scholarly journals Spatiotemporal sequence of mesoderm and endoderm lineage segregation during mouse gastrulation

Development ◽  
2020 ◽  
Vol 148 (1) ◽  
pp. dev193789
Author(s):  
Simone Probst ◽  
Sagar ◽  
Jelena Tosic ◽  
Carsten Schwan ◽  
Dominic Grün ◽  
...  
Keyword(s):  
Primitive Streak ◽  
Cell Types ◽  
Complete Separation ◽  
Embryonic Cell ◽  
Spatiotemporal Pattern ◽  
Nodal Signaling ◽  
Layer Formation ◽  
Single Cell Rna Sequencing ◽  
Dependent Cell ◽  
Germ Layer Formation

ABSTRACTAnterior mesoderm (AM) and definitive endoderm (DE) progenitors represent the earliest embryonic cell types that are specified during germ layer formation at the primitive streak (PS) of the mouse embryo. Genetic experiments indicate that both lineages segregate from Eomes-expressing progenitors in response to different Nodal signaling levels. However, the precise spatiotemporal pattern of the emergence of these cell types and molecular details of lineage segregation remain unexplored. We combined genetic fate labeling and imaging approaches with single-cell RNA sequencing (scRNA-seq) to follow the transcriptional identities and define lineage trajectories of Eomes-dependent cell types. Accordingly, all cells moving through the PS during the first day of gastrulation express Eomes. AM and DE specification occurs before cells leave the PS from Eomes-positive progenitors in a distinct spatiotemporal pattern. ScRNA-seq analysis further suggested the immediate and complete separation of AM and DE lineages from Eomes-expressing cells as last common bipotential progenitor.

scholarly journals Spatiotemporal sequence of mesoderm and endoderm lineage segregation during mouse gastrulation

2020 ◽  
Author(s):  
Simone Probst ◽  
Sagar ◽  
Jelena Tosic ◽  
Carsten Schwan ◽  
Dominic Grün ◽  
...  
Keyword(s):  
Mouse Embryo ◽  
Primitive Streak ◽  
Cell Types ◽  
Complete Separation ◽  
Embryonic Cell ◽  
Spatiotemporal Pattern ◽  
Cell Lineages ◽  
Dependent Cell ◽  
Summary Statement ◽  
Germ Layer Formation

AbstractAnterior mesoderm (AM) and definitive endoderm (DE) progenitors represent the earliest embryonic cell types that are specified during germ layer formation at the primitive streak (PS) of the mouse embryo. Genetic experiments indicate that both lineages segregate from Eomes expressing progenitors in response to different NODAL signaling levels. However, the precise spatiotemporal pattern of the emergence of these cell types and molecular details of lineage segregation remain unexplored. We combined genetic fate labeling and imaging approaches with scRNA-seq to follow the transcriptional identities and define lineage trajectories of Eomes dependent cell types. All cells moving through the PS during the first day of gastrulation express Eomes. AM and DE specification occurs before cells leave the PS from discrete progenitor populations that are generated in distinct spatiotemporal patterns. Importantly, we don’t find evidence for the existence of progenitors that co-express markers of both cell lineages suggesting an immediate and complete separation of AM and DE lineages.Summary statementCells lineages are specified in the mouse embryo already within the primitive streak where Mesp1+ mesoderm and Foxa2+ endoderm are generated in a spatial and temporal sequence from unbiased progenitors.

Clonal analysis of epiblast fate during germ layer formation in the mouse embryo

Development ◽  
1991 ◽  
Vol 113 (3) ◽  
pp. 891-911 ◽  
Author(s):  
K.A. Lawson ◽  
J.J. Meneses ◽  
R.A. Pedersen
Keyword(s):  
Single Cells ◽  
Primitive Streak ◽  
Clonal Analysis ◽  
Neural Plate ◽  
Embryonic Axis ◽  
Population Doubling ◽  
Germ Layer ◽  
Layer Formation ◽  
Fate Map ◽  
Germ Layer Formation

