• Genomics & Informatics
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• 제18권3호
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• pp.26.1-26.6
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• 2020

Single-cell RNA sequencing (scRNA-seq) has been widely applied to provide insights into the cell-by-cell expression difference in a given bulk sample. Accordingly, numerous analysis methods have been developed. As it involves simultaneous analyses of many cell and genes, efficiency of the methods is crucial. The conventional cell type annotation method is laborious and subjective. Here we propose a semi-automatic method that calculates a normalized score for each cell type based on user-supplied cell type-specific marker gene list. The method was applied to a publicly available scRNA-seq data of mouse cardiac non-myocyte cell pool. Annotating the 35 t-stochastic neighbor embedding clusters into 12 cell types was straightforward, and its accuracy was evaluated by constructing co-expression network for each cell type. Gene Ontology analysis was congruent with the annotated cell type and the corollary regulatory network analysis showed upstream transcription factors that have well supported literature evidences. The source code is available as an R script upon request.

• 대한임상검사과학회지
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• 제56권1호
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• pp.10-20
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• 2024

RNA-시퀀싱은 표본에 대한 전사체 전체의 패턴을 제공하는 기법이다. 그러나 RNA-시퀀싱은 표본 내 전체 세포에 대한 평균 유전자 발현만 제공할 수 있으며, 표본 내의 이질성(heterogeneity)에 대한 정보는 제공하지 못한다. 단일 세포 RNA-시퀀싱 기술의 발전을 통해 우리는 표본의 단일 세포 수준에서 이질성과 유전자 발현의 동역학(dynamics)에 대한 이해를 할 수 있게 되었다. 예를 들어, 우리는 단일 세포 RNA-시퀀싱을 통해 복잡한 조직을 구성하는 다양한 세포 유형을 식별할 수 있으며, 특정 세포 유형의 유전자 발현 변화와 같은 정보를 알 수 있다. 단일 세포 RNA-시퀀싱은 처음 도입된 이후 많은 이들의 관심을 끌게 되었으며, 이를 활용하기 위한 대규모 생물정보학(bioinformatics) 도구가 개발되었다. 그러나 단일 세포 RNA-시퀀싱에서 생성된 빅데이터 분석에는 데이터 전처리에 대한 이해와 전처리 이후 다양한 분석 기술에 대한 이해가 필요하다. 본 종설에서는 단일 세포 RNA-시퀀싱 데이터분석과 관련된 작업과정의 개요를 제시한다. 먼저 데이터의 품질 관리, 정규화 및 차원 감소와 같은 데이터의 전 처리 과정에 대해 설명한다. 그 이후, 가장 일반적으로 사용되는 생물정보학 도구를 활용한 데이터의 후속 분석에 대해 설명한다. 본 종설은 이 분야에 관심이 있는 새로운 연구자를 위한 가이드라인을 제공하는 것을 목표로 한다.

• Molecules and Cells
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• 제44권3호
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• pp.127-135
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• 2021

Since the introduction of RNA sequencing (RNA-seq) as a high-throughput mRNA expression analysis tool, this procedure has been increasingly implemented to identify cell-level transcriptome changes in a myriad of model systems. However, early methods processed cell samples in bulk, and therefore the unique transcriptomic patterns of individual cells would be lost due to data averaging. Nonetheless, the recent and continuous development of new single-cell RNA sequencing (scRNA-seq) toolkits has enabled researchers to compare transcriptomes at a single-cell resolution, thus facilitating the analysis of individual cellular features and a deeper understanding of cellular functions. Nonetheless, the rapid evolution of high throughput single-cell "omics" tools has created the need for effective hypothesis verification strategies. Particularly, this issue could be addressed by coupling cell engineering techniques with single-cell sequencing. This approach has been successfully employed to gain further insights into disease pathogenesis and the dynamics of differentiation trajectories. Therefore, this review will discuss the current status of cell engineering toolkits and their contributions to single-cell and genome-wide data collection and analyses.

