome rather than the transcriptome [41].”
Improved detection of differentially represented DNA barcodes for high‐throughput clonal phenomics
Akimov, Y. A., Bulanova, D. R., Timonen, S., Wennerberg, K., & Aittokallio, T. A. (2020) · Molecular Systems Biology · doi:10.15252/msb.20199195 · Cited by 19
Endothelial ontogeny and the establishment of vascular heterogeneity
Stone, O. A., Zhou, B., Red‐Horse, K., & Stainier, D. Y. R. (2021) · BioEssays · doi:10.1002/bies.202100036 · Cited by 19
Basophil differentiation, heterogeneity, and functional implications
Chen, Y., Tang, H., Yao, B., Pan, S., Ying, S., & Zhang, C. (2024) · Trends in Immunology · doi:10.1016/j.it.2024.05.009 · Cited by 18
Isnard, P., & Humphreys, B. D. (2024) · American Journal Of Pathology · doi:10.1016/j.ajpath.2024.06.012 · Cited by 18
LoxCode in vivo barcoding reveals epiblast clonal fate bias to fetal organs
Weber, T., Biben, C., Miles, D. C., Glaser, S. P., Tomei, S., Lin, C., Kueh, A. J., Pál, M., Zhang, S., Tam, P., et al. (2025) · Cell · doi:10.1016/j.cell.2025.04.026 · Cited by 26
Immuno-metabolic interfaces in cardiac disease and failure
Bertero, E., Dudek, J., Cochain, C., Delgobo, M., Ramos, G. C., Gerull, B., Higuchi, T., Vaeth, M., Zernecke, A., Frantz, S., et al. (2021) · Cardiovascular Research · doi:10.1093/cvr/cvab036 · Cited by 19
Reconstructing developmental landscapes and trajectories from single-cell data
Schiebinger, G. R. (2021) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2021.06.002 · Cited by 21
Granulocyte development, tissue recruitment, and function during allergic inflammation
Radtke, D., & Voehringer, D. (2023) · European Journal of Immunology · doi:10.1002/eji.202249977 · Cited by 19
Revisiting the lineage contribution of hematopoietic stem and progenitor cells
Gao, S., Zhang, Y., & Liu, F. (2023) · Development · doi:10.1242/dev.201609 · Cited by 17
Storm, P., Zhang, Y., Nilsson, F., Fiorenzano, A., Krausse, N., Åkerblom, M., Davidsson, M., Yuan, J., Kirkeby, A., Björklund, T., et al. (2024) · Science Advances · doi:10.1126/sciadv.adn3057 · Cited by 18
“This sensitivity is in line with other similar lineage tracing reports ( 17 , 18 ) with transgene promotor silencing and inefficient capture on bead oligo-dT reverse transcription primers as likely contributors to loss of barcode detection of LibA, aggravated by interference of viral superinfection…”
Singh, I., Fernández-Pérez, D., Sanchez, P. S., & Rodriguez-Fraticelli, A. (2025) · Cell stem cell · doi:10.1016/j.stem.2025.01.012 · Cited by 30
Self-citationTran, A., Yang, P., Yang, J. Y. H., & Ormerod, J. T. (2022) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqac023 · Cited by 20
“However, cell reprogramming experiments have resulted in very heterogeneous outcomes with many cell subpopulations, often dependent on the initial cell state (21,22).”
BackgroundRevealing gene function with statistical inference at single-cell resolution
Trapnell, C. (2024) · Nature Reviews Genetics · doi:10.1038/s41576-024-00750-w · Cited by 19
“CellTags 119 , LARRY 120 Methods for embedding synthetic, transcribed barcodes within cells that can be readout via single-cell sequencing, facilitating comparison of the transcriptomes of clones Lineage recording GESTALT 62 , MEMOIR 121 CRISPR-based editing of synthetic arrays of lineage barcodes…”
Kim, W., Park, E., Yoo, H. S., Park, J., Jung, Y. M., & Park, J. H. (2022) · Nanomaterials · doi:10.3390/nano12172934 · Cited by 18
A statistical method for quantifying progenitor cells reveals incipient cell fate commitments
Deng, S., Gong, H., Zhang, D., Zhang, M., & He, X. (2024) · Nature Methods · doi:10.1038/s41592-024-02189-7 · Cited by 19
“To demonstrate this issue we analyzed a dataset that records with static cell barcodes the in vitro differentiation process of mouse hematopoietic stem cells (Methods) 61 .”
