Description

This track displays data from Cells of the adult human heart. Single-cell and single-nucleus RNA sequencing (RNA-seq) was used to profile transcriptomes from six regions of the heart: the interventricular septum (SP), apex (AX), left ventricle (LV), right ventricle (RV), left atrium (LA), and right atrium (RA). A total of 11 cardiac cell types were identified along with their marker genes after uniform manifold approximation and projection (UMAP) embedding of 487,106 cells. Note that the RNA-seq data is generated using Tag-sequencing (Tag-seq) and does not cover all exons.

This track collection contains nine bar chart tracks of RNA expression in the human heart where cells are grouped by cell type (Heart HCA Cells), age (Heart HCA Age), donor (Heart HCA Donor), region of the heart (Heart HCA Region), sample (Heart HCA Sample), sex (Heart HCA Sex), source (Heart HCA Source), cell state (Heart HCA State), and 10x chemistry version (Heart HCA Version). The default track displayed is Heart HCA Cells.

Display Conventions

The cell types are colored by which class they belong to according to the following table.

Cells that fall into multiple classes will be colored by blending the colors associated with those classes. The colors will be purest in the Heart HCA 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.

Method

Healthy heart tissues were obtained from 14 UK and North American transplant organ donors ages 40-75. Tissues were taken from deceased donors after circulatory death (DCD) and after brain death (DBD). To minimize transcriptional degradation, heart tissues were stored and transported on ice until freezing or tissue dissociation. Single nuclei were isolated from flash-frozen tissue using mechanical homogenization with a glass Dounce tissue grinder. Fresh heart tissues were enzymatically dissociated and automatically digested using gentleMACS Octo Dissociator. Next, Hoechst-positive single nuclei were FACS sorted prior to library preparation. In parallel, Cell suspensions from fresh heart tissue were enriched for CD45+ cells using MACS LS columns. Libraries of single cell and single nuclei were prepared using 10x Genomics 3' v2 or v3. 3' gene expression libraries were sequenced on an Illumina HiSeq4000 and NextSeq500. In total 45,870 cells, 78,023 CD45+ enriched cells, and 363,213 nuclei were profiled for 11 major cell types of the heart.

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.

Credit

Thanks to Monika Litviňuková, Carlos Talavera-Ló, and 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 Gerardo Perez. The UCSC work was paid for by the Chan Zuckerberg Initiative.

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.

References

Litviňuková M, Talavera-López C, Maatz H, Reichart D, Worth CL, Lindberg EL, Kanda M, Polanski K, Heinig M, Lee M et al. Cells of the adult human heart. Nature. 2020 Dec;588(7838):466-472. PMID: 32971526; PMC: PMC7681775