Transcriptomic profile of embryoid bodies under hypoxia at single cell level
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Curated by GigaByte
Editors Assessment:
This is a Data Release paper describing a mouse embryoid body single-cell RNA-seq dataset generated to study how oxygen availability shapes early cell differentiation. Acosta-Iborra et al. differentiated R1 mouse embryonic stem cells into embryoid bodies for 8 or 10 days, exposing them to hypoxia or normoxia for the final 16 or 48 hours of differentiation, then profiled thousands of cells per condition using droplet-based scRNA-seq from 10X. This yielding eight raw/filtered HDF5 count matrices across the four conditions. This was validated with flow cytometry, immunofluorescence, and EdU assays, confirming that hypoxia increased endothelial marker expression and vascular network complexity while inducing cell cycle arrest. This pattern mirrored transcriptionally, with hypoxic samples showing markedly higher proportions of cells in G0/G1 phase and elevated hypoxia gene-signature scores. QC analysis (and peer review in GigaByte) confirmed high data quality across samples, and conservative low-resolution clustering revealed a largely homogeneous progenitor population with a smaller, more differentiated subset. While there are limitations (mature endothelial cells were too sparse to robustly test the original hypothesis) the authors present this as an open, well-validated resource for comparative studies of hypoxia responses, benchmarking single-cell computational tools, and investigating early lineage specification and oxygen signaling more broadly.
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Abstract
Oxygen availability is a key regulator of cellular physiology and hypoxia plays a central role driving vasculogenesis and angiogenesis during development. Although bulk transcriptomics has revealed important oxygen-regulated gene networks, such approaches cannot resolve the cellular heterogeneity and lineage dynamics characteristic of early differentiation. To address this, we generated a single-cell transcriptomic dataset from murine embryoid bodies, a widely used in vitro model of early embryonic development, cultured 8 or 10 days under hypoxic (1% O2) or normoxic (21% O2) conditions for the final 16 or 48 hours of differentiation. This resource enables detailed exploration of how oxygen availability influences lineage specification, vascular and hematopoietic development, and cellular heterogeneity during early differentiation. Beyond developmental biology, the dataset provides a valuable reference for comparative studies of hypoxia responses, benchmarking of single-cell analysis methods, and integrative investigations into oxygen signaling across diverse biological systems.
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Editors Assessment:
This is a Data Release paper describing a mouse embryoid body single-cell RNA-seq dataset generated to study how oxygen availability shapes early cell differentiation. Acosta-Iborra et al. differentiated R1 mouse embryonic stem cells into embryoid bodies for 8 or 10 days, exposing them to hypoxia or normoxia for the final 16 or 48 hours of differentiation, then profiled thousands of cells per condition using droplet-based scRNA-seq from 10X. This yielding eight raw/filtered HDF5 count matrices across the four conditions. This was validated with flow cytometry, immunofluorescence, and EdU assays, confirming that hypoxia increased endothelial marker expression and vascular network complexity while inducing cell cycle arrest. This pattern mirrored transcriptionally, with hypoxic samples showing markedly higher …
Editors Assessment:
This is a Data Release paper describing a mouse embryoid body single-cell RNA-seq dataset generated to study how oxygen availability shapes early cell differentiation. Acosta-Iborra et al. differentiated R1 mouse embryonic stem cells into embryoid bodies for 8 or 10 days, exposing them to hypoxia or normoxia for the final 16 or 48 hours of differentiation, then profiled thousands of cells per condition using droplet-based scRNA-seq from 10X. This yielding eight raw/filtered HDF5 count matrices across the four conditions. This was validated with flow cytometry, immunofluorescence, and EdU assays, confirming that hypoxia increased endothelial marker expression and vascular network complexity while inducing cell cycle arrest. This pattern mirrored transcriptionally, with hypoxic samples showing markedly higher proportions of cells in G0/G1 phase and elevated hypoxia gene-signature scores. QC analysis (and peer review in GigaByte) confirmed high data quality across samples, and conservative low-resolution clustering revealed a largely homogeneous progenitor population with a smaller, more differentiated subset. While there are limitations (mature endothelial cells were too sparse to robustly test the original hypothesis) the authors present this as an open, well-validated resource for comparative studies of hypoxia responses, benchmarking single-cell computational tools, and investigating early lineage specification and oxygen signaling more broadly.