Deciphering the species-level structure of topologically associating domainsPreprint
Singh, R., & Berger, B. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.28.466333 · Cited by 14
“Use of TAD signatures for cell fate prediction We obtained data from Weinreb et al.’s lineage tracing study (GEO accession GSE140802; [56]), count normalizing and log transforming the transcript counts.”
BackgroundInfluentialBridging scales: From cell biology to physiology using in situ single-cell technologies
Nagle, M. P., Tam, G. S., Maltz, E., Hemminger, Z., & Wollman, R. (2021) · Cell Systems · doi:10.1016/j.cels.2021.03.002 · Cited by 15
Reconstructing cell lineage trees with genomic barcoding: approaches and applications
Li, Z., Yang, W., Wu, P., Shan, Y., Zhang, X., Chen, F., Yang, J., & Yang, J.-R. (2023) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2023.05.011 · Cited by 18
Clonal tracking of haematopoietic cells: insights and clinical implications
Cordes, S., Wu, C., & Dunbar, C. E. (2020) · British Journal of Haematology · doi:10.1111/bjh.17175 · Cited by 17
“Similarly, a lentiviral expression cassette containing a barcode expressed at high levels constitutively has allowed simultaneous barcode retrieval along with singlecell transcriptomics to investigate HSPC differentiation and self-renewal pathways both in vitro as well as in vivo following transplantation.(45)”
BackgroundSugden, W. W., & North, T. E. (2021) · Life · doi:10.3390/life11101027 · Cited by 16
Lin, L., Zhang, Y., Qian, W., Liu, Y., Zhang, Y., Lin, F., Liu, C., Lu, G., Sun, D., Guo, X., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2119767119 · Cited by 16
“However, this application normally relies on exogenous barcodes created by transforming barcode libraries (11) or Cas9-based genome-editing tools (12).”
BackgroundBAR-Seq clonal tracking of gene-edited cells
Ferrari, S., Beretta, S., Jacob, A., Cittaro, D., Albano, L., Merelli, I., Naldini, L., & Genovese, P. (2021) · Nature Protocols · doi:10.1038/s41596-021-00529-x · Cited by 15
scTOP: physics-inspired order parameters for cellular identification and visualization
Yampolskaya, M., Herriges, M. J., Ikonomou, L., Kotton, D. N., & Mehta, P. (2023) · Development · doi:10.1242/dev.201873 · Cited by 15
Synthetic DNA barcodes identify singlets in scRNA-seq datasets and evaluate doublet algorithms
Zhang, Z., Melzer, M. E., Arun, K. M., Sun, H., Eriksson, C., Fabian, I., Shaashua, S., Kiani, K., Oren, Y., & Goyal, Y. (2024) · Cell Genomics · doi:10.1016/j.xgen.2024.100592 · Cited by 18
Systems analysis of hematopoiesis using single-cell lineage tracing
Rodriguez-Fraticelli, A., & Camargo, F. D. (2020) · Current Opinion in Hematology · doi:10.1097/moh.0000000000000624 · Cited by 16
Self-citationCohen, K., Mouhadeb, O., Shlomo, S. B., Langer, M., Neumann, A., Noam Erez, A., Moshkovits, I., Pelet, R., Kedar, D. J., Brazowski, E., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.110026 · Cited by 16
“Given the recent discovery of NeuMos and DCMos (Weinreb et al., 2020; Yáñez et al., 2017), we speculated that COMMD10 deficiency in Ly6Chi monocytes might favor enrichment for NeuMos.”
