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 Single-cell RNA sequencing identifies the transcriptomes for most to all cell types of a flatworm. INTRODUCTION The complete sequence of animal genomes has had a transformative impact on biological research. Whereas the genome sequence of an organism contains the information for its development and physiology, the transcriptomes (the sets of actively transcribed genes) of the cell types in an organism define how the genome is used for the unique functions of its cells. Cell number and complexity have historically made the identification of all cell types, much less their transcriptomes, an extreme challenge for most multicellular organisms. Recent advances in single-cell RNA sequencing (SCS) have greatly enhanced the ability to determine cell type transcriptomes, with SCS of thousands of cells readily achievable. RATIONALE We reasoned that it might be possible, given these advances, to determine the transcriptomes of essentially every cell type of a complete organism possessing an unknown number of cell types. The planarian Schmidtea mediterranea, famous for its regeneration ability, is an attractive case study for such an undertaking. Planarians possess a complex anatomy with diverse differentiated cell types, including many found across animals. Furthermore, planarians contain a proliferating cell population called neoblasts that includes pluripotent stem cells. Neoblasts mediate regeneration and constitutive tissue turnover. Consequently, lineage precursors for essentially all differentiated cells types are also present in adults. Finally, planarians constitutively express positional information guiding tissue turnover. Therefore, comprehensive SCS at a single time point (the adult) could allow transcriptome determination for all differentiated cell types and for lineage precursors, and could identify patterning information that guides new cell production and organization. Capturing this information in most organisms would require sampling adults and many transient embryonic stages. RESULTS We used the SCS method Drop-seq to determine the transcriptomes for 66,783 individual cells from adult planarians. We locally saturated cell type coverage by iteratively sequencing distinct body regions and assessing the frequency of known rare cell types in the data. Clustering the cells by shared gene expression grouped cells into broad tissue classes. Subclustering of each broad tissue type in isolation enabled separation of cells into the cell populations constituting each tissue. These analyses enabled the identification of a previously unidentified tissue group and the classification of poorly characterized tissues into their constituent cell types, including numerous previously unknown cell types. Transcriptomes were identified for many rare cell types, including those that exist as rarely as ~10 cells in an animal that has 105 to 106 cells, which suggests that near-to-complete cellular saturation was reached. In addition, transcriptomes for known and novel lineage precursors, from pluripotent stem cell to differentiated cell types, were generated. Precursor transcriptomes identified transcription factors required for maintenance of associated differentiated cells during homeostatic cell turnover. Finally, the data were used to identify genes regionally expressed in muscle, which is the site of planarian patterning gene expression. CONCLUSION We successfully used SCS to generate transcriptomes for most to all cells of a complete organism. This resource provides a wealth of data regarding the cellular site of expression of thousands of conserved genes and the transcriptomes for cell types widely used in animals. These data will inform studies of these genes and cell types broadly, and will provide a resource for the fields of planarian biology and comparative evolutionary biology. This work also provides a template for the generation of cell type transcriptome atlases, which can be applied to a large array of organisms. An atlas of planarian cell type transcriptomes. High-throughput single-cell RNA sequencing of adult planarians reveals a cell type transcriptome atlas that includes rare cell types and many novel cell populations, cellular transition states, and patterning information, as demonstrated by two regionally expressed genes in muscle. The transcriptome of a cell dictates its unique cell type biology. We used single-cell RNA sequencing to determine the transcriptomes for essentially every cell type of a complete animal: the regenerative planarian Schmidtea mediterranea. Planarians contain a diverse array of cell types, possess lineage progenitors for differentiated cells (including pluripotent stem cells), and constitutively express positional information, making them ideal for this undertaking. We generated data for 66,783 cells, defining transcriptomes for known and many previously unknown planarian cell types and for putative transition states between stem and differentiated cells. We also uncovered regionally expressed genes in muscle, which harbors positional information. Identifying the transcriptomes for potentially all cell types for many organisms should be readily attainable and represents a powerful approach to metazoan biology.

