Biology subjects

Gottgens, B.

Publications and source records attributed to Gottgens, B..

At least 19 recordsLinked to original sources

bioRxiv2026

A scalable in vitro cell competition model identifies preleukemic super competitor clones

Preleukemic and leukemic conditions are frequently characterized by the acquisition of recurrent genetic mutations in hematopoietic stem cells (HSCs). One of the most frequently mutated genes in both clonal hematopoiesis and myeloid malignancies is the ten-eleven translocation 2 (TET2) gene, which encodes an epigenetic enzyme with a critical role in the regulation of gene transcription. While substantial work has shown that TET2 loss-of-function mutations lead to a clonal advantage, the underpinning cellular mechanism remains unclear, especially with respect to the early interactions with other cells. To study these early cell interactions of mutant and non-mutant cells, we developed an in vitro clonal competition platform where single-cell derived cultures are split into subclonal fractions which can be simultaneously cross-competed against multiple different clones of an opposing genotype. We identify a novel preleukemic cell phenotype that parallels the developmental biology phenomenon of super-competition, whereby ~10% of TET2-mutant clones actively and selectively suppress wild type (WT) cell expansion and, in some cases, completely eliminate WT clones. Molecular profiling and functional assays point to RAC1-GEF signalling inhibition as a specific WT cell vulnerability that is promoted, and tolerated, by neighbouring TET2-mutated clones. In addition to pinpointing selective drivers of non-mutant cell suppression, this clonal competition platform offers a broadly applicable new approach to study cell competition dynamics at an unprecedented scale.

cancer biology↗

bioRxiv2026

Single-Cell Proteo-Transcriptomic Profiling Uncovers Post-Translational Regulatory Layers in Human Hematopoiesis

Background: Hematopoietic stem cells (HSCs) have the unique ability to produce all mature cell types in the blood and understanding the mechanisms governing their differentiation and renewal is a driving question in stem cell biology. While single-cell RNA sequencing has transformed our view of human hematopoiesis, mRNA abundance represents an incomplete proxy for functional cell states. Here, we apply single-cell multimodal profiling to simultaneously measure 280 surface and intracellular protein targets alongside whole transcriptomes within individual adult human hematopoietic stem and progenitor cells. Results: By directly coupling modalities within single cells, we show that protein-RNA correlations peak dynamically in transitioning intermediate progenitors across lineages, consistent with pervasive post-transcriptional mechanics underlying lineage choice. Furthermore, key transcription factor proteins maintain multilineage co-expression longer into commitment than their transcripts, demarcating a possible window of fate decision reversibility. Moreover, low and flat CTNNB1 mRNA levels mask late-erythroid {beta}-catenin protein enrichment, apparently pairing with E-cadherin expression and suggesting post-translational stabilization at the cell membrane. Conclusions: This dataset enables the observation of translational dynamics and RNA-protein relationships throughout the differentiation landscape at an unprecedented level of granularity. Together, our findings demonstrate that transcriptomics alone misses fundamental regulatory programs, establishing single-cell proteo-transcriptomics as a powerful tool for decoding human stem cell fate.

cell biology↗

bioRxiv2026

Generative inverse design steers human hematopoietic cell fate in vitro

Inverse design has advanced the discovery of molecules and materials. Yet it remains largely unexplored for steering cell fate, where inputs are continuous, combinatorial culture conditions and outputs are distributions of cell states. Human hematopoiesis, in which combinations and doses of growth factors steer stem cells toward each blood lineage, is a demanding test case. While forward models can evaluate discrete conditions, the vast combinatorial space renders searching for a specific, target-producing design an intractable inverse problem. Here, we introduce LabCompass, an inverse-modeling framework that optimizes experimental designs toward candidates expected to produce specified target cell states, using a flow-matching generative model guided by cellular phenotypes predicted by a forward surrogate. We applied LabCompass to primary human CD34+ in vitro cultures, where continuous cytokine and small-molecule parameters govern hematopoietic cell fate. In a lab-in-the-loop setting, we experimentally validated model-driven designs and used these measurements to update the model across four successive loops. LabCompass recovered established lineage-inducing designs, improved predictions with new data, and enriched target populations across lineages. Incorporating new parameters expanded the design space and enriched rare populations beyond initial reach. Across loops, we generated a 78-million-cell spectral flow cytometry dataset and identified distinct culture conditions converging on the same target cell states. Our results establish generative inverse modeling as a compelling paradigm for navigating high-dimensional, continuous experimental spaces, and demonstrate that virtual cell models should be judged not only by how accurately they predict cellular responses, but also by how effectively they guide experiments toward desired biological outcomes.

cell biology↗

bioRxiv2026

Mesenchymal stroma cell-derived stem cell factor mediates cross-species compatibility of the hematopoietic stem cell niche.