InfluentialDiscovering New Progenitor Cell Populations through Lineage Tracing and In Vivo ImagingPreprint
Das, R. N., & Yaniv, K. (2020) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a035618 · Cited by 12
“These progenitor cells traverse a defined developmental trajectory involving progressive fate decision steps, each refining their identity, until they reach their functional end state (Weinreb et al. 2018).”
BackgroundSingle-Cell Multiomics Reveals Distinct Cell States at the Top of the Human Hematopoietic HierarchyPreprint
Sommarin, M. N. E., Dhapola, P., Safi, F., Warfvinge, R., Ulfsson, L. G., Erlandsson, E., Konturek-Cieśla, A., Thakur, R. K., Böiers, C., Bryder, D., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.01.437998 · Cited by 14
“Since accumulating data indicate that the function of a cell is reflected primarily by its enhancer accessibility[19, 20], we reasoned that a fraction of the CLOUD-HSPCs should contain an HSC enhancer signature that is decisive for HSC function.”
BackgroundInfluentialCell lineage tracing: Methods, applications, and challenges
Mao, S., Zhang, C., Chen, R., Tang, S., Fan, X., & Hu, J. (2025) · Quantitative Biology · doi:10.1002/qub2.70006 · Cited by 18
“Data integration often requires specialized algorithms and large ‐ scale validation to ensure fidelity, particularly when dealing with diverse biological systems [13, 64].”
InfluentialAdvances in CRISPR ‐Cas9 in lineage tracing of model animals
Cao, J., Guo, Z., Xu, X., Li, P., Fang, Y., & Deng, S. (2025) · Animal Models and Experimental Medicine · doi:10.1002/ame2.70033 · Cited by 15
Furer, N., Rappoport, N., Milman, O., Tavor, S., Lifshitz, A., Bercovich, A., Ben-Kiki, O., Danin, A., Kedmi, M., Shipony, Z., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03716-5 · Cited by 17
“Although classic studies linked these cells with a GMP origin, more recent studies suggested that these emerge, at least in part, from erythroid progenitors in both mice and humans 7,16 .”
Resolving the hematopoietic stem cell state by linking functional and molecular assays
Jassinskaja, M., Gońka, M., & Kent, D. G. (2023) · Blood · doi:10.1182/blood.2022017864 · Cited by 15
Howland, K. K., & Brock, A. (2023) · Trends in cancer · doi:10.1016/j.trecan.2023.03.008 · Cited by 15
Non-genetic mechanisms of drug resistance in acute leukemias
Calderon, A., Han, C., Karma, S., & Wang, E. (2023) · Trends in cancer · doi:10.1016/j.trecan.2023.09.003 · Cited by 17
Cell of origin epigenetic priming determines susceptibility to Tet2 mutation
Schiroli, G., Kartha, V. K., Duarte, F. M., Kristiansen, T. A., Mayerhofer, C., Shrestha, R., Earl, A., Hu, Y., Tay, T., Rhee, C., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48508-6 · Cited by 15
“High complexity barcoding library LARRY Barcode Version 1 library 83 was a gift from Fernando Camargo (Addgene #140024).”
InfluentialYuan, X., Hao, X., Chan, H. L., Zhao, N., Pedroza, D. A., Liu, F., Le, K., Smith, A. J., Calderon, S. J., Lieu, N., et al. (2024) · JCI Insight · doi:10.1172/jci.insight.182621 · Cited by 15
“We also examined the expression of a published gene signature that was shown to predict the differentiation of HSPCs toward neutrophils (43) (Supplemental Table 20).”
BackgroundMethodInfluentialRosen, B. P., Li, Q. V., Cho, H., Liu, D., Yang, D., Graff, S., Yan, J., Luo, R., Verma, N., Damodaran, J. R., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53284-4 · Cited by 16
Watanabe, H., Rana, M., Son, M., Chiu, P. Y., Fei, Y., Choi, K., Diamond, B., & Sherry, B. A. (2024) · Molecular Medicine · doi:10.1186/s10020-024-00970-0 · Cited by 14
“This revealed two separate pathways for DC-like or neutrophil-like monocyte differentiation resulting in different gene expression patterns in mature cells in bone marrow (Weinreb et al. 2020).”
