Organogenetic transcriptomes of the Drosophila embryo at single cell resolution.

To gain insight into the transcription programs activated during the formation of Drosophila larval structures, we carried out single cell RNA sequencing during two periods of Drosophila embryogenesis: stages 10-12, when most organs are first specified and initiate morphological and physiological specialization; and stages 13-16, when organs achieve their final mature architectures and begin to function. Our data confirm previous findings with regards to functional specialization of some organs - the salivary gland and trachea - and clarify the embryonic functions of another - the plasmatocytes. We also identify two early developmental trajectories in germ cells and uncover a potential role for proteolysis during germline stem cell specialization. We identify the likely cell type of origin for key components of the Drosophila matrisome and several commonly used Drosophila embryonic cell culture lines. Finally, we compare our findings with other recent related studies and with other modalities for identifying tissue-specific gene expression patterns. These data provide a useful community resource for identifying many new players in tissue-specific morphogenesis and functional specialization of developing organs.

Combination of blockade of endothelin signalling and compensation of IGF1 expression protects the retina from degeneration.

Retinitis pigmentosa (RP) and macular dystrophy (MD) cause severe retinal dysfunction, affecting 1 in 4000 people worldwide. This disease is currently assumed to be intractable, because effective therapeutic methods have not been established, regardless of genetic or sporadic traits. Here, we examined a RP mouse model in which the Prominin-1 (Prom1) gene was deficient and investigated the molecular events occurring at the outset of retinal dysfunction. We extracted the Prom1-deficient retina subjected to light exposure for a short time, conducted single-cell expression profiling, and compared the gene expression with and without stimuli. We identified the cells and genes whose expression levels change directly in response to light stimuli. Among the genes altered by light stimulation, Igf1 was decreased in rod photoreceptor cells and astrocytes under the light-stimulated condition. Consistently, the insulin-like growth factor (IGF) signal was weakened in light-stimulated photoreceptor cells. The recovery of Igf1 expression with the adeno-associated virus (AAV) prevented photoreceptor cell death, and its treatment in combination with the endothelin receptor antagonist led to the blockade of abnormal glial activation and the promotion of glycolysis, thereby resulting in the improvement of retinal functions, as assayed by electroretinography. We additionally demonstrated that the attenuation of mammalian/mechanistic target of rapamycin (mTOR), which mediates IGF signalling, leads to complications in maintaining retinal homeostasis. Together, we propose that combinatorial manipulation of distinct mechanisms is useful for the maintenance of the retinal condition.

scCompressSA: dual-channel self-attention based deep autoencoder model for single-cell clustering by compressing gene-gene interactions.

BACKGROUND: Single-cell clustering has played an important role in exploring the molecular mechanisms about cell differentiation and human diseases. Due to highly-stochastic transcriptomics data, accurate detection of cell types is still challenged, especially for RNA-sequencing data from human beings. In this case, deep neural networks have been increasingly employed to mine cell type specific patterns and have outperformed statistic approaches in cell clustering. RESULTS: Using cross-correlation to capture gene-gene interactions, this study proposes the scCompressSA method to integrate topological patterns from scRNA-seq data, with support of self-attention (SA) based coefficient compression (CC) block. This SA-based CC block is able to extract and employ static gene-gene interactions from scRNA-seq data. This proposed scCompressSA method has enhanced clustering accuracy in multiple benchmark scRNA-seq datasets by integrating topological and temporal features. CONCLUSION: Static gene-gene interactions have been extracted as temporal features to boost clustering performance in single-cell clustering For the scCompressSA method, dual-channel SA based CC block is able to integrate topological features and has exhibited extraordinary detection accuracy compared with previous clustering approaches that only employ temporal patterns.

sciCNV: high-throughput paired profiling of transcriptomes and DNA copy number variations at single-cell resolution.