The regulation of human hematopoietic stem cell (HSC) function within its native bone marrow microenvironment remains poorly understood due to the limitations of existing humanized models. Here, we present a non-conditioned human HSC xenotransplantation platform that serves as a physiologically relevant in vivo surrogate to study these complex cellular interactions. Using this system, we uncover a dynamic, cross-species communication between human HSCs and the murine niche, revealing a profound cellular and molecular plasticity of the bone marrow microenvironment in response to humanization. Upon engraftment, platelet-derived growth factor receptor alpha positive (Pdgfra+) mesenchymal stromal cells (MSCs) undergo significant numerical expansion and a major transcriptional shift, transitioning from a mixed adipo- and osteo-primed state toward a leptin receptor positive (Lepr+) predominantly adipo-primed, hematopoiesis-supporting signature. Functional validation demonstrates that this niche plasticity is a critical determinant of stem cell engraftment: the targeted depletion of Lepr+ MSCs or the genetic deletion of stem cell factor results in the rapid mobilization and lack of engraftment of human HSCs, respectively. Our findings establish niche plasticity as a primary regulator of human HSC function and demonstrate the utility of this cross-species platform as a modular genetic toolbox for precise in vivo engineering of the bone marrow microenvironment. Ultimately, this adaptable system provides a powerful framework for elucidating human stem cell biology and advancing bone marrow transplantation therapies.

cell biology↗

bioRxiv2026

Self-supervised learning for a gene program-centric view of cell states

Single-cell omics has extended the biological interrogation of cell state from examining the expression of individual genes to unbiased profiling of tens of thousands of genes at once. However, extracting biological insights from such high-dimensional data remains challenging. To enable downstream analyses, many computational approaches compress cell state into a single latent representation. This can obscure the structure of underlying gene programs (GP), defined as coordinated sets of biologically related genes, such as signalling pathway response modules or transcription factor targets. Here, we present Tripso, a self-supervised transformer deep learning model which learns multiple GP-specific embeddings from predefined GPs, while also enabling the discovery of novel, data-driven GPs. Tripso facilitates principled comparisons across development, disease, and experimental systems. Firstly, in a dataset of human hematopoietic cells spanning prenatal development through adulthood and aging and including newly generated data, Tripso resolved age-specific GP patterns, including elevated JAK-STAT activity in pediatric hematopoietic cells and postnatal shifts in IKZF1 GP activity during B cell differentiation. Secondly, leveraging Tripso GP embeddings and comparing in vivo to in vitro data, we hypothesized and experimentally validated that inhibition of the SEC61 translocon improved maintenance of hematopoietic stem cells in culture. Finally, Tripsos capacity for data-driven GP discovery revealed a previously uncharacterized tissue-resident memory T cell GP with increased activity in atopic dermatitis. Its spatial co-localization with sebaceous gland-associated immune niches was demonstrated in spatial transcriptomic and proteomic data. Thus, by moving beyond single embeddings of cellular states, Tripso enables interpretable and actionable discoveries, demonstrating how GP-centric modelling can generate hypotheses with substantial biomedical relevance. By anchoring cellular representations in meaningful GPs, Tripso establishes a principled and biologically grounded framework towards the development of interpretable virtual cell models.

bioinformatics↗

bioRxiv2026

Predicting how perturbations reshape cellular trajectories with PerturbGen

A major challenge in biology is predicting how cells transition between states over time and how perturbations disrupt these transitions. Understanding such dynamics is critical for identifying interventions that reverse pathological programs or reprogram cells toward desired states. Although recent computational approaches can predict single-cell perturbation responses in silico, they cannot predict responses across dynamic cell trajectories, for example how early perturbations reconfigure later cell states. To address this gap, we introduce PerturbGen, a generative foundation model trained on over 100 million single-cell transcriptomes that predicts perturbation responses along cellular trajectories. PerturbGen predicts how genetic perturbation at source state shapes downstream states, alters gene programs and trajectories across time, for example in differentiation or disease progression. We apply PerturbGen to three newly generated multi-condition human single-cell datasets spanning immune responses, hematopoiesis and skin development. In an in vivo immune challenge, PerturbGen predicts that knocking out an IL1B signal in myeloid cells attenuates later cytokine-interferon programs, with downstream changes consistent with a reversal of IL-1{beta} stimulation signature. In hematopoiesis, anchoring perturbation-induced programs to human genetics enables simulation of monogenic blood disorders, recapitulates established disease-associated biology whilst systematically revealing lineage-specific programs, including in lineages where this was not previously possible. In skin organoids, PerturbGen predicted that Wnt activation enhances stromal differentiation recapitulating the trajectory observed in human prenatal skin, findings that were functionally validated by experimentally activating Wnt signaling. Together, PerturbGen extends modeling of gene perturbations from static to dynamic cellular systems. We envision PerturbGen enabling the creation of in silico, trajectory-aware perturbation atlases and virtual cells across diverse biological scenarios, supporting optimization of disease models and prioritization of candidate molecular interventions for therapeutic discovery.

