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As the number of single‐cell transcriptomics datasets grows, the natural next step is to integrate the accumulating data to achieve a common ontology of cell types and states. However, it is not straightforward to compare gene expression levels across datasets and to automatically assign cell type labels in a new dataset based on existing annotations. In this manuscript, we demonstrate that our previously developed method, scVI, provides an effective and fully probabilistic approach for joint representation and analysis of scRNA‐seq data, while accounting for uncertainty caused by biological and measurement noise. We also introduce single‐cell ANnotation using Variational Inference (scANVI), a semi‐supervised variant of scVI designed to leverage existing cell state annotations. We demonstrate that scVI and scANVI compare favorably to state‐of‐the‐art methods for data integration and cell state annotation in terms of accuracy, scalability, and adaptability to challenging settings. In contrast to existing methods, scVI and scANVI integrate multiple datasets with a single generative model that can be directly used for downstream tasks, such as differential expression. Both methods are easily accessible through scvi‐tools. SYNOPSIS This study demonstrates the ability of scVI to integrate single‐cell RNA‐seq datasets in a variety of settings and presents scANVI, a new development based on scVI for automated annotation of cell types and states. In scVI, datasets from different labs and technologies are integrated in a joint latent space. In scANVI, cell type annotations are transferred between datasets and across different scenarios. Uncertainties of differential gene expression in multiple samples are quantified. The performance of scVI and scANVI in data integration and cell state annotation is superior to other related methods. Graphical Abstract This study demonstrates the ability of scVI to integrate single‐cell RNA‐seq datasets in a variety of settings and presents scANVI, a new development based on scVI for automated annotation of cell types and states.

Glioblastomas are highly heterogeneous brain tumors. Despite the availability of standard treatment for glioblastoma multiforme (GBM), i.e., Stupp protocol, which involves surgical resection followed by radiotherapy and chemotherapy, glioblastoma remains refractory to treatment and recurrence is inevitable. Moreover, the biology of recurrent glioblastoma remains unclear. Increasing evidence has shown that intratumoral heterogeneity and the tumor microenvironment contribute to therapeutic resistance. However, the interaction between intracellular heterogeneity and drug resistance in recurrent GBMs remains controversial. The aim of this study was to map the transcriptome landscape of cancer cells and the tumor heterogeneity and tumor microenvironment in recurrent and drug‐resistant GBMs at a single‐cell resolution and further explore the mechanism of drug resistance of GBMs. We analyzed six tumor tissue samples from three patients with primary GBM and three patients with recurrent GBM in which recurrence and drug resistance developed after treatment with the standard Stupp protocol using single‐cell RNA sequencing. Using unbiased clustering, nine major cell clusters were identified. Upregulation of the expression of stemness‐related and cell‐cycle‐related genes was observed in recurrent GBM cells. Compared with the initial GBM tissues, recurrent GBM tissues showed a decreased proportion of microglia, consistent with previous reports. Finally, vascular endothelial growth factor A expression and the blood–brain barrier permeability were high, and the O6‐methylguanine DNA methyltransferase‐related signaling pathway was activated in recurrent GBM. Our results delineate the single‐cell map of recurrent glioblastoma, tumor heterogeneity, tumor microenvironment, and drug‐resistance mechanisms, providing new insights into treatment strategies for recurrent glioblastomas. We observed upregulation of the expression of stemness‐related and cell‐cycle‐related genes in recurrent GBM cells. Further, we observed that recurrent GBM tissues showed a decreased proportion of microglia, consistent with previous reports, and that vascular endothelial growth factor A expression and the blood–brain barrier permeability were high, and the O6‐methylguanine DNA methyltransferase‐related signaling pathway was activated in recurrent GBM. Our results provide new insights into treatment strategies for recurrent glioblastomas.

Summary The tea plant is an economically important woody beverage crop. The unique taste of tea is evoked by certain metabolites, especially catechin esters, whereas their precise formation mechanism in different cell types remains unclear. Here, a fast protoplast isolation method was established and the transcriptional profiles of 16 977 single cells from 1st and 3rd leaves were investigated. We first identified 79 marker genes based on six isolated tissues and constructed a transcriptome atlas, mapped developmental trajectories and further delineated the distribution of different cell types during leaf differentiation and genes associated with cell fate transformation. Interestingly, eight differently expressed genes were found to co‐exist at four branch points. Genes involved in the biosynthesis of certain metabolites showed cell‐ and development‐specific characteristics. An unexpected catechin ester glycosyltransferase was characterized for the first time in plants by a gene co‐expression network in mesophyll cells. Thus, the first single‐cell transcriptional landscape in woody crop leave was reported and a novel metabolism pathway of catechin esters in plants was discovered.