Chromosome copy number variations (CNVs) are a near-universal feature of cancer; however, their individual effects on cellular function are often incompletely understood. Single-cell ribonucleic acid (RNA) sequencing (scRNA-seq) might be leveraged to reveal the function of intra-clonal CNVs; however, it cannot directly link cellular gene expression to CNVs. Here, we report a high-throughput scRNA-seq analysis pipeline that provides paired CNV profiles and transcriptomes for single cells, enabling exploration of the effects of CNVs on cellular programs. RTAM1 and -2 normalization methods are described, and are shown to improve transcriptome alignment between cells, increasing the sensitivity of scRNA-seq for CNV detection. We also report single-cell inferred chromosomal copy number variation (sciCNV), a tool for inferring single-cell CNVs from scRNA-seq at 19-46 Mb resolution. Comparison of sciCNV with existing RNA-based CNV methods reveals useful advances in sensitivity and specificity. Using sciCNV, we demonstrate that scRNA-seq can be used to examine the cellular effects of cancer CNVs. As an example, sciCNV is used to identify subclonal multiple myeloma (MM) cells with +8q22-24. Studies of the gene expression of intra-clonal MM cells with and without the CNV demonstrate that +8q22-24 upregulates MYC and MYC-target genes, messenger RNA processing and protein synthesis, which is consistent with established models. In conclusion, we provide new tools for scRNA-seq that enable paired profiling of the CNVs and transcriptomes of single cells, facilitating rapid and accurate deconstruction of the effects of cancer CNVs on cellular programming.

hDirect-MAP: projection-free single-cell modeling of response to checkpoint immunotherapy.

There is a lack of robust generalizable predictive biomarkers of response to immune checkpoint blockade in multiple types of cancer. We develop hDirect-MAP, an algorithm that maps T cells into a shared high-dimensional (HD) expression space of diverse T cell functional signatures in which cells group by the common T cell phenotypes rather than dimensional reduced features or a distorted view of these features. Using projection-free single-cell modeling, hDirect-MAP first removed a large group of cells that did not contribute to response and then clearly distinguished T cells into response-specific subpopulations that were defined by critical T cell functional markers of strong differential expression patterns. We found that these grouped cells cannot be distinguished by dimensional-reduction algorithms but are blended by diluted expression patterns. Moreover, these identified response-specific T cell subpopulations enabled a generalizable prediction by their HD metrics. Tested using five single-cell RNA-seq or mass cytometry datasets from basal cell carcinoma, squamous cell carcinoma and melanoma, hDirect-MAP demonstrated common response-specific T cell phenotypes that defined a generalizable and accurate predictive biomarker.

Single cell transcriptomics of cerebrospinal fluid cells from patients with recent-onset narcolepsy.

Narcolepsy is a rare cause of hypersomnolence and may be associated or not with cataplexy, i.e. sudden muscle weakness. These forms are designated narcolepsy-type 1 (NT1) and -type 2 (NT2), respectively. Notable characteristics of narcolepsy are that most patients carry the HLA-DQB1*06:02 allele and NT1-patients have strongly decreased levels of hypocretin-1 (synonym orexin-A) in the cerebrospinal fluid (CSF). The pathogenesis of narcolepsy is still not completely understood but the strong HLA-bias and increased frequencies of CD4+ T cells reactive to hypocretin in the peripheral blood suggest autoimmune processes in the hypothalamus. Here we analyzed the transcriptomes of CSF-cells from twelve NT1 and two NT2 patients by single cell RNAseq (scRNAseq). As controls, we used CSF cells from patients with multiple sclerosis, radiologically isolated syndrome, and idiopathic intracranial hypertension. From 27,255 CSF cells, we identified 20 clusters of different cell types and found significant differences in three CD4+ T cell and one monocyte clusters between narcolepsy and multiple sclerosis patients. Over 1000 genes were differentially regulated between patients with NT1 and other diseases. Surprisingly, the most strongly upregulated genes in narcolepsy patients as compared to controls were coding for the genome-encoded MTRNR2L12 and MTRNR2L8 peptides, which are homologous to the mitochondria-encoded HUMANIN peptide that is known playing a role in other neurological diseases including Alzheimer's disease.

Single-cell transcriptome landscape elucidates the cellular and developmental responses to tomato chlorosis virus infection in tomato leaf.