BackgroundUncovering cellular networks in branching morphogenesis using single-cell transcriptomics
Goodwin, K., & Nelson, C. M. (2020) · Current topics in developmental biology/Current Topics in Developmental Biology · doi:10.1016/bs.ctdb.2020.09.004 · Cited by 13
Cardiac specification during gastrulation – The Yellow Brick Road leading to Tinman
Stutt, N., Song, M., Wilson, M. D., & Scott, I. C. (2021) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2021.11.011 · Cited by 13
Unbiased profiling of multipotency landscapes reveals spatial modulators of clonal fate biasesPreprint
Erickson, A. G., Isaev, S. V., Artemov, A. V., He, J., Semsch, B., Муртазина, А. Р., Sun, J., Mangold, K., Chalou, A., Frisén, J., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.15.623687 · Cited by 14
“Clone2vec re-176 analysis of published hematopoietic lineage tracing data [20] was able to recover previously described fate patterns with their associated genes, additionally uncovering more subtle continuous axes of variation (see Supplementary Note: Real Data).”
A spatial code governs olfactory receptor choice and aligns sensory maps in the nose and brain
Brann, D. H., Tsukahara, T., Tau, C., Kalloor, D., Lubash, R. W., Kannan, L. T., Klimpert, N., Köllő, M., Escamilla-Del-Arenal, M., Bintu, B., et al. (2026) · Cell · doi:10.1016/j.cell.2026.03.051 · Cited by 15
Loke, J. C. T., Kim, P. G., Nguyen, T. T. P., Boileau, M., McConkey, M. E., Miller, A., Shin, W., Hergott, C. A., Ericsson, M., Nordstrom, A. E. H., et al. (2025) · Blood · doi:10.1182/blood.2024028033 · Cited by 17
Rubio-Ponce, A., Hidalgo, A., & Ballesteros, I. (2020) · Current Opinion in Immunology · doi:10.1016/j.coi.2020.08.003 · Cited by 13
Quo Vadis? Immunodynamics of Myeloid Cells after Myocardial Infarction
Moggio, A., Schunkert, H., Kessler, T., & Sager, H. B. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232415814 · Cited by 15
“These technical advances allow to follow stem cells and their progeny at single cell level revealing novel gene dynamics during differentiation and highlighting different maturation stages [46,47].”
BackgroundCatching Our Breath: Updates on the Role of Dendritic Cell Subsets in Asthma
Lajiness, J. D., & Cook‐Mills, J. M. (2023) · Advanced Biology · doi:10.1002/adbi.202200296 · Cited by 13
The evolving definition of plant cell type
Amini, S., Doyle, J. J., & Libault, M. (2023) · Frontiers in Plant Science · doi:10.3389/fpls.2023.1271070 · Cited by 13
Wijaya, L. S., Gábor, A., Pot, I., van de Have, L., Sáez-Rodríguez, J., Stevens, J. L., Dévédec, S. E. L., Callegaro, G., & van de Water, B. (2023) · Toxicological Sciences · doi:10.1093/toxsci/kfad121 · Cited by 17
“In other contexts, transcriptomic profiling has been reported to have higher pre-dictability toward cellular outcomes compared with a sole interpretation from the activation of transcription factors (Weinreb et al. , 2020).”
BackgroundMao, J., You, H., Wang, M., Ba, Y., Qian, J., Cheng, P., Lu, C., & Chen, J. (2023) · Kidney International · doi:10.1016/j.kint.2023.11.027 · Cited by 17
Clonal differences underlie variable responses to sequential and prolonged treatment
Schaff, D. L., Fasse, A. J., White, P. E., Velde, R. V., & Shaffer, S. M. (2024) · Cell Systems · doi:10.1016/j.cels.2024.01.011 · Cited by 15
Analysis of synthetic cellular barcodes in the genome and transcriptome with BARtab and bartools
Holze, H., Talarmain, L., Fennell, K. A., Lam, E. Y. N., Dawson, M. A., & Vassiliadis, D. (2024) · Cell Reports Methods · doi:10.1016/j.crmeth.2024.100763 · Cited by 13
“7,8,10,11,19 Thus, there is a need for an end-to-end integrated solution for cellular barcoding dataset pre-processing, analysis, and visualization that is flexible to different barcode designs and is portable and scalable across computational environments.”
