Comprehensive Lineage Tracing Maps the Landscape of Cell Fate Decisions in Mouse Embryogenesis

Figure 1. Reconstruction of unbiased cell fate mapping during mammalian development using PEtracer technology. Using PEtracer technology, the preprint authors obtained chimeric mouse embryos. As cells divide, genetic marks accumulate on edit site in different cassettes. By sorting cells and subsequent scRNAseq, phylogenetic reconstruction of developmental lineage relationships was possible. This preprint figure was made available under a CC-BY 4.0 International license.

Background

Mammalian embryogenesis is highly robust: embryos can tolerate perturbations and still generate coherent body plans. Yet, how this developmental flexibility coexists with the remarkable reproducibility of embryogenesis remains poorly understood.

Recent advances in single-cell and spatial profiling have greatly refined our understanding of embryonic development^1,2. However, many current approaches still infer developmental relationships primarily from transcriptional similarity, making it difficult to directly connect molecular identity, lineage ancestry, and fate specification. Some genome editing-based lineage tracing systems allowed this to some extent, but these remain limited in obtaining the sufficient resolution to reconstruct complete cell trajectories in mice^3–7.

In this preprint, Colgan and colleagues introduce PEtracer, a lineage recording system that continuously adds heritable genetic marks during cell division. Previously, the authors validated the use of PEtracer in a syngeneic mouse model of lung metastasis to assess the impact of cell extravasation, colonization, and outgrowth in breast cancer⁸.

This innovative technical tool is the first approach that can examine both cell lineage and transcriptional identity during embryogenesis. It is also compatible with spatial transcriptomics (MERFISH), enabling integration of cell lineage in tissue architecture. By coupling heritable edits with scRNAseq, PEtracer allows the reconstruction of high-resolution lineage trees, enabling in vivo fate mapping. Finally, it enables tunable editing rates and sufficient resolution to resolve trajectories and cell identities during embryonic cell divisions.

In this preprint, the authors offer the scientific community, for the first time, the complete unbiased fate mapping of more than 1.5 million cells found in early-developing mouse embryos from E7.5 to E10.

Key findings

Mammalian lineage dynamics are remarkably reproducible

One of the most striking findings of the study is the high reproducibility of lineage architecture across independently generated embryos, despite the robust and partially non-deterministic nature of mammalian development. From E7.5 to E10.0, the authors reconstructed lineage paths across 16 embryos, revealing remarkably consistent patterns of division timing, cell subtype population distributions, and fate restriction trajectories. These data suggest that mammalian embryogenesis is governed by tightly constrained developmental programs that generate robust fate outcomes. Thus, revealing robustness as a fundamental property of early embryogenesis.

Germ layers are committed way earlier than expected

Going further, the authors used germ layer specification to probe whether biases emerged prior to full specification. Surprisingly, they detected fate restriction as early as E4.0, well before gastrulation, in a tightly restricted manner. This suggests that the specification decision for some tissues is made earlier than previously expected. Moreover, prolonged multipotency was detected along the anterior-posterior axis. The more posterior the cells were, the longer they stayed multipotent.

Shared transcriptional states can emerge from distinct lineage origins

The authors further demonstrated that transcriptionally similar cell states may emerge from distinct developmental origins. Endothelial populations derived from multiple mesodermal compartments converged toward a shared transcriptional program while retaining detectable signatures of their tissue of origin. Similarly, atrial and ventricular cardiomyocytes shared overlapping molecular identities despite descending from lineage compartments that were essentially non-overlapping and corresponded to distinct heart fields. These findings highlight an important limitation of developmental trajectory inference approaches relying primarily on transcriptional similarity: convergent molecular states can obscure fundamentally distinct developmental histories.

Fate specification depends on tissue context

The authors showed that lineage, cell position, and timing control identity. For example, they showed that notochord cells are one of the earliest specified cell types sharing a mixed developmental origin from the three germ layers. Interestingly, during heart field development, cardiac cell identity was acquired before any clear transcriptional defined cell subtype. While trunk neural crest cell progenitors are highly influenced by their migratory environment, they retained their bipotency longer than expected. Similarly, the authors showed that transcriptional and regional structures within the embryo do not necessarily correspond to lineage boundaries. At the midbrain-hindbrain boundary, lineage clades frequently spanned both regions despite sharp transcriptional differences. Together, these observations suggest that lineage history, spatial organization, signaling environments, and transcriptional state contribute, with varying relative weights, to fate specification depending on tissue context.

