Profiling of Single-Cell Transcriptomes

Deciphering Müller cell heterogeneity signatures in diabetic retinopathy across species: an integrative single-cell analysis

Diabetic retinopathy (DR), a leading cause of visual impairment, demands a profound comprehension of its cellular mechanisms to formulate effective therapeutic strategies. Our study presentes a comprehensive single-cell analysis elucidating the intricate landscape of Müller cells within DR, emphasizing their nuanced involvement. Utilizing scRNA-seq data from both Sprague-Dawley rat models and human patients, we delineated distinct Müller cell clusters and their corresponding gene expression profiles. These findings were further validated through differential gene expression analysis utilizing human transcriptomic data. Notably, certain Müller cell clusters displayed upregulation of the Rho gene, implying a phagocytic response to damaged photoreceptors within the DR microenvironment. This phenomenon was consistently observed across species. Additionally, the co-expression patterns of RHO and PDE6G within Müller cell clusters provided compelling evidence supporting their potential role in maintaining retinal integrity during DR. Our results offer novel insights into the cellular dynamics of DR and underscore Müller cells as promising therapeutic targets for preserving vision in retinal disorders induced by diabetes.

Exploring the advances of single-cell RNA sequencing in thyroid cancer: a narrative review

Thyroid cancer, a prevalent form of endocrine malignancy, has witnessed a substantial increase in occurrence in recent decades. To gain a comprehensive understanding of thyroid cancer at the single-cell level, this narrative review evaluates the applications of single-cell RNA sequencing (scRNA-seq) in thyroid cancer research. ScRNA-seq has revolutionised the identification and characterisation of distinct cell subpopulations, cell-to-cell communications, and receptor interactions, revealing unprecedented heterogeneity and shedding light on novel biomarkers for therapeutic discovery. These findings aid in the construction of predictive models on disease prognosis and therapeutic efficacy. Altogether, scRNA-seq has deepened our understanding of the tumour microenvironment immunologic insights, informing future studies in the development of effective personalised treatment for patients. Challenges and limitations of scRNA-seq, such as technical biases, financial barriers, and ethical concerns, are discussed. Advancements in computational methods, the advent of artificial intelligence (AI), machine learning (ML), and deep learning (DL), and the importance of single-cell data sharing and collaborative efforts are highlighted. Future directions of scRNA-seq in thyroid cancer research include investigating intra-tumoral heterogeneity, integrating with other omics technologies, exploring the non-coding RNA landscape, and studying rare subtypes. Overall, scRNA-seq has transformed thyroid cancer research and holds immense potential for advancing personalised therapies and improving patient outcomes. Efforts to make this technology more accessible and cost-effective will be crucial to ensuring its widespread utilisation in healthcare.

Application of Single-Cell RNA Sequencing in Ovarian Development

The ovary is a female reproductive organ that plays a key role in fertility and the maintenance of endocrine homeostasis, which is of great importance to women's health. It is characterized by a high heterogeneity, with different cellular subpopulations primarily containing oocytes, granulosa cells, stromal cells, endothelial cells, vascular smooth muscle cells, and diverse immune cell types. Each has unique and important functions. From the fetal period to old age, the ovary experiences continuous structural and functional changes, with the gene expression of each cell type undergoing dramatic changes. In addition, ovarian development strongly relies on the communication between germ and somatic cells. Compared to traditional bulk RNA sequencing techniques, the single-cell RNA sequencing (scRNA-seq) approach has substantial advantages in analyzing individual cells within an ever-changing and complicated tissue, classifying them into cell types, characterizing single cells, delineating the cellular developmental trajectory, and studying cell-to-cell interactions. In this review, we present single-cell transcriptome mapping of the ovary, summarize the characteristics of the important constituent cells of the ovary and the critical cellular developmental processes, and describe key signaling pathways for cell-to-cell communication in the ovary, as revealed by scRNA-seq. This review will undoubtedly improve our understanding of the characteristics of ovarian cells and development, thus enabling the identification of novel therapeutic targets for ovarian-related diseases.

