A single-cell transcriptome atlas profiles early organogenesis in human embryos
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE157329 | GEO | 2021/09/01
REPOSITORIES: GEO
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Project description:Mammalian embryos exhibits sophisticated cell organizations that are intricately orchestrated at both molecular and cellular level. It has recently become apparent that cells within the animal body display significant heterogeneity, both in terms of their cellular properties and their spatial distributions. However, current spatial transcriptomics profiling either lack three-dimensional representation or are limited in their ability to capture the complexity of embryonic tissues and organs. Here, we present a represented spatial transcriptome atlas of all major organs at embryonic day 13.5 (E13.5) in the mouse embryo, and provide a three- dimensional rendering of molecular regulation for embryonic patterning with stacked sections. By integrating this spatial transcriptome data with corresponding single-cell transcriptome data, we offer a detailed molecular annotation of the dynamic nature of organ development, spatial cellular interaction, embryonic axes and divergence of cell fates underlying mammalian development, which would pave the way for precise organ engineering and stem cell-based regenerative medicine.
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Project description:Stranded RNA-seq from human embryo tissues and organs
2016-09-02 | E-MTAB-3928 | biostudies-arrayexpress
Project description:Background: Organogenesis is crucial for proper organ formation during mammalian embryonic development. However, the similarities and shared features between different organs and the cellular heterogeneity during this process at single-cell resolution remain elusive. Results: We perform single-cell RNA sequencing analysis of 1,916 individual cells from eight organs and tissues of E9.5 to E11.5 mouse embryos, namely, the forebrain, hindbrain, skin, heart, somite, lung, liver, and intestine. Based on the regulatory activities rather than the expression patterns, all cells analyzed can be well classified into four major groups with epithelial, mesodermal, hematopoietic and neuronal identities. For different organs within the same group, the similarities and differences of their features and developmental paths are revealed and reconstructed. Conclusions: We identify mutual interactions between epithelial and mesenchymal cells and detect epithelial cells with prevalent mesenchymal features during organogenesis, which are similar to the features of intermediate epithelial/mesenchymal cells during tumorigenesis. The comprehensive transcriptome at single-cell resolution profiled in our study paves the way for future mechanistic studies of the gene- regulatory networks governing mammalian organogenesis.
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Project description:A balance of morphogen gradients during embryogenesis is thought to determine the identity of inner ear end organs. We applied this developmental principle to aggregates of human pluripotent stem cells and found that modulations of Sonic Hedgehog and WNT signaling promote stem cell-derived otic progenitors to express ventral otic markers. Strikingly, these ventralized otic progenitors gave rise to hair cells with short hair bundles comprised of stereocilia arrayed in a geometry reminiscent of cochlear hair cells. Moreover, these ventralized hair cells expressed multiple markers defining outer or inner hair cells in the cochlea. These results reveal that early morphogenic signals are sufficient for not only establishing cochlear gene expression, but also defining structural properties pertaining to the cochlear sensory epithelium.
2022-04-14 | GSE200629 | GEO
Project description:We here report transcriptome profiling of human embryos at six successive developmental stages (i.e., Carnegie Stages 9 to 14), representing the first comprehensive gene expression database of early human organogenesis. Through a series of data mining and comparisons with the transcriptome during mouse embryogenesis and the disparate genomic data in human embryonic stem cells, we revealed that development potential during early human organogenesis is orchestrated by two dominant categories of genes. Specifically, most gradually induced genes are largely differentiation related whereas those gradually repressed are involved in both stemness- and differentiation-relevant aspects of the developmental potential. Further through integrative mining we uncovered a molecular network that well characterizes stemness- and differentiation-relevant aspects of developmental potentials during early human organogenesis. Analysis of published data showed that the network could serve to evaluate various differentiation models. Our results make a significant step towards understanding of human embryogenesis at a molecular level and suggest that developmental potentials are under control of shared regulatory events. With the consent of subjects and of the Ethical Review Board of the Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine,we collected human post-implantation embryos at six successive time periods: Carnegie Stages 9 to 14 (E20 to E32), covering the first third of organogenesis. Using the Affymetrix HG-U133A Genechip microarrays, three replicates were independently profiled for each stage to minimize the influence of the embryo-to-embryo variation. Raw expression data were normalized using Robust Multi-array Averaging (RMA) with quantile normalization. The resultant expression data were imported into Extraction of Differential Gene Expression (EDGE) software for the detection of probesets exhibiting the consistent changes within the triplicates and differential expression (denoted as hORG expression matrix). The hORG expression matrix was subjected to Linear Models for Microarray Data (LIMMA) bioconductor library for identification of stage-transitive transcriptome changes, and self-organizing map combined with singular value decomposition (SOM-SVD) as well as SOM-based two-phase gene clustering for the topology-preserving extraction of temporal expression patterns. Hypergeometric distribution-based enrichment analyses were performed to explore the underlying biological relevance of gene groups of interest using diverse external annotated databases. The Cytoscape plug-in jActiveModules was modified to identify expression-active connected subnetworks in the compiled human interaction/association network.
