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Single-Cell RNA-Seq Study Leads to Cell Type Map of All Major Human Organs

NEW YORK – In a new study published in Nature on Wednesday, researchers in China described the cell type composition of all major human organs, based on the RNA sequences of more than 500,000 single cells from Chinese Han donors.

Using single-cell mRNA sequencing, the researchers revealed a hierarchy for many tissues that have not been well characterized until now. They established what they called a single-cell human cell landscape (HCL) analysis pipeline to help identity cells and performed a single-cell comparative analysis of landscapes for both humans and mouse to reveal conserved genetic networks.

"We found that stem and progenitor cells exhibit strong transcriptomic stochasticity, while the differentiated cells are more distinct," the authors wrote. "Our study provides a valuable resource for human biology."

In previous studies, these researchers had reported a method called Microwell-seq — a cost-effective single-cell mRNA sequencing technology that offers advantages in doublet rate and cell-type compatibility. Sequencing titration experiments and cross-platform comparisons suggested that this method could robustly detect rare populations even at low sequencing depth, so they planned to use Microwell-seq for this study to create a basic landscape of major human cell types using sample donations from a Chinese Han population.

The investigators' analyses included both fetal and adult samples and covered a total of 60 human tissue types. They also analyzed seven types of cell cultures, including induced pluripotent stem cells, embryoid body cells, hematopoietic cells derived from H9/OP9 co-cultures, and pancreatic beta cells. Altogether, 702,968 single cells passed their quality control measures. The complete human tissue dataset was grouped into 102 major clusters, sub-clustered into 843 cell types.

"Through correlation analysis between bulk and single-cell mRNA sequencing as well as cell number sub-sampling analysis, we estimated a high gene and cell-type coverage of HCL," the authors wrote. "These data encompass the most comprehensive cell-type repertoire yet described for the human species."

To allow for public access to the resource, the researchers created an HCL website.

One highlight, they noted, was that master transcription factors work in discrete modules to specify major human cell types such as neurons, erythroid cells, and acinar cells. They also uncovered previously unrecognized cell heterogeneity in a wide range of human tissues, found novel types of S-shaped body cells in the fetal kidney, and discovered a new cell type in the adult kidney.

The researchers also aimed to study human organ development by assessing the similarity of cell types between fetal- and adult-stage tissues. In the kidney and lung, they found that gene expression patterns of epithelial, mesenchymal, endothelial, and immune cells were correlated between the two stages, and that tissue-resident immune and stromal cells appeared early during organogenesis. They then performed a trajectory analysis for fetal and adult HCL data and developed a landscape showing projections from fetal progenitors toward adult mature cell types.

Finally, the investigators used the HCL database to build a single-cell mapping pipeline named scHCL for the classification of human cell types. They integrated their HCL with other published human datasets and made transcriptome references for all available human cell-type clusters from single-cell studies.

"By mapping bulk RNA sequencing data to our HCL reference, we can robustly define cell lineages of cultured cell population or cancer cell organoids," the authors wrote.