Systematic reconstruction of the cellular trajectories of mammalian embryogenesis (E8.5)
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA772276 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR16472300_1.fastq.gz | Fastqsanger.gz | |||
| SRR16472300_2.fastq.gz | Fastqsanger.gz | |||
| SRR16472400_1.fastq.gz | Fastqsanger.gz | |||
| SRR16472400_2.fastq.gz | Fastqsanger.gz | |||
| SRR16472500_1.fastq.gz | Fastqsanger.gz |
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Project description:Mammalian embryogenesis is characterized by rapid cellular proliferation and diversification. Within a few weeks, a single cell zygote gives rise to millions of cells expressing a panoply of molecular programs, including much of the diversity that will subsequently be present in adult tissues. Although intensively studied, a comprehensive delineation of the major cellular trajectories that comprise mammalian development in vivo remains elusive. For mouse embryogenesis in particular, we and others have performed single cell or single nucleus RNA-seq data (scRNA-seq) during implantation, gastrulation and organogenesis. Here we set out to integrate several single cell RNA-seq datasets (scRNA-seq) that collectively span mouse gastrulation and organogenesis. However, a technical challenge that we faced is that the datasets that we sought to integrate were generated by different groups at different times using different scRNA-seq technologies. In particular, probably because there was no overlapping timepoint, the integration of scRNA-seq data generated at E8.5 (cells, 10X Genomics) and E9.5 (nuclei, sci-RNA-seq3) was challenging (Cao et al. 2019; Pijuan-Sala et al. 2019). To address this, we set out to generate new data at E8.5 that might serve to “bridge” these two datasets. Because of how quickly changes are occurring during this window of development, we focused on individual, somite-resolved E8.5 embryos using a simplified, optimized version of sci-RNA-seq3. We selected 12 embryos from 2 separate litters harvested at E8.5, including a single primitive streak stage embryo (prior to somitogenesis) and 11 embryos staged in 1-somite increments from 2 to 12 somites. The optimized sci-RNA-seq3 method markedly improved data quality, with 9-fold higher UMIs and 6-fold higher gene detection per nucleus, relative to (Cao et al. 2019). Overall, we collected published data (Cheng et al. 2019; Mohammed et al. 2017; Pijuan-Sala et al. 2019), the new E8.5 data, and published data from one study spanning E9.5 to E13.5 but with deeper sequencing of those libraries (Cao et al. 2019). Altogether, we define cell states at each of 19 successive stages spanning E3.5 to E13.5, heuristically connect them to their pseudo-ancestors and pseudo-descendants. Despite being constructed through automated procedures, the resulting trajectories of mammalian embryogenesis (TOME) are largely consistent with our contemporary understanding of mammalian development. In addition, the new E8.5 data itself comprises a foundational resource for mammalian developmental biology (especially for the early somitogenesis), and are made available in a way that will facilitate their ongoing annotation by the research community.
2022-03-11 | GSE186069 | GEO
Project description:Systematic reconstruction of the cellular trajectories of mammalian embryogenesis
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Project description:During embryogenesis, cells acquire distinct fates by transitioning through transcriptional states. To uncover these transcriptional trajectories during zebrafish embryogenesis, we sequenced 38,731 cells and developed URD, a simulated diffusion-based computational reconstruction method. URD identified the trajectories of 25 cell types through early somitogenesis, gene expression along them, and their spatial origin in the blastula. Analysis of Nodal signaling mutants revealed that their transcriptomes were canalized into a subset of wild-type transcriptional trajectories. Some wild-type developmental branchpoints contained cells expressing genes characteristic of multiple fates. These cells appeared to trans-specify from one fate to another. These findings reconstruct the transcriptional trajectories of a vertebrate embryo, highlight the concurrent canalization and plasticity of embryonic specification, and provide a framework to reconstruct complex developmental trees from single-cell transcriptomes. This SuperSeries is composed of the SubSeries listed below.