Plant viral diseases compromise the growth and yield of the crop globally, and they tend to be more serious under extreme temperatures and drought climate changes. Currently, regulatory dynamics during plant development and in response to virus infection at the plant cell level remain largely unknown. In this study, single-cell RNA sequencing on 23 226 individual cells from healthy and tomato chlorosis virus-infected leaves was established. The specific expression and epigenetic landscape of each cell type during the viral infection stage were depicted. Notably, the mesophyll cells showed a rapid function transition in virus-infected leaves, which is consistent with the pathological changes such as thinner leaves and decreased chloroplast lamella in virus-infected samples. Interestingly, the F-box protein SKIP2 was identified to play a pivotal role in chlorophyll maintenance during virus infection in tomato plants. Knockout of the SlSKIP2 showed a greener leaf state before and after virus infection. Moreover, we further demonstrated that SlSKIP2 was located in the cytomembrane and nucleus and directly regulated by ERF4. In conclusion, with detailed insights into the plant responses to viral infections at the cellular level, our study provides a genetic framework and gene reference in plant-virus interaction and breeding in the future research.

Single-cell RNA-seq analysis decodes the kidney microenvironment induced by polystyrene microplastics in mice receiving a high-fat diet.

In recent years, the environmental health issue of microplastics has aroused an increasingly significant concern. Some studies suggested that exposure to polystyrene microplastics (PS-MPs) may lead to renal inflammation and oxidative stress in animals. However, little is known about the essential effects of PS-MPs with high-fat diet (HFD) on renal development and microenvironment. In this study, we provided the single-cell transcriptomic landscape of the kidney microenvironment induced by PS-MPs and HFD in mouse models by unbiased single-cell RNA sequencing (scRNA-seq). The kidney injury cell atlases in mice were evaluated after continued PS-MPs exposure, or HFD treated for 35 days. Results showed that PS-MPs plus HFD treatment aggravated the kidney injury and profibrotic microenvironment, reshaping mouse kidney cellular components. First, we found that PS-MPs plus HFD treatment acted on extracellular matrix organization of renal epithelial cells, specifically the proximal and distal convoluted tubule cells, to inhibit renal development and induce ROS-driven carcinogenesis. Second, PS-MPs plus HFD treatment induced activated PI3K-Akt, MAPK, and IL-17 signaling pathways in endothelial cells. Besides, PS-MPs plus HFD treatment markedly increased the proportions of CD8+ effector T cells and proliferating T cells. Notably, mononuclear phagocytes exhibited substantial remodeling and enriched in oxidative phosphorylation and chemical carcinogenesis pathways after PS-MPs plus HFD treatment, typified by alterations tissue-resident M2-like PF4+ macrophages. Multispectral immunofluorescence and immunohistochemistry identified PF4+ macrophages in clear cell renal cell carcinoma (ccRCC) and adjacent normal tissues, indicating that activate PF4+ macrophages might regulate the profibrotic and pro-tumorigenic microenvironment after renal injury. In conclusion, this study first systematically revealed molecular variation of renal cells and immune cells in mice kidney microenvironment induced by PS-MPs and HFD with the scRNA-seq approach, which provided a molecular basis for decoding the effects of PS-MPs on genitourinary injury and understanding their potential profibrotic and carcinogenesis in mammals.

Tumor markers for lipid metabolism-related genes: Based on small cell lung cancer and bronchial asthma dual analysis.

Numerous studies have elucidated the intricate relationship between bronchial asthma and small cell lung cancer (SCLC), as well as the role lipid metabolism genes play in transitioning from bronchial asthma to SCLC. Despite this, the predictive power of single gene biomarkers remains insufficient and necessitates the development of more accurate prognostic models. In our study, we downloaded and preprocessed scRNA-seq of SCLC from the GEO database GSE164404 and severe asthma scRNA-seq from GSE145013 using the Seurat package. Using the MSigDB database and geneCard database, we selected lipid metabolism-related genes and performed scRNA-seq data analysis from the gene expression GEO database, aiming to uncover potential links between immune signaling pathways in bronchial asthma and SCLC. Our investigations yielded differentially expressed genes based on the scRNA-seq dataset related to lipid metabolism. We executed differential gene analysis, gene ontology, and Kyoto Encyclopedia of Genes and Genomes analyses. In-depth GSEA pathway activation analysis, crucial target gene predictions via protein-protein interactions, and key cluster gene evaluations for differential and diagnostic ROC values correlation analysis confirmed that key cluster genes are significant predictors for the progression of bronchial asthma to SCLC. To validate our findings, we performed wet laboratory experiments using real-time quantitative PCR to assess the expression of these relevant genes in SCLC cell lines. In conclusion, this research proposes a novel lipid metabolism-related gene marker that can offer comprehensive insights into the pathogenesis of bronchial asthma leading to SCLC. Although this study does not directly focus on senescence-associated molecular alterations, our findings in the lipid metabolism genes associated with inflammation and cancer progression offer valuable insights for further research targeting senescence-related changes in treating inflammatory diseases.