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地中海涡虫的细胞类型转录组图谱

绘制涡虫转录组图 细胞类型的转录组定义了控制其生物学的活性基因。两组使用单细胞 RNA 测序来定义完整动物（再生涡虫 Schmidtea mediterranea）的基本上所有细胞类型的转录组。由于多能干细胞不断分化以使该物种身体的任何部位恢复活力，因此所有发育谱系在成年动物中都很活跃。芬奇等人。确定了大多数（如果不是全部）涡虫细胞类型的转录组，包括一些以前未知的。他们还确定了控制位置信息的过渡状态和基因。普拉斯等人。使用单细胞转录组学和计算算法重建谱系树，捕获从干细胞到分化细胞的发育进程。然后，他们可以预测沿树具体打开和关闭的基因程序，并使用这种方法来研究细胞类型在再生过程中的行为。这些全动物转录组“图谱”是研究后生动物生物学的有力方法。科学，这个问题 p。eaaq1736, p. eaaq1723 单细胞 RNA 测序鉴定了扁虫的大多数到所有细胞类型的转录组。引言 动物基因组的完整序列对生物学研究产生了变革性的影响。生物体的基因组序列包含其发育和生理学的信息，而生物体中细胞类型的转录组（活性转录的基因组）定义了基因组如何用于其细胞的独特功能。细胞数量和复杂性历来使识别所有细胞类型，更不用说它们的转录组，这对大多数多细胞生物来说是一个极端的挑战。单细胞 RNA 测序 (SCS) 的最新进展大大增强了确定细胞类型转录组的能力，可以轻松实现数千个细胞的 SCS。基本原理我们推断，鉴于这些进展，确定具有未知数量细胞类型的完整生物体的基本上每种细胞类型的转录组是可能的。以再生能力着称的地中海涡虫 Schmidtea 是此类项目的一个有吸引力的案例研究。涡虫拥有复杂的解剖结构，具有不同的分化细胞类型，包括许多在动物中发现的细胞。此外，涡虫含有称为新生细胞的增殖细胞群，其中包括多能干细胞。新生细胞介导再生和组成性组织更新。因此，基本上所有分化细胞​​类型的谱系前体也存在于成人中。最后，涡虫组成性地表达指导组织更新的位置信息。因此，单个时间点（成体）的综合 SCS 可以确定所有分化细胞​​类型和谱系前体的转录组，并可以识别指导新细胞生产和组织的模式信息。在大多数生物体中捕获这些信息需要对成体和许多短暂的胚胎阶段进行采样。结果我们使用 SCS 方法 Drop-seq 来确定 66 个的转录组，来自成年涡虫的 783 个单个细胞。我们通过对不同的身体区域进行迭代排序并评估数据中已知稀有细胞类型的频率来局部饱和细胞类型覆盖率。通过共享基因表达对细胞进行聚类，将细胞分为广泛的组织类别。每种广泛组织类型的分离亚簇能够将细胞分离成构成每种组织的细胞群。这些分析能够识别以前未识别的组织组，并将特征较差的组织分类为其组成细胞类型，包括许多以前未知的细胞类型。许多稀有细胞类型的转录组被鉴定出来，包括那些在具有 105 到 106 个细胞的动物中很少存在约 10 个细胞的那些，这表明已达到接近完全的细胞饱和。此外，还生成了从多能干细胞到分化细胞类型的已知和新谱系前体的转录组。前体转录组鉴定了在稳态细胞更新期间维持相关分化细胞所需的转录因子。最后，这些数据用于识别肌肉中区域表达的基因，肌肉是涡虫模式基因表达的部位。结论我们成功地使用 SCS 为完整生物体的大多数细胞到所有细胞生成转录组。该资源提供了大量关于数千种保守基因表达的细胞位点和广泛用于动物的细胞类型的转录组的数据。这些数据将为这些基因和细胞类型的研究提供广泛的信息，并将为涡虫生物学和比较进化生物学领域提供资源。这项工作还为生成细胞类型转录组图谱提供了模板，可应用于大量生物体。涡虫细胞类型转录组图谱。成年涡虫的高通量单细胞 RNA 测序揭示了一个细胞类型转录组图谱，其中包括稀有细胞类型和许多新细胞群、细胞过渡状态和模式信息，正如肌肉中两个区域表达的基因所证明的那样。细胞的转录组决定了其独特的细胞类型生物学。我们使用单细胞 RNA 测序来确定完整动物的基本上每种细胞类型的转录组：再生涡虫 Schmidtea mediterranea。涡虫包含多种细胞类型，拥有分化细胞​​（包括多能干细胞）的谱系祖细胞，并且组成性表达位置信息，使它们成为这项工作的理想选择。我们为 66,783 个细胞生成了数据，定义了已知和许多以前未知的涡虫细胞类型的转录组，以及干细胞和分化细胞之间的假定过渡状态。我们还在肌肉中发现了区域表达的基因，其中包含位置信息。识别许多生物体的潜在所有细胞类型的转录组应该很容易实现，并且代表了一种强大的后生动物生物学方法。使它们成为这项事业的理想选择。我们为 66,783 个细胞生成了数据，定义了已知和许多以前未知的涡虫细胞类型的转录组，以及干细胞和分化细胞之间的假定过渡状态。我们还在肌肉中发现了区域表达的基因，其中包含位置信息。识别许多生物体的潜在所有细胞类型的转录组应该很容易实现，并且代表了一种强大的后生动物生物学方法。使它们成为这项事业的理想选择。我们为 66,783 个细胞生成了数据，定义了已知和许多以前未知的涡虫细胞类型的转录组，以及干细胞和分化细胞之间的假定过渡状态。我们还在肌肉中发现了区域表达的基因，其中包含位置信息。识别许多生物体的潜在所有细胞类型的转录组应该很容易实现，并且代表了一种强大的后生动物生物学方法。