Fetal Gene Atlas Fetal Lineage Track Settings
 
Fetal Gene Atlas binned by cell lineage and organ from Cao et al 2020

Track collection: Fetal Gene Atlas from Cao et al 2020

+  Description
+  All tracks in this collection (8)

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Log10(x+1) transform:    View limits maximum: UMI/cell (range 0-10000)

Categories:  
 Adrenal-Adrenocortical cells
 Adrenal-CSH1 CSH2 positive cells
 Adrenal-Chromaffin cells
 Adrenal-Erythroblasts
 Adrenal-Lymphoid cells
 Adrenal-Megakaryocytes
 Adrenal-Myeloid cells
 Adrenal-SLC26A4 PAEP positive cells
 Adrenal-Schwann cells
 Adrenal-Stromal cells
 Adrenal-Sympathoblasts
 Adrenal-Vascular endothelial cells
 Cerebellum-Astrocytes
 Cerebellum-Granule neurons
 Cerebellum-Inhibitory interneurons
 Cerebellum-Microglia
 Cerebellum-Oligodendrocytes
 Cerebellum-Purkinje neurons
 Cerebellum-SLC24A4 PEX5L positive cells
 Cerebellum-Unipolar brush cells
 Cerebellum-Vascular endothelial cells
 Cerebrum-Astrocytes
 Cerebrum-Excitatory neurons
 Cerebrum-Inhibitory neurons
 Cerebrum-Limbic system neurons
 Cerebrum-Megakaryocytes
 Cerebrum-Microglia
 Cerebrum-Oligodendrocytes
 Cerebrum-SKOR2 NPSR1 positive cells
 Cerebrum-Vascular endothelial cells
 Eye-Amacrine cells
 Eye-Astrocytes
 Eye-Bipolar cells
 Eye-Corneal and conjunctival epithelial cells
 Eye-Ganglion cells
 Eye-Horizontal cells
 Eye-Lens fibre cells
 Eye-Microglia
 Eye-PDE11A FAM19A2 positive cells
 Eye-Photoreceptor cells
 Eye-Retinal pigment cells
 Eye-Retinal progenitors and Muller glia
 Eye-Skeletal muscle cells
 Eye-Smooth muscle cells
 Eye-Stromal cells
 Eye-Vascular endothelial cells
 Heart-CLC IL5RA positive cells
 Heart-Cardiomyocytes
 Heart-ELF3 AGBL2 positive cells
 Heart-Endocardial cells
 Heart-Epicardial fat cells
 Heart-Erythroblasts
 Heart-Lymphatic endothelial cells
 Heart-Lymphoid cells
 Heart-Megakaryocytes
 Heart-Myeloid cells
 Heart-SATB2 LRRC7 positive cells
 Heart-Schwann cells
 Heart-Smooth muscle cells
 Heart-Stromal cells
 Heart-Vascular endothelial cells
 Heart-Visceral neurons
 Intestine-Chromaffin cells
 Intestine-ENS glia
 Intestine-ENS neurons
 Intestine-Erythroblasts
 Intestine-Intestinal epithelial cells
 Intestine-Lymphatic endothelial cells
 Intestine-Lymphoid cells
 Intestine-Mesothelial cells
 Intestine-Myeloid cells
 Intestine-Smooth muscle cells
 Intestine-Stromal cells
 Intestine-Vascular endothelial cells
 Kidney-Erythroblasts
 Kidney-Lymphoid cells
 Kidney-Megakaryocytes
 Kidney-Mesangial cells
 Kidney-Metanephric cells
 Kidney-Myeloid cells
 Kidney-Stromal cells
 Kidney-Ureteric bud cells
 Kidney-Vascular endothelial cells
 Liver-Erythroblasts
 Liver-Hematopoietic stem cells
 Liver-Hepatoblasts
 Liver-Lymphoid cells
 Liver-Megakaryocytes
 Liver-Mesothelial cells
 Liver-Myeloid cells
 Liver-Stellate cells
 Liver-Vascular endothelial cells
 Lung-Bronchiolar and alveolar epithelial cells
 Lung-CSH1 CSH2 positive cells
 Lung-Ciliated epithelial cells
 Lung-Lymphatic endothelial cells
 Lung-Lymphoid cells
 Lung-Megakaryocytes
 Lung-Mesothelial cells
 Lung-Myeloid cells
 Lung-Neuroendocrine cells
 Lung-Squamous epithelial cells
 Lung-Stromal cells
 Lung-Vascular endothelial cells
 Lung-Visceral neurons
 Muscle-Erythroblasts
 Muscle-Lymphatic endothelial cells
 Muscle-Lymphoid cells
 Muscle-Megakaryocytes
 Muscle-Myeloid cells
 Muscle-Satellite cells
 Muscle-Schwann cells
 Muscle-Skeletal muscle cells
 Muscle-Smooth muscle cells
 Muscle-Stromal cells
 Muscle-Vascular endothelial cells
 Pancreas-Acinar cells
 Pancreas-CCL19 CCL21 positive cells
 Pancreas-Ductal cells
 Pancreas-ENS glia
 Pancreas-ENS neurons
 Pancreas-Erythroblasts
 Pancreas-Islet endocrine cells
 Pancreas-Lymphatic endothelial cells
 Pancreas-Lymphoid cells
 Pancreas-Mesothelial cells
 Pancreas-Myeloid cells
 Pancreas-Smooth muscle cells
 Pancreas-Stromal cells
 Pancreas-Vascular endothelial cells
 Placenta-AFP ALB positive cells
 Placenta-Extravillous trophoblasts
 Placenta-IGFBP1 DKK1 positive cells
 Placenta-Lymphoid cells
 Placenta-Megakaryocytes
 Placenta-Myeloid cells
 Placenta-PAEP MECOM positive cells
 Placenta-Smooth muscle cells
 Placenta-Stromal cells
 Placenta-Syncytiotrophoblasts and villous cytotrophoblasts
 Placenta-Trophoblast giant cells
 Placenta-Vascular endothelial cells
 Spleen-AFP ALB positive cells
 Spleen-Erythroblasts
 Spleen-Lymphoid cells
 Spleen-Megakaryocytes
 Spleen-Mesothelial cells
 Spleen-Myeloid cells
 Spleen-STC2 TLX1 positive cells
 Spleen-Stromal cells
 Spleen-Vascular endothelial cells
 Stomach-Ciliated epithelial cells
 Stomach-ENS glia
 Stomach-ENS neurons
 Stomach-Erythroblasts
 Stomach-Goblet cells
 Stomach-Lymphatic endothelial cells
 Stomach-Lymphoid cells
 Stomach-MUC13 DMBT1 positive cells
 Stomach-Mesothelial cells
 Stomach-Myeloid cells
 Stomach-Neuroendocrine cells
 Stomach-PDE1C ACSM3 positive cells
 Stomach-Parietal and chief cells
 Stomach-Squamous epithelial cells
 Stomach-Stromal cells
 Stomach-Vascular endothelial cells
 Thymus-Antigen presenting cells
 Thymus-Stromal cells
 Thymus-Thymic epithelial cells
 Thymus-Thymocytes
 Thymus-Vascular endothelial cells
View table schema
Data last updated at UCSC: 2021-01-11 04:16:28

