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Spatial transcriptomics, with other spatial technologies, has enabled scientists to dissect the organization and interaction of different cell types within the tumor microenvironment. We asked experts to discuss some aspects of this technology from revealing the tumor microenvironment and heterogeneity, to tracking tumor evolution, to guiding tumor therapy, to current technical challenges., Competing Interests: Declaration of interests A.C.A. is a member of the SAB for Tizona Therapeutics, Trishula Therapeutics, Compass Therapeutics, Zumutor Biologics, Excepgen, and ImmuneOncia, which have interests in cancer immunotherapy. A.C.A. is also a paid consultant for iTeos Therapeutics and Larkspur Biosciences. A.C.A.’s interests were reviewed and managed by the Brigham and Women’s Hospital and Partners Healthcare in accordance with their conflict of interest policies. A.S. is a conjoint Associate Professor at UNSW Sydney. A.S. receives research support from Nanostring Technologies, 10X Genomics and Curio Biosciences. P.S. is a co-founder and member of the BOD of Glencoe Software, a member of the BOD for Applied Biomath, and a member of the SAB for RareCyte, NanoString and Montai Health; P.S. holds equity in Glencoe, Applied Biomath and RareCyte. P.K.S. is a consultant for Merck and the Sorger lab has received research funding from Novartis and Merck in the past five years. B.I. has received honoraria from consulting with Merck, Janssen Pharmaceuticals, AstraZeneca and Volastra Therapeutics. Other authors declare no competing interests., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Complex dynamic processes such as development involve the deployment of gene regulatory pathways that transform the spatial arrangement of cells. Disentangling these genetic programs is at the core of many biological problems. Stereo-seq is a promising spatial transcriptomics method, as demonstrated by three papers in this issue of Developmental Cell, each in a distinct biological context., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 Elsevier Inc. All rights reserved.)

During tumor progression, cancer cells come into contact with various non-tumor cell types, but it is unclear how tumors adapt to these new environments. Here, we integrate spatially resolved transcriptomics, single-cell RNA-seq, and single-nucleus RNA-seq to characterize tumor-microenvironment interactions at the tumor boundary. Using a zebrafish model of melanoma, we identify a distinct "interface" cell state where the tumor contacts neighboring tissues. This interface is composed of specialized tumor and microenvironment cells that upregulate a common set of cilia genes, and cilia proteins are enriched only where the tumor contacts the microenvironment. Cilia gene expression is regulated by ETS-family transcription factors, which normally act to suppress cilia genes outside of the interface. A cilia-enriched interface is conserved in human patient samples, suggesting it is a conserved feature of human melanoma. Our results demonstrate the power of spatially resolved transcriptomics in uncovering mechanisms that allow tumors to adapt to new environments., (© 2021. The Author(s).)

Deciphering the principles and mechanisms by which gene activity orchestrates complex cellular arrangements in multicellular organisms has far-reaching implications for research in the life sciences. Recent technological advances in next-generation sequencing- and imaging-based approaches have established the power of spatial transcriptomics to measure expression levels of all or most genes systematically throughout tissue space, and have been adopted to generate biological insights in neuroscience, development and plant biology as well as to investigate a range of disease contexts, including cancer. Similar to datasets made possible by genomic sequencing and population health surveys, the large-scale atlases generated by this technology lend themselves to exploratory data analysis for hypothesis generation. Here we review spatial transcriptomic technologies and describe the repertoire of operations available for paths of analysis of the resulting data. Spatial transcriptomics can also be deployed for hypothesis testing using experimental designs that compare time points or conditions-including genetic or environmental perturbations. Finally, spatial transcriptomic data are naturally amenable to integration with other data modalities, providing an expandable framework for insight into tissue organization., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

The evolution of development has been studied through the lens of gene regulation by examining either closely related species or extremely distant animals of different phyla. In nematodes, detailed cell- and stage-specific expression analyses are focused on the model Caenorhabditis elegans , in part leading to the view that the developmental expression of gene cascades in this species is archetypic for the phylum. Here, we compared two species of an intermediate evolutionary distance: the nematodes C. elegans (clade V) and Acrobeloides nanus (clade IV). To examine A. nanus molecularly, we sequenced its genome and identified the expression profiles of all genes throughout embryogenesis. In comparison with C. elegans , A. nanus exhibits a much slower embryonic development and has a capacity for regulative compensation of missing early cells. We detected conserved stages between these species at the transcriptome level, as well as a prominent middevelopmental transition, at which point the two species converge in terms of their gene expression. Interestingly, we found that genes originating at the dawn of the Ecdysozoa supergroup show the least expression divergence between these two species. This led us to detect a correlation between the time of expression of a gene and its phylogenetic age: evolutionarily ancient and young genes are enriched for expression in early and late embryogenesis, respectively, whereas Ecdysozoa-specific genes are enriched for expression during the middevelopmental transition. Our results characterize the developmental constraints operating on each individual embryo in terms of developmental stages and genetic evolutionary history., Competing Interests: The authors declare no conflict of interest.