Single-cell RNA sequencing to identify cellular heterogeneity and targets in cardiovascular diseases: from bench to bedside.

The mechanisms of cardiovascular diseases (CVDs) remain incompletely elucidated. Single-cell RNA sequencing (scRNA-seq) has enabled the profiling of single-cell transcriptomes at unprecedented resolution and throughput, which is critical for deciphering cardiovascular cellular heterogeneity and underlying disease mechanisms, thereby facilitating the development of therapeutic strategies. In this review, we summarize cellular heterogeneity in cardiovascular homeostasis and diseases as well as the discovery of potential disease targets based on scRNA-seq, and yield new insights into the promise of scRNA-seq technology in precision medicine and clinical application.

Transcriptome Changes of Hematopoietic Stem and Progenitor Cells in the Peripheral Blood of COVID-19 Patients by scRNA-seq.

Coronavirus disease 2019 (COVID-19) threatens public health all over the world. It is well-accepted that the immune cells in peripheral blood are widely involved in the pathological process of COVID-19. However, hematopoietic stem and progenitor cells (HSPCs), as the main source of peripheral immune cells, have not been well studied during COVID-19 infection. We comprehensively revealed the transcriptome changes of peripheral blood HSPCs after COVID-19 infection and vaccination by single-cell RNA-seq. Compared with healthy individuals, the proportion of HSPCs in COVID-19 patients significantly increased. The increase in the proportion of HSPCs might be partly attributed to the enhancement of the HSPCs proliferation upon COVID-19 infection. However, the stemness damage of HSPCs is reflected by the decrease of differentiation signal, which can be used as a potential specific indicator of the severity and duration of COVID-19 infection. Type I interferon (IFN-I) and translation signals in HSPCs were mostly activated and inhibited after COVID-19 infection, respectively. In addition, the response of COVID-19 vaccination to the body is mild, while the secondary vaccination strengthens the immune response of primary vaccination. In conclusion, our study provides new insights into understanding the immune mechanism of COVID-19 infection.

Single-Cell RNA-Sequencing Reveals the Skeletal Cellular Dynamics in Bone Repair and Osteoporosis.

The bone is an important organ that performs various functions, and the bone marrow inside the skeleton is composed of a complex intermix of hematopoietic, vascular, and skeletal cells. Current single-cell RNA sequencing (scRNA-seq) technology has revealed heterogeneity and sketchy differential hierarchy of skeletal cells. Skeletal stem and progenitor cells (SSPCs) are located upstream of the hierarchy and differentiate into chondrocytes, osteoblasts, osteocytes, and bone marrow adipocytes. In the bone marrow, multiple types of bone marrow stromal cells (BMSCs), which have the potential of SSPCs, are spatiotemporally located in distinct areas, and SSPCs' potential shift of BMSCs may occur with the advancement of age. These BMSCs contribute to bone regeneration and bone diseases, such as osteoporosis. In vivo lineage-tracing technologies show that various types of skeletal lineage cells concomitantly gather and contribute to bone regeneration. In contrast, these cells differentiate into adipocytes with aging, leading to senile osteoporosis. scRNA-seq analysis has revealed that alteration in the cell-type composition is a major cause of tissue aging. In this review, we discuss the cellular dynamics of skeletal cell populations in bone homeostasis, regeneration, and osteoporosis.

