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Recent advances in multiplexed single‐cell transcriptomics experiments facilitate the high‐throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible. Therefore, computational methods are needed to predict, interpret, and prioritize perturbations. Here, we present the compositional perturbation autoencoder (CPA), which combines the interpretability of linear models with the flexibility of deep‐learning approaches for single‐cell response modeling. CPA learns to in silico predict transcriptional perturbation response at the single‐cell level for unseen dosages, cell types, time points, and species. Using newly generated single‐cell drug combination data, we validate that CPA can predict unseen drug combinations while outperforming baseline models. Additionally, the architecture's modularity enables incorporating the chemical representation of the drugs, allowing the prediction of cellular response to completely unseen drugs. Furthermore, CPA is also applicable to genetic combinatorial screens. We demonstrate this by imputing in silico 5,329 missing combinations (97.6% of all possibilities) in a single‐cell Perturb‐seq experiment with diverse genetic interactions. We envision CPA will facilitate efficient experimental design and hypothesis generation by enabling in silico response prediction at the single‐cell level and thus accelerate therapeutic applications using single‐cell technologies. Synopsis The compositional perturbation autoencoder (CPA) is a deep learning model for predicting the transcriptomic responses of single cells to single or combinatorial treatments from drugs and genetic manipulations. CPA can be trained on highly multiplexed, single‐cell experiments with thousands of conditions to predict unmeasured phenotypes (e.g., specific dose responses). It can generalize to predict responses to small molecules never seen in the training by adding priors on chemical space. Validations using a newly generated combinatorial drug perturbation dataset demonstrate the accuracy of CPA in predicting unseen drug combinations. CPA is also applicable to genetic combinatorial screens, as shown by imputing in silico 5,329 missing combinations in a single‐cell perturb‐seq experiment with diverse genetic interactions. Graphical Abstract The compositional perturbation autoencoder (CPA) is a deep learning model for predicting the transcriptomic responses of single cells to single or combinatorial treatments from drugs and genetic manipulations.

Several groups recently coupled CRISPR perturbations and single-cell RNA-seq for pooled genetic screens. We demonstrate that vector designs of these studies are susceptible to ∼50% swapping of guide RNA-barcode associations because of lentiviral template switching. We optimized a published alternative, CROP-seq, in which the guide RNA also serves as the barcode, and here confirm that this strategy performs robustly and doubled the rate at which guides are assigned to cells to 94%.

Single-cell analyses have begun to provide insight into the differences among and within the individual cells that make up a tissue or organism. However, technological barriers owing to the small amount of material present in each single cell have prevented parallel analyses. Cao et al. present sci-CAR, a pooled barcode method that jointly analyzes both the RNA transcripts and chromatin profiles of single cells. By applying sci-CAR to lung adenocarcinoma cells and mouse kidney tissue, the authors demonstrate precision in assessing expression and genome accessibility at a genome-wide scale. The approach provides an improvement over bulk analysis, which can be confounded by differing cellular subgroups. Science , this issue p. 1380 A technique termed sci-CAR can assess both chromatin accessibility and RNA transcription at the single-cell level. Although we can increasingly measure transcription, chromatin, methylation, and other aspects of molecular biology at single-cell resolution, most assays survey only one aspect of cellular biology. Here we describe sci-CAR, a combinatorial indexing–based coassay that jointly profiles chromatin accessibility and mRNA (CAR) in each of thousands of single cells. As a proof of concept, we apply sci-CAR to 4825 cells, including a time series of dexamethasone treatment, as well as to 11,296 cells from the adult mouse kidney. With the resulting data, we compare the pseudotemporal dynamics of chromatin accessibility and gene expression, reconstruct the chromatin accessibility profiles of cell types defined by RNA profiles, and link cis-regulatory sites to their target genes on the basis of the covariance of chromatin accessibility and transcription across large numbers of single cells.

Integrating single-cell trajectory analysis with pooled genetic screening could reveal the genetic architecture that guides cellular decisions in development and disease. We applied this paradigm to probe the genetic circuitry that controls epithelial-to-mesenchymal transition (EMT). We used single-cell RNA sequencing to profile epithelial cells undergoing a spontaneous spatially determined EMT in the presence or absence of transforming growth factor-β. Pseudospatial trajectory analysis identified continuous waves of gene regulation as opposed to discrete ‘partial’ stages of EMT. KRAS was connected to the exit from the epithelial state and the acquisition of a fully mesenchymal phenotype. A pooled single-cell CRISPR-Cas9 screen identified EMT-associated receptors and transcription factors, including regulators of KRAS, whose loss impeded progress along the EMT. Inhibiting the KRAS effector MEK and its upstream activators EGFR and MET demonstrates that interruption of key signaling events reveals regulatory ‘checkpoints’ in the EMT continuum that mimic discrete stages, and reconciles opposing views of the program that controls EMT. Transcriptional profiling of 61,052 cells undergoing epithelial-to-mesenchymal transition (EMT) shows continuous waves of gene regulation, not discrete stages. A CRISPR screen orders EMT regulators along EMT progression.

