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The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution

Mapping the vertebrate developmental landscape As embryos develop, numerous cell types with distinct functions and morphologies arise from pluripotent cells. Three research groups have used single-cell RNA sequencing to analyze the transcriptional changes accompanying development of vertebrate embryos (see the Perspective by Harland). Wagner et al. sequenced the transcriptomes of more than 90,000 cells throughout zebrafish development to reveal how cells differentiate during axis patterning, germ layer formation, and early organogenesis. Farrell et al. profiled the transcriptomes of tens of thousands of embryonic cells and applied a computational approach to construct a branching tree describing the transcriptional trajectories that lead to 25 distinct zebrafish cell types. The branching tree revealed how cells change their gene expression as they become more and more specialized. Briggs et al. examined whole frog embryos, spanning zygotic genome activation through early organogenesis, to map cell states and differentiation across all cell lineages over time. These data and approaches pave the way for the comprehensive reconstruction of transcriptional trajectories during development. Science, this issue p. 981, p. eaar3131, p. eaar5780; see also p. 967 A single-cell transcriptome analysis of whole frog embryos reveals cell states and provides a map of differentiation over time. INTRODUCTION Metazoan development represents a big jump in complexity compared with unicellular life in two aspects: cell-type differentiation and cell spatial organization. In vertebrate embryos, many distinct cell types appear within just a single day of life after fertilization. Studying the developmental dynamics of all embryonic cell types is complicated by factors such as the speed of early development, complex cellular spatial organization, and scarcity of raw material for conventional analysis. Genetics and experimental embryology have clarified major transcription factors and secreted signaling molecules involved in the specification of early lineages. However, development involves parallel alterations in many cellular circuits, not just a few well-described factors. RATIONALE We recently developed a microfluidics-based single-cell RNA sequencing method capable of efficiently profiling tens of thousands of individual transcriptomes. Building on earlier studies that showed how single-cell transcriptomics can reveal cell states within complex tissues, we reasoned that a series of such measurements from embryos, if collected with sufficient time resolution, could allow reconstruction of developmental cell-state hierarchies. We focused on the western claw-toed frog, Xenopus tropicalis, which serves as one of the best-studied model systems of early vertebrate development. We profiled these embryos from just before the onset of zygotic transcription up to a point at which dozens of distinct cell types have formed encompassing progenitors of most major organs. To establish aspects of development general to vertebrates, we additionally incorporated data from the copublished paper by Wagner et al. on zebrafish embryos, which separated from frogs about 400 million years ago. RESULTS We profiled 136,966 single-cell transcriptomes over the first day of life of Xenopus tropicalis. Our analysis classifies 259 gene expression clusters across 10 time points, which belong to 69 annotated embryonic cell types and capture further substructure. Using a computational approach to link cell states between time points, a resulting cell-state graph agrees well with previous lineage-tracing studies and shows that developmental fate choices can be well approximated by a treelike model. Many cell states are detected considerably earlier than previously understood, thus revealing the earliest events in their differentiation. The data lends clarity to numerous specific developmental processes, such as the developmental origin of the vertebrate neural crest. Through an evolutionary comparison with zebrafish, we identified diverging features of developmental dynamics, including many genes showing cell-type specificity in one organism but not in another. Yet, we also identified conserved patterns in the reuse of transcription factors across lineages and in multilineage priming at fate branch points. The resulting resource is available in an interactive online browser that allows in silico exploration of any gene in any cell state (tinyurl.com/scXen2018). CONCLUSION The approaches and results presented here, along with the copublished paper by Wagner et al., establish the first steps toward a data-driven dissection of developmental dynamics at the scale of entire organisms. They provide a useful, annotated resource for developmental biologists, comprehensively tracking differentiation programs as they unfold on a high-dimensional gene expression landscape. Although demonstrated on model organisms, the same approaches could be transformative to the study of nonmodel organisms by allowing rapid and quantitative description of differentiation processes across the tree of life, opening up a new front in evolutionary biology. Single-cell analysis of whole developing vertebrate embryos. Xenopus embryos at 10 time points over the first day of life were dissociated, barcoded, and sequenced, yielding 136,966 single-cell transcriptomes. These data were clustered and connected over time to reveal a complete view of transcriptional changes in each embryonic lineage and clarify numerous features of early development. hpf, hours postfertilization. Time series of single-cell transcriptome measurements can reveal dynamic features of cell differentiation pathways. From measurements of whole frog embryos spanning zygotic genome activation through early organogenesis, we derived a detailed catalog of cell states in vertebrate development and a map of differentiation across all lineages over time. The inferred map recapitulates most if not all developmental relationships and associates new regulators and marker genes with each cell state. We find that many embryonic cell states appear earlier than previously appreciated. We also assess conflicting models of neural crest development. Incorporating a matched time series of zebrafish development from a companion paper, we reveal conserved and divergent features of vertebrate early developmental gene expression programs.