Research Article

Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics

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Science  25 May 2018:
Vol. 360, Issue 6391, eaaq1723
DOI: 10.1126/science.aaq1723

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Mapping the planarian transcriptome

A cell type's transcriptome defines the active genes that control its biology. Two groups used single-cell RNA sequencing to define the transcriptomes for essentially all cell types of a complete animal, the regenerative planarian Schmidtea mediterranea. Because pluripotent stem cells constantly differentiate to rejuvenate any part of the body of this species, all developmental lineages are active in adult animals. Fincher et al. determined the transcriptomes for most, if not all, planarian cell types, including some that were previously unknown. They also identified transition states and genes governing positional information. Plass et al. used single-cell transcriptomics and computational algorithms to reconstruct a lineage tree capturing the developmental progressions from stem to differentiated cells. They could then predict gene programs that are specifically turned on and off along the tree, and they used this approach to study how the cell types behaved during regeneration. These whole-animal transcriptome “atlases” are a powerful way to study metazoan biology.

Science, this issue p. eaaq1736, p. eaaq1723

Structured Abstract


Understanding the differentiation of stem cells into the vast amount of cell types that form the human body is a central problem of basic and medical science. The recent advances in single-cell sequencing techniques now make it possible to capture the transcriptomes of thousands of cells in a fast and cost-effective manner, opening a new way to study the cell composition of organs, tissues, and developmental stages. Yet, single-cell transcriptomics per se just provides a snapshot of cellular dynamics and transient cell populations. Computational algorithms have emerged that infer a pseudotemporal ordering of cells based on comparison of their transcriptomic profiles, allowing new insights into stem cell biology and tissue differentiation. However, these algorithms were designed for relatively simple scenarios, such as the differentiation of cells belonging to a specific lineage or the lineage relationships among cells from a particular tissue, and cannot evaluate all possible cellular differentiation trajectories in complex animals. To this end, we use single-cell transcriptomic approaches to improve our molecular understanding of how stem cells differentiate into the set of cell types that make an entire complex adult animal.


Freshwater planarians such as Schmidtea mediterranea offer a unique opportunity to approach this question. These animals are immortal and constantly renew and regenerate all tissues owing to the presence of a large pool of pluripotent stem cells that continuously differentiate into all mature cell types. Therefore, we reasoned that an unbiased single-cell transcriptomic approach should allow us to capture not only terminally differentiated cell types but also intermediate cellular states, possibly enabling cell lineage reconstruction of the whole animal from transcriptomic data.


We performed massively parallel single-cell transcriptomics profiling of thousands of cells from adult planarians. At the molecular level, we identified and characterized dozens of cell types, including stem cells, progenitors, and terminally differentiated cells. We then applied a new computational algorithm, partition-based graph abstraction (PAGA), which can predict a lineage tree for the whole animal in an unbiased way. By combining the predictions from PAGA with several independent lines of evidence, including single-cell transcriptome data from purified stem cells and stem cell–depleted animals, analysis of gene expression dynamics, and a method called velocyto that predicts future gene expression from mRNA metabolism, we produced a consolidated lineage tree that included all identified cell types rooted to a single stem cell group. We used this information to identify gene sets co-regulated during the differentiation of many specific cell types. To show the power of our approach, we applied single-cell transcriptomics to regenerating planarians and characterized how each cell type in the adult planarian body dynamically responds to regenerative body remodeling at the transcriptomic and cellular levels. Our results highlight that some cell types that had been previously overlooked in molecular studies quickly decrease their abundance, indicating that they may serve as an energy reservoir that fuels the regeneration process.


We have shown that it is possible to use single-cell transcriptomics to (i) build a cell atlas of an adult animal, (ii) reconstruct the lineage relationships of its cells in an unbiased way, and (iii) identify gene sets which likely contain genes that are involved in programming the lineage tree. Moreover, we demonstrated how single-cell transcriptomics can be used to study complex and dynamic cellular processes such as regeneration. Notably, our approach is applicable to other model and non–model organisms, assuming that their differentiation processes are sampled with sufficient time resolution. To foster future studies, we provide a detailed tutorial on the application of our approach, and we make our data available through an interactive web interface. This study opens the door to powerful approaches for understanding molecular mechanisms of development and regeneration in animals.

A lineage tree for complex animals from single-cell transcriptomics.

Planarians are multicellular organisms. They contain adult pluripotent stem cells that continuously renew all tissues and differentiate into all adult cell types. Using single-cell transcriptomics, we characterized all major mature cell types and many intermediate cellular states. We then derived a lineage tree describing planarian stem cell differentiation into all mature cell types of the animal.


Flatworms of the species Schmidtea mediterranea are immortal—adult animals contain a large pool of pluripotent stem cells that continuously differentiate into all adult cell types. Therefore, single-cell transcriptome profiling of adult animals should reveal mature and progenitor cells. By combining perturbation experiments, gene expression analysis, a computational method that predicts future cell states from transcriptional changes, and a lineage reconstruction method, we placed all major cell types onto a single lineage tree that connects all cells to a single stem cell compartment. We characterized gene expression changes during differentiation and discovered cell types important for regeneration. Our results demonstrate the importance of single-cell transcriptome analysis for mapping and reconstructing fundamental processes of developmental and regenerative biology at high resolution.

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