bioinformatics↗

bioRxiv2026

Comparative Biology at Single-Cell Resolution: Rigorous Matching of Atlases for Cross-Species Analysis

Single-cell transcriptomics has revolutionised developmental biology by providing an unprecedented, fine-grained view of cellular lineages. However, our ability to compare species and distinguish universal from species-specific developmental principles remains limited by biological and technical variability. To address this, we introduce RIMA (RIgorous Matching of Atlases), a method for quantitatively comparing transcriptomic atlases across species at near-single-cell resolution. RIMA uses a novel computational approach to identify matching cell states across atlases and leverages this to enable quantitative comparative analyses. Applied to gastrulation in mouse, rabbit, and macaque, RIMA recapitulates a developmental hourglass pattern, identifying a molecular similarity bottleneck at the onset of organogenesis. It further uncovers conserved developmental programmes, including a core set of transcription factors driving epithelial-mesenchymal transition, and highlights transcriptional boosts of erythroid differentiation genes that are conserved across species but exhibit shifted onset timing. Furthermore, RIMA enables cross-species prediction of gene expression, augmenting sparse atlases and correcting differences between model and target organisms. Beyond cross-species comparisons, RIMAs framework extends naturally to any setting where large systematic differences exist across datasets, including in vitro to in vivo comparisons, opening new avenues for improving biological models and advancing translational research.

bioinformatics↗

bioRxiv2025

Pseudodynamics+: Reconstructing Population Dynamics from Time-Resolved Single Cell Landscapes with Physics Informed Neural Networks

Single-cell profiling provides snapshots of the heterogeneous states that characterise developmental processes, organ regeneration and progression towards disease in a complex landscape. The underlying trajectories are of pivotal interest, but existing methods for reconstructing cell state trajectories commonly neglect population sizes. However, snapshot experiments make it difficult to interpret cell flux because the observed trajectories are confounded by changes in overall population size. This ambiguity can lead to misinterpreting changes in proliferation or death rates as changes in cellular migration. We introduce pseudodynamics+, a physics-informed neural network framework that solves high-dimensional flow equations on complex, branching landscapes. By integrating single-cell genomics with population dynamics, pseudodynamics+ estimates state- and time-dependent parameters of growth, differentiation, and diffusion. The model recapitulates proliferation bursts during T-cell maturation and, when applied to LARRY-barcoded data, predicts differentiation rates consistent with clonal behaviour. When applied to time-resolved persistent-labelling datasets of in vivo mouse bone marrow haematopoiesis, pseudodynamics+ reconstructs continuous tissue flows with dynamic parameters aligned with known molecular signatures. Notably, simulations revealed a previously unrecognised shift from megakaryocyte-biased to balanced progenitor output, explained by evolving fate preferences of progenitor states, as revealed by simulations leveraging our estimated dynamic parameters. Pseudodynamics+ therefore establishes a population-aware framework for reconstructing single-cell population dynamics and is available at https://github.com/Gottgens-lab/pseudodynamics_plus.

bioinformatics↗

bioRxiv2025

A Step-wise, Deterministic and Fatal Mouse Model of Myeloid Neoplasm with Spontaneous Acquisition of Patient-relevant RTK-RAS Mutations

