Description

This track displays data from A reference single-cell transcriptomic atlas of human skeletal muscle tissue reveals bifurcated muscle stem cell populations. Muscle tissue was analyzed using single-cell RNA-sequencing (scRNA-seq) and subsequent clustering distinguished 16 muscle-resident cell types based on their identified marker genes found in De Micheli et al., 2020. Muscle samples were from surgically discarded tissue taken from a wide variety of anatomical sites.

This track collection contains two bar chart tracks of RNA expression in the human muscle where cells are grouped by cell type (Muscle Cells) or biosample (Muscle Sample). The default track displayed is Muscle 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 Muscle 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. Note that the Muscle Sample subtrack is colored based on colors provided from Figure 1 from De Micheli et al., 2020.

Relevant Figures From De Micheli et al. 2020

Details on sex, age, anatomical site, and single-cell transcriptomes after quality control (QC) filtering from 10 donors. Colors represent areas from which samples were taken from.

De Micheli et al. Skelet Muscle. 2020. / CC BY 4.0

Cell type proportions across the 10 donors and grouped by leg (donors 02, 07, 08), trunk (donors 01, 05, 06, 09, 10), and face (donors 03, 04).

De Micheli et al. Skelet Muscle. 2020. / CC BY 4.0

Method

Muscle samples were taken from 10 healthy donors of ages ranging from 41-81 years old from different sections of the face (F), trunk (T), and leg (L). Excessive fat and connective tissue were removed from the muscle samples prior to enzymatic dissociation. Next, libraries were prepared using the 10x Genomics 3' v2 or v3 library kit and sequenced on the Illumina NextSeq 500. This resulted in libraries with 200-250 million reads which were processed using Cell Ranger version 3.1. In total, over 22,000 RNA transcriptomic profiles were generated from all of the samples after quality control filtering. The single cell transcriptomes from all 10 datasets were integrated using a scRNA-seq integration method called Scanorama as described in the reference below.

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 Andrea De Micheli of the Cosgrove Laboratory at Cornell University 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 Luis Nassar. The UCSC work was paid for by the Chan Zuckerberg Initiative.

References

De Micheli AJ, Spector JA, Elemento O, Cosgrove BD. A reference single-cell transcriptomic atlas of human skeletal muscle tissue reveals bifurcated muscle stem cell populations. Skelet Muscle. 2020 Jul 6;10(1):19. PMID: 32624006; PMC: PMC7336639