By Felicia Kuperwaser & Itai Yanai

A large-scale, high-resolution cell atlas of gene expression and regulation in human embryos enables innovative investigation of development through multi‑organ and multi‑modal analysis.

Charles Darwin developed his theory of natural selection by comparing features between individuals and species. A comparative approach is also crucial to establish the cellular taxonomy that underlies human physiology. Technological advances in single-cell genomics have facilitated the production of numerous cell atlases that, through comparative analysis, define the full set of cells that constitute a system of interest — usually a whole organ1. Extending the scope of an atlas from organ to whole organism increases the power of this approach by capturing data across physiological systems. To this end, two papers in Science present the comprehensive molecular characterization of cell types across nearly all organs during human fetal development2,3. They reveal previously unidentified cell subtypes, and define cell-differentiation pathways through analysis of gene expression and chromatin (the DNA–protein complex into which a cell’s genetic material is packaged).

The work is a remarkable feat, both technically, in terms of the complexity of the paired data, and because of the scale of the studies, which involved analysis of 15 organs from human fetuses between 72 and 129 days after conception. In the first of the papers, Cao et al.2 generated gene-expression profiles (transcriptomes) from 4 million single cells across these organs. Analysis of these profiles revealed 77 main cell types, defined with reference to existing single-organ atlas data.

In the second of the papers, Domcke et al.3presented an improved method for assessing chromatin accessibility, an analysis that provides insight into how genes are regulated during development. Loosely packaged chromatin regions are thought to be more accessible to regulatory proteins such as transcription factors, and are often involved in regulating gene expression and in establishing and maintaining cell identity. The authors’ approach enabled the analysis of 800,000 cells from the same samples as those used by Cao and colleagues, which led to the identification of 54 of the same cell types.

The considerable data collected allowed both groups to define highly expressed ‘marker’ genes and corresponding transcription factors unique to each cell type. The authors also integrated their atlases with existing mouse atlas data4, making each a more robust and complete reference. Combining these data sets enables validation of how cell types are characterized in each species and will help researchers to better design experiments that use mouse models to investigate human physiology. Together, the papers constitute a substantial resource, which is openly available on an interactive website (

The authors developed an analytical framework that led to interesting biological insights, demonstrating the potential of this body of work for making discoveries. They defined previously uncharacterized cell subtypes by comparing expression and chromatin patterns across organs, and they used this multi-organ approach for cell-lineage analysis.

Domcke et al. compared cell-lineage diversity across organs and revealed that circulating blood cell subtypes are almost identical, irrespective of the organ from which they were isolated. Conversely, they found that endothelial cells (key components of blood vessel walls) are regulated by many tissue-specific factors and differ by organ. Therefore, in trying to understand functional relationships between these subtypes and other cells during development, tissue context might figure more prominently in endothelial cell variability than it does in other lineages. Cao et al. precisely annotated three subtypes of red blood cell (erythroid) progenitor, each representing a different stage of maturation, and measured their presence across organs. They identified early erythroid progenitors in the adrenal gland, a previously unknown site of erythroid development, which might bridge the developmental switch in the site of production of these cells from fetal liver to bone marrow.

Domcke and colleagues also used the paired data sets to assess the relationship between gene expression and its regulation. They identified previously unknown transcription factors specific to discrete developmental stages by analysing transcription-factor binding sites in accessible chromatin regions. Then, on the basis of the relationships between expression of cell-type-specific transcription factors and binding-site availability, they assigned putative functions to these transcription factors as activators or repressors (Fig. 1).

Figure 1

Figure 1 | Combined data types in a cell atlas for human development. A new cell atlas of human development combines data on gene expression2 and chromatin accessibility3 (chromatin is the DNA–protein complex in which DNA is packaged — ‘looser’ packaging makes DNA accessible to regulatory proteins such as transcription factors) in cells across 15 developing organs. The researchers combined these data to study the roles of transcription factors in human development, by cataloguing the expression of transcription factors of interest and the presence of their binding domains in accessible chromatin in each cell type. Transcription factors for which expression positively correlated with the presence of binding domains (such as TFα in this example) were assigned as transcriptional activators, whereas a negative correlation (as with TFβ) suggested a role as transcriptional repressors.

These studies represent the next generation of atlas papers. Currently, standard cell atlases characterize a single organ on a molecular level using one data modality. The new work provides a road map for unifying these disparate data sets.

A limitation of the work is that the current atlases correspond only to a specific developmental window, and not every organ is included. However, the atlas can be expanded with the integration of new data, and the growing resource will be an asset to biologists in standardizing cell types across development. Unidentified cells are typically characterized in relation to the other cell types of that organ, but these definitions might vary between data sets. Multi-organ analysis creates a consistent framework of characteristic cell types against which to compare new data. It can match unidentified cells with corresponding cell types in another organ on the basis of shared expression patterns or, conversely, it can highlight tissue-specific differences between previously grouped cells.

Standardization in the field will yield a more refined, uniform and valuable resource that will facilitate exploration of new questions. For example, it will help researchers to investigate how cells of a given lineage differ depending on tissue-intrinsic properties or dynamic lineage changes. Immune cell expression and function might differ, for instance, depending on the organs they target or on changes in their site of production.

Although the data presented capture healthy development, characterization of these tissues also has implications for the study of disease. For example, this resource will help to enhance our basic understanding of stem-cell differentiation by identifying key regulators of cell fate and development. This, in turn, will aid in the analysis of lineage dysregulation in developmental disorders. Its utility will also extend to investigating adult diseases characterized by changes in cell state and differentiation, such as cancer, degenerative disease and ageing. Ultimately, these comparisons, both to disordered development and to diseased adult tissue, might reveal targets for therapeutic intervention as well as fundamental principles of human physiology and development.


  1. 1.

    Aldridge, S. & Teichmann, S. A. Nature Commun. 11, 4307 (2020).

  2. 2.

    Cao, J. et al. Science 370, eaba7721 (2020).

  3. 3.

    Domcke, S. et al. Science 370, eaba7612 (2020).

  4. 4.

    Cao, J. et al. Nature 566, 496–502 (2019).

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