Application of single-cell RNA sequencing in embryonic development

Single-cell sequencing: Current applications in various tuberculosis specimen types

Tuberculosis (TB) is a chronic disease caused by Mycobacterium tuberculosis (M.tb) and responsible for millions of deaths worldwide each year. It has a complex pathogenesis that primarily affects the lungs but can also impact systemic organs. In recent years, single-cell sequencing technology has been utilized to characterize the composition and proportion of immune cell subpopulations associated with the pathogenesis of TB disease since it has a high resolution that surpasses conventional techniques. This paper reviews the current use of single-cell sequencing technologies in TB research and their application in analysing specimens from various sources of TB, primarily peripheral blood and lung specimens. The focus is on how these technologies can reveal dynamic changes in immune cell subpopulations, genes and proteins during disease progression after M.tb infection. Based on the current findings, single-cell sequencing has significant potential clinical value in the field of TB research. Next, we will focus on the real-world applications of the potential targets identified through single-cell sequencing for diagnostics, therapeutics and the development of effective vaccines.

The frontier of precision medicine: application of single-cell multi-omics in preimplantation genetic diagnosis

The advent of single-cell multi-omics technologies has revolutionized the landscape of preimplantation genetic diagnosis (PGD), offering unprecedented insights into the genetic, transcriptomic, and proteomic profiles of individual cells in early-stage embryos. This breakthrough holds the promise of enhancing the accuracy, efficiency, and scope of PGD, thereby significantly improving outcomes in assisted reproductive technologies (ARTs) and genetic disease prevention. This review provides a comprehensive overview of the importance of PGD in the context of precision medicine and elucidates how single-cell multi-omics technologies have transformed this field. We begin with a brief history of PGD, highlighting its evolution and application in detecting genetic disorders and facilitating ART. Subsequently, we delve into the principles, methodologies, and applications of single-cell genomics, transcriptomics, and proteomics in PGD, emphasizing their role in improving diagnostic precision and efficiency. Furthermore, we review significant recent advances within this domain, including key experimental designs, findings, and their implications for PGD practices. The advantages and limitations of these studies are analyzed to assess their potential impact on the future development of PGD technologies. Looking forward, we discuss the emerging research directions and challenges, focusing on technological advancements, new application areas, and strategies to overcome existing limitations. In conclusion, this review underscores the pivotal role of single-cell multi-omics in PGD, highlighting its potential to drive the progress of precision medicine and personalized treatment strategies, thereby marking a new era in reproductive genetics and healthcare.

The Advancement and Application of the Single-Cell Transcriptome in Biological and Medical Research

Single-cell RNA sequencing technology (scRNA-seq) has been steadily developing since its inception in 2009. Unlike bulk RNA-seq, scRNA-seq identifies the heterogeneity of tissue cells and reveals gene expression changes in individual cells at the microscopic level. Here, we review the development of scRNA-seq, which has gone through iterations of reverse transcription, in vitro transcription, smart-seq, drop-seq, 10 × Genomics, and spatial single-cell transcriptome technologies. The technology of 10 × Genomics has been widely applied in medicine and biology, producing rich research results. Furthermore, this review presents a summary of the analytical process for single-cell transcriptome data and its integration with other omics analyses, including genomes, epigenomes, proteomes, and metabolomics. The single-cell transcriptome has a wide range of applications in biology and medicine. This review analyzes the applications of scRNA-seq in cancer, stem cell research, developmental biology, microbiology, and other fields. In essence, scRNA-seq provides a means of elucidating gene expression patterns in single cells, thereby offering a valuable tool for scientific research. Nevertheless, the current single-cell transcriptome technology is still imperfect, and this review identifies its shortcomings and anticipates future developments. The objective of this review is to facilitate a deeper comprehension of scRNA-seq technology and its applications in biological and medical research, as well as to identify avenues for its future development in alignment with practical needs.

Single-Cell and Spatial Transcriptome Analysis of Dermal Fibroblast Development in Perinatal Mouse Skin: Dynamic Lineage Differentiation and Key Driver Genes

Several single-cell RNA studies of developing mouse skin have elucidated the molecular and cellular processes involved in skin development. However, they have primarily focused on either the fetal or early postnatal period, leaving a gap in our understanding of skin development. In this study, we conducted a comprehensive time-series analysis by combining single-cell RNA-sequencing datasets collected at different stages of development (embryonic days 13.5, 14.5, and 16.5 and postnatal days 0, 2, and 4) and validated our findings through multipanel in situ spatial transcriptomics. Our analysis indicated that embryonic fibroblasts exhibit heterogeneity from a very early stage and that the rapid determination of each lineage occurs within days after birth. The expression of putative key driver genes, including Hey1, Ebf1, Runx3, and Sox11 for the dermal papilla trajectory; Lrrc15 for the dermal sheath trajectory; Zfp536 and Nrn1 for the papillary fibroblast trajectory; and Lrrn4cl and Mfap5 for the fascia fibroblast trajectory, was detected in the corresponding, spatially identified cell types. Finally, cell-to-cell interaction analysis indicated that the dermal papilla lineage is the primary source of the noncanonical Wnt pathway during skin development. Together, our study provides a transcriptomic reference for future research in the field of skin development and regeneration.

Single-Cell RNA Sequencing: Opportunities and Challenges for Studies on Corneal Biology in Health and Disease

The structure and major cell types of the multi-layer human cornea have been extensively studied. However, various cell states in specific cell types and key genes that define the cell states are not fully understood, hindering our comprehension of corneal homeostasis, related diseases, and therapeutic discovery. Single-cell RNA sequencing is a revolutionary and powerful tool for identifying cell states within tissues such as the cornea. This review provides an overview of current single-cell RNA sequencing studies on the human cornea, highlighting similarities and differences between them, and summarizing the key genes that define corneal cell states reported in these studies. In addition, this review discusses the opportunities and challenges of using single-cell RNA sequencing to study corneal biology in health and disease.