C9orf16 represents the aberrant genetic programs and drives the progression of PDAC.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC), constituting 90% of pancreatic cancers, is the fourth leading cause of cancer-related deaths in the world. Lack of early detection of PDAC contributes to its poor prognosis as patients are often diagnosed at an advanced stage of disease. This is mostly due to the lack of promising diagnostic and therapeutic targets and corresponding drugs. METHODS AND RESULTS: Here, by bioinformatic analysis of single cell RNA-sequencing data on normal pancreas tissues, primary and metastatic PDAC tumors, we identified a promising PDAC biomarker, C9orf16. The expression of C9orf16, rarely detectable in normal epithelial cells, was upregulated in primary PDAC cancer cells and was further elevated in metastatic PDAC cancer cells. Gain or loss of function of C9orf16 demonstrated its critical functions in regulating the cell proliferation, invasion and chemotherapy resistance of cancer cells. Pathway analysis and functional studies identified MYC signaling pathways as the most activated pathways in regulating C9orf16 expression and in mediating the development and progression of PDAC. CONCLUSIONS: These data suggested a crucial gene regulation system, MYC-C9orf16, which is actively involved in PDAC development and progression, and targeting this system should be a novel diagnostic and therapeutic target for PDAC.

Single-cell transcriptomics reveal temporal dynamics of critical regulators of germ cell fate during mouse sex determination.

Despite the importance of germ cell (GC) differentiation for sexual reproduction, the gene networks underlying their fate remain unclear. Here, we comprehensively characterize the gene expression dynamics during sex determination based on single-cell RNA sequencing of 14 914 XX and XY mouse GCs between embryonic days (E) 9.0 and 16.5. We found that XX and XY GCs diverge transcriptionally as early as E11.5 with upregulation of genes downstream of the bone morphogenic protein (BMP) and nodal/Activin pathways in XY and XX GCs, respectively. We also identified a sex-specific upregulation of genes associated with negative regulation of mRNA processing and an increase in intron retention consistent with a reduction in mRNA splicing in XY testicular GCs by E13.5. Using computational gene regulation network inference analysis, we identified sex-specific, sequential waves of putative key regulator genes during GC differentiation and revealed that the meiotic genes are regulated by positive and negative master modules acting in an antagonistic fashion. Finally, we found that rare adrenal GCs enter meiosis similarly to ovarian GCs but display altered expression of master genes controlling the female and male genetic programs, indicating that the somatic environment is important for GC function. Our data are available on a web platform and provide a molecular roadmap of GC sex determination at single-cell resolution, which will serve as a valuable resource for future studies of gonad development, function, and disease.

Downregulation of zinc finger protein 71 in laryngeal squamous cell carcinoma tissues and its potential molecular mechanism and clinical significance: a study based on immunohistochemistry staining and data mining.

BACKGROUND: The molecular mechanism of laryngeal squamous cell carcinoma (LSCC) is not completely clear, which leads to poor prognosis and treatment difficulties for LSCC patients. To date, no study has reported the exact expression level of zinc finger protein 71 (ZNF71) and its molecular mechanism in LSCC. METHODS: In-house immunohistochemistry (IHC) staining (33 LSCC samples and 29 non-LSCC samples) was utilized in analyzing the protein expression level of ZNF71 in LSCC. Gene chips and high-throughput sequencing data collected from multiple public resources (313 LSCC samples and 192 non-LSCC samples) were utilized in analyzing the exact mRNA expression level of ZNF71 in LSCC. Single-cell RNA sequencing (scRNA-seq) data was used to explore the expression status of ZNF71 in different LSCC subpopulations. Enrichment analysis of ZNF71, its positively and differentially co-expressed genes (PDCEGs), and its downstream target genes was employed to detect the potential molecular mechanism of ZNF71 in LSCC. Moreover, we conducted correlation analysis between ZNF71 expression and immune infiltration. RESULTS: ZNF71 was downregulated at the protein level (area under the curve [AUC] = 0.93, p < 0.0001) and the mRNA level (AUC = 0.71, p = 0.023) in LSCC tissues. Patients with nodal metastasis had lower protein expression level of ZNF71 than patients without nodal metastasis (p < 0.05), and male LSCC patients had lower mRNA expression level of ZNF71 than female LSCC patients (p < 0.01). ZNF71 was absent in different LSCC subpopulations, including cancer cells, plasma cells, and tumor-infiltrated immune cells, based on scRNA-seq analysis. Enrichment analysis showed that ZNF71 and its PDCEGs may influence the progression of LSCC by regulating downstream target genes of ZNF71. These downstream target genes of ZNF71 were mainly enriched in tight junctions. Moreover, downregulation of ZNF71 may influence the development and even therapy of LSCC by reducing immune infiltration. CONCLUSION: Downregulation of ZNF71 may promote the progression of LSCC by reducing tight junctions and immune infiltration; this requires further study.