Helicobacter hepaticus -infected Rag 2 ⁻/⁻ mice emulate many aspects of human inflammatory bowel disease, including the development of colitis and colon cancer. To elucidate mechanisms of inflammation-induced carcinogenesis, we undertook a comprehensive analysis of histopathology, molecular damage, and gene expression changes during disease progression in these mice. Infected mice developed severe colitis and hepatitis by 10 wk post-infection, progressing into colon carcinoma by 20 wk post-infection, with pronounced pathology in the cecum and proximal colon marked by infiltration of neutrophils and macrophages. Transcriptional profiling revealed decreased expression of DNA repair and oxidative stress response genes in colon, but not in liver. Mass spectrometric analysis revealed higher levels of DNA and RNA damage products in liver compared to colon and infection-induced increases in 5-chlorocytosine in DNA and RNA and hypoxanthine in DNA. Paradoxically, infection was associated with decreased levels of DNA etheno adducts. Levels of nucleic acid damage from the same chemical class were strongly correlated in both liver and colon. The results support a model of inflammation-mediated carcinogenesis involving infiltration of phagocytes and generation of reactive species that cause local molecular damage leading to cell dysfunction, mutation, and cell death. There are strong correlations among histopathology, phagocyte infiltration, and damage chemistry that suggest a major role for neutrophils in inflammation-associated cancer progression. Further, paradoxical changes in nucleic acid damage were observed in tissue- and chemistry-specific patterns. The results also reveal features of cell stress response that point to microbial pathophysiology and mechanisms of cell senescence as important mechanistic links to cancer.

Chronic inflammation increases cancer risk. While it is clear that cell signaling elicited by inflammatory cytokines promotes tumor development, the impact of DNA damage production resulting from inflammation-associated reactive oxygen and nitrogen species (RONS) on tumor development has not been directly tested. RONS induce DNA damage that can be recognized by alkyladenine DNA glycosylase (Aag) to initiate base excision repair. Using a mouse model of episodic inflammatory bowel disease by repeated administration of dextran sulfate sodium in the drinking water, we show that Aag-mediated DNA repair prevents colonic epithelial damage and reduces the severity of dextran sulfate sodium-induced colon tumorigenesis. Importantly, DNA base lesions expected to be induced by RONS and recognized by Aag accumulated to higher levels in Aag-deficient animals following stimulation of colonic inflammation. Finally, as a test of the generality of this effect we show that Aag-deficient animals display more severe gastric lesions that are precursors of gastric cancer after chronic infection with Helicobacter pylori. These data demonstrate that the repair of DNA lesions formed by RONS during chronic inflammation is important for protection against colon carcinogenesis.

Deamination of nucleobases in DNA and RNA results in the formation of xanthine (X), hypoxanthine (I), oxanine, and uracil, all of which are miscoding and mutagenic in DNA and can interfere with RNA editing and function. Among many forms of nucleic acid damage, deamination arises from several unrelated mechanisms, including hydrolysis, nitrosative chemistry, and deaminase enzymes. Here we present a fourth mechanism contributing to the burden of nucleobase deamination: incorporation of hypoxanthine and xanthine into DNA and RNA caused by defects in purine nucleotide metabolism. Using Escherichia coli and Saccharomyces cerevisiae with defined mutations in purine metabolism in conjunction with analytical methods for quantifying deaminated nucleobases in DNA and RNA, we observed large increases (up to 600-fold) in hypoxanthine in both DNA and RNA in cells unable to convert IMP to XMP or AMP (IMP dehydrogenase, guaB; adenylosuccinate synthetase, purA, and ADE12), and unable to remove dITP/ITP and dXTP/XTP from the nucleotide pool (dITP/XTP pyrophosphohydrolase, rdgB and HAM1). Conversely, modest changes in xanthine levels were observed in RNA (but not DNA) from E. coli lacking purA and rdgB and the enzyme converting XMP to GMP (GMP synthetase, guaA). These observations suggest that disturbances in purine metabolism caused by known genetic polymorphisms could increase the burden of mutagenic deaminated nucleobases in DNA and interfere with gene expression and RNA function, a situation possibly exacerbated by the nitrosative stress of concurrent inflammation. The results also suggest a mechanistic basis for the pathophysiology of human inborn errors of purine nucleotide metabolism.

