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Advances and Opportunities in Single-Cell Transcriptomics for Plant Research.
Single-cell approaches are quickly changing our view on biological systems by increasing the spatiotemporal resolution of our analyses to the level of the individual cell. The field of plant biology has fully embraced single-cell transcriptomics and is rapidly expanding the portfolio of available technologies and applications. In this review, we give an overview of the main advances in plant single-cell transcriptomics over the past few years and provide the reader with an accessible guideline covering all steps, from sample preparation to data analysis. We end by offering a glimpse of how these technologies will shape and accelerate plant-specific research in the near future.
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SeuratIntegrate: an R package to facilitate the use of integration methods with Seurat.
MOTIVATION: Integrating multiple datasets has become an increasingly common task in scRNA-seq analysis. The advent of single-cell atlases adds further complexity, as they often involve combining data with nested batch effects. While common tools such as Seurat offer access to batch-correction methods, the diversity of available options remains limited. With growing evidence that integration method performance varies significantly between datasets, making an informed decision in selecting the most appropriate integration approach is not trivial. A broader range of accessible methods combined with a comprehensive toolbox for comparative integration analysis, would support more effective and flexible single-cell data integration workflows. RESULTS: Built on Seurat's foundations, we developed SeuratIntegrate, an open source R package that expands integration methods available to Seurat users, including Python-based approaches, while operating entirely within the R environment. The package enables integration benchmarking using well-established performance metrics, and provides automated Python environment management, cross-language object conversion, and tools for score handling and visualization. All features are designed for ease of use and extensibility. AVAILABILITY AND IMPLEMENTATION: The source code, installation process and vignettes demonstrating usage are freely available on GitHub: https://github.com/cbib/Seurat-Integrate. A Zenodo deposit contains a copy of the package code along with the data to reproduce the results presented above (accession 10.5281/zenodo.14288360). The package is released under the MIT License.
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A single-cell and spatially resolved atlas of human osteosarcomas.
Osteosarcomas are intricate cellular ecosystems, where heterotypic interactions significantly influence disease progression and therapeutic outcomes. Despite their importance, a detailed understanding of their cellular composition and organizational structure remains elusive. In this study, we provide a comprehensive single-cell and spatially resolved transcriptomics analysis of human osteosarcomas. We construct a cellular meta-map to dissect spatial transcriptomic data, unveiling a detailed atlas of osteosarcoma compositional subgroups. We meticulously characterize the unique gene signatures and functional states of each subgroup and investigate the impact of chemotherapy on these cellular subpopulations. Additionally, our spatial transcriptomics analysis identifies a distinct spatial niche, located at the forefront of tumor necrotic zones, potentially associated with chemotherapy resistance. We also delve into the crosstalk between different cellular subgroups. This study furnishes a comprehensive transcriptional atlas of osteosarcoma's cellular architecture, enriching our comprehension of its complexity and laying the groundwork for more targeted therapeutic approaches.
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Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq.
Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequencing (RNA-seq) predominates. Positioned as a superior technology, that makes the discovery of novel transcripts routine, most RNA-seq analyses are in fact modeled on the known transcriptome. Limitations of the RNA-seq methodology have emerged, while the design of, and the analysis strategies applied to, arrays have matured. An equitable comparison between these technologies is provided, highlighting advantages that modern arrays hold over RNA-seq. Array protocols more accurately quantify constitutively expressed protein coding genes across tissue replicates, and are more reliable for studying lower expressed genes. Arrays reveal long noncoding RNAs (lncRNA) are neither sparsely nor lower expressed than protein coding genes. Heterogeneous coverage of constitutively expressed genes observed with RNA-seq, undermines the validity and reproducibility of pathway analyses. The factors driving these observations, many of which are relevant to long-read or single-cell sequencing are discussed. As proposed herein, a reappreciation of bulk transcriptomic methods is required, including wider use of the modern high-density array data-to urgently revise existing anatomical RNA reference atlases and assist with more accurate study of lncRNAs.
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Cell atlas of trabecular meshwork in glaucomatous non-human primates and DEGs related to tissue contract based on single-cell transcriptomics.