This evaluation refers to version 1 of the preprint
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AbstractOxygen availability is a key regulator of cellular physiology and hypoxia plays a central role driving vasculogenesis and angiogenesis during development. While bulk transcriptomics has revealed important oxygen-regulated gene networks, such approaches cannot resolve the cellular heterogeneity and lineage dynamics characteristic of early differentiation. To address this, we generated a single-cell transcriptomic dataset from murine embryoid bodies, a widely used in vitro model of early embryonic development, cultured 8 or 10 days under hypoxic (1% O2) or normoxic (21% O2) conditions for the final 16 or 48 hours of differentiation. This resource enables detailed exploration of how oxygen availability influences lineage specification, vascular and hematopoietic development, and cellular heterogeneity during early differentiation. …
AbstractOxygen availability is a key regulator of cellular physiology and hypoxia plays a central role driving vasculogenesis and angiogenesis during development. While bulk transcriptomics has revealed important oxygen-regulated gene networks, such approaches cannot resolve the cellular heterogeneity and lineage dynamics characteristic of early differentiation. To address this, we generated a single-cell transcriptomic dataset from murine embryoid bodies, a widely used in vitro model of early embryonic development, cultured 8 or 10 days under hypoxic (1% O2) or normoxic (21% O2) conditions for the final 16 or 48 hours of differentiation. This resource enables detailed exploration of how oxygen availability influences lineage specification, vascular and hematopoietic development, and cellular heterogeneity during early differentiation. Beyond developmental biology, the dataset provides a valuable reference for comparative studies of hypoxia responses, benchmarking of single-cell analysis methods, and integrative investigations into oxygen signaling across diverse biological systems.
This paper is peer reviewed in GigaByte journal and the peer reviews are released under a CC-BY license. See: Bárbara Acosta-Iborra, Yosra Berrouayel, Laura Puente-Santamaría, Luis del Peso, Benilde Jiménez, Transcriptomic profile of embryoid bodies under hypoxia at single cell level, Gigabyte, 2026 https://doi.org/10.46471/gigabyte.178
Reviewer 1. Gerardo Cordero
Is the validation suitable for this type of data? Yes. The experimental effect was validated. Minor comments: 1)In the second line of the abstract please change the proposition ‘while' to ‘although’ 2)Which Illumina platform did you use? 3)Do you have quality control metrics for mitochondrial contamination? This can be used as an indicator of a reduction of cell viability during processing.
Reviewer 2. Wei Zhang
Is there sufficient detail in the methods and data-processing steps to allow reproduction?
No. The experimental procedures are generally clear; however, the data analysis requires further improvement. More detailed descriptions of the data processing and analysis steps are needed. For example, specific parameters used in Cell Ranger should be explicitly reported. Additional downstream processing using commonly adopted tools such as Seurat to generate cell clustering results would be beneficial. This would not only provide an extra layer of data quality assessment, but also facilitate data reuse by enabling users to work directly with processed datasets without the need to perform a full reanalysis.
Is there sufficient data validation and statistical analyses of data quality?
No. The authors provide both biological and technical validations supporting the robustness of the dataset, and standard single-cell RNA-seq quality metrics indicate high technical quality. However, as noted above, additional downstream analyses could further characterize data quality, for example by estimating the proportion of doublets and assessing the fraction of cells with high mitochondrial gene content, among other commonly used metrics. The authors note that the data have been analyzed in a preprint manuscript; including more detailed analyses in the present manuscript would further strengthen the value of this data release.
Is the validation suitable for this type of data?
No. While the authors present solid biological and technical validations, and independent assays demonstrate hypoxia responses consistent with previous studies, the sequencing data represent the core contribution of this manuscript. Additional analyses leveraging the single-cell transcriptomic data to directly examine angiogenesis or endothelial expansion would further strengthen the validation and enhance the value of the dataset for reuse.
Is there sufficient information for others to reuse this dataset or integrate it with other data?
No. Although the reuse potential is clearly articulated, providing more concrete details on the structure and contents of the deposited data—such as the number of samples and file types—would further facilitate data reuse and integration.
Additional Comments:
This manuscript describes a well-designed single-cell RNA-seq dataset generated from murine embryoid bodies differentiated under controlled hypoxic and normoxic conditions. The experimental procedures are generally clear and methodologically sound, and the dataset has potential value as a community resource. However, several issues should be addressed:1） More detailed downstream analyses would strengthen the manuscript and better demonstrate the utility and quality of the dataset. 2）The overall data size is relatively limited, comprising only four experimental conditions/time points, which may restrict its broader applicability. 3）The authors state that these sequencing data have already been used in a preprint manuscript by the same group. It is therefore unclear whether the dataset remains appropriate for publication in this journal as a standalone Data Release.
Re-review: The revised version has largely addressed the previous concerns. The methods are described in greater detail, the data presentation is more comprehensive, and the overall quality of the manuscript has improved substantially. However, I have some concerns regarding the cell clustering shown in Figure 5. Several clusters (e.g., clusters 6, 8, and 10) appear to be strong outliers. It would be helpful to further examine these subpopulations, for example by assessing whether they are influenced by batch effects and whether batch-effect correction using appropriate software is necessary, although it is also possible that these subclusters are biologically meaningful. In addition, performing doublet detection and filtering prior to re-clustering the cells would likely be more appropriate, as some outlier subclusters (e.g., cluster 10) might disappear after these steps.
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