Single-cell RNA sequencing identifies molecular targets associated with poor in vitro maturation performance of oocytes collected from ovarian stimulation.

STUDY QUESTION: What is the transcriptome signature associated with poor performance of rescue IVM (rIVM) oocytes and how can we rejuvenate them? SUMMARY ANSWER: The GATA-1/CREB1/WNT signalling axis was repressed in rIVM oocytes, particularly those of poor quality; restoration of this axis may produce more usable rIVM oocytes. WHAT IS KNOWN ALREADY: rIVM aims to produce mature oocytes (MII) for IVF through IVM of immature oocytes collected from stimulated ovaries. It is not popular due to limited success rate in infertility treatment. Genetic aberrations, cellular stress and the absence of cumulus cell support in oocytes could account for the failure of rIVM. STUDY DESIGN, SIZE, DURATION: We applied single-cell RNA sequencing (scRNA-seq) to capture the transcriptomes of human in vivo oocytes (IVO) (n = 10) from 7 donors and rIVM oocytes (n = 10) from 10 donors. The effects of maternal age and ovarian responses on rIVM oocyte transcriptomes were also studied. In parallel, we studied the effect of gallic acid on the maturation rate of mouse oocytes cultured in IVM medium with (n = 84) and without (n = 85) gallic acid. PARTICIPANTS/MATERIALS, SETTING, METHODS: Human oocytes were collected from donors aged 28-41 years with a body mass index of <30. RNA extraction, cDNA generation, library construction and sequencing were performed in one preparation. scRNA-seq data were then processed and analysed. Selected genes in the rIVM versus IVO comparison were validated by quantitative real-time PCR. For the gallic acid study, we collected immature oocytes from 5-month-old mice and studied the effect of 10-µM gallic acid on their maturation rate. MAIN RESULTS AND THE ROLE OF CHANCE: The transcriptome profiles of rIVM/IVO oocytes showed distinctive differences. A total of 1559 differentially expressed genes (DEGs, genes with at least 2-fold change and adjusted P < 0.05) were found to be enriched in metabolic processes, biosynthesis and oxidative phosphorylation. Among these DEGs, we identified a repression of WNT/ß-catenin signalling in rIVM when compared with IVO oocytes. We found that oestradiol levels exhibited a significant age-independent correlation with the IVO mature oocyte ratio (MII ratio) for each donor. rIVM oocytes from women with a high MII ratio were found to have over-represented cellular processes such as anti-apoptosis. To further identify targets that contribute to the poor clinical outcomes of rIVM, we compared oocytes collected from young donors with a high MII ratio with oocytes from donors of advanced maternal age and lower MII ratio, and revealed that CREB1 is an important regulator. Thus, our study identified that GATA-1/CREB1/WNT signalling was repressed in both rIVM oocytes versus IVO oocytes and in rIVM oocytes of lower versus higher quality. Consequently we investigated gallic acid, as a potential antioxidant substrate in human rIVM medium, and found that it increased the mouse oocyte maturation rate by 31.1%. LARGE SCALE DATA: Raw data from this study can be accessed through GSE158539. LIMITATIONS, REASONS FOR CAUTION: In the rIVM oocytes of the high- and low-quality comparison, the number of samples was limited after data filtering with stringent selection criteria. For the oocyte stage identification, we were unable to predict the presence of oocyte spindle, so polar body extrusion was the only indicator. WIDER IMPLICATIONS OF THE FINDINGS: This study showed that GATA-1/CREB1/WNT signalling was repressed in rIVM oocytes compared with IVO oocytes and was further downregulated in low-quality rIVM oocytes, providing us the foundation of subsequent follow-up research on human oocytes and raising safety concerns about the clinical use of rescued oocytes. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the Collaborative Research Fund, Research Grants Council, C4054-16G, and Research Committee Funding (Research Sustainability of Major RGC Funding Schemes), The Chinese University of Hong Kong. The authors have no conflicts of interest to declare.

Microfluidics applications for high-throughput single cell sequencing.

