Single‐cell RNA sequencing technologies and applications: A brief overview

Jovic, Dragomirka; Liang, Xue; Zeng, Huiqing; Lin, Lin; Xu, Fengping; Luo, Yonglun

doi:10.1002/ctm2.694

Cited by 411 publications

(306 citation statements)

References 207 publications

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“…Lastly, there are also techniques based on the principle of combinatorial indexing for barcode attachment [ 80 , 81 , 82 ]. A more thorough review and benchmarking of the many existing scRNA-seq methods have been reported by others [ 83 , 84 ]. These four types of scRNA-seq assays have all been used for studying MKs and their precursors in humans.…”

Section: Single-cell Transcriptomics Of Healthy Megakaryocytesmentioning

confidence: 99%

The Analysis of the Human Megakaryocyte and Platelet Coding Transcriptome in Healthy and Diseased Subjects

Wispelaere

Freson

2022

IJMS

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Platelets are generated and released into the bloodstream from their precursor cells, megakaryocytes that reside in the bone marrow. Though platelets have no nucleus or DNA, they contain a full transcriptome that, during platelet formation, is transported from the megakaryocyte to the platelet. It has been described that transcripts in platelets can be translated into proteins that influence platelet response. The platelet transcriptome is highly dynamic and has been extensively studied using microarrays and, more recently, RNA sequencing (RNA-seq) in relation to diverse conditions (inflammation, obesity, cancer, pathogens and others). In this review, we focus on bulk and single-cell RNA-seq studies that have aimed to characterize the coding transcriptome of healthy megakaryocytes and platelets in humans. It has been noted that bulk RNA-seq has limitations when studying in vitro-generated megakaryocyte cultures that are highly heterogeneous, while single-cell RNA-seq has not yet been applied to platelets due to their very limited RNA content. Next, we illustrate how these methods can be applied in the field of inherited platelet disorders for gene discovery and for unraveling novel disease mechanisms using RNA from platelets and megakaryocytes and rare disease bioinformatics. Next, future perspectives are discussed on how this field of coding transcriptomics can be integrated with other next-generation technologies to decipher unexplained inherited platelet disorders in a multiomics approach.

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Section: Single-cell Transcriptomics Of Healthy Megakaryocytesmentioning

confidence: 99%

The Analysis of the Human Megakaryocyte and Platelet Coding Transcriptome in Healthy and Diseased Subjects

Wispelaere

Freson

2022

IJMS

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“…Single cell RNA-seq (scRNA-seq) technology enables high throughput transcriptomic profiling of individual cells. First published in 2009, scRNA-seq has evolved massively over the past decade, giving rise to more streamlined and affordable scRNA-seq technologies such as microfluidic-based microwell-based, droplet-based and in situ barcoding [ 127 , 128 ]. These methods, however, require cells or nuclei to be in suspension, leading to the loss of information on the spatial contexture.…”

Section: Emergence Of Single-cell Technologiesmentioning

confidence: 99%

The Multi-Dimensional Biomarker Landscape in Cancer Immunotherapy

Lee

Kannan

Lim

et al. 2022

IJMS

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The field of immuno-oncology is now at the forefront of cancer care and is rapidly evolving. The immune checkpoint blockade has been demonstrated to restore antitumor responses in several cancer types. However, durable responses can be observed only in a subset of patients, highlighting the importance of investigating the tumor microenvironment (TME) and cellular heterogeneity to define the phenotypes that contribute to resistance as opposed to those that confer susceptibility to immune surveillance and immunotherapy. In this review, we summarize how some of the most widely used conventional technologies and biomarkers may be useful for the purpose of predicting immunotherapy outcomes in patients, and discuss their shortcomings. We also provide an overview of how emerging single-cell spatial omics may be applied to further advance our understanding of the interactions within the TME, and how these technologies help to deliver important new insights into biomarker discovery to improve the prediction of patient response.

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“…New types of cells and more clearly defined cellular subsets have been identified using cluster algorithms and unbiased dimension reduction. Single-cell RNA bioinformatic methods have been described in detail previously [ 13 , 14 , 15 , 16 ].…”

Section: Single-cell Omics Technologiesmentioning

confidence: 99%

New Insights into Cerebral Vessel Disease Landscapes at Single-Cell Resolution: Pathogenetic and Therapeutic Perspectives

et al. 2022

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Cerebrovascular diseases are a leading cause of death and disability globally. The development of new therapeutic targets for cerebrovascular diseases (e.g., ischemic, and hemorrhagic stroke, vascular dementia) is limited by a lack of knowledge of the cellular and molecular biology of health and disease conditions and the factors that cause injury to cerebrovascular structures. Here, we describe the role of advances in omics technology, particularly RNA sequencing, in studying high-dimensional, multifaceted profiles of thousands of individual blood and vessel cells at single-cell resolution. This analysis enables the dissection of the heterogeneity of diseased cerebral vessels and their atherosclerotic plaques, including the microenvironment, cell evolutionary trajectory, and immune response pathway. In animal models, RNA sequencing permits the tracking of individual cells (including immunological, endothelial, and vascular smooth muscle cells) that compose atherosclerotic plaques and their alteration under experimental settings such as phenotypic transition. We describe how single-cell RNA transcriptomics in humans allows mapping to the molecular and cellular levels of atherosclerotic plaques in cerebral arteries, tracking individual lymphocytes and macrophages, and how these data can aid in identifying novel immune mechanisms that could be exploited as therapeutic targets for cerebrovascular diseases. Single-cell multi-omics approaches will likely provide the unprecedented resolution and depth of data needed to generate clinically relevant cellular and molecular signatures for the precise treatment of cerebrovascular diseases.

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Single‐cell RNA sequencing technologies and applications: A brief overview

Cited by 411 publications

References 207 publications

The Analysis of the Human Megakaryocyte and Platelet Coding Transcriptome in Healthy and Diseased Subjects

The Analysis of the Human Megakaryocyte and Platelet Coding Transcriptome in Healthy and Diseased Subjects

The Multi-Dimensional Biomarker Landscape in Cancer Immunotherapy

New Insights into Cerebral Vessel Disease Landscapes at Single-Cell Resolution: Pathogenetic and Therapeutic Perspectives

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