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Sensory neurons are distinguished by distinct signaling networks and receptive characteristics. Thus, sensory neuron types can be defined by linking transcriptome-based neuron typing with the sensory phenotypes. Here we classify somatosensory neurons of the mouse dorsal root ganglion （DRG） by high-coverage single-cell RNA-sequencing （10 950 ±1 218 genes per neuron） and neuron size-based hierarchical clustering. Moreover, single DRG neurons responding to cutaneous stimuli are recorded using an in vivo whole-cell patch clamp technique and classified by neuron-type genetic markers. Small diameter DRG neurons are classified into one type of low-threshold mechanoreceptor and five types of mechanoheat nociceptors （MHNs）. Each of the MHN types is further categorized into two subtypes. Large DRG neurons are categorized into four types, including neurexophilin 1-expressing MHNs and mechanical nociceptors （MNs） expressing BAil-associated protein 2-like I （Baiap211）. Mechanoreceptors expressing trafficking protein particle complex 3-like and Baiap211-marked MNs are subdivided into two subtypes each. These results provide a new system for cataloging somatosensory neurons and their transcriptome databases.

Background Recently, pioneering expression quantitative trait loci (eQTL) studies on single cell RNA sequencing (scRNA-seq) data have revealed new and cell-specific regulatory single nucleotide variants (SNVs). Here, we present an alternative QTL-related approach applicable to transcribed SNV loci from scRNA-seq data: scReQTL. ScReQTL uses Variant Allele Fraction (VAF RNA ) at expressed biallelic loci, and corelates it to gene expression from the corresponding cell. Results Our approach employs the advantage that, when estimated from multiple cells, VAF RNA can be used to assess effects of SNVs in a single sample or individual. In this setting scReQTL operates in the context of identical genotypes, where it is likely to capture RNA-mediated genetic interactions with cell-specific and transient effects. Applying scReQTL on scRNA-seq data generated on the 10 × Genomics Chromium platform using 26,640 mesenchymal cells derived from adipose tissue obtained from three healthy female donors, we identified 1272 unique scReQTLs. ScReQTLs common between individuals or cell types were consistent in terms of the directionality of the relationship and the effect size. Comparative assessment with eQTLs from bulk sequencing data showed that scReQTL analysis identifies a distinct set of SNV-gene correlations, that are substantially enriched in known gene-gene interactions and significant genome-wide association studies (GWAS) loci. Conclusion ScReQTL is relevant to the rapidly growing source of scRNA-seq data and can be applied to outline SNVs potentially contributing to cell type-specific and/or dynamic genetic interactions from an individual scRNA-seq dataset. Availability: https://github.com/HorvathLab/NGS/tree/master/scReQTL

Despite marked development in cancer therapies during recent decades, the prognosis for advanced cancer remains poor. The conventional tumor–cell‐centric view of cancer can only explain part of cancer progression, and thus a thorough understanding of the tumor microenvironment (TME) is crucial. Among cells within the TME, cancer‐associated fibroblasts (CAFs) are attracting attention as a target for cancer therapy. However, CAFs present a heterogeneous population of cells and more detailed classification of CAFs and investigation of functions of each subset is needed to develop novel CAF‐targeted therapies. In this context, application of newly developed approaches to single‐cell analysis has already made an impact on our understanding of the heterogeneity of CAFs. Here, we review the recent literature on CAF heterogeneity and function, and discuss the possibility of novel therapies targeting CAF subsets. The conventional tumor–cell‐centric view of cancer can only explain a part of cancer progression, thus understanding of the tumor microenvironment (TME) is crucial. Among cells within the TME, cancer‐associated fibroblasts (CAFs) are attracting attention as a target for cancer therapy. Here, we review the recent literature that has improved our understanding of heterogeneity in CAFs and function of each subset, and discuss the possibility of novel therapies targeting CAF subsets.

Distant metastasis remains the major cause of morbidity for breast cancer. Individuals with liver or brain metastasis have an extremely poor prognosis and low response rates to anti‐PD‐1/L1 immune checkpoint therapy compared to those with metastasis at other sites. Therefore, it is urgent to investigate the underlying mechanism of anti‐PD‐1/L1 resistance and develop more effective immunotherapy strategies for these patients. Using single‐cell RNA sequencing, a high‐resolution map of the entire tumor ecosystem based on 44 473 cells from breast cancer liver and brain metastases is depicted. Identified by canonical markers and confirmed by multiplex immunofluorescent staining, the metastatic ecosystem features remarkable reprogramming of immunosuppressive cells such as FOXP3+ regulatory T cells, LAMP3+ tolerogenic dendritic cells, CCL18+ M2‐like macrophages, RGS5+ cancer‐associated fibroblasts, and LGALS1+ microglial cells. In addition, PD‐1 and PD‐L1/2 are barely expressed in CD8+ T cells and cancer/immune/stromal cells, respectively. Interactions of the immune checkpoint molecules LAG3‐LGALS3 and TIGIT‐NECTIN2 between CD8+ T cells and cancer/immune/stromal cells are found to play dominant roles in the immune escape. In summary, this study dissects the intratumoral heterogeneity and immunosuppressive microenvironment in liver and brain metastases of breast cancer for the first time, providing insights into the most appropriate immunotherapy strategies for these patients. High‐resolution landscapes of the entire tumor ecosystem from breast cancer liver and brain metastases are first depicted using single‐cell RNA sequencing. The metastatic breast cancer microenvironment features remarkable intratumoral heterogeneity and abundant immunosuppressive cells. This study provides unique insights into the immunotherapeutic strategies most appropriate for patients with liver or brain metastatic breast cancer.