The fate of cells in the epiblast at prestreak and early primitive streak stages has been studied by injecting horseradish peroxidase (HRP) into single cells in situ of 6.7-day mouse embryos and identifying the labelled descendants at midstreak to neural plate stages after one day of culture. Ectoderm was composed of descendants of epiblast progenitors that had been located in the embryonic axis anterior to the primitive streak. Embryonic mesoderm was derived from all areas of the epiblast except the distal tip and the adjacent region anterior to it: the most anterior mesoderm cells originated posteriorly, traversing the primitive streak early; labelled cells in the posterior part of the streak at the neural plate stage were derived from extreme anterior axial and paraxial epiblast progenitors; head process cells were derived from epiblast at or near the anterior end of the primitive streak. Endoderm descendants were most frequently derived from a region that included, but extended beyond, the region producing the head process: descendants of epiblast were present in endoderm by the midstreak stage, as well as at later stages. Yolk sac and amnion mesoderm developed from posterolateral and posterior epiblast. The resulting fate map is essentially the same as those of the chick and urodele and indicates that, despite geometrical differences, topological fate relationships are conserved among these vertebrates. Clonal descendants were not necessarily confined to a single germ layer or to extraembryonic mesoderm, indicating that these lineages are not separated at the beginning of gastrulation. The embryonic axis lengthened up to the neural plate stage by (1) elongation of the primitive streak through progressive incorporation of the expanding lateral and initially more anterior regions of epiblast and, (2) expansion of the region of epiblast immediately cranial to the anterior end of the primitive streak. The population doubling time of labelled cells was 7.5 h; a calculated 43% were in, or had completed, a 4th cell cycle, and no statistically significant regional differences in the number of descendants were found. This clonal analysis also showed that (1) growth in the epiblast was noncoherent and in most regions anisotropic and directed towards the primitive streak and (2) the midline did not act as a barrier to clonal spread, either in the epiblast in the anterior half of the axis or in the primitive streak. These results taken together with the fate map indicate that, while individual cells in the epiblast sheet behave independently with respect to their neighbours, morphogenetic movement during germ layer formation is coordinated in the population as a whole.

scholarly journals Single-cell transcriptomic analysis of mIHC images via antigen mapping

2021 ◽  
Vol 7 (10) ◽  
pp. eabc5464
Author(s):  
Kiya W. Govek ◽  
Emma C. Troisi ◽  
Zhen Miao ◽  
Rachael G. Aubin ◽  
Steven Woodhouse ◽  
...  
Keyword(s):  
Single Cell ◽  
Spatial Patterns ◽  
Cell Types ◽  
Level Of Detail ◽  
Cell Populations ◽  
Sequencing Data ◽  
Spatially Resolved ◽  
Murine Spleen ◽  
Single Cell Rna Sequencing ◽  
Antibody Panel

Highly multiplexed immunohistochemistry (mIHC) enables the staining and quantification of dozens of antigens in a tissue section with single-cell resolution. However, annotating cell populations that differ little in the profiled antigens or for which the antibody panel does not include specific markers is challenging. To overcome this obstacle, we have developed an approach for enriching mIHC images with single-cell RNA sequencing data, building upon recent experimental procedures for augmenting single-cell transcriptomes with concurrent antigen measurements. Spatially-resolved Transcriptomics via Epitope Anchoring (STvEA) performs transcriptome-guided annotation of highly multiplexed cytometry datasets. It increases the level of detail in histological analyses by enabling the systematic annotation of nuanced cell populations, spatial patterns of transcription, and interactions between cell types. We demonstrate the utility of STvEA by uncovering the architecture of poorly characterized cell types in the murine spleen using published cytometry and mIHC data of this organ.

scholarly journals Single-cell data clustering based on sparse optimization and low-rank matrix factorization

2021 ◽  
Author(s):  
Yinlei Hu ◽  
Bin Li ◽  
Falai Chen ◽  
Kun Qu
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Matrix Factorization ◽  
Data Clustering ◽  
Cell Types ◽  
Low Rank ◽  
Sequencing Data ◽  
Rank Matrix ◽  
Single Cell Rna Sequencing ◽  
Low Rank Matrix

Abstract Unsupervised clustering is a fundamental step of single-cell RNA sequencing data analysis. This issue has inspired several clustering methods to classify cells in single-cell RNA sequencing data. However, accurate prediction of the cell clusters remains a substantial challenge. In this study, we propose a new algorithm for single-cell RNA sequencing data clustering based on Sparse Optimization and low-rank matrix factorization (scSO). We applied our scSO algorithm to analyze multiple benchmark datasets and showed that the cluster number predicted by scSO was close to the number of reference cell types and that most cells were correctly classified. Our scSO algorithm is available at https://github.com/QuKunLab/scSO. Overall, this study demonstrates a potent cell clustering approach that can help researchers distinguish cell types in single-cell RNA sequencing data.

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