Serio, R. N., Scheben, A., Lu, B., Gargiulo, D. V., Patruno, L., Buckholtz, C. L., Chaffee, R. J., Jibilian, M. C., Persaud, S. G., Staklinski, S. J., et al. (2024) · Cancer Discovery · doi:10.1158/2159-8290.cd-23-1332 · Cited by 14
Signoretto, I., Calzetti, F., Finotti, G., Lonardi, S., Balanzin, C., Bianchetto-Aguilera, F. M., Gasperini, S., Gardiman, E., Castellucci, M., Russignan, A., et al. (2025) · Cellular and Molecular Immunology · doi:10.1038/s41423-025-01259-w · Cited by 14
“According to knowledge recently acquired by scRNA-seq studies and clonal tracking analysis [1, 2], hematopoiesis is currently believed to occur as a continuous process along developmental trajectories, without going through discrete hierarchic progenitor populations [3, 4].”
Hematopoietic and Chronic Myeloid Leukemia Stem Cells: Multi-Stability versus Lineage Restriction
Brown, G. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232113570 · Cited by 14
“The near‐ neighbor pathways in a continuum were towards erythrocytes, basophils, neutrophils, monocytes, dendritic cells, B cells, and T cells [68], which is similar to the above.”
ResultGenomic context sensitivity of insulator functionPreprint
Ribeiro-dos-Santos, A. M., Hogan, M. S., Luther, R. D., Brosh, R., & Maurano, M. T. (2022) · Genome Research · doi:10.1101/gr.276449.121 · Cited by 14
“cell, which can provide a unique combinatorial genetic identifier for cells derived from a given clone during transfection (Lu et al. 2011; Biddy et al. 2018; Weinreb et al. 2020).”
BackgroundFatecode: Cell fate regulator prediction using classification autoencoder perturbationPreprint
Sadria, M., Layton, A. T., Goyal, S., & Bader, G. D. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.16.520772 · Cited by 13
“5a), to examine the method’s accuracy in detecting master regulators in cell differentiation into neutrophils and monocytes 43 .”
MethodLineageVAE: reconstructing historical cell states and transcriptomes toward unobserved progenitors
Majima, K., Kojima, Y., Minoura, K., Abe, K., Hirose, H., & Shimamura, T. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae520 · Cited by 12
“…advancements have demonstrated that integrating scRNA-seq measurements with lineage tracing using cell barcodes allows the tracking of clonal relationships and observation of transitional cell states during differentiation at discrete and sparse time points (Weinreb et al. 2020, Oren et al. 2021).”
BackgroundMethodDARLIN mouse for in vivo lineage tracing at high efficiency and clonal diversity
Li, L., Bowling, S., Lin, H., Chen, D., Wang, S., & Camargo, F. D. (2025) · Nature Protocols · doi:10.1038/s41596-025-01141-z · Cited by 14
“…to study diverse areas of stem cell biology, including hematopoietic cell migration 19,20 , lineage branching points during development 19,25 , hematopoiesis developmental hierarchy 13,14,20 , epigenetic memory of HSCs 20 , HSC and T cell fate biases 20,26–29 and HSC responses to chemotherapy 19 .”