In colorectal cancer, oncogenic mutations transform a hierarchically organized and homeostatic epithelium into invasive cancer tissue lacking visible organization. We sought to define transcriptional states of colorectal cancer cells and signals controlling their development by performing single‐cell transcriptome analysis of tumors and matched non‐cancerous tissues of twelve colorectal cancer patients. We defined patient‐overarching colorectal cancer cell clusters characterized by differential activities of oncogenic signaling pathways such as mitogen‐activated protein kinase and oncogenic traits such as replication stress. RNA metabolic labeling and assessment of RNA velocity in patient‐derived organoids revealed developmental trajectories of colorectal cancer cells organized along a mitogen‐activated protein kinase activity gradient. This was in contrast to normal colon organoid cells developing along graded Wnt activity. Experimental targeting of EGFR‐BRAF‐MEK in cancer organoids affected signaling and gene expression contingent on predictive KRAS/BRAF mutations and induced cell plasticity overriding default developmental trajectories. Our results highlight directional cancer cell development as a driver of non‐genetic cancer cell heterogeneity and re‐routing of trajectories as a response to targeted therapy. SYNOPSIS Colorectal cancer (CRC) cells can adopt a range of transcriptomic states. This study uses single cell RNA sequencing of primary CRC tissue and organoids to identify patient‐overarching CRC cell transcriptome clusters. RNA metabolic labelling indicates preferred CRC cell developmental trajectories. CRC cells of multiple patients clustered into six groups – termed TC1‐4, Goblet‐like, and stem‐like – characterized by differential transcriptional footprints of oncogenic signaling pathways. CRC organoid cells develop along a decreasing MAPK gradient. Experimental targeting of EGFR‐MAPK in CRC organoids re‐routes developmental trajectories. Clinically relevant inhibition of EGFR‐MAPK can result in preferential CRC cell development towards endpoints expressing high levels of stem cell markers. Graphical Abstract Colorectal cancer (CRC) cells can adopt a range of transcriptomic states. This study uses single cell RNA sequencing of primary CRC tissue and organoids to identify patient‐overarching CRC cell transcriptome clusters. RNA metabolic labelling indicates preferred CRC cell developmental trajectories.

Exacerbated pro‐inflammatory immune response contributes to COVID‐19 pathology. However, despite the mounting evidence about SARS‐CoV‐2 infecting the human gut, little is known about the antiviral programs triggered in this organ. To address this gap, we performed single‐cell transcriptomics of SARS‐CoV‐2‐infected intestinal organoids. We identified a subpopulation of enterocytes as the prime target of SARS‐CoV‐2 and, interestingly, found the lack of positive correlation between susceptibility to infection and the expression of ACE2 . Infected cells activated strong pro‐inflammatory programs and produced interferon, while expression of interferon‐stimulated genes was limited to bystander cells due to SARS‐CoV‐2 suppressing the autocrine action of interferon. These findings reveal that SARS‐CoV‐2 curtails the immune response and highlights the gut as a pro‐inflammatory reservoir that should be considered to fully understand SARS‐CoV‐2 pathogenesis. Synopsis Single cell sequencing and multiplex single‐molecule RNA FISH analyses on SARS‐CoV‐2 infected human intestinal organoids characterize the tropism of SARS‐CoV‐2 and identify strategies developed by the virus to interfere with the host intrinsic innate immune response. SARS‐CoV‐2 primarily infects the enterocyte lineage. High expression levels of ACE2 does not correlate with higher infectability of cells by SARS‐CoV‐2. ACE2 expression is downregulated upon SARS‐CoV‐2 infection of human intestinal epithelial cells. Infected cells show a high pro‐inflammatory response and little to no interferon‐mediated response as the result of a SARS‐CoV‐2‐mediated inhibition of interferon signaling. Graphical Abstract Single cell sequencing and multiplex single‐molecule RNA FISH analyses on SARS‐CoV‐2 infected human intestinal organoids characterize the tropism of SARS‐CoV‐2 and identify strategies developed by the virus to interfere with the host intrinsic innate immune response.