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Project description:Systematic reconstruction of the cellular trajectories of mammalian embryogenesis (deeper sequencing of E9.5-E13.5)
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Project description:Mammalian embryogenesis is characterized by rapid cellular proliferation and diversification. Within a few weeks, a single cell zygote gives rise to millions of cells expressing a panoply of molecular programs, including much of the diversity that will subsequently be present in adult tissues. Although intensively studied, a comprehensive delineation of the major cellular trajectories that comprise mammalian development in vivo remains elusive. For mouse embryogenesis in particular, we and others have performed single cell or single nucleus RNA-seq data (scRNA-seq) during implantation, gastrulation and organogenesis. Here we set out to integrate several single cell RNA-seq datasets (scRNA-seq) that collectively span mouse gastrulation and organogenesis. However, a technical challenge that we faced is that the datasets that we sought to integrate were generated by different groups at different times using different scRNA-seq technologies. In particular, probably because there was no overlapping timepoint, the integration of scRNA-seq data generated at E8.5 (cells, 10X Genomics) and E9.5 (nuclei, sci-RNA-seq3) was challenging (Cao et al. 2019; Pijuan-Sala et al. 2019). To address this, we set out to generate new data at E8.5 that might serve to “bridge” these two datasets. Because of how quickly changes are occurring during this window of development, we focused on individual, somite-resolved E8.5 embryos using a simplified, optimized version of sci-RNA-seq3. At the same time, to obtain higher quality data across E9.5-E13.5, we performed a deeper sequencing (specifically, three additional Novaseq runs) of previously reported libraries (Cao et al. 2019). Compared to the previous data (Cao et al. 2019), the median UMI count per cell improved from 671 to 1,434, while the median genes detected per cell improved from 518 to 735. Overall, we collected published data (Cheng et al. 2019; Mohammed et al. 2017; Pijuan-Sala et al. 2019), the new E8.5 data, and the deeper sequencing of previous libraries (Cao et al. 2019). Altogether, we define cell states at each of 19 successive stages spanning E3.5 to E13.5, heuristically connect them to their pseudo-ancestors and pseudo-descendants. Despite being constructed through automated procedures, the resulting trajectories of mammalian embryogenesis (TOME) are largely consistent with our contemporary understanding of mammalian development. In addition, the data of deeper sequencing of previously reported libraries itself comprises a foundational resource for mammalian developmental biology, and are made available in a way that will facilitate their ongoing annotation by the research community.
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Project description:This SuperSeries is composed of the SubSeries listed below.
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Project description:Mammalian embryogenesis is characterized by rapid cellular proliferation and diversification. Within a few weeks, a single-cell zygote gives rise to millions of cells expressing a panoply of molecular programs. Although intensively studied, a comprehensive delineation of the major cellular trajectories that comprise mammalian development in vivo remains elusive. Here, we set out to integrate several single-cell RNA-sequencing (scRNA-seq) datasets that collectively span mouse gastrulation and organogenesis, supplemented with new profiling of ~150,000 nuclei from approximately embryonic day 8.5 (E8.5) embryos staged in one-somite increments. Overall, we define cell states at each of 19 successive stages spanning E3.5 to E13.5 and heuristically connect them to their pseudoancestors and pseudodescendants. Although constructed through automated procedures, the resulting directed acyclic graph (TOME (trajectories of mammalian embryogenesis)) is largely consistent with our contemporary understanding of mammalian development. We leverage TOME to systematically nominate transcription factors (TFs) as candidate regulators of each cell type's specification, as well as 'cell-type homologs' across vertebrate evolution.
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Project description:This project is based on the extension of the single cell transcriptomics atlas of mouse development towards E9.5. Inference of cell differentiation trajectories was carried out using Waddington-Optimal Transport, and the resulting computational reconstruction was contrasted with grafting experiments as well as complementary scRNA-seq experiments.
2023-01-01 | E-MTAB-11763 | biostudies-arrayexpress
Project description:This project is based on the extension of the single cell transcriptomics atlas of mouse development towards E9.5. Inference of cell differentiation trajectories was carried out using Waddington-Optimal Transport, and the resulting computational reconstruction was contrasted with grafting experiments as well as complementary scRNA-seq experiments. This data submission refers to the grafting experiments.
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