Leukaemia arises through the stepwise transformation of healthy haematopoietic cells, yet the asymptomatic premalignant phase and its progression to overt disease remain poorly understood. To model this process, we engineered a patient-derived CEBPA mutation into Hoxb8-FL multipotent murine progenitors and transplanted them into syngeneic mice, capturing a clinically silent premalignant stage. All recipients developed overt disease after [~]12 months with 100% penetrance and all acquired secondary RTK-RAS mutations, often with identical amino acid changes to those in patients. Single-cell transcriptomics and phenotypic profiling showed that premalignant mutant cells adopt a plasmacytoid dendritic progenitor-like state in vitro which generates both myeloid and B-lymphoid lineages during premalignancy in vivo, with individual tumours restricted to one lineage. Specificity for RTK-RAS mutations coupled with ongoing differentiation is reminiscent of Juvenile Myelomonocytic Leukaemia, where cellular models are currently lacking, thus providing a tractable model of myeloid neoplasm for mechanistic studies and drug discovery.

cancer biology↗

bioRxiv2025

A new double reporter strategy reveals a subset of non-migratory hematopoietic stem cells localized in a dynamic bone marrow niche.

Interactions of hematopoietic stem cells (HSCs) with the bone marrow microenvironment are critical to regulate stem cell function in homeostasis, emergency hematopoiesis and ageing. The dynamic behavior of endogenous HSCs in their niches has been challenging to study due to the complexity of markers required to define pure HSCs. Multiple recently developed reporter strategies advanced our capacity to identify HSCs in situ. Yet, they provide different levels of HSC enrichment and are frequently not stable in situations of perturbed hematopoiesis, leading to contradictory observations of HSC migratory behavior. Here we employed a new double reporter strategy by combining the Hoxb5-mKO2 and Vwf-GFP reporters, that are stably expressed in homeostasis, stress and ageing. Hoxb5+Vwf+ cells represent a subset of highly pure and potent long-term HSCs with a platelet-biased pattern of differentiation, that are included in the populations identified by other reporter strategies. Intravital microscopy revealed Hoxb5+Vwf+ cells to be non-migratory in homeostasis, following platelet depletion when these cells are actively proliferating, and during ageing. This non-migratory behavior of HSCs in homeostasis and stress indicates that their activation does not inherently depend on relocation to alternative niches eliciting proliferation, as previously proposed. We found Hoxb5+Vwf+ HSCs in direct contact with vasculature and LepR+ perivascular cells but not preferentially closer to megakaryocytes. Nevertheless, increased megakaryopoiesis following platelet depletion brings megakaryocytes into close proximity of Hoxb5+Vwf+ HSCs, revealing previously unrecognized niche dynamics in HSC regulation during regeneration. DATA SHARING STATEMENTOriginal data will be made available upon reasonable request. The RNA sequencing data used in this study has been published before35 and is available from GEO (GSE81682). The code used for analysis is available from https://github.com/loversaber/Secchi_Paper_RNAseq_Analysis.git. KEY POINTSO_LICombined expression of Hoxb5-mKO2 and Vwf-GFP reporters defines a population of highly enriched long-term HSCs in situ and in vivo. C_LIO_LIHoxb5+Vwf+ HSCs are non-migratory in homeostasis, stress hematopoiesis and ageing, while their niche is highly dynamic. C_LI

cell biology↗

bioRxiv2025

Weighted sliced inverse regression for scalable supervised dimensionality reduction of spatial transcriptomics data

With the dramatic take-up of spatially resolved transcriptomics biotechnologies, performing spatially-aware analysis of the resulting data is crucial to maximise advances in biological understanding. Dimensionality reduction is a first step in almost any analysis of spatial transcriptomics data, regardless of whether the data is collected at the single-cell or spot level. While common approaches, such as principal component analysis, aim to identify low-dimensional scores that preserve total variances of gene expression features, such variances do not usually correspond to biologically relevant spatial variation. To this end, we have developed weighted sliced inverse regression (wSIR), a sufficient dimension reduction technique that performs dimensionality reduction and retains as much predictive power of the spatial coordinates as possible. As a linear dimensionality reduction approach, wSIR is applicable to multiple distinct spatial transcriptomic datasets, and is extremely scalable due to the algorithm and our Rcpp implementation, with over 100, 000 cells processed in under 2 minutes on a standard laptop. The feature loadings are interpretable, and new non-spatial data can be projected into the wSIR low-dimensional space for further downstream analyses. We examine wSIRs performance through benchmarking and demonstrate its capability of biological discovery through two case studies in breast cancer and early embryonic development.

genomics↗

bioRxiv2025

A subset of Haematopoietic Stem Cells resists Plasmodium infection-induced stress by uncoupling interferon sensing and metabolic activation

