scholarly journals Advanced Single-cell Omics Technologies and Informatics Tools for Genomics, Proteomics, and Bioinformatics Analysis

2021 ◽  
Author(s):  
Luonan Chen ◽  
Rong Fan ◽  
Fuchou Tang
Keyword(s):  
Single Cell ◽  
Bioinformatics Analysis ◽  
Omics Technologies ◽  
Informatics Tools

scholarly journals Recent Progress in Cardiovascular Research Involving Single-Cell Omics Approaches

2021 ◽  
Vol 8 ◽  
Author(s):  
Zhehao Dai ◽  
Seitaro Nomura
Keyword(s):  
Single Cell ◽  
Recent Progress ◽  
Disease Gene ◽  
Cell Type ◽  
Cardiovascular Research ◽  
Omics Technologies ◽  
Technological Advances ◽  
Cell Type Specific ◽  
Intercellular Communications ◽  
Research Resources

Cardiovascular diseases are among the leading causes of morbidity and mortality worldwide. Although the spectrum of the heart from development to disease has long been studied, it remains largely enigmatic. The emergence of single-cell omics technologies has provided a powerful toolbox for defining cell heterogeneity, unraveling previously unknown pathways, and revealing intercellular communications, thereby boosting biomedical research and obtaining numerous novel findings over the last 7 years. Not only cell atlases of normal and developing hearts that provided substantial research resources, but also some important findings regarding cell-type-specific disease gene program, could never have been established without single-cell omics technologies. Herein, we briefly describe the latest technological advances in single-cell omics and summarize the major findings achieved by such approaches, with a focus on development and homeostasis of the heart, myocardial infarction, and heart failure.

scholarly journals Application of Single Cell Technologies to the Study of Hematopoiesis

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. SCI-19-SCI-19
Author(s):  
Bertie Gottgens
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Mouse Models ◽  
Research Funding ◽  
Bioinformatics Analysis ◽  
Stem Cell Differentiation ◽  
Molecular Profiling ◽  
Blood Stem Cell ◽  
Human Patient ◽  
Cell Technologies

The Gottgens group uses a combination of experimental and computational approaches to study how transcription factor networks control the function of blood stem cells and how mutations that perturb such networks cause diseases. The group's current research focuses on (i) single cell genomics of early blood development, (ii) computer models of the transcriptional landscape of blood stem cell differentiation, (iii) transcriptional consequences of leukaemogenic mutations, and (iv) molecular characterization of human blood stem cell populations used in cell and gene therapy protocols. As requested by the session chair, this year's presentation will first provide an overview of single cell technologies, and how they are advancing our understanding of multiple facets of haematology research. This will include single cell molecular profiling, as well as single cell functional assays, and in particular also how a combination of the two allows a more precise definition of haematopoietic stem and progenitor cell types. The rest of the presentation will focus on our multidisciplinary work combining single cell molecular profiling, bioinformatics analysis and experimental/functional validation to study the normal haematopoiesis, and contrast this with 6 mouse models of pre-leukaemic disease. Comprehensive bioinformatics analysis reveals not only qualitative changes in cellular abundance, but also pinpoints the underlying molecular changes that are most likely driving the early stages of malignant disease. An overarching theme will be how single cell landscapes allow us to move seamlessly between different scales of biological investigation, from the molecular to the cellular and whole tissue scale. Finally, extrapolation to human patient data demonstrates disease relevance of gene sets identified from comparative analysis of single cell transcriptional landscapes in mouse models. Disclosures Gottgens: Astra Zeneca: Research Funding; GSK: Research Funding; Novo Nordisk: Consultancy, Research Funding; Autolus: Consultancy, Research Funding.

scholarly journals The new technologies of high-throughput single-cell RNA sequencing

2019 ◽  
Vol 23 (5) ◽  
pp. 508-518
Author(s):  
E. A. Vodiasova ◽  
E. S. Chelebieva ◽  
O. N. Kuleshova
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
High Performance ◽  
New Technologies ◽  
Bioinformatics Analysis ◽  
Single Cells ◽  
Rapid Development ◽  
Cell Types ◽  
Regulatory Pathways ◽  
Sequencing Technologies

A wealth of genome and transcriptome data obtained using new generation sequencing (NGS) technologies for whole organisms could not answer many questions in oncology, immunology, physiology, neurobiology, zoology and other fields of science and medicine. Since the cell is the basis for the living of all unicellular and multicellular organisms, it is necessary to study the biological processes at its level. This understanding gave impetus to the development of a new direction – the creation of technologies that allow working with individual cells (single-cell technology). The rapid development of not only instruments, but also various advanced protocols for working with single cells is due to the relevance of these studies in many fields of science and medicine. Studying the features of various stages of ontogenesis, identifying patterns of cell differentiation and subsequent tissue development, conducting genomic and transcriptome analyses in various areas of medicine (especially in demand in immunology and oncology), identifying cell types and states, patterns of biochemical and physiological processes using single cell technologies, allows the comprehensive research to be conducted at a new level. The first RNA-sequencing technologies of individual cell transcriptomes (scRNA-seq) captured no more than one hundred cells at a time, which was insufficient due to the detection of high cell heterogeneity, existence of the minor cell types (which were not detected by morphology) and complex regulatory pathways. The unique techniques for isolating, capturing and sequencing transcripts of tens of thousands of cells at a time are evolving now. However, new technologies have certain differences both at the sample preparation stage and during the bioinformatics analysis. In the paper we consider the most effective methods of multiple parallel scRNA-seq using the example of 10XGenomics, as well as the specifics of such an experiment, further bioinformatics analysis of the data, future outlook and applications of new high-performance technologies.