Self-citationSingle-cell susceptibility to viral infection is driven by variable cell states
Reffsin, S., Miller, J., Ayyanathan, K., Dunagin, M. C., Heyman, Y., Jain, N., Schultz, D., Cherry, S. R., & Raj, A. (2025) · Cell · doi:10.1016/j.cell.2025.10.021 · Cited by 11
Resolving cellular dynamics using single-cell temporal transcriptomics
Liu, Y., Huang, K., & Chen, W. (2024) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2023.103060 · Cited by 10
Histopathologic Analysis of Human Kidney Spatial Transcriptomics Data
Isnard, P., Li, D., Xuanyuan, Q., Wu, H., & Humphreys, B. D. (2024) · American Journal Of Pathology · doi:10.1016/j.ajpath.2024.06.011 · Cited by 13
scLTdb: a comprehensive single-cell lineage tracing database
Jiang, J., Ye, X., Kong, Y., Guo, C., Zhang, M., Cao, F., Zhang, Y., & Pei, W. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae913 · Cited by 13
“This dataset was generated by an integration barcode based scLT technology (LARRY), to track the differentiation of hematopoietic stem and progenitor cells (HSPCs) in vitro ( 39 ).”
InfluentialIn vivo models of subclonal oncogenesis and dependency in hematopoietic malignancy
Bowman, R. L., Dunbar, A. J., Mishra, T., Xiao, W., Waarts, M., Maestre, I. F., Eisman, S. E., Cai, L., Mowla, S., Shah, N., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.10.009 · Cited by 14
Single-Cell RNA Sequencing to Disentangle the Blood System
Acosta, J., Ssozi, D., & van Galen, P. (2021) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.120.314654 · Cited by 13
Advancing Stem Cell Research through Multimodal Single-Cell AnalysisPreprint
Kuciński, I., & Göttgens, B. (2020) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a035725 · Cited by 12
Coordinated Changes in Gene Expression Kinetics Underlie both Mouse and Human Erythroid MaturationPreprint
Barile, M., Imaz-Rosshandler, I., Inzani, I., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.12.21.423773 · Cited by 12
Hematopoietic stem cell metabolism within the bone marrow niche – insights and opportunities
Kemna, K. P., van der Burg, M., Lankester, A. C., & Giera, M. A. (2024) · BioEssays · doi:10.1002/bies.202400154 · Cited by 12
Redefining cellular reprogramming with advanced genomic technologies
Morris, S. A. (2025) · Nature Reviews Genetics · doi:10.1038/s41576-025-00899-y · Cited by 16
“Using a retrospective clonal barcoding with resampling design, similar to previous studies 67,128 , the authors identified the rare ancestral cells within the starting population, which later generated iPS cell colonies, which importantly enabled preinduction molecular profiling of the permissive…”
InfluentialNguyen, L. T., Zimmermann, K., Kowenz‐Leutz, E., Lim, R., Hofstätter, M., Mildner, A., & Leutz, A. (2023) · Stem Cell Reports · doi:10.1016/j.stemcr.2023.11.011 · Cited by 11
Single-cell lineage tracing with endogenous markers
Xue, Y., Su, Z., Lin, X., Ho, M. K., & Yu, K. H. O. (2024) · Biophysical Reviews · doi:10.1007/s12551-024-01179-5 · Cited by 11
“; Tian et al. 2021; VanHorn and Morris 2021; Weinreb et al. 2020; Yang et al. 2022).”
BackgroundCampbell, G. P., Amin, D., Hsieh, K., Hussey, G. S., Leger, A. J. S., Gross, J. M., Badylak, S. F., & Kuwajima, T. (2024) · npj Regenerative Medicine · doi:10.1038/s41536-024-00374-y · Cited by 12
“These top 20 DEGs include Ccr2 34 , Sirpb1c 35 , Cd209a 36 , Ly6C2 37 , and Slamf7 38 , whichare normally expressed in monocytes, and Cxcr2 34 , Atp8b4 39 , H2-aa 40 and Clec4n 41 , which are expressed in neutrophils.”
Michaels, Y. S., Major, M. C., Bonham-Carter, B., Zhang, J.-Q., Heydari, T., Edgar, J. M., Siu, M. M., Greenstreet, L., Vilarrasa‐Blasi, R., Kim, S., et al. (2024) · Cell Systems · doi:10.1016/j.cels.2024.11.001 · Cited by 11
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-09-28, under version 3 of the claim definition (prompt extract-v3).
A second model labelled each claim on 2026-09-28 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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