Summary Stalk rot caused by Fusarium verticillioides (Fv) is one of the most destructive diseases in maize production. The defence response of root system to Fv invasion is important for plant growth and development. Dissection of root cell type‐specific response to Fv infection and its underlying transcription regulatory networks will aid in understanding the defence mechanism of maize roots to Fv invasion. Here, we reported the transcriptomes of 29 217 single cells derived from root tips of two maize inbred lines inoculated with Fv and mock condition, and identified seven major cell types with 21 transcriptionally distinct cell clusters. Through the weighted gene co‐expression network analysis, we identified 12 Fv‐responsive regulatory modules from 4049 differentially expressed genes (DEGs) that were activated or repressed by Fv infection in these seven cell types. Using a machining‐learning approach, we constructed six cell type‐specific immune regulatory networks by integrating Fv‐induced DEGs from the cell type‐specific transcriptomes, 16 known maize disease‐resistant genes, five experimentally validated genes (ZmWOX5b, ZmPIN1a, ZmPAL6, ZmCCoAOMT2, and ZmCOMT), and 42 QTL or QTN predicted genes that are associated with Fv resistance. Taken together, this study provides not only a global view of maize cell fate determination during root development but also insights into the immune regulatory networks in major cell types of maize root tips at single‐cell resolution, thus laying the foundation for dissecting molecular mechanisms underlying disease resistance in maize.

Single-cell RNA-seq (scRNA-seq) has been highlighted as a powerful tool for the description of human cell transcriptome, but the technology has not been broadly applied in plant cells. Herein, we describe the successful development of a robust protoplast cell isolation system in the peanut leaf. A total of 6,815 single cells were divided into eight cell clusters based on reported marker genes by applying scRNA-seq. Further, a pseudo-time analysis was used to describe the developmental trajectory and interaction network of transcription factors (TFs) of distinct cell types during leaf growth. The trajectory enabled re-investigation of the primordium-driven development processes of the mesophyll and epidermis. These results suggest that palisade cells likely differentiate into spongy cells, while the epidermal cells originated earlier than the primordium. Subsequently, the developed method integrated multiple technologies to efficiently validate the scRNA-seq result in a homogenous cell population. The expression levels of several TFs were strongly correlated with epidermal ontogeny in accordance with obtained scRNA-seq values. Additionally, peanut AHL23 (AT-HOOK MOTIF NUCLEAR LOCALIZED PROTEIN 23), which is localized in nucleus, promoted leaf growth when ectopically expressed in Arabidopsis by modulating the phytohormone pathway. Together, our study displays that application of scRNA-seq can provide new hypotheses regarding cell differentiation in the leaf blade of Arachis hypogaea. We believe that this approach will enable significant advances in the functional study of leaf blade cells in the allotetraploid peanut and other plant species.

The serious coronavirus disease‐2019 (COVID‐19) was first reported in December 2019 in Wuhan, China. COVID‐19 is an infectious disease caused by severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2). Angiotensin converting enzyme 2(ACE2) is the cellular receptor for SARS‐CoV‐2. Considering the critical roles of testicular cells for the transmission of genetic information between generations, we analyzed single‐cell RNA‐sequencing (scRNA‐seq) data of adult human testis. The mRNA expression of ACE2 was expressed in both germ cells and somatic cells. Moreover, the positive rate of ACE2 in testes of infertile men was higher than normal, which indicates that SARS‐CoV‐2 may cause reproductive disorders through pathway activated by ACE2 and the men with reproductive disorder may easily to be infected by SARS‐CoV‐2. The expression level of ACE2 was related to the age, and the mid‐aged with higher positive rate than young men testicular cells. Taken together, this research provides a biological background of the potential route for infection of SARS‐CoV‐2 and may enable rapid deciphering male‐related reproductive disorders induced by COVID‐19.

Sepsis remains a leading cause of in-hospital mortality worldwide. In recognition of its substantial morbidity and mortality even with optimal treatment, the World Health Organization has declared sepsis a global health priority. The immunoregulatory mechanisms in sepsis are highly complex, and the immune status during the disease course is closely associated with both short- and long-term patient outcomes, making early recognition and intervention critical for survival. While single-cell RNA sequencing (scRNA-seq) has been widely applied to decipher innate immune responses in sepsis patients, in-depth characterization of T lymphocyte subsets remains relatively limited. Urosepsis is a common complication of urinary tract stones. Although clinical studies have identified several risk factors for urosepsis, the immunological alterations in high-risk individuals are poorly understood. Here, we employed single-cell transcriptomics to investigate T-cell immunological changes in high-risk urosepsis patients and septic patients, complemented by single-cell T cell receptor (TCR) sequencing (scTCR-seq) to profile the peripheral TCR repertoire in these two pathological states. Our analysis revealed that, compared to non-high-risk controls, septic patients exhibited features of T cell exhaustion across multiple subsets, whereas high-risk individuals showed signs of enhanced T cell-mediated adaptive immunity. Notably, we identified a distinct CD4 + T cell subset (C10_Tn_IFN) and, through protein-protein interaction analysis, uncovered key protein targets ( IFIT3, RSAD2 ) potentially regulating its interferon signaling pathway. Furthermore, we observed significantly reduced TCR diversity accompanied by altered CDR3 sequence characteristics and VJ gene usage frequencies in several CD4 + and CD8 + T cell subsets from sepsis patients. These findings provide important insights into the relationship between T cell functionality and the severity of infectious inflammation.