As the major channel of aqueous humor outflow, dysfunction of trabecular meshwork (TM) can lead to intraocular pressure elevating, which can trigger primary open-angle glaucoma (POAG). In this study, we use single-cell RNA sequencing (scRNA-seq) technique to build an atlas and further explore the spontaneous POAG and healthy macaques cellular heterogeneity associated with the dysfunction of TM contraction. We built the TM atlas, which identified 14 different cell types. In Beam A, Beam B, Beam C, and smooth muscle cell (SMC) cell types, we first found multiple genes associated with TM contraction (e.g., TPM1, ACTC1, TNNT1), determining their differential expression in the POAG and healthy groups. In addition, the microstructural alterations in TM of POAG non-human primates were observed, which was compact and collapsed. Thus, our study indicated that TPM1 may be a key target for regulating TM structure, contraction function, and resistance of aqueous humor outflow.
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The Myeloid Cell Compartment-Cell by Cell.
Myeloid cells are a major cellular compartment of the immune system comprising monocytes, dendritic cells, tissue macrophages, and granulocytes. Models of cellular ontogeny, activation, differentiation, and tissue-specific functions of myeloid cells have been revisited during the last years with surprising results; for example, most tissue macrophages are yolk sac derived, monocytes and macrophages follow a multidimensional model of activation, and tissue signals have a significant impact on the functionality of all these cells. While these exciting results have brought these cells back to center stage, their enormous plasticity and heterogeneity, during both homeostasis and disease, are far from understood. At the same time, the ongoing revolution in single-cell genomics, with single-cell RNA sequencing (scRNA-seq) leading the way, promises to change this. Prevailing models of hematopoiesis with distinct intermediates are challenged by scRNA-seq data suggesting more continuous developmental trajectories in the myeloid cell compartment. Cell subset structures previously defined by protein marker expression need to be revised based on unbiased analyses of scRNA-seq data. Particularly in inflammatory conditions, myeloid cells exhibit substantially vaster heterogeneity than previously anticipated, and work performed within large international projects, such as the Human Cell Atlas, has already revealed novel tissue macrophage subsets. Based on these exciting developments, we propose the next steps to a full understanding of the myeloid cell compartment in health and diseases.
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Characterization of 2,2',4,4'-tetrabromodiphenyl ether (BDE47)-induced testicular toxicity via single-cell RNA-sequencing.
BACKGROUND: The growing male reproductive diseases have been linked to higher exposure to certain environmental compounds such as 2,2',4,4'-tetrabromodiphenyl ether (BDE47) that are widely distributed in the food chain. However, the specific underlying molecular mechanisms for BDE47-induced male reproductive toxicity are not completely understood. METHODS: Here, for the first time, advanced single-cell RNA sequencing (ScRNA-seq) was employed to dissect BDE47-induced prepubertal testicular toxicity in mice from a pool of 76 859 cells. RESULTS: Our ScRNA-seq results revealed shared and heterogeneous information of differentially expressed genes, signaling pathways, transcription factors, and ligands-receptors in major testicular cell types in mice upon BDE47 treatment. Apart from disruption of hormone homeostasis, BDE47 was discovered to downregulate multiple previously unappreciated pathways such as double-strand break repair and cytokinesis pathways, indicative of their potential roles involved in BDE47-induced testicular injury. Interestingly, transcription factors analysis of ScRNA-seq results revealed that Kdm5b (lysine-specific demethylase 5B), a key transcription factor required for spermatogenesis, was downregulated in all germ cells as well as in Sertoli and telocyte cells in BDE47-treated testes of mice, suggesting its contribution to BDE47-induced impairment of spermatogenesis. CONCLUSIONS: Overall, for the first time, we established the molecular cell atlas of mice testes to define BDE47-induced prepubertal testicular toxicity using the ScRNA-seq approach, providing novel insight into our understanding of the underlying mechanisms and pathways involved in BDE47-associated testicular injury at a single-cell resolution. Our results can serve as an important resource to further dissect the potential roles of BDE47, and other relevant endocrine-disrupting chemicals, in inducing male reproductive toxicity.