The inherent heterogeneity of individual cells in cell populations plays significant roles in disease development and progression, which is critical for disease diagnosis and treatment. Substantial evidences show that the majority of traditional gene profiling methods mask the difference of individual cells. Single cell sequencing can provide data to characterize the inherent heterogeneity of individual cells, and reveal complex and rare cell populations. Different microfluidic technologies have emerged for single cell researches and become the frontiers and hot topics over the past decade. In this review article, we introduce the processes of single cell sequencing, and review the principles of microfluidics for single cell analysis. Also, we discuss the common high-throughput single cell sequencing technologies along with their advantages and disadvantages. Lastly, microfluidics applications in single cell sequencing technology for the diagnosis of cancers and immune system diseases are briefly illustrated.

Single-cell RNA sequencing to understand host-virus interactions.

Single-cell RNA sequencing (scRNA-seq) has allowed for the profiling of host and virus transcripts and host-virus interactions at single-cell resolution. This review summarizes the existing scRNA-seq technologies together with their strengths and weaknesses. The applications of scRNA-seq in various virological studies are discussed in depth, which broaden the understanding of the immune atlas, host-virus interactions, and immune repertoire. scRNA-seq can be widely used for virology in the near future to better understand the pathogenic mechanisms and discover more effective therapeutic strategies.

Beyond benchmarking and towards predictive models of dataset-specific single-cell RNA-seq pipeline performance.

BACKGROUND: The advent of single-cell RNA-sequencing (scRNA-seq) has driven significant computational methods development for all steps in the scRNA-seq data analysis pipeline, including filtering, normalization, and clustering. The large number of methods and their resulting parameter combinations has created a combinatorial set of possible pipelines to analyze scRNA-seq data, which leads to the obvious question: which is best? Several benchmarking studies compare methods but frequently find variable performance depending on dataset and pipeline characteristics. Alternatively, the large number of scRNA-seq datasets along with advances in supervised machine learning raise a tantalizing possibility: could the optimal pipeline be predicted for a given dataset? RESULTS: Here, we begin to answer this question by applying 288 scRNA-seq analysis pipelines to 86 datasets and quantifying pipeline success via a range of measures evaluating cluster purity and biological plausibility. We build supervised machine learning models to predict pipeline success given a range of dataset and pipeline characteristics. We find that prediction performance is significantly better than random and that in many cases pipelines predicted to perform well provide clustering outputs similar to expert-annotated cell type labels. We identify characteristics of datasets that correlate with strong prediction performance that could guide when such prediction models may be useful. CONCLUSIONS: Supervised machine learning models have utility for recommending analysis pipelines and therefore the potential to alleviate the burden of choosing from the near-infinite number of possibilities. Different aspects of datasets influence the predictive performance of such models which will further guide users.

Unveiling Shared Immune Responses in Porcine Alveolar Macrophages during ASFV and PRRSV Infection Using Single-Cell RNA-seq.

African swine fever virus (ASFV) and porcine reproductive and respiratory syndrome virus (PRRSV) infections lead to severe respiratory diseases in pigs, resulting in significant economic losses for the global swine industry. While numerous studies have focused on specific gene functions or pathway activities during infection, an investigation of shared immune responses in porcine alveolar macrophages (PAMs) after ASFV and PRRSV infections was lacking. In this study, we conducted a comparison using two single-cell transcriptomic datasets generated from PAMs under ASFV and PRRSV infection. Pattern recognition receptors (PRRs) RIG-I (DDX58), MDA5 (IFIH1), and LGP2 (DHX58) were identified as particularly recognizing ASFV and PRRSV, triggering cellular defense responses, including the upregulation of four cytokine families (CCL, CXCL, IL, and TNF) and the induction of pyroptosis. Through weighted gene co-expression network analysis and protein-protein interaction analysis, we identified thirteen gene and protein interactions shared by both scRNA-seq analyses, suggesting the ability to inhibit both ASFV and PRRSV viral replication. We discovered six proteins (PARP12, PARP14, HERC5, DDX60, RSAD2, and MNDA) in PAMs as inhibitors of ASFV and PRRSV replication. Collectively, our findings showed detailed characterizations of the immune responses in PAMs during ASFV and PRRSV infections, which may facilitate the treatments of these viral diseases.