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Project description:Extensive studies of the model plant Arabidopsis has enabled a deep understanding of organs and tissues throughout plant development. Yet, a fundamental understanding of cell types and states across organs and development is still lacking. Here, we present a single-nucleus transcriptome atlas of Arabidopsis seed-to-seed development encompassing diverse tissues across ten developmental time points. Analysis of over 400,000 nuclei revealed 183 major and 653 subclusters that demarcate cell type and state. Cross-organ analyses revealed that the transcriptional identity of many cell types is conserved across development but influenced by the organ of origin and developmental timing. In addition, groups of transcription factors were enriched and uniquely expressed in individual organs and time points, suggesting developmental gatekeeping of transcription factor activation. Finally, we employed spatial transcriptomics to validate our findings in the highly complex silique organ.
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Project description:Emerging spatial profiling technology has enabled high-plex molecular profiling in biological tissues, preserving the spatial and morphological context of gene or protein expression. Here we describe expanded chemistry for the Digital Spatial Profiling platform to quantify whole transcriptomes in human and mouse tissues using a wide range of spatial profiling strategies and sample types. We designed multiplexed in situ hybridization probe pools targeting the protein-coding genes in the human and mouse transcriptomes, hereafter referred to as the human or mouse Whole Transcriptome Atlas (WTA). We validated the human and mouse WTA assays using cell lines to demonstrate concordance with orthogonal gene expression profiling methods in profiled region sizes ranging from ∼10-500 cells. By benchmarking against bulk RNAseq and single-molecule fluorescence in situ hybridization, we demonstrate robust transcript detection possible down to ∼100 transcripts per region. To assess the performance of WTA across tissue and sample types, we applied WTA to biological questions in cancer, molecular pathology, and developmental biology. We show that spatial profiling with WTA can detect expected spatial gene expression differences between tumor and tumor microenvironment, identify spatial disease-specific heterogeneity in gene expression in histological structures of the human kidney, and comprehensively map transcriptional programs in anatomical substructures of nine organs in the developing mouse embryo. Digital Spatial Profiling technology with the WTA assays provides a flexible method for spatial whole transcriptome profiling applicable to diverse tissue types and biological contexts.
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Project description:Emerging spatial profiling technology has enabled high-plex molecular profiling in biological tissues, preserving the spatial and morphological context of gene or protein expression. Here we describe expanded chemistry for the Digital Spatial Profiling platform to quantify whole transcriptomes in human and mouse tissues using a wide range of spatial profiling strategies and sample types. We designed multiplexed in situ hybridization probe pools targeting the protein-coding genes in the human and mouse transcriptomes, hereafter referred to as the human or mouse Whole Transcriptome Atlas (WTA). We validated the human and mouse WTA assays using cell lines to demonstrate concordance with orthogonal gene expression profiling methods in profiled region sizes ranging from ∼10-500 cells. By benchmarking against bulk RNAseq and single-molecule fluorescence in situ hybridization, we demonstrate robust transcript detection possible down to ∼100 transcripts per region. To assess the performance of WTA across tissue and sample types, we applied WTA to biological questions in cancer, molecular pathology, and developmental biology. We show that spatial profiling with WTA can detect expected spatial gene expression differences between tumor and tumor microenvironment, identify spatial disease-specific heterogeneity in gene expression in histological structures of the human kidney, and comprehensively map transcriptional programs in anatomical substructures of nine organs in the developing mouse embryo. Digital Spatial Profiling technology with the WTA assays provides a flexible method for spatial whole transcriptome profiling applicable to diverse tissue types and biological contexts.
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Project description:Emerging spatial profiling technology has enabled high-plex molecular profiling in biological tissues, preserving the spatial and morphological context of gene or protein expression. Here we describe expanded chemistry for the Digital Spatial Profiling platform to quantify whole transcriptomes in human and mouse tissues using a wide range of spatial profiling strategies and sample types. We designed multiplexed in situ hybridization probe pools targeting the protein-coding genes in the human and mouse transcriptomes, hereafter referred to as the human or mouse Whole Transcriptome Atlas (WTA). We validated the human and mouse WTA assays using cell lines to demonstrate concordance with orthogonal gene expression profiling methods in profiled region sizes ranging from ∼10-500 cells. By benchmarking against bulk RNAseq and single-molecule fluorescence in situ hybridization, we demonstrate robust transcript detection possible down to ∼100 transcripts per region. To assess the performance of WTA across tissue and sample types, we applied WTA to biological questions in cancer, molecular pathology, and developmental biology. We show that spatial profiling with WTA can detect expected spatial gene expression differences between tumor and tumor microenvironment, identify spatial disease-specific heterogeneity in gene expression in histological structures of the human kidney, and comprehensively map transcriptional programs in anatomical substructures of nine organs in the developing mouse embryo. Digital Spatial Profiling technology with the WTA assays provides a flexible method for spatial whole transcriptome profiling applicable to diverse tissue types and biological contexts.
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