• Molecules and Cells
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• 제45권9호
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• pp.610-619
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• 2022

Cellular senescence plays a paradoxical role in tumorigenesis through the expression of diverse senescence-associated (SA) secretory phenotypes (SASPs). The heterogeneity of SA gene expression in cancer cells not only promotes cancer stemness but also protects these cells from chemotherapy. Despite the potential correlation between cancer and SA biomarkers, many transcriptional changes across distinct cell populations remain largely unknown. During the past decade, single-cell RNA sequencing (scRNA-seq) technologies have emerged as powerful experimental and analytical tools to dissect such diverse senescence-derived transcriptional changes. Here, we review the recent sequencing efforts that successfully characterized scRNA-seq data obtained from diverse cancer cells and elucidated the role of senescent cells in tumor malignancy. We further highlight the functional implications of SA genes expressed specifically in cancer and stromal cell populations in the tumor microenvironment. Translational research leveraging scRNA-seq profiling of SA genes will facilitate the identification of novel expression patterns underlying cancer susceptibility, providing new therapeutic opportunities in the era of precision medicine.

• Genomics & Informatics
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• 제21권2호
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• pp.18.1-18.11
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• 2023

Immunologists have activated T cells in vitro using various stimulation methods, including phorbol myristate acetate (PMA)/ionomycin and αCD3/αCD28 agonistic antibodies. PMA stimulates protein kinase C, activating nuclear factor-κB, and ionomycin increases intracellular calcium levels, resulting in activation of nuclear factor of activated T cell. In contrast, αCD3/αCD28 agonistic antibodies activate T cells through ZAP-70, which phosphorylates linker for activation of T cell and SH2-domain-containing leukocyte protein of 76 kD. However, despite the use of these two different in vitro T cell activation methods for decades, the differential effects of chemical-based and antibody-based activation of primary human T cells have not yet been comprehensively described. Using single-cell RNA sequencing (scRNA-seq) technologies to analyze gene expression unbiasedly at the single-cell level, we compared the transcriptomic profiles of the non-physiological and physiological activation methods on human peripheral blood mononuclear cell-derived T cells from four independent donors. Remarkable transcriptomic differences in the expression of cytokines and their respective receptors were identified. We also identified activated CD4 T cell subsets (CD55⁺) enriched specifically by PMA/ionomycin activation. We believe this activated human T cell transcriptome atlas derived from two different activation methods will enhance our understanding, highlight the optimal use of these two in vitro T cell activation assays, and be applied as a reference standard when analyzing activated specific disease-originated T cells through scRNA-seq.

• IMMUNE NETWORK
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• 제20권4호
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• pp.34.1-34.8
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• 2020

Cryopreservation and thawing of PBMCs are inevitable processes in expanding the scale of experiments in human immunology. Here, we carried out a fundamental study to investigate the detailed effects of PBMC cryopreservation and thawing on transcriptomes. We sorted Tregs from fresh and cryopreserved/thawed PBMCs from an identical donor and performed single-cell RNA-sequencing (scRNA-seq). We found that the cryopreservation and thawing process minimally affects the key molecular features of Tregs, including FOXP3. However, the cryopreserved and thawed sample had a specific cluster with up-regulation of genes for heat shock proteins. Caution may be warranted in interpreting the character of any cluster of cells with heat shock-related properties when cryopreserved and thawed samples are used for scRNA-seq.

• BMB Reports
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• 제57권5호
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• pp.232-237
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• 2024

This study investigated how adipose tissue-derived mesenchymal stem cells (AT-MSCs) respond to chondrogenic induction using droplet-based single-cell RNA sequencing (scRNA-seq). We analyzed 37,219 high-quality transcripts from control cells and cells induced for 1 week (1W) and 2 weeks (2W). Four distinct cell clusters (0-3), undetectable by bulk analysis, exhibited varying proportions. Cluster 1 dominated in control and 1W cells, whereas clusters (3, 2, and 0) exclusively dominated in control, 1W, and 2W cells, respectively. Furthermore, heterogeneous chondrogenic markers expression within clusters emerged. Gene ontology (GO) enrichment analysis of differentially expressed genes unveiled cluster-specific variations in key biological processes (BP): (1) Cluster 1 exhibited up-regulation of GO-BP terms related to ribosome biogenesis and translational control, crucial for maintaining stem cell properties and homeostasis; (2) Additionally, cluster 1 showed up-regulation of GO-BP terms associated with mitochondrial oxidative metabolism; (3) Cluster 3 displayed up-regulation of GO-BP terms related to cell proliferation; (4) Clusters 0 and 2 demonstrated similar up-regulation of GO-BP terms linked to collagen fibril organization and supramolecular fiber organization. However, only cluster 0 showed a significant decrease in GO-BP terms related to ribosome production, implying a potential correlation between ribosome regulation and the differentiation stages of AT-MSCs. Overall, our findings highlight heterogeneous cell clusters with varying balances between proliferation and differentiation before, and after, chondrogenic stimulation. This provides enhanced insights into the single-cell dynamics of AT-MSCs during chondrogenic differentiation.