Although the function of the mammalian pancreas hinges on complex interactions of distinct cell types, gene expression profiles have primarily been described with bulk mixtures. Here we implemented a droplet-based, single-cell RNA-seq method to determine the transcriptomes of over 12,000 individual pancreatic cells from four human donors and two mouse strains. Cells could be divided into 15 clusters that matched previously characterized cell types: all endocrine cell types, including rare epsilon-cells; exocrine cell types; vascular cells; Schwann cells; quiescent and activated stellate cells; and four types of immune cells. We detected subpopulations of ductal cells with distinct expression profiles and validated their existence with immuno-histochemistry stains. Moreover, among human beta- cells, we detected heterogeneity in the regulation of genes relating to functional maturation and levels of ER stress. Finally, we deconvolved bulk gene expression samples using the single-cell data to detect disease-associated differential expression. Our dataset provides a resource for the discovery of novel cell type-specific transcription factors, signaling receptors, and medically relevant genes., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The concept of germ layers has been one of the foremost organizing principles in developmental biology, classification, systematics and evolution for 150 years (refs 1 - 3). Of the three germ layers, the mesoderm is found in bilaterian animals but is absent in species in the phyla Cnidaria and Ctenophora, which has been taken as evidence that the mesoderm was the final germ layer to evolve. The origin of the ectoderm and endoderm germ layers, however, remains unclear, with models supporting the antecedence of each as well as a simultaneous origin. Here we determine the temporal and spatial components of gene expression spanning embryonic development for all Caenorhabditis elegans genes and use it to determine the evolutionary ages of the germ layers. The gene expression program of the mesoderm is induced after those of the ectoderm and endoderm, thus making it the last germ layer both to evolve and to develop. Strikingly, the C. elegans endoderm and ectoderm expression programs do not co-induce; rather the endoderm activates earlier, and this is also observed in the expression of endoderm orthologues during the embryology of the frog Xenopus tropicalis, the sea anemone Nematostella vectensis and the sponge Amphimedon queenslandica. Querying the phylogenetic ages of specifically expressed genes reveals that the endoderm comprises older genes. Taken together, we propose that the endoderm program dates back to the origin of multicellularity, whereas the ectoderm originated as a secondary germ layer freed from ancestral feeding functions.

New methods employ RNA-seq to study single cells within complex tissues by in situ sequencing or mRNA capture from single photoactivated cells.

RNA-Seq enables the efficient transcriptome sequencing of many samples from small amounts of material, but the analysis of these data remains challenging. In particular, in developmental studies, RNA-Seq is challenged by the morphological staging of samples, such as embryos, since these often lack clear markers at any particular stage. In such cases, the automatic identification of the stage of a sample would enable previously infeasible experimental designs. Here we present the 'basic linear index determination of transcriptomes' (BLIND) method for ordering samples comprising different developmental stages. The method is an implementation of a traveling salesman algorithm to order the transcriptomes according to their inter-relationships as defined by principal components analysis. To establish the direction of the ordered samples, we show that an appropriate indicator is the entropy of transcriptomic gene expression levels, which increases over developmental time. Using BLIND, we correctly recover the annotated order of previously published embryonic transcriptomic timecourses for frog, mosquito, fly and zebrafish. We further demonstrate the efficacy of BLIND by collecting 59 embryos of the sponge Amphimedon queenslandica and ordering their transcriptomes according to developmental stage. BLIND is thus useful in establishing the temporal order of samples within large datasets and is of particular relevance to the study of organisms with asynchronous development and when morphological staging is difficult.

A fundamental question in developmental biology relates to the connection between morphological stages and their underlying molecular activity. Here we demonstrate that, at the molecular level, embryonic development in five Caenorhabditis species proceeds through two distinct milestones in which the transcriptome is resistant to differences in species-specific developmental timings. By comparing the complete protein-coding transcriptomes of individually timed embryos across ten morphological markers, we found that developmental milestones can be characterized by their expression dynamics and activation of key developmental regulators. This approach led us to discover the nematode phylotypic stage and to show that in chordates and arthropods it is represented as two distinct stages, suggesting that animal body plans might evolve by uncoupling and elaboration on formerly synchronous processes., (Copyright © 2012 Elsevier Inc. All rights reserved.)