scholarly journals Enhancing Our Understanding of Plant Cell-to-Cell Interactions Using Single-Cell Omics

2021 ◽  
Vol 12 ◽  
Author(s):  
Sandra Thibivilliers ◽  
Marc Libault
Keyword(s):  
Single Cell ◽  
Hair Cells ◽  
Plant Cells ◽  
Single Cell Level ◽  
Cellular Interactions ◽  
Cell Level ◽  
Dynamic Regulation ◽  
Omics Technologies ◽  
Spatial Profiling ◽  
Root Hair Cells

Plants are composed of cells that physically interact and constantly adapt to their environment. To reveal the contribution of each plant cells to the biology of the entire organism, their molecular, morphological, and physiological attributes must be quantified and analyzed in the context of the morphology of the plant organs. The emergence of single-cell/nucleus omics technologies now allows plant biologists to access different modalities of individual cells including their epigenome and transcriptome to reveal the unique molecular properties of each cell composing the plant and their dynamic regulation during cell differentiation and in response to their environment. In this manuscript, we provide a perspective regarding the challenges and strategies to collect plant single-cell biological datasets and their analysis in the context of cellular interactions. As an example, we provide an analysis of the transcriptional regulation of the Arabidopsis genes controlling the differentiation of the root hair cells at the single-cell level. We also discuss the perspective of the use of spatial profiling to complement existing plant single-cell omics.

scholarly journals Unraveling Heterogeneity in Transcriptome and Its Regulation Through Single-Cell Multi-Omics Technologies

2020 ◽  
Vol 11 ◽  
Author(s):  
Qiao Rui Xing ◽  
Nadia Omega Cipta ◽  
Kiyofumi Hamashima ◽  
Yih-Cherng Liou ◽  
Cheng Gee Koh ◽  
...  
Keyword(s):  
Single Cell ◽  
Omics Technologies

scholarly journals Single-Cell Multiomics Analysis for Drug Discovery

Metabolites ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 729
Author(s):  
Sam F. Nassar ◽  
Khadir Raddassi ◽  
Terence Wu
Keyword(s):  
Drug Discovery ◽  
Single Cell ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Population Level ◽  
Single Species ◽  
Cell Populations ◽  
Omics Technologies ◽  
Rna Molecules ◽  
Health And Disease

Given the heterogeneity seen in cell populations within biological systems, analysis of single cells is necessary for studying mechanisms that cannot be identified on a bulk population level. There are significant variations in the biological and physiological function of cell populations due to the functional differences within, as well as between, single species as a result of the specific proteome, transcriptome, and metabolome that are unique to each individual cell. Single-cell analysis proves crucial in providing a comprehensive understanding of the biological and physiological properties underlying human health and disease. Omics technologies can help to examine proteins (proteomics), RNA molecules (transcriptomics), and the chemical processes involving metabolites (metabolomics) in cells, in addition to genomes. In this review, we discuss the value of multiomics in drug discovery and the importance of single-cell multiomics measurements. We will provide examples of the benefits of applying single-cell omics technologies in drug discovery and development. Moreover, we intend to show how multiomics offers the opportunity to understand the detailed events which produce or prevent disease, and ways in which the separate omics disciplines complement each other to build a broader, deeper knowledge base.

scholarly journals Cortical Cartography: Mapping Arealization Using Single-Cell Omics Technology

2021 ◽  
Vol 15 ◽  
Author(s):  
Patricia R. Nano ◽  
Claudia V. Nguyen ◽  
Jessenya Mil ◽  
Aparna Bhaduri
Keyword(s):  
Single Cell ◽  
Gene Networks ◽  
Structural Characteristics ◽  
Computational Power ◽  
Human Cortex ◽  
Modular Network ◽  
New Era ◽  
Omics Technologies ◽  
Cortical Areas ◽  
Cognitive Power

The cerebral cortex derives its cognitive power from a modular network of specialized areas processing a multitude of information. The assembly and organization of these regions is vital for human behavior and perception, as evidenced by the prevalence of area-specific phenotypes that manifest in neurodevelopmental and psychiatric disorders. Generations of scientists have examined the architecture of the human cortex, but efforts to capture the gene networks which drive arealization have been hampered by the lack of tractable models of human neurodevelopment. Advancements in “omics” technologies, imaging, and computational power have enabled exciting breakthroughs into the molecular and structural characteristics of cortical areas, including transcriptomic, epigenomic, metabolomic, and proteomic profiles of mammalian models. Here we review the single-omics atlases that have shaped our current understanding of cortical areas, and their potential to fuel a new era of multi-omic single-cell endeavors to interrogate both the developing and adult human cortex.

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