• BMB Reports
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• 제48권7호
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• pp.388-394
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• 2015

The brain is an organ that consists of various cell types. As our knowledge of the structure and function of the brain progresses, cell type-specific research is gaining importance. Together with advances in sequencing technology and bioinformatics, cell type-specific transcriptome studies are providing important insights into brain cell function. In this review, we discuss 3 different cell type-specific transcriptome analyses i.e., Laser Capture Microdissection (LCM), Translating Ribosome Affinity Purification (TRAP)/RiboTag, and single cell RNA-Seq, that are widely used in the field of neuroscience. [BMB Reports 2015; 48(7): 388-394]

• BMB Reports
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• 제55권3호
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• pp.113-124
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• 2022

Single-cell RNA sequencing (scRNA-seq) has greatly advanced our understanding of cellular heterogeneity by profiling individual cell transcriptomes. However, cell dissociation from the tissue structure causes a loss of spatial information, which hinders the identification of intercellular communication networks and global transcriptional patterns present in the tissue architecture. To overcome this limitation, novel transcriptomic platforms that preserve spatial information have been actively developed. Significant achievements in imaging technologies have enabled in situ targeted transcriptomic profiling in single cells at single-molecule resolution. In addition, technologies based on mRNA capture followed by sequencing have made possible profiling of the genome-wide transcriptome at the 55-100 ㎛ resolution. Unfortunately, neither imaging-based technology nor capture-based method elucidates a complete picture of the spatial transcriptome in a tissue. Therefore, addressing specific biological questions requires balancing experimental throughput and spatial resolution, mandating the efforts to develop computational algorithms that are pivotal to circumvent technology-specific limitations. In this review, we focus on the current state-of-the-art spatially resolved transcriptomic technologies, describe their applications in a variety of biological domains, and explore recent discoveries demonstrating their enormous potential in biomedical research. We further highlight novel integrative computational methodologies with other data modalities that provide a framework to derive biological insight into heterogeneous and complex tissue organization.

• International Journal of Stem Cells
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• 제16권3호
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• pp.342-355
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• 2023

Background and Objectives: Osteoblasts are derived from bone marrow mesenchymal stem cells (BMMSCs) and play important role in bone remodeling. While our previous studies have investigated the cell subtypes and heterogeneity in osteoblasts and BMMSCs separately, cell-to-cell communications between osteoblasts and BMMSCs in vivo in humans have not been characterized. The aim of this study was to investigate the cellular communication between human primary osteoblasts and bone marrow mesenchymal stem cells. Methods and Results: To investigate the cell-to-cell communications between osteoblasts and BMMSCs and identify new cell subtypes, we performed a systematic integration analysis with our single-cell RNA sequencing (scRNA-seq) transcriptomes data from BMMSCs and osteoblasts. We successfully identified a novel preosteoblasts subtype which highly expressed ATF3, CCL2, CXCL2 and IRF1. Biological functional annotations of the transcriptomes suggested that the novel preosteoblasts subtype may inhibit osteoblasts differentiation, maintain cells to a less differentiated status and recruit osteoclasts. Ligand-receptor interaction analysis showed strong interaction between mature osteoblasts and BMMSCs. Meanwhile, we found FZD1 was highly expressed in BMMSCs of osteogenic differentiation direction. WIF1 and SFRP4, which were highly expressed in mature osteoblasts were reported to inhibit osteogenic differentiation. We speculated that WIF1 and sFRP4 expressed in mature osteoblasts inhibited the binding of FZD1 to Wnt ligand in BMMSCs, thereby further inhibiting osteogenic differentiation of BMMSCs. Conclusions: Our study provided a more systematic and comprehensive understanding of the heterogeneity of osteogenic cells. At the single cell level, this study provided insights into the cell-to-cell communications between BMMSCs and osteoblasts and mature osteoblasts may mediate negative feedback regulation of osteogenesis process.