Hematopoietic stem cells (HSCs) sustain lifelong haematopoiesis as their progeny differentiate into all blood cell lineages. Homeostatic HSCs are mostly quiescent and only rarely divide, however their proliferation and differentiation rates can be modulated by external factors. Acute and chronic infections from a wide range of pathogens are known to challenge HSCs at the population level, being forced to respond to inflammation-mediated organismal demand to replenish the myeloid cell pool. However, less is known about the degree of heterogeneity in the HSCs response to inflammation at the single cell level. Here, using a natural murine malaria model and an NHS-ester biotin dilution assay we identify two subsets of HSCs, BiotinLo and BiotinHi, with distinct proliferation kinetics. Using combined functional, single-cell transcriptomics and phenotypic analyses, we uncover that BiotinHi HSCs remain highly functional despite expressing strong interferon response signatures. These infection-resistant HSCs express high levels of MHC II and are metabolically distinct from the remaining HSCs as they maintain less active mitochondria. These findings demonstrate that a likely reserve pool of HSCs remains highly functional during Plasmodium infection not because cells are shielded, but because they maintain a stemness associated metabolic profile despite effectively sensing inflammation.

cell biology↗

bioRxiv2025

A non-catalytic role for MLL2 in controlling chromatin organisation and mobility during the priming of pluripotent cells for differentiation

How the chromatin regulator MLL2 (KMT2B) influences cell differentiation remains poorly understood. MLL2 is the main histone 3 lysine 4 (H3K4) trimethyltransferase acting at bivalent promoters in embryonic stem cells (ESCs) and is required for ESCs to differentiate into neuroectoderm. We show here that this requirement occurs during exit from naive pluripotency, days before neuroectoderm differentiation is impaired. Although MLL2 knockout has only a subtle effect on transcription during exit, reducing the expression of a few important neuroectodermal transcription factors, it substantially remodels chromatin architecture, disrupting 3D chromatin loops associated with bivalent promoters. The enzymatic activity of MLL2 is not needed for stabilising these loops or for neuroectoderm differentiation. This non-catalytic function of MLL2 in stabilising 3D chromatin loops has implications for lineage specification. Because MLL2 shares features with all four MLLs, chromatin tethering, rather than H3K4 methylation, may represent the primary function of MLL proteins during lineage commitment.

cell biology↗

bioRxiv2025

Delayed Trp53 activation protects Dnmt3a-mutant hematopoietic stem cells from inflammatory attrition.

Hematopoietic stem cells (HSCs) accumulate somatic mutations over time, some conferring a fitness advantage that can lead to clonal hematopoiesis (CH). Mutations in DNMT3A, particularly at hotspot R882, are the most prevalent in CH and carry an increased risk of acute myeloid leukemia (AML). Although DNMT3A R882 mutations are linked to global DNA hypomethylation, the mechanisms underlying their selective advantage remain unclear. Here, we show that Dnmt3a-R882H mutant HSCs exhibit resilience under inflammatory and genotoxic stress. During IL-1{beta}-induced emergency granulopoiesis, Dnmt3a R882H/+ HSCs uncouple increased proliferation from stem cell exhaustion. In contrast, wild-type HSCs rapidly progress to terminal differentiation. We link this phenotype to a delayed activation of the p53-p21-DREAM axis, that allows mutant HSCs to avoid attrition, despite increased replication stress. Similarly, mutant HSCs exhibit delayed Trp53 activation following irradiation, but eventually recover a physiological Trp53 response. Analysis of patient data reveals shared phenotypic features between DNMT3A and monoallelic TP53 mutations in CH and myeloid neoplasms, highlighting potential functional similarities. Collectively, these findings suggest that the expansion of DNMT3A-mutant clones is affected by impaired TP53 signaling, which confers resilience against stressors. Therapeutic strategies targeting inflammatory pathways or the p53-p21-DREAM axis may reduce DNMT3A-CH expansion and/or progression and its associated risks.

molecular biology↗

bioRxiv2025

Selection of pre-leukemic hematopoietic stem cells driven by distinct extracellular matrix molecules

Despite rapid advances in mapping genetic drivers and gene expression changes in hematopoietic stem cells (HSCs), there is a relative paucity of studies at the protein level. Here, we perform a deep, multi-omic characterization (epigenome, transcriptome and proteome) of HSCs carrying a loss-of-function mutation in Tet2, a key driver of increased self-renewal in blood cancers. Using state-of-the-art, multiplexed, low-input mass spectrometry (MS)-based proteomics, we profile wildtype (WT) and TET2-deficient (Tet2-/-) HSCs and show that the proteome captures previously unrecognized molecular processes which define the pre-leukemic HSC molecular landscape. Specifically, we obtain more accurate stratification of WT and Tet2-/- HSCs than transcriptomic approaches and identify extracellular matrix (ECM) molecules as novel points of dysregulation upon TET2 loss. HSC expansion assays using ECM-functionalized hydrogels confirm a selective effect on the expansion of Tet2-mutant HSCs. Taken together, our study represents a comprehensive molecular characterization of Tet2-mutant HSCs and identifies a previously unanticipated role of ECM molecules in regulating self-renewal of disease-driving HSCs.