Single-cell RNA sequencing of peripheral blood reveals immune cell dysfunction in premature ovarian insufficiency

Background

Premature ovarian insufficiency (POI) is one of the most common causes of female infertility and the etiology is highly heterogeneous. Most cases are idiopathic and the pathogenesis remains unclear. Previous studies proved that the immune system plays a crucial role in POI. However, the precise role of immune system remains unclear. This study aimed to analyze the characteristics of peripheral blood mononuclear cells (PBMC) from patients with POI by single-cell RNA sequencing (scRNA-seq) and to explore the potential involvement of immune response in idiopathic POI.

Methods

PBMC was collected from three normal subjects and three patients with POI. PBMC was subjected to scRNA-seq to identify cell clusters and differently expressed genes (DEGs). Enrichment analysis and cell-cell communication analysis were performed to explore the most active biological function in the immune cells of patients with POI.

Results

In total, 22 cell clusters and 10 cell types were identified in the two groups. Compared with normal subjects, the percentage of classical monocytes and NK cells was decreased, the abundance of plasma B cells was increased, and CD4/CD8 ratio was significantly higher in POI. Furthermore, upregulation of IGKC, IFITM1, CD69, JUND and downregulation of LYZ, GNLY, VCAN, and S100A9 were identified, which were enriched in NK cell-mediated cytotoxicity, antigen processing and presentation, and IL-17 signaling pathway. Among them, IGHM and LYZ were respectively the most significantly upregulated and downregulated genes among all cell clusters of POI. The strength of cell-cell communication differed between the healthy subjects and patients with POI, and multiple signaling pathways were assessed. The TNF pathway was found to be unique in POI with classical monocytes being the major target and source of TNF signaling.

Conclusions

Dysfunction of cellular immunity is related to idiopathic POI. Monocytes, NK cells, and B cells, and their enriched differential genes may play a role in the development of idiopathic POI. These findings provide novel mechanistic insight for understanding the pathogenesis of POI.

Time-resolved transcriptomics of mouse gastric pit cells during postnatal development reveals features distinct from whole stomach development

Whole-organ transcriptomic analyses have emerged as a common method for characterizing developmental transitions in mammalian organs. However, it is unclear if all cell types in an organ follow the whole-organ defined developmental trajectory. Recently, a postnatal two-stage developmental process was described for the mouse stomach. Here, using laser capture microdissection to obtain in situ transcriptomic data, we show that mouse gastric pit cells exhibit four postnatal developmental stages. Interestingly, early stages are characterized by the up-regulation of genes associated with metabolism, a functionality not typically associated with pit cells. Hence, beyond revealing that not all constituent cells develop according to the whole-organ determined pathway, these results broaden our understanding of the pit cell phenotypic landscape during stomach development.

Disruption of the gene regulatory programme in neurodevelopmental disorders

Cortical development consists of a series of synchronised events, including fate transition of cortical progenitors, neuronal migration, specification and connectivity. It is becoming clear that gene expression programs governing these events rely on the interplay between signalling molecules, transcription factors and epigenetic mechanisms. When genetic or environmental factors disrupt expression of genes involved in important brain development processes, neurodevelopmental disorders can occur. This review aims to highlight how recent advances in technologies have helped uncover and imitate the gene regulatory mechanisms commonly disrupted in neurodevelopmental disorders.

Sample-multiplexing approaches for single-cell sequencing

Single-cell sequencing is widely used in biological and medical studies. However, its application with multiple samples is hindered by inefficient sample processing, high experimental costs, ambiguous identification of true single cells, and technical batch effects. Here, we introduce sample-multiplexing approaches for single-cell sequencing in transcriptomics, epigenomics, genomics, and multiomics. In single-cell transcriptomics, sample multiplexing uses variants of native or artificial features as sample markers, enabling sample pooling and decoding. Such features include: (1) natural genetic variation, (2) nucleotide-barcode anchoring on cellular or nuclear membranes, (3) nucleotide-barcode internalization to the cytoplasm or nucleus, (4) vector-based barcode expression in cells, and (5) nucleotide-barcode incorporation during library construction. Other single-cell omics methods are based on similar concepts, particularly single-cell combinatorial indexing. These methods overcome current challenges, while enabling super-loading of single cells. Finally, selection guidelines are presented that can accelerate technological application.

Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review

Recent developments have revolutionized the study of biomolecules. Among them are molecular markers, amplification and sequencing of nucleic acids. The latter is classified into three generations. The first allows to sequence small DNA fragments. The second one increases throughput, reducing turnaround and pricing, and is therefore more convenient to sequence full genomes and transcriptomes. The third generation is currently pushing technology to its limits, being able to sequence single molecules, without previous amplification, which was previously impossible. Besides, this represents a new revolution, allowing researchers to directly sequence RNA without previous retrotranscription. These technologies are having a significant impact on different areas, such as medicine, agronomy, ecology and biotechnology. Additionally, the study of biomolecules is revealing interesting evolutionary information. That includes deciphering what makes us human, including phenomena like non-coding RNA expansion. All this is redefining the concept of gene and transcript. Basic analyses and applications are now facilitated with new genome editing tools, such as CRISPR. All these developments, in general, and nucleic-acid sequencing, in particular, are opening a new exciting era of biomolecule analyses and applications, including personalized medicine, and diagnosis and prevention of diseases for humans and other animals.