Extracting dynamical information from single‐cell transcriptomics is a novel task with the promise to advance our understanding of cell state transition and interactions between genes. Yet, theory‐oriented, bottom‐up approaches that consider differences among cell states are largely lacking. Here, we present spliceJAC, a method to quantify the multivariate mRNA splicing from single‐cell RNA sequencing (scRNA‐seq). spliceJAC utilizes the unspliced and spliced mRNA count matrices to constructs cell state‐specific gene–gene regulatory interactions and applies stability analysis to predict putative driver genes critical to the transitions between cell states. By applying spliceJAC to biological systems including pancreas endothelium development and epithelial–mesenchymal transition (EMT) in A549 lung cancer cells, we predict genes that serve specific signaling roles in different cell states, recover important differentially expressed genes in agreement with pre‐existing analysis, and predict new transition genes that are either exclusive or shared between different cell state transitions. Synopsis spliceJAC builds a multivariate mRNA splicing model from single‐cell transcriptome data to infer the context‐specific gene regulation and the key driver genes that guide the transition between cell states. spliceJAC constructs cell state‐specific gene regulatory networks and quantifies changes in signaling roles between cell states. spliceJAC employs stability analysis to identify driver genes that guide transitions between cell states. Context‐specific gene regulation and transition genes are identified using spliceJAC during pancreas endothelium development and epithelial–mesenchymal transition (EMT) in A549 lung cancer cells. Graphical Abstract spliceJAC builds a multivariate mRNA splicing model from single‐cell transcriptome data to infer the context‐specific gene regulation and the key driver genes that guide the transition between cell states.

Renal aging, marked by the accumulation of senescent cells and chronic low‐grade inflammation, leads to renal interstitial fibrosis and impaired function. In this study, we investigate the role of macrophages, a key regulator of inflammation, in renal aging by analyzing kidney single‐cell RNA sequencing data of C57BL/6J mice from 8 weeks to 24 months. Our findings elucidate the dynamic changes in the proportion of kidney cell types during renal aging and reveal that increased macrophage infiltration contributes to chronic low‐grade inflammation, with these macrophages exhibiting senescence and activation of ferroptosis signaling. CellChat analysis indicates enhanced communications between macrophages and tubular cells during aging. Suppressing ferroptosis alleviates macrophage‐mediated tubular partial epithelial‐mesenchymal transition in vitro, thereby mitigating the expression of fibrosis‐related genes. Using SCENIC analysis, we infer Stat1 as a key age‐related transcription factor promoting iron dyshomeostasis and ferroptosis in macrophages by regulating the expression of Pcbp1, an iron chaperone protein that inhibits ferroptosis. Furthermore, through virtual screening and molecular docking from a library of anti‐aging compounds, we construct a docking model targeting Pcbp1, which indicates that the natural small molecule compound Rutin can suppress macrophage senescence and ferroptosis by preserving Pcbp1. In summary, our study underscores the crucial role of macrophage iron dyshomeostasis and ferroptosis in renal aging. Our results also suggest Pcbp1 as an intervention target in aging‐related renal fibrosis and highlight Rutin as a potential therapeutic agent in mitigating age‐related renal chronic low‐grade inflammation and fibrosis. During renal aging, the accumulation of senescent macrophages promotes tubular partial epithelial‐mesenchymal transition through the secretion of the senescence‐associated secretory phenotype, ultimately contributing to age‐related renal fibrosis. We propose that Pcbp1 is a key factor for iron homeostasis, and its downregulation promotes renal macrophage senescence by inducing iron dyshomeostasis. While the transcription factor Stat1 contributes to Pcbp1 downregulation, Rutin can preserve the level of Pcbp1 under senescent conditions. This suggests that Rutin is a promising agent for modulating the function of Pcbp1 during renal aging.

Heart failure (HF) is known as the final manifestation of cardiovascular diseases. Although cellular heterogeneity of the heart is well understood, the phenotypic transformation of cardiac cells in progress of HF remains obscure. This study aimed to analyze phenotypic transformation of cardiac cells in HF through human single-cell RNA transcriptome profile. Here, phenotypic transformation of cardiomyocytes (CMs), endothelial cells (ECs), and fibroblasts was identified by data analysis and animal experiments. Abnormal myosin subunits including the decrease in Myosin Heavy Chain 6, Myosin Light Chain 7 and the increase in Myosin Heavy Chain 7 were found in CMs. Two disease phenotypes of ECs named inflammatory ECs and muscularized ECs were identified. In addition, myofibroblast was increased in HF and highly associated with abnormal extracellular matrix. Our study proposed an integrated map of phenotypic transformation of cardiac cells and highlighted the intercellular communication in HF. This detailed definition of cellular transformation will facilitate cell-based mapping of novel interventional targets for the treatment of HF.