Full-Length Single-Cell RNA-Sequencing with FLASH-seq

The single-cell RNA-sequencing (scRNA-seq) field has evolved tremendously since the first paper was published back in 2009 (Tang et al. Nat Methods 6:377-382, 2009). While the first methods analyzed just a handful of cells, the throughput and performance rapidly increased over a very short time span. However, it was not until the introduction of emulsion droplets methods, such as the well-known kits commercialized by 10x Genomics, that the robust and reproducible analysis of thousands of cells became feasible (Zheng et al Massively parallel digital transcriptional profiling of single cells. Nat Commun 8:14049, 2017). Despite generating data at a speed and a cost per cell that remains unmatched for full-length protocols like Smart-seq (Hagemann-Jensen et al Single-cell RNA counting at allele and isoform resolution using Smart-seq3. Nat Biotechnol 38:708-714, 2020; Picelli et al Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 10:1096-1098, 2013), scRNA-seq in droplets still comes with the drawback of addressing only the terminal portion of the transcripts, thus lacking the required sensitivity for comprehensively analyzing the entire transcriptome.Building upon the existing Smart-seq2/3 workflows (Hagemann-Jensen et al Single-cell RNA counting at allele and isoform resolution using Smart-seq3. Nat Biotechnol 38:708-714, 2020; Picelli et al Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 10:1096-1098, 2013), we developed FLASH-seq (FS), a new full-length scRNA-seq method capable of detecting a significantly higher number of genes than previous versions, requiring limited hands-on time and with a great potential for customization (Hahaut et al. Lightning Fast and Highly Sensitive Full-Length Single-cell sequencing using FLASH-Seq. http://biorxiv.org/lookup/doi/10.1101/2021.07.14.452217. https://doi.org/10.1101/2021.07.14.452217, 2021). Here, we present three variants of the FS protocol.Standard FLASH-seq (FS), which builds upon Smart-seq2 developed in the past, is non-stranded and does not use unique molecular identifiers (UMIs) but still remains the easiest method to measure gene expression in a cell population.FLASH-seq low-amplification (FS-LA) represents the fastest method, which generates sequencing-ready libraries in 4.5 h, without sacrificing performance.FLASH-seq with UMIs (FS-UMI) builds upon the same principle as Smart-seq3 and introduces UMIs for molecule counting and isoform reconstruction. The newly designed template-switching oligonucleotide (TSO) contains a 5-bp spacer, which allows the generation of high-quality data while minimizing the amount of strand-invasion artifacts.

Single-cell transcriptomics identifies Col1a1 and Col1a2 as hub genes in obesity-induced cardiac fibrosis

Obesity is a risk factor for cardiovascular disease, leading to ventricular dysfunction and cardiac fibrosis, in which non-cardiomyocytes (nonCMs) play an important role. Early detection and treatment of heart illness may help to limit its progression. We screened for key markers of obesity-induced cardiac fibrosis using single-cell transcriptomics techniques. To begin, an obese mouse model was constructed using a high-fat diet. From a pathogenic perspective, pathological alterations in the obesity-induced heart were found. Differentially expressed genes (DEGs) were identified and functional enrichment analysis was performed. Then, to look for hub genes, key modules of DEGs were built. Finally, the cellular location of the hub genes was investigated. In mice, a high-fat diet raised body weight, messed up myocardial shape, and increased cardiac collagen content. NonCMs transcriptome data revealed 15 different cell types, including fibroblasts, immunological cells, and endothelial cells. There were a total of 33 DEGs found, with 22 up-regulated genes and 11 down-regulated genes. DEGs have a high connection with collagen and extracellular matrix (ECM), according to functional enrichment analysis. Col1a1 and Col1a2 scored well in module analysis and hub gene screening, and were chosen as hub genes. Col1a1 and Col1a2 were shown to be mostly expressed by fibroblasts after localization study. As a result, we believe Col1a1 and Col1a2 may be important markers of obesity-induced cardiac fibrosis, in which fibroblasts play a critical role.

Fast and highly sensitive full-length single-cell RNA sequencing using FLASH-seq

We present FLASH-seq (FS), a full-length single-cell RNA sequencing (scRNA-seq) method with increased sensitivity and reduced hands-on time compared to Smart-seq3. The entire FS protocol can be performed in ~4.5 hours, is simple to automate and can be easily miniaturized to decrease resource consumption. The FS protocol can also use unique molecular identifiers (UMIs) for molecule counting while displaying reduced strand-invasion artifacts. FS will be especially useful for characterizing gene expression at high resolution across multiple samples.