What we like about this preprint

Lucie’s perspective

As a 3rd-year PhD student in developmental biology studying dorsal root ganglia neurogenesis during embryogenesis in a physiopathological neurodegenerative context, I am constantly thinking about how cell identities emerge, differentiate, and are maintained during embryogenesis and early postnatal stages. I was immediately drawn to this preprint because it fundamentally reshapes how we think about early mammalian development. I usually assume that transcriptional identity mainly predicts cell fate. However, this preprint shows that fate decisions depend not only on cell-intrinsic programs but also on spatial context along embryonic axes. Thus, this perspective is directly influencing how I think about sensory neuron development. I was also fascinated by the technical innovation displayed in this preprint. Indeed, developing a tool capable of continuously following lineage restriction in vivo – in a mammal – felt genuinely eye‑opening. I can’t help but think about how such a tool can be used in the neurodegenerative context in which I am working.

I have the feeling that this preprint transforms what once seemed like an impossible dream into a quantitative, innovative, and deeply informative view of how cell fates and lineages emerge in vivo. From my personal perspective, it offers me a new way to rethink DRG lineage diversification, progenitor maintenance, and how spatial cues can shape neuronal specification. This is the kind of preprint that shifts how you see your own system.

Béryl’s perspective

As a developmental biologist, I found this preprint to be somewhat of a tour de force in an amniote embryo. I was initially drawn to this work because of my interest in how local cellular environments shape developmental trajectories and how tissue robustness emerges during embryogenesis.

I was particularly intrigued by the observation that different tissues appear to rely on lineage history, spatial position, and signaling environments in different ways for fate specification, suggesting that embryogenesis may not follow a single universal logic but rather multiple developmental “regimes” depending on tissue context.

In this regard, I found the neural crest analyses especially compelling. The observation that trunk neural crest progenitors retain the capacity to generate both DRG and autonomic lineages before rapidly resolving into distinct fates during migration is remarkably consistent with longstanding models of progressive neural crest fate restriction and environmentally driven specification. What I especially appreciated with this preprint is that these concepts now emerge from an unbiased, embryo-scale reconstruction of lineage dynamics rather than from targeted lineage tracing of selected progenitor populations. Finally, I was excited by the broader implications of this work for regeneration and disease. A longstanding question in the field is whether regeneration truly recapitulates embryonic developmental programs^9–11. Comparing the robustness, plasticity, and lineage constraints of embryonic versus regenerative trajectories could provide fascinating insights into how developmental stability is maintained or altered during regeneration and disease progression.

References

1. Briggs, J. A. et al. The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution. Science 360, eaar5780 (2018).
2. Farrell, J. A. et al. Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis. Science 360, eaar3131 (2018).
3. Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).
4. Weinreb, C., Rodriguez-Fraticelli, A., Camargo, F. D. & Klein, A. M. Lineage tracing on transcriptional landscapes links state to fate during differentiation. Science 367, eaaw3381 (2020).
5. Qiu, C. et al. Systematic reconstruction of cellular trajectories across mouse embryogenesis. Nat. Genet. 54, 328–341 (2022).
6. Frieda, K. L. et al. Synthetic recording and in situ readout of lineage information in single cells. Nature 541, 107–111 (2017).
7. Kalhor, R. et al. Developmental barcoding of whole mouse via homing CRISPR. Science 361, eaat9804 (2018).
8. Koblan, L. W. et al. High-resolution spatial mapping of cell state and lineage dynamics in vivo with PEtracer. Science 390, eadx3800 (2025).
9. Sinigaglia, C. et al. Distinct gene expression dynamics in developing and regenerating crustacean limbs. Proc. Natl. Acad. Sci. 119, e2119297119 (2022).
10. Xu, Y., Saini, A., Zhang, W., Zhou, L. & Mokalled, M. H. Spinal cord regeneration deploys adult molecular programs that do not recapitulate embryonic development.
11. Johnston, H. et al. Whole body regeneration deploys a rewired embryonic gene regulatory network logic. Preprint at https://doi.org/10.1101/658930 (2019).

Future directions and questions for the authors

• The study has been carried out from E7.5 to E10. Using the same approach and editing rate, how far can this lineage technique go?
• To what extent are the observed convergent transcriptional states functionally equivalent? Could cells with distinct developmental histories retain subtle physiological or epigenetic differences despite similar transcriptomic identities?
• In endothelial cells, a transcription memory of this ancestral mesodermal origin is kept. How long does this mesodermal origin last? Does it apply to other cell types?
• Could similar lineage-transcriptional integration approaches help reveal latent developmental abnormalities in disease models, particularly in disorders currently considered primarily degenerative?

Tags: lineage tracing

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