IntroductionLong-term COVID-19 syndrome (LTCS) or “long COVID” is a debilitating post-viral condition affecting approximately 2%–8% of individuals after SARS-CoV-2 infection. It manifests typically ≥3 months post-infection with symptoms persisting for at least 2 months, including fatigue, pulmonary dysfunction, and cognitive impairment, in the absence of alternative diagnoses. The biological mechanisms underlying LTCS remain poorly defined, yet emerging evidence implicates immune dysregulation.MethodsWe profiled plasma antibodies and cytokines from healthy controls (HC, N = 66), convalescents (CONV, N = 24), and LTCS patients (N = 94), followed by multiparametric 14-color flow cytometry of PBMCs from HC (N = 9), CONV (N = 6), and LTCS (N = 23) participants. To gain mechanistic insight, we performed single-cell transcriptomic profiling (scRNA-seq) on PBMCs from HC (N = 8), CONV (N = 6), and LTCS (N = 32) individuals.ResultsLTCS patients exhibited elevated anti-SARS-CoV-2 IgG (spike S1/RBD/N) titers compared with HC, but displayed significantly reduced systemic cytokine levels, including IFN-γ, TNF-α, IL-6, and IL-10. Flow cytometry revealed marked depletion of CD56+CD16+ NK cells and CD56+CD3+ NKT cells, accompanied by altered T-cell activation states. scRNA-seq confirmed NK type I cell loss and uncovered broad transcriptional reprogramming with upregulation of PDCD4, CHD1, CXCR4, and SLC7A5 and downregulation of TGFBR3, RIPOR2, and MBNL1. Gene set enrichment analyses indicated activation of circadian and translational programs and suppression of olfactory receptor, neurotransmitter receptor, and GABA-gated ion-channel pathways. Functional assays validated reduced NK-cell inflammatory capacity in LTCS participants.DiscussionLTCS is characterized by systemic cytokine attenuation and a quantitative and functional NK-cell deficit coupled to neurosensory pathway suppression. These findings identify NK cells as key sentinels of LTCS pathophysiology and highlight an NK-centric neuroimmune axis as a promising target for biomarker discovery and therapeutic intervention.

Background Cancer cells selectively promote the translation of oncogenic transcripts to stimulate cancer progression. Although growing evidence has revealed that tRNA modifications and related genes participate in this process, their roles in head and neck squamous cell carcinoma (HNSCC) remain largely uncharacterized. Here, we sought to investigate the function and mechanisms of the transfer RNA (tRNA) N7‐methylguanosine (m7G) modification in regulating the occurrence and development of HNSCC. Methods Cell lost‐of‐function and gain‐of‐function assays, xenograft models, conditional knockout and knockin mouse models were used to study the physiological functions of tRNA m7G modification in HNSCC tumorigenesis. tRNA modification and expression profiling, mRNA translation profiling and rescue assays were performed to uncover the underlying molecular mechanisms. Single‐cell RNA sequencing (scRNA‐seq) was conducted to explore the tumor microenvironment changes. Results The tRNA m7G methyltransferase complex components Methyltransferase‐like 1 (METTL1)/WD repeat domain 4 (WDR4) were upregulated in HNSCC and associated with a poor prognosis. Functionally, METTL1/WDR4 promoted HNSCC progression and metastasis in cell‐based and transgenic mouse models. Mechanistically, ablation of METTL1 reduced the m7G levels of 16 tRNAs, inhibiting the translation of a subset of oncogenic transcripts, including genes related to the phosphatidylinositol‐3‐kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling pathway. In addition, chemical modulators of the PI3K/Akt/mTOR signaling pathway reversed the effects of Mettl1 in mouse HNSCC. Furthermore, scRNA‐seq results revealed that Mettl1 knockout in mouse tumor cells altered the immune landscape and cell‐cell interaction between the tumor and stromal compartment. Conclusions The tRNA m7G methyltransferase METTL1 was found to promote the development and malignancy of HNSCC through regulating global mRNA translation, including the PI3K/AKT/mTOR signaling pathway, and found to alter immune landscape. METTL1 could be a promising treatment target for HNSCC patients.