FLASH-seq speeds up high-sensitivity scRNA-seq while sparing resources.

Endogenous fluctuations of OCT4 and SOX2 bias pluripotent cell fate decisions

SOX2 and OCT4 are pioneer transcription factors playing a key role in embryonic stem (ES) cell self‐renewal and differentiation. How temporal fluctuations in their expression levels bias lineage commitment is unknown. Here, we generated knock‐in reporter fusion ES cell lines allowing to monitor endogenous SOX2 and OCT4 protein fluctuations in living cells and to determine their impact on mesendodermal and neuroectodermal commitment. We found that small differences in SOX2 and OCT4 levels impact cell fate commitment in G1 but not in S phase. Elevated SOX2 levels modestly increased neuroectodermal commitment and decreased mesendodermal commitment upon directed differentiation. In contrast, elevated OCT4 levels strongly biased ES cells towards both neuroectodermal and mesendodermal fates in undirected differentiation. Using ATAC‐seq on ES cells gated for different endogenous SOX2 and OCT4 levels, we found that high OCT4 levels increased chromatin accessibility at differentiation‐associated enhancers. This suggests that small endogenous fluctuations of pioneer transcription factors can bias cell fate decisions by concentration‐dependent priming of differentiation‐associated enhancers.

Dynamic regulation of chromatin accessibility by pluripotency transcription factors across the cell cycle

The pioneer activity of transcription factors allows for opening of inaccessible regulatory elements and has been extensively studied in the context of cellular differentiation and reprogramming. In contrast, the function of pioneer activity in self-renewing cell divisions and across the cell cycle is poorly understood. Here we assessed the interplay between OCT4 and SOX2 in controlling chromatin accessibility of mouse embryonic stem cells. We found that OCT4 and SOX2 operate in a largely independent manner even at co-occupied sites, and that their cooperative binding is mostly mediated indirectly through regulation of chromatin accessibility. Controlled protein degradation strategies revealed that the uninterrupted presence of OCT4 is required for post-mitotic re-establishment and interphase maintenance of chromatin accessibility, and that highly OCT4-bound enhancers are particularly vulnerable to transient loss of OCT4 expression. Our study sheds light on the constant pioneer activity required to maintain the dynamic pluripotency regulatory landscape in an accessible state.

Mitotic chromosome binding predicts transcription factor properties in interphase

Mammalian transcription factors (TFs) differ broadly in their nuclear mobility and sequence-specific/non-specific DNA binding. How these properties affect their ability to occupy specific genomic sites and modify the epigenetic landscape is unclear. The association of TFs with mitotic chromosomes observed by fluorescence microscopy is largely mediated by non-specific DNA interactions and differs broadly between TFs. Here we combine quantitative measurements of mitotic chromosome binding (MCB) of 501 TFs, TF mobility measurements by fluorescence recovery after photobleaching, single molecule imaging of DNA binding, and mapping of TF binding and chromatin accessibility. TFs associating to mitotic chromosomes are enriched in DNA-rich compartments in interphase and display slower mobility in interphase and mitosis. Remarkably, MCB correlates with relative TF on-rates and genome-wide specific site occupancy, but not with TF residence times. This suggests that non-specific DNA binding properties of TFs regulate their search efficiency and occupancy of specific genomic sites.

Reversible De-differentiation of Mature White Adipocytes into Preadipocyte-like Precursors during Lactation

Adipose tissue in the mammary gland undergoes dramatic remodeling during reproduction. Adipocytes are replaced by mammary alveolar structures during pregnancy and lactation, then reappear upon weaning. The fate of the original adipocytes during lactation and the developmental origin of the re-appearing adipocyte post involution are unclear. Here, we reveal that adipocytes in the mammary gland de-differentiate into Pdgfrα⁺ preadipocyte- and fibroblast-like cells during pregnancy and remain de-differentiated during lactation. Upon weaning, de-differentiated fibroblasts proliferate and re-differentiate into adipocytes. This cycle occurs over multiple pregnancies. These observations reveal the potential of terminally differentiated adipocytes to undergo repeated cycles of de-differentiation and re-differentiation in a physiological setting.