Reactive oxygen species (ROS) appear to play a role in limiting both cellular and organismic lifespan. However, because of their pleiotropic effects, it has been difficult to ascribe a specific role to ROS in initiating the process of cellular senescence. We have studied the effects of oxidative DNA damage on cell proliferation, believing that such damage is of central importance to triggering senescence. To do so, we devised a strategy to decouple levels of 8-oxoguanine, a major oxidative DNA lesion, from ROS levels. Suppression of MTH1 expression, which hydrolyzes 8-oxo-dGTP, was accompanied by increased total cellular 8-oxoguanine levels and caused early-passage primary and telomerase-immortalized human skin fibroblasts to rapidly undergo senescence, doing so without altering cellular ROS levels. This senescent phenotype recapitulated several salient features of replicative senescence, notably the presence of senescence-associated beta-galactosidase (SA beta-gal) activity, apparently irreparable genomic DNA breaks, and elevation of $p21^{Cip1} $, p53, and $p16^{INK4A} $ tumor suppressor protein levels. Culturing cells under low oxygen tension (3%) largely prevented the shMTH1-dependent senescent phenotype. These results indicate that the nucleotide pool is a critical target of intracellular ROS and that oxidized nucleotides, unless continuously eliminated, can rapidly induce cell senescence through signaling pathways very similar to those activated during replicative senescence.

Thyroid hormone (TH) regulates diverse developmental events and can drive disparate cellular outcomes. In zebrafish, TH has opposite effects on neural crest derived pigment cells of the adult stripe pattern, limiting melanophore population expansion, yet increasing yellow/orange xanthophore numbers. To learn how TH elicits seemingly opposite responses in cells having a common embryological origin, we analyzed individual transcriptomes from thousands of neural crest-derived cells, reconstructed developmental trajectories, identified pigment cell-lineage specific responses to TH, and assessed roles for TH receptors. We show that TH promotes maturation of both cell types but in distinct ways. In melanophores, TH drives terminal differentiation, limiting final cell numbers. In xanthophores, TH promotes accumulation of orange carotenoids, making the cells visible. TH receptors act primarily to repress these programs when TH is limiting. Our findings show how a single endocrine factor integrates very different cellular activities during the generation of adult form. Hormones control the development of animals from embryos all the way into adulthood. For example, thyroid hormone is needed to transform a tadpole into an adult frog, and it is essential for developing the nervous system and regulating metabolism in countless other adult animals. However, it remains unclear how a single hormone can control such a diverse range of outcomes. One way to learn more about the effects of thyroid hormone during development is to study zebrafish pigmentation. Pigment cells arise from a group of stem cells in the embryo called the neural crest. Two of these pigment cells respond to thyroid hormone in different ways: it causes orange pigment cells called xanthophores to expand in number, and at the same time limits the number of black pigment cells called melanophores. To investigate how thyroid hormone effects the numbers of these pigment cells Saunders et al. mapped the active genes of individual cells derived from the neural crest. Further experiments were then performed on the fish themselves based on these gene activity maps. Comparing fish with and without thyroid hormone showed the hormone actually helps both orange and black pigment cells to mature, but in very different ways. For the orange xanthophores, thyroid hormone drives cells already poised to change into their adult form to acquire orange pigments. For the black melanophores, it causes them to mature into their final non-dividing adult state. This results in xanthophores becoming visible just as the number of melanophores is forced to curtail. Saunders et al. also found the receptor for thyroid hormone acts like a brake for both pigment cells, making sure neither cell type matures in the absence of the hormone. These experiments show how one hormone can independently regulate different cell types as they mature into their adult form. The finding that thyroid hormone limits the growth of melanocytes may explain why people who produce too little thyroid hormone are at greater risk of melanoma – a form of skin cancer that starts in the melanocytes. But more studies are needed to see if thyroid hormone has the same limiting effect on melanocytes in humans.

Single cell RNA sequencing can yield high-resolution cell-type–specific expression signatures that reveal new cell types and the developmental trajectories of cell lineages. Here, we apply this approach to Arabidopsis (Arabidopsis thaliana) root cells to capture gene expression in 3,121 root cells. We analyze these data with Monocle 3, which orders single cell transcriptomes in an unsupervised manner and uses machine learning to reconstruct single cell developmental trajectories along pseudotime. We identify hundreds of genes with cell-type–specific expression, with pseudotime analysis of several cell lineages revealing both known and novel genes that are expressed along a developmental trajectory. We identify transcription factor motifs that are enriched in early and late cells, together with the corresponding candidate transcription factors that likely drive the observed expression patterns. We assess and interpret changes in total RNA expression along developmental trajectories and show that trajectory branch points mark developmental decisions. Finally, by applying heat stress to whole seedlings, we address the longstanding question of possible heterogeneity among cell types in the response to an abiotic stress. Although the response of canonical heat-shock genes dominates expression across cell types, subtle but significant differences in other genes can be detected among cell types. Taken together, our results demonstrate that single cell transcriptomics holds promise for studying plant development and plant physiology with unprecedented resolution.