Description

This group of tracks shows data from A human cell atlas of fetal gene expression. This is a collection of single cell and single nucleus combinatorial indexing-based RNA-seq data covering 4 million cells from 15 organs obtained during mid-gestation. The cells were sequenced in a highly multiplexed fashion and then clustered with annotations as described in Cao et al., 2020.

The Fetal Cells subtrack contains the data organized by cell type, with RNA signals from all cells of a given type pooled and averaged into one bar for each cell type. The Fetal Lineage subtrack shows similar data, but with the cell types subdivided more finely and by organ. Additional bar chart subtracks pool the cell by other characteristics such as by sex (Fetal Sex), assay (FetalAssay), donor (Fetal Donor ID), experiment (Fetal Exp), organ (Fetal Organ), and reverse transcription group (Fetal RT Group).

Please see descartes.brotmanbaty.org for further interactive displays and additional data.

Display Conventions and Configuration

The cell types are colored by which class they belong to according to the following table. The coloring algorithm allows cells that show some blended characteristics to show blended colors so there will be some color variation within a class. The colors will be purest in the Fetal Cells subtrack, where the bars represent relatively pure cell types. They can give an overview of the cell composition within other categories in other subtracks as well.

Color Cell classification
neural
adipose
fibroblast
immune
muscle
hepatocyte
trophoblast
secretory
ciliated
epithelial
endothelial
glia

Methods

Three-level single-cell combinatorial indexing (sci-RNAseq3) as described in Cao et al., 2020 was used on 121 samples from 28 fetuses estimated 72 to 129 days post-conception. This included samples from 15 organs. and resulted in RNA profiles for 4 million cells. The samples were flash-frozen for majority of the experiments and then nuclei extracted for sequencing. Samples from tissues from the kidney and digestive system were fixed after disassociation to deactivate endogenous RNases and proteases.

The cell/gene matrix and cell-level metadata was downloaded from the UCSC Cell Browser. The UCSC command line utility matrixClusterColumns, matrixToBarChart, and bedToBigBed were used to transform these into a bar chart format bigBed file that can be visualized. The coloring was done by defining colors for the broad level cell classes and then using another UCSC utility, hcaColorCells, to interpolate the colors across all cell types. The UCSC utilities can be found on our download server.

Data Access

The raw bar chart data can be explored interactively with the Table Browser, or the Data Integrator. For automated analysis, the data may be queried from our REST API. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.

Credits

Thanks to the many authors who worked on producing and publishing this data set. The data were integrated into the UCSC Genome Browser by Jim Kent and Brittney Wick then reviewed by Jairo Navarro. The UCSC work was paid for by the Chan Zuckerberg Initiative.

References

Cao J, O'Day DR, Pliner HA, Kingsley PD, Deng M, Daza RM, Zager MA, Aldinger KA, Blecher-Gonen R, Zhang F et al. A human cell atlas of fetal gene expression. Science. 2020 Nov 13;370(6518). PMID: 33184181; PMC: PMC7780123

Cao J, Spielmann M, Qiu X, Huang X, Ibrahim DM, Hill AJ, Zhang F, Mundlos S, Christiansen L, Steemers FJ et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature. 2019 Feb;566(7745):496-502. PMID: 30787437; PMC: PMC6434952