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Stereo-cell coupled with single-cell transcriptomics identifies a transitional metabolic state in maturing skeletal muscle myofibers.
Identification of skeletal muscle fiber types and metabolic reprogramming are crucial for postnatal muscle maturation, but high-resolution metabolism and spatial heterogeneity of muscle fibers in mid-maturation remain poorly understood. Our study performed single-cell RNA sequencing (scRNA-seq) and single-cell nuclear RNA sequencing (snRNA-seq) on five hind limb muscles from 5-week-old mice, combined with Stereo-cell at single muscle fiber resolution, to elucidate myofiber subtype maturation and its metabolic changes. Integrating scRNA-seq and snRNA-seq data, a comprehensive mouse skeletal muscle cell atlas was constructed, demonstrating the complementary advantages of the two techniques in capturing interstitial cells and multinucleated muscle fibers. Our analysis resolved a continuous maturational lineage from type I to IIB myonuclei (IIB_1-3). Notably, the IIB_3 myonuclei subtype exhibited a dual hypermetabolic phenotype, with increased oxidative phosphorylation (OXPHOS) and glycolytic activity, which differs from the purely glycolytic phenotype observed in adult mice. Stereo-cell further validated this transitional metabolic state and revealed spatial heterogeneity within individual IIB myofibers, with localized high-oxidation regions. Furthermore, we observed a mixed myofiber phenotype, with subtype-specific myosin heavy chain expression enriched at the myofiber terminals, indicating directional transformation of myofiber during maturation. In summary, this study reveals a previously undescribed transitional metabolic feature of IIB-type myofiber during postnatal muscle maturation and elucidates the spatial metabolic heterogeneity of myofiber, providing new insights into the regulatory mechanisms of skeletal muscle developmental plasticity and metabolic specialization.
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Electroacupuncture Slows Experimental Myopia Progression by Improving Retinal Mitochondrial Function: A Study Based on Single-Cell RNA Sequencing.
This study aimed to establish a complete atlas of retinal cells in lens-induced myopia (LIM) and electroacupuncture (EA) intervention by single-cell RNA sequencing (scRNA-seq) and to explore the potential mechanism of EA in improving experimental myopia progression in guinea pigs. scRNA-seq is used to assess changes in individual cellular gene levels in the retina of LIM- and EA-treated guinea pigs. In addition, the role of EA in slowing myopia progression by improving retinal mitochondrial function is further investigated. scRNA-seq identified ten cell clusters in the retina of LIM and EA guinea pigs and mitochondrial respiratory chain-related genes in Cones and Muller-glia cells-Cytochrome oxidase subunit III (COX3), NADH dehydrogenase subunit 4 (ND4), and NADH dehydrogenase subunit 2 (ND2) are closely related to lens-induced myopia. A comprehensive atlas in the retina of LIM and EA guinea pigs at a single-cell level is established, and the positive role of EA in improving retinal mitochondrial function to slow the experimental myopia progression in guinea pigs is revealed.
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Single-cell brain atlas of Parkinson's disease mouse model.
Parkinson's disease (PD) is a neurodegenerative disease, leading to the impairment of movement execution. PD pathogenesis has been largely investigated, either limited to bulk transcriptomic levels or at certain cell types, which failed to capture the cellular heterogeneity and intrinsic interplays among distinct cell types. Here, we report the application of single-nucleus RNA-seq on midbrain, striatum, and cerebellum of the α-syn-A53T mouse, a well-established PD mouse model, and matched controls, generating the first single cell transcriptomic atlas for the PD model mouse brain composed of 46,174 individual cells. Additionally, we comprehensively depicte the dysfunctions in PD pathology, covering the elevation of NF-κB activity, the alteration of ion channel components, the perturbation of protein homeostasis network, and the dysregulation of glutamatergic signaling. Notably, we identify a variety of cell types closely associated with PD risk genes. Taken together, our study provides valuable resources to systematically dissect the molecular mechanism of PD pathogenesis at the single-cell resolution, which facilitates the development of novel approaches for diagnosis and therapies against PD.