cell biology↗

bioRxiv2024

A Spatiotemporal Atlas of Mouse Gastrulation and Early Organogenesis to Explore Axial Patterning and Project In Vitro Models onto In Vivo Space

At the onset of murine gastrulation, pluripotent epiblast cells migrate through the primitive streak, generating mesodermal and endodermal precursors, while the ectoderm arises from the remaining epiblast. Together, these germ layers establish the body plan, defining major body axes and initiating organogenesis. Although comprehensive single cell transcriptional atlases of dissociated mouse embryos across embryonic stages have provided valuable insights during gastrulation, the spatial context for cell differentiation and tissue patterning remain underexplored. In this study, we employed spatial transcriptomics to measure gene expression in mouse embryos at E6.5 and E7.5 and integrated these datasets with previously published E8.5 spatial transcriptomics1 and a scRNA-seq2 atlas spanning E6.5 to E9.5. This approach resulted in a comprehensive spatiotemporal atlas, comprising over 150,000 cells with 88 refined cell type annotations as well as genome-wide transcriptional imputation during mouse gastrulation and early organogenesis. The atlas facilitates exploration of gene expression dynamics along anterior-posterior and dorsal-ventral axes at cell type, tissue, and organismal scales, revealing insights into mesodermal fate decisions within the primitive streak. Moreover, we developed a bioinformatics pipeline to project additional scRNA-seq datasets into a spatiotemporal framework and demonstrate its utility by analysing cardiovascular models of gastrulation3. To maximise impact, the atlas is publicly accessible via a user-friendly web portal empowering the wider developmental and stem cell biology communities to explore mechanisms of early mouse development in a spatiotemporal context.

developmental biology↗

bioRxiv2024

Semaphorin 4A maintains functional diversity of the hematopoietic stem cell pool

Somatic stem cell pools are comprised of diverse, highly specialized subsets whose individual contribution is critical for the overall regenerative function. In the bone marrow, myeloid-biased HSC (myHSC) are indispensable for replenishment of myeloid cells and platelets during inflammatory response but at the same time, become irreversibly damaged during inflammation and aging. Here, we identify an extrinsic factor, Semaphorin 4A (Sema4A), which non cell-autonomously confers myHSC resilience to inflammatory stress. We show that the absence of Sema4A, myHSC inflammatory hyper-responsiveness in young mice drives excessive myHSC expansion, myeloid bias and profound loss of regenerative function with age. Mechanistically, Sema4A is mainly produced by neutrophils, signals via a cell surface receptor Plexin D1 and safeguards myHSC epigenetic state. Our study shows that by selectively protecting a distinct stem cell subset, an extrinsic factor preserves functional diversity of somatic stem cell pool throughout organismal lifespan.

cell biology↗

bioRxiv2024

STAT3 signalling enhances tissue expansion during postimplantation mouse development

STAT3 signalling has been studied extensively in the context of self-renewal and differentiation of mouse embryonic stem cells. Zygotic STAT3 is required for normal postimplantation development. On an outbred genetic background, Stat3 null embryos consistently lagged behind their littermates, beginning with significant reduction of epiblast cells at implantation. Remarkably, mutants closely resemble non-affected embryos from the previous day at all postimplantation stages examined. We pinpoint this phenotype to loss of the serine-phosphorylated form of STAT3 which predominates in postimplantation embryonic tissues. Bulk RNA-sequencing analysis of isolated mouse epiblasts confirmed Stat3 null embryos exhibited developmental delay transcriptionally. Single cell RNA sequencing of mid gestation chimaeras containing STAT3 null embryonic stem cells revealed exclusion of mutant cells exclusively from the erythroid lineage. Although Stat3 null embryonic stem cells can differentiate into erythroid and hematopoietic lineages in vitro, they are out-competed when mixed with wild type cells. Combined with the reduced size of STAT3 null epiblasts after implantation, our results implicate a role for STAT3 in cell proliferation affecting temporal control of embryonic progression and